literature review on e commerce

Consumer-driven e-commerce: A literature review, design framework, and research agenda on last-mile logistics models

International Journal of Physical Distribution & Logistics Management

ISSN : 0960-0035

Article publication date: 14 March 2018

Issue publication date: 22 March 2018

The purpose of this paper is to re-examine the extant research on last-mile logistics (LML) models and consider LML’s diverse roots in city logistics, home delivery and business-to-consumer distribution, and more recent developments within the e-commerce digital supply chain context. The review offers a structured approach to what is currently a disparate and fractured field in logistics.

Design/methodology/approach

The systematic literature review examines the interface between e-commerce and LML. Following a protocol-driven methodology, combined with a “snowballing” technique, a total of 47 articles form the basis of the review.

The literature analysis conceptualises the relationship between a broad set of contingency variables and operational characteristics of LML configuration (push-centric, pull-centric, and hybrid system) via a set of structural variables, which are captured in the form of a design framework. The authors propose four future research areas reflecting likely digital supply chain evolutions.

Research limitations/implications

To circumvent subjective selection of articles for inclusion, all papers were assessed independently by two researchers and counterchecked with two independent logistics experts. Resulting classifications inform the development of future LML models.

Practical implications

The design framework of this study provides practitioners insights on key contingency and structural variables and their interrelationships, as well as viable configuration options within given boundary conditions. The reformulated knowledge allows these prescriptive models to inform practitioners in their design of last-mile distribution.

Social implications

Improved LML performance would have positive societal impacts in terms of service and resource efficiency.

Originality/value

This paper provides the first comprehensive review on LML models in the modern e-commerce context. It synthesises knowledge of LML models and provides insights on current trends and future research directions.

• Literature review
• Omnichannel
• Digital supply chains

Lim, S.F.W.T. , Jin, X. and Srai, J.S. (2018), "Consumer-driven e-commerce: A literature review, design framework, and research agenda on last-mile logistics models", International Journal of Physical Distribution & Logistics Management , Vol. 48 No. 3, pp. 308-332. https://doi.org/10.1108/IJPDLM-02-2017-0081

Emerald Publishing Limited

Copyright © 2018, Stanley Frederick W.T. Lim, Xin Jin and Jagjit Singh Srai

Published by Emerald Publishing Limited. This article is published under the Creative Commons Attribution (CC BY 4.0) licence. Anyone may reproduce, distribute, translate and create derivative works of this article (for both commercial and non-commercial purposes), subject to full attribution to the original publication and authors. The full terms of this licence may be seen at http://creativecommons.org/licences/by/4.0/legalcode

Introduction

Last-mile delivery has become a critical source for market differentiation, motivating retailers to invest in a myriad of consumer delivery innovations, such as buy-online-pickup-in-store, autonomous delivery solutions, lockers, and free delivery upon minimum purchase levels ( Lim et al. , 2017 ). Consumers care about last-mile delivery because it offers convenience and flexibility. For these reasons, same-day and on-demand delivery services are gaining traction for groceries (e.g. Deliv Fresh, Instacart), pre-prepared meals (e.g. Sun Basket), and retail purchases (e.g. Dropoff, Amazon Prime Now) ( Lopez, 2017 ). To meet customer needs, parcel carriers are increasing investments into urban and automated distribution hubs ( McKevitt, 2017 ). However, there is a lack of understanding as to how best to design last-mile delivery models with retailers turning to experimentations that, at times, attract scepticism from industry observers (e.g. Cassidy, 2017 ). For example, Sainsbury’s, Somerfield, and Asda established innovative pick centres, but closed them down within a few years ( Fernie et al. , 2010 ). eBay launched its eBay Now same-day delivery service in 2012, but in July 2015, it announced the closure of this programme. Google, likewise, opened and then closed its two delivery hubs for Google Express in 2013 and 2015, respectively ( O’Brien, 2015 ).

The development of these experimental last-mile logistics (LML) models, not surprisingly, created uncertainty within increasingly complicated and fragmented distribution networks. Without sustainable delivery economics, last-mile service provision will struggle to survive (as was the experience of Sainsbury’s, Somerfield, Asda, eBay, Google, and Webvan) with retailers increasingly challenged to find an optimal balance between pricing, consumer expectations for innovative new channels, and service levels ( Lopez, 2017 ; McKevitt, 2017 ).

Although several contributions have been made in the LML domain, the literature on LML models remains relatively fragmented, thus hindering a comprehensive and holistic understanding of the topic to direct research efforts. Hitherto, existing studies provide limited or no guidance on how contingency variables influence the selection of LML configurations ( Agatz et al. , 2008 ; Fernie et al. , 2010 ; Mangiaracina et al. , 2015 ; Lagorio et al. , 2016 ; Savelsbergh and Van Woensel, 2016 ). Our paper addresses this knowledge deficiency by reviewing the disparate academic literature to capture key contingency and structural variables characterizing the different forms of last-mile distribution. We then theoretically establish the connection between these variables thereby providing a design framework for LML models. Our corpus is comprised of 47 papers published in 16 selected peer-reviewed journals during the period from 2000 to 2017. The review is performed from the standpoint of retailers operating LML. As such, some LML research streams are deliberately excluded, including issues related to public policy, urban traffic regulations, logistics infrastructure, urban sustainability, and environment.

This paper is structured as follows. First, we provide a working definition for LML and introduce relevant terms. Second, we set out the research methodology and conduct descriptive analyses of the corpus. The substantive part of the paper is an analysis of the literature on LML models and the development of a design framework for LML. The framework synthesises a set of structural and contingency variables and explicates their interrelationships, shedding light on how these interactions influence LML design. Finally, we highlight the key gaps in the extant literature and propose future research opportunities.

Defining LML

The term “last-mile” originated in the telecommunications industry and refers to the final leg of a network. Today, LML denotes the last segment of a delivery process, which is often regarded as the most expensive, least efficient aspect of a supply chain and with the most pressing environmental concerns ( Gevaers et al. , 2011 ). Early definitions of LML were narrowly stated as the “extension of supply chains directly to the end consumer”; that is, a home delivery service for consumers ( Punakivi et al. , 2001 ; Kull et al. , 2007 ). Several synonyms, such as last-mile supply chain, last-mile, final-mile, home delivery, business-to-consumer distribution, and grocery delivery, have also been used.

Despite their nuances, existing LML definitions converge on a common understanding that refers to the last part of a delivery process. However, existing definitions (details available from the authors) appear incomplete in capturing the complexities driven by e-commerce, such as omission in defining an origin ( Esper et al. , 2003 ; Kull et al. , 2007 ; Gevaers et al. , 2011 ; Ehmke and Mattfeld, 2012 ; Dablanc et al. , 2013 ; Harrington et al. , 2016 ); exclusion of in-store order fulfilment processes as a fulfilment option ( Hübner, Kuhn and Wollenburg, 2016 ); and/or non-specification of the destination (or end point), including failure to capture the collection delivery point (CDP) as a reception option ( Esper et al. , 2003 ; Kull et al. , 2007 ). Without a consistent and robust definition of LML, the design of LML models is problematic.

For the purpose of this review, we examine existing terminology on last-mile delivery systems in order to create a working definition for LML. As part of this definition, we introduce the concept of an “order penetration point” ( Fernie and Sparks, 2009 ) as a way of defining the origin of the last-mile. The order penetration point refers to an inventory location (e.g. fulfilment centre, manufacturer site, or retail store) where a fulfilment process is activated by a consumer order. After this point, products are uniquely assigned to the consumers who ordered them, making the order penetration point a natural starting point for LML. The destination point is commonly dictated by the consumer, hence we use “final consignee’s preferred destination point” as the terminology to indicate where an order is delivered. The choice of destination point could be a home/office, a reception box (RB), or a pre-designated CDP.

Last-mile logistics is the last stretch of a business-to-consumer (B2C) parcel delivery service. It takes place from the order penetration point to the final consignee’s preferred destination point.

Extending the above definition, we reference Bowersox et al. ’s (2012) view of a supply chain as a series of “cycles”, with half the cycle being the product/order flow and the other, information flow. We also reference the Supply Chain Operations Reference model ( Supply Chain Council, 2010 ) recognising that LML operates within a broader supply network. In particular, the LML cycle coincides with the consumer service cycle, interfacing direct-to-consumer-goods manufacturers, wholesalers, retailers with the end consumer ( Bowersox et al. , 2012 ). The process may be divided into three sub-processes, namely source, make, and deliver.

These three sub-processes set the focus for this review and they align with the delivery order phase in LML, namely picking, packing, and delivery. This model is consistent with Campbell and Savelsbergh’s (2005) view of the business-to-consumer process comprising order sourcing, order assembly, and order delivery. Accordingly, this review focuses on the examination of LML models: LML distribution structures and the contingency variables associated with these structures. The term “distribution structure” covers the stages from order fulfilment to delivery to the final consignee’s preferred destination point. It includes the modes of picking (e.g. warehouse or store-based), transportation (e.g. direct delivery by the retailer’s own fleet), and reception (e.g. consumer-pickup) ( Kämäräinen et al. , 2001 ). The associated contingency variables provide guidance for decision support by highlighting the key characteristics of each distribution structure for the design and selection, matching product, and consumer attributes ( Boyer and Hult, 2005 ).

Research methodology

A structured literature review aims to identify the conceptual content of a rapidly growing field of knowledge, as well as to provide guidance on theory development and future research direction ( Meredith, 1993 ; Easterby-Smith et al. , 2002 ; Rousseau et al. , 2008 ). Structured reviews differ from more narrative-based reviews because of the requirement to provide a detailed description of the review procedure in order to reduce bias; this requirement thereby increases transparency and replicability ( Tranfield et al. , 2003 ). Therefore, undertaking a structured review ensures the fidelity, completeness, and rigour of the review itself ( Greenhalgh and Peacock, 2005 ).

Our review provides a snapshot of the diversity of theoretical approaches present in LML literature. It does not pretend to cover the entirety of the literature, but rather offers an informative and focused evaluation of purposefully selected literature to answer specific research questions. In the following sections, we discuss the execution of the four main steps (planning, searching, screening, and extraction/synthesis/reporting) as outlined by Tranfield et al. (2003) . We also incorporate literature review guidelines suggested by Saenz and Koufteros (2015) . Our study uses key research questions identified by an expert panel and we reference the Association of Business Schools journal ranking 2015 to decide which journals to include in this scholarship ( Cremer et al. , 2015 ). Our review includes the classification of contributions across methodological domains. In later sections, we utilise insights from the literature review to develop an LML design framework that captures the relationships between distribution structures via a set of structural and associated contingency variables.

What is the current state of research and practice on LML distribution in the e-commerce context?

What are the associated contingency variables that can influence the selection of LML distribution structures?

How can the contingency variables identified in RQ2 be used to inform the selection of LML distribution structures?

The academic material in this study covers the period from 2000 to 2017. This period coincides with critical industry events, such as the emergence and subsequent demise of the online grocer, Webvan. The review is limited to peer-reviewed publications to ensure the quality of the corpus ( Saenz and Koufteros, 2015 ) and considers 16 journals, including one practitioner journal ( MIT Sloan Management Review ), to capture theoretical perspectives on industry best practices. Only articles from the selected journals have been included in this review, with one exception, where we included the article by Wang et al. (2014) , published in Mathematical Problems in Engineering . The article was deemed critical as it represents the only piece of work to date that connects and extends prior research on the evaluation of CDPs.

The 16 journals were selected based on their primary focus on empirical and conceptual development, rather than on their discussion of analytical modelling. Although we appreciate that there are significant research studies in this area (e.g. operations research), the focus of this review led us to primarily consider how scholars conceptualise LML distribution structures and apply theoretical variables to LML design through quantitative, qualitative, or conceptual approaches, rather than through mathematic-based models. The mathematic-based model literature focuses on the development of stylised and optimisation models in areas of multi-echelon distribution systems, vehicle routing problems ( Savelsbergh and Van Woensel, 2016 ), buy-online-pick-up-in-store services ( Gao and Su, 2017 ), pricing and delivery choice, inventory-pricing, delivery service levels, discrete location-allocation, channel design, and optimal order quantities via newsvendor formulation for different fulfilment options ( Agatz et al. , 2008 ), amongst others. These studies typically employ a series of assumptions to simplify real-world operations in order to provide closed-form or heuristic-based prescriptive solutions ( Agatz et al. , 2008 ; Savelsbergh and Van Woensel, 2016 ). Therefore, this review excluded journals with a primarily mathematical modelling or operations research focus. However, it included relevant mathematical modelling articles – published in any of the 16 selected journals – as long as they explicated types of LML distribution structure and/or the associated contingency variables. Finally, this study also excluded general management journals in order to fit the operational focus of this research.

The literature search was conducted on the following databases: ISI Web of Science, Science Direct, Scopus, and ABI/Inform Global. Two search rounds were undertaken to maximise inclusion of all relevant articles. The first literature probe was performed using the following search terms: “urban logistics” OR “city logistics” OR “last-mile logistics” OR “last mile logistics”. To extend the corpus, we incorporated the “snowballing” technique of tracing citations backward and forward to locate leads to other related articles; this study used this process in the second round to supplement a protocol-driven methodology. This approach resulted in new search terms and scholar identification to refine the search strategy as the study unfolded ( Greenhalgh and Peacock, 2005 ). The following new search terms were identified: “home delivery”, “B2C distribution”, “extended supply chain”, “final mile”, “distribution network”, “distribution structure”, and “grocery delivery”. These new keywords were then used to create additional search strings with Boolean connectors (AND, OR, AND NOT). Finally, in order to cross-check the searches, we consulted with a supply chain professor from Arizona State University and one from the University of Cambridge. It is therefore posited that the review coverage is reasonably comprehensive.

Exclusion criteria: paper titles bearing the terms “urban logistics”, “city logistics”, “last-mile logistics”, or “last-mile” but with limited coverage on distribution structures and the associated design variables were excluded (e.g. public policy, urban traffic regulations, logistics infrastructure, urban sustainability, environment), as were editorial opinions, conference proceedings, textbooks, book reviews, dissertations, and unpublished working papers.

Inclusion criteria: papers with coverage of distribution structures and design variables in the e-commerce context were included, regardless of their actual study focus. We included multiple research methods to have both established findings as well as emergent theorising.

During the search phase, we identified 425 articles referencing our subject terms. We eliminated duplicates based on titles and name of authors and rejected articles matching the exclusion criteria. For example, while the paper by Gary et al. (2015) holds the keyword “urban logistics” in the title, it focuses on logistics prototyping, rather than LML models, as a method to engage stakeholders. This paper, therefore, was excluded. The elimination stage resulted in 100 articles being considered relevant for further review. Results were exported to reference management software, EndNote version X8, for further review and to facilitate data management. We then adopted the inclusion criteria to select the final articles. Finally, we grouped the articles into two categories: LML distribution structures and the associated contingency variables. Ultimately, a total of 47 journal articles form the corpus of this review.

Extraction, synthesis, and reporting

Following an initial review of the 47 articles, a summary of each article was prepared using a spreadsheet format organised under descriptive (year, journal, title), methodology (article type, theoretical lens, sampling protocol), and thematic categories (article purpose, context, LML distribution structures, design variables, others) as adapted from Pilbeam et al. (2012) .

Accordingly, we conducted three analyses: descriptive, methodological, and thematic ( Richard and Beverly, 2014 ). The descriptive analysis summarises the research development over the period of interest, and the distribution statistics of the journals. The methodological analysis highlights the research methods employed in the domain, while the thematic analysis synthesises the main outcomes from the extracted literature and provides an overview of the review structure. Reporting structures were organised in a manner that sequentially responds to the research questions posed earlier.

Descriptive analysis

Table I provides summary statistics of the papers reviewed, author affiliations c , identifying contributions, as well as those journals where surprisingly contributions have yet to be made.

Methodological analysis

Typology-oriented provision: owing to the recent proliferation of LML models, a typology-oriented approach was particularly conducive for understanding LML practices. Lee and Whang (2001) , Chopra (2003) , Boyer and Hult (2005) , and Vanelslander et al. (2013) each developed LML structural types to assist design under different consumer and product attributes. These studies mostly captured the linearly “chain-centric” LML models prevalent in the pre-digital era.

Literature review and conceptual studies: several reviews have contributed in this domain. Some papers focused on specific areas, such as the evolution of British retailing ( Fernie et al. , 2010 ) and distribution network design ( Mangiaracina et al. , 2015 ), whereas others discussed several topics at once ( Agatz et al. , 2008 ; Lagorio et al. , 2016 ; Savelsbergh and Van Woensel, 2016 ). Narrowly focused papers identified limited LML structural types or variables influencing distribution network design, while more broadly focused papers examined wider issues in urban, city, or multichannel logistics. Conceptual studies typically provided guidance on the selection of LML “types” based on certain performance criteria (e.g. Punakivi and Saranen, 2001 ; Chopra, 2003 ), or logistics service quality (e.g. Yuan and David, 2006 ).

Empirical studies: these studies mainly compared LML types or demonstrated the impact of particular variables upon LML. Studies undertaking the former research purpose (contrasting types) employed simulations, field/mail surveys, and econometrics to examine performance or CO 2 emissions (e.g. Punakivi et al. , 2001 ). One paper employed a mixed-method approach (case research and modelling) to understand the organisation of the physical distribution processes in omnichannel supply networks ( Ishfaq et al. , 2016 ). Empirical studies aiming at the latter research purpose (evidencing impact) used field and laboratory experiments and statistical methods on survey data to examine the interplay between operational strategies and consumer behaviour (e.g. Esper et al. , 2003 ; Boyer and Hult, 2005 ; Kull et al. , 2007 ). These studies also employed econometrics to examine the effects of cross-channel interventions (e.g. Forman et al. , 2009 ; Gallino and Moreno, 2014 ). Additionally, a few studies used case research to provide operational guidance via framework development, such as last-mile order fulfilment ( Hübner, Kuhn and Wollenburg, 2016 ) and LML design, to capture the interests of various stakeholders ( Harrington et al. , 2016 ).

Mathematical modelling: studies also employed a variety of mathematical tools and techniques to formulate LML problems and find optimum solutions, mostly for vehicle routing problems ( Campbell and Savelsbergh, 2005 ; McLeod et al. , 2006 ; Aksen and Altinkemer, 2008 ; Crainic et al. , 2009 ; Wang et al. , 2014 ). In their work, Campbell and Savelsbergh (2006) combined optimisation modelling with simulation to demonstrate the value of incentives. Other studies focused on identifying optimum distribution strategies (e.g. Netessine and Rudi, 2006 ; Li et al. , 2015 ), inventory rationing policy ( Ayanso et al. , 2006 ), delivery time slot pricing ( Yang and Strauss, 2017 ), and formulating new models to capture emerging practices, such as crowd-sourced delivery ( Wang et al. , 2016 ).

Thematic analysis

The grounded theory approach ( Glasser and Strauss, 1967 ) was used to code and classify emerging repeated concepts and terminologies via the qualitative data analysis software, MAXQDA version 12. The classification was based on the two categories defining LML models: LML distribution structures and their associated contingency variables. Coding of the data was conducted independently by two authors. The distinguishing terms and concepts were documented in a codebook; where their views differed, the issues were discussed until consensus was reached. Terminologies relating to each classification level were either derived from the extant literature or introduced in this paper to unify key concepts.

For the first category, the types of LML distribution structure are classified based on different levels of effort required by vendor and consumer: push-centric, pull-centric, and hybrid. A push-centric system requires the vendor to wholly undertake the distribution functions required to deliver the ordered product(s) to the consumer’s doorstep; a pull-centric system requires the consumer to wholly undertake the collection and transporting function; and a hybrid system requires some effort on the parts of both the vendor and consumer and is varied by the location of the decoupling point. A further breakdown divided the push-centric distribution system into modes of picking (manufacturer-based, distribution centre (DC)-based, and local brick-and-mortar (B&M) store-based); the pull-centric distribution system was divided into modes of collection from fulfilment point (local B&M store and information store); and the hybrid distribution system was divided into modes of CDP (attended collection delivery point (CDP-A) and unattended collection delivery point (CDP-U)).

The second category captures the associated contingency variables commonly used in existing studies. This study created a list of 13 variables that influence the structural forms of last-mile distribution: consumer geographical density, consumer physical convenience, consumer time convenience, demand volume, order response time, order visibility, product availability, product variety, product customisability, product freshness, product margin, product returnability, and service capacity. These variables determine the manner in which, or the efficiency with which, a distribution structure fulfils consumer needs while relating to the idiosyncrasies of product types.

These classifications facilitate the understanding of LML models and enabled future structural variables to be consistently categorised. Figure 1 serves to present a structural overview of the LML models reported in the literature.

Review of LML distribution structures

push: product “sent” to consumer’s postcode by someone other than the consumer;

pull: product “fetched” from product source by the consumer; and

hybrid: product “sent” to an intermediate site, from which the product is “fetched” by the consumer.

Table II summarises the corpus on LML distribution structures.

Push-centric system: n -tier direct to home

This study found that the push-centric system is the most commonly adopted distribution form. It typically comprises a number of intermediate stages ( n -tier) between the source and destination in order to create distribution efficiencies. The literature classifies three picking variants according to fulfilment (inventory) location: manufacturer-based (or “drop-shipping”), DC-based, or local B&M store-based (i.e. retailer’s intermediate warehouse or store). The destination can either be consumers’ homes or, increasingly, their workplaces ( McKinnon and Tallam, 2003 ). The mode of delivery can be in-sourced (using retailer’s own vehicle fleet), outsourced to a third-party logistics provider (3PL) ( Boyer and Hult, 2005 ), or crowd-sourced using independent contractors ( Wang et al. , 2016 ).

When selecting a distribution channel, retailers need to trade-off between fulfilment capabilities, inventory levels ( Netessine and Rudi, 2006 ), product availability and variety ( Agatz et al. , 2008 ), transportation cost ( Rabinovich et al. , 2008 ), and responsiveness ( Chopra, 2003 ). The nearer the picking site is to the consumer segment, the more responsive is the channel. However, this responsiveness comes at the expense of lower-level inventory aggregation and higher risks associated with stock-outs ( Netessine and Rudi, 2006 ).

Pull-centric system: consumer self-help

The literature also discussed two variants of the pull-centric system. Both variants require consumers to participate (or self-help) throughout the transaction process, from order fulfilment to order transportation. The first variant represents the traditional way of shopping at a local B&M store, with consumers performing the last-mile “delivery”. The second “information store” variant adopts a concept known as “dematerialisation”, substituting information flow for material flow ( Lee and Whang, 2001 ). This variant recognises that material or physical flows are typically more expensive than information flows due to the costs of (un)loading, handling, warehousing, shipping, and product returns.

This study found that despite the popularity of online shopping, there are still occasions where consumers favour traditional offline shopping. Perceived or actual difficulties with inspecting non-digital products, the product returns process, or slow and expensive shipping can deter consumers from online shopping ( Forman et al. , 2009 ). This study also demonstrates other benefits of a pull-centric system, including lower capital investments and possible carry-over (or halo) effects into in-store sales ( Johnson and Whang, 2002 ).

Hybrid system: n -tier to consumer self-help location

The rich literature here mainly compared different modes of reception. Variants typically entailed a part-push and part-pull configuration. For instance, the problem associated with “not-at-home” responses within attended home delivery (AHD) can be mitigated by delivering the product to a CDP for consumers to pick up. The literature discussed two CDP variants: CDP-A and CDP-U. It found that retailers establish CDP-A through developing new infrastructure development, through utilising existing facilities, or establishing partnerships with a third party ( Wang et al. , 2014 ). Other terminologies associated with CDP-A include “click-and-collect”, “pickup centre”, “click-and-mortar”, and “buy-online-pickup-in-store”. The literature showed that retailers establish CDP-U (or unattended reception) through independent RBs equipped with a docking mechanism, or shared RBs, whose locations range from private homes to public sites (e.g. petrol kiosks and train stations) accessible by multiple users ( McLeod et al. , 2006 ).

These CDP-A and CDP-U strategies are commonly adopted by multi/omnichannel retailers to exploit their existing store networks, to provide convenience to consumers through ancillary delivery services, and to expedite returns handling ( Yrjölä, 2001 ). Moreover, the research showed that integrating online technologies with physical infrastructures enables retailers to achieve synergies in cost savings, improved brand differentiation, enhanced consumer trust, and market extension ( Fernie et al. , 2010 ). Studies have also investigated the cost advantage and operational efficiencies of using CDP-U over AHD and CDP-A (e.g. Wang et al. , 2014 ). CDP-U reduces home delivery costs by up to 60 per cent ( Punakivi et al. , 2001 ), primarily by exploiting time window benefit ( Kämäräinen et al. , 2001 ).

Development of LML design framework

This section addresses the second and third research questions by developing a framework that contributes to LML design practice. The development process is governed by contingency theory ( Lawrence and Lorsch, 1967 ), in which “fit” is a central concept. The contingency theory maintains that structural, contextual, and environmental variables should fit with one another to produce organisational effectiveness. The management literature conceptualises fit as profile deviation (e.g. Jauch and Osborn, 1981 ; Doty et al. , 1993 ) in terms of the degree of consistency across multiple dimensions of organisational design and context. The probability of organisational effectiveness increases as the fit between the different types of variables increases ( Jauch and Osborn, 1981 ; Doty et al. , 1993 ). In this paper, the environmental and contextual variables are jointly branded as contingency variables since the object was to examine how these variables impact the structural form of LML distribution.

We developed the LML design framework in two steps. First, we synthesised a set of LML structural and contingency variables and established the relationship between these through a review of the LML literature. Second, we reformulated the descriptive (i.e. science-mode) knowledge obtained via the first step into prescriptive (i.e. design-mode) knowledge. We adopted the contingency perspective in combination with Romme’s (2003) approach to inform knowledge reformulation.

Synthesising LML structural variables

Product source refers to the location where products are stored when an order is accepted; it coincides with the start point of an LML network. It can be contextualised as a supply network member entity (manufacturer, distributor, or retailer). To illustrate, the computer manufacturer Dell (customisation services), online grocer Ocado (home delivery services), and the UK’s leading supermarket chain Tesco (click-and-collect services) source their products from manufacturer, distributor, and retailer sites, respectively.

Geographical scope concerns the distance separating the start point (product source) and the end point (final consignee’s preferred destination point) of an LML network. An LML network can be classified as centrally based (e.g. Dell Services) or locally based (e.g. Tesco’s click-and-collect).

Mode of distribution describes the delivery mode from the point where an order is fully fulfilled to the end point; it can be classified into three types: self-delivery (e.g. Tesco’s self-owned fleet for home deliveries), 3PL delivery including crowdsourcing (e.g. Dell Services), and consumer-pickup (e.g. Tesco’s click-and-collect services).

Number of nodes concerns the operations in which products are “stationary”, residing in a facility for processing or storage. As opposed to nodes, links represent movements between nodes. There are two variations in respect to this variable: two-node and multiple-node. For example, a two-node structure can be found in Dell’s direct-to-consumer distribution channel, where computers are assembled and orders fulfilled at the factory prior to direct home delivery. In contrast, multiple-node structures are reflected in “in-transit merge” structure where an order comprising components sourced from multiple locations are assembled at a common node. As a case in point, when consumer order a computer processing unit (CPU) from Dell along with a Sony monitor, a parcel carrier would pick up the CPU from a Dell factory and the monitor from a Sony factory, then would merge the two into a single shipment at a hub prior to delivery ( Chopra, 2003 ).

Synthesising LML contingency variables

Consumer geographical density: the number of consumers per unit area ( Boyer and Hult, 2005 ; Boyer et al. , 2009 ; Mangiaracina et al. , 2015 ).

Consumer physical convenience: the effort consumers exert to receive orders ( Chopra, 2003 ; Harrington et al. , 2016 ).

Consumer time convenience: the time committed by consumers for the reception of orders. This variable fluctuates according to the structural form of last-mile distribution ( Rabinovich and Bailey, 2004 ; Yuan and David, 2006).

Demand volume: the number of products ordered by consumers relative to the distribution structure ( Chopra, 2003 ; Boyer and Hult, 2005 ).

Order response time: the time difference between order placement and order delivery ( Kämäräinen et al. , 2001 ; Mangiaracina et al. , 2015 ).

Order visibility: the ability of consumers to track their order from placement to delivery ( Chopra, 2003 ; Harrington et al. , 2016 ).

Product availability and product variety: product availability is the probability of having products in stock when a consumer order arrives ( Chopra, 2003 ; Yuan and David, 2006).

Product variety is the number of unique products (or stock keeping units) offered to consumers ( Punakivi et al. , 2001 ; Punakivi and Saranen, 2001 ).

Product customisability: the ability for products to be adapted to consumer specifications ( Boyer and Hult, 2005 ).

Product freshness: the time elapsed from the moment a product is fully manufactured to the moment when it arrives at the consumption point ( Boyer and Hult, 2005 ).

Product margin: the net income divided by revenue ( Boyer and Hult, 2005 ; Campbell and Savelsbergh, 2005 ).

Product returnability: the ease with which consumers can return unsatisfactory products ( Chopra, 2003 ; Yuan and David, 2006).

Service capacity: the ability of an LML system to provide the intended delivery service and to match consumer demand at any given point in time ( Rabinovich and Bailey, 2004 ; Yuan and David, 2006).

Synthesising the relationship between LML structural and contingency variables

Firms that target customers who can tolerate a large response time require few locations that may be far from the customer and can focus on increasing the capacity of each location. On the other hand, firms that target customers who value short response times need to locate close to them.

This statement identifies the association between a structural variable, namely “geographical scope”, and a contingency variable, namely “order response time”. Within the literature, two variations emerged for each variable: centralised vs localised network for geographical scope and long vs short delivery period for order response time; i.e. centralised geographical scope corresponds to long response time, while localised scope is more responsive. As such, the findings demonstrate that by identifying connecting rationales and the variations at different levels for each variable, we can capture correlations between two sets of variables (i.e. structural and contingency). Continuing this procedure across relevant statements found in our corpus, Table IV summarises the outputs.

Reformulation from science-mode into design-mode knowledge

We adopted the approach by Romme (2003) to reformulate the descriptive knowledge (i.e. science-mode, developed in the previous section) into prescriptive (i.e. design-mode) knowledge so that the latter becomes more accessible to guide practitioners in their LML design thinking. This approach has previously been used to contextualise various design scenarios (e.g. Zott and Amit, 2007 ; Holloway et al. , 2016 ; Busse et al. , 2017 ). For example, Busse et al. (2017) employed a variant of the approach to investigate how buying firms facing low supply chain visibility can utilise their stakeholder network to identify salient supply chain sustainability risks.

if necessary, redefine descriptive (properties of) variables into imperative ones (e.g. actions to be taken);

redefine the probabilistic nature of a hypothesis into an action-oriented design proposition;

add any missing context-specific conditions and variables (drawing on other research findings obtained in science- or design-mode); and

in case of any interdependencies between hypotheses/propositions, formulate a set of propositions.

[If order response time delivered by an LML network is short, then the geographical scope of the LML network should be localised].

[For an LML network to achieve short order response time, localise the geographical scope].

Following similar procedures, the science-mode knowledge describing the relationships between structural and contingency variables can be reformulated to the design-mode shown in Table V . Collectively, the resulting design-mode knowledge constitutes a set of design guidelines for LML practitioners.

Main research issues, gaps, and future lines of research

Although the literature covered in this study thoroughly addresses LML structures, the extant literature has limitations. Based on this study’s findings, there are four main areas that require future study.

Operational challenges in executing last-mile operations

The extant literature has focused on the planning aspect of LML, rather than exploring operational challenges. Consequently, research often takes a simplistic chain-level perspective of LML in order to develop simplistic design prescriptions for practitioners. While this approach seems suitable in the pre-digital era, it is inadequate to capture the complexities of last-mile operations in the omnichannel environment ( Lim et al. , 2017 ). The focus on LML nodes as solely unifunctional is also inadequate ( Vanelslander et al. , 2013 ). Not acknowledging the multi-functionality of individual nodes limits understanding of how this variant works.

To address the limitations of extant research, we propose extending the current research from addressing linear point-to-point LML “chains” (e.g. Chopra, 2003 ; Boyer and Hult, 2005 ) to also addressing the “networks” context, where multiple chains are intertwined and more widely practised in the industry. A study of LML systems using 3PL shared by multiple companies is an example of necessary future research. We also recommend future research to address the multi-functionality of individual nodes in an LML system. A study that addresses the ability of an LML node to simultaneously be a manufacturer and a distributor introduces more structural variance and needs to be theoretically addressed.

Additionally, existing literature typically focuses on comparing structural variants’ performance outcomes and their corresponding consumer and product attributes. However, we argue that such focus limits our understanding of how LML distribution structures interact as part of the broader omnichannel system. Accordingly, an avenue for future research would employ configuration perspectives ( Miller, 1986 ; Lim and Srai, 2018 ) to complement the traditional reductionist approaches (e.g. Boyer et al., 2009 ) in order to more holistically examine LML models. Future studies could consider the structural interactions with relational governance of supply network entities, in order to promote information sharing and enhancing visibility, which are critical in omnichannel retailing ( Lim et al. , 2016 ).

Finally, while recent articles have started to examine the effects of online and offline channel integrations (e.g. Gallino and Moreno, 2014 ), limited contributions have been made to date to understand how retailers integrate their online and offline operations and resources to deliver a seamless experience for consumers ( Piotrowicz and Cuthbertson, 2014 ; Hübner, Kuhn and Wollenburg, 2016 ). We propose revisiting the pull-centric system variants in the context of active consumer participation to understand the approaches retailers can use to attract consumers to their stores. In this regard, the subject can benefit from insightful case studies to advance our understanding of the challenges retailers face, as well as the operational processes retailers adopt to meet these challenges.

Intersection between last-mile operations and “sharing economy” models

With the exception of one paper ( Wang et al. , 2016 ), the majority of the extant literature discusses conventional LML models. Given the rapidly growing sharing economy that generates innovative business models (e.g. Airbnb, Uber, Amazon Prime Now) in several sectors (e.g. housing, transportation, and logistics, respectively) and exploits collaborative consumption ( Hamari et al. , 2016 , p. 2047) and logistics ( Savelsbergh and Van Woensel, 2016 ), there is an immense research scope at the intersection between LML and sharing economy models. First, we propose empirical studies to examine how retailers can effectively employ crowdsourcing models for the last-mile and to show how they can effectively integrate these models into their existing last-mile operations, such as combining in-store fulfilment through delivery using “Uber-type” solutions. This type of study is critical for understanding the impact of crowdsourcing models on retail operations and for promoting their adoption. Second, papers addressing omnichannel issues ( Hübner, Kuhn and Wollenburg, 2016 ; Hübner, Wollenburg and Holzapfel, 2016 ; Ishfaq et al. , 2016 ) are emerging. The emergence of new omnichannel distribution models demands theoretical development and the identification of new design variables. These models include on-demand delivery model (e.g. Instacart), distribution-as-a-service (e.g. Amazon, Ocado), “showroom” concept stores (e.g. Bonobos.com, Warby Parker), in-store digital walls (e.g. Adidas U.S. adiVerse), unmanned delivery (e.g. drones, ground robots), and additive printing (e.g. The UPS store 3D print). Increasingly, we also observe the growing convergence of roles and functions between online and traditional B&M retailers, which suggests new integrated LML models. These new roles and functions demand future research. Finally, while collaborative logistics enable the sharing of assets and capacities in order to increase utilisation and reduce freight, its success rests on developing a logistics ecosystem of relevant stakeholders (including institutions). Consequently, exciting research opportunities exist to explore new design variables that capture key stakeholders’ interests at various levels ( Harrington et al. , 2016 ).

Data harmonisation and analytics: collection and sharing platforms

The literature review revealed that, to date, there has been a tendency towards geographical-based studies and the use of simulated data. For example, this review reports studies based in Finland ( Punakivi and Saranen, 2001 ), Scotland ( McKinnon and Tallam, 2003 ), the USA ( Boyer et al. , 2009 ), England ( McLeod et al. , 2006 ), Germany ( Wollenburg et al. , 2017 ), and Brazil ( Wanke, 2012 ), amongst others. While these studies contribute to generating a useful library of contexts, they are difficult to compare, given differences in geography and geographically based data collection and analysis methods. Moreover, the majority of the studies in this review (41.30 per cent) were based on modelling and simulated data with limited application to real-world data sets, which might suggest a lack of quality data sets. Simulated data limit the advancement of domain knowledge, thus the development of real-world data sets could significantly fuel progress. As such, more attention should be focused on developing data sets, e.g. through the use of transaction and consumer-level data, to gain insights into last-mile behaviours and to design more effective LML models.

Additionally, future studies should standardise data collection in order to address current trends in urbanisation and omnichannel retailing, which are changing retail landscapes and consumer shopping behaviours. This study recommends establishing a data collection framework to guide scholars in LML design, with scholars developing new competences in data mining analytics to exploit large-scale data sets.

Moving from prescriptive to predictive last-mile distribution design

Extant studies have derived correlations between variation of independent variables (e.g. order response time) and variation of dependent variables (e.g. degree of centralisation) to provide prescriptive solutions to the design of last-mile distribution structures. However, these relationships (both linear and non-linear) are often confounded by other factors due to the real-world complexities and they inherently face multicollinearity and endogeneity issues, including the omitted variable bias problem, which leads to biased conclusions. Moreover, model complexity increases as more variables are included, potentially causing overfitting. Given these complexities, researchers usually find immense challenges in untangling these relationships. In this regard, we offer several valuable future lines of research leveraging more advanced techniques for the design of last-mile distribution.

First, our review captured 13 contingency variables that influence the design of last-mile distribution. Future research could discuss other contingency variables and investigate the use of statistical machine and deep learning techniques to identify the most critical contingency variables and uncover hidden relationships to develop predictive models. Second, as urbanisation trends continue, more institutional attention is required on urban logistics focused on negative externalities (congestion and carbon emissions) driven by the intensification of urban freight. According to our review, there is insufficient attention paid to urban freight delivery, and we propose exploring archetyping of urban areas for the development of predictive models to guide the design of urban last-mile distribution systems.

Third, the developed design framework is based on the assumption that only one last-mile distribution structure may be adopted for a given scenario. As we observed in the omnichannel setting, it is common for retailers to concurrently operate multiple distribution structures. The interrelationships between the various structural combinations under the management of a single LML operator also present a potential future research direction.

Last, there is room for a combination of methods to more appropriately tackle the increasingly complicated and fragmented distribution networks in the omnichannel environment. Indeed, this research revealed only two papers in the corpus that have employed a mixed-method approach. Ishfaq et al. (2016) used case research and classification-tree analysis to understand the organisation of distribution processes in omnichannel supply networks, while Campbell and Savelsbergh (2006) combined analytical modelling with simulation to demonstrate the value of incentives in influencing consumer behaviour to reduce delivery costs.

Conclusions

This paper offers the first comprehensive review and analysis of literature regarding e-commerce LML distribution structures and their associated contingency variables. Specifically, the study offers value by using a design framework to explicate the relationship between a broad set of contingency variables and the operational characteristics of LML configuration via a set of structural variables with clearly defined boundaries. The connection between contingency variables and structural variables is critical for understanding LML configuration choices; without understanding this connection, extant knowledge is non-actionable, leaving practitioners with an overwhelming number of seemingly relevant variables that have vague relationships with the structural forms of last-mile distribution.

From a theoretical contribution perspective, this paper identifies attributes of delivery performance linked to product-market segments and the system dynamics that underpin them. This understanding of the interrelationships between LML dimensions enables us to classify prior work, which is somewhat fragmented, to provide insights on emerging business models. The reclassification of LML structures helps practitioners understand the three dominant system dynamics (push-centric, pull-centric, and hybrid) and their related contingency variables. Synthesising structural and contingency variables, the network design framework ( Table IV ) sets out the connections, which when reformulated ( Table V ), provide practitioners design prescriptions under varying LML contexts.

Accordingly, the literature review demonstrates that push-centric LML models driven by order visibility performance are ideally suited to variety-seeking market segments where consumers prioritise time convenience over physical convenience. Conversely, it shows that pull-centric LML models favour order response time, order visibility, and product returnability performance, which are widely observed in markets where consumers desire high physical convenience, low product customisability, and high product variety. Most interestingly of all, this study explains the emergent hybrid systems, where service capacity performance excellence is delivered through multiple clusters of contingency variables, which suits availability-sensitive markets and markets where consumers prioritise physical (over time) convenience.

This paper identifies four areas for further research: operational challenges in executing last-mile operations; intersection between last-mile operations and sharing economy models; data harmonisation and analytics; and moving from prescriptive to predictive last-mile distribution design. Research in these areas could contribute to consolidating the body of knowledge on LML models while maintaining the essential multidisciplinary character. We hope that this review will serve as a foundation to current research efforts, stimulate suggested lines of future research, and assist practitioners to design enhanced LML models in a changing digital e-commerce landscape.

Classification of literature review on LML models

Journal pool for reviewed papers

LML design framework

Aksen , D. and Altinkemer , K. ( 2008 ), “ A location-routing problem for the conversion to the ‘click-and-mortar’ retailing: the static case ”, European Journal of Operational Research , Vol. 186 No. 2 , pp. 554 - 575 .

Agatz , N.A.H. , Fleischmann , M. and van Nunen , J.A.E.E. ( 2008 ), “ E-fulfillment and multi-channel distribution – a review ”, European Journal of Operational Research , Vol. 187 No. 2 , pp. 339 - 356 .

Ayanso , A. , Diaby , M. and Nair , S.K. ( 2006 ), “ Inventory rationing via drop-shipping in Internet retailing: a sensitivity analysis ”, European Journal of Operational Research , Vol. 171 No. 1 , pp. 135 - 152 .

Bell , D.R. , Gallia , S. and Moreno , A. ( 2014 ), “ How to win in an omnichannel world ”, MIT Sloan Management Review , Vol. 56 No. 1 , pp. 45 - 53 .

Bowersox , D.J. , Closs , D.J. , Cooper , M.B. and John , C.B. ( 2012 ), Supply Chain Logistics Management , 4th ed. , McGraw-Hill , New York, NY .

Boyer , K. and Hult , G. ( 2005 ), “ Extending the supply chain: integrating operations and marketing in the online grocery industry ”, Journal of Operations Management , Vol. 23 No. 6 , pp. 642 - 661 .

Boyer , K. and Hult , G. ( 2006 ), “ Customer behavioral intentions for online purchases: an examination of fulfillment method and customer experience level ”, Journal of Operations Management , Vol. 24 No. 2 , pp. 124 - 147 .

Boyer , K.K. , Prud’homme , A.M. and Chung , W. ( 2009 ), “ The last mile challenge: evaluating the effects of customer density and delivery window patterns ”, Journal of Business Logistics , Vol. 30 No. 1 , pp. 185 - 201 .

Busse , C. , Schleper , M.C. , Weilenmann , J. and Wagner , S.M. ( 2017 ), “ Extending the supply chain visibility boundary: utilizing stakeholders for identifying supply chain sustainability risks ”, International Journal of Physical Distribution & Logistics Management , Vol. 47 No. 1 , pp. 18 - 40 .

Campbell , A.M. and Savelsbergh , M. ( 2005 ), “ Decision support for consumer direct grocery initiatives ”, Transportation Science , Vol. 39 No. 3 , pp. 313 - 327 .

Campbell , A.M. and Savelsbergh , M. ( 2006 ), “ Incentive schemes for attended home delivery services ”, Transportation Science , Vol. 40 No. 3 , pp. 327 - 341 .

Cassidy , W.B. ( 2017 ), “ Last-mile business explodes on e-commerce demand ”, available at: www.joc.com/international-logistics/logistics-providers/last-mile-business-explodes-e-commerce-demand_20170529.html/ (accessed 16 September 2017 ).

Chopra , S. ( 2003 ), “ Designing the distribution network in a supply chain ”, Transportation Research Part E: Logistics and Transportation Review , Vol. 39 No. 2003 , pp. 123 - 140 .

Crainic , T.G. , Ricciardi , N. and Storchi , G. ( 2009 ), “ Models for evaluating and planning city logistics systems ”, Transportation Science , Vol. 43 No. 4 , pp. 432 - 454 .

Cremer , R.D. , Laing , A. , Galliers , B. and Kiem , A. ( 2015 ), Academic Journal Guide 2015 , Association of Business Schools , London .

Dablanc , L. , Giuliano , G. , Holliday , K. and O’Brien , T. ( 2013 ), “ Best practices in urban freight management – lessons from an international survey ”, Transportation Research Record: Journal of the Transportation Research Board , Vol. 2379 , pp. 29 - 38 , available at: http://trrjournalonline.trb.org/doi/abs/10.3141/2379-04

De Koster , R.B.M. ( 2002 ), “ Distribution structures for food home shopping ”, International Journal of Physical Distribution & Logistics Management , Vol. 32 No. 5 , pp. 362 - 380 .

Doty , D.H. , Glick , W.H. and Huber , G.P. ( 1993 ), “ Fit, equifinality, and organizational effectiveness: a test of two configurational theories ”, Academy of Management Journal , Vol. 36 No. 6 , pp. 1196 - 1250 .

Dumrongsiri , A. , Fan , M. , Jain , A. and Moinzadeh , K. ( 2008 ), “ A supply chain model with direct and retail channels ”, European Journal of Operational Research , Vol. 187 No. 3 , pp. 691 - 718 .

Easterby-Smith , M. , Thorpe , R. and Lowe , A. ( 2002 ), Management Research: An Introduction , Sage , London .

Ehmke , J.F. and Mattfeld , D.C. ( 2012 ), “ Vehicle routing for attended home delivery in city logistics ”, Procedia – Social and Behavioral Sciences , Vol. 39 No. 2012 , pp. 622 - 632 .

Esper , T.L. , Jensen , T.D. , Turnipseed , F.L. and Burton , S. ( 2003 ), “ The last mile: an examination of effects of online retail delivery strategies on consumers ”, Journal of Business Logistics , Vol. 24 No. 2 , pp. 177 - 203 .

Fernie , J. and Sparks , L. ( 2009 ), Logistics and Retail Management , 3rd ed. , Kogan Page , London .

Fernie , J. , Sparks , L. and McKinnon , A.C. ( 2010 ), “ Retail logistics in the UK: past, present and future ”, International Journal of Retail & Distribution Management , Vol. 38 Nos 11/12 , pp. 894 - 914 .

Forman , C. , Ghose , A. and Goldfarb , A. ( 2009 ), “ Competition between local and electronic markets: how the benefit of buying online depends on where you live ”, Management Science , Vol. 55 No. 1 , pp. 47 - 57 .

Gallino , S. and Moreno , A. ( 2014 ), “ Integration of online and offline channels in retail: the impact of sharing reliable inventory availability information ”, Management Science , Vol. 60 No. 6 , pp. 1434 - 1451 .

Gao , F. and Su , X. ( 2017 ), “ Omnichannel retail operations with buy-online-and-pick-up-in-store ”, Management Science , Vol. 63 No. 8 , pp. 2478 - 2492 .

Gary , G. , Rashid , M. and Eve , C. ( 2015 ), “ Exploring future cityscapes through urban logistics prototyping: a technical viewpoint ”, Supply Chain Management: An International Journal , Vol. 20 No. 3 , pp. 341 - 352 .

Gevaers , R. , Van de Voorde , E. and Vanelslander , T. ( 2011 ), “ Characteristics and typology of last-mile logistics from an innovation perspective in an urban context ”, in Macharis , C. and Melo , S. (Eds), City Distribution and Urban Freight Transport , Edward Elgar Publishing, Inc. , Cheltenham , pp. 56 - 71 , available at: https://books.google.com/books?hl=en&lr=&id=DpYwMe9fBEkC&oi=fnd&pg=PA56&dq=%E2%80%9CCharacteristics+and+typology+of+last-mile+logistics+from+an+innovation+perspective+in+an+urban+context&ots=Gjvpb_6-Of&sig=S1ZYhHZ0gX1Ob6QBWKiNQ-wMkWc#v=onepage&q=%E2%80%9CCharacteristics%20and%20typology%20of%20last-mile%20logistics%20from%20an%20innovation%20perspective%20in%20an%20urban%20context&f=false

Glasser , B.G. and Strauss , A.L. ( 1967 ), The Discovery of Grounded Theory: Strategies for Qualitative Research , Aldine , Chicago, IL .

Greenhalgh , T. and Peacock , R. ( 2005 ), “ Effectiveness and efficiency of search methods in systematic reviews of complex evidence: audit of primary sources ”, British Medical Journal , Vol. 331 Nos 7524 , pp. 1064 - 1065 .

Hamari , J. , Sjöklint , M. and Ukkonen , A. ( 2016 ), “ The sharing economy: why people participate in collaborative consumption ”, Journal of the Association for Information Science and Technology , Vol. 67 No. 9 , pp. 2047 - 2059 .

Harrington , T.S. , Srai , J.S. , Kumar , M. and Wohlrab , J. ( 2016 ), “ Identifying design criteria for urban system ‘last-mile’ solutions – a multi-stakeholder perspective ”, Production Planning & Control , Vol. 27 No. 6 , pp. 456 - 476 .

Holloway , S.S. , van Eijnatten , F.M. , Romme , A.G.L. and Demerouti , E. ( 2016 ), “ Developing actionable knowledge on value crafting: a design science approach ”, Journal of Business Research , Vol. 69 No. 5 , pp. 1639 - 1643 .

Hübner , A. , Kuhn , H. and Wollenburg , J. ( 2016 ), “ Last mile fulfilment and distribution in omni-channel grocery retailing ”, International Journal of Retail & Distribution Management , Vol. 44 No. 3 , pp. 228 - 247 .

Hübner , A. , Wollenburg , J. and Holzapfel , A. ( 2016 ), “ Retail logistics in the transition from multi-channel to omni-channel ”, International Journal of Physical Distribution & Logistics Management , Vol. 46 Nos 6/7 , pp. 562 - 583 .

Ishfaq , R. , Defee , C.C. and Gibson , B.J. ( 2016 ), “ Realignment of the physical distribution process in omni-channel fulfillment ”, International Journal of Physical Distribution & Logistics Management , Vol. 46 Nos 6/7 , pp. 543 - 561 .

Jauch , L.R. and Osborn , R.N. ( 1981 ), “ Toward an integrated theory of strategy ”, Academy of Management Review , Vol. 6 No. 3 , pp. 491 - 498 .

Johnson , M.E. and Whang , S. ( 2002 ), “ e-Business and supply chain management: an overview and framework ”, Production and Operations Management , Vol. 11 No. 4 , pp. 413 - 423 .

Kämäräinen , V. and Punakivi , M. ( 2002 ), “ Developing cost-effective operations for the e-grocery supply chain ”, International Journal of Logistics Research and Applications , Vol. 5 No. 3 , pp. 285 - 298 .

Kämäräinen , V. , Saranen , J. and Holmström , J. ( 2001 ), “ The reception box impact on home delivery efficiency in the e-grocery business ”, International Journal of Physical Distribution & Logistics Management , Vol. 31 No. 6 , pp. 414 - 426 .

Kull , T.J. , Boyer , K. and Calantone , R. ( 2007 ), “ Last-mile supply chain efficiency: an analysis of learning curves in online ordering ”, International Journal of Operations & Production Management , Vol. 27 No. 4 , pp. 409 - 434 .

Lagorio , A. , Pinto , R. and Golini , R. ( 2016 ), “ Research in urban logistics: a systematic literature review ”, International Journal of Physical Distribution & Logistics Management , Vol. 46 No. 10 , pp. 908 - 931 .

Lau , H.K. ( 2012 ), “ Demand management in downstream wholesale and retail distribution: a case study ”, Supply Chain Management: An International Journal , Vol. 17 No. 6 , pp. 638 - 654 .

Lawrence , P.R. and Lorsch , J.W. ( 1967 ), Organization and Environment , Harvard University Press , Cambridge, MA .

Lee , H.L. and Whang , S. ( 2001 ), “ Winning the last mile in e-commerce ”, MIT Sloan Management Review , Vol. 42 No. 4 , pp. 54 - 62 .

Li , Z. , Lu , Q. and Talebian , M. ( 2015 ), “ Online versus bricks-and-mortar retailing: a comparison of price, assortment and delivery time ”, International Journal of Production Research , Vol. 53 No. 13 , pp. 3823 - 3835 .

Lim , S.F.W.T. and Srai , J.S. ( 2018 ), “ Examining the anatomy of last-mile distribution in e-commerce omnichannel retailing: a supply network configuration approach ”, International Journal of Operations & Production Management (forthcoming) .

Lim , S.F.W.T. , Wang , L. and Srai , J.S. ( 2017 ), “ Wal-mart’s omni-channel synergy ”, Supply Chain Management Review , September/October , pp. 30 - 37 , available at: www.scmr.com/article/wal_marts_omni_channel_synergy

Lim , S.F.W.T. , Rabinovich , E. , Rogers , D.S. and Laseter , T.M. ( 2016 ), “ Last-mile supply network distribution in omnichannel retailing: a configuration-based typology ”, Foundations and Trends in Technology Information and Operations Management , Vol. 10 No. 1 , pp. 1 - 87 .

Lopez , E. ( 2017 ), “ Last-mile delivery options grow ever more popular ”, Supply Chain Dive, available at: www.supplychaindive.com/news/last-mile-technology-options-investment/442453/ (accessed 2 July 2017 ).

McKevitt , J. ( 2017 ), “ FedEx and UPS to compete with USPS for last-mile delivery ”, Supply Chain Dive, available at: www.internetretailer.com/2015/07/29/global-e-commerce-set-grow-25-2015 (accessed 2 July 2017 ).

McKinnon , A.C. and Tallam , D. ( 2003 ), “ Unattended delivery to the home: an assessment of the security implications ”, International Journal of Retail & Distribution Management , Vol. 31 No. 1 , pp. 30 - 41 .

McLeod , F. , Cherrett , T. and Song , L. ( 2006 ), “ Transport impacts of local collection/delivery points ”, International Journal of Logistics Research and Applications , Vol. 9 No. 3 , pp. 307 - 317 .

Mangiaracina , R. , Song , G. and Perego , A. ( 2015 ), “ Distribution network design: a literature review and a research agenda ”, International Journal of Physical Distribution & Logistics Management , Vol. 45 No. 5 , pp. 506 - 531 .

Meredith , J. ( 1993 ), “ Theory building through conceptual methods ”, International Journal of Operations & Production Management , Vol. 13 No. 5 , pp. 3 - 11 .

Miller , D. ( 1986 ), “ Configurations of strategy and structure: towards a synthesis ”, Strategic Management Journal , Vol. 7 No. 3 , pp. 233 - 249 .

Netessine , S. and Rudi , N. ( 2006 ), “ Supply chain choice on the Internet ”, Management Science , Vol. 52 No. 6 , pp. 844 - 864 .

O’Brien , M. ( 2015 ), “ eBay shuts down same-day delivery pilots ”, Multichannel Merchant, available at: http://multichannelmerchant.com/news/ebay-shuts-day-delivery-pilots-28072015/ (accessed 6 September 2015 ).

Pilbeam , C. , Alvarez , G. and Wilson , W. ( 2012 ), “ The governance of supply networks: a systematic literature review ”, Supply Chain Management: An International Journal , Vol. 17 No. 4 , pp. 358 - 376 .

Piotrowicz , W. and Cuthbertson , R. ( 2014 ), “ Introduction to the special issue information technology in retail: toward omnichannel retailing ”, International Journal of Electronic Commerce , Vol. 18 No. 4 , pp. 5 - 16 .

Punakivi , M. and Saranen , J. ( 2001 ), “ Identifying the success factors in e-grocery home delivery ”, International Journal of Retail & Distribution Management , Vol. 29 No. 4 , pp. 156 - 163 .

Punakivi , M. and Tanskanen , K. ( 2002 ), “ Increasing the cost efficiency of e-fulfilment using shared reception boxes ”, International Journal of Retail & Distribution Management , Vol. 30 No. 10 , pp. 498 - 507 .

Punakivi , M. , Yrjölä , H. and Holmström , J. ( 2001 ), “ Solving the last mile issue – reception box or delivery box ”, International Journal of Physical Distribution & Logistics Management , Vol. 31 No. 6 , pp. 427 - 439 .

Rabinovich , E. and Bailey , J.P. ( 2004 ), “ Physical distribution service quality in internet retailing: service pricing, transaction attributes, and firm attributes ”, Journal of Operations Management , Vol. 21 No. 6 , pp. 651 - 672 .

Rabinovich , E. , Rungtusanatham , M. and Laseter , T. ( 2008 ), “ Physical distribution service performance and Internet retailer margins: the drop-shipping context ”, Journal of Operations Management , Vol. 26 No. 6 , pp. 767 - 780 .

Randall , T. , Netessine , S. and Rudi , N. ( 2006 ), “ An empirical examination of the decision to invest in fulfillment capabilities: a study of Internet retailers ”, Management Science , Vol. 52 No. 4 , pp. 567 - 580 .

Richard , W. and Beverly , W. ( 2014 ), “ Special issue: building theory in supply chain management through ‘systematic reviews’ of the literature ”, Supply Chain Management: An International Journal , Vol. 19 Nos 5/6 , available at: https://doi.org/10.1108/SCM-08-2014-0275

Romme , A.G.L. ( 2003 ), “ Making a difference: organization as design ”, Organization Science , Vol. 14 No. 5 , pp. 558 - 573 .

Rousseau , D.M. , Manning , J. and Denyer , D. ( 2008 ), “ Evidence in management and organizational science: assembling the field’s full weight of scientific knowledge through syntheses ”, Academy of Management Annals , Vol. 2 No. 1 , pp. 475 - 515 .

Saenz , M.J. and Koufteros , X. ( 2015 ), “ Special issue on literature reviews in supply chain management and logistics ”, International Journal of Physical Distribution & Logistics Management , Vol. 45 Nos 1/2 , available at: https://doi.org/10.1108/IJPDLM-12-2014-0305

Savelsbergh , M. and Van Woensel , T. ( 2016 ), “ 50th anniversary invited article – city logistics: challenges and opportunities ”, Transportation Science , Vol. 50 No. 2 , pp. 579 - 590 .

Småros , J. and Holmström , J. ( 2000 ), “ Viewpoint: reaching the consumer through e-grocery VMI ”, International Journal of Retail & Distribution Management , Vol. 28 No. 2 , pp. 55 - 61 .

Sternbeck , M.G. and Kuhn , H. ( 2014 ), “ An integrative approach to determine store delivery patterns in grocery retailing ”, Transportation Research Part E: Logistics and Transportation Review , Vol. 70 No. 2014 , pp. 205 - 224 .

Supply Chain Council ( 2010 ), “ Supply chain operations reference model: overview of SCOR version 10.0 ”, Supply Chain Council Inc., Pittsburgh, PA .

Tranfield , D. , Denyer , D. and Smart , P. ( 2003 ), “ Towards a methodology for developing evidence-informed management knowledge by means of a systematic review ”, British Journal of Management , Vol. 14 No. 3 , pp. 207 - 222 .

Vanelslander , T. , Deketele , L. and Van Hove , D. ( 2013 ), “ Commonly used e-commerce supply chains for fast moving consumer goods: comparison and suggestions for improvement ”, International Journal of Logistics Research and Applications , Vol. 16 No. 3 , pp. 243 - 256 .

Wang , X. , Zhan , L. , Ruan , J. and Zhang , J. ( 2014 ), “ How to choose ‘last mile’ delivery modes for e-fulfillment ”, Mathematical Problems in Engineering , Vol. 2014 No. 2014 , pp. 1 - 11 .

Wang , Y. , Zhang , D. , Liu , Q. , Shen , F. and Lee , L.H. ( 2016 ), “ Towards enhancing the last-mile delivery: an effective crowd-tasking model with scalable solutions ”, Transportation Research Part E: Logistics and Transportation Review , Vol. 93 No. 2016 , pp. 279 - 293 .

Wanke , P.F. ( 2012 ), “ Product, operation, and demand relationships between manufacturers and retailers ”, Transportation Research Part E: Logistics and Transportation Review , Vol. 48 No. 1 , pp. 340 - 354 .

Weltevreden , J.W.J. ( 2008 ), “ B2c e-commerce logistics: the rise of collection-and-delivery points in the Netherlands ”, International Journal of Retail & Distribution Management , Vol. 36 No. 8 , pp. 638 - 660 .

Wollenburg , J. , Hübner , A. , Kuhn , H. and Trautrims , A. ( 2017 ), “ From bricks-and-mortar to bricks-and-clicks – logistics networks in omni-channel grocery retailing ”, International Journal of Physical Distribution & Logistics Management , available at: http://link.springer.com.ezproxy.usq.edu.au/chapter/10.1007/978-90-481-2471-8_17/fulltext.html

Yang , X. and Strauss , A.K. ( 2017 ), “ An Approximate dynamic programming approach to attended home delivery management ”, European Journal of Operational Research , Vol. 263 No. 3 , pp. 935 - 945 .

Yrjölä , H. ( 2001 ), “ Physical distribution considerations for electronic grocery shopping ”, International Journal of Physical Distribution & Logistics Management , Vol. 31 No. 10 , pp. 746 - 761 .

Yuan , X. and David , B.G. ( 2006 ), “ Developing a framework for measuring physical distribution service quality of multi-channel and ‘pure player’ internet retailers ”, International Journal of Retail & Distribution Management , Vol. 34 Nos 4/5 , pp. 278 - 289 .

Zott , C. and Amit , R. ( 2007 ), “ Business model design and the performance of entrepreneurial firms ”, Organization Science , Vol. 18 No. 2 , pp. 181 - 199 .

Corresponding author

Related articles, we’re listening — tell us what you think, something didn’t work….

Report bugs here

All feedback is valuable

Please share your general feedback

Join us on our journey

Platform update page.

Visit emeraldpublishing.com/platformupdate to discover the latest news and updates

Questions & More Information

Answers to the most commonly asked questions here

E-Commerce Website: A Systematic Literature Review

Ieee account.

• Change Username/Password
• Update Address

Purchase Details

• Payment Options
• Order History
• View Purchased Documents

Profile Information

• Communications Preferences
• Profession and Education
• Technical Interests
• US & Canada: +1 800 678 4333
• Worldwide: +1 732 981 0060
• Contact & Support
• About IEEE Xplore
• Accessibility
• Terms of Use
• Nondiscrimination Policy
• Privacy & Opting Out of Cookies

A not-for-profit organization, IEEE is the world's largest technical professional organization dedicated to advancing technology for the benefit of humanity. © Copyright 2024 IEEE - All rights reserved. Use of this web site signifies your agreement to the terms and conditions.

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

• View all journals
• My Account Login
• Explore content
• About the journal
• Publish with us
• Sign up for alerts
• Open access
• Published: 04 May 2024

E-commerce and foreign direct investment: pioneering a new era of trade strategies

• Yugang He   ORCID: orcid.org/0000-0001-5758-069X 1  

Humanities and Social Sciences Communications volume  11 , Article number:  566 ( 2024 ) Cite this article

337 Accesses

1 Altmetric

Metrics details

• Business and management

This study explores the dynamic interplay between foreign direct investment, e-commerce, and China’s export growth from 2005 to 2022 against the backdrop of the rapidly evolving global economy. Utilizing advanced analytical models that combine province- and year-fixed effects with fully modified ordinary least squares and dynamic ordinary least-squares methodologies, we delve into how foreign direct investment and e-commerce collectively boost China’s export capabilities. Our findings highlight a significant alignment between China’s export expansion and the global sustainable development agenda. We observe that China’s export growth transcends mere international investment and digital market engagement, incorporating sustainable practices such as effective utilization of local labor resources and an emphasis on technological advancements. This study also uncovers how knowledge capital and educational attainment positively impact export figures. A notable regional disparity is observed, with the eastern regions of China being more responsive to foreign direct investment and e-commerce influences on export trade compared to their western counterparts. This disparity underscores the need for region-specific policy approaches and sustainable strategies to evenly distribute the benefits of foreign direct investment and e-commerce. The study concludes that while foreign direct investment and e-commerce are crucial for China’s export growth, the underlying theme is sustainable development, with technological innovation and human capital being key to ongoing export success. The findings advocate for policies that balance economic drivers with sustainable development goals, ensuring both economic prosperity and environmental sustainability.

Similar content being viewed by others

Foreign direct investment and the innovation performance of local enterprises

Export duration and firm markups: evidence from china.

The rise and fall of countries in the global value chains

Introduction.

In its ascent towards global economic preeminence, China has undergone transformative alterations in its provincial export trade architecture, metamorphosed by the intricate orchestration of economic vectors and technological advents within the globally interconnected milieu. Central to this paradigm shift is the synthesis of foreign direct investment, the burgeoning trajectory of e-commerce, the proper deployment of indigenous labor resources, and tactically channeled technological capital. An adept comprehension of these intricate dynamics becomes essential for informed forecasts pertaining to China’s export evolution and its symbiotic relationship with sustainable developmental objectives. The exponential proliferation of China’s export vertical can be attributed to its accurate incorporation of foreign direct investment, pivotal in catalyzing technological assimilations, fortifying workforce competencies, and forging novel market corridors. In tandem, the surge in e-commerce has revolutionized market penetration modalities, enabling Chinese offerings to seamlessly infiltrate global commerce arenas. Moreover, China’s abundant labor capital, juxtaposed with deliberate technological ventures, has accentuated its competitive foothold in global trade arenas. Yet, the velocity of this expansive trajectory beckons a meticulous assessment through a prism of sustainability, addressing facets of resource optimization, laboral integrity, and ecological prudence.

In the current academic landscape, a significant emphasis has been placed on dissecting the myriad ramifications of foreign direct investment on export enhancement, with studies underscoring its cardinal role in technological integration and amplifying operational efficacy. The integration of e-commerce facets, as delineated by Hao et al. ( 2023 ), offered a refined perspective, spotlighting the instrumental role of digital conduits in transcending conventional trade barriers. The interrelation of labor capital, as articulated by Zhang et al. ( 2016 ), in concert with technological advancements, as expounded by Autor et al. ( 2015 ), underscored the salience of indigenous assets and frontier innovations in the export dialog. However, despite the expansive literature, a comprehensive appraisal amalgamating these aspects, especially within the framework of China’s regional disparities, is palpably lacking. From a methodological standpoint, diverse econometric paradigms have been employed in antecedent research, yet province- and year-fixed effect models are increasingly lauded for their analytical precision. The eastern corridors, advantaged by their littoral proximity, have conventionally steered the export zeitgeist. Academic contributions, such as those by Duan et al. ( 2020 ), underscored this region’s proficiency in harnessing foreign direct investment and e-commerce potentialities. In juxtaposition, the central and western sectors, albeit resource-rich and labor-abundant, evince a marked lag in technological embrace and foreign direct investment influx. This regional polarization, as theorized by Zhong et al. ( 2022 ), accentuates the necessity for tailored policy interventions to promulgate balanced and sustainable growth vectors. In this context, our scholarly pursuit seeks to redress the prevailing knowledge chasm. The intricate interplay of foreign direct investment, e-commerce, labor dynamics, and technological innovation in molding China’s export tapestry is indubitable. Yet, exhaustive scrutiny, particularly one sensitive to regional grades, stands as an academic imperative. Grounded in methodological robustness and echoing sustainability principles, this study aims to demystify this intricate interconnection, catalyze informed policy deliberations, and buttress China’s odyssey towards a sustainable export paradigm.

Drawing upon the aforementioned analytical discourse, this research delves into the complex relationship between foreign direct investment, e-commerce, and the growth of exports in China from 2005 to 2022, situated within the context of a rapidly changing global economic landscape. Using advanced statistical methods, such as province- and year-fixed effects analysis along with fully modified ordinary least squares and dynamic ordinary least-squares methods, the study gives a more complete picture of how foreign direct investment and e-commerce work together to make China’s exports stronger. A key aspect of this study is its alignment with the global sustainable development agenda, examining how China’s export growth extends beyond basic international investment and digital commerce. It integrates sustainable practices, such as the effective use of local labor and a focus on technological advancement, offering insights into the role of knowledge capital and educational attainment in boosting export figures. Our analysis reveals a pronounced regional variation in the impact of foreign direct investment and e-commerce on export trade, with Eastern China showing greater responsiveness compared to the Western regions. This finding highlights the necessity for region-specific policies and sustainable strategies to ensure a balanced distribution of foreign direct investment and e-commerce benefits across the country. The study’s methodology stands out in the existing literature for its comprehensive approach, combining advanced econometric techniques to dissect the multifaceted influences on China’s export sector. It addresses a gap in previous research by providing a clearer picture of the interplay between foreign direct investment, e-commerce, and export growth within the unique context of China’s evolving economy. The research emphasizes the need for a nuanced understanding of China’s position in the global economy, exploring the relationship between foreign direct investment and e-commerce in a way that prior empirical studies have not fully captured. By doing so, the study offers valuable insights for policymakers and stakeholders, advocating for strategies that not only foster economic growth but also align with sustainable development objectives, ensuring the long-term prosperity and environmental sustainability of China’s economy.

This study presents several significant contributions to the current academic understanding of China’s export sector, particularly focusing on sustainable development. First, our analysis synthesizes the roles of foreign direct investment and e-commerce, offering fresh insights into their collective influence on China’s exports. This aspect builds upon the work of Fidrmuc and Korhonen ( 2010 ), who underscored the impacts of global capital and digital advancements on emerging economies. Our study extends this perspective by explicitly linking these factors to export growth in the Chinese context. Second, we introduce a nuanced approach by examining regional variations in export performance, moving beyond the limitations of previous studies that often treated China’s economy as a uniform entity. Grübler et al. ( 2007 ), who emphasized the value of regional analysis in producing more thorough economic insights than national overviews, served as an inspiration for this strategy. Third, our research highlights the role of local labor resources as a key component of sustainable export strategies. This aligns with Sun’s ( 2022 ) assertion of human capital as a critical driver of economic growth, positioning it as a sustainable asset in China’s export framework. Fourth, the study delves into the impact of technological investment on sustainable export growth, expanding upon Qian et al. ( 2021 ) thesis that technology is fundamental to achieving green growth. We explore how technological advancements contribute specifically to the sustainability of China’s export sector. Lastly, the research advocates for a balanced approach to economic growth and environmental sustainability, echoing Wright’s ( 2019 ) argument for the necessity of balancing economic development with ecological preservation. Our study furthers this dialog by illustrating how such a balance can be achieved within the context of China’s export dynamics. Together, these facets of our research offer new perspectives on the complex relationship between economic activities, technological innovation, and sustainable development in the context of China’s growing role in the global market. These insights are particularly relevant for policymakers and business leaders looking to navigate the challenges and opportunities presented by China’s evolving export landscape.

The subsequent sections of this article are structured as follows: section “Literature review” delves into a comprehensive review of extant literature, shedding light on prior research in this domain. In the section “Variables and model”, we elucidate the methodological approach, detailing the variables employed and the underlying model. Section “Empirical results” offers a synthesis of the empirical results, coupled with a discussion of the implications. Lastly, the section “Conclusions” culminates with conclusions, policy recommendations, and avenues for future research in this field.

Literature review

In today’s global trade environment, the interplay between foreign direct investment and e-commerce has become a critical factor influencing export trends. Current research highlights foreign direct investment’s pivotal role in driving technology transfer and expanding markets. Concurrently, e-commerce platforms have revolutionized trading patterns, facilitating instantaneous market connections and broadening international reach. Additionally, elements like labor resource allocation and technological progress intertwine with these primary factors, creating a multifaceted framework that reveals the complexities of modern export strategies.

In contemporary academic discourse, the impact of foreign direct investment on China’s export trade has received significant attention. Yet, the complex relationship with e-commerce remains insufficiently explored. The prevailing literature, as seen in the works of Li et al. ( 2019 ), Wang et al. ( 2020 ), and Jin and Huang ( 2023 ), mainly focuses on the direct effects of foreign direct investment on export efficiency through capital infusion and technological transfers. These studies, however, tend to overlook the burgeoning dimension of digital commerce. Addressing this gap, Fu et al. ( 2016 ), Chen et al. ( 2023 ), and Lei and Xie ( 2023 ) provide a more nuanced perspective by acknowledging the role of digital transformation in global trade. They underscore e-commerce’s potential to complement foreign direct investment, particularly in enhancing market access for Chinese exports. Expanding on this viewpoint, Qi et al. ( 2020 ), Klimenko and Qu ( 2023 ), and Yan et al. ( 2023 ) examine how e-commerce platforms democratize export opportunities, even for smaller entities, thus amplifying foreign direct investment’s impact. The insights of Zhang and Yang ( 2022 ), Mahalik et al. ( 2023 ), and Cordes and Marinova ( 2023 ) served as inspiration for this research’s more integrative approach. It goes beyond the traditional analysis of foreign direct investment’s influence on exports to include the transformative role of e-commerce. This methodological advancement builds upon and extends the analyses of Götz ( 2020 ), Auboin et al. ( 2021 ), and Ha ( 2022 ), who, despite their thoroughness, did not fully address the synergistic relationship between foreign direct investment and digital trade channels. Aligned with the analytical frameworks of Agarwal and Wu ( 2015 ), He et al. ( 2021 ), and Shanmugalingam et al. ( 2023 ), this study emphasizes a thorough understanding of trade dynamics in the digital era. By incorporating e-commerce as a key variable alongside foreign direct investment, it fills a critical gap in the literature. This approach resonates with the findings of Zhang and Zeng ( 2023 ), Xiao and Abula ( 2023 ), and Sun et al. ( 2024 ) on the growing influence of digital platforms on trade and extends their work by empirically quantifying this impact within the context of China’s export landscape. In conclusion, this research contributes significantly to the existing body of literature by integrating the crucial role of e-commerce. It provides a more comprehensive view of the dynamics shaping China’s export trade, thereby addressing a vital need in the ongoing academic conversation.

The existing literature recognizes the impact of e-commerce on China’s export trade but lacks a thorough exploration of its synergistic effects with foreign direct investment and traditional trade mechanisms. Previous studies, such as those by Giuffrida et al. ( 2017 ) and Li et al. ( 2019 ), have primarily focused on the direct impact of e-commerce on market expansion and customer engagement, emphasizing its role in broadening the global reach of Chinese products. However, these studies often treat e-commerce as an isolated factor, not integrating it with broader economic elements like foreign direct investment. A more nuanced perspective is emerging from research such as Blanchard, Jean-Marc ( 2019 ), Villegas-Mateos ( 2022 ), and Singh and Singh ( 2022 ), which begin to address the interaction between e-commerce and foreign direct investment but do not provide a comprehensive analysis. These studies show how e-commerce platforms can enhance export efficiency in conjunction with foreign direct investment, yet they stop short of examining how e-commerce is transforming traditional export models. This research addresses this gap by adopting an integrative methodology, drawing on the approaches of Wang et al. ( 2021 ) and Yin and Choi ( 2023 ). This methodology extends beyond evaluating the direct effects of e-commerce on exports to also consider its interplay with foreign direct investment. Such an approach expands upon the frameworks used in studies by Zhang ( 2019 ) and Phang et al. ( 2019 ), which, while insightful, did not fully capture e-commerce’s complex dynamics within China’s integrated market economy. Additionally, this study aligns with the emerging literature, such as the works of Gao ( 2018 ) and Li et al. ( 2020 ), advocating for a holistic view of digital trade’s role in economic growth. By incorporating a comprehensive array of variables, including technological advancement and digital infrastructure quality, this research provides a more robust analysis than previous studies like those by Katz and Callorda ( 2018 ), Sinha et al. ( 2020 ), and Wei and Ullah ( 2022 ). In conclusion, this study overcomes previous shortcomings in academic research by offering a detailed empirical examination of how e-commerce, in conjunction with foreign direct investment and traditional trade mechanisms, shapes China’s export landscape. It contributes significantly to academic discourse by presenting a more complete understanding of e-commerce’s role in the modern economy, thus fulfilling a critical need in the ongoing narrative on global trade and digital economics.

In analyzing China’s export sector, the influence of labor resource allocation, technological advancements, knowledge capital, and educational attainment, particularly in relation to e-commerce, warrants a deeper exploration. Initial research efforts, exemplified by Bhaumik et al. ( 2016 ), Song and Wang ( 2018 ), and Liu and Xie ( 2020 ), have individually evaluated the impacts of labor and technology on export performance, underscoring their roles in bolstering China’s position in international markets. Yet, these studies typically overlooked the integration of e-commerce into their analytical models. Recent scholarly works, including those by Kwak et al. ( 2019 ), Elia et al. ( 2021 ), and Tang and Li ( 2023 ), have started to recognize the combined effect of technological prowess and labor skills within the framework of e-commerce. However, these investigations fall short of comprehensively examining how knowledge capital and education intersect with e-commerce to affect export trends. The methodologies of Lin et al. ( 2020 ), Hanelt et al. ( 2021 ), and Abdul-Rahim et al. ( 2022 ) served as the foundation for this study’s holistic approach to closing this research gap. Our approach is comprehensive, assessing not just the direct impacts of labor, technology, education, and knowledge on exports but also situating these impacts in the context of the growing e-commerce domain. This method expands upon the analytical scope of previous studies like Wei et al. ( 2020 ) and Li et al. ( 2023 ), which, despite their thoroughness, did not fully delve into the complex relationship between e-commerce and China’s export dynamics. Furthermore, our study aligns with the evolving scholarly narrative, as seen in the works of Banalieva and Dhanaraj ( 2019 ) and Huang et al. ( 2023 ), advocating for an integrated view of digital commerce’s interaction with traditional economic variables. By including an extensive analysis of factors such as digital infrastructure and market development in e-commerce, this research offers a more detailed examination than earlier studies by Gorla et al. ( 2017 ) and Wang et al. ( 2024 ). In summary, this research fills existing gaps in the literature by thoroughly investigating how labor resources, technological investments, knowledge capital, and education, in conjunction with e-commerce, shape the export sector in China. It provides a comprehensive perspective on the synergy between traditional economic elements and digital trade, addressing a critical need in the ongoing discussion of global trade and economic progression.

Variables and model

Numerous studies have explored the significant impact of foreign direct investment on a nation’s export trends, highlighting foreign direct investment’s critical role in reshaping export strategies. Researchers like Choong ( 2012 ) and Otchere et al. ( 2016 ) have pointed out that foreign direct investment not only provides essential capital but also facilitates technological transfer, thereby boosting efficiency and productivity in host countries. Moreover, the aspect of sustainability is increasingly becoming interlinked with foreign direct investment, often bringing eco-friendly technologies and sustainable methodologies to the forefront, enhancing a nation’s prospects for long-term export stability, as noted by Perrini and Tencati ( 2006 ). Simultaneously, the influence of the digital revolution, particularly the rise of e-commerce, has significantly transformed the nature of exports. Studies by Wang ( 2010 ) and Teng et al. ( 2022 ) highlight that in China’s expanding digital landscape, e-commerce platforms have leveled the playing field, allowing even smaller businesses to access the global market. According to Rita and Ramos ( 2022 ), Amornkitvikai et al. ( 2022 ), and He et al. ( 2021 ), e-commerce is also in line with the global trend towards sustainable trading due to its traceable and transparent nature. Considering these complex interactions, export trade volume becomes an appropriate variable to study, representing the combined and sustainable effects of foreign direct investment and e-commerce. This research, therefore, focuses on the export trade volumes of China’s provinces, incorporating foreign direct investment inflows and e-commerce transaction data as independent variables. This approach aims to shed light on their hypothesized influence on provincial export patterns.

To fully grasp the complex factors affecting export trade, it’s crucial to look beyond conventional indicators like foreign direct investment and e-commerce. A deeper exploration into academic literature and fundamental economic theories uncovers the critical role of labor resource allocation and technological advancements in shaping export patterns. The foundational Heckscher-Ohlin theorem, supported by research from Castilho et al. ( 2012 ) and Antràs et al. ( 2017 ), underscores the vital impact of labor resources on global trade trends. Darku ( 2021 ) extends this perspective, emphasizing the sustainability aspects and suggesting that effectively managed labor resources can contribute to more equitable and environmentally responsible trading practices. Additionally, examining the role of technology provides insights into the nuances of export competitiveness. Rooted in Romer’s theory of endogenous growth and backed by findings from Jones ( 2019 ) and Anzoategui et al. ( 2019 ), there is a consensus that deliberate technology investments boost productivity and support sustainable growth through cleaner, more efficient production methods. Zhou et al. ( 2021 ) further clarify this idea, showing how sustainable technologies and competitive exports are interlinked. Recognizing the importance of these two factors, this study incorporates labor resource allocation and technological inputs as key control variables. To empirically anchor these theoretical concepts, we use urban employment data from various provinces as indicators of labor resource allocation and local government spending on technology as a reflection of technological investments. Building on the work of Mansion and Bausch ( 2020 ), Lyu et al. ( 2022 ), and Mohammad Shafiee et al. ( 2023 ), this paper also introduces knowledge capital quantified by the number of patent licenses. Following Atkin ( 2016 ), Ahmed et al. ( 2020 ), and Blanchard and Olney ( 2017 ), the paper incorporates education level, measured by the average number of schooling years.

Due to data availability, this paper selects balanced provincial-level data from 2005 to 2022. Since 2005, e-commerce across various Chinese provinces has seen rapid development, making this period particularly relevant to the study’s context. The unavailability of data from Tibet necessitates the inclusion of 30 other provinces and municipalities in China, namely Beijing, Tianjin, Shanxi, Inner Mongolia, Liaoning, Jilin, Heilongjiang, Shanghai, Jiangsu, Zhejiang, Anhui, Fujian, Jiangxi, Shandong, Henan, Hubei, Hunan, Guangdong, Guangxi, Hainan, Chongqing, Sichuan, Guizhou, Yunnan, Shaanxi, Gansu, Qinghai, Ningxia, and Xinjiang. The data used in this study is sourced from three official databases, each providing specific insights into our variables of interest. The Bureau of Statistics of China supplies data on export trade volume, knowledge capital, education level, labor resource endowment, and technological investment. Information on e-commerce is obtained from the China E-commerce Report, while data on foreign direct investment is sourced from the Statistical Bulletin of China’s Outward Foreign Direct Investment.

In examining the interplay between foreign direct investment and e-commerce on export trade using China’s province data, it is imperative to adopt a robust econometric technique that effectively captures both time-invariant and entity-specific heterogeneities. The two-way fixed effects regression model, as elaborated upon by Wooldridge ( 2010 ) and advocated by Baltagi ( 2021 ), is particularly adept at mitigating potential omitted variable biases in panel data, making it especially suitable for our study’s empirical context. By incorporating both entity and time-fixed effects, this approach controls for unobserved province-specific factors that may influence export trade (such as local policies or geographical advantages) and time-specific shocks (like global economic trends or national regulatory shifts) that uniformly affect all provinces. By accounting for these dual dimensions of variability, the model ensures that the estimated effects of foreign direct investment and e-commerce are purged of confounding influences, thus bolstering the credibility of causal inferences drawn from the results. Given the dynamism of China’s economic landscape, combined with the evolving trajectories of foreign direct investment and e-commerce, leveraging the two-way fixed effects regression offers a rigorous and robust approach to discerning their impact on export trade. The model is shown as follows:

In Eq. ( 1 ), the subscript ‘ i ’ represents individual provinces, while t delineates the temporal dimension, capturing the yearly variations. Within this model, ex symbolizes the export trade volume, serving as our dependent variable. On the explanatory side, ec corresponds to e-commerce metrics, ‘fdi’ quantifies foreign direct investment inflows, ‘lab’ encapsulates labor resource endowment, and ‘tec’ signifies the magnitude of technological investment. ‘kn’ indicates knowledge capital. ‘ed’ stands for education level. The term a 0 denotes the intercept, providing a baseline measure for our regression. The vector [ a 1 , a 6 ] comprises the coefficients estimated for each explanatory variable, reflecting their respective strengths and directions of influence on export trade. To control for potential unobserved heterogeneities, η embodies province-specific fixed effects, while δ accounts for year-specific fixed effects, ensuring that time-invariant provincial attributes and common temporal shocks are appropriately adjusted for. The error term, ϵ , is presumed to follow a white noise process, indicating randomness and the absence of serial correlation. The empirical focal points of this study are the coefficients a 1 and a 2 . In our analytical framework, the ‘+’ symbol is strategically used to represent the expected positive effect of various independent variables—including e-commerce, foreign direct investment, labor resource endowment, technological investment, knowledge capital, and education level—on the export volumes of Chinese provinces. This symbolism is central to our hypothesis, positing that these variables play a beneficial role in shaping export trends across different provinces. The underlying premise of this hypothesis is that variables like foreign direct investment, enhanced e-commerce capabilities, and other pertinent factors positively stimulate export activities. In essence, the '+' sign indicates a probable correlation where increases or improvements in these independent variables are likely to correspond with a rise in export volumes from the provinces. Such a correlation is instrumental in dissecting how various economic elements and technological progressions, specific to China’s varied regional landscapes, can bolster the nation’s export capacity. This exploration is particularly salient for understanding China’s export mechanics. It provides a nuanced view of how strategic investments in technology, human capital development, and leveraging local resources can collectively uplift the export sector, reinforcing China’s position in the global economy. The ‘+‘ sign, therefore, not only signifies a positive correlation but also serves as a gateway to understanding the multifaceted drivers that enhance export efficiency in the context of China’s evolving economic landscape.

Robustness test

Considering the relatively modest scale of our sample in this study, there exists a plausible risk of heteroskedasticity and autocorrelation in the outcomes estimated through the use of annual and provincial fixed effects models. These statistical issues could potentially introduce biases into our analytical results, thereby affecting the reliability of our conclusions. To mitigate this challenge, our research strategically implements two advanced econometric methodologies: fully modified ordinary least squares and dynamic ordinary least squares. The fully modified ordinary least-squares technique, a refined version of the ordinary least-squares methodology, is particularly adept at addressing complexities arising from heteroskedasticity and autocorrelation. The efficacy of this approach in handling such statistical nuances is well documented in the works of scholars such as Pedroni ( 2001 ), Christou and Pittis ( 2002 ), Trapani ( 2015 ), Li et al. ( 2020 ), Kripfganz and Sarafidis ( 2021 ), Norkutė et al. ( 2021 ), and Kheifets and Phillips ( 2023 ). These studies validate the use of fully modified ordinary least squares as a robust tool for enhancing the accuracy of econometric estimations, especially in scenarios similar to those in our study. Similarly, the dynamic ordinary least squares method offers a comprehensive solution for addressing the challenges of endogeneity and serial correlation, which are common in time-series data. Research by Chudik and Pesaran ( 2015 ), Moon and Weidner ( 2017 ), Liu et al. ( 2020 ), Ahn and Thomas ( 2023 ), Hartono et al. ( 2023 ), and Fingleton ( 2023 ) underscore the effectiveness of dynamic ordinary least squares in ensuring more precise and reliable results in econometric analysis. This technique, by adjusting for both the lead and lag dynamics of the variables, enhances the accuracy of regression coefficients, thereby providing a more nuanced understanding of the underlying data patterns. Both fully modified ordinary least squares and dynamic ordinary least squares are sophisticated enhancements of the traditional least-squares approach. These methods have been specifically adapted to address the intricate statistical issues inherent in panel data analysis, like the one employed in our study. By incorporating these advanced techniques, we aim to mitigate potential biases arising from heteroskedasticity, autocorrelation, and endogeneity, thereby enhancing the credibility and robustness of our findings. Equation ( 2 ) in our study meticulously outlines the application of these methods, demonstrating their integration into our analytical framework to yield more reliable and insightful results.

This outcome is directly derived from the differential regression, as shown in Eq. ( 3 ).

Let’s consider \(\tilde{\Theta }\) and \(\tilde{\Psi }\) to represent the long-term covariance matrix calculated using the residuals denoted by \([\tilde{{\uptau }_{{\rm{t}}}}=(\tilde{{\uptau }_{1{\rm{t}}}},\tilde{{\uptau }_{2{\rm{t}}{^\prime} }}){^\prime} ]\) . Based on this assumption, we are able to represent the modified data as depicted in Eq. ( 4 ). This representation considers the complex interdependencies reflected in the covariance matrix, laying the groundwork for subsequent examination and understanding of the data within the framework of our chosen model.

In our study, the term for bias correction, crucial for refining our model, is detailed in Eq. ( 5 ). This component is essential for enhancing the accuracy and dependability of our results, as it compensates for possible biases encountered during the estimation phase.

Therefore, the formulation of the fully modified ordinary least-squares estimator, pivotal to our analysis, is encapsulated in Eq. ( 6 ). This estimator is integral to refining our estimations, as it addresses potential issues of serial correlation and endogeneity within our regression models. By employing the fully modified ordinary least-squares method, we gain a more accurate and insightful comprehension of the relationships present in our dataset.

In Eq. ( 6 ), \({\rm{Z}}_{\rm{t}}=({\rm{y}}_{\rm{t}}^{{\prime} }{\rm{D}}_{\rm{t}}^{{\prime} })\) . Developing estimators for the long-term covariance matrix, a critical component in the implementation of fully modified ordinary least squares, is highlighted in studies by Atil et al. ( 2023 ), Wagner ( 2023 ), Phillips and Kheifets ( 2024 ), and Pelagatti and Sbrana ( 2024 ). This process is essential for the precision and efficacy of the fully modified ordinary least-squares approach. It entails refining the OLS regression by including both preceding and subsequent factors, ensuring that the error component in Eq. ( 1 ) remains uncorrelated with the entire historical sequence of random regressor variations. This method, as detailed in the research by Mark and Sul ( 2003 ), Panopoulou and Pittis ( 2004 ), Bruns et al. ( 2021 ), and Wang et al. ( 2024 ), is efficiently captured in Eq. ( 7 ).

By incorporating q lags and r leads of the differenced regressors, the persistent correlation between variables τ 1 t and τ 2 t is effectively neutralized. This adjustment allows the estimation of φ  = ( β ′, γ ′)’ through the least-squares estimator to align with the asymptotic distribution achieved via the fully modified ordinary least-squares method. These methods are notably effective, as emphasized by Bai et al. ( 2021 ), Chebrolu et al. ( 2021 ), De Menezes et al. ( 2021 ), Zhao et al. ( 2022 ), and Bollen et al. ( 2022 ), in overcoming challenges like endogeneity, serial correlation, and biases that are typically prevalent in studies with smaller sample sizes.

Empirical results

Descriptive statistical analysis.

For the purpose of this study, data extraction was conducted, harnessing information from 31 distinct provincial datasets covering the temporal bracket of 2005–2022. This compilation was sourced directly from the authoritative National Bureau of Statistics of China, ensuring data authenticity and integrity. An initial stage of rigorous analytical procedures was executed, encompassing both qualitative descriptive statistical evaluations and quantitative correlation analyses. This served to provide a holistic view of the data landscape, enabling the identification of patterns and inter-variable relationships. The culminating findings from this analytical phase are methodically tabulated in Table 1 . For clarity and comprehensive representation, the results are segmented into two distinct panels: Panel A elucidates the statistical analysis of variable description, while Panel B delineates the correlation matrices.

Within Panel A of Table 2 , an examination of the data yields insights into provincial economic dynamics. The export trade registers an average value of 2.226, complemented by a notably narrow standard deviation of 0.085. This suggests a trend of ascent in export trade across the majority of provinces. Conversely, the foreign direct investment landscape, with a mean of 0.241 and a slightly more dispersed standard deviation of 0.117, indicates a predominant trajectory of foreign direct investment enhancement among provinces, albeit with some variability. E-commerce, represented by a mean of 2.276, portrays a positive trend; however, its relatively expansive standard deviation of 0.572 implies a diverse range of advancements and perhaps volatility within this sector. This is emblematic of the rapidly evolving and heterogeneous landscape of e-commerce in China, a reflection that aligns with empirical observations on the nation’s digital commerce forefront. The labor resource endowment is quantified with a mean of 2.791 and a standard deviation of 0.315, providing insights into a generally favorable labor capital across provinces. The metrics for technological investment, with an average of 0.997 and a standard deviation of 0.441, underline the ongoing endeavors in technological innovation but also hint at disparities in the extent and pace of such investments across the provinces. Finally, the metric for knowledge capital is calculated with an average value of 4.012 and a standard deviation of 1.506. Meanwhile, the education level is measured, showing an average value of 0.907 and a standard deviation of 0.217.

In the wake of conducting a correlation analysis, the subsequent findings are articulated in Panel B of Table 1 . An inaugural examination of the data reveals a discernible positive relationship between foreign direct investment and e-commerce relative to the scope of China’s provincial export trade. Parallel to this, a deeper analytical traverse into the data underscores a tangible connection between labor resource endowment and technological forays as pivotal determinants of export trajectories. This interrelationship accentuates the premise that provinces emphasizing sustainable labor methodologies and avant-garde technological endeavors are not solely shaping a resilient economic structure but are concurrently enhancing their export trade capacities. This synergy between sustainability-oriented strategies and burgeoning trade volumes fortifies the argument that sustainability stands as a potent stimulant, accentuating both foreign direct investment and e-commerce outcomes. Furthermore, the analysis essentially establishes a positive correlation between knowledge capital, education level, and the export trade of China’s provinces.

In this investigation, a quintet of econometric techniques is deployed to discern the nuanced impacts of foreign direct investment and e-commerce on export trade. These methodologies encompass pooled ordinary least squares (Model 1), panel ordinary least squares (Model 2), province-specific fixed effects (Model 3), year-fixed effects (Model 4), and a provincial and year-fixed-effects approach integrating both provincial and annual dimensions (Model 5). The outcomes of these estimations are documented in Table 2 . Upon evaluating the data through the prism of the Chow test, we discerned a clear rejection of the null hypothesis, indicating the inadequacy of pooled ordinary least squares for this dataset. Subsequent to this, the Hausman test was executed, which further rejected the null hypothesis, rendering the province-fixed effect model suboptimal. The decision to employ Model 5—integrating both province- and year-fixed effects—is grounded in several advanced econometric postulations. Kropko and Kubinec ( 2020 ), Hill et al. ( 2020 ), and Fernández-Val and Weidner ( 2018 ) posited that in the presence of unobserved heterogeneity—factors that remained constant over time but vary across entities or vice versa—implementing province- and year-fixed effects can yield unbiased and consistent estimators. This became particularly salient when considering phenomena such as global economic oscillations or overarching regulatory changes, which exerted a consistent impact across all provinces. By accounting for these twin axes of variability, Model 5 ensures the extrication of extraneous influences from the core relationship between foreign direct investment, e-commerce, and export trade. This approach enhances the robustness of the analysis, fortifying the validity of causal extrapolations drawn from the empirical results.

In Table 2 , our primary focus is on the insights garnered from Model 5. However, it is crucial to recognize the crucial role that the outcomes of the additional four models played. These models act as a robustness check, lending further credibility to our main findings. Model 5’s empirical data highlights a robust and statistically significant link between the surge in foreign direct investment and the increase in export trade within Chinese provinces. Specifically, a 1% increase in foreign direct investment inflows is associated with a 0.209% rise in provincial export trade volume. Shifting our analysis to the impact of e-commerce on the export landscape of Chinese provinces, we observe a compelling dynamic. E-commerce is identified as a significant driver of export growth. Quantitatively speaking, a 1% growth in e-commerce activities results in a 0.405% increase in provincial export volumes. Moreover, our research identifies critical factors influencing export patterns in Chinese provinces, notably labor resources and technological investments. The study reveals that a 1% elevation in labor resource availability correlates with a 0.715% increment in export volumes at the provincial level. In the same vein, a 1% rise in technological investments is linked to a 0.304% boost in exports. Additionally, the study brings to light the constructive effects of knowledge capital and education levels on provincial export trade. An increase of 1% in these variables is found to enhance export volumes by 0.083% and 0.101%, respectively.

The positive correlation between foreign direct investment inflows and increased export trade can be understood through various theoretical frameworks and empirical studies. Drawing on the research of Adikari et al. ( 2021 ), Rehman et al. ( 2023 ), and Zhang and Chen ( 2020 ), the eclectic paradigm suggests that foreign direct investment promotes export trade by transferring advanced technologies, managerial expertise, and marketing skills to the host country. These spillover effects enhance the competitiveness of domestic firms, boosting their export potential. Additionally, foreign direct investment helps to establish export-oriented industries within host economies, as seen in China’s Special Economic Zones, which act as production and export hubs (Chiang and De Micheaux, 2022 ; Ngoc et al., 2022 ; Huang et al., 2023 ; Vukmirović et al., 2021 ). This influx of capital, technology, and knowledge through foreign direct investment acts as a catalyst, creating a trade-friendly environment and aligning provinces with a more globally integrated economic path. Several factors support e-commerce’s positive impact on provincial export volumes. Firstly, e-commerce reduces informational disparities, fostering a transparent market conducive to robust exports. Additionally, as e-commerce platforms grow, their value proposition to users strengthens, encouraging an environment ripe for increasing transactions, including exports. Thirdly, e-commerce inherently reduces transactional friction, enabling businesses to engage more effectively in international trade. The theories and results of researchers like Onjewu et al. ( 2022 ), who contend that e-commerce lowers traditional trade barriers and enables even small businesses to participate in global markets, support this viewpoint. Lipton et al. ( 2018 ) and Fritz et al. ( 2004 ) show that online platforms allow businesses to overcome geographic limitations, thus expanding their export reach. Tolstoy et al. ( 2021 ) and Zhong et al. ( 2022 ) discuss how e-commerce’s digital footprint lessens the constraints of geographical distance, creating a more fluid international trade environment. Khan and Khan ( 2021 ) and Watson et al. ( 2018 ) illustrate how digital trade avenues boost export growth by adapting to market changes and consumer preferences. Additionally, Xi et al. ( 2023 ) and Deng et al. ( 2023 ) highlight the relationship between digital infrastructures and export portfolio diversification, with e-commerce spurring product innovation and differentiation. In conclusion, the integration of these theoretical insights and empirical evidence underlines the significant role of e-commerce as a key driver in enhancing the scale of export trade in Chinese provinces.

Labor resources and technological investments have been identified as key factors positively influencing the scale of export trade in Chinese provinces. This result is consistent with the Heckscher–Ohlin theorem, which states that regions typically export goods that effectively use their most abundant resources, according to research from Kunroo and Ahmad ( 2023 ) and Akther et al. ( 2022 ). Given China’s substantial labor force, provinces endowed with richer labor resources are naturally capable of higher production, thereby supporting larger export volumes. Conversely, the relationship between technological investments and the strength of exports is anchored in contemporary economic growth theories, particularly those emphasizing the role of technology in economic development. Aghion et al. ( 1998 ) reinforce this notion, demonstrating that technological investment in regions not only enhances productivity but also provides a competitive advantage in international markets, thus boosting export capacity. Moreover, the study finds that both knowledge capital and education levels positively impact the scale of export trade in Chinese provinces. This underscores the importance of intellectual resources and educational attainment as drivers of export dynamics in a rapidly evolving economy like China’s. The correlation with knowledge capital reflects China’s strategic emphasis on innovation and intellectual property. Liu et al. ( 2017 ) emphasize that investments in research and development, especially in technology and sciences, have significantly enhanced China’s export capabilities, leading to an increase in patents and technological breakthroughs. Due to these advancements, Chinese products now have a competitive advantage in the global market with higher value and higher quality. Similarly, the significance of education in boosting export trade is notable. Yang ( 2012 ) points out that China’s focus on higher education and vocational training has equipped its workforce with the necessary skills for export-oriented industries, facilitating the production of more sophisticated, high-value products. Chen et al. ( 2022 ) further discuss how the synergy between technological advancement and educational development contributes to a more dynamic and diversified export sector. This interplay is vital for China’s ability to adapt to global economic changes and more effectively participate in international trade. In conclusion, the increase in exports due to heightened knowledge capital and education levels signifies China’s strategic transition towards a knowledge-based economy. This shift is reshaping the structure of its domestic industries and redefining China’s role and competitiveness in the global market.

In this study, meticulous measures were taken to guarantee both the accuracy and reliability of the results, especially those obtained from the analysis using the province and year-fixed effect models. To ensure the dependability of our findings, an extensive robustness check was conducted on the outcomes of the province and year-fixed effect model. This involved the use of two econometric techniques: fully modified ordinary least squares and dynamic ordinary least squares. The implementation of fully modified ordinary least squares and dynamic ordinary least squares was critical in substantiating the integrity of the inferences drawn from the province and year-fixed effect model. The employment of these methods not only bolsters the solidity of our results but also reflects a commitment to the best standards of empirical rigor and methodological thoroughness. This approach to data verification underlies the credibility and trustworthiness of our conclusions. The specifics of these findings are systematically outlined in Table 3 .

Table 3 presents a detailed evaluation of the estimated parameters, focusing on both their magnitude and statistical significance. Remarkably, the findings obtained through the application of fully modified ordinary least squares and dynamic ordinary least squares align closely with those from the initial province and year-fixed effect model. This alignment between fully modified ordinary least squares and dynamic ordinary least squares, in comparison to the province and year-fixed effect model, robustly confirms the accuracy of the original model. The consistency observed across these varied econometric methods not only strengthens the trustworthiness of the province and year-fixed effect model but also substantiates the reliability of the study’s overall findings. The convergence of results across these methodologies indicates that the initial province and year-fixed effect model was meticulously crafted and successfully captured the essential dynamics of the variables under examination. The adoption of this comprehensive cross-validation process, which incorporates multiple analytical techniques, reinforces the solidity and validity of the research’s conclusions. This multi-faceted approach to analysis assures a high level of confidence in the integrity and reliability of the study’s results.

Regional heterogeneity analysis

Spanning a considerable geographical expanse, China is officially categorized into three distinct regional demarcations: eastern, central, and western. The eastern precinct is widely acknowledged as the epitome of China’s developmental zenith, encapsulating its most economically advanced locales. Conversely, the central sector is recognized for its intermediary developmental status, while the western swathes are often delineated by developmental lacunae. These territories, though unified under a single nationhood, manifest disparate attributes ranging from their economic growth trajectories, state-directed policy nuances, and infrastructural development gradients to their inherent geographical peculiarities. To delve into the multifaceted influence of foreign direct investment and e-commerce on regional export dynamics, our empirical approach disaggregated the core dataset, structuring it into three region-specific sub-samples. This strategic bifurcation aimed at discerning the variable intensities of foreign direct investment and e-commerce influences across these heterogeneous regions. The analytical outcomes derived from this region-centric examination are detailed in Table 4 .

Reflected in Table 4 , the repercussions of foreign direct investment on export trade reveal intricate regional gradations within China’s geographical tapestry. Concretely, a marginal ascent of 1% in foreign direct investment is associated with a 0.278% enhancement in the export dynamism of the eastern provinces. This increment tapers to 0.179% for central provinces and further diminishes to 0.161% for their western counterparts. The scholarly discourses of Contractor et al. ( 2020 ), Dang and Zhao ( 2020 ), and Batschauer da Cruz et al. ( 2022 ) elucidated that the synergy between foreign direct investment and export growth hinged upon a triad of factors: intrinsic firm capabilities, locational attributes, and the operational modus operandi. The eastern provinces, historically recognized as China’s economic epicenter, are imbued with a robust infrastructural matrix, streamlined trade corridors, and a business milieu that gravitates towards global market integration. These intrinsic locational advantages, complemented by the spatial competition theory proposed by Proost and Thisse ( 2019 ), Redding and Rossi-Hansberg ( 2017 ), and Goerzen et al. ( 2013 ), amplify the efficacy of foreign direct investment in spurring export trade. On the contrary, the central belt, despite its ascending economic trajectory, is intermittently stymied by transitional economic impediments, occasionally attenuating the foreign direct investment-export nexus. The western provinces, albeit burgeoning, still navigate developmental constraints, resonating with Wang and Zhao ( 2015 ) and Jiang et al. ( 2016 )‘s backwash effects, wherein peripheral regions grapple to harness the complete spectrum of foreign direct investment benefits. From a sustainability lens, echoing the tenets of Milne and Gray’s ( 2013 ) Triple Bottom Line framework, the magnitude and mode of foreign direct investment’s assimilation should be judiciously balanced to ensure economic, social, and environmental equanimity. The immediate economic impetus observed, particularly in the eastern provinces, warrants an integrated approach wherein foreign direct investment infusion aligns with sustainable practices, ensuring that regional development dovetails with ecological stewardship and socio-cultural inclusivity. Such a harmonized trajectory ensures that the fruits of foreign direct investment are not ephemeral but perennial, fostering a resilient and sustainable export landscape across all regions.

Referring to the results presented in Table 4 , an augmentation of 1% in e-commerce transaction volume is observed to lead to a differentiated impact on the export trade across China’s tripartite regional structure: specifically, a surge of 0.397% in the eastern provinces, an enhancement of 0.365% in the central provinces, and a growth of 0.325% in the western provinces. This regional heterogeneity in the influence of e-commerce on export trade can be supported by a confluence of academic perspectives and established theoretical underpinnings. Drawing insights from Porter, Michael’s ( 2011 ) Competitive advantage theory, the eastern provinces, having established themselves as economic powerhouses, have already harnessed advanced infrastructural frameworks and digital ecosystems. This enables them to efficiently leverage the capabilities of e-commerce, thereby reflecting a more pronounced augmentation in their export trade. The central provinces, as highlighted by North and Douglass’s ( 1989 ) theory of institutional change, are navigating through evolving institutional landscapes, mediating between traditional trade mechanisms and burgeoning digital frontiers. While they have made significant strides, the transformational gaps that exist temper the full realization of e-commerce benefits in the domain of exports. The western provinces, on the other hand, are still grappling with foundational challenges. Drawing from Sachs and Warner’s ( 2001 ) resource curse hypothesis, these provinces, abundant in natural resources, might have historically focused more on primary sectors, leading to a lag in the adoption and integration of e-commerce into their economic tapestry. This could partially elucidate the relatively muted growth in export trade from e-commerce advancements. Incorporating the sustainability ethos, as expounded in the triple bottom line approach by Elkington ( 1998 ), the expansion of e-commerce should not merely serve economic objectives. It should be orchestrated in a manner that respects ecological boundaries and promotes social inclusivity. Especially in regions like the western provinces, where development is paramount, it is critical to ensure that the surge in e-commerce-driven exports is not at the expense of environmental degradation or social disparities, thereby upholding a balanced, sustainable developmental trajectory.

Conclusions

Amidst the fast-paced evolution of the global economy, key factors such as foreign direct investment and e-commerce have become instrumental in reshaping China’s export sector between 2005 and 2022. Our analytical models, which utilize a combination of province- and year-fixed effects analysis along with fully modified ordinary least squares and dynamic ordinary least-squares methodologies, shed light on how foreign direct investment and e-commerce synergistically enhance China’s export capabilities. Significantly, this expansion in China’s exports aligns with the global agenda for sustainable development. It’s encouraging to see that China’s growth in exports extends beyond the realms of international investment and digital marketplaces, intertwining sustainable practices like optimizing local labor resources and prioritizing technological advancements. These approaches contribute to a more sustainable export environment. Our findings further reveal that variables such as knowledge capital and educational levels positively influence China’s export figures. Additionally, our analysis of regional disparities provides a deeper understanding. The eastern regions of China show greater responsiveness to foreign direct investment and e-commerce in driving export trade, whereas the western regions respond more modestly. This variation highlights the need for tailored policies and sustainability strategies to ensure a fair distribution of the benefits from foreign direct investment and e-commerce across all regions. In conclusion, while foreign direct investment and e-commerce are key drivers of China’s export growth, the broader story is one of sustainable development. Technological innovation and human capital development are pivotal to China’s continued success in exports. Moving forward, it is essential for policymakers to maintain a careful equilibrium between these economic drivers and sustainable development goals, fostering a balance between economic growth and environmental sustainability.

Drawing upon the insights derived from this study, we elucidate several policy recommendations along with practical solutions. First, for policymakers and business leaders, investing in technology and education is identified as a crucial strategy. The significant impact of technological innovation and a well-educated workforce on export growth underscores the necessity for ongoing investment in these domains. For academia, this opens avenues for further research into specific types of educational programs and technological innovations that most effectively enhance export capabilities. Businesses, especially in the export sector, should prioritize employee training and the adoption of cutting-edge technologies to maintain competitiveness. Second, considering the varied responsiveness to foreign direct investment and e-commerce between China’s eastern and western regions, it’s imperative for regional authorities and business managers to customize their policies and strategies to suit the unique needs and strengths of their regions. This could involve targeted investments in infrastructure and digital capabilities in the eastern regions while simultaneously focusing on cultivating other competitive advantages in the western regions. Academia can play a role by conducting region-specific research to identify the most effective strategies for each area. Third, the intersection of export growth with sustainable development goals necessitates a comprehensive approach to policymaking. Managers in the export sector are encouraged to integrate sustainable practices into their business models, such as the utilization of environmentally friendly technologies and adherence to fair labor practices. This area also presents an opportunity for academic research into the effective implementation of sustainable practices in the export sector, aiming to balance profitability and competitiveness. Finally, our findings suggest that although foreign direct investment and e-commerce are significant drivers of export growth, their benefits are not uniformly experienced across all regions. This indicates the need for balanced development strategies that ensure equitable benefits from foreign direct investment and e-commerce across various regions. Strategies might include enhancing e-commerce infrastructure in less-developed areas or offering incentives for foreign investment in regions currently less engaged with these investments. For academics, this highlights the necessity of researching ways to optimize the impact of foreign direct investment and e-commerce across diverse regions, promoting equitable economic growth. These policy implications offer a strategic roadmap for leveraging key drivers of export growth in China, highlighting the importance of regional customization, sustainable development, and balanced economic strategies.

In the course of this research, certain limitations emerged that warrant acknowledgment. Firstly, the study’s timeframe, spanning from 2005 to 2022, may not fully capture the evolving dynamics of foreign direct investment and e-commerce in the context of China’s longer-term economic history. A more expansive temporal analysis could provide deeper historical insights. Secondly, while the fully modified ordinary least squares and dynamic ordinary least-squares methodologies and fixed effect models offer robustness, they may not encompass all the nuanced intricacies of the interactions between the chosen variables. Future research could employ mixed-method approaches, blending quantitative and qualitative inquiries to attain a richer understanding. Thirdly, our focus on regional heterogeneity, while pivotal, may overlook intra-regional variances that can significantly influence export trends. Subsequent studies might delve deeper into micro-level analyses, probing district- or city-level data. Fourthly, the emphasis on sustainability, though aligned with global imperatives, is predominantly viewed through the lenses of labor and technology. Incorporating other sustainability metrics, such as environmental or social indicators, could render a holistic view. Lastly, the external validity of our findings, primarily centered on China, might be limited in their generalizability to other nations. Comparative studies juxtaposing China’s experiences with those of other global players could bridge this gap. Addressing these limitations would not only refine the existing body of knowledge but also ensure a more comprehensive alignment of economic strategies with sustainable development goals.

Data availability

All data generated or analyzed during this study are included in this published article.

Abdul-Rahim R, Bohari SA, Aman A, Awang Z (2022) Benefit–risk perceptions of FinTech adoption for sustainability from bank consumers’ perspective: the moderating role of fear of COVID-19. Sustainability 14(14):8357, https://www.mdpi.com/2071-1050/14/14/8357

Article   CAS   Google Scholar  

Adikari AMP, Liu H, Marasinghe MMSA (2021) Inward foreign direct investment-induced technological innovation in Sri Lanka? Empirical evidence using ARDL approach. Sustainability 13(13):7334, https://www.mdpi.com/2071-1050/13/13/7334

Article   Google Scholar  

Agarwal J, Wu T (2015) Factors influencing growth potential of E-commerce in emerging economies: an institution-based N-OLI framework and research propositions. Thunderbird Int Bus Rev 57(3):197–215. https://doi.org/10.1002/tie.21694

Aghion P, Howitt P, Brant-Collett M, García-Peñalosa C (1998) Endogenous growth theory. MIT Press

Ahmed Z, Zafar MW, Ali S (2020) Linking urbanization, human capital, and the ecological footprint in G7 countries: an empirical analysis. Sustain Cities Soc 55:102064, https://www.sciencedirect.com/science/article/pii/S2210670720300512

Ahn SC, Thomas GM (2023) Likelihood-based inference for dynamic panel data models. Empir Econ 64(6):2859–2909. https://doi.org/10.1007/s00181-023-02375-0

Akther T, Voumik LC, Hasanur Rahman M (2022) The pattern of international trade between Bangladesh and USA: Heckscher–Ohlin and Rybczynski analysis. Mod Supply Chain Res Appl 4(3):162–176. https://doi.org/10.1108/MSCRA-03-2022-0011

Amornkitvikai Y, Tham SY, Harvie C, Writthym Buachoom W (2022) Barriers and factors affecting the e-commerce sustainability of Thai micro-, small-and medium-sized enterprises (MSMEs). Sustainability 14(14):8476, https://www.mdpi.com/2071-1050/14/14/8476

Antràs P, Alonso De Gortari, Itskhoki O (2017) Globalization, inequality and welfare. J Int Econ 108:387–412. https://www.sciencedirect.com/science/article/pii/S0022199617300958

Anzoategui D, Comin D, Gertler M, Martinez J (2019) Endogenous technology adoption and R&D as sources of business cycle persistence. Am Econ J 11(3):67–110. https://doi.org/10.1257/mac.20170269

Atil L, Fellag H, Sipols AE, Santos-Martín MT, De Blas CS (2023) Non-linear cointegration test, based on record counting statistic. Comput Econ https://doi.org/10.1007/s10614-023-10520-1

Atkin D (2016) Endogenous skill acquisition and export manufacturing in Mexico. Am Econ Rev 106(8):2046–2085. https://www.aeaweb.org/articles?id=10.1257/aer.20120901

Auboin M, Koopman R, Xu A (2021) Trade and innovation policies: coexistence and spillovers. J Policy Model 43(4):844–872. https://www.sciencedirect.com/science/article/pii/S0161893821000375

Autor DH, Dorn D, Hanson GH (2015) Untangling trade and technology: evidence from local labour markets. Econ J 125(584):621–646. https://academic.oup.com/ej/article-abstract/125/584/621/5077881

Bai J, Choi SH, Liao Y (2021) Feasible generalized least squares for panel data with cross-sectional and serial correlations. Empir Econ 60(1):309–326. https://doi.org/10.1007/s00181-020-01977-2

Baltagi BH (2021) Econometric analysis of panel data. Springer texts in business and economics. Springer International Publishing, Cham

Banalieva ER, Dhanaraj C (2019) Internalization theory for the digital economy. J Int Bus Stud 50(8):1372–1387. https://doi.org/10.1057/s41267-019-00243-7

Batschauer da Cruz, Beatriz C, Eliete Floriani D, Amal M (2022) The OLI paradigm as a comprehensive model of FDI determinants: a sub-national approach. Int J Emerg Mark 17(1):145–176. https://www.emerald.com/insight/content/doi/10.1108/IJOEM-07-2019-0517/full/html

Bhaumik, Kumar S, Driffield N, Zhou Y (2016) Country specific advantage, firm specific advantage and multinationality—sources of competitive advantage in emerging markets: evidence from the electronics industry in China. Int Bus Rev 25(1):165–176. https://www.sciencedirect.com/science/article/pii/S0969593115000050

Blanchard EJ, Olney WW (2017) Globalization and human capital investment: export composition drives educational attainment. J Int Econ 106:165–183. https://www.sciencedirect.com/science/article/pii/S0022199617300302

Blanchard, Jean-Marc F (2019) Brazil’s Samba with China: economics brought them closer, but failed to ensure their Tango. J Chin Political Sci 24(4):583–603. https://doi.org/10.1007/s11366-018-09586-8

Bollen KA, Fisher ZF, Giordano ML, Lilly AG, Luo L, Ye A (2022) An introduction to model implied instrumental variables using two stage least squares (MIIV-2SLS) in structural equation models (SEMs). Psychol Methods 27(5):752, https://psycnet.apa.org/record/2021-70427-001

Article   PubMed   Google Scholar  

Bruns SB, Moneta A, Stern DI (2021) Estimating the economy-wide rebound effect using empirically identified structural vector autoregressions. Energy Econ 97:105158, https://www.sciencedirect.com/science/article/pii/S0140988321000633

Castilho M, Menéndez M, Sztulman A (2012) Trade liberalization, inequality, and poverty in Brazilian states. World Dev 40(4):821–835. https://www.sciencedirect.com/science/article/pii/S0305750X11002403

Chebrolu N, Läbe T, Vysotska O, Behley J, Stachniss C (2021) Adaptive robust kernels for non-linear least squares problems. IEEE Robot Autom Lett 6(2):2240–2247. https://ieeexplore.ieee.org/abstract/document/9361339/

Chen H, Yan B, Fei R, Bao S (2023) Assessing the impact of trade policy uncertainty on pollution emissions: an analysis of Chinese firms’ green transformation. Environ Sci Pollut Res 30(47):104577–104591. https://doi.org/10.1007/s11356-023-29778-x

Chen J, Hu X, Huang J, Lin R (2022) Market integration and green economic growth—recent evidence of China’s city-level data from 2004–2018. Environ Sci Pollut Res 29(29):44461–44478. https://doi.org/10.1007/s11356-022-19070-9

Chiang M‐H, De Micheaux EL (2022) China’s outward foreign direct investment in Southeast Asia: analyzing the Chinese state’s strategies and potential influence. Thunderbird Int Bus Rev 64(6):581–593. https://doi.org/10.1002/tie.22311

Choong C-K (2012) Does domestic financial development enhance the linkages between foreign direct investment and economic growth? Empir Econ 42(3):819–834. https://doi.org/10.1007/s00181-011-0455-2

Christou C, Pittis N (2002) Kernel and bandwidth selection, prewhitening, and the performance of the fully modified least squares estimation method. Econom Theory 18(4):948–961. https://www.cambridge.org/core/journals/econometric-theory/article/kernel-and-bandwidth-selection-prewhitening-and-the-performance-of-the-fully-modified-least-squares-estimation-method/9F28178B61EF30D406AC2ABDC0AECBC0

Article   MathSciNet   Google Scholar  

Chudik A, Pesaran MH (2015) Common correlated effects estimation of heterogeneous dynamic panel data models with weakly exogenous regressors. J Econ 188(2):393–420. https://www.sciencedirect.com/science/article/pii/S0304407615000767

Contractor FJ, Dangol R, Nuruzzaman N, Raghunath S (2020) How do country regulations and business environment impact foreign direct investment (FDI) inflows? Int Bus Rev 29(2):101640, https://www.sciencedirect.com/science/article/pii/S0969593118305997

Cordes DL, Marinova D (2023) Systematic literature review of the role of E-commerce in providing pathways to sustainability for poverty alleviation in sub-Saharan Africa. Discov Sustain 4(1):7. https://doi.org/10.1007/s43621-022-00109-3

Article   ADS   Google Scholar  

Dang L, Zhao J (2020) Cultural risk and management strategy for Chinese enterprises’ overseas investment. China Econ Rev 61:101433, https://www.sciencedirect.com/science/article/pii/S1043951X20300304

Darku AB (2021) International trade and income convergence: sorting out the nature of bilateral trade. Int J Financ Econ 26(4):5337–5348. https://doi.org/10.1002/ijfe.2068

De Menezes DQF, Prata DM, Secchi AR, Pinto JC (2021) A review on robust M-estimators for regression analysis. Comput Chem Eng 147:107254, https://www.sciencedirect.com/science/article/pii/S0098135421000326

Deng T, Khan MA, Uddin M, Haider A (2023) Connecting fiscal decentralization with climate change mitigation in China: directions for carbon capturing systems. Processes 11(3):712, https://www.mdpi.com/2227-9717/11/3/712

Duan W, Zhu S, Lai M (2020) The impact of COVID-19 on China’s trade and outward FDI and related countermeasures. J Chin Econ Bus Stud 18(4):355–364. https://doi.org/10.1080/14765284.2020.1855395

Elia S, Giuffrida M, Mariani MM, Bresciani S (2021) Resources and digital export: an RBV perspective on the role of digital technologies and capabilities in cross-border e-commerce. J Bus Res 132:158–169. https://www.sciencedirect.com/science/article/pii/S0148296321002484

Elkington J (1998) Partnerships from cannibals with forks: the triple bottom line of 21st-century business. Environ Qual Manag 8(1):37–51. https://doi.org/10.1002/tqem.3310080106

Fernández-Val I, Weidner M (2018) Fixed effects estimation of large- T panel data models. Annu Rev Econ 10(1):109–138. https://doi.org/10.1146/annurev-economics-080217-053542

Fidrmuc J, Korhonen I (2010) The impact of the global financial crisis on business cycles in Asian emerging economies. J Asian Econ 21(3):293–303. https://www.sciencedirect.com/science/article/pii/S1049007809000657

Fingleton B (2023) Estimating dynamic spatial panel data models with endogenous regressors using synthetic instruments. J Geogr Syst 25(1):121–152. https://doi.org/10.1007/s10109-022-00397-3

Fritz M, Hausen T, Schiefer G (2004) Developments and development directions of electronic trade platforms in US and European agri-food markets: impact on sector organization. Int food Agribus Manag Rev 7(1030-2016–82569):1–21. https://ageconsearch.umn.edu/record/8146/

Google Scholar  

Fu X, Woo WT, Hou J (2016) Technological innovation policy in China: the lessons, and the necessary changes ahead. Econ Change Restruct 49(2–3):139–157. https://doi.org/10.1007/s10644-016-9186-x

Gao H (2018) Digital or trade? The contrasting approaches of China and US to digital trade. J Int Econ Law 21(2):297–321. https://academic.oup.com/jiel/article-abstract/21/2/297/4996884

Giuffrida M, Mangiaracina R, Perego A, Tumino A (2017) Cross-border B2C e-commerce to Greater China and the role of logistics: a literature review. Int J Phys Distrib Logist Manag 47(9):772–795. https://www.emerald.com/insight/content/doi/10.1108/IJPDLM-08-2016-0241/full/html

Goerzen A, Asmussen CG, Nielsen BB (2013) Global cities and multinational enterprise location strategy. J Int Bus Stud 44(5):427–450. https://doi.org/10.1057/jibs.2013.11

Gorla N, Chiravuri A, Chinta R (2017) Business-to-business e-commerce adoption: an empirical investigation of business factors. Inf Syst Front 19(3):645–667. https://doi.org/10.1007/s10796-015-9616-8

Götz M (2020) Attracting foreign direct investment in the era of digitally reshaped international production. The primer on the role of the investment policy and clusters—the case of Poland. J East-West Bus 26(2):131–160. https://doi.org/10.1080/10669868.2019.1692985

Grübler A, O’Neill B, Riahi K, Chirkov V, Goujon A, Kolp P, Prommer I, Scherbov S, Slentoe E (2007) Regional, national, and spatially explicit scenarios of demographic and economic change based on SRES. Technol Forecast Soc Change 74(7):980–1029. https://www.sciencedirect.com/science/article/pii/S0040162506001454

Ha LT (2022) Are digital business and digital public services a driver for better energy security? Evidence from a European sample. Environ Sci Pollut Res 29(18):27232–27256. https://doi.org/10.1007/s11356-021-17843-2

Hanelt A, Bohnsack R, Marz D, Antunes Marante C (2021) A systematic review of the literature on digital transformation: insights and implications for strategy and organizational change. J Manag Stud 58(5):1159–1197. https://doi.org/10.1111/joms.12639

Hao S, Chen Z, Wang C-C, Hung C-Y (2023) Impact of digital service trade barriers and cross-border digital service inputs on economic growth. Sustainability 15(19):14547, https://www.mdpi.com/2071-1050/15/19/14547

Hartono, Gian P, Robiyanto Robiyanto (2023) Factors affecting the inconsistency of dividend policy using dynamic panel data model. SN Bus Econ 3(2):53. https://doi.org/10.1007/s43546-023-00431-6

He Y, Wu R, Choi Y-J (2021) International logistics and cross-border E-commerce trade: who matters whom? Sustainability 13(4):1745, https://www.mdpi.com/2071-1050/13/4/1745

Hill TD, Davis AP, Roos JM, French MT (2020) Limitations of fixed-effects models for panel data. Sociol Perspect 63(3):357–369. https://doi.org/10.1177/0731121419863785

Huang Y, Muhammad S, Raza F, Usman M (2023) Asymmetric role of natural resources dependence, industrialization, and foreign direct investment in China’s economic growth. Resour Policy 85:103932, https://www.sciencedirect.com/science/article/pii/S0301420723006438

Jiang X, Zhang L, Xiong C, Wang R (2016) Transportation and regional economic development: analysis of spatial spillovers in China provincial regions. Netw Spat Econ 16(3):769–790. https://doi.org/10.1007/s11067-015-9298-2

Jin G, Huang Z (2023) Asymmetric influence of China’s outward FDI and exports on trade-adjusted resources footprint in belt and road node countries: moderating role of governance. Resour Policy 82:103558, https://www.sciencedirect.com/science/article/pii/S0301420723002696

Jones CI (2019) Paul Romer: ideas, nonrivalry, and endogenous growth. Scand J Econ 121(3):859–883. https://doi.org/10.1111/sjoe.12370

Katz R, Callorda F (2018) Accelerating the development of Latin American digital ecosystem and implications for broadband policy. Telecommun Policy 42(9):661–681. https://www.sciencedirect.com/science/article/pii/S0308596117302914

Khan H, Khan Z (2021) The efficacy of marketing skills and market responsiveness in marketing performance of emerging market exporting firms in advanced markets: the moderating role of competitive intensity. Int Bus Rev 30(6):101860, https://www.sciencedirect.com/science/article/pii/S0969593121000676

Kheifets IL, Phillips PCB (2023) Fully modified least squares cointegrating parameter estimation in multicointegrated systems. J Econ 232(2):300–319. https://www.sciencedirect.com/science/article/pii/S030440762100186X

Klimenko M, Qu J (2023) Global Digital Platforms, technology transfer and foreign direct investment policies in two‐sided markets. Econ Inq 61(3):584–604. https://doi.org/10.1111/ecin.13132

Kripfganz S, Sarafidis V (2021) Instrumental-variable estimation of large- T panel-data models with common factors. Stata J 21(3):659–686. https://doi.org/10.1177/1536867X211045558

Kropko J, Kubinec R (2020) Interpretation and identification of within-unit and cross-sectional variation in panel data models. PLoS ONE 15(4):e0231349, https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0231349

Article   CAS   PubMed   PubMed Central   Google Scholar  

Kunroo MH, Ahmad I (2023) Heckscher–Ohlin theory or the modern trade theory: how the overall trade characterizes at the global level? J Quant Econ 21(1):151–174. https://doi.org/10.1007/s40953-022-00330-x

Kwak J, Zhang Y, Yu J (2019) Legitimacy building and e-commerce platform development in China: the experience of Alibaba. Technol Forecast Soc Change 139:115–124. https://www.sciencedirect.com/science/article/pii/S0040162518309636

Lei T, Xie P (2023) Fostering enterprise innovation: the impact of China’s pilot free trade zones. J Knowl Econ https://doi.org/10.1007/s13132-023-01501-8

Li F, Frederick S, Gereffi G (2019) E-Commerce and industrial upgrading in the Chinese apparel value chain. J Contemp Asia 49(1):24–53. https://doi.org/10.1080/00472336.2018.1481220

Li K, Kim DJ, Lang KR, Kauffman RJ, Naldi M (2020) How should we understand the digital economy in Asia? Critical assessment and research agenda. Electron Commer Res Appl 44:101004, https://www.sciencedirect.com/science/article/pii/S1567422320300818

Article   PubMed   PubMed Central   Google Scholar  

Li K, Cui G, Lu L (2020) Efficient estimation of heterogeneous coefficients in panel data models with common shocks. J Econ 216(2):327–353. https://www.sciencedirect.com/science/article/pii/S0304407619302222

Li R, Liu Y, Bustinza OF (2019) FDI, service intensity, and international marketing agility: the case of export quality of Chinese enterprises. Int Mark Rev 36(2):213–238. https://www.emerald.com/insight/content/doi/10.1108/IMR-01-2018-0031/full/html

Li Y, He Y, Wu R (2023) Traversing the macroeconomic terrain: an exploration of South Korea’s economic responsiveness to cross-border e-commerce production technology alterations in the global arena. Sustainability 15(15):11719, https://www.mdpi.com/2071-1050/15/15/11719

Lin J, Luo Z, Luo X (2020) Understanding the roles of institutional pressures and organizational innovativeness in contextualized transformation toward e-business: evidence from agricultural firms. Int J Inf Manag 51:102025, https://www.sciencedirect.com/science/article/pii/S0268401219301896

Lipton A, Hardjono T, Pentland A (2018) Digital Trade Coin: towards a more stable digital currency. R Soc Open Sci 5(7):180155. https://doi.org/10.1098/rsos.180155

Article   ADS   PubMed   PubMed Central   Google Scholar  

Liu J, Xie J (2020) Environmental regulation, technological innovation, and export competitiveness: an empirical study based on China’s manufacturing industry. Int J Environ Res Public Health 17(4):1427, https://www.mdpi.com/1660-4601/17/4/1427

Liu L, Moon HR, Schorfheide F (2020) Forecasting with dynamic panel data models. Econometrica 88(1):171–201. https://doi.org/10.3982/ECTA14952

Liu X, Schwaag Serger S, Tagscherer U, Chang AY (2017) Beyond catch-up—can a new innovation policy help China overcome the middle income trap? Sci Public Policy 44(5):656–669. https://academic.oup.com/spp/article-pdf/doi/10.1093/scipol/scw092/20917267/scw092.pdf

Lyu C, Peng C, Yang H, Li H, Gu X (2022) Social capital and innovation performance of digital firms: serial mediation effect of cross-border knowledge search and absorptive capacity. J Innov Knowl 7(2):100187, https://www.sciencedirect.com/science/article/pii/S2444569X22000270

Mahalik MK, Pal S, Le T-H, Mishra S (2023) Does environmental policy stringency improve nature’s health in BRICS economies? Implications for sustainable development. Environ Sci Pollut Res 31(1):509–528. https://doi.org/10.1007/s11356-023-31134-y

Mansion SE, Bausch A (2020) Intangible assets and SMEs’ export behavior: a meta-analytical perspective. Small Bus Econ 55(3):727–760. https://doi.org/10.1007/s11187-019-00182-5

Mark NC, Sul D (2003) Cointegration vector estimation by panel DOLS and long‐run money demand*. Oxf Bull Econ Stat 65(5):655–680. https://doi.org/10.1111/j.1468-0084.2003.00066.x

Milne MJ, Gray R (2013) W(h)Ither ecology? The triple bottom line, the global reporting initiative, and corporate sustainability reporting. J Bus Ethics 118(1):13–29. https://doi.org/10.1007/s10551-012-1543-8

Mohammad Shafiee M, Warkentin M, Motamed S (2023) Do human capital and relational capital influence knowledge-intensive firm competitiveness? The roles of export orientation and marketing knowledge capability. J Knowl Manag https://www.emerald.com/insight/content/doi/10.1108/JKM-11-2022-0921/full/html

Moon HR, Weidner M (2017) Dynamic linear panel regression models with interactive fixed effects. Econom Theory 33(1):158–195. https://www.cambridge.org/core/journals/econometric-theory/article/dynamic-linear-panel-regression-models-with-interactive-fixed-effects/CE84629C05BB652892D7B7659A1D5CD5

Ngoc PTB, Vu HQ, Long PD (2022) Domestic total factor productivity with trade and heterogenous foreign direct investment in developing countries: a case of Vietnamese manufacturing. Int J Emerg Mark. https://www.emerald.com/insight/content/doi/10.1108/IJOEM-08-2021-1333/full/html

Norkutė M, Sarafidis V, Yamagata T, Cui G (2021) Instrumental variable estimation of dynamic linear panel data models with defactored regressors and a multifactor error structure. J Econ 220(2):416–446. https://www.sciencedirect.com/science/article/pii/S0304407620301275

North, Douglass C (1989) Final remarks-institutional change and economic history. J Inst Theor Econ/Z Gesamt Staatswiss 238:45, https://www.jstor.org/stable/40751187

Onjewu A-KE, Hussain S, Haddoud MY (2022) The interplay of e-commerce, resilience and exports in the context of COVID-19. Inf Syst Front 24(4):1209–1221. https://doi.org/10.1007/s10796-022-10342-w

Otchere I, Soumaré I, Yourougou P (2016) FDI and financial market development in Africa. World Econ 39(5):651–678. https://doi.org/10.1111/twec.12277

Panopoulou E, Pittis N (2004) A comparison of autoregressive distributed lag and dynamic OLS cointegration estimators in the case of a serially correlated cointegration error. Econom J 7(2):585–617. https://academic.oup.com/ectj/article-abstract/7/2/585/5073337

Pedroni P (2001) Fully modified OLS for heterogeneous cointegrated panels. In: Baltagi BH, Fomby TB, Carter Hill R (eds) Nonstationary panels, panel cointegration, and dynamic panels. Emerald Group Publishing Limited, pp. 93–130

Pelagatti M, Sbrana G (2024) Estimating correlations among elliptically distributed random variables under any form of heteroskedasticity. Quant Finance 1–14. https://doi.org/10.1080/14697688.2023.2278502

Perrini F, Tencati A (2006) Sustainability and stakeholder management: the need for new corporate performance evaluation and reporting systems. Bus Strategy Environ 15(5):296–308. https://doi.org/10.1002/bse.538

Phang DCW, Wang K, Wang Q, Kauffman RJ, Naldi M (2019) How to derive causal insights for digital commerce in China? A research commentary on computational social science methods. Electron Commer Res Appl 35:100837, https://www.sciencedirect.com/science/article/pii/S1567422319300146

Phillips PCB, Kheifets IL (2024) High-dimensional IV cointegration estimation and inference. J Econ 238(2):105622, https://www.sciencedirect.com/science/article/pii/S030440762300338X

Porter ME (2011) Competitive advantage of nations: creating and sustaining superior performance. Simon and Schuster

Proost S, Thisse J-F (2019) What can be learned from spatial economics? J Econ Lit 57(3):575–643. https://doi.org/10.1257/jel.20181414

Qi X, Chan JH, Hu J, Li Y (2020) Motivations for selecting cross-border e-commerce as a foreign market entry mode. Ind Mark Manag 89:50–60. https://www.sciencedirect.com/science/article/pii/S0019850118308071

Qian Y, Liu J, Cheng Z, Forrest JY-L (2021) Does the smart city policy promote the green growth of the urban economy? Evidence from China. Environ Sci Pollut Res 28(47):66709–66723. https://doi.org/10.1007/s11356-021-15120-w

Redding SJ, Rossi-Hansberg E (2017) Quantitative spatial economics. Annu Rev Econ 9(1):21–58. https://doi.org/10.1146/annurev-economics-063016-103713

Rehman A, Radulescu M, Ahmad F, Kamran Khan M, Iacob SE, Cismas LM (2023) Investigating the asymmetrical influence of foreign direct investment, remittances, reserves, and information and communication technology on Pakistan’s economic development. Econ Res-Ekonom Istraž 36(2):2131591. https://doi.org/10.1080/1331677X.2022.2131591

Rita P, Ramos RF (2022) Global research trends in consumer behavior and sustainability in E-Commerce: a bibliometric analysis of the knowledge structure. Sustainability 14(15):9455, https://www.mdpi.com/2071-1050/14/15/9455

Sachs JD, Warner AM (2001) The curse of natural resources. Eur Econ Rev 45(4–6):827–838. https://www.sciencedirect.com/science/article/pii/S0014292101001258

Shanmugalingam P, Shanmuganeshan A, Manorajan A, Kugathasan M, Pathirana GY (2023) Does e-commerce really matter on international trade of Asian countries: evidence from panel data. PLoS ONE 18(4):e0284503, https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0284503

Singh S, Singh R (2022) Revisiting the debate on import-led substitution and export-led industrialization: where is India heading under self-reliant India? J World Trade 56(1). https://kluwerlawonline.com/journalarticle/Journal+of+World+Trade/56.5/TRAD2022005

Sinha A, Sengupta T, Alvarado R (2020) Interplay between technological innovation and environmental quality: formulating the SDG policies for next 11 economies. J Clean Prod 242:118549, https://www.sciencedirect.com/science/article/pii/S0959652619334195

Song M, Wang S (2018) Market competition, green technology progress and comparative advantages in China. Manag Decis 56(1):188–203. https://www.emerald.com/insight/content/doi/10.1108/MD-04-2017-0375/full/html

Stojanovic V, He S, Zhang B (2020) State and parameter joint estimation of linear stochastic systems in presence of faults and n on‐Gaussian noises. Int J Robust Nonlinear Control 30(16):6683–6700. https://doi.org/10.1002/rnc.5131

Sun L, Li,M X, Wang Y (2024) Digital trade growth and mineral resources In developing countries: implications for green recovery. Resour Policy 88:104338, https://www.sciencedirect.com/science/article/pii/S0301420723010498

Sun X (2022) Human capital, radical product innovation, and product proliferation: evidence from China. Emerg Mark Financ Trade 58(7):1938–1950. https://doi.org/10.1080/1540496X.2021.1945437

Tang W, Li G (2023) Enhancing competitiveness in cross-border e-commerce through knowledge-based consumer perception theory: an exploration of translation ability. J Knowl Econ https://doi.org/10.1007/s13132-023-01673-3

Teng Z, He Y, Wu R (2022) E-commerce: does sustainable logistics development matter? Sustainability 15(1):579, https://www.mdpi.com/2071-1050/15/1/579

Tolstoy D, Nordman ER, Hånell SM, Özbek N (2021) The development of international e-commerce in retail SMEs: an effectuation perspective. J World Bus 56(3):101165, https://www.sciencedirect.com/science/article/pii/S1090951620300936

Trapani L (2015) Testing for exogeneity in cointegrated panels. Oxf Bull Econ Stat 77(4):475–494. https://doi.org/10.1111/obes.12072

Villegas-Mateos A (2022) Toward a sustainable entrepreneurial ecosystem in Qatar. Sustainability 15(1):127, https://www.mdpi.com/2071-1050/15/1/127

Vukmirović V, Kostić-Stanković M, Pavlović D, Ateljević J, Bjelica D, Radonić M, Sekulić D (2021) Foreign direct investments’ impact on economic growth in Serbia. J Balk East Stud 23(1):122–143. https://doi.org/10.1080/19448953.2020.1818028

Wagner M (2023) Fully modified least squares estimation and inference for systems of cointegrating polynomial regressions. Econ Lett 228:111186, https://www.sciencedirect.com/science/article/pii/S0165176523002112

Wang C, Liu T, Wen D, Li D, Vladislav G, Zhu Y (2021) The impact of international electronic commerce on export trade: evidence from China. J Theor Appl Electron Commer Res. 16(7):2579–2593. https://www.mdpi.com/0718-1876/16/7/142

Wang D, Zheng Y, Li G (2024) High-dimensional low-rank tensor autoregressive time series modeling. J Econ 238(1):105544, https://www.sciencedirect.com/science/article/pii/S0304407623002609

Wang J-F (2010) E-commerce communities as knowledge bases for firms. Electron Commer Res Appl 9(4):335–345. https://www.sciencedirect.com/science/article/pii/S1567422309000842

Wang Y, Zhao T (2015) Impacts of energy-related CO 2 emissions: evidence from underdeveloped, developing and highly developed regions in China. Ecol Indic 50:186–195. https://www.sciencedirect.com/science/article/pii/S1470160X14005330

Wang Y, Gao H, Wang H (2024) The digital silk road and trade growth—a quasi-natural experiment based on silk road E-commerce. Res Int Bus Financ 67:102140, https://www.sciencedirect.com/science/article/pii/S0275531923002660

Wang Y, Jia F, Schoenherr T, Gong Y, Chen L (2020) Cross-border e-commerce firms as supply chain integrators: the management of three flows. Ind Mark Manag 89:72–88. https://www.sciencedirect.com/science/article/pii/S0019850118308642

Watson GF, Weaven S, Perkins H, Sardana D, Palmatier RW (2018) International market entry strategies: relational, digital, and hybrid approaches. J Int Mark 26(1):30–60. https://doi.org/10.1509/jim.17.0034

Wei L, Ullah S (2022) International tourism, digital infrastructure, and CO 2 emissions: fresh evidence from panel quantile regression approach. Environ Sci Pollut Res 29(24):36273–36280. https://doi.org/10.1007/s11356-021-18138-2

Wei YD, Lin J, Zhang L (2020) E-commerce, Taobao Villages and regional development in China * . Geogr Rev 110(3):380–405. https://doi.org/10.1111/gere.12367

Winkler AM, Ridgway GR, Webster MA, Smith SM, Nichols TE (2014) Permutation inference for the general linear model. Neuroimage 92:381–397. https://www.sciencedirect.com/science/article/pii/S1053811914000913

Wooldridge JM (2010) Econometric analysis of cross section and panel data. MIT Press

Wright DK (2019) Long-term dynamics of pastoral ecology in northern Kenya: an old model for new resilience. J Anthropol Archaeol 55:101068, https://www.sciencedirect.com/science/article/pii/S0278416518302216

Xi X, Wei M, Teo BS-X (2023) The construction and evolution path of cross-border e-commerce ecosystem. Cent Eur Manag J 31(2):378–387. http://journals.kozminski.cem-j.org/index.php/pl_cemj/article/view/710

Xiao Y, Abula B (2023) Examining the impact of digital economy on agricultural trade efficiency in RCEP region: a perspective based on spatial spillover effects. J Knowl Econ https://doi.org/10.1007/s13132-023-01484-6

Yan Z, Lu X, Chen Y, Wang K (2023) Institutional distance, internationalization speed and cross-border e-commerce platform utilization. Manag Decis 61(1):176–200. https://www.emerald.com/insight/content/doi/10.1108/MD-09-2021-1172/full/html

Yang C (2012) Restructuring the export-oriented industrialization in the Pearl River Delta, China: institutional evolution and emerging tension. Appl Geogr 32(1):143–157. https://www.sciencedirect.com/science/article/pii/S0143622810001463

Yin ZH, Choi CH (2023) The effects of China’s cross-border e-commerce on its exports: a comparative analysis of goods and services trade. Electron Commer Res 23(1):443–474. https://doi.org/10.1007/s10660-021-09483-y

Zhang C, Zeng W (2023) Evaluating the construction of a digital supervision platform for digital trade systems: a multilateral perspective. J Knowl Econ 十一月. https://doi.org/10.1007/s13132-023-01597-y

Zhang C-H, Zhang SS (2014) Confidence intervals for low dimensional parameters in high dimensional linear models. J R Stat Soc Ser B: Stat Methodol 76(1):217–242. https://academic.oup.com/jrsssb/article-abstract/76/1/217/7075942

Zhang M, Yang R (2022) FDI and spillovers: new evidence from Malaysia’s manufacturing sector. Rev Dev Econ 26(2):847–877. https://doi.org/10.1111/rode.12857

Zhang Q, Sun Z, Wu F, Deng X (2016) Understanding rural restructuring in China: the impact of changes in labor and capital productivity on domestic agricultural production and trade. J Rural Stud 47:552–562. https://www.sciencedirect.com/science/article/pii/S0743016716300638

Zhang S, Chen C (2020) Does outward foreign direct investment facilitate China’s export upgrading? China World Econ 28(5):64–89. https://doi.org/10.1111/cwe.12328

Zhang X (2019) Investigation of E‐commerce in China in a geographical perspective. Growth Change 50(3):1062–1084. https://doi.org/10.1111/grow.12307

Zhao Y, He X, Ma L, Liu H (2022) Unbiasedness-constrained least squares state estimation for time-varying systems with missing measurements under round-robin protocol. Int J Syst Sci 53(9):1925–1941. https://doi.org/10.1080/00207721.2022.2031338

Article   ADS   MathSciNet   Google Scholar  

Zhong M, Wang Z, Ge X (2022) Does cross-border E-commerce promote economic growth? Empirical research on China’s pilot zones. Sustainability 14(17):11032, https://www.mdpi.com/2071-1050/14/17/11032

Zhou X, Cai Z, Tan KH, Zhang L, Du J, Song M (2021) Technological innovation and structural change for economic development in China as an emerging market. Technol Forecast Soc Change 167:120671, https://www.sciencedirect.com/science/article/pii/S0040162521001037

Download references

Author information

Authors and affiliations.

Department of Chinese Trade and Commerce, Sejong University, Seoul, 05006, Republic of Korea

You can also search for this author in PubMed   Google Scholar

Contributions

The author confirms sole responsibility for the conception and design, analysis and interpretation, and manuscript preparation.

Corresponding author

Correspondence to Yugang He .

Ethics declarations

Competing interests.

The author declares that he was a member of the Editorial Board of Humanities & Social Sciences Communications at the time of acceptance for publication. The manuscript was assessed in accordance with Humanities & Social Sciences Communications’ standard editorial processes.

Ethical approval

This article does not contain any studies with human participants performed by any of the authors.

Informed consent

Additional information.

Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ .

Reprints and permissions

About this article

Cite this article.

He, Y. E-commerce and foreign direct investment: pioneering a new era of trade strategies. Humanit Soc Sci Commun 11 , 566 (2024). https://doi.org/10.1057/s41599-024-03062-w

Download citation

Received : 16 November 2023

Accepted : 12 April 2024

Published : 04 May 2024

DOI : https://doi.org/10.1057/s41599-024-03062-w

Share this article

Anyone you share the following link with will be able to read this content:

Sorry, a shareable link is not currently available for this article.

Provided by the Springer Nature SharedIt content-sharing initiative

Quick links

• Explore articles by subject
• Guide to authors
• Editorial policies

Click through the PLOS taxonomy to find articles in your field.

For more information about PLOS Subject Areas, click here .

Loading metrics

Open Access

Peer-reviewed

Research Article

Remanufacturing and channel strategies in e-commerce closed-loop supply chain

Roles Conceptualization, Data curation, Methodology, Project administration, Writing – original draft

Affiliation China Telecom Research Institute, Guangzhou, 510630, China

Roles Formal analysis, Methodology, Software, Writing – review & editing

* E-mail: [email protected]

Affiliation School of Economics and Management, Beijing University of Posts and Telecommunications, Beijing, 100876, China

Roles Resources, Supervision, Validation, Writing – review & editing

Affiliations School of Economics and Management, Beijing University of Posts and Telecommunications, Beijing, 100876, China, School of Modern Post (School of Automation), Beijing University of Posts and Telecommunications, Beijing, 100876, China

• Ying Shi, 
• Rong Ma, 
• Tianjian Yang

• Published: May 16, 2024
• https://doi.org/10.1371/journal.pone.0303447
• Reader Comments

This paper studies the recycling and remanufacturing mode and sales channel issues in the closed-loop supply chain. Specifically, this study establishes an e-commerce closed-loop supply chain consisting of a manufacturer and an e-commerce platform, and divides the recycling model into recycling by the manufacturer or recycling by the platform. Considering two common sales models in e-commerce platforms: the resale model and agency model, combined with the recycling model, four different research scenarios are formed. We use backward induction to solve the Stackelberg game problem and explore the remanufacturing and channel strategies of the manufacturer and the e-commerce platform. The research results show that for the manufacturer, under the same recycling model, when consumers’ preference for remanufactured products and the sensitivity of recycling volume to recycling prices are low, he will prefer the resale model. Under the same sales model, the manufacturer always prefers the recycling model in which he is responsible for recycling. However, the choice of platform is contrary to that of the manufacturer. In the resale model, both the manufacturer and the platform will choose to recycle by themselves, which cannot achieve a win-win situation. Under the agency model, when consumers’ preference for remanufactured products is high and the sensitivity coefficient of recycling volume to recycling price is low, supply chain members can achieve a win-win situation, and the scope of the win-win situation decreases as the unit production cost of new products increases. In addition, rising consumer preference for remanufactured products will lead to lower consumer surplus.

Citation: Shi Y, Ma R, Yang T (2024) Remanufacturing and channel strategies in e-commerce closed-loop supply chain. PLoS ONE 19(5): e0303447. https://doi.org/10.1371/journal.pone.0303447

Editor: Mohammad Masukujjaman, Management and Science University Faculty of Business Management and Professional Studies, MALAYSIA

Received: January 24, 2024; Accepted: April 24, 2024; Published: May 16, 2024

Copyright: © 2024 Shi et al. This is an open access article distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Data Availability: All relevant data are within the manuscript.

Funding: The author(s) received no specific funding for this work.

Competing interests: The authors have declared that no competing interests exist.

1. Introduction

Research on supply chains has long had a strong foundation in sustainable development, and many studies have been conducted based on closed-loop supply chains. A closed-loop supply chain (CLSC) refers to the recycling of goods from consumers and the reuse of all or part of the goods to obtain added value. Guide and Van Wassenhove define a closed-loop supply chain from a business perspective as: a system designed, controlled and operated to maximize value creation throughout a product’s lifecycle and to dynamically recover value from different types and quantities of returns over time [ 1 ]. Recently, the "China Renewable Resource Recycling Industry Development Report (2023)" released by the China National Resources Recycling Association pointed out that the total volume of renewable resource recycling in China in 2022 was approximately 371 million tons [ 2 ]. This number highlights the importance of renewable resource recycling and its huge potential for the sustainable development of our country.

The continuous development of the Internet has promoted the development of the e-commerce market. According to the "China E-Commerce Report (2022)" released by the Ministry of Commerce, data from the National Bureau of Statistics of China show that in 2022, the national e-commerce transaction volume reached 43.83 trillion yuan, which is an increase of 3.5% over the previous year. The discussion on CLSC has expanded to include the context of e-commerce due to its rapid growth. Product recycling and the sale of remanufactured products are common in e-commerce, and there are different recycling entities. On the one hand, e-platforms can be responsible for recycling. For example, large e-commerce platforms JD.com and Taobao both provide recycling services to consumers, including door-to-door pickup and in-person quality inspection services. There are also specialized second-hand product recycling platforms, such as Xianyu and Zhuanzhuan. On the other hand, as the main body of product manufacturing and sales, manufacturers may also serve for recycling. For example, Bright Milk recycles milk cartons, and Uniqlo also announced product recycling and reuse activities on its official website. Moreover, to encourage consumers to recycle products, some manufacturers have also developed recycling incentive mechanisms. For example, the German water purifier brand BRITA recycles filter elements from consumers. Scores can be accumulated based on the number of recycling filters, which can be used to redeem new water purifier filter elements. It can be seen that different recycling models are both common in CLSC. Trade-in services are also a common recycling incentive mechanism, where consumers can exchange old (used) products for new ones [ 3 ].

In the e-commerce platform supply chain, in addition to the selection of recycling and remanufacturing entities, there is also an important business strategy, that is, the selection of sales modes. Existing studies have discussed the CLSC decision-making issues of different recycling entities, but did not consider the different sales modes in e-commerce platforms [ 4 ]. The resale mode and agency sales mode are the two main sales models on e-commerce platforms. As an online retailer, the platform purchases goods wholesale from manufacturers and resells them to customers. This is a resale mode, such as JD.com ’s self-operated sales. The e-commerce platform operates as an online market, offering customers and manufacturers a trading platform and charging manufacturers commissions. This is an agency mode, such as the Taobao platform. In the agency mode, producers can interact directly with customers, whereas in the resale mode, the only role is to produce goods and wholesale them to the platform. What impact will different distances from consumers have on the choice of recycling mode? Is there a relationship between the way manufacturers sell their products and their choice of recycling mode? There is no clear conclusion yet on this issue. China’s two leading e-commerce platforms, JD.com and Taobao platforms both provide product recycling services to consumers. There is a lack of discussion on how different recycling models perform under different sales modes, and what impact different model combinations have on the profitability of supply chain members.

This study seeks to answer the following questions in light of the aforementioned theoretical and practical motivations:

(1) In the e-commerce closed-loop supply chain, what are the optimal recycling models for the manufacturer and the e-commerce platform under various sales models?

(2) Faced with the same recycling model, how do supply chain participants make channel strategies?

(3) Is there a strategy acceptable to both supply chain members to create a win-win scenario?

(4) What impact will different strategies have on consumer surplus?

To solve these problems, this paper establishes an e-commerce closed-loop supply chain model consisting of an e-commerce platform and a manufacturer. Considering two recycling models, the manufacturer is responsible for recycling and the e-commerce platform is responsible for recycling, as well as the two sales models of resale and agency on the e-commerce platform. Combining different strategies, four research scenarios are constructed. We establish the profit functions of the manufacturer and the e-commerce platform in each scenario respectively, and obtained the equilibrium solutions in each scenario by solving the Stackelberg game problem. By comparing the equilibrium solutions of different scenarios, the strategic choices of supply chain members are obtained. This study discusses the different sales models of the e-commerce platform from the perspective of different recycling entities in the closed-loop supply chain, supplementing the shortcomings of the existing literature by offering management insights into the operational choices made by participants in the closed-loop supply chain for e-commerce.

The remainder of this paper includes the following. Section 2 summarizes the literature relevant to this study. Section 3 explains the establishment of the model. The four models are discussed in detail in Section 4. Section 5 discusses the strategies of supply chain members. Section 6 compares the consumer surpluses in four models. The study findings are summarized in Section 7.

2. Literature review

The literature related to this study is mainly about the closed-loop supply chain and e-commerce sales modes.

2.1. Closed-loop supply chain

Savaskan et al. studied the closed-loop supply chain problem considering product remanufacturing, considered three different recycling modes and designed a coordination mechanism [ 5 ]. Many studies on CLSC are based on this. The closed-loop supply chain was defined by Guide and Van Wassenhove [ 1 ] and how it was developing from a commercial standpoint was summed up.

Scholars have discussed CLSC issues in a competitive environment. When there are competing retailers in the supply chain, supply chain members have different choices for direct and indirect recycling modes in decentralized and closed-loop supply chain structures [ 6 ]. Manufacturers have an incentive to remanufacture when there are competitors in the supply chain, but when competition declines, this incentive will diminish. In contrast, service competition hurts both competing manufacturers, while price competition might boost remanufacturers’ profitability [ 7 ]. A three-level CLSC network model with competition was developed by Qiang et al., and the effects of competition intensity and other variables on equilibrium were explored [ 8 ]. Both direct horizontal competition between two manufacturers and vertical competition between manufacturers and retailers were examined by Patare and Venkataraman [ 9 ]. They discovered that a higher level of competition can raise product quality.

As an important part of CLSC, consumer behavior has also attracted the attention of scholars. To optimize their utility, consumers may have varied preferences for different products due to the differences between new and remanufactured products. Scholars have done some studies taking into account customer preferences. The ideal price for both new and remanufactured goods was investigated by Abbey et al. using data from large-scale trials conducted in consumer preference models [ 10 ]. A rise in customer demand for remanufactured goods can boost supply chain efficiency overall and positively affect both product and price points. However, remanufactured products will suffer if manufacturers penalize e-commerce platforms given that they are concerned about fairness [ 11 ]. The proportion of green consumers among total consumers and their green preferences are also beneficial to manufacturers’ economic benefits and have an important impact on manufacturers’ green product segmentation strategies [ 12 ]. Due to the existence of consumer preferences, the factors that affect consumers’ willingness to purchase remanufactured products are also a question worth studying. Agrawal et al. conducted a behavioral experiment [ 13 ]. Hazen et al. examined customers’ propensity to switch from buying new items to buying remanufactured ones by combining macro-level pricing, government incentives, and environmental benefit variables with the moderating effects of micro-level consumer attitudes [ 14 ]. Consumers’ propensity to buy remanufactured products is greatly influenced by several factors, including perceived risks, costs, and moral obligations and responsibilities [ 15 ].

Due to the supervision of corporate social responsibility and the pursuit of sustainable social and economic development, the government also plays an important role in CLSC, which has attracted the attention of scholars [ 16 , 17 ]. The government’s management of CLSC mainly has two aspects, one is supervision and the other is subsidies. In terms of government regulation, the influence of recycling regulations on the remanufacturing business was examined by Esenduran et al. [ 18 ]. The trading supervision of carbon emission reductions by the government influences the decisions made in CLSC. By controlling the price of carbon trading, the government can have an impact on supply chain choices [ 19 ]. Carbon taxes are also a way for governments to regulate in order to promote sustainable development. Ma and Liu [ 20 ], and Li et al. [ 21 ] both discussed the carbon tax issue. Wang and Hong analyzed the best pricing and recycling practices in a CLSC with two recycling channels where the government provides subsidies to the manufacturer or two recyclers [ 22 ]. They found that subsidy policies stimulate consumption and increase the profits of supply chain members. Furthermore, government subsidies can regulate CLSC’s profit distribution. The effect of the subsidy will depend on the subsidy rate as well as the subsidy ceiling [ 23 ].

An essential component of CLSC is returns. Its objective is to recycle waste or products that don’t satisfy customer expectations from customers to a specific point in the supply chain where they can be processed. Researchers have studied return policies in great detail [ 24 , 25 ]. Additional shipping charges are frequently associated with the return process and are typically covered by the customer or retailer. It makes sense for customers to shoulder the cost when considering the real number of returns—that is, whether the volume of returns is high or the percentage of non-defective products among the returned products is low [ 26 ]. Zhang et al. conducted a study on the issue of defective products and waste returns. They concluded that, to lower the rate of defective product returns, it is not desirable to incur significant costs to improve product quality [ 27 ]. The best return policies vary depending on the supply contract. Comparative analysis revealed that buy-back and wholesale pricing contracts have stricter return policies than quantity discount contracts, which also result in higher demand and return requirements [ 28 ]. In an effort to encourage consumers to adopt sustainable practices, managers have created various programs for recycling used goods. To confirm the efficacy of these programs, Taleizadeh et al. set up various scenarios for examination. They discovered that acceptable return rules can accomplish supply chain coordination as well as environmental protection [ 29 ].

The various entities in charge of recycling and remanufacturing in CLSC have been covered in studies. Recycling activities can be carried out in a CLSC under cap-and-trade regulation by retailers, manufacturers, or other parties, and the carbon emissions under various regimes vary [ 30 ]. Manufacturers or sellers are able to remanufacture waste WEEE products under the WEEE CLSC. The best options for remanufacturing companies vary depending on the funding policies of the government [ 31 ].

Scholars have also addressed many aspects of the e-commerce CLSC, including platforms that offer extra warranty services, low-carbon e-commerce closed-loop supply chains, and differential pricing [ 11 , 32 , 33 ]. Blockchain technology is closely related to e-commerce. Ma and Hu talked about how platforms could maximize the synergy between "blockchain + sales formats" to enhance CLSC’s ESS (economic, social, and environmental) performance [ 34 ]. Liu et al. discussed the recycling channel structure selection problem of the e-commerce CLSC. The difference from this study is that they discussed three different recycling models, but did not consider different sales models [ 35 ].

Although studies related to CLSC have considered different recycling and manufacturing entities and have also studied channel issues, they haven’t looked at the topic of e-commerce-related sales channel strategies.

2.2. E-commerce sales mode

The resale model and agency model are the two main sales models in e-commerce. How to choose the optimal model is an important strategic issue faced by supply chain members. Abhishek et al. constructed a stylized theoretical framework to solve a crucial issue for e-tailers: When should an agency sales strategy be employed rather than a more traditional resale approach [ 36 ]? Based on this, many studies on e-commerce sales modes have been carried out. Tian et al. compared the performance of different sales modes in the e-commerce supply chain, offering guidance for mode selection and important references for subsequent research [ 37 ]. Diverse aspects have been incorporated by scholars into the channel models research. Manufacturers tend to select the agency model when there are detrimental effects from online channels to offline channels and the online channels are not competitive [ 38 ]. The choice of channels by manufacturers is significantly influenced by the presence of the secondary market. One important consideration is the price differential between new and old products. Manufacturers who want to sell expensive products will opt for the reselling model if there is a secondary market [ 39 ]. Hu et al. further studied the interaction between suppliers’ strategies for introducing market channels and e-tailers’ sales mode choices, they found that channel competition also affects the choice of sales model [ 40 ].

Related research has also extended to the situation with more supply chain members. In this case, there is generally horizontal competition between manufacturers or retailers. Researchers looked at the case of an e-commerce platform with several competitors and concluded that it makes more sense for manufacturers to choose resale on the platform rather than sell directly to customers. Simultaneously, if a manufacturer just opts for direct sales channels, then another manufacturer ought to run both platform resale channels and direct sales channels [ 41 , 42 ]. In contrast to platforms, Wang et al. talked about the emergence of independent internet retailers. The findings of the study indicate that when direct sales are low-cost, manufacturers will opt for them. Otherwise, commissions and competition have an impact on the choice of agency and resale models [ 43 ]. The above studies are all based on information symmetry, and scholars have also discussed scenarios of information asymmetry [ 44 , 45 ]. Sun et al. investigated the influence of sales form [ 46 ]. Under different sales structures, e-commerce platforms have varying incentives to reveal demand information to upstream. For instance, under the agency model, information regarding negative demand should not be shared, and information about strong market demand should not be disclosed during resale [ 47 ].

Hot issues such as logistics services and live sales in e-commerce are inseparable from discussions combined with sales models [ 48 ]. The platform’s choice of sales model will be influenced by its level of logistics. The hybrid sales model is the ideal option when the platform’s degree of logistics significantly surpasses that of third parties [ 49 ]. The platform’s decision to establish market channels is also affected by the level of logistics services. With high logistics service sales, platforms are more willing to introduce market channels [ 50 ]. In addition, as an emerging type of e-commerce, the issue of live streaming sales and e-commerce sales modes has also attracted the attention of scholars. Supply chain participants will select the agency model simultaneously when evaluating the competition and spillover impacts of live broadcasting under suitable commissions due to negative competition effects and low competition intensity [ 51 ].

Cao et al. studied the trade-in problem, considered the competition between the third-party seller and platform self-operation store, analyzed different trade-in models, and found the optimal trading strategy of the platform [ 52 ]. Yang et al. examined the issue of firms providing dual-channel trade-in programs and analyzed the impact of the profitability of dual-channel firms in the trade-in operation model [ 3 ].

Existing research lacks the issue of sales mode selection in e-commerce CLSC. The discrepancies between this research and relevant literature are presented in Table 1 . As can be seen from the table, our research is close to that of Yang et al. [ 3 ], but they studied the issue of trade-in for old products and did not consider the sales of remanufactured products, nor did they discuss the combination of different sales models and recycling models. This study supplements the deficiencies of related research. We integrate the approaches of the channel model and the recycling model, considering the inclinations of consumers towards remanufactured goods. Based on the decision-making of supply chain members, win-win issues are discussed.

• PPT PowerPoint slide
• PNG larger image
• TIFF original image

https://doi.org/10.1371/journal.pone.0303447.t001

3. Problem description and assumptions

As shown in Fig 1 , We construct a closed-loop e-commerce supply chain that consists of an e-commerce platform (she) and a manufacturer (he). In the illustration, the forward product circulation direction is represented by the solid line, and the reverse product circulation direction is shown by the dotted line, and the green color represents the supply chain member responsible for recycling. The market offers both brand-new and remanufactured products. Based on different collection models and channel structures, four different scenarios are established: (a) Model MR: e-commerce platform resale model, the collection subject is the manufacturer. As shown in the figure, the manufacturer sells new and remanufactured products to the e-commerce platform at wholesale prices w n and w r , and then the platform sells the products to consumers at resale prices p n and p r . The manufacturer recycles the product to the consumer at price f . (b) Model MA: agency sales model, the collection subject is the manufacturer. The manufacturer sells the new and remanufactured products directly to consumers at resale prices p n and p r , and the platform charges a certain percentage of commission α . The manufacturer recycles the product to the consumer at price f . (c) Model ER: e-commerce platform resale model, the collection subject is the e-commerce platform. The manufacturer sells the new product to the e-commerce platform at a wholesale price w n , and then the platform sells the new product to consumers at a resale price p n . The e-commerce platform recycles products to consumers at price f and sells remanufactured products directly to consumers at price p r . (d) Model EA: agency sales model, the collection subject is the e-commerce platform. The manufacturer sells the new products directly to consumers at resale prices p n , and the platform charges a certain percentage of commission α . The e-commerce platform recycles products to consumers at price f and sells remanufactured products directly to consumers at price p r .

https://doi.org/10.1371/journal.pone.0303447.g001

3.1. Consumer demand

3.2. Production cost

The manufacturer’s unit costs of producing new and remanufactured goods are c n and c r , respectively. Based on Zheng et al. we assume that c n > c r = 0. That is, a new product’s unit cost is more than a remanufactured product’s [ 54 , 58 ].

3.3. Recycling cost

All notations and explanations are given in Table 2 .

https://doi.org/10.1371/journal.pone.0303447.t002

4. Model and analyse

For the four different scenarios, we establish the profit function separately, and apply the Stackelberg game-theoretic model to obtain the equilibrium solutions by backward derivation and analyze the results.

4.1. Model MR

Corollary 1 states that the wholesale price and sales price of the new product and the remanufactured product are positively correlated with the unit production cost of the new product. The impact of an increase in new product production costs on new product prices is in line with pricing strategies. To achieve profitability, the wholesale price set by the manufacturer will rise, and this will impact the platform retailer’s sales pricing. The increase in the price of the new product requires the manufacturer to adjust that of the remanufactured good at the same time to keep the competitive relationship between the two products in the market. The wholesale and sales prices of the remanufactured product are positively correlated with consumer preference for the remanufactured product, and negatively related to the sensitivity coefficient of recycling volume to recycling price. It makes sense for customer choices to have an influence on product prices. A higher value of λ results in a lower recycling price for the remanufactured product. This lowers the cost of the remanufacturing process for the producer and ultimately lowers the remanufactured product’s wholesale price. The remanufactured product’s sales price decreases as well.

4.2. Model MA

Corollary 2 points out that under the agency model, the price at which the manufacturer sells the new and remanufactured product is positively related to the new product’s unit cost. The sales price of the remanufactured product is positively correlated with consumer preference for the remanufactured product, and negatively related to the sensitivity coefficient of recycling quantity to recycling price. This is consistent with scene MR. In scenario MA, the manufacturer has to pay a commission to the platform. The commission has a positive relationship with the sales price of both goods. This happens as a result of the manufacturer’s profit margins being reduced by increasing the fee. To improve profits, the manufacturer must raise prices.

4.3. Model ER

According to Corollary 3, the unit cost of manufacture of a new product has a positive correlation with all prices. This conclusion is consistent with Proposition 1. Consumer preferences for remanufactured products negatively affect the sales price of the new product and positively affect that of the remanufactured one. This is easily explained. Remanufactured items become more competitive and customers are more prepared to embrace them as their awareness of environmental issues grows. The remanufactured product’s price increases while the new product’s price decreases. The selling prices of both new and remanufactured goods are negatively correlated with the sensitivity coefficient of recycling quantity to recycling price. This is also consistent with the conclusion of Corollary 1. As λ increases, the platform’s recycling cost decreases, leading to a decrease in the selling price.

4.4. Model EA

As demonstrated by Corollary 4, the influence of the new product’s unit production cost and the product recycling quantity’s sensitivity coefficient to the recycling price on the equilibrium price in model EA are in line with the previous findings. That is, whether it is manufacturing costs or recycling costs, rising expenses will always result in higher pricing. Furthermore, there exists a positive correlation between commission rates and the sales price of both new and remanufactured goods. The product pricing structure on the market shifts as a new product’s price goes up with commissions. The platform will raise the sales price in order to stay competitive if it thinks that the market can handle higher pricing and that customers are still eager to purchase.

4.5. Pricing analysis

Through the equilibrium solutions of the wholesale and sales prices of new and remanufactured products under different scenarios, the following findings are reached.

Proposition 1 The wholesale prices in the four scenarios have the following relationships:

Proposition 1 states that in the resale model, remanufactured items have a lower wholesale price than new products. The wholesale price of new products is not affected by the recycling entity. That is, regardless of whether the manufacturer or the platform is in charge of recycling and remanufacturing goods, the wholesale price of new products stays the same. The difference in wholesale prices is determined by production costs. Based on the hypothesis of the study, compared to remanufactured items, new products have a greater unit production cost, so there will be higher wholesale prices. The manufacturing and sales of remanufactured products are impacted by changes in the recycling system, while the production and selling of new products are unaffected, meaning that the wholesale costs of new products remain unchanged. To display the comparison between equilibrium prices more intuitively, we conducted numerical simulations. Numerical simulation methods have been widely used in the study of decision optimization. The numerical simulation in this article is based on the theoretical and practical basis of previous research, and the relevant parameters are assigned values [ 11 , 58 ].

Fig 2 illustrates how consumer desire for the remanufactured product causes the difference between the wholesale costs of the new product and the remanufactured product to close. This is consistent with cognition. The demand for the remanufactured product will rise due to the increased customer preference, which will also raise its price and reduce the difference between it and the new product.

https://doi.org/10.1371/journal.pone.0303447.g002

Proposition 2. The selling prices in the four scenarios have the following relationships:

As seen in Fig 3 , Proposition 2 indicates that the link between product sales prices and the new product’s unit manufacturing cost ( c n ) is significant. When c n is small, the sales price of items under the resale model is higher than that of the agency model, according to a comparison of the prices of new and remanufactured goods under the same recycling structure. Comparing the prices under the same sales model, it is found that when c n is small, the sales price of the product when recycled by the manufacturer is always greater than the price when recycled by the e-commerce platform. When new products are recycled by the manufacturer rather than the e-commerce platform, the sales price of the former is always higher under the resale model. The higher price under the resale model than the agency model can be explained by double marginalization. Under the resale model, the platform sets the retail price and sells the goods to the customer after the manufacturer sets the wholesale price. Both have profit maximization as their goal, and product pricing is subject to double marginalization, which is higher than in a model where the manufacturer sells at a direct price.

https://doi.org/10.1371/journal.pone.0303447.g003

Whoever is in charge of recycling and remanufacturing does not affect the manufacturing and marketing process for the new product. However, a change in the recycling entity affects the remanufactured product. When the manufacturer carries out the recycling, the sales price of the new and remanufactured products are decided by the same subject, and when the platform carries out recycling, the manufacturer and the platform decide on the sales prices respectively. Since there is no way to observe the pricing of the other product, the price of the new product will be set in such a way as to avoid overpricing and losing the market. Simultaneous pricing provides better control over the sales price and market conditions. For the remanufactured goods, when c n is low, the cost difference between the two products is small and the sales price of the product is the same as that of the new product. When c n is high, the new product’s production costs are high. As a result, the manufacturer recycling model will customarily lower wholesale prices for the remanufactured product in order to maintain profit margins. As a result, the remanufactured product’s resale price will be lower than in the platform recycling scenario. Fig 3 illustrates how the price of both products rises in tandem with the new product’s unit cost of production. The price of a new product when recycled by the manufacturer under the resale model is always higher than the price via the recycling model on the e-commerce platform. Comparing Fig 3A–3D respectively, it can be seen that when consumers’ preference for the remanufactured product increases, for the new product, the sales price does not change much under the platform recycling model, but increases in the manufacturer recycling mode. For the remanufactured product, the reduction in β significantly reduces the sales price. This is due to reduced product preference leading to reduced product demand, thus sellers lower prices to attract consumers.

5. Recycling and channel strategies

In this section, we discuss the strategies of the supply chain members. After discussing the manufacturer’s and the e-commerce platform’s respective strategies, we go over win-win situations for both sides.

5.1. The manufacturer’s strategies

To study the manufacturer’s optimal sales model under different recycling models and the optimal recycling model under different sales models, we compare the manufacturer’s profit under different scenarios, and come up with the following conclusions.

Proposition 3 shows that in the model where the manufacturer is responsible for recycling, when λ is small the manufacturer chooses the resale model, otherwise the manufacturer chooses the agency model. In the model where the platform is responsible for recycling, when c n is small, if the commission is high the manufacturer chooses the resale model, otherwise he chooses the agency model. In the product recycling framework where the manufacturer has the responsibility for recycling, the cost of recycling is high when λ is low and decreases as λ rises. The agency model requires the manufacturer to pay the commission. Due to cost structure considerations, the manufacturer chooses the agency model when the recycling cost is low to gain more profit. The conclusion of Proposition 3(ii) seems to contradict common sense, and we offer the following explanation. From (i) and (ii) of Proposition 1, when c n is small, new products and remanufactured goods are offered at higher prices in the resale model; when c n is large, new and remanufactured goods are offered at greater prices in the agency model. Meanwhile, the wholesale price increases as the unit cost of new products rises. So for the manufacturer, when new items have low unit production costs, the profit margin under the agency model becomes low as the commission rises, so he will choose the resale model. The manufacturer will select the agency model as α increases because the selling price of the product under the agency model is higher at this time and is positively correlated with the commission, which is necessary to obtain a larger profit margin when the unit cost of production of the new product is high.

We use numerical analysis to provide a graphic representation of the relationship between the manufacturer’s profit and customer demand for remanufactured products, as well as the sensitivity of recycling volume to recycling pricing. As shown in Fig 4 , the manufacturer’s profit is higher in the resale model than in the agency model when the recycling quantity is less sensitive to the recycling price.

Manufacturer’s channel strategy in (a) the model with manufacturer recycling; (b) the model with e-commerce platform recycling ( c n = 0.9, α = 0.075).

https://doi.org/10.1371/journal.pone.0303447.g004

Proposition 4 shows that in both the resale model and the agency mode, the manufacturer chooses to recycle himself, that is, given any sales model, the manufacturer is willing to be responsible for product recycling and remanufacturing himself. Under the resale model, the manufacturer doesn’t face consumers directly, making new products and selling them to the platform retailer at wholesale prices. If the manufacturer is responsible for recycling and remanufacturing and then wholesaling to the platform, he can better control the cost, realize the distribution of products and reduce the intensity of competition in the market. Under the agency mode, the manufacturer faces consumers directly. If he is also responsible for recycling, he can have better control over the entire CLSC process and can adjust his own pricing and profits. It can be seen that for the manufacturer, no matter what sales mode he is in, it is more profitable to take on the role of recycling and remanufacturing. As seen in Fig 5 , the manufacturer’s profit difference (orange part in the figure) under the two recycling modes increases as consumers’ preference for remanufactured products increases. A rise in β increases the market demand for the remanufactured product, hence increasing the manufacturer’s profitability from recycling and producing the remanufactured product.

https://doi.org/10.1371/journal.pone.0303447.g005

5.2. The E-commerce platform’s strategies

To study the platform’s optimal sales model under different recycling models and the optimal recycling model under different sales models, we compare the e-platform’s profit under various scenarios and come up with the following conclusions.

Proposition 5(i)shows that in the scenario when the recycling is conducted by the manufacturer, the platform chooses the resale model when the sensitivity of the recycling volume to the recycling price ( λ ) is high, and the platform chooses the agency model when λ is low. This is the opposite of the manufacturer’s choice in Proposition 3. A rise in λ represents a decrease in the cost of recycling. When the manufacturer’s recycling cost is low, the wholesale price is also lowered, and the platform can make more profit by wholesaling the product from the manufacturer and then re-selling it through the resale model. As the cost of recycling increases, the platform is unable to make higher profits through wholesale and then re-sale, so she prefers to adopt the agency model of charging a commission to the manufacturer.

Proposition 5(ii) also concludes the opposite of Proposition 3. The platform’s decision is influenced by the new product’s unit manufacturing cost in the scenario where the platform is in charge of recycling. When c n is small, the platform chooses resale when alpha is small, and when c n is large, the platform chooses agency when alpha is small. When c n is small, the price of the product is low, and the platform cannot make more profit from the agency model when α is low, so she chooses the resale model. When c n is large, we know from Proposition 2 that the sales price under the agency model is greater. Meanwhile, as α increases, the price rises in both channels under the agent mode, and when α is too large, the excessively high price will have a dampening effect on demand and will have an impact on the platform’s profit, so she will shift to choose the resale mode. Similarly, we use numerical analysis to show in Fig 6 the impact of β and λ on platform profits. As Fig 6 illustrates, when the recycling amount is less sensitive to the recycling price, the manufacturer’s profit is larger in the resale model than in the agency model. Additionally, the manufacturer makes greater earnings in the resale model than in the agency model when consumer desire for the remanufactured product increases.

E-commerce platform’s channel strategy in (a) the model with manufacturer recycling; (b) the model with e-commerce platform recycling ( c n = 0.9, α = 0.075).

https://doi.org/10.1371/journal.pone.0303447.g006

Proposition 6 suggests that in the resale model, the platform prefers to recycle by herself rather than the manufacturer. This finding suggests that the platform’s choice is opposite to that of the manufacturer (Proposition 4). The new product is manufactured by the manufacturer and then wholesaled to the platform under the resale model; the platform is not in charge of the new product’s manufacturing process. When the platform is in charge of recycling the product and remanufacturing and selling it, she has control over the remanufactured product and increases her competitiveness. The platform is thus able to make more profit. As stated in Proposition 6’s conclusion, the resale model does not present a situation in which both the manufacturer and the e-commerce platform benefit. The agency model’s platform profit comparison is complicated and comes from a numerical study.

As shown in Fig 7 , in the agency model, when customer desire for the remanufactured product is low, the e-commerce platform chooses to perform product recycling herself. When the sensitivity of recycling volume to recycling price is low, the platform chooses the model in which the manufacturer conducts recycling. In addition, the cost of producing a new product rises per unit, the platform chooses the model where she conducts product recycling herself. Remanufactured products are in low demand when there is little customer desire for them. In the agency model, the platform has no sales revenue for new products, only commission revenue. Therefore, the platform’s profit margin is low if the manufacturer recycles the product and sells it to the platform in quantity. Similarly, when the unit production cost is high, the profit margin of selling the new product becomes small, and the commission that the platform can get becomes less. The platform prefers that the manufacturer shoulder the expense of recycling when λ is small because of its high cost.

https://doi.org/10.1371/journal.pone.0303447.g007

Because both the manufacturer and the e-commerce platform desire to recycle the goods themselves, Proposition 6 demonstrates that a win-win scenario cannot be achieved under the resale model. Under the agency model, as can be seen in Fig 8 , when β is high, a win-win scenario can be achieved. When β is high, as Fig 7 illustrates, the e-commerce platform also wants to carry out product recycling and sales of remanufactured products by the manufacturer, so a win-win situation is achieved at this point. When c n rises, the win-win space becomes smaller (the orange area in the figure shrinks from the black to the blue line). The same effect occurs when the sensitivity coefficient of the recycling quantity to the recycling price becomes larger. As analyzed earlier, an increase in both makes the platform more willing to choose the model of having herself carry out the recycling, which is the opposite of the manufacturer’s choice, so it will lead to a smaller win-win scope.

https://doi.org/10.1371/journal.pone.0303447.g008

6. Consumer surplus

In this section, we analyze consumer surplus under different scenarios. In green supply chains, consumer surplus is an important indicator for evaluating corporate social responsibility and sustainable development. Consumer surplus represents the residual utility of consumers after purchasing a product, and is usually calculated through the maximum product sales price acceptable to consumers and the actual sales price [ 60 , 61 ].

https://doi.org/10.1371/journal.pone.0303447.g009

7. Conclusions

In this study, a closed-loop e-commerce supply chain is established, and the issue of selecting sales and recycling models for the manufacturer and e-commerce platform is examined. We investigate the resale and agency models in e-commerce, as well as two recycling models wherein the responsibility for recycling and selling remanufactured products lies with the manufacturer and the e-commerce platform, respectively. By merging the models, we create four research scenarios. We analyzed the equilibrium solutions under each model and examined the strategies of manufacturers and e-commerce platforms. The conclusions and management takeaways are listed below.

7.1. Main findings

This study establishes an e-commerce closed-loop supply chain research model based on existing research, supplements the research conclusions in this field, and has theoretical significance.

Savaskan et al. [ 5 ] earlier studied the problem of different recycling entities in the closed-loop supply chain. Comparing the models of manufacturer recycling, retailer recycling and third-party recycling respectively, they found that under decentralized decision-making, the optimal recycling method for the manufacturer is retailer recycling. By establishing a combination of different sales models and recycling models in a closed-loop supply chain in the context of e-commerce, and comparing equilibrium solutions in different scenarios, this study not only obtained the manufacturer’s optimal strategy, but also obtained the e-commerce platform’s strategy selection.

First, for the manufacturer, in the scenario when recycling is his responsibility, when there is little customer interest in remanufactured goods or when there is little correlation between the price and quantity of recycling, the resale model is selected. In the scenario when recycling is the platform’s responsibility, when the unit production cost is small, the manufacturer with large commissions will choose the resale model, otherwise, he will choose the agency model. Cost is clearly a major factor in the manufacturer’s choice of sales strategy under various recycling scenarios. Within a given sales model, the manufacturer has the same recycling model choices. Specifically, when it comes to agency or resale modes, the manufacturer will always decide to recycle on his own. In addition, whatever the recycling strategy, the manufacturer’s profit under the agency model tends to surpass that under the resale model as consumers’ interest in remanufactured goods increases.

Secondly, for the platform, in the model where the manufacturer is responsible for recycling, in situations when recycling volume and recycling price are highly correlated, she usually selects the resale model and vice versa. The choice of platform is influenced by the unit production cost of new goods under the model where the platform is in charge of recycling products. In instances when costs are minimal, the platform selects an agency as commission levels rise. The platform selects resale when the cost is high and the commission rises. Under a given sales model, the e-commerce platform prefers to handle recycling herself rather than the manufacturer in the resale model. Since the strategy differs from the manufacturer’s, the resale model cannot result in a win-win scenario. When customers have little interest in remanufactured goods, the e-commerce platform opts to recycle the products herself under the agency model. The platform favors the manufacturer’s recycling model when the amount of recycling is less sensitive to the price of recycling. In addition, the platform chooses to recycle herself when the cost of producing new goods rises per unit.

Since the decision-making goals of both parties in the game are to maximize their own interests, conflicts will inevitably exist when choosing between different modes. Zhang et al. [ 31 ] showed in their study that when there is no government-funded coordination, the remanufacturing model that is the responsibility of the manufacturer will harm the retailer’s profits. Quan et al. [ 53 ] compared the models in which the manufacturer is responsible for recycling and the retailer is responsible for recycling and found that in most cases, the manufacturer and retailer prefer to be responsible for recycling themselves. In addition, they studied the conditions under which both parties can reach an agreement (i.e., a win-win situation), that is, when the market potential of the two periods meets certain conditions, a win-win situation can be achieved. Our study also analyzes the conditions for achieving a win-win situation for supply chain members by comparing the equilibrium strategies of the manufacturer and the e-commerce platform.

By examining the strategies used by supply chain participants, we discover that in the agency model, the platform will choose a recycling model within a specific range, which is consistent with the manufacturer’s choice, so it can achieve a win-win situation. Customers’ strong desire for the remanufactured product or a low sensitivity of recycling volume to recycling pricing is the prerequisite. A larger win-win scope can be achieved when the unit production cost of new products is low. Since both parties’ choices in the reselling model are opposing ones, a win-win scenario is not possible.

In the study of the closed-loop supply chain, consumer surplus has been fully discussed by scholars. Mu et al. [ 12 ] discussed the consumer surplus problem in the green supply chain and analyzed the impact of green product segmentation strategies. Jia and Li [ 57 ] discussed the consumer surplus under four distribution models in the closed-loop supply chain and found that there were different results under different order fulfillment costs and platform commission rates. In the trade-in problem, different models have different impacts on consumer surplus. If the waiting cost of consumers is high, the cooperation model between the enterprise and the platform can bring a higher consumer surplus than the self-built model [ 3 ].

Our study compares consumer surplus under different combinations of recycling and sales models in closed-loop supply management in the context of e-commerce and finds that consumer surplus is highest under the agency model where the platform is responsible for recycling, at which point double marginalization is alleviated. In addition, the reduction in consumer preference for remanufactured products and the reduction in recycling costs of remanufactured products will lead to an increase in consumer surplus.

7.2. Managerial implecations

Through the analysis of the theoretical model, we provide some management implications for supply chain members.

Manufacturers in closed-loop supply chains need to fully consider consumer preferences for remanufactured products when making decisions. From the conclusion, we see that consumer preferences for remanufactured products will affect manufacturers’ profits under different recycling and sales models. Categories with high consumer acceptance of remanufactured products are usually those with higher value, shorter life cycles, longer service life, and relatively affordable prices. Acceptance of remanufacturing is generally lower for products that require a high degree of hygiene, safety and performance, and for those that are closely related to individual tastes and preferences. Based on this conclusion, manufacturers can decide based on product category when choosing a sales mode. For a given recycling model, the manufacturers can prioritize the resale sales model for remanufactured products with low consumer preference, such as medical devices. Furthermore, given the sales model, manufacturers should give priority to recycling products themselves. Because from conclusion we see that higher profits can be achieved by recycling by the manufacturer himself. In other words, manufacturers should proactively pursue the important role of recyclers in CLSC.

There will be distinct equilibria since the manufacturer’s and the platform’s best options differ. Since the optimal choices of platforms and manufacturers are not entirely consistent, this means that when one party has more say, the interests of the other party may be harmed. This also means that different equilibrium situations will occur under different power structures. When the platform can make relevant decisions, as mentioned earlier, consumers’ preference of the remanufactured products should be taken into consideration. For example, under the agency model, for the remanufactured products that aren’t welcomed by consumers, the platform can proactively provide recycling services and act as a recycler to obtain higher profits. When the manufacturer is the formulation of decision-making, the platform can improve the profitability in the corresponding model, such as by increasing commissions.

Since a win-win situation can only be achieved under certain conditions, if the e-commerce platform and the manufacturer only make decisions from their own perspectives, no matter what kind of power structure they are under, one party may be harmed. Such a cooperation model is bound to not be a stable structure and is not conducive to the long-term stable development of the supply chain. When a win-win situation cannot be reached, both supply chain members should strengthen communication, reduce conflicts, and avoid damage to the profits. In a given sales model, the manufacturer hopes to recycle by itself, but the platform has different optimal choices in the resale mode. Therefore, to meet the optimal conditions, manufacturers should give priority to choosing an agency model to promote the realization of a win-win. Furthermore, compared to the resale model, the agency model has a larger consumer surplus. In order to assume corporate responsibility and improve social welfare, supply chain members should also work together to achieve a win-win situation and bring more utility to consumers under the agency model.

This study also has certain implications for government management decisions. On the one hand, given the conflicts that may arise in CLSC, the government should assume the responsibility for coordination. The government can establish a market coordination mechanism to improve the communication efficiency of supply chain members. When there is a decision-making conflict between the two sides of the supply chain, the government can coordinate and maintain the stability of the closed-loop supply chain. On the other hand, from the perspective of environmental sustainability and consumer welfare, the government should improve the public’s environmental awareness and encourage consumers to participate in environmental protection practices through publicity and science popularization. To avoid the reduction of utility caused by the increase in consumers’ environmental awareness, the government should regulate the price of remanufactured products. At the same time, to encourage supply chain members to participate in environmental protection practices, appropriate subsidies can be provided to reduce the cost of recycling and remanufacturing for supply chain members to increase their enthusiasm.

For consumers, we see from the research results that as consumers increase their preference for remanufactured products, consumer surplus will decrease. On the one hand, consumers should increase their awareness of environmental protection and voluntarily participate in environmentally sustainable practices. On the other hand, to protect their rights and interests, consumers should actively participate in the government’s supervision of remanufactured product pricing and jointly promote the good operation of the closed-loop supply chain.

7.3. Limitations

This study seeks to address the issue of channel and recycling mode selection in the e-commerce closed-loop supply chain, but there are still some limitations. For example, remanufacturing and recycling are the responsibility of the same supply chain member in this study. Future research may consider situations where remanufacturing and recycling responsibilities are separated, such as the presence of third-party corporate recycling, and discuss more scenarios. Further, scenarios of government subsidies or regulations can also be considered to solve more practical problems.

Supporting information

S1 appendix. proofs of propositions..

https://doi.org/10.1371/journal.pone.0303447.s001

• View Article
• Google Scholar
• 2. "China National Resources Recycling Association." accessed 19 October 2023, http://www.crra.com.cn .
• PubMed/NCBI

Advertisement

Systematic literature review of the role of e-commerce in providing pathways to sustainability for poverty alleviation in Sub-Saharan Africa

• Open access
• Published: 02 February 2023
• Volume 4 , article number  7 , ( 2023 )

Cite this article

You have full access to this open access article

• Darrold L. Cordes 1 &
• Dora Marinova 1  

5466 Accesses

4 Citations

1 Altmetric

Explore all metrics

Poverty elimination by 2030 is the major initiative of the United Nations Sustainable Development Goals. However, poverty in Sub-Saharan Africa is rising. There is an absence of structural reform for transformational change across the region. E-commerce is an enabler of small and large businesses in developed economies. Community-led initiatives for poverty alleviation may benefit from the transactional capabilities of e-commerce for direct trade with suppliers and consumers. Well-structured small and medium-size enterprises (SMEs) can foster local innovation and entrepreneurship, and collaboration between SMEs can enhance product development and marketing strategies. This review aims to discover formal research into the application of e-commerce in sustainable development models for poverty alleviation in Sub-Saharan Africa, and the extent of innovation, entrepreneurship, and collaboration among SMEs. The review found an absence of formal research into theories and practical strategies for sustainability innovations across the low-income spectrum. Organizational structures have not been developed to stimulate outreach, to foster innovation and entrepreneurship, or to embrace technology. Further, there is limited discussion on the importance of collaboration for the sharing of knowledge and joint business activities, but there is acknowledgement that SMEs can provide spatially diversified sustainable development. This article proposes a framework for the implementation and management of networks of SMEs focused on the sustainable development of low-income communities.

Similar content being viewed by others

Innovative Sustainable Business Models: A New Way to Recover Beyond the Pandemic

Towards a comprehensive analytical framework and future research agenda for research on sharing economy business models: thematic analyses approach

A critical appraisal of the social entrepreneurship paradigm in an international setting: a proposed conceptual framework.

Avoid common mistakes on your manuscript.

1 Introduction

Global efforts to eliminate poverty by 2030 under the United Nations Sustainable Development Goals [ 1 ] have been mitigated by increases in armed conflict, climate change, and the emergence of the COVID19 pandemic during 2020 [ 2 ]. It was estimated that an additional 100 million people may fall into poverty during 2020 due to COVID19 and a further 132 million by 2030 because of climate change [ 2 ]. However, prior to the pandemic, the rate of poverty reduction had slowed, and the World Bank [ 2 ] observed that Sub-Saharan Africa (S-SA) was a major contributor to this slowing. The number of people falling below the extreme poverty line of US$1.90 per day was increasing because of population growth in the region [ 2 ].

While there are differing approaches to forecasting poverty rates, there is a consensus that the elimination of poverty in S-SA Africa by 2030 is not achievable [ 2 , 3 , 4 , 5 ]. Lakner et al. [ 3 ] studied the relative impact of economic growth and inequality on poverty projections from 2019 to 2030. They concluded that a 1% decrease in Gini for each country reduced poverty by more than a 1% increase in GDP did. Economic inequalities across S-SA are high in comparison to other global regions and economic growth in isolation will not lower poverty [ 6 ]. Remedies to reduce inequality include the creation of better paid jobs, property ownership, removal of gender inequality, and the redistributions of taxes to improve schools and health services [ 3 ]. The nature of economic development varies across the region and the effects of foreign aid programs (FAP), foreign direct investment (FDI), and trade do not necessarily result in a reduction of poverty [ 7 ]. FDI in industries, such as mining, the banking sector, and telecommunications may not result in broad transformational change for the region [ 7 , 8 , 9 ]. Further, FDI and FAPs may operate in weak institutional environments and the impact on poverty may not be readily accounted for [ 8 ]. Anetor et al. [ 7 ] observed a positive, but inconsistent, correlation between trade and poverty reduction across the region.

Small medium enterprises (SMEs) have the potential to create many jobs over diverse sectors with greater geographic diversity [ 10 , 11 , 12 ]. However, there are challenges to the success of SMEs including lack of funding, poor management, skills deficits, absence of mentoring, inadequate infrastructure, and low demand for locally produced products and services [ 10 , 12 , 13 , 14 , 15 ]. Corruption is also a significant factor in the operational structure and performance of SMEs in S-SA [ 16 , 17 ]. Microfinance has played a role in the elevation of people out of poverty but there is limited evidence that it leads to the sustainability of SMEs [ 18 ]. The success of SMEs is highly dependent on skill levels and innovations of the entrepreneurs, and technology adoption [ 19 ]. While 65% of university graduates across S-SA are unemployed [ 20 ], the propensity for innovation and technology adoption is low [ 20 ]. Technology transfers have great potential to alleviate poverty despite not living up to full potential [ 21 ]. The issues surrounding failures to fully capitalize on the transferred technology relate to the process of the transfer, local support issues, poor “socio-cultural entrenchment,” and lack of adequate marketing strategies [ 21 ]. However, viable local business strategies may be established when drawing upon the immense body of intellectual capital available in Africa [ 20 ]. It is feasible to establish innovation or technology clusters that are linked and can share resources through collaborative networks to collectively develop locally and regionally relevant products from the core technology [ 22 , 23 ]. This initiative is replicable, generalizable, and offers great potential for community-led programs for sustainability and poverty alleviation. Sashi [ 24 ] proposes the encapsulation of microfinance with strategic and market advice to allow entrepreneurs to make and sell products. This is an income enhancing activity and aligns with technology transfer programs [ 21 , 22 ] and export-led initiatives [ 16 , 22 , 25 ].

Urquhart et al. [ 26 ] contend that while information and communications technology (ICT) may help to alleviate poverty, just how this can be done has yet to be fully developed. Urquhart et al. [ 26 ] frame social capital and knowledge within information technology to conceptualize interventions for poverty reduction. This framework suggests what Peffers et al. [ 27 ] describe as a systematic and iterative approach to the development of artifacts to address a problem, in this case poverty alleviation. However, viable theoretical constructs have not emerged to define a way forward for sustainable development programs for poverty reduction [ 26 , 28 , 29 , 30 ]. Diga et al. [ 31 ] state that ICT policy interventions in Africa promote a techno-centric approach that places emphasis on economic outcomes and neglects other aspects of wellbeing, and they call for a more “contested, discursive policy environment.” Access to information then becomes essential for any meaningful public policy discourse. The dissemination of information is recursive within the ICT framework through different levels of media (radio, television, and social media) to inform and engage the community in such discourse. Gebremichael and Jackson [ 32 ] introduce the concept of “information poverty” to add to the complex nature of poverty and to identify a digital divide that is emerging as a delineator of poverty.

Laudon and Traver [ 33 ] define e-commerce as “digitally enabled transactions” for the purposes of transferring value and that e-commerce is part of a broader e-business definition that also includes transactions where no value is exchanged. E-commerce conjures thoughts of exchanges over the Internet, but this is not necessarily the case. Khavul and Bruton [ 28 ] describe how telecommunications and mobile payments have reduced transaction costs in making and receiving payments.

The focus of this systematic literature review (SLR) is to inform formal research into the roles of e-commerce, innovation, entrepreneurship, and collaboration in the development of sustainable models for community-led initiatives for poverty alleviation. This objective is encapsulated in the following research questions:

Research Question 1 — Does electronic commerce provide pathways for sustainable development of low-income communities to alleviate poverty in Sub-Saharan Africa?

Research Question 2 — What roles do entrepreneurship and innovation play in sustainable development in low-income communities in Sub-Saharan Africa?

Research Question 3 — Does social media help guide sustainable development in low-income communities in Sub-Saharan Africa?

The significance of this research is in the development of a systematic approach to SME development in S-SA. SMEs hold the best hope for widespread economic, social, and environmental programs. These programs require a readily deployable financial, intellectual, legal, and technological framework within which local innovation and entrepreneurship can flourish. Each program can generate continuous real-time data to inform policy makers and investors on the progress of each SME, with measures of the impact on social wellbeing of the communities they serve. The significance of this research also lies in the idea that the digital divide can be closed through the actions of these communities rather than rely on the push strategies of government policies. Another benefit is that these communities become enumeration areas that are continuously reporting household information and obviate the need for expensive census and survey data collection in the future.

This SLR draws upon information systems research to propose a new approach to SME development that engages with regional, national, and global economies through e-commerce. This platform is inherently computational and data intensive. Hence, the contribution to theory arises out of data analytics and the real-time insights into generalizability of sustainable development programs and the wellbeing of all communities, not just poor communities. This SLR follows the guidelines prescribed by PRISMA 2020 [ 34 ]. Accordingly, the following sections cover methodology, search, results, discussion of results and contributions, conclusions, and future research.

2 Methodology

The search for relevant articles was framed within the search process illustrated in Fig.  1 . An iterative process is used to optimize the database search criteria to obtain a comprehensive collection of the most relevant and credible research articles. Articles are systematically recovered from the research repositories, each within proprietary query definitions. The combination of the bibliographic capabilities of EndNote and the textual analysis capabilities of NVivo facilitate meta-analysis and good record keeping at each iteration. Multiple tools, including Excel, Tableau, and custom code may be used for the visualization of the search outcomes depending on requirements. Excel is the main tool used in this SLR for visualizing search outcomes.

Search Process

2.1 Search words and phrases

This SLR aligns with the terminology used in the United Nations Sustainable Development Goals [ 1 ]. While the terminology used by the United Nations is well-defined, observations in the professional literature indicate ambiguity. The following discussion addresses this ambiguity so that the search outcomes more precisely align with the research questions.

Poverty . Haughton and Khandker [ 35 ] define poverty in terms of wellbeing, inequality, and vulnerability. Wellbeing is expressed as levels for consumption of commodities, health, education, freedom, self-esteem, access to services, and transport above which a person, family, or a community can equitably function in the broader society. Inequality measures the distribution of incomes across the population as shown by the Gini Index (GNI). Vulnerability is the “risk of falling into poverty.” The people in this group are vulnerable to a significant event that may erode or eliminate their income earning potential. Poverty is multi-dimensional, difficult to define, and it varies across regions, and across countries. It is not to be confused with standard-of-living which is a broader measure usually related to per capita income and is subject to interpretation against measures of inequality [ 35 ]. However, poverty is more simply stated as the ability to purchase commodities [ 35 ] and is quantified as $1.90 per day for workers and their families [ 36 ].

Sub-Saharan Africa. This is the list of countries in Africa defined by the Library of Congress [ 37 ] that lay south of the Sahara Desert. This SLR is focused on this list of countries, but broader areas of research that are applicable to this region may simply refer to developing countries .

Sustainable development and sustainability. Waas et al. [ 38 ] note that these terms are often used interchangeably. They also observed that research scholars often associated sustainable development with economic growth while sustainability also embraces social and environmental issues. Sustainable development is a process through which sustainability can be achieved [ 38 ]. Di Fabio [ 39 ] state that sustainability creates a balance between current and future aims [ 39 ], and hence is an outcome of sustainable development. Sustainability reflects resilience while maintaining dynamism for changing social needs. Because of the lack of consensus on the definitions for sustainable development and sustainability these terms are used interchangeably in the search for research articles. Otherwise, in this SLR, where the context permits, sustainable development refers to all actions and outcomes of initiatives that successfully transition to sustainability.

Information and communications technology or information and communications and technology. ICT, ICTs, or IT are terms commonly used to describe structural (such as telecommunications networks, data centers, Internet, and the Web), operational, and transactional aspects of information systems [ 40 ].

E-commerce or ecommerce or electronic commerce . These terms relate to “digitally enabled transactions” for the purposes of transferring value [ 33 ]. E-commerce falls under the umbrella of ICT and in this SLR both terms are used to search for the presence of electronic processing. In this SLR, e-commerce, where the context permits, refers to electronic commerce, ecommerce, or ICT.

Innovation. Refers to the propensity for solutions that improve wellbeing. The objective is to discover research that illuminates innovative solutions for potential generalization geographically and culturally. Innovation is usually a product of entrepreneurship and in this SLR a search for innovation may reveal entrepreneurship and vice versa.

Social media. Social media is the substrate for the delivery of a wide range of information and communication services including social networking and the formation of special interest groups. The detection of the presence of social media may be indicative of collaboration, cooperatives, and working groups in sustainable development projects within communities and between communities. The absence of social media may be indicative of a digital divide and the lack of reach of ICT infrastructure and services to low-income communities.

These terms inform the construction of the key words and phrases used in the following search process. The objective is to search for articles that relate to research on poverty (or low-income) in Sub-Saharan Africa (or developing countries, or any Sub-Saharan African country) that accord with the concepts of sustainability (or sustainable development). The outcomes of this meta-search can then be searched for the specific requirements of the research questions.

2.2 Search process

Online databases, including Scopus, Proquest, Web of Science, ScienceDirect, and Sage, were investigated systematically with trial searches. Scopus and Proquest consistently yielded the most articles across all research questions. The search inclusion criteria required articles to be peer reviewed, published in journals or conference proceedings, English language, and published during or after 2000.

Figure  2 illustrates the hierarchy of the searches. Four queries were made on each of the Scopus and Proquest databases. Query 1 established the set of articles from which articles for each research question were drawn. Queries 2, 3, and 4 extract articles that do not have a requirement of sustainability or sustainable development in the search criteria. These queries are used only to highlight the differences between the respective outcomes from Query 1.

Search Structure

Table 1 shows the Boolean structure for each of the four queries referred to in Fig.  2 . The mandatory inclusive search terms are shown horizontally (AND operator) with search word options shown vertically (OR operator).

This search process was applied systematically to the selected databases to recover articles that are relevant to the research questions. However, there are limitations that may have a material impact on the outcomes, these are discussed as follows.

2.3 Limitations of the methodology

This SLR seeks to discover research literature on the roles of e-commerce, innovation, entrepreneurship, and social media in S-SA within the constraints of poverty or low-income, and sustainability or sustainable development. This is a narrow perspective that may preclude significant current activities in sustainable development. The databases chosen for the recovery of research articles were chosen purposively. Other databases may have contained publications that may have captured additional perspectives on the research questions. The searches were limited to peer-reviewed articles presented for publication in journals or in conference proceedings. This excludes research notes, book chapters, institutional reports (World Bank, International Monetary Fund, Organization of Economic Cooperation and Development, United Nations, National Statistics Offices), dissertations, aid agency reports, and reports by various government and private sector organizations. The term e-commerce is widely used in business and information systems contexts but is not necessarily a term that is widely used by consumers. Further, the research community is more likely to use a general term such as ICT without targeting e-commerce specifically. ICT discovers everything related to information, communication, and technology. E-commerce may be buried in terms like sales, purchases, merchant payments, or mobile money, and they may not be discoverable under the methodology of this SLR [ 41 ]. The following summarizes the results of the searches and lists relevant articles for each of the research questions.

3 Search results

The literature search was conducted in two phases. The first phase searched the Scopus and Proquest databases with Queries 1—4 structured in accordance with Table 1 . Table 2 records the number of research articles returned for each query on each database. Eight files were created in readiness for uploading to Endnote.

The second phase of the literature search involved the uploading of the 8 query files from the first phase to Endnote to create 4 consolidated library files as shown in Table 2 . The Endnote upload and consolidation process eliminated many duplicates. The consolidated Query 1 library in EndNote was then searched using the queries shown in Table 3 and by manual selection to eliminate any undetected duplicates and off-topic articles. EndNote also searches for the PDF of the full text for each article and attaches it to the article record in Endnote. This was not always successful, and the remaining PDFs were extracted manually from the journals. The results of Queries 2, 3, and 4 are included in Table 3 to highlight the restriction of adding sustainability of sustainable development in the Query 1 search criteria.

The Table 3 Query 1 articles with attached PDFs for each research question were uploaded to NVivo for further analysis. NVivo was used to study the prevalence of the Table 3 search words in each article and to eliminate any articles that did not contribute appreciably to the research questions. Appendix A Tables 6 , 7 , 8 list the articles returned from the Table 3 Query 1 searches and refined using NVivo. The Query 1 consolidated library was also searched with keywords such as agent-based, big data, data analytics, socio-technical, machine learning, artificial intelligence, and design science research to retrieve any research articles on potential theoretical and evidence-based frameworks supporting the research questions. The results of these queries are shown in Appendix A Table 9 . The following is an assessment of the quality of these articles in terms of their potential contribution to the research questions.

4 Assessment

Each of the files for the research questions were analyzed using NVivo. The purpose of this step was to provide a very high-level assessment of the frequency of occurrences and contextual significance of the search words and phrases in the articles to give a broad view of the quality and relevance of their content to the research questions. Other textual searches were performed to test for the presence of omitted relevant keywords/phrases. Figure  3 summarizes the search results across all articles for all research questions across. As an example, Fig.  3 shows there were a total of 948 occurrences of the search word innovation in a total of 19 articles. The keywords/phrases for Research Question 1 are not well represented. 183 references to ICTs appeared in a total of 8 articles of which only 4 were selected for review. This may indicate a research gap or the presence of a lack of access to the Internet in low-income communities. There are almost zero references to electronic commerce, ecommerce, or e-commerce, the primary focus of Research Question 1.

Distribution of Search Words/Phrases in All Research Articles

The sources of the articles were examined for diversity. Were articles drawn from a narrow journalistic point of view, and are the journals credible? Appendix B Table 1 lists 19 journals and 3 conference proceedings from which the final list of 23 articles were recovered. The chronology of the final set of articles shown in Fig.  4 indicates only a moderate interest in this research area over the past decade. There is considerable diversity in the sources of articles. The reasons for this were not researched. The proliferation of journals is taken as a positive indicator of intellectual diversity but there is a potential research gap in the literature within the search criteria. The impact factors were not available for all journals and no conclusions were reached under any merit classification.

Year of Publishing of All Articles

The literature search process was sensitive to any evidence of structural form and organizational management of poverty alleviation initiatives. Such structures are a necessary precursor to the implementation of e-commerce strategies and to the collection and dissemination of information on the social, economic, and environmental outcomes of the initiatives. There is no current systematic approach to sustainable development for poverty alleviation in S-SA [ 26 , 28 , 29 , 30 ]. The following discussion identifies broad structural issues across S-SA with examples of initiatives to address aspects of these structural deficiencies. There is an absence of a coordinated effort to develop cross-border trade and community-wide sustainable programs for the region.

5.1 Research question 1

Appendix A Table 6 lists 4 articles that discuss poverty, sustainable development, and ICT in a variety of contexts that address Research Question 1. ICT related topics in these articles covered areas such as information/knowledge/education, infrastructure, Internet accessibility, and social networks. However, apart from acknowledging that poverty was a serious problem facing millions of people and that ICT could play a pivotal role in its alleviation, the results did not form a consensus on a systematic approach to how ICT could be effectively deployed to meet this challenge. Further, Appendix A Fig.  9 highlights the almost complete absence of e-commerce from the research discourse. ICTs include numerous manifestations of information and communications technologies and systems. ICTs are often referred to as a top-down paradigm driven by policy initiatives to extend reach into society. It is the boundary of this reach that is often referred to as the digital divide. For ICTs to be relevant to sustainable development they must be transactional as well as informational. Each of these presents additional “divides.” Negash [ 42 ] introduce the concepts of the information divide which denies access to relevant information, the skills divide which relates to learning, and the economic divide which limits employment and business development.

How can information motivate innovation and entrepreneurship in communities that are profoundly poor, and survival is a daily struggle? How can the transactional capability lead to a more sustainable existence? Access to the bewildering world behind an Internet connection is not osmotic for these communities. In a domestication of ICT study in urban slums in Nairobi, Kenya, Wamuyu [ 43 ] learned that few households had access the Internet. To connect to the Internet a computer or smart phone or other mobility device is required, and there must be an affordable public Internet access point. The most common Internet access point for low-income communities is the mobile telephone service. Other Internet access points are combinations of shared and dedicated wireless and cable connected services, but these need substantial physical infrastructure within the service area. Even if access to the public Internet service is free, a computer or smartphone may not be affordable. Further, the lack of ICT skills and digital literacy will limit the usefulness of Internet access. Wamuyu [ 43 ] also noted that many children from low-income areas attended schools without Internet access. Michael-Onuoha et al. [ 44 ] contend that libraries can provide a range of services including ICT skills development, mobile information services, consulting, and agricultural information services to contribute to sustainable development and poverty alleviation. Negash [ 42 ] also approaches ICT in sustainable development of low-income communities from an educational perspective. However, no insights were gained into any sustainable development programs within urban low-income areas that utilized e-commerce or any other Internet service driving economic development.

Skuse and Cousins [ 45 ] similarly discuss the cost of access to telecommunications services in a low-income rural area in South Africa. Rural areas have various levels of coverage and there are provisions for communities to build and operate their own local networks. Skuse and Cousins [ 45 ] observed that the cost of access and the inability of poor people to participate in small telecommunications enterprises may worsen the poverty crisis. The cost of access and the use of the Internet as a service is beyond the reach of the rural poor in most instances. There are exceptions if they receive remittances from family members who have migrated to urban areas [ 45 ]. Skuse and Cousins [ 45 ] suggest welfare payments to lift qualifying households out of poverty and briefly refer to initiatives under the sustainable livelihoods approach (SLA) [ 46 ]; but there was no mention of any substantive poverty alleviation initiatives where ICTs were an enabler of economic development. An informal review of more contemporary literature and media reports since 2007 indicates that rural telecommunications coverage and Internet access in South Africa is still problematic.

5.2 Research question 2

Appendix A Table 7 lists 16 articles on entrepreneurship and innovation that address Research Question 2. These articles cover a diverse range of subject matter summarized in Table 4 . The articles offer insights to the importance of innovation at a local level and provide examples of projects that appear to have been successful. Appendix A Fig.  10 shows the distribution of the search words and phrases in this reference set.

Research Question 2 was framed around the thinking that community-led entrepreneurial innovations may lead to sustainability and empowerment. Abisuga-Oyekunle et al. [ 10 ] investigated whether SMEs are a good strategy for widespread job creation. They concluded that, despite structural problems, including access to electricity, difficult establishment procedures, long business development cycles, and limited funding, SMEs can contribute to developmental change in S-SA. Abisuga-Oyekunle et al. [ 10 ] note that SMEs are better positioned to take advantage of local capacity, are not so capital intensive, create more jobs, and promote independence with local decision making. However, the lack of access to equity and debt financing for SMEs is a major impediment to growth and many SMEs fail in the early stages. They also state that the diversity of SMEs in different market sectors can potentially withstand competition from larger international entities. This requires a high level of integration and collaboration among countries in S-SA where the lack of public infrastructure, different trade rules, the lack of a uniform stable currency, and other factors present significant operational and transactional difficulties [ 10 ].

One such integrative effort was the introduction of the “Organisation pour l'harmonisation en Afrique du droit des affaires" (OHADA), a western style legal framework that was introduced in West and Central Africa following the financial collapse of the CFA currency in 1993. It was meant to facilitate a consistent regional investment environment in West and Central Africa and to attract foreign investment [ 47 ]. OHADA purports to provide a uniform legal environment promoting regional integration and development but it has only been adopted by francophone countries. English-speaking countries in the region (Ghana, Nigeria, Sierra Leone, and Liberia) preferred common law [ 47 ]. The imposition of OHADA may not be optimum for local business environments because there are significant gaps between the official law and the practices of local firms in the region [ 47 ]. The laws should be changed to allow for the more efficient conduct of micro, small, and medium enterprises in low-income communities and the needs of sustainable development initiatives for poverty alleviation [ 47 ]. Hence, a cultural boundary limiting legal integration and a uniform approach to sustainable development is still heavily influenced by colonialism at a time when the African Union is actively engaged in the removal of colonial footprints from the African continent [ 48 ]. Several regional efforts including the Economic Community of West African States (ECOWAS), the Economic Community of Central African States (ECCAS), the East African Community (EAC), the South African Development Community (SADC), and other market and inter-government bodies have been formed to address integration issues. The African Union aims for greater unity and cooperation between its 55 member states [ 48 ].

Abisuga-Oyekunle et al. [ 10 ] also comment on problems confronting policy decisions on poverty alleviation because of a lack of reliable household data. Regime instability, corruption, insufficient capacity, and inadequate public infrastructure exacerbates access to reliable and current data. Reliable Internet services make data collection much easier than traditional survey processes. Self-reporting, automated reporting, remote sensing, and other techniques can provide large volumes of data with near real-time analysis and reporting.

Abisuga-Oyekunle et al. [ 10 ] undertook an analysis of World Bank statistics on innovation and technology use in 27 S-SA countries. Figure  5 presents a summary of this analysis. Of the firms surveyed across the 27 S-SA countries within the 2013–2017 survey period, only 15.86% were engaged in research and development (R&D) and only 36.73% had developed an innovative process. 42.47% of firms surveyed had introduced a new product or service and 72.35% of which were new market entrants with the new product. Only 29.6% of the firms surveyed had a website and 57.93% communicated with customers using email. While this survey used data from the period 2013–2017, the presence of e-commerce in market valuable transactions appears minimal.

Summary of Percentage of S-SA Firms Engagement in Innovation and Technology

Sustainability enhancing innovations can be instrumental in resolving poverty and its environmental impacts [ 28 ]. A key factor in the assimilation of innovations into communities is influenced by the extent of social networks and business ecosystems, the internal hierarchy of networks, and other internal and external ties [ 28 ]. Kaplinsky et al. [ 49 ] observed that research and development activities in low-income countries have not resulted in innovative products and services for “bottom of the pyramid” markets. Innovations must be designed and marketed to address the specific requirements of these communities, and that a one-design-fits-all approach is unlikely to get significant traction [ 28 , 50 ]. In developing countries, the tendency is to assume a homogeneous need across the low-income spectrum. However, low-income markets share the same heterogeneity characteristics as developed markets and for products to be accepted by consumers, corporations need to undertake similar levels of market research and adjust their business practices, product configurations, and marketing strategies accordingly [ 28 ]. Khavul and Bruton [ 28 ] draw upon three examples to illustrate this claim: (1) fuel efficient stoves, (2) safe drinking water, and (3) electricity. While each of these examples had obvious benefit for consumers, the uptake was not what was hoped for, primarily because the there was a lack of understanding of the nuances of the market. Poverty in developing countries is an intrinsic part of the markets, and corporations expecting to enter these markets must engage at multiple levels [ 28 ]. Kaplinsky et al. [ 49 ] contend that innovation in emerging countries such as India and China can lead to products for markets in low-income countries that are less expensive, easier to use, and require less supportive infrastructure. This is supported by the appearance of inexpensive and often low-quality products from India and China in low-income countries [ 50 ]. Researchers and business managers need to reach into behavioral science to gain further insights into decision processes within these communities, and to address “deeply entrenched behavior” [ 28 ].

Innovations that are generalizable across S-SA are the main interest of this research. One such example is the mobile payments service introduced in Kenya in [ 28 ]. Mobile payments are now widespread across S-SA [ 51 ] and have been adopted in India [ 52 ]. Digital banking enables the settlement of payments via mobile phones over telecommunication networks. This is the simplest and most readily available e-commerce capability. Consumers can settle payments with merchants and transfer funds between family and colleagues at lower costs, especially for low value transactions. Bongomin et al. [ 53 ], while not addressing poverty, concluded there was a “positive relationship between mobile money usage and financial inclusion”, and the importance of social networks on this relationship in Uganda.

Other innovations in S-SA are hard to find. The following examples are dependent on policy initiatives for small business and funding from various sources. They also lack structural support (research and development, management, advocacy, and market positioning) to transition innovations into sustainability. Matthews et al. [ 54 ] provide an example of an innovation that they claim could create millions of jobs for Africans, reduce crime rates, use renewable energy, and “save the planet”. A solar-powered roadside vulcanizing machine (air compressor) is proposed. This is an ambitious goal reflective of the poor state of roads across S-SA and the low level of roadworthiness of vehicles. van Welie et al. [ 55 ] use ideas within socio-technical transition theory to examine how sanitation services in Kenya can be established as viable small businesses and their transition to sustainability. They used a systematic approach to identify segments in the value chain including collection and conveyance, processing, and disposal. While acknowledging innovations in the treatment segment with economically viable products such as animal fertilizer and biogas, the provision of well-maintained non-sewered sanitation services is undeveloped and requires innovation to complete a viable value chain [ 55 ]. There are backlogs and delays in providing affordable low-income housing in South Africa [ 56 ]. Innovative lean construction techniques can eliminate time wastage and improve profits compared with conventional construction [ 56 ]. A lean construction framework incorporating innovative financing, construction, subsidies, and institutional arrangements to address the chronic shortage of housing in South Africa is proposed [ 56 ]. This framework can lead to the development of a housing sector with skills and technological development [ 56 ]. Michael-Onuoha et al. [ 44 ] believes that libraries in Nigeria can contribute to sustainable development and poverty alleviation. The libraries can provide a range of services including ICT skills development, mobile information services, consulting, and agricultural information services. Economic growth in low-income countries can lead to the demand for new products and services and multi-national enterprises (MNEs) who contribute to the development of these markets will reap large benefits [ 49 ]. Ramos-Mejia et al. [ 57 ] attempt to place sustainable development initiatives for poverty alleviation into a framework that can then be examined under socio-technical transition theory (STTT). They discuss the challenges confronting the sustainability of poverty alleviating innovations in low-income countries where supportive political and commercial infrastructure may be weak or non-existent and offer suggestions for future research. To highlight these challenges, Okon [ 58 ] observed the outcomes of two initiatives in the Niger delta region in Nigeria. Two successive programs aimed to empower women and to educate and train youth in vocational skills failed because there was no diffusion of innovation. According to Okon [ 58 ] these failures suffered from top-down imperatives rather than a lateral engagement of the beneficiaries in the objectives, conduct, and outcomes of the programs.

Policies that create an environment for technology initiatives to thrive can be the catalyst to attract foreign venture capital [ 59 ]. Foreign venture capital investments can build local competencies and foster sustainable innovations much faster than other forms of funding [ 59 ]. Venture capital investors bring technical, management and marketing competencies to product development for local and potentially global markets [ 59 ]. However, the experiences with microfinance have been less encouraging. Arp et al. [ 18 ] undertook two studies to investigate the performance of formal microfinance, informal moneylenders, and trade finance. These studies were driven by the debate over the effectiveness of microfinance in terms of the impact on poverty and sustainability under the United Nations Sustainable Development Goals. Their findings concluded that microfinance does not result in sustainability for borrowers in low-income communities. The administrative processes for formal lending, despite lower interest rates, were a deterrent to borrowers whereas the ease of borrowing from moneylenders, despite increased costs, was more attractive. Alternatively, trade finance had the perception of being interest free because cash was not directly involved. Equipment, fertilizer, and seeds were exchanged for offtake arrangements for the farm output [ 18 ]. Trade financiers also became more integrated with rural communities and were able to contribute advice and other support and were more trusted than formal or informal moneylenders [ 18 ]. In this context, trade financiers perform a similar role as venture capitalist, albeit at a local level and rarely to stimulate innovation [ 18 ]. Tanzanian women were met with new experiences of prejudice and inequality when applying for and managing microcredit [ 60 ]. Many were able to cope with the “oppressive” burdens of repayment regimes, but others were trapped in a cycle of working and repayments, and not advancing to the level of self-determination [ 60 ].

Social entrepreneurship is a combination of people, resources, and innovation that may be directed to solving social problems including poverty alleviation [ 61 ]. Social entrepreneurs are leaders in their community. They marshal resources and take actions for the benefit of the community. Foy Connor and Bent-Goodley [ 61 ] discuss the role of women entrepreneurs working to address educational needs of women and girls in low-income communities, to empower people with disabilities, and to develop ways for women to become engaged in income-earning activities. Foy Connor and Bent-Goodley [ 61 ] acknowledge that this type of entrepreneurship is not generalizable, but when combined with other initiatives the social entrepreneur can play an important role in sustainable development. There are complex qualitative issues surrounding women in entrepreneurial roles [ 60 ]. The process of self-determination and elevation as business owners creates tensions with their traditional roles of subservient inequality. Women dealt with this through discussion and renegotiation of their relationship contracts or through compartmentalization of their entrepreneurial life from their traditional life [ 60 ].

Corporate social responsibility (CSR) may contribute to economic development in low-income communities [ 62 ]. Corporations may integrate local participation in areas such as manufacturing and distribution into their core business strategy, rather than taking a philanthropic approach to the poor [ 62 ]. Philanthropy is counter to corporate profits whereas business strategies that contribute financial benefits from engaging local capital and resources may have a direct impact on profits. Bai and McMartin [ 62 ] briefly discuss how social impact credits could be earned through the alignment of business strategies with social need, albeit with accountability challenges.

5.3 Research question 3

Appendix A Table 8 lists 3 articles on social media, social networks, and collaboration for Research Question 3. This research question was formulated on the premise that for community-led businesses to create generalizable sustainability models, collaborative networks providing access to a wide range of resources and advocacy services were essential. Social media with a large inventory of applications and services for collaboration, sharing of problems and ideas, socialization, commerce, and a say in the shaping of communities and the broader society. There is limited evidence in the formal research of the systemic use of social and collaborative networks in sustainability initiatives in S-SA. Appendix A Fig.  11 shows the distribution of search words and phrases in this reference set.

Reed [ 63 ] focuses on the poverty-environment-sustainable development nexus. Reed [ 63 ] believes that global corporatization has exacerbated protections for the environment and has accelerated the clearing of forests for other pursuits. Reed [ 63 ] states that, among other institutional reforms for environmental sustainability in low-income countries, poor communities should be granted more control over natural resources and the environment. This can only be achieved through greater collaboration between all stakeholders with civil society having a greater voice in the outcomes.

Brown et al. [ 64 ] observed a successful example of collaboration in Ethiopia between the Humbo community, government and non-government organizations, and external participants bringing advice and money to a reforestation project. The Humbo project was inspired out of the 1984 famine in Ethiopia which drew attention to the almost complete degradation of the Ethiopian forests and the resulting devastation of the communities that relied upon them [ 64 ]. The project directly engaged with the communities through the establishment of cooperatives to manage revenues earned from carbon credits. The cooperatives are responsible for the development of community assets such as grain milling and other agribusiness projects [ 64 ]. According to World Vision Australia, one of the project’s sponsors, the project has been a huge success in generating income through the sale of carbon credits to the World Bank, the sequestration of carbon, and investment in local infrastructure [ 65 ].

Capability enhancement at the community level is essential for any gains in poverty alleviation [ 66 ]. Capability deprivation refers to the inability to effect changes to enhance the wellbeing of the community because of lack of social support, illiteracy, basic education, health care systems, and real property [ 66 ]. Mabogunje [ 66 ] describes a project which commenced in the Nigerian city of Ijebu-Ode in 1998. The objective of this project was to address capability deprivation to guide initiatives for poverty alleviation. The project used a consultative process to engage the whole community in the design and implementation of the poverty alleviation plan. This lateral approach helped to coalesce local knowledge, to identify skills, and to stimulate innovation. Mabogunje [ 66 ] states that after 7 years employment increased, poverty reduced, skill levels improved, and cooperatives had been established in agribusiness. However, the program required considerable financial support from government programs, microfinance, and project management. Therefore, the question of sustainability could not be answered. Mabogunje [ 66 ] also state that micro-finance was management intensive and could not singularly reduce poverty. Default rates had grown significantly. Other issues related to accountability of the cooperatives that had been formed, and there was limited capacity to access further funds for growth [ 66 ]. The project is still in operation ( https://www.idipr.org.ng/ ).

The next section discusses ideas for the development of a formal structure for SMEs to provide a consistent organizational framework for diverse initiatives that can be generalized across spatial, demographic, and cultural domains. This framework is intrinsically computational and forms the basis of a data-driven approach to social, economic, and environmental sustainability.

6 Potential SME framework

This SLR did not directly reveal any significant recognition of the role of e-commerce in sustainable development of low-income communities in S-SA. The importance of ICT is acknowledged but e-commerce as a sub-element of ICT does not gain any prominence. There is a sense that ICTs are a policy push concept that is further illustrated by the existence of the digital divide. The digital divide separates households and SMEs in low-income communities from the informational and transactional capabilities of the Internet. Innovation and entrepreneurial initiatives arise from observing role models and the proliferation of ideas of others. The digital divide creates a chasm that puts this out of reach. This chasm can be narrowed if there is a contemporaneous “pull” strategy from within the low-income communities. However, there is an absence of formal research into theories and practical strategies that may be applied to gain widespread proliferation of sustainability innovations across the low-income spectrum [ 28 , 67 ]. The organizational structures within communities have not been developed to stimulate outreach, to foster innovation and entrepreneurship, or to embrace technology. Further, there is an absence of formal discussion on the importance of collaborative networks that can contribute to the sharing of ideas, joint marketing initiatives including brand development, and the transactional benefits of e-commerce. The theory and its practical derivations must transcend spatial, demographic, and cultural boundaries for universal application. Low-income communities have unique social structures that need to be understood and incorporated into sustainable development initiatives [ 28 ].

There are research opportunities engaging socio-technical transition theory [ 57 ], complexity theory with agent-based modelling [ 68 ], design science research [ 27 ], and other management and organizational theories to create frameworks for sustainability transitions from poverty to empowerment [ 69 ]. There are also several emerging data analytics and machine learning techniques that may also be useful [ 70 , 71 , 72 ] for progress monitoring and forecasting. The following discussion draws upon research articles referred to in Appendix A Tables 6 , 7 , 8 , 9 , additional articles from the Query 2, Query 3, and Query 4 searches (Fig.  2 ), and other research articles. A brief synopsis of a potential SME framework follows.

6.1 Socio-technical transition theory

The multi-level perspective (MLP) of STTT (Geels) [ 73 ] may be used to illustrate sustainable development and sustainability transitions for poverty alleviation [ 57 ]. The MLP is defined at three levels as depicted in Fig.  6 .

Landscape—this level embodies the social, political, demographic, and cultural dimensions of influence in a region or country.

Regime—this level is where incumbent sustainable systems reside. It is characterized by the regulatory environment, politics, business, advocacy (lobby, industry associations) groups, and the infrastructure of society.

Niche—this is where technical innovations or sustainable developments are conceived, grow, and strive to transition to sustainability at the regime level.

Multiple-Level Perspectives of STTT for Poverty Alleviation

The literature on STTT provides analytical accounts of technological transitions with explanations of how various technological innovations merged to force regime change [ 57 ]. One example is the impact of renewable energy systems (solar and wind) on fossil fuel power generation systems. However, Ramos-Mejia et al. [ 57 ] noted challenges in applying STTT to poverty alleviation in developing countries where there is often a lack of institutional support and where complex social structures prevail. The landscape has a mix of characteristics including security, social structures, and political integrity which differentiate it from that of developed countries [ 57 ]. Similarly, socio-technical regimes also suffer from uncertainty of industry structures (formal private and government firms, and informal entities), the absence of protective laws, and corruption [ 57 ]. Ramos-Mejia et al. [ 57 ] note that culture, lifestyle, rural and urban challenges, gender, and class makes it difficult to apply the MLP to sustainability transitions in developing countries and calls upon researchers to undertake further research to resolve this or to develop new frameworks.

The MLP can be used as a computational framework for the study of potential poverty alleviation strategies. This is made possible through the availability of data that more precisely describes the landscape, regime, and niche levels together with new and advanced data collection techniques enabled by the Internet, smart mobility devices, and remote sensing technologies. No country or region is perfectly homogeneous. The MLP can be used to describe and forecast conditions at a micro level, and the likelihood of community-based projects reaching sustainability in the future. The following briefly describes techniques that enhance operational management and to provide a data-intensive knowledge-based approach to increasingly improve the reliability of sustainability forecasts.

6.2 Design science research methodology

Wieringa [ 74 ] describes design science research to be an approach which first involves the conceptualization of a solution to a research question. The design of an artifact which addresses this conceptual solution can then be constructed and implemented as an experiment. The design undergoes continuous iterative evaluation and refinement until the artifact performs to a defined level of quality [ 27 ].

Table 5 illustrates an adaptation of the Peffers et al. [ 27 ] six-step design science research methodology (DSRM) to describe a theoretical and practical approach to the systematic design, development and refinement of an artifact that may be used in sustainable development projects for poverty alleviation. The DSRM artifact of Peffers et al. [ 27 ] is enhanced to include social, economic, and environmental elements to form a social construct for a community-based SME. DSRM is intrinsically computational and serves to provide structure for SME projects and can generate large volumes of data to inform management strategies to facilitate and nurture sustainable innovations. For example, research in indoor farming to mitigate climate change effects and water and land usage should proceed under a collaborative shared-knowledge approach. The DRSM is an Internet edge instantiation with full informational and transactional capabilities accessing local, regional, and global markets. It will typically include production management, business management, sales, marketing, and reporting elements.

6.3 Agent-based modelling

ABM is a theory that applies studies of interactions at the relational level within social groups or networks (agents) to predict their impact on higher level systems [ 75 ] (pathways to sustainability). ABM has potential application in modelling trajectories for sustainable development projects and their likelihood of attaining sustainability. ABM recognizes a physical agent (person, social group, object, community) or a conceptual agent (contract, poverty measure) to represent sustainable development initiatives across complex multiple spatial, demographic, and cultural dimensions.

Figure  7 is an illustration of the ABM concepts within which collaborating agents interact and align towards sustainability.

ABM and Sustainability Transitions

There are challenges to the selection of an agent in low-income community sustainable development. Well-defined communities of households (say 150) could be selected as agents. However, Khavul and Bruton [ 28 ] draw attention to the importance of understanding the nature of the social structures within community groups to determine how receptive individuals within the community are to new innovations or products. They observed that the fabric of social networks is maintained through strong family ties, external connections, and the attitudes of local leaders [ 28 ]. This implies a level of homogeneity that may not exist in other communities. The homogenous nature of communities could lead to widespread acceptance of innovation or not. Macy and Willer [ 75 ] also draw upon emergence theory to suggest that homogeneity could lead to more powerful outcomes for the collective acceptance of innovation than that observed at the individual level of acceptance. However, in sustainable development for poverty alleviation, the concept of emergence is complex and is difficult to quantify as a measure of social wellbeing. Instead, an SME that contributes to the social, economic, and environmental imperatives of sustainability of the same community could be nominated as the agent. The SME would report on the number of jobs created and the total payroll, its investment in social infrastructure such as water supply and sanitation, and its investment in environmental remediation such as waste management as a proxy for social wellbeing.

The MLP/DRSM structure can support both approaches to learn more precisely how a community is developing. Data on household incomes, school attendance rates for boys and girls, health clinic visits, small business activities, frequencies of social gatherings, home ownership, transportation, and other metrics can contribute to the learned models for social wellbeing.

ABM is not that useful for single agents but can be applied to the trajectories of collectives of agents (communities) towards sustainability. Trajectories of multiple instantiations of collaborating SMEs can be modeled used rules-based ABM to provide insights into the sustainability of similar sustainable development projects leading to more informed managerial and policy decisions. Agents are “niches” for poverty alleviation and ABM provides a computational overlay that derives its inputs from the DSRM artifact and presents a near real-time view of the path to sustainability.

6.4 MLP computational model

Figure  8 depicts how the DSRM, and ABM fit within the MLP. In this diagram, each DSRM defines the methodology for the design, development, and operationalizing of the sustainable development project. ABM models the pathways to sustainability in the regime. ABM may also be useful in directing sustainability transitions into well-functioning institutions at the regime level and avoid areas of corruption, conflict, ambiguity, and insecurity, and therefore address the issues raised by Ramos-Mejia et al. [ 57 ].

Integration of DSRM and ABM into MLP

The MLP is a computational framework along with DSRM and ABM which are both inherently computational. Each niche is computational because each development project is quantifiable. The regime level can be quantified in terms of institutional support, public infrastructure, and business structures. The landscape can also be quantified in terms of human development, political transparency, national security, and the environment. The MLP can generate high volumes of data which can be combined with other data sources (remote sensing data, survey data) and be analyzed to provide near real-time visualizations of sustainable development initiatives, and to progressively improve the predictive quality of the model.

6.5 Data analytics and machine learning

Data analytics is simply the processing of data to gain useful insights to support decision making. The processing of data is straightforward, and tools range from simple spreadsheets to more sophisticated big data toolkits depending on the source, type, and volume of data. Survey data such as from census collection is static because it is a snapshot in time. Big data is characterized by volume, velocity, and variety [ 76 ]. Data is collected from a variety of sensors and often streamed at high velocity and high volume. Big data analytics can process data in near real time with predictive and prescriptive outputs, and a variety of visualizations. Blumenstock et al. [ 70 ] combined mobile phone metadata with survey data from Rwanda to predict poverty, wealth, social connections, travel patterns, and other expenditures. Njuguna and McSharry [ 71 ] successfully combined mobile phone data, night light data (illumination levels at night), and population data to predict regions of poverty. Xie et al. [ 72 ] trained a convolutional neural network (CNN) using night light data and reported poverty prediction results approaching that of survey data. Accurate census and survey data is not readily available in S-SA [ 70 , 71 , 72 ] but night light data is available from the National Oceanic and Atmospheric Administration [ 77 ].

Big data analytics and machine learning (ML) is emerging as a field of research that can contribute to the monitoring and prediction of the impacts of sustainable development initiatives on poverty alleviation. Sustainable development projects in low-income communities can be established with new methods for data collection. This data, together with remote sensing data, can provide almost real-time supervision of these projects.

7 Theoretical contributions

There is a complete absence of theory that addresses sustainable development for poverty alleviation [ 26 , 28 , 29 , 30 ]. Further, this SLR did not inform the research questions with any evidence of a systematic approach to the application of e-commerce that has so successfully inspired and catapulted small, medium, and large businesses in developed countries into global markets. In the absence of any developmental theory from which practical solutions could be derived and implemented, this SLR instead proposes an adaptation of the MLP of STTT [ 57 ] and of the DSRM [ 27 ] to establish a framework that encapsulates the social, political, and commercial environment of a country or region, and proposes a formal structure for the implementation of SMEs. The MLP of STTT has been used to explain the historical transition of multiple instantiations of a single socio-technical initiative into sustainability, and the DSRM is an information systems methodology for the systematic development of a technical artifact. For the MLP and DSRM to be useful in studying the future likelihood of any initiative becoming sustainable, it must support multiple complex social phenomena, be computational, and it must be immediately responsive to changes in the societal dynamic. The MLP/DSRM construct forms the basis for the systematic implementation of SMEs that provide support for a wide range of business support systems, including e-commerce, and contributes to originality in developmental theory for sustainable development in low-income countries.

The first part of the proposed MLP construct hypothesizes a sensitive quantitative assessment of the probability of successful transitions into sustainability of any sustainable development initiative. Each of the landscape, regime, and niche levels is assigned a probability that it can support such initiatives. A weak or corrupt political environment at the landscape level negatively impacts the probability of successful outcomes, whereas positive policy initiatives and investor support at the niche level will increase the probability of successful outcomes. The initial probabilities can be determined from any available survey data such as census data, living standards surveys, business data, remote sensing data, mobile phone metadata, weather data, health reports, education levels, and other sources. With improved data collection methods, the MLP can continuously evolve to accurately reflect regional and community environments. Location specific data such as crime rates, terrorism activities, or climate change effects on certain agribusiness initiatives can be easily incorporated. This construct is data intensive and can provide highly detailed and focused visualizations of countries, regions, and communities to inform policy decisions on poverty alleviation initiatives. This first part of the proposed construct is effectively a purposeful socio-geographic representation of the conditions that directly influence the likelihood of successful transitions to sustainability.

The niche level of the MLP is where the sustainable development initiatives are conceived and encouraged into sustainability at the regime level. At this level there are many initiatives (SMEs) operating in diverse business sectors. It is proposed that these entities be structured in accordance with the modified DSRM, with each entity providing a wide range of information that can be monitored and analyzed remotely. These SMEs are rules-constrained and must contribute measurable social, economic, and environmental benefits to its associated community. The transition to sustainability of a single SME can be observed, as can collectives of SMEs that are in the same business sector, spatial sector, or any other common dimension that can be identified for each entity. This is a highly structured approach but any niche structure that meets the required data generation requirements can also be recognized and supported under this model. The path to sustainability for communities of similar SME operations can be modeled by ABM, with directional targets for each of the pre-determined social, economic, and environmental goals being provided by ML. Each entity will report progress against the social, economic, and environmental goals, and will provide information to the ABM for directional correction and reporting purposes.

8 Managerial and policy implications

The main outcome of this SLR is confirmation that large numbers of SMEs can engage in highly diverse activities over a broader demographic [ 10 , 11 , 12 ] than larger location-centric businesses. Large commercial operations play a significant role in the overall economy, but SMEs are central to strategies for low-income community development and poverty alleviation. This implies a stronger managerial and policy focus on the development of frameworks for the systematic development of community-based SMEs that can be generalized across spatial and cultural boundaries. For SMEs to achieve success across multiple industry sectors (agribusiness, manufacturing, construction, retail, services), organizational structures must be put in place that facilitate funding, business management, job creation, marketing (including brand development), access to information (farming techniques, production quality management), and performance reporting. E-commerce enables SMEs to access regional, national, and international markets for the supply and purchase of goods and services.

For instance, in Ghana there are about 3000 small pond aquaculture businesses that collectively produce about 57,000MT of tilapia and catfish per annum [ 78 ]. There are significant management, funding, quality control, and competitive issues burdening the growth of this industry at a time when marine fisheries are declining rapidly. Hasselberg et al. [ 78 ] advocate for greater investment in the supply chains for small fisheries, and for policy makers to act to safeguard the interests of small fisheries to address the declining marine fish stocks, and to investigate seasonal availability which has a significant impact on the consumer price for fish. This requires combined private and public sector involvement and a new breed of investors that are interested in the long-term success of land-based aquaculture in Ghana.

The management implications are significant. There is the need to conduct intensive trials of the MLP/DSRM structure proposed above and to evaluate this structure with a project like the small fisheries in Ghana. This will provide valuable insights into the generalizability of small fisheries across the region. This is a construct that is a diversification of manufacturing in a time when centralized manufacturing has offered benefits of economies of scale and logistical efficiencies. However, this diversification is essential to the spatial uniformity of sustainable social, economic, and environmental benefits. The application of the MLP/DSRM structure to small farms in the cocoa sector in Ghana also holds promise, as does the remediation of vast areas of land decimated by illegal gold mining with the ecological benefits of bamboo production for sustainable housing, or to the development of indoor farming that vastly reduces water consumption, land use, and chemicals in the food chain in the face of climate change across the region.

The management of large collectives of similar industries is simplified under the highly data intensive MLP/DRSM construct. Instead of centralizing the manufacture, it allows for the centralization of the management of manufacture including production, quality control, supply chains, marketing, and payments (e-commerce). The MLP/DRSM construct can be augmented, for example, with emerging ML techniques to uniformly apply adjusted feeding regimes for all fisheries to optimize growth and product quality. The threats of disease are also mitigated with diversification. When the early onset of disease is detected, mitigation techniques can be immediately implemented to prevent the spread of the disease. This geographic diversification also supports production diversification to eliminate the seasonality effects that currently influence product availability, and in the production of different fish species. Production scheduling means that there is always a constant supply of product with minimal price variability. Quality control from the fisheries to the consumer can be assisted with block chain technology that records the certifications of all supply chain participants. In the fisheries example, the block chain allows for the immediate tracing of a defective product back to the fishery that produced it and facilitates rapid action to mitigate the spread of illness from human consumption.

From a policy perspective, initiatives to help facilitate social, economic, and environmental development can be continuously monitored and reported for their effectiveness. Such initiatives may include infrastructure (roads, energy, water, telecommunications) or more focused support for SMEs including tax incentives, grant funding, employment incentives, training programs, health, and education services.

9 Conclusions

The outcome of this literature review is the premise of each of the research questions was not well supported by the available literature and there is considerable scope for research over a wide range of social, economic, and environmental disciplines. The literature supported the need for entrepreneurship and innovation in SMEs and the development of collaborative networks, but there was no clarity on how ICT or e-commerce could be embedded into SME ecosystems. A common institutional approach is to provide structural support for ICT in terms of access to telecommunications and online government services. What is lacking is the metaphorical last mile where community projects draw upon high-performance infrastructure and thrive independently with minimal external governance other than what is required under law.

In S-SA, sustainable development projects to address poverty include agribusiness, manufacturing, construction, health, education, and other services. ICT is persuasive across all business activities in design, production, operations, and business support services such as website development (with e-commerce capabilities), marketing support, software development for special applications, mobile applications, media production, and digital production services. It would be difficult to conceive of any sustainable development program that does not extend the reach of the Internet to every business and community in developing countries, and eventually to individuals. However, while the literature was sparse in examples of successful diffusion of innovation in S-SA, mobile payments was reported as major socio-technical innovation. Mobile payment services facilitate lower cost transactions between individuals and for the payment of merchant services. Separate reports indicate this has become ubiquitous across S-SA, often exceeding bank transactions. Payment systems are an integral part of e-commerce and mobile payments will contribute to the development of low-cost methods for settling SME e-commerce transactions in S-SA.

The literature search did not reveal any systematic theoretical or practical frameworks for poverty alleviation. Socio-technical transition theory was the subject of one article but the applicability of the MLP was drawn into question because of structural problems in developing countries. However, in the presence of increased access to data and advanced data analytics techniques it is proposed that the MLP be adapted as a computational framework for the design, implementation, operations, and monitoring of sustainable development initiatives. DSRM provides structure for the SME and informs the contribution to the social, economic, and environmental wellbeing of the community it serves. It also informs ABM which visualizes the trajectories of sustainable developments towards sustainability. Data analytics and machine learning may also be used to predict population growth and migration, climate change effects, the diffusion effects of sustainable development initiatives, and other factors that contribute to social wellbeing.

10 Future research

A potential SME framework has been introduced. Future research will involve the development of economic models for potential community-level SME projects (e.g., agribusiness, manufacturing, construction, or services) using this framework. These models should reveal an understanding of the diffusion of benefits to local communities as well as the regional generalizability of specific models. At a community level this could indicate the level of job creation, investment in social and environmental infrastructure, and potential benefits through collaboration with other communities. At a macro level, modeling should reveal insights to regional benefits of SMEs operating in the same industry, and macro-economic impacts regionally and nationally. This information can be used to guide policy initiatives in business development, skills training, tariff structures, tax programs, and other support programs. Data generation models will evaluate the viability of accessing big data for highly nuanced data analytics of trends in the social wellbeing of households and communities. Climate change models could also be applied to agribusiness SMEs to determine future mitigation strategies. A study into the use of mobile money services may provide valuable insights into the current usage of these services and the propensity for additional services arising from large scale SME deployments.

Availability of data and material

All database search results are available in Endnote library format.

United Nations. Sustainable development goal 1. End poverty in all its forms everywhere. 2017. https://sustainabledevelopment.un.org/sdg1 .

World Bank. Poverty and shared prosperity. Reversals of fortune. World Bank Group. 2021. https://openknowledge.worldbank.org/bitstream/handle/10986/34496/9781464816024.pdf .

Lakner C, Gerszon Mahler D, Negre M, Prydz EB. How much does reducing inequality matter for global poverty? 2020. https://openknowledge.worldbank.org/bitstream/handle/10986/33902/How-Much-Does-Reducing-Inequality-Matter-for-Global-Poverty.pdf?sequence=1 .

Mubecua MA, David OJ. So far so good? Tracking the poverty eradication goal of SDGs in Kenya, Nigeria, and South Africa. J Public Aff. 2019;19(4): e1964. https://doi.org/10.1002/pa.1964 .

Article   Google Scholar  

Vieri S, Calabro G. Food security and land grabbing in low-income countries of the Sub-Saharan Africa. J Manag Syst. 2019;20(172):118–25.

Google Scholar  

Adesina JO. Inequality in Sub-Saharan Africa: dimensions and drivers. World science report 2016. United Nations Educational, Scientific, and Cultural Organization (UNESCO). 2016. https://en.unesco.org/inclusivepolicylab/sites/default/files/analytics/document/2019/7/Adesina_wssr_2016_chap_18.pdf .

Anetor FO, Esho E, Verhoef G. The impact of foreign direct investment, foreign aid, and trade on poverty reduction: evidence from Sub-Saharan African countries. Cogent Econ Finance. 2020;8(1):1737347. https://doi.org/10.1080/23322039.2020.1737347 .

Adegboye FB, Osabohien R, Olokoyo FO, et al. Institutional quality, foreign direct investment, and economic development in Sub-Saharan Africa. Humanit Soc Sci Commun. 2020;7(38):1–9. https://doi.org/10.1057/s41599-020-0529-x .

United Nations Economic Commission for Africa. Report on sustainable development goals for the West Africa subregion. United Nations Economic and Social Council Economic Commission for Africa. 2015. https://archive.uneca.org/sites/default/files/PublicationFiles/west_africa_sdg_main_report_englishfin_0.pdf .

Abisuga-Oyekunle OA, Patra SK, Muchie M. SMEs in sustainable development: their role in poverty reduction and employment generation in Sub-Saharan Africa. Afr J Sci Technol Innov Dev. 2020;12(4):405–19. https://doi.org/10.1080/20421338.2019.1656428 .

Azunu R, Mensah JK. Local economic development and poverty reduction in developing societies: the experience of the ILO decent work project in Ghana. Local Econ. 2019;34(5):405–20. https://doi.org/10.1177/0269094219859234 .

Hambayi T, Vedanthachari LN. Access to credit as a tool for overcoming SME failures: a case of Sub-Saharan Africa. In: Understanding bankruptcy: global issues, perspectives and challenges. New York: Nova Sciences Publishers; 2017. p. 195–220.

Kassam L, Dorward A. A comparative assessment of the poverty impacts of pond and cage aquaculture in Ghana. Aquaculture. 2017;470:110–22. https://doi.org/10.1016/j.aquaculture.2016.12.017 .

Okpara JO. Factors constraining the growth and survival of SMEs in Nigeria: implications for poverty alleviation. Manag Res Rev. 2011;34(2):156–71. https://doi.org/10.1108/01409171111102786 .

Siringi EM. Women’s small and medium enterprises for poverty alleviation in Sub-Saharan Africa: lessons from Kenya. Manag Res Rev. 2011;34(2):186–206. https://doi.org/10.1108/01409171111102803 .

Adomako S, Amankwah-Amoah J, Tarba SY, Khan Z. Perceived corruption, business process digitization, and SMEs’ degree of internationalization in Sub-Saharan Africa. J Bus Res. 2021;123:196–207. https://doi.org/10.1016/j.jbusres.2020.09.065 .

Nyarku KM, Oduro S. Effect of legal and regulatory framework on SMEs growth in the Accra metropolis of Ghana. Int J Entrep Innov. 2018;19(3):207–17. https://doi.org/10.1177/1465750317742842 .

Arp F, Ardisa A, Ardisa A. Microfinance for poverty alleviation: do transnational initiatives overlook fundamental questions of competition and intermediation? Transnatl Corp. 2017;24(3):103. https://unctad.org/system/files/official-document/diaeia2017d4a8_en.pdf .

Danquah M, Amankwah-Amoah J. Assessing the relationships between human capital, innovation, and technology adoption: evidence from Sub-Saharan Africa. Technol Forecast Soc Change. 2017;122:24–33. https://doi.org/10.1016/j.techfore.2017.04.021 .

Ikejiaku B-V. Poverty-conflict nexus: the contentious issue revisited. Eur J Sustain Dev. 2012;1(2):127–50.

Bendul J, Rosca E, Hoffmann T. Sustainable technology transfer for poverty alleviation: a unified framework for challenges and transdisciplinary solution approaches. WIT Trans Ecol Environ. 2015. https://doi.org/10.2495/SDP150691 .

Kaplinsky R, Morris M. Trade and industrialisation in Africa: SMEs, manufacturing, and cluster dynamics. J Afr Trade. 2019;6(1–2):47–59. https://doi.org/10.2991/jat.k.190812.001 .

Rogerson CM. Successful SMEs in South Africa: the case of clothing producers in the Witwatersrand. Dev South Afr. 2010;17(5):687–716. https://doi.org/10.1080/713661433 .

Sashi CM. The make-buy decision in marketing financial services for poverty alleviation. J Financial Serv Mark. 2011;15(4):296–308. https://doi.org/10.1057/fsm.2010.25 .

Astrid Ruiz T. The elephant in the room: gender and export-led poverty reduction. Manag Decis. 2007;45(8):1359–78. https://doi.org/10.1108/00251740710819087 .

Urquhart C, Liyanage S, Kah MMO. ICTs and poverty reduction: a social capital and knowledge perspective. J Inf Technol. 2008;23(3):203–13. https://doi.org/10.1057/palgrave.jit.2000121 .

Peffers K, Tuunanen T, Rothenberger MA, Chatterjee S. A design science research methodology for information systems research. J Manag Inf Syst. 2008;24(3):5–78. https://doi.org/10.2753/MIS0742-1222240302 .

Khavul S, Bruton GD. Harnessing innovation for change: sustainability and poverty in developing countries. J Manag Stud. 2013;50(2):285–306. https://doi.org/10.1111/j.1467-6486.2012.01067.x .

Mazambani L, Mutambara E. Deepening sustainable value creation in market-led poverty alleviation through a demand and supply integration framework: significance to tourism. Afr J Hosp Tour Leis. 2018;7(2):4–16.

Aftab M, Ismail I. Defeating poverty through education: the role of ICT. Transform Bus Econ. 2015;14(3):21–37.

Diga K, Fortune N, Plantinga P. ICT policy and poverty reduction in Africa. J Policy Regul Strategy Telecommun Inf Media. 2013;15(5):114–27. https://doi.org/10.1108/info-05-2013-0032 .

Gebremichael MD, Jackson JW. Bridging the gap in Sub-Saharan Africa: a holistic look at information poverty and the region’s digital divide. Gov Inf Q. 2006;23(2):267–80. https://doi.org/10.1016/j.giq.2006.02.011 .

Laudon KC, Traver CG. E-commerce 2017: business, technology, society. Boston: Pearson; 2017.

PRISMA. The PRISMA 2020 statement: an updated guideline for reporting systematic reviews. BMJ. 2020. https://doi.org/10.1136/bmj.n71 .

Haughton J, Khandker SR. Handbook on poverty and inequality. Washington, DC: The World Bank; 2009. https://doi.org/10.1596/978-0-8213-7613-3 .

Book   Google Scholar  

World Bank. What is the $1.90 poverty line, and based on this new measure, how many people are living in extreme poverty in the world? 2012. https://datahelpdesk.worldbank.org/knowledgebase/articles/746163-what-is-the-1-90-poverty-line-and-based-on-this .

The Library of Congress. List of Sub-Saharan African countries. 2010. https://www.loc.gov/rr/amed/guide/afr-countrylist.html .

Waas T, Hugé J, Verbruggen A, Wright T. Sustainable development: a bird’s eye view. Sustainability. 2011;3(10):1637–61. https://doi.org/10.3390/su3101637 .

Di Fabio A. The psychology of sustainability and sustainable development for well-being in organizations. Front Psychol. 2017. https://doi.org/10.3389/fpsyg.2017.01534 .

Zuppo CM. Defining ICT in a boundaryless world: the development of a working hierarchy. Int J Manag Inf Technol. 2012;4(3):13.

GSMA. The mobile economy: Sub-Saharan Africa. GSM Association. 2020. https://www.gsma.com/mobileeconomy/wp-content/uploads/2020/09/GSMA_MobileEconomy2020_SSA_Eng.pdf .

Negash S. Accessing ICT enabled content in low-income countries: think big, start small, and scale up. Int J Inf Commun Technol Educ. 2010;6(4):49–60. https://doi.org/10.4018/jicte.2010100105 .

Wamuyu PK. Closing the digital divide in low-income urban communities: a domestication approach. Interdiscip J E-Skills Lifelong Learn. 2017;13:117–42. https://doi.org/10.28945/3885 .

Michael-Onuoha HC, Nkiko C, Omorodion O. Poverty eradication: the role of Nigerian libraries towards the achievement of the sustainable development goals (SDGs). Libr Philos Pract. 2020;1(13). https://digitalcommons.unl.edu/cgi/viewcontent.cgi?article=8003&context=libphilprac

Skuse A, Cousins T. Managing distance: rural poverty and the promise of communication in post-apartheid South Africa. J Asian Afr Stud. 2007;42(2):185–207. https://doi.org/10.1177/0021909607074867 .

Krantz L. The sustainable livelihood approach to poverty reduction. 2001. https://commdev.org/wp-content/uploads/pdf/publications/The-Sustainable-Livelihood-Approach-to-Poverty-Reduction-SIDA.pdf .

Deschamps I. Assessing the organisation pour l’Harmonisation en Afrique du Droit des Affaires’s contributions to poverty reduction in Africa: a grounded outlook. Law Dev Rev. 2013;6(2):S111–53. https://doi.org/10.1515/ldr-2013-0022 .

African Union. About the African Union. (n.d.). https://au.int/en/overview .

Kaplinsky R, Chataway J, Clark N, Hanlin R, Kale D, Muraguri L, Wamae W. Below the radar: what does innovation in emerging economies have to offer other low-income economies? Int J Technol Manag Sustain Dev. 2009;8(3):177. https://doi.org/10.1386/ijtm.8.3.177/1 .

Van den Waeyenberg S, Hens L. Crossing the bridge to poverty, with low-cost cars. J Consum Mark. 2008;25(7):439–45.

J-PAL. The rise of mobile money in Sub-Saharan Africa: has this digital technology lived up to its promises? 2020. https://www.povertyactionlab.org/blog/10-22-20/rise-mobile-money-sub-saharan-africa-has-digital-technology-lived-its-promises .

Maripally A, Bridwell L. The future of financial inclusion and its impact on poverty reduction in India. Competition Forum. 2017;15(2):329–34.

Bongomin GOC, Ntayi JM, Munene JC, Malinga CA. Mobile money and financial inclusion in Sub-Saharan Africa: the moderating role of social networks. J Afr Bus. 2018;19(3):361–84. https://doi.org/10.1080/15228916.2017.1416214 .

Matthews VO, Atayero AA, Popoola SI. Development of a solar photovoltaic vulcanizing machine towards extreme poverty eradication in Africa. In: Paper presented at the lecture notes in engineering and computer science. 2016. https://pdfs.semanticscholar.org/aac9/456e0a6e9e2c5b2f4641504a8711484db3f4.pdf .

van Welie MJ, Truffer B, Yap XS. Towards sustainable urban basic services in low-income countries: a technological innovation system analysis of sanitation value chains in Nairobi. Environ Innov Soc Trans. 2019;33:196–214. https://doi.org/10.1016/j.eist.2019.06.002 .

Chakwizira J. Low-income housing backlogs and deficits “blues” in South Africa. What solutions can a lean construction approach proffer? J Settl Spat Plan. 2019;10(2):71–88. https://doi.org/10.24193/JSSP.2019.2.01 .

Ramos-Mejia M, Franco-Garcia ML, Jauregui-Becker JM. Sustainability transitions in the developing world: challenges of socio-technical transformations unfolding in contexts of poverty. Environ Sci Policy. 2018;84:217–23. https://doi.org/10.1016/j.envsci.2017.03.010 .

Okon GB. Diffusion of innovation patterns among poverty alleviation agencies and sustainable development challenges in the Niger delta region: the Rivers State experience. Rev Eur Stud. 2014;6(2):40–4. https://doi.org/10.5539/res.v6n2p40 .

Hain DS, Jurowetzki R. Local competence building and international venture capital in low-income countries: exploring foreign high-tech investments in Kenya’s Silicon Savanna. J Small Bus Enterp Dev. 2018;25(3):447–82. https://doi.org/10.1108/JSBED-03-2017-0092 .

Sigalla RJ, Carney S. Poverty reduction through entrepreneurship: microcredit, learning and ambivalence amongst women in urban Tanzania. Int J Educ Dev. 2012;32(4):546–54. https://doi.org/10.1016/j.ijedudev.2012.02.011 .

Foy Connor R, Bent-Goodley TB. Zanzibari social entrepreneurs and poverty alleviation strategies: understanding efforts to build local community sustainability. J Community Pract. 2016;24(3):302–18. https://doi.org/10.1080/10705422.2016.1201784 .

Bai Z, McMartin K. Corporate social responsibility: a new perspective for alleviating poverty while maximizing profits. In: Paper presented at the TIC-STH'09: 2009 IEEE Toronto International Conference—Science and Technology for Humanity. 2009. https://ieeexplore.ieee.org/document/5444386 .

Reed D. Poverty and the environment: can sustainable development survive globalization? Nat Res Forum. 2002;26(3):176–84. https://doi.org/10.1111/0165-0203.00019 .

Brown DR, Dettmann P, Rinaudo T, Tefera H, Tofu A. Poverty alleviation and environmental restoration using the clean development mechanism: a case study from Humbo, Ethiopia. Environ Manag. 2011;48(2):322–33. https://doi.org/10.1007/s00267-010-9590-3 .

World Vision Australia. Humble Humbo’s carbon trade upgrade. (n.d.). https://www.worldvision.com.au/global-issues/work-we-do/climate-change/humble-humbo-carbon-trade-upgrade .

Mabogunje AL. Tackling the African “poverty trap”: the Ijebu-Ode experiment. Proc Natl Acad Sci USA. 2007;104(43):16781. https://doi.org/10.1073/pnas.0704765104 .

Pansera M, Martinez F. Innovation for development and poverty reduction: an integrative literature review. J Manag Dev. 2017;36(1):2–13. https://doi.org/10.1108/JMD-02-2015-0013 .

Schreinemachers P, Berger T, Aune JB. Simulating soil fertility and poverty dynamics in Uganda: a bio-economic multi-agent systems approach. Ecol Econ. 2007;64(2):387–401. https://doi.org/10.1016/j.ecolecon.2007.07.018 .

Martin DP. Knowledge transfer models and poverty alleviation in developing countries: critical approaches and foresight. Third World Q. 2019;40(7):1209–26. https://doi.org/10.1080/01436597.2019.1597340 .

Blumenstock J, Cadamuro G, On R. Predicting poverty and wealth from mobile phone metadata. Science. 2015;350(6264):1073–6. https://doi.org/10.1126/science.aac4420 .

Article   CAS   Google Scholar  

Njuguna C, McSharry P. Constructing spatiotemporal poverty indices from big data. J Bus Res. 2017;70:318–27. https://doi.org/10.1016/j.jbusres.2016.08.005 .

Xie M, Jean N, Burke M, Lobell D, Ermon S. Transfer learning from deep features for remote sensing and poverty mapping. In: Paper presented at the 30th AAAI conference on artificial intelligence, AAAI 2016. 2016. https://arxiv.org/abs/1510.00098v2 .

Geels FW. Technological transitions as evolutionary configuration processes: a multi-level perspective and a case-study. Res Policy. 2002;31(8/9):1257–74. https://doi.org/10.1016/S0048-7333(02)00062-8 .

Wieringa RJ. Design science methodology for information systems and software engineering. Heidelberg: Springer; 2014.

Macy M, Willer R. From factors to actors: computational sociology and agent-based modeling. Annu Rev Sociol. 2002;28:143–66.

Gandomi A, Haider M. Beyond the hype: big data concepts, methods, and analytics. Int J Inf Manag. 2015;35(2):137–44. https://doi.org/10.1016/j.ijinfomgt.2014.10.007 .

NOAA. Nighttime lights. (n.d.). https://sos.noaa.gov/datasets/nighttime-lights/ .

Hasselberg AE, Askre I, Scholtens J, Overa R, Bank MS, Atter A, Kjellevold M. Fish for food and nutrition security in Ghana: challenges and opportunities. Glob Food Secur. 2020. https://doi.org/10.1016/j.gfs.2020.100380 .

Download references

Author information

Authors and affiliations.

Curtin University, Perth, Australia

Darrold L. Cordes & Dora Marinova

You can also search for this author in PubMed   Google Scholar

Contributions

D.C. wrote the manuscript text. All authors reviewed the manuscript text. All authors read and approved the final manuscript.

Corresponding author

Correspondence to Darrold L. Cordes .

Ethics declarations

Competing interests.

The authors declare no competing interests.

Additional information

Publisher's note.

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Appendix A - Lists of research articles

2.1 research question 1.

See Table 6 , Fig.  9 .

Occurrences of Search Words/Phrases

2.2 Research question 2

See Table 7 , Fig.  10

2.3 Research question 3

See Table 8 , Fig.  11

2.4 Other queries

See Table 9

Appendix B – List of journals/publications

See Table 10

Rights and permissions

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ .

Reprints and permissions

About this article

Cordes, D.L., Marinova, D. Systematic literature review of the role of e-commerce in providing pathways to sustainability for poverty alleviation in Sub-Saharan Africa. Discov Sustain 4 , 7 (2023). https://doi.org/10.1007/s43621-022-00109-3

Download citation

Received : 10 September 2022

Accepted : 01 November 2022

Published : 02 February 2023

DOI : https://doi.org/10.1007/s43621-022-00109-3

Share this article

Anyone you share the following link with will be able to read this content:

Sorry, a shareable link is not currently available for this article.

Provided by the Springer Nature SharedIt content-sharing initiative

• Sustainability
• Sustainable development
• Entrepreneurship
• Sub-Saharan Africa
• Social media
• Social networks
• Collaboration
• Find a journal
• Publish with us
• Track your research

Academia.edu no longer supports Internet Explorer.

To browse Academia.edu and the wider internet faster and more securely, please take a few seconds to  upgrade your browser .

Enter the email address you signed up with and we'll email you a reset link.

• We're Hiring!
• Help Center

E-Commerce in India: Literature Review

Related Papers

International Journal of Electronic Marketing and Retailing

Prateek Kalia, Ph.D.

Thoughtful insights on business model components of top e-retailers based in India have been achieved through content analysis of reliable books, reports, journals and the web. Six major e-retailers are compared on the basis of monthly traffic data obtained from similarweb.com. It is observed that online retail is a meager 0.5% of overall retail in India and future potential is huge. Due to FDI restrictions all top e-retailers under this study except HS18 prefer marketplace model in pure/hybrid form and earn revenue through transaction fee. Their marketing strategy essentially includes social media and internet. They operate with lean manpower and functional departmentalisation except Flipkart which employs massive 10,000 plus employees and prefers to recruit generalists. National capital region and Bangalore are preferred locations for establishment of their headquarters. This review will be useful to businesses and researchers interested in developing/benchmarking successful e-retail business model to win and sustain competition.

Dr. Subhadeep Mukherjee

E-commerce stands for electronic commerce. E-commerce is performing business online and electronically. Over last few years the popularity of e-commerce has rigorously developed due to its quick and convenient way of exchanging goods and regional and global services. India will be booming platform for e-commerce business models; the country already reported 65% growth in e-commerce retail business year in 2015-2016. The paper is focused on the conceptual research with exploratory cum descriptive nature on the basis of secondary data. This paper explains the concept of e-commerce, business models for e-commerce, differences between traditional commerce and electronic commerce, merits and limitations of e-commerce. It also highlights various trends and challenges of e-commerce and also with the essential opportunity and growth factors required for e-commerce in India.

Jayakrishnan S Nair

E-retailing or online is growing at faster pace in India. It has witnessed steady growth of 50-60 % over the years. E-retailing accounts for 10 % of e-commerce activities in India. Even though there are growth prospects for online retail in India we have challenges which need to be addressed. The article focuses on the opportunities and challenges for online retailers in Indian business environment.

varun shenoy

Development of secured encryption gateways for safe transfer of information over the web, online transactions wrote a new chapter in the history of E-Business Development. Advent of E-mail and printable E-receipts further solidified the conduct of online web business and transactions as a voucher or invoice in case of physical transactions. With processes like Search Engine Optimization (SEO), SAP, Web Sourcing, Online data Modelling, Database Management systems, Web Advertisements and Digital Marketing becoming prominent as a pivotal strategy for Organizational goods sale, a practically real Global Online Virtual Market took shape. With few global major players, India was still a virgin market. With immense opportunistic population market existing at the Indian territory with a concept of brick & mortar shopping, few entrepreneurs decided to ride the online wave. With Internet Revolution gaining brisk momentum and rising IT employee levels increasing every year, entrepreneurs decided to leverage the demographies. Hence, this study takes up a case where in e-commerce start-ups like Flipkart, Myntra, Jabong, Snapdeal, Zomato, Redbus, mydeals247, bigbasket, paytm etc. Succeeded in capturing Indian consumers. Case also enlightens how if Internet used as strategic tool can lead to profitability.

Asian Journal of Multidisciplinary Studies

Sumit Goklaney

RUDRAJEET PAL

Lincoln Blumell, Jenn Cianca, Peter Richardson, and William Tabbernee, "The Roman Near East," in William Tabbernee, ed., Early Christianity in Contexts: An Exploration across Cultures and Continents (Grand Rapids, MI: Baker Academic, 2014), 11-62.

William Tabbernee

This first chapter of the book Early Christianity in Contexts surveys the cultural context and the literary and material evidence for early Christian communities in Jerusalem (William Tabbernee); Judaea, Samaria, Galilee, Syria Phoenice, Phoenicia/Phoenica Libanensis, the Decapolis, and North- Central- and Southern Arabia (Peter Richardson); as well as the Sinai, Arabia Felix (Lincoln Blumell), Antioch-on-the Orontes, the Tetrapolis, and Syria Coele (Jenn Cianca).

Gerardo Zapata

Herders Biblische Studien 100

Eckart Otto

Methods and Techniques of Scriptural Scholarship in the Disputes between Scribes of the Temple of Jerusalem and at the Sanctuary on Garizim in the Book of Deuteronomy and the Book of Joshua; publ in: Vor allen Dingen: Das Alte Testament. Festschrift für Christoph Dohmen, ed. B. Schmitz/T. Hieke/M Ederer, Herders Biblische Studien 100, Freiburg/Basel/Wien 2023, 195-210

Scuola Archeologica Italiana di Atene

La Scuola Archeologica Italiana di Atene è lieta di invitarvi alla presentazione del volume: PASSEGGIATE ITALIANE (Traduzione italiana) di Semni Karouzou. L’evento si terrà Giovedì 11 maggio 2023 alle ore 19.00 nell’Aula Magna “Doro Levi”, in odòs Parthenonos 14. Intervengono: Emanuele PAPI (SAIA) Lila MARANGOU (Università di Ioannina) Paola PELAGATTI (Accademia dei Lincei) Gerasimos ZORAS (Università Nazionale Capodistriana di Atene) Maurizio De Rosa (EPTbooks) L'evento sarà coordinato da Emeri FARINETTI (Università di Roma 3 - SAIA) Seguirà un rinfresco. Η Ιταλική Αρχαιολογική Σχολή Αθηνών με ιδιαίτερη χαρά σας προσκαλεί στην παρουσίαση του βιβλίου PASSEGGIATE ITALIANE (μετάφραση στα ελληνικά), της Σέμνης Καρούζου. Η εκδήλωση θα πραγματοποιηθεί την Πέμτη 11 Μαίου 2023 στις 7 μ.μ. στην Αίθουσα Εκδηλώσεων "Doro Levi", οδός Παρθενώνος 14. Πρόγραμμα: Ομιλητές: Emanuele PAPI (IAΣΑ) Lila MARANGOU (Πανεπιστήμιο Ιωαννίνων) Paola PELAGATTI (Accademia dei Lincei) Gerasimos ZORAS (ΕΚΠΑ) Maurizio De Rosa (EPTbooks) με συντονίστρια την Emeri FARINETTI (Università di Roma 3 - ΙΑΣΑ) Θα ακολουθήσει δεξίωση The Italian Archaeological School at Athens is pleased to invite you to the Book Launch of: PASSEGGIATE ITALIANE (Traduzione italiana) by Semni Karouzou. Thursday, May 11th, 2023. "Doro Levi Lecture Hall", Parthenonos 14, Athens, at 7 p.m. Speakers: Emanuele PAPI (IASA) Lila MARANGOU (University of Ioannina) Paola PELAGATTI (Accademia dei Lincei) Gerasimos ZORAS (National and Capodistrian University of Athens) Maurizio De Rosa (EPTbooks) The event will be coordinated by: Emeri FARINETTI (University of Rome 3 - IASA) A reception will follow.

RELATED TOPICS

•   We're Hiring!
•   Help Center
• Find new research papers in:
• Health Sciences
• Earth Sciences
• Cognitive Science
• Mathematics
• Computer Science
• Academia ©2024

Enter the URL below into your favorite RSS reader.

Cross-border Retail E-Commerce and De Minimis: The Case of Kazakhstan

• Citation (BibTeX)

View more stats

The development of international e-commerce has expanded opportunities for business and consumption in Kazakhstan and worldwide. However, these rapid changes have challenged the governments’ regulation of the flow of cross-border goods, ranging from clearance to customs duty and taxes collection. Among concerns is the flow of low-value consignments, the impact of which had previously been seen as beneficial. This paper examines whether cross-border e-commerce and the de minimis threshold are advantageous in Kazakhstan based on context, description, cause-and-effect and statistical analysis. The findings show a partial impact of de minimis threshold changes on the increase in retail e-commerce goods imported and on the decrease in the value of mis-declared goods; however, in Kazakhstan the consequences from the import of mis-declared low-value goods on the tax revenue are insignificant. Misuse of the de minimis threshold in Kazakhstan is confirmed by the study. Government actions for solving this problem involve giving higher priority to people’s access to higher quality and/or cheaper personal use goods. Also, the potential for further improvement of statistics on cross-border e-commerce is identified.

1. Introduction

The rapid development of e-commerce across the world has resulted in policy actions in many countries, as well as discussions around its advantages and disadvantages. Among these concerns is the impact of cross-border retail e-commerce on national economies and the countries’ wellbeing. The bottom line is issues such as taxation and customs duties for government revenues and fair competition among domestic and foreign retailers, the increasing burden for customs offices due to the growing number of low-value parcels and the purchasing power of the population (KPMG International , 2017; Mitchell & Mishra , 2017; Nakao , 2021; Organisation for Economic Co-operation and Development , 2019c) . The impact of the listed issues, however, may differ between developed and developing countries (KPMG International , 2017) .

As part of the world economy, Kazakhstan is vulnerable to international e-commerce spillover effects. Retail e-commerce in the internal market is both part of the domestic and the international online market. This article discusses how retail cross-border e-commerce influences Kazakhstan’s economy. It focuses on the impact of the de minimis threshold for personal use goods.

The paper is structured as follows. First, a brief background to the current national customs regulation of cross-border e-commerce is given. Then, the literature review critically reflects the main inferences of previous studies on this subject. The next sections describe the methodology and data used to analyse the impact of cross-border e-commence on the national economy. Finally, results and recommendations based on this analysis are outlined.

2. Background

In Kazakhstan, the development of retail e-commerce has increasing potential. In the 2020 United Nations Conference on Trade and Development (UNCTAD) B2C E-commerce Index, the country was placed sixtieth out of 152 countries with an index value of 68.2 (UNCTAD , 2021a) while in 2016 it had been eighty-eighth out of 137 countries with an index value of 35.5 (UNCTAD , 2017) . The increase in this ranking could also result from the country’s trade logistics data, where in 2017–2019 the three indicators were higher relative to the world average (UNCTAD , 2021b) . More people were engaged in distance shopping in Kazakhstan (94% had mail delivered at home compared with 86.7% for the world) with a higher postal reliability index (64.4% versus 43.4% for the world) and faster customs clearance (7.2 days for clearance of direct exports against the world average of 7.6 days) (UNCTAD , 2021b) .

This, in its turn, shows developments in the national customs administration. Signing up to the SAFE Framework of Standards to Secure and Facilitate Global Trade (SAFE Framework) (World Customs Organization (WCO) , 2005) and the Framework of Standards for Cross-Border E-Commerce 2018 (E-commerce Framework) (WCO , 2018) , Kazakhstan has adhered to these fundamental international standards and ensured safe and favourable conditions for the flow of retail goods across the border. Both the Code of the Republic of Kazakhstan on Customs Affairs in the Republic of Kazakhstan 2010 (Customs Code of Kazakhstan 2010) and the Code of the Republic of Kazakhstan on Customs Regulation in the Republic of Kazakhstan 2017 (Customs Code of Kazakhstan 2017) declare de minimis for cross-border retail personal goods and from 2018, for that of e-commerce, among other enhancements ( Code of the Republic of Kazakhstan on Customs Affairs in the Republic of Kazakhstan , 2010; Code of the Republic of Kazakhstan on Customs Regulation in the Republic of Kazakhstan , 2017; President of the Republic of Kazakhstan , 2023) . This is in line with the Customs Code of the Eurasian Economic Union (EAEU Customs Code) as well being part of the membership obligations of the country.

An important step in the implementation of the agreements in Kazakhstan was the adoption of the Order of the Council of the Eurasian Economic Commission ‘On Particular Issues of Conducting Pilot Project (Experiments) in the Field of Foreign E-trade in Goods in the Member States of the Eurasian Economic Union’ of 2021 (e.g. , Eurasian Economic Union (EAEU) , 2021d) . The project is ongoing (e. g. , EAEU , 2021a , 2021b , 2021c) .

Moreover, Kazakhstan as a member of the EAEU has been actively involved in the harmonisation of the union’s legislation on customs administration with the fundamental international standards of the E-commerce Framework with special consideration given to the customs administration specifications within the framework of cross-border e-commerce (WCO , 2018) . It should be noted that factors significantly affecting these specifications, established in the 2018 E-commerce Framework, are the explosive growth in the supply of low-value parcels and the formation of international chains. As a result, the need for an e-commerce operator to facilitate goods flow through Customs is confirmed.

Currently, amendments to the EAEU Customs Code are being developed to improve customs administration related to e-commerce goods while applying the EAEU’s technical regulation norms as well as increasing the competitiveness of the national producers of the member countries (EAEU , 2022c) . This includes the introduction of the concept of an e-commerce operator and a declaration for e-commerce goods. Kazpost JSC, the national postal operator and a few express carriers are under consideration as the e-commerce operator.

3. Literature review

The challenges raised by e-commerce in general are due to its digital nature, the features and implications of which have not been fully identified and reflected in regulatory documents in many countries, including Kazakhstan. The use of digital e-commerce for cross-border trade, however, was not uncommon even at the start of the year 2000. As Lopez-Bassols and Vickery (2001) highlight, international retail purchase was not as common as trade among businesses themselves because of low confidence in internet use and online shops, as well as lack of internet access.

It is claimed that the biggest trigger for individuals becoming more active in cross-border online shopping was the coronavirus pandemic; an assertion generally supported by many recent studies (e.g., Congressional Research Service , 2022; World Customs Organization , 2022 ). This is particularly true for developing countries. The unexpected necessity for social distancing during the 2020 pandemic left people with almost no choice but to move to online shopping. For instance, PricewaterhouseCoopers (PwC) Kazakhstan’s survey among e-commerce retailers shows a 1.8 times increase in the domestic retail e-market in the national currency in 2020, or a 1.7 times increase in US dollars (PwC , 2021) .

Governments were forced to accelerate ongoing programs to ensure internet access to almost everyone. For instance, in less-developed countries within ongoing and new government strategies, governments ‘implemented support measures to facilitate B2C e-commerce’ (UNCTAD , 2021a , p. 13) . Support for these programs was enabled by improvements in the online sales processes used by the retailers and intermediaries, such as payments and delivery (PwC , 2021) . This provided customers with practical experience in gaining skills in navigating online sales platforms as well as giving them confidence in the reliability of online shopping, including cross-border shopping.

The digital transformation has affected not only trading methods, but also the very definition of e-commerce, to reflect the diversification in the technology used. If in earlier studies e-commerce was defined as trade conducted via telephone or fax, in later studies the online platform is recognised as another possible method for purchases and sales (e.g. , see OECD , 2002 , 2019c , 2019a , 2019b) . For this paper, however, the latter definition of e-commerce is used as it serves our objectives on the analysis of the impact of cross-border e-commerce.

As Blegen (2020) and Huria (2019) note, at this stage of customs administration development, tangible goods are the only subject of border clearance. Additionally, imported goods bought for non-commercial use and of low value have been treated as those not worth subjecting to standard customs and taxation procedures since the costs outweigh the benefits (Hintsa et al. , 2014; Holloway & Rae , 2012) . They are treated as being within the de minimis and their thresholds are identified and established by each country on their own regarding the purposes to be served and estimated cost-benefits.

However, the increase in the quantity of imported goods because of e-commerce’s rapid development has sparked discussions on whether this approach remains valid (Blegen , 2020; European Commission , 2020; Usman , 2019) . First, owing to such advantages as the shortened consignment delivery time, availability of comparatively cheaper and better-quality consumer goods, among others, the more low-value tax-free consignments that pass the border the more alternative costs for the national economy (Nakao , 2021) . The forgone benefits for the economy could be expressed in lower sales to the taxpayer retailers (e.g., Harbolt , 2019 ), redirecting their purchases from wholesale to direct cross-border e-commerce purchases to save on tax differentials (Shi et al. , 2019) and even in moving the business abroad to win on tax exemption on goods that have now become imports (Nakao , 2021) ; and thus, doubling the losses in tax revenue for the governments. More to the point, Nakao (2021) refers to the governments’ concerns on job losses due to decreases in sales by domestic suppliers. Then the very possible consequence is an undermined purchasing power of the people.

Secondly, misuse of the simplified clearance is identified in some papers. One way this is done is via mis-declaration. WCO (2017) and Li (2019) refer to cases when commercial consignments are declared as non-traded goods for personal use only. Another method of misuse as a means of tax avoidance as discussed in WCO (2017), Shi et al. (2019) , Li (2019) and Nakao (2021) is the purposeful lowering of the consignments’ value by vendors. This leads to incorrect tariff classification and duty and tax avoidance in lowering the payable amount.

Harbolt (2019) holds a contrary view on the subject; tax avoidance is asserted to take place when customers opt for cheaper foreign goods. Based on previous studies and his empirical research, Harbolt argues that online cross-border purchases from the other countries with lower sales taxes are the responses of consumers not wanting to bear the burden of higher domestic sales taxes, provided the tax differentials outweigh travel costs related to the purchase. In connection to cross-border retail e-commerce it could be added that the tax differentials should outweigh transportation costs for customers, if only expenses are considered.

When comparing these three different approaches on tax avoidance (mis-declaration, lowering of value and opting for cheaper goods), the subject is a customer only in the latter, rather than a seller and/or a customer in the first two, and the method is e-commerce itself, not the changes in a parcel’s metrics or purposes. What is common is that tax avoidance, along with the foreseen growth of international e-commerce, will cause further rocketing of the number of low-value consignments passing through Customs. However, if in the first two cases there is a necessity for overseeing fraud risks (Li , 2019; Nakao , 2021) , the latter case could not be considered as fraud provided the goods pass the border legally. So, it is worth noting that not all means of tax avoidance should be considered misuse.

Furthermore, the sales tax burden is the customer’s regardless of who transfers taxes on goods to governments — a customer or a vendor (see e. g., Nakao , 2021 ). Therefore, it is arguable that a customer purchasing goods abroad could be viewed as a tax evader. Alternatively, some papers express positive views on this preference by consumers. UNCTAD (2019) and Eurostat (2022) highlight the benefits for consumers as ‘greater choices and lower prices’ (UNCTAD, 2019, p. 2), which are given by ‘the smooth functioning of the single market for e-commerce’ (Eurostat , 2022) . Even when there is no time-savings on customs clearance, direct online retail cross-border purchases offer a wider ‘range of product choice’ (Li , 2019 , p. 25) .

Returning to discussions on the merits of simplified customs clearance procedures for low-value consignments, it is argued that security concerns, such as drugs and transportation of other illegal items, remain, and will possibly grow with e-commerce (e.g., Huria , 2019 ). Therefore, even under the simplified clearance procedures the increase in consignments adds to the workload of the customs office (Nakao , 2021) . Nonetheless, Nakao further argues that the declared benefits of increased customs efficiency due to simplifications in clearance for low-value consignments are not applicable to developed countries with already relatively efficient customs procedures. Nakao’s statement is supportive by KPMG International (2017) that points out the differences in the impact of e-commerce among developed and developing countries.

The arguments outlined above have provoked reconsiderations of the previous policy on international retail sales by some governments (see e.g., Shi et al. , 2019 and Nakao , 2021 ). For example, Austria, China and the European Union (EU) lowered their de minimis thresholds with Australia and the EU introducing a foreign suppliers’ obligation to collect taxes from consumers and transfer these to the resident country of the purchaser of the goods. For instance, from 1 July 2021, previously tax-free non-postal consignments of no more than EUR22 crossing the border into the EU are now subject to VAT (WCO , 2022) . As declared by the WCO (2022) , ‘This is to ensure fairness among EU producers and to curb fraud among traders which is estimated at €7 billion a year’ (p. 46).

The opposite position was taken by the United States (US). The US raised the threshold and negotiated with its trade partners to do so for goods imported from the US (Nakao , 2021) . According to Nakao, this is because the US taxation system is different from those of the other three countries (Austria, China and the EU) in that it obliges a consumer to be the source of the sales tax accrual and payment.

As our review shows there is room for further discussions and policy actions on the advantages and disadvantages of cross-border retail e-commerce. We agree with Huria (2019) in that ‘the cost–benefit analysis should not be just from the perspective of revenue but also the wider economic impact of lowering consumer prices through e-commerce and providing access to cheaper imported inputs’ (p. 38). Therefore, opting for cheaper foreign goods due to tax differentials, with higher quality and wider choices, is rather an exercise in free choice by the customer, provided the entire process of acquiring the goods is legal. The establishment of this legal framework considers the competition conditions for businesses and the costs and revenue for the public budget, and even creating opportunities for customer choice.

4. Methodology and data

To obtain theoretical and empirical insights of de minimis policy implemented internationally and in Kazakhstan, peer-reviewed papers, analytical reports and research papers from international organisations such as the WCO, OECD, KPMG and PwC, and legislative documents of Kazakhstan, the EAEU and WCO, were analysed. However, from an empirical viewpoint this study is characterised by the limited availability of statistics on cross-border low-value goods purchases of both traditional and e-commerce goods by Kazakhstani residents and non-residents. Data for cross-border retail e-commerce, cross-border retail e-commerce for personal use goods and cross-border traditional purchases for personal use in terms of the number, weights, values and time taken for parcels to flow through the border are not available on the websites of the Bureau of National Statistics of the Agency for Strategic Planning and Reforms of the Republic of Kazakhstan and the State Revenue Committee of the Ministry of Finance of the Republic of Kazakhstan (SRC). There is no separation in the official data on the taxes and Customs collected between cross-border e-commerce and traditional purchases, and no available statistics on misuse and security issues related to the de minimis threshold.

To overcome this limitation in data, consideration was given to the fact that cross-border e-commerce goods delivery is usually by one of two general ways in Kazakhstan — postal or cargo-express delivery. Both use aeroplanes, railways, ships and automobiles as intermediaries. Therefore, data on overall imports by different modes of transport from the SRC was used in the analysis to obtain a broad picture of the situation. Data for the period 2015—2021 were used, as follows.

Data and information on limitations of the de minimis threshold were obtained from the Customs Codes of both Kazakhstan and the EAEU (Customs Code of Kazakhstan 2010; Customs Code of Kazakhstan 2017; EAEU, 2017; 2022a; 2022b; 2022c). Data on government revenue were obtained from the SRC’s website and data for mis-declared trade of goods were derived from the information provided to the authors by the National Bank of the Republic of Kazakhstan (National Bank) through the online platform, ‘E-otinish’ (National Bank , 2022) , developed for submitting and receiving citizen’s appeals to government bodies.

Therefore, the main research method applied was descriptive. That is, quantitative and qualitative observations were employed to identify patterns in certain aspects of the research objectives such as the relationships between the de minimis threshold, retail e-commerce imports of personal goods, public revenue, tax and duty collection, and customs administration workload.

Simple correlation analysis was conducted to evaluate the impact of de minimis policy change in Kazakhstan on the value of imported purchases. Statistics on the changes over the years in imported goods by all modes of transport (obtained from the SRC website, see Table 3), the changes in the de minimis threshold value of purchases delivered by modes other than air, as well as changes in the limits on the threshold-use frequency (see Table 1), were used. The data on de minimis threshold weight did not produce any results and therefore were excluded from the correlation analysis. Also, since there were no changes in limitations on the threshold-use frequency on any mode of transport other than postal and cargo-express deliveries, the correlation analysis was conducted to estimate the relationship between the changes in applying the limitations and in imports by post only.

To investigate whether the change of the threshold had any impact on government revenue, data on budget income, total tax revenue and its components were used for statistical comparative analysis. Correlation and comparative statistical analysis of the impact of the de minimis threshold on the import value of retail goods and public revenue were performed.

Context analysis of documents such as ‘ Development Plan 2023–2027 ’ (Ministry of Finance of the Republic of Kazakhstan , 2024) helped strengthen the study and allowed us to draw some inferences on such issues as the misuse of the de minimis threshold, and government objectives and actions in implementing de minimis policy.

Along with the methods above, the cause-and-effect method was applied in the interpretation of the results. Thus, singular aspects of the study, for instance, misuse of the threshold, were identified and then factors that triggered those singular aspects were investigated, for example, the pandemic, the threshold change and the development of e-commerce.

It should also be noted that the issue of multi-currency was solved by using the official exchange rates published on the official website of the National Bank. All currency units were converted into US dollars. It should be highlighted, though, that de minimis thresholds stated in official documents in euro were first converted into the national currency (tenge) and then the tenge equivalents were converted into US dollars. This was done because the source of the data was the official exchange rate provided by the National Bank and was in the national currency.

5. Analysis and results

Prior to 2018 in Kazakhstan, there was no tax and duty for import of e-commerce retail goods. Since 2018 these goods are subject to regulations similar to consignments for personal use transported by a carrier or by post: that is, the same thresholds, the same uniform rates of customs duty and tax, and the same limitations are applied. Thus, it makes no difference to a carrier or a post office whether a consignment is the subject of e-commerce or not.

Since then, the de minimis threshold has been gradually decreasing regardless of the mode of transport, except via air (Table 1). Notably, the change for delivered purchases favoured mainly cheaper goods because it extends to the value of the imported good not its weight. What is more, in 2020 the limits on the threshold-use frequency were removed (EAEU, 2017). This reflects the policy concerns of ensuring access of the population to higher quality and relatively cheaper consumer goods.

Source : Customs Code of Kazakhstan 2010; Customs Code of Kazakhstan 2017; EAEU (2017); EAEU (2022a); EAEU (2022b); EAEU (2022c); National Bank of the Republic of Kazakhstan (n.d.) ; Ministry of Finance of the Republic of Kazakhstan (2015)

Simple correlation analysis shows that overall changes in the value and weight of imported goods have some correlation with those of the de minimis threshold (Table 2). The results suggest that, on average, there is a positive correlation (relationship) between changes in de minimis threshold and the value of imports via air, and between changes in de minimis threshold and in the weight of imports via rail and post. That is, the decrease in the level of the threshold tends to lead to an increase in purchases of more expensive goods delivered via air and of heavier goods delivered via rail and by post.

Furthermore, there is a weak relationship between the limits on the threshold-use frequency and the changes in imports by post. This may reflect the relatively lower cost of delivery by post as well as the previously mentioned common approach for cross-border e-commerce goods delivery — postal and cargo-express delivery. It should be noted that the postal service wins by its infrastructure, which gives it the ability to deliver to remote destinations within the country with relatively cheaper delivery costs.

Source : State Revenue Committee of the Republic of Kazakhstan (n.d.) .

However, caution should be observed when interpreting the correlation results. Examination of the input data on changes in imports shows that in 2019, for example, the year of a twofold decrease in the threshold in value, there were increases in all import groups (Table 3). As mentioned in the methodology section, cross-border e-commerce personal use goods delivery is usually via either postal or cargo-express delivery. Here air, rail and road transportation are intermediates for such deliveries. Given that these data on import are the sums of values or weights of the import for commercial and non-commercial use, including for personal use, the discrepancy could result from an overlap with the effects of the larger part of the ‘not-for-personal-use’ part of the import. The statistics used for the analysis do not allow us to separate the deliveries, firstly, of personal use goods from the other types of imported consignments and, secondly, into the two transport groups (postal and cargo-express).

Source: State Revenue Committee of the Republic of Kazakhstan (n.d.)

Nevertheless, the correlation results offer an overall picture of the possible directions of the de minimis policy impacts. Decreasing de minimis as well as removal of limits on the threshold-use frequency tend to increase the flow of cross-border low-value goods via air and railway check points rather than automobile check points.

From the figures in Table 4 for the period 2016–2021, most of the budget revenue is from taxes collected. In their turn, these taxes are mainly from internal activities and only 11–12 per cent are from imports. At the same time, the taxes and duties from purchases for personal use did not reach 1 per cent of the total tax revenue for the entire period 2015–2021. Thus, it could be said that the changes in the threshold value did not greatly affect the revenue collected from foreign and domestic activities, and therefore, the decrease did not negatively affect the sales of the internal market.

Source: State Revenue Committee of the Republic of Kazakhstan (n.d.); National Bank of the Republic of Kazakhstan (n.d.)

Based on the data on adjustments made in the value of imports by individuals provided by the National Bank for 2017–2021 (Table 5), we conclude that the number of mis-declared imports is decreasing, even though the shuttle import adjustments made by the National Bank were decreasing in 2020–2021. Here caution should be given to the fact that the sharp reduction and the subsequent low trend in shuttle trade in 2020 is from the second quarter. Restrictions due to COVID-19 were implemented from March 2020 in Kazakhstan and about the same time in China, one of Kazakhstan’s main trading partners. Therefore, some effects on the decrease in value of shuttle trade might be attributed to the COVID-19 response (National Bank , 2022) .

In contrast to shuttle trade, the adjustments for e-commerce imports by individuals are increasing (Table 5). This inference is also supported by the following observations. In line with the information from Table 1, from March 2022 the de minimis threshold was increased to its 2018 level (EUR1000); but the relative value of mis-declared e-commerce imports increased. Moreover, according to the SRC, the de minimis increase of 2022 led to a decrease in ‘the number of issued customs receipt orders for e-commerce parcels with the cost and weight exceeding the limit’ relative to 2021, that is, by 35 per cent, reaching 15,109; ‘nevertheless, the amount of collected payments has increased by 26.5 per cent’ (SRC , 2023) . This might suggest that de minimis policy change encouraged the growth of the cross-border e-trade but had lesser effects on mis-declared e-commerce.

Nevertheless, the figures for both shuttle trade and overall mis-declared imports suggest an overall decreasing trend in mis-declared imports. Therefore, our theory on the possible effect of the threshold change on cross-border purchases, including mis-declaration of traditional cross-border purchases, is reasonable.

Source : National Bank of the Republic of Kazakhstan (2022)

In addition, lost public revenue for 2017–2021 due to mis-declared trade was calculated using a taxation rate of 12 per cent VAT to estimate the amount of possible tax received from these activities (Table 5). The customs duty of 20,000 tenge (USD48.4, according to a USD/KZT exchange rate of 412.95 for 2020), import duty of 0–15 per cent and antidumping duty, which depends on the type of goods imported, were disregarded ( Code of the Republic of Kazakhstan: On taxes and other obligatory payments to the budget (Tax Code) , 2017). Also, an assumption was made that these mis-declared purchases were taxable in full. The results show the increasing share of lost tax revenue from e-commerce imports by individuals in the total lost tax revenue from mis-declared imports by individuals (Table 5). The impact for the public revenue, estimated by adding the total lost tax revenue from mis-declared imports by individuals to the total tax revenue and taking its share from this sum, is within the range of 0.4 per cent of the potential revenue from total customs duty and tax in 2020 and 2021, to 1.4 per cent of that in 2017 (National Bank of the Republic of Kazakhstan , 2022) . Thus, the negative impact of mis-declared cross-border purchases by individuals appears to have decreased since 2020.

One of the sources of these mis-declarations of imports stems from the de minimis criteria. There were four criteria before 2019 and three since (EAEU, 2017). They are purpose, value and weight of the cross-border purchases for personal use, and frequency of the de minimis threshold use (EAEU, 2017). Since adjustments of the National Bank are made within the national balance of payments and assuming that all imports clear Customs, mis-declaration of the value of imports should be considered first. That is, to some extent, misuse of the de minimis threshold was confirmed.

Analysis of the strategic document entitled ‘Development Plan 2023–2027’ (Ministry of Finance of the Republic of Kazakhstan , 2024) shows that malpractice with another criterion is also occurring: there are issues with incorrect statements regarding the purpose of imported low-value goods. Thus, to overcome this issue the Strategic Plan of the Ministry of Finance of the Republic of Kazakhstan aims to digitalise customs administration to track goods from Customs to the consumer and ensure fair and transparent business (Ministry of Finance of the Republic of Kazakhstan , 2024) .

To better combat illicit trade, the WCO proposes the development of international cooperation in this area (WCO, n.d.). An example of such cooperation is the initiative of the EAEU on regulation of e-commerce. This will provide a framework for the regulation of imports through direct delivery from the seller to the purchaser via postal or express delivery and through customs warehouses for storage of imported goods (EAEU, 2021a). In the former case, as was mentioned previously, the single national operator in Kazakhstan is KazPost, which will be the only authorised trade facilitator in parcel delivery (EAEU, 2021a). What is more, KazPost and the SRC of Kazakhstan have already begun cooperating on sharing of import data by KazPost through data systems integration (EAEU, 2021a); thus the initiative will allow extension of this cooperation to express delivery. Overall, the initiative is aimed to optimise customs declaration and reduce mis-declaration, as well as reduce the time of delivery of e-commerce purchases.

However, the impact of de minimis policy change on Customs in terms of workload is not obvious. First, there is some reduction in one type of registration of customs documents and some increases in other types. Second, the increase in payments from the increase in e-commerce imports suggests that increased border flows might also be due to the development of e-commerce itself in Kazakhstan, and increased involvement of more individuals in e-commerce. Third, there are no statistics available on the number of low-value goods crossing the border.

The analysis shows that even though there is only weak evidence of the dependence of the import of personal use goods on the de minimis threshold, some inferences can be made on the partial impact of the de minimis threshold changes on the increase in retail e-commerce goods import and the decrease in the value of mis-declared goods. The threshold and the overall import of goods for personal use have no effect on the amount of total tax and duty revenue. Also, some misuse of the de minimis threshold occurs in practice. However, whether the workload of Customs has been affected by the de minimis policy changes is not obvious.

6. Conclusions and recommendations

There are ongoing concerns on the value of simplifying customs clearance for low-value goods flow. Among these are whether the de minimis threshold should be decreased, how to balance the business environment for both internal and foreign retailers, whether it is opportunity or tax avoidance when consumers purchase cheaper goods abroad, and whether cross-border e-commerce negatively affects public revenue.

E-commerce in Kazakhstan is gradually introducing customers to international networks and is supported by legislative facilitation of the clearance of low-value goods through Customs, including establishing favourable de minimis thresholds. Therefore, we conclude that retail e-commerce of personal use goods is an opportunity to provide the domestic market with higher quality and/or cheaper goods.

As the study indicates, there are gaps in monitoring these processes, such as the absence of statistics on retail e-commerce flow across the border. These restrict the empirical analysis of the advantages and disadvantages of cross-border retail e-commerce and the actions taken by the government. Therefore, the introduction of separate indicators and data collection of the value and quantity of cross-border e-commerce, retail e-commerce and retail e-commerce of low-value parcels, as well as the frequency of threshold use, are suggested as further improvements in data management for Customs.

This paper makes some inferences on the relationships between the de minimis threshold, retail e-commerce imports of personal goods, public revenue, tax and duty collection and customs administration workload. Nonetheless, outside the scope of our analysis are exchange rates and other indicators that characterise internal market development and dependence on external markets, as well as security concerns such as illicit drugs and the transportation of other illegal items. These are possible topics for further research.

This paper also touched upon issues of de minimis misuse. However, it should be noted that the objective of the policy of ensuring people’s access to foreign goods of higher quality and/or lower prices prevails over the objectives of combating tax avoidance in retail personal use import. It focuses more on soft and systemic measures to prevent the intentional mis-declaration of the purpose of imported low-value goods, and to a lesser extent on the intentional mis-declaration of their value, through digitalisation of Customs. The government’s initiatives to solve de minimis misuse involve the use of big data. In this regard we support the WCO recommendations on using technologies related to data analysis (WCO , n.d.) . That is, increasing the potential of Customs and staff to use and analyse big data should be considered during the initial stages of any government initiatives.

Submitted : March 29, 2023 AEST

Accepted : August 16, 2023 AEST