literature review of marketing

Positioning – a literature review

PSU Research Review

ISSN : 2399-1747

Article publication date: 11 July 2020

Issue publication date: 10 September 2021

The purpose of this paper is to review state-of-the-art literature on product/brand positioning to re-examine the positioning concept and developing a more comprehensive definition from a theoretical viewpoint.

Design/methodology/approach

A systematic review of positioning was conducted. The review conformed to a rigorous set of core principles: it was systematic (organized according to a method designed to address the review questions), transparent (explicitly stated), reproducible and updatable and synthesized (summarized the evidence relating to the review question).

The literature review reveals that there is lack of coherent definition for positioning, and there is no mutual agreement among marketing scholars and practitioners about the exact meaning of the concept. Therefore, comprehensive definition of positioning encompassing the five underlying positioning perspectives (competition; empty slot/mind; consumers’ perception, differentiation and competitive advantage) is suggested.

Research limitations/implications

This paper will be useful for academicians to analyze the current nature of academic research in this area and will provide an added advantage to managers to design and implement positioning strategies for their product/brands that will allow their organizations to gain competitive advantage. This study acknowledges limitations with respect to its exclusive search criteria, which might affect its generalizability.

Social implications

Position and positioning is of relevance in society in broad terms, e.g. in sports, politics and culture. Positioning strategy is discussed and implemented in different industries (business-to-business and consumer), for all kinds of brands (including, for instance, corporate brands) and for “brands” in the very widest sense (such as places or people).

Originality/value

This is the first systematic review of positioning that provides a detailed understanding of the current state of positioning research on a single platform and also draws a comprehensive positioning conceptualization.

Literature review
Product and positioning

Saqib, N. (2021), "Positioning – a literature review", PSU Research Review , Vol. 5 No. 2, pp. 141-169. https://doi.org/10.1108/PRR-06-2019-0016

Emerald Publishing Limited

Published in PSU Research Review . 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

1. Introduction

Positioning has received much attention over the past decade and has emerged as a highly influential marketing management paradigm. It is generally accepted that theoretically, practically and strategically positioning has become one of the key components in modern marketing management, both from the academic point of view ( Aaker and Shansby, 1982 ; Arnott , 1992, 1994 ; Blankson and Kalafatis, 2004 ; Boatswain, 2015 ; Crawford et al. , 1983 ; Day et al. ,1990 ; Diwan and Bodla, 2011 ; Fuchs and Diamantopoulos, 2012 ; Hooley et al. , 2012 ; Kapferer, 2012 ; Kotler, 2003 ; Porter, 1996 ; Sengupta, 2005 ; Soundararaj and Rengamani, 2002 ; Urde and Koch, 2014 ; Wind, 1982 ) and from the practical or business point of view ( Oglivy, 1983 ; Ries and Trout, 1981 ; Trout and Rivkin, 1996 ). The importance of positioning is emphasized by various authors ( Aaker and Shansby, 1982 ; Arnott, 1992 ; Blankson and Kalafatis, 2004 ; Boatswain, 2015 ; Diwan and Bodla, 2011 ; Sengupta, 2005 ) who note that positioning decisions determine the direction of a firm’s overall marketing strategy and that an effective marketing mix can only be developed once a company has crafted a distinct positioning strategy. By making the wrong positioning decision, a company could develop a misguided marketing mix and thus go down an undesirable path.

Moreover, because of its inevitable effect on profitability and long-term success of the firm it has been applied to consumer products ( Boatswain, 2015 ; Crawford, 1985 ; Diwan and Bodla, 2011 ; Fuchs and Diamantopoulos, 2010 ), industrial products ( Simkin et al. , 1985 ; Iyer et al. , 2018 ; Jalkala and Keranen, 2014 ; Pandaa et al. , 2018 ), financial services ( Burton and Easingwood, 2006 ; Easingwood and Mahajan, 1989 ; Kim and Mauborgne, 2000 ; Shostack, 1987 ), retail services ( Abril et al. , 2009 ; Auken and Lonial,1991 ; Corstjens and Doyle, 1989 ; Holmes, 1974 ) and tourism services ( Botha et al. , 1999 ; Gartner, 1989 ; Javalgi et al. , 1995 ; Pike and Page, 2014 ). Thus, the wide use of the positioning concept underlines its importance, usefulness and applicability.

The literature is full of statements emphasizing the importance of positioning. Aaker and Shansby (1982) claim that product positioning is so central and critical that it should be considered at the level of a mission statement. Dovel (1990) considers positioning as the essence of a business and backbone of a business plan. While Johansson and Thorelli (1985) , Keller (2009) , Perreault and McCarthy (1996) , Wilson and Fenwick (1978) and Wind (1980) believe that product positioning is the foundation of the firms marketing strategy. More specifically, Maggard (1976) points out that positioning can make a real contribution as a conceptual vehicle through which various marketing concepts (market segmentation, product differentiation, consumer preference, target market and the like) might be synchronized more effectively. Crawford (1985) believes that positioning is meant to drive the entire marketing programme of the organization and sees positioning as an ingredient of total strategy, not just an advertising ploy, product, brand, price, promotion and distribution must all be consistent with the positioning statement. Richarme (2007) argues that marketers should adopt positioning as their fifth “P” and use it in conjunction with the other four “Ps”. To a large degree, it is a higher-order “P” that rides on the base of the other four “Ps” and at the same time serves as a bridge to corporate strategy.

Ries and Trout (1986) acknowledge positioning to be the tool of competitive warfare. It helps customers to know the real differences among competing products ( DiMingo, 1988 ) and helps in creating a distinctive image of the brand in consumers’ minds ( Wells and Prensky, 1996 ) or brand value by shaping of customers perceptions ( Park et al. , 1986 ; Devlin et al. , 1995 ). Schouten and McAlexander (1989) contend that a key benefit of a successful positioning strategy is the partial insulation it gives from the competitive pressures of other firm. Therefore, positioning is an important source of competitive advantage ( Cronshaw et al. , 1990 ; Gwin and Gwin, 2003 ; Sengupta, 2005 ).

In today’s over-communicated and product-saturated consumer world, effective positioning is critical to brand success ( Marsden, 2002 ). There is a positive relationship between the positioning related decision and the brand success that is the success of brand moves around the pivot of positioning decision ( Fuchs and Diamantopoulos, 2010 ; Pham and Muthukrishnan, 2002 ; Punj and Moon, 2002 ). This not true for only a new brand, it is also of relevance for existing brands when enlarging one’s own market potential or when differentiating a brand from its competitors by repositioning ( Trommsdorf, 2002 ). Therefore, branding and positioning are interrelated and positioning is also the cornerstone of brand management ( Blankson and Kalafatis, 2007 ; de Chernatony, 2009 ; Esch, 2010 ).

Several authors ( Brooksbank, 1994 ; Day et al. , 1990 ; Fisher, 1991 ; Mazanec, 1995 ; Porter, 1996 ; Urban and Hauser, 1993 ) are of the view that long-term success of companies and their products depend on how well they are positioned in the marketplace. Positioning has an impact on important consumer-based outcome variables such as higher consumer loyalty, higher brand equity and value ( Hartmann et al. , 2005 ; Kalra and Goodstein, 1998 ; Knox, 2004 ), less customer vulnerability ( Romaniuk, 2001 ), positively shaped preferences and beliefs about brand value, greater willingness to search for the brand ( Schiffman and Kanuk, 2007 ; Trommsdorf and Paulssen, 2005 ; DiMingo, 1988 ), perceived price sensitivity ( Kalra and Goodstein, 1998 ), brand affect ( Jewell, 2007 ) and brand salience and recall ( Alba and Chattopadhyay, 1986 ).

In addition to non-financial customer-centred indicators, literature has examined positioning effectiveness in terms of financial performance indicators. Cravens and Piercy (2009) claim that effective positioning of the firm’s products is essential in gaining and sustaining superior performance. More specifically, several authors ( Blankson et al. , 2008 ; Blankson and Crawford, 2012 ; Brooksbank, 1994 ; Clement and Werner-Grotemeyer, 1990 ; Day et al. , 1990 ; Devlin et al. , 1995 ; Ennew and Mirza, 1995 ; Fisher, 1991 ; Kalafatis et al. , 2000 ; Kalra and Goodstein, 1998 ; Lee and Liao, 2009 ; Suzuki, 2000 ) claim that positioning has an impact on the financial performance of a company. Hence, the most important decision firm will ever make about its product is how it should position its product.

This article presents an exhaustive examination of research on positioning, particularly research that addresses the problem of conceptualizing and defining positioning. The basis of the article is a literature review of positioning research published in academic journals between 1969 and 2017. These articles range across such disciplines as marketing, strategic marketing and management. The study uses network analysis and text mining to identify how research defines positioning and discusses how the definitions of positioning have been developed on different perspectives.

2. Concept of positioning

The concept of positioning can be traced back to the 1960s when positioning was popularized in consumer product marketing by pioneers such as Alpert and Gatty (1969) they identified positioning as the differentiation of brands according to consumer perceptions they studied differences in consumers perceptions of the organizations products brands when these were positioned differently using technology as the differentiating dimension over similar products in the market place. However, contemporary writers on the subject of positioning ( Hooley et al. , 1998 ; Kotler, 2003 ; Blankson and Kalafatis, 2004 ) sustain Ries and Trout were among the first to define positioning and its origins lie in their article “Positioning is a game people play in today’s me-too market place” published in the Industrial Marketing journal in 1969. In their seminal article, they defined positioning as “as a strategy for ‘staking out turf’ or ‘filling a slot’ in the mind of target customers”. They then made the concept popular by publishing a series of articles in Advertising Age in 1972. “The Positioning Era Cometh”, a three-part article series published in Advertising Age magazine. The groundbreaking series illustrated perceptual positioning related to the concept of positioning and triggered a profound paradigm shift in how people viewed advertising and marketing and how firms advertised their products. Back in 1982, Ries and Trout published their book, Positioning: The Battle for Your Mind, which placed an entirely different spin on the concept. Ries and Trout (1986) , however, consider “Positioning within the context of perceiving the product, merchandise, a service, a company, an institution, or even a person”. They noted that positioning is not what is done to the product/service, but rather what is done to the mind of the customer/consumer. According to the authors, the key issue is to position the offering in the mind of the consumer/customer such that positioning shifts the importance of marketing from the product to the battle for your mind. They further stated that the basic approach of positioning is not to create something new and different, but to manipulate what’s already up there in the mind, to retie the connections that already exist.

2.1 Issues in positioning research

Although there is a vast amount of literature on positioning, and this inquisitive verb is in great favour among marketing experts, it is one of the most convoluted concept and is still subject to incomprehension. The concept of positioning is subject to considerable differences in interpretation ( Maggard, 1976 ). It is perhaps one of the thorniest and most complex concepts in marketing ( Bhat and Reddy, 1998 ). One of the reasons for this circumstance is the issue that there is no mutual agreement among marketing scholars and practitioners about the exact meaning of the concept. It is, however, important to note that the lack of coherent definitions ( Arnott, 1992 ; Blankson and Kalafatis, 2004 ; Crosier, 1981 ; DiMingo, 1988 ; Holmes, 1973 ; Maggard, 1976 and Smith and Lusch, 1976 ) and the difficulties involved in the implementation of the positioning process by practitioners ( de Chernatony, 1994 ) has invariably given rise to comments about the lack of appreciation of the positioning concept ( Pollay, 1985 ). Such dilemma was first expressed in the writings of Aaker and Shansby (1982) who stated that: “positioning means different things to different people”. To some, it means the segmentation decision. To others it is an image question. To still others it means selecting which product features to emphasize, and it still holds true today. The foregoing is summarized by Bainsfair (1990) who states that positioning is one of those words which everybody uses but few people understand. According to Rigger (1995) , the absence of a rigorous definition is inhibiting both practitioner and academic scholars in developing appropriate means of measuring the operationalization of positioning. Blankson and Kalafatis (2004) highlighted that there has been no single universally accepted definition of the concept of positioning. Specifically, the boundaries of the concept are often not clearly defined – the question what exactly falls under the scope of positioning has not been sufficiently answered in literature and is still subject to heavy debate in the marketing community. This state of affairs has given rise to several varying terms associated with the concept, i.e. positioning, position, product positioning, market positioning, etc., but as stated by Arnott (1994) , the various terminologies are simply “several sides of the same coin” and complement each other. Further according to Smith and Lusch (1976) , product position and brand position are different in scope; product position refers to the objective attributes in relation to other products and brand position refers to subjective attributes in relation to competing brands and this perceived image of the brand does not belong to the product but is the property of consumers perceptions of a brand. However, in broader terms, the terms product positioning and brand positioning usually mean the same thing ( Kazmi, 2007 ).

Urde and Koch (2014) in their review of positioning also claim that there is surprising vagueness of the concept, the lack of the holistic view and the dominance of the market oriented approach. According to Fuchs (2008) , positioning is an important, rich and a difficult area for future research. Marketers have developed an impressive variety of highly valuable research techniques and models in positioning research. However, on the conceptual and empirical front, research on positioning is scarce and lagging behind. Chew (2005) also claims that there are little theoretical/conceptual frameworks to guide positioning research and also, the extant positioning literature is largely normative and the issues discussed tend to be subjective. Nevertheless, more research is needed to obtain a better general understanding of the positioning concept. In the following section, the present review and analysis of definitions of positioning used in articles from 1969 to 2017 are presented.

3. Research method

This study used a systematic literature review to identify articles that define or conceptualize the concept of positioning. Systematic review has its origins in the medical field and has been developed through the Cochrane Collaboration. Some of the features of this approach have been adopted in the social sciences. More recently, the approach has been closely scrutinized to determine its appropriateness in the management field and conclusions indicate that “for practitioners/managers, systematic review helps develop a reliable knowledge base by accumulating knowledge from a range of studies ( Brown and Oplatka, 2006 ).

A systematic literature review is neither a formal full-length literature review nor a meta-analysis, as it conforms to a rigorous set of core principles. It has to be systematic (organized according to a method designed to address the review questions), transparent (explicitly stated), reproducible and updatable and synthesized (summarizes the evidence relating to the review question) ( Briner and Denyer, 2012 ). In other words, it is an essential tool for an evidence-based practice ( Briner and Denyer, 2012 ) that differs from traditional narrative reviews by adopting a replicable, scientific and transparent process ( Tranfield et al. , 2003 ). In line with MacInnis’s (2011) framework for conceptual contributions in marketing, our analysis involves identifying how entities (definitions) are different by revealing the underlying key perspectives in various positioning definitions. The present study examines not only how these definitions are different but also what they have in common.

3.1 Search strategy

The review identified relevant articles, which enabled a transparent, documented research process with criteria for including and excluding articles. The systematic review involved the following steps: State research questions develop guidelines for collecting literature, decide on inclusion and exclusion criteria, develop a comprehensive search plan for finding literature, develop a codebook for classifying and describing literature, code the literature and synthesize the literature ( Tranfield et al. , 2003 ; Witell et al. , 2016 ). The present study explores the various ways in which positioning has been defined in the literature to determine whether these definitions are different and also what they have in common.

The main search strategy identified research articles that defined the concept of positioning. To capture this, inclusion and exclusion criteria were developed. The initial inclusion criteria were broad to ensure that all relevant articles were identified, were peer-reviewed empirical or conceptual articles, were published in English and had the definition of positioning. To achieve the mentioned objective, five dominant academic databases including Scopus, Emerald, EBSCOS, Wiley Online Library and Science Direct were explored to identify articles on positioning. This paper reviews literature spanning from 1969 to 2017. Articles were identified in the “article title, abstract, and keywords” section of the said databases using keywords as “positioning”; “product positioning”; and “brand positioning”. To keep the search process specific to the objectives of this study, above keywords were used with the subject limits of “Business, management and accounting”; “Social Sciences”; and “Psychology”.

3.2 Sample selection

The initial search yielded 1,557 empirical or conceptual articles, 1,502 of which were in English. Figure 1 provides an overview of the selection process

All articles were scanned for relevance, which revealed two clear trends. First, although many of the articles used the term “positioning” in the abstract, few actually defined, conceptualized, or emphasized the term. Second, many of those articles that did specifically focus on positioning did not provide a specific definition of the concept. This lack of a definition provides further merit to our claim that a clear understanding of positioning is missing in the literature. In total, 354 articles that had a clear focus on positioning were selected for further analysis.

Two authors independently read the selected 354 articles to ensure that they met the inclusion criteria and to identify those that defined or conceptualized positioning. Those authors compared and discussed the results; in cases of disagreement, a third author was consulted. The final sample included 152 articles that provided at least one of the following: a clear definition, a conceptualization or an explicit referral to a specific definition or conceptualization of positioning.

3.3 Data analysis

To analyze the sample of articles, a combination of qualitative content analysis and quantitative analysis was used, which is a method for systematically and objectively evaluating texts ( Lombard et al. , 2002 ). The analysis was conducted in three steps – classification, coding and text analysis – using qualitative text mining ( Feldman and Sanger, 2007 ). Researchers often face the question of how to summarize text and determine what words and concepts are more significant than others. To go further than merely summarize, quantitative text analysis was used so that our review would be more than just descriptive statistics and qualitatively comparing and present definitions. Textmining, also known as text data mining or knowledge discovery from textual databases, refers to the process of extracting interesting and non-trivial patterns or knowledge from text documents ( Feldman and Sanger, 2007 ; Witell et al. , 2016 ). The rationale for this process builds on social network theory, which describes linkages among social entities or nodes in a network and the implications of these linkages and can be used on text to determine which words are significant ( Xie, 2005 ; Witell et al. , 2016 ).

All selected articles were downloaded and definitions were captured in digital plain-text format. Each article was then coded according to several predetermined variables, such as context, definitions, approach and type of study (for example, empirical, conceptual) to describe the characteristics of the sample. The study analyzed the specific definition of positioning offered in each article; by “cleaning” the definitions from “positioning is defined as […]” and focusing only on the words included in the actual definition of the concept. In addition, all common words such as “and” or “of” were removed. All text were stemmed, a procedure that involves reducing all words with the same stem to a common form (Lovins, 1968; Witell et al. , 2016 ). By using this method, the five key perspectives were identified in the pool of positioning definitions.

4. Analysis and results

This section begins by describing the year-wise and journal-wise distribution of the 47 identified journal articles. The section then describes the conceptualizations of positioning proposed by previous studies.

4.1 Journal-wise distribution of articles

This classification was done to observe where positioning research is being published. Articles related to positioning were found to be published in 33 reputed peer-reviewed journals in different time periods ( Table 1 ). This number is encouraging for academicians concerned about identifying and selecting a channel for their positioning manuscripts. Among these reputed journals, the dominant outlet of positioning research have been the Journal of Marketing , Journal of Product and Innovation Management and Business Horizon.

4.2 Year-wise distribution of articles

Articles were classified based on their year of publication from 1969 to 2019 to identify the longitudinal pattern of academic research. Figure 2 shows that the emergence of publications on positioning started in 1969, followed by steady growth up until 1989. From 1990 onwards, it is clear from the figure that there is exponential growth till 2009. However, the trend line also indicates a decreasing pattern after 2010, which implies that the literature on positioning is decreasing. After 2010, only six papers were published, which is the lowest number of papers as compared to previous years. This concludes that there is a need for increasing concerns and interests on the positioning topic.

4.3 Conceptualization of positioning in the marketing discipline

Most of the authors have based their definitions on Ries and Trouts (1969) original description of positioning, i.e. they have made minor adjustments, but constructed their basic reasoning upon the words of Ries and Trout.

There are many diverse interpretations of positioning as each author has preferred his/her own definition and has viewed positioning through different perspectives. The various perspectives from which positioning are viewed by most of the authors are listed in Table 2 . It provides a description of each perspective, and denotes how many times each perspective is found in the pool of positioning definitions.

Although these core perspectives all represent fundamental elements of the concept that delineates positioning, they were not all captured by every definition. Each perspective is discussed in turn.

4.3.1 P1 – Competition.

The “Competition” (P1) perspective as already mentioned is found in 56 of the 152 (39%) definitions listed in Appendix . This perspective underlies the idea that positioning helps in creating an image for the product in relative to separate or apart from competitors. The perspective (P1) is clearly articulated in several of the definitions, and in particular, that offered by Kapferer (2004) , “Positioning means emphasizing the distinctive characteristics that make it different from its competitors and appealing to the public”. Similarly, Kotler (2003) defined “Positioning as an act of designing a company’s offering and image so that they occupy a meaningful and distinct competitive position in the target market’s minds”. Many others (including Aaker and Shansby, 1982 ; Belch and Belch, 1995 ; Kotler and Anderson, 1996 ; Lovelock et al. , 2014 ; McIntyre, 1975 ) also included this perspective in their definitions.

4.3.2 P2 – Empty slot/mind.

The perspective “Empty slot/Mind” (P2) captures the idea that the act of positioning seeks to find and fill an empty slot/window in the minds of the prospective buyers. P2 is evident in several definitions as listed in Appendix . This perspective is also dominant as it was identified in 55 of the 152 (36%) positioning definitions. The “Empty slot/Mind” perspective is rooted in Ries and Trout’s (1969) seminal work on positioning and in particular, the popularity of the phrase “filling a slot in the minds of the target customers”. P2 is clearly asserted in several definitions, for instance, in Crawford et al. (1983) “Product positioning is the act of creating and altering product perceptions in customers’ minds”. Similarly, P2 is asserted in Wright’s (1997) definition stating “Positioning involves and owning a territory in the mind of the consumer it’s not just occupying the position, but owning it”, and in Boone and Kurtz’s (2009) definition stating “Positioning is placing at a certain point or location within a market in the minds of prospective buyers”.

4.3.3 P3 – consumers’ perception.

The perspective “Consumers’ perception” (P3) captures the idea that the act of positioning seeks to purposefully establish or evoke changes in consumers’ minds regarding offering. P3 is evident in several definitions as listed in Appendix . This perspective was identified in 34 of the 152 (22 %) positioning definitions. P3 is clearly expressed in several of the definitions, and in particular, that offered by Sengupta (1990) “Positioning is the concept of perceptual space and consumers mind is regarded as a geometric perceptual space with product categories and brands occupying different points in that space”. Similarly, P3 is expressed in Arnott (1994) “Positioning is the deliberate, proactive, iterative process of defining, modifying and monitoring consumer perceptions of a marketable object”.

4.3.4 P4 – Differentiation.

The “Differentiation” (P4) perspective is evidenced in 19 of the 152 (13%) positioning definitions as listed in Appendix . This perspective captures the notion that creating meaningful differentiation in an offering represents a key aspect of the concept of positioning. P4 is clearly captured in Myers (1996) definition “Positioning refers to the problem of differentiating one’s own product/service from other competing entries in the market place”. Likewise, Zikmund and D’Amico (1989) define “Positioning as a process to identify salient product characteristics that differentiate the brand from competitive brands”. P4 is consistent with the widely accepted view that differentiating an offering is a cornerstone to the positioning of a product, and therein, the success of the brand in the marketplace ( Wind, 1982 ; Bhat and Reddy, 1998 ; Hooley et al. , 1998 ).

4.3.5 P5 – Competitive advantage.

The “Competitive advantage” perspective, is evident only in 5 of the 152 (3%) of the definitions. This perspective underlies the idea that positioning helps in gaining a competitive advantage by implementing a value creating strategy not simultaneously being implemented by any current or potential competitors. P5 is clearly articulated in several of the definitions as listed in Appendix , and in particular, that offered by Palmer (1994) “Positioning is an attempt by the organization to distinguish its offerings from those of its competitors in order to give it a competitive advantage within the market”. Hooley et al. (1998) also articulated the same in their definition, “Positioning is the act of designing the company’s offering and image so that they occupy a meaningful and distinct competitive advantage”. P6 is consistent with the widely accepted view that a well-positioned brand enhances the overall competitiveness of the brand and generates a sustainable competitive advantage for the firm Aaker and McLoughlin (2007) , Blankson et al. (2013) , Ghodeshwar (2008) , Hooley et al. (2012) , Kotler (2003) , Porter (1996) . Accepting the view that competitive advantage represents the cornerstone of the positioning concept, the researcher found it surprising that only five definitions from the pool captured this perspective.

Based on (1) the core perspectives as discussed in the foregoing Section (2) the recognized need for an universally-accepted definition of positioning (3) the inconsistencies of the core meaning of the positioning construct and the researcher’s conviction that marketing research begins with a clear underlying meaning of the phenomenon in question, following definition of positioning encompassing the five underlying positioning perspectives is suggested:

Positioning is a strategy of finding the desired consumer perception of product/brand and filling an empty slot/window in the minds of the target customers by creating and communicating an image which differentiates its unique position from competitor to gain a competitive advantage in the market.

5. Research implications

On the theoretical front, this review makes multiple contributions. First, the study presents a comprehensive systematic review of 152 identified articles in the marketing discipline to reveal how researchers have explored this concept so far and presents a route for future research. Second, this review makes a contribution to understanding what positioning is. Specifically, this research contributes by identifying the key perspectives in definitions of positioning. Gaining insights from existing conceptualizations of the construct and supporting that by the theoretical foundations, a concise definition, broad in scope and perspective, has been derived, the suggested definition will provide clearer comprehension of the concept of positioning and a base on which to advance empirical research on positioning. Third, by providing the distribution schema of customer engagement articles based on different criteria, this study is believed to serve as a valuable tool for researchers to understand the current scenario of positioning research in the marketing discipline and aid in moving the field forward. On the practical front, this study exhibits the favorable outcomes organizations can derive by having a proper definition of positioning. Developing and implementing an organization’s positioning is seen as a crucial element of an organization’s strategic orientation to markets. The more an organization knows about positioning, the better adept it will be to enact so. Therefore, understanding positioning is imperative in that regard; this review will help organizations comprehend that better. Further, understanding how various perspectives are connected with positioning will help managers to design and implement positioning strategies for their products/brands and allow organizations to gain competitive advantage.

6. Conclusion and limitations

The goal of this systematic review was to review state-of-the-art literature on product/brand positioning to re-examine the positioning concept and developing a more comprehensive definition from a theoretical viewpoint. Positioning has been defined in several nuanced ways. This fragmentation can be misleading, and a systematic review can provide a useful analysis to highlight the fragmentation and propose boundaries to better define positioning. However, a systematic review also has its own methodological limitations, including the level of precision. To tackle this limitation, we started broadly and then focused on specific databases and research terms. Although some dimensions might have been missed, we believe our conclusions obtained a reasonable level of redundancy in the databases that we used for this study. We also wanted to contribute to the literature and hope that further research on this important strategic concept will refine and clarify our results. This systematic review presented the results of an analysis and synthesis of the broader positioning literature. A review of 152 published positioning studies from the literatures identified the various perspectives from which positioning are viewed by most of the authors. The five most frequently identified perspectives were competition, empty slot/mind, consumers’ perception, differentiation and competitive advantage. Importantly, the findings of this review confirm that despite the relatively established body of literature, there is there is lack of coherent definition for positioning, and there is no mutual agreement among marketing scholars and practitioners about the exact meaning of the concept.

Flow diagram of article selection process

Number of positioning (definition) related articles (1969–2017)

Journal-wise distribution of articles

Core perspectives of positioning

Overview of positioning definitions

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Internet marketing: a content analysis of the research

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Published: 31 January 2013
Volume 23 , pages 177–204, ( 2013 )

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J. Ken Corley II 1 ,
Zack Jourdan 2 &
W. Rhea Ingram 2

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The amount of research related to Internet marketing has grown rapidly since the dawn of the Internet Age. A review of the literature base will help identify the topics that have been explored as well as identify topics for further research. This research project collects, synthesizes, and analyses both the research strategies (i.e., methodologies) and content (e.g., topics, focus, categories) of the current literature, and then discusses an agenda for future research efforts. We analyzed 411 articles published over the past eighteen years (1994-present) in thirty top Information Systems (IS) journals and 22 articles in the top 5 Marketing journals. The results indicate an increasing level of activity during the 18-year period, a biased distribution of Internet marketing articles focused on exploratory methodologies, and several research strategies that were either underrepresented or absent from the pool of Internet marketing research. We also identified several subject areas that need further exploration. The compilation of the methodologies used and Internet marketing topics being studied can serve to motivate researchers to strengthen current research and explore new areas of this research.

A Backward Glance of who and what Marketing Scholars have Been Researching, 1977–2002

Marketing Research Directions in the 80’s and 90’s

Marketing Theory: The Present Stage Of Development

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Introduction

In the early years of the Internet Age, the potential of using the Internet as a distribution channel excited business managers who believed this tool would boost sales and increase organizational performance (Hansen 1995 ; Westland and Au 1997 ). These believers suspected an online presence could offer advantages to their customers, while providing a shopping experience similar to the traditional bricks-and-mortar store (Jarvenpaa and Todd 1996 ). The advantages included providing around the clock access for customers, reducing geographic boundaries to provide access to new markets, and enabling immediate communication with customers.

The prediction of an explosion of online shopping became a marriage between information technology experts and marketing professionals. Most would believe the information technology researchers were studying the Internet technology and its advantages, while the marketers were focused on the consumer’s use of the technology. As technology advanced, more marketing activities emerged to market goods and services via the Internet. Today, Internet marketing is defined as “the use of the Internet as a virtual storefront where products are sold directly to the customer” (Kiang et al. 2000 , p. 383), or another view includes “the strategic process of creating, distributing, promoting, and pricing products for targeted customers in the virtual environment of the Internet” (Pride et al. 2007 ). This research attempts to categorize the various Internet marketing activities in a broad context including strategies such as customer relationship management (Hwang 2009 ), electronic marketplaces (Novak and Schwabe 2009 ), online auctions (Loebbecke et al. 2010 ), and electronic branding (Otim and Grover 2010 ) in tandem with unique IS issues including web site evaluation (Chiou et al. 2010 ), piracy (Smith and Telang 2009 ), security (Ransbotham and Mitra 2009 ), and technology architecture (Du et al. 2008 ).

With concepts as varied as this in one research domain, a periodic review is necessary to discover and explore new technologies such as mobile banking (Sripalawat et al. 2011 ), virtual worlds (Sutanto et al. 2011 ), and social media (de Valck et al. 2009 ) as they emerge on the Internet marketing landscape. The following sections of the paper will examine the current literature to determine what is known about the concept of Internet marketing. First, a description of the methodology for the analysis of the Internet marketing research is presented. This is followed by the results including an analysis of a smaller sample of the Internet marketing research in the top Marketing journals. Finally, the research is summarized with a discussion of the limitations of this project and suggestions for future research.

Methodology

The approach to this analysis of the Internet marketing research is to first identify trends in the Information System (IS) literature. Specifically, we wished to capture the trends pertaining to (1) the number and distribution of Internet marketing articles published in the leading journals, (2) methodologies employed in Internet marketing research, and (3) the research topics being published in this area of research. During the analysis of the literature, we attempted to identify gaps and needs in the research and therefore discuss a research agenda which allows for the progression of research (Webster and Watson 2002 ). In short, we hope to paint a representative landscape of the current Internet marketing literature base in IS in order to influence the direction of future research efforts in this important area of study.

In order to examine the current state of research on Internet marketing, the authors conducted a literature review and analysis in three phases: Phase 1 accumulated a representative pool of articles; Phase 2 classified the articles by research method; and, Phase 3 classified the research by research topic. Each of the three phases is discussed in the following paragraphs.

Phase 1: accumulation of article pool

We used the Thomson Reuters Web of Science (WoS) citation database and Google Scholar to search for research articles with a focus on Internet marketing. The search parameters were constrained based on (a) a list of top ranked journals, (b) a specific time range, and (c) key search terms.

First, the researchers chose to use the top 30 journals from Peffers and Tang’s ( 2003 ) IS journals ranking (see Table 1 ). Peffers and Tang’s ( 2003 ) ranking of ‘pure’ IS journals was adopted for this study because it was based on the responses of IS researchers who were asked to rank journals by their “relative value to the researcher and the audience as an outlet for IS research.” In Peffers and Tang’s ( 2003 ) original ranking scheme two journals, ‘Communications of the Association of Information Systems’ and ‘Information and Management,’ tied for fifth place. Peffers and Tang resolved this issue by ranking both journals in the fifth position skipping the rank of the sixth position. As noted in Table 1 , 7 of the top 30 journals were not listed in the WoS database. Consequently, all 30 journals were searched using Google Scholar and only 23 journals were searched using the WoS database. The search parameters were further constrained to a specific timeframe.

Electronic commerce and Internet marketing did not exist prior to the widespread adoption and dissemination of the public Internet and the Worldwide Web (WWW). Therefore, the search parameters were further constrained based on the historical timeframe in which technologies capable of facilitating the development of e-commerce were first introduced. The graphical user interface based browser known as Netscape Navigator was launched as a free download for public use in 1994. Many experts identify the launch of Netscape Navigator as the historical event leading to the global public’s widespread adoption and use of the Internet and the World Wide Web (WWW) (Friedman 2006 ). Therefore, the search parameters for both WoS and Google Scholar were constrained to time period of 1994 through August of 2011.

The final constraint was based on the key search term “Internet Marketing.” In both WoS and Google Scholar the search engine scanned for the term ‘Internet Marketing’ and close variations of this term found in the title, abstract, and keywords of articles published in the top 30 IS journals between January of 1994 and August of 2011 when the search was executed. There was considerable overlap in the pool of articles returned from the two search engines (WoS and Google Scholar). Once duplicate entries and non-research articles (book reviews, editorials, commentary, etc.) were removed 453 articles remained in the composite data pool. The researchers then reviewed each article and identified 42 articles that were unrelated to the topic of Internet marketing. These 42 articles represented false positives returned from the WoS and Google Scholar search engines and were subsequently removed leaving 411 articles in the final composite article data pool for analysis.

Phase 2: classification by research strategy

Once the researchers identified the articles for the final data pool, each article was examined and categorized according to its research strategy. Due to the subjective nature of research strategy classification, content analysis methods were used for the categorization process. Figure 1 illustrates steps in the content analysis process adapted from Neuendorf ( 2002 ) and successfully employed by several similar research studies (Corley et al. 2011 ; Cumbie et al. 2005 ; Jourdan et al. 2008 ). First, the research categories were adopted from Scandura and Williams ( 2000 ) (see Table 2 ), who extended the research strategies initially described by McGrath ( 1982 ). Specifically, nine categories of research strategies were selected including: Formal theory/literature reviews, sample survey, laboratory experiment, experimental simulation, field study (primary data), field study (secondary data), field experiment, judgment task, and computer simulation.

Overview of literature analysis

Second, to guard against the threats to reliability (Neuendorf 2002 ), we performed a pilot test on articles meeting the search parameters from other top journals. That is, the articles used in the pilot test (a) were not part of the data set generated in Phase 1, and (b) the data generated from the pilot test were not included in the final data analysis for this study. Researchers independently categorized the articles in the pilot test based on the best fit among the nine research strategies. After all articles in the pilot test were categorized, the researchers compared their analyses. In instances where the independent categorizations did not match the researchers re-evaluated the article collaboratively by reviewing the research strategy definitions, discussing the disagreement thoroughly, and collaboratively assigning the article to a single category. This process allowed the researchers to develop a collaborative interpretation of the research strategy definitions. Simply stated, this pilot test served as a training session for accurately categorizing the articles for this study with respect to research strategy.

Each research strategy is defined by a specific design approach and each is also associated with certain tradeoffs that researchers must make when designing a study. These tradeoffs are inherent flaws that limit the conclusions that can be drawn from a particular research strategy. These tradeoffs refer to three aspects of a study that can vary depending on the research strategy employed. These variable aspects include: generalizability from the sample to the target population (external validity); precision in measurement and control of behavioural variables (internal and construct validity); and the issue of realism of context (Scandura and Williams 2000 ).

Cook and Campbell ( 1976 ) stated that a study has generalizability when the study has external validity across times, settings, and individuals. Formal theory/literature reviews and sample surveys have a high degree of generalizability by establishing the relationship between two constructs and illustrating that this relationship has external validity. A research strategy that has low external validity but high internal validity is the laboratory experiment. In the laboratory experiment, where the degree of measurement precision is high, cause and effect relationships may be determined, but these relationships may not be generalizable for other times, settings, and populations. While the formal theory/literature reviews and sample surveys have a high degree of generalizability and the laboratory experiment has a high degree of precision of measurement, these strategies have low degree of contextual realism. The only two strategies that maximize degree of contextual realism are field studies that use either primary or secondary data because the data is collected in an organizational setting (Scandura and Williams 2000 ).

The other four strategies maximize neither generalizability, nor degree of precision in measurement, nor degree of contextual realism. This point illustrates the futility of using only one strategy when conducting Internet marketing research. Because no single strategy can maximize all types of validity, it is best for researchers to use a variety of research strategies. Table 2 contains an overview of the nine strategies and their ranking on the three strategy tradeoffs (Scandura and Williams 2000 ).

Two coders independently reviewed and classified each article according to research strategy. Only a few articles were reviewed at one sitting to minimize coder fatigue and thus protect intercoder reliability (Neuendorf 2002 ). Upon completion of the independent classification, a tabulation of agreements and disagreements were computed, intercoder crude agreement (percent of agreement) was 91.8 % percent, and intercoder reliability using Cohen’s Kappa (Cohen 1960 ) was calculated ( k = 0.847). These two calculations were well within the acceptable ranges for intercoder crude agreement and intercoder reliability (Neuendorf 2002 ). The reliability measures were calculated prior to discussing disagreements as mandated by Weber ( 1990 ). If the original reviewers did not agree on how a particular article was coded, an additional reviewer arbitrated the discussion of how the disputed article was to be coded. This process resolved the disputes in all cases.

Phase 3: categorization by internet marketing research topic

Typically the process of categorizing research articles by a specific research topic involves an iterative cycle of brainstorming and discussion sessions among the researchers. This iterative process helps to identify common themes within the data pool of articles. Through the collaborative discussions during this process researchers can synthesize a hierarchical structure within the literature of overarching research topics and more granular level subtopics. The final outcome is a better understanding of the current state of a particular stream of research. This iterative process was modified for this specific study on the topic of Internet marketing.

During the initial stages of the current project the researchers began investigating tentative outlets for publishing a literature review on the topic of Internet marketing. A special call for papers (CFP) on the topic of Internet marketing from the journal ‘Electronic Marketing’ was identified as a potential target journal by one of the authors. Further investigation revealed that the editors had outlined six specific research topic categories for the special CFP including: Business Models of Online Marketing, The Future of Search Strategies, The Internet Advertising Landscape, Commercial Exploitation of Web 2.0 in Consumer Marketing and in an Organizational Context, Evaluation of Online Performance, and Other Topics. Each of these six research topics was accompanied by a general definition and a few examples. The researchers adopted these six research topics to categorize the articles in the data pool.

A second pilot study was performed mirroring the first pilot test as a means of training for categorizing articles by research topic. Researchers independently categorized the articles in the pilot test based on the best fit among the six research topics. After all articles in the pilot test were categorized, the researchers compared their analyses. In instances where the independent categorizations did not match, the researchers re-evaluated the article collaboratively by reviewing the research category definitions, discussing the disagreement thoroughly, and collaboratively assigning the article to a single category. This process allowed the researchers to develop a collaborative interpretation of the research topic definitions (see Table 3 ).

Once we established the category definitions, we independently placed each article in one Internet marketing category. As before, we categorized only a few articles at a time to minimize coder fatigue and thus protect intercoder reliability (Neuendorf 2002 ). Upon completion of the classification process, we tabulated agreements and disagreements, intercoder crude agreement (percent of agreement) was 86.2 %, and intercoder reliability using Cohen’s Kappa (Cohen 1960 ) for each category was calculated ( k = .08137). Again, the latter two calculations were well within the acceptable ranges (Neuendorf 2002 ). We again calculated the reliability measures prior to discussing disagreements as mandated by Weber ( 1990 ). If the original reviewers did not agree on how a particular article was coded, a third reviewer arbitrated the discussion of how the disputed article was to be coded. This process also resolved the disputes in all cases.

In order to identify gaps and needs in the research (Webster and Watson 2002 ), we hope to paint a representative landscape of the current Internet marketing literature base in order to influence the direction of future research efforts in this important area of study. In order to examine the current state of this research, the authors conducted a literature review and analysis in three phases. Phase 1 accumulated a representative pool of Internet marketing articles, and the articles were then analyzed with respect to year of publication and journal. Phase 2 contains a short discussion of the research strategies set forth by Scandura and Williams ( 2000 ) and the results of the classification of the articles by those research strategies. Phase 3 involved the creation and use of six Internet marketing research topics, a short discussion of each topic, and the results of the classification of each article within the research topics. These results are discussed in the following paragraphs.

Results of phase 1

Using the described search criteria within the selected journals, we collected a total of 411 articles (For the complete list of articles in our sample, see Appendix A .) In phase 1, we further analyzed the articles’ year of publication and journal. Figure 2 shows the number of articles per year in our sample. Please note that 2011 only represents articles acquired using WoS and Google Scholar search engines which were available at the time (August 2011) the search was conducted. There is a general increasing trend over the 18 year period, but no articles were found to be published in 1994 & 1996. The year 2010 shows the most activity with 52 articles (12.7 %). With Internet marketing issues becoming ever more important to researchers and practitioners, this comes as no surprise. Understanding 2011 was only a partial year in our sample, we were not concerned by the difference in quantity of publications over time.

Number of Internet Marketing Articles Published Per Year

In order to identify the research strategies used by Internet marketing research articles in the top 30 Information Systems (IS) journals in our sample, Table 4 was created to show the number of Internet marketing articles in each journal broken down by research strategy. This table illustrates the high level of Internet marketing publications that use the Formal Theory/Literature Review, Sample Survey, Field Study – Primary, and Field Study – Secondary research strategies. This indicates a body of research that is still in the exploratory stages. This table also illustrates the proclivity of some journals to accept certain research strategies over others. For example, the journals Decision Support Systems , International Journal of Electronic Commerce , and Journal of Management Information Systems had articles in this data set using seven of the nine research strategies. With this information, researchers that favour certain research strategies can target their research papers to journals that favour these strategies.

Number of Internet Marketing Articles Published in Each Research Strategy Category

Results of phase 2

The results of the categorization of the 411 articles according to the nine research strategies described by Scandura and Williams ( 2000 ) are summarized in Fig. 3 and Table 5 . Of the 411 articles, 110 articles (26.8 %) were classified as Formal Theory/Literature review making it the most prevalent research strategy. This was followed by Sample Survey with 94 articles (or 22.9 %), Field Study – Secondary Data with 91 articles (22.1 %), Field Study – Primary Data with 66 articles (16.1 %), and Computer Simulation with 25 articles (6.1 %). These five research strategies composed 94 % of the articles in the sample. No articles were classified as a Judgment Task. So, the remaining three research strategies represented the remaining six percent of the sample which included Lab Experiment with 11 articles (2.7 %), Field Experiment with 11 articles (2.7 %), and Experimental Simulation with 3 articles (0.7 %).

Further analysis showing the research strategies over the 18 year period from 1994 to August 2011 (Table 6 ) illustrates that Formal Theory/Literature Review, Sample Survey, Field Study – Secondary Data, and Field Study – Primary Data are represented in almost every year of the timeframe. No articles were found in the years 1994 & 1996, and only one article was found in 1995. These four strategies are exploratory in nature and indicate the beginnings of a body of research (Scandura and Williams 2000 ). Further categorization and analysis of the articles with respect to Internet marketing topic categories was conducted in the third phase of this research project.

Results of phase 3

Table 7 shows the number of articles per Internet marketing research topic category. These six categories provided a topic area classification for all of the 411 articles in our research sample. Of the 411 articles, 41.1 % were classified as ‘Business Models of Online Marketing’ making it the most prevalent Internet marketing topic category. This category was followed by ‘The Internet Advertising Landscape’ (22.4 %), ‘Evaluation of Online Performance’ (16.5 %), and ‘Other’ (10.0 %). These four research strategies accounted for 90 % of the articles in the sample. The topic categories titled ‘Commercial Exploitation of Web 2.0 in Consumer Marketing and in an Organizational Context’ and ‘The Future of Search Strategies’ represented the remaining six per cent (5.8 %) and four percent (4.1 %) of the articles. This illustration of the share of Internet marketing research that is represented by each category reveals the amount of attention topic categories of Internet marketing research have historically received among the top 30 IS journals.

By plotting Internet marketing research topics against research strategies (Table 8 ), many of the gaps in Internet marketing research are exposed. The gaps are at the intersection of less used methodologies (Judgement Task, Experimental Simulation, Lab Experiment) and less studied domains in Internet marketing (Search Strategies and Web 2.0). We believe these gaps exist for two reasons. First, some of these research strategies are not prevalent in IS research, and some top IS journals do not accept papers that use unusual research strategies. So, researchers avoid unorthodox strategies. The reason some of these categories have not been studied is because they represent relatively new phenomena, and the research has not caught up with the business reality. The great news for researchers interested in Internet marketing is that this domain should provide research opportunities for years to come. To better illustrate the categorization process, Table 9 presents a sample of articles noting their corresponding research strategy and research topic. These articles were randomly selected as typical examples and are not meant to serve as hallmarks of a particular research strategy or research topic within Internet marketing research.

About half (49 %) of the journal articles in this study use the Formal Theory/Literature Review and Sample Survey research strategies indicating the exploratory nature of the current research. We speculate the strategies used to study these topics were prevalent for several reasons. First, these strategies are the most appropriate for the early stages of research. In these exploratory years of Internet marketing research, formal theory/literature reviews are appropriate in order to determine what other strategies are being used in the research, define the topics under investigation, and find research in reference disciplines that are conducting similar research. Second, many researchers in business schools may prefer to administer sample surveys and field studies instead of laboratory experiment, experimental simulation, judgment task, and computer simulation because of the preferences for certain research strategies in the top journals in Information Systems and Marketing. Finally, organizations are less likely to commit to certain strategies (i.e. primary & secondary field studies and field experiments) because these strategies are more expensive for the organizations. These types of research strategies are very labour intensive to the organization being studied because records will need to be examined, personnel will need to be interviewed, and senior managers will be required to devote large amounts of their expensive time to help facilitate the research project. It is interesting to note that many of the articles coded as Field Study – Secondary and Computer Simulation used historical auction and pricing data freely available from the World Wide Web to avoid this issue.

Investigating the marketing literature

In order to investigate the Internet marketing research being conducted in the top Marketing Journals, we also performed a smaller literature review using the top five ranked marketing research journals following the same methodology previously described for the top 30 ranked IS journals. This list was compiled from three recent marketing journal rankings (Hofacker et al. 2009 ; Moussa and Touzani 2010 ; and Polonsky and Whitelaw 2006 ). The data pool included 24 articles, and after screening out irrelevant articles (book reviews, opinion pieces, etc.) the remaining 22 articles were categorized by research strategy and research topic (see Appendix B ). Upon completion of the categorization process, we tabulated agreements and disagreements. Intercoder crude agreement (percent of agreement) was 95.4 % for research strategy and 90.9 % for research topic. Cohen’s Kappa could not be calculated because the sample size was too small. These two calculations were well within the acceptable ranges (Neuendorf 2002 ). The results of the literature review of the top five marketing journals are displayed in Tables 10 and 11 .

The number of articles published on the topic of Internet marketing in each of the top five ranked marketing journals is presented in Table 10 . It is interesting to note that no articles were found in Journal of Consumer Research while 16 of the 22 (72.7 %) articles in the data pool were published in Marketing Science . This could indicate (a) Marketing Science is a top outlet for Internet marketing research or (b) the other Marketing journals use keywords other than “Internet marketing” to classify this area of research. The number of articles categorized based on both research strategy and research topic is presented in Table 11 . The three research strategies with the largest number of articles among the top five marketing journals were “Formal Theory / Lit Review” (45.5 %), “Field Study - Secondary” (27.3 %), and “Field Study – Primary” (18.2 %). This indicates, like the research published in the top IS journals, the Internet marketing research published in the top marketing journals is also still in the exploratory stages.

Fourteen of the twenty-two articles (63.6 %) were categorized within the research topic labelled “the Internet Advertising Landscape” while no articles were categorized within the research topics “Commercial Exploitation of Web 2.0” or “Evaluation of Online Performance.” In contrast to the analysis of the top thirty ranked IS journals in which the top three research topics were “Business Models of Online Marketing” (41.1 %), “the Internet Advertising Landscape” (22.4 %), and Evaluation of Online Performance (16.5 %); the top three research topics within the top five marketing journals were “the Internet marketing Landscape” (63.6 %), “Business Models of Online Marketing” (13.6 %), and “Other Topics” (13.6 %). Due to the small number of articles in the sample, it is difficult to make any statements regarding trends in the Internet marketing research in the top Marketing journals.

Limitations and directions for future research

The current analysis of the Internet marketing literature is not without limitations and should be offset with future efforts. In summary, this literature review highlights the upward trend of Internet marketing research but also the limitations of both the research strategies employed and the topics investigated. The authors would suggest future literature reviews should expand article searches to full article text searches, search a broader domain of research outlets, and include other Internet marketing related search terms. Our literature analysis is meant to serve as a representative sample of articles and not a comprehensive or exhaustive analysis of the entire population of articles published on the topic of ‘Internet marketing.’ To further investigate this body of research, future research studies could explore the diversity of the Internet marketing research domain (Lee et al. 2007 ) or revisit Ngai and Wat’s ( 2002 ) electronic commerce literature review to assess the progress of that research stream. Other studies could take a more in depth look at the various business models or Internet advertising strategies associated with Internet marketing by reviewing the literature in areas such as electronic auctions, search strategies, social media, e-tailing, and various other research domains.

As Internet marketing continues to grow, future studies should consider the role of research relative to generalizability, precision of measure, and realism of context. Future research efforts should adopt more precise measures of what is occurring in this domain. Much of the research in our sample reports the new technologies and issues in Internet marketing without attempting to explain the fundamental issues of IS research. This is to be expected as this research domain appears to still be in the exploratory stages. For researchers to continue to attempt to answer the important questions in Internet marketing, future studies need to employ a wider variety of research strategies to investigate these important issues. Scandura and Williams ( 2000 ) stated that looking at research strategies employed over time by triangulation in a given subject area can provide useful insights into how theories are developing. In addition to the lack of variety in research strategy, very little triangulation has occurred during the timeframe used to conduct this literature review. This absence of coordinated theory development causes the research in Internet marketing to appear haphazard and unfocused.

However, the good news is that many of the research strategies and topics in this research are available for future research efforts. Of particular interest to researchers and practitioners would be studies observing consumer behaviour in real time using lab and field experiments or measuring purchasing behaviour from using stored click stream data in a secondary field study. We encourage researchers in fields of IS and Marketing to continue developing the body of research on this important topic using cross-disciplinary teams composed of researchers from business and the behavioural sciences. In addition, future studies could consider the six Internet marketing categories with respect to the research strategies. More specifically, each ‘zero’ appearing in Tables 8 and 11 represent gaps in the literature which provide countless opportunities for researchers to build upon the current body of published research. With this in mind, we hope this research analysis lays a foundation for developing a more complete body of knowledge relative to Internet marketing research within the fields of Information Systems and Marketing.

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J. Ken Corley II

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Responsible Editor: Christopher Patrick Holland

Appendix A – data sample (411 information systems articles)

Abbasi, A., Chen, H. C., & Nunamaker, J. F. (2008). Stylometric Identification in Electronic Markets: Scalability and Robustness. Journal of Management Information Systems, 25 (1), 49–78. doi: 10.2753/mis0742-1222250103

Adam, S. (2002). A model of Web use in direct and online marketing strategy. Electronic Markets, 12 (4), 262–269.

Albrecht, C. C., Dean, D. L., & Hansen, J. V. (2005). Marketplace and technology standards for B2B e-commerce: progress, challenges, and the state of the art. Information & Management, 42 (6), 865–875. doi: 10.1016/j.im.2004.09.003

Allen, G., & Wu, J. A. (2010). How well do shopbots represent online markets? A study of shopbots’ vendor coverage strategy. European Journal of Information Systems, 19 (3), 257–272. doi: 10.1057/ejis.2010.6

Amblee, N., & Bui, T. (2008). Can brand reputation improve the odds of being reviewed on-line? International Journal of Electronic Commerce, 12 (3), 11–28.

Amir, Y., Awerbuch, B., & Borgstrom, R. S. (2000). A cost-benefit framework for online management of a metacomputing system. Decision Support Systems, 28 (1–2), 155–164. doi: 10.1016/s0167-9236(99)00081-0

Anckar, B., & Walden, P. (2000). Destination Maui? An exploratory assessment of the efficacy of self-booking in travel. Electronic Markets, 10 (2), 110–119.

Animesh, A., Ramachandran, V., & Viswanathan, S. (2010). Quality Uncertainty and the Performance of Online Sponsored Search Markets: An Empirical Investigation. Information Systems Research, 21 (1), 190–201. doi: 10.1287/isre.1080.0222

Animesh, A., Viswanathan, S., & Agarwal, R. (2011). Competing “Creatively” in Sponsored Search Markets: The Effect of Rank, Differentiation Strategy, and Competition on Performance. Information Systems Research, 22 (1), 153–169.

Antony, S., Lin, Z. X., & Xu, B. (2006). Determinants of escrow service adoption in consumer-to-consumer online auction market: An experimental study. Decision Support Systems, 42 (3), 1889–1900. doi: 10.1016/j.dss.2006.04.012

Apigian, C. H., Ragu-Nathan, B. S., & Ragu-Nathan, T. (2006). Strategic profiles and Internet Performance: An empirical investigation into the development of a strategic Internet system. Information & Management, 43 (4), 455–468.

Aron, R., & Clemons, E. K. (2001). Achieving the optimal balance between investment in quality and investment in self-promotion for information products. Journal of Management Information Systems, 18 (2), 65–88.

Arunkundram, R., & Sundararajan, A. (1998). An economic analysis of electronic secondary markets: installed base, technology, durability and firm profitability. Decision Support Systems, 24 (1), 3–16. doi: 10.1016/s0167-9236(98)00059-1

Ayanso, A., & Yoogalingam, R. (2009). Profiling Retail Web Site Functionalities and Conversion Rates: A Cluster Analysis. International Journal of Electronic Commerce, 14 (1), 79–113. doi: 10.2753/jec1086-4415140103

Ba, S., Stallaert, J., Whinston, A. B., & Zhang, H. (2005). Choice of transaction channels: The effects of product characteristics on market evolution. Journal of Management Information Systems, 21 (4), 173–197.

Bai, X. (2011). Predicting consumer sentiments from online text. Decision Support Systems, 50 (4), 732–742. doi: 10.1016/j.dss.2010.08.024

Bakos, J. Y., & Nault, B. R. (1997). Ownership and investment in electronic networks. Information Systems Research, 8 (4), 321–341. doi: 10.1287/isre.8.4.321

Bakos, Y., & Katsamakas, E. (2008). Design and ownership of two-sided networks: Implications for Internet platforms. Journal of Management Information Systems, 25 (2), 171–202. doi: 10.2753/mis0742-1222250208

Bakos, Y., Lucas, H. C., Oh, W., Simon, G., Viswanathan, S., & Weber, B. W. (2005). The impact of e-commerce on competition in the retail brokerage industry. Information Systems Research, 16 (4), 352–371. doi: 10.1287/isre.1050.0064

Bampo, M., Ewing, M. T., Mather, D. R., Stewart, D., & Wallace, M. (2008). The effects of the social structure of digital networks on viral marketing performance. Information Systems Research, 19 (3), 273–290.

Bapna, R., Chang, S. A., Goes, P., & Gupta, A. (2009). Overlapping online auctions: empirical characterization of bidder strategies and auction prices. MIS Quarterly, 33 (4), 763–783.

Bapna, R., Goes, P., & Gupta, A. (2003). Replicating online Yankee auctions to analyze auctioneers’ and bidders’ strategies. Information Systems Research, 14 (3), 244–268. doi: 10.1287/isre.14.3.244.16562

Bapna, R., Jank, W., & Shmueli, G. (2008). Price formation and its dynamics in online auctions. Decision Support Systems, 44 (3), 641–656. doi: 10.1016/j.dss.2007.09.004

Barrot, C., Albers, S., Skiera, B., & Schafers, B. (2010). Vickrey vs. eBay: Why Second-Price Sealed-Bid Auctions Lead to More Realistic Price-Demand Functions. International Journal of Electronic Commerce, 14 (4), 7–38. doi: 10.2753/jec1086-4415140401

Basu, A., & Muylle, S. (2003). Online support for commerce processes by web retailers* 1. Decision Support Systems, 34 (4), 379–395.

Beech, J., Chadwick, S., & Tapp, A. (2000). Scoring with the Net-the Cybermarketing of English Football Clubs. Electronic Markets, 10 (3), 176–184.

Belanger, F., Hiller, J. S., & Smith, W. J. (2002). Trustworthiness in electronic commerce: the role of privacy, security, and site attributes. The Journal of Strategic Information Systems, 11 (3–4), 245–270.

Bell, D., de Cesare, S., Iacovelli, N., Lycett, M., & Merico, A. (2007). A framework for deriving semantic web services. Information Systems Frontiers, 9 (1), 69–84. doi: 10.1007/s10796-006-9018-z

Benbunan-Fich, R., & Fich, E. M. (2004). Effects of Web traffic announcements on firm value. International Journal of Electronic Commerce, 8 (4), 161–181.

Bergen, M. E., Kauffman, R. J., & Lee, D. (2005). Beyond the hype of frictionless markets: Evidence of heterogeneity in price rigidity on the Internet. Journal of Management Information Systems, 22 (2), 57–89.

Bhargava, H. K., & Choudhary, V. (2004). Economics of an information intermediary with aggregation benefits. Information Systems Research, 15 (1), 22–36. doi: 10.1287/isre.1040.0014

Bhatnagar, A., & Papatla, P. (2001). Identifying locations for targeted advertising on the Internet. International Journal of Electronic Commerce, 5 (3), 23–44.

Bhattacharjee, S., Gopal, R., Lertwachara, K., & Marsden, J. R. (2006). Whatever happened to payola? An empirical analysis of online music sharing. Decision Support Systems, 42 (1), 104–120.

Blount, Y. (2011). Employee management and service provision: a conceptual framework. Information Technology & People, 24 (2), 134–157. doi: 10.1108/09593841111137331

Bock, G. W., Lee, S. Y. T., & Li, H. Y. (2007). Price comparison and price dispersion: products and retailers at different Internet maturity stages. International Journal of Electronic Commerce, 11 (4), 101–124.

Bockstedt, J. C., Kauffman, R. J., & Riggins, F. J. (2006). The move to artist-led on-line music distribution: A theory-based assessment and prospects for structural changes in the digital music market. International Journal of Electronic Commerce, 10 (3), 7–38. doi: 10.2753/jec1086-4415100301

Bolton, G., Loebbecke, C., & Ockenfels, A. (2008). Does competition promote trust and trustworthiness in online trading? An experimental study. Journal of Management Information Systems, 25 (2), 145–169. doi: 10.2753/mis0742-1222250207

Browne, G. J., Durrett, J. R., & Wetherbe, J. C. (2004). Consumer reactions toward clicks and bricks: investigating buying behaviour on-line and at stores. Behaviour & Information Technology, 23 (4), 237–245. doi: 10.1080/01449290410001685411

Bunduchi, R. (2005). Business relationships in Internet-based electronic markets: the role of goodwill trust and transaction costs. Information Systems Journal, 15 (4), 321–341. doi: 10.1111/j.1365-2575.2005.00199.x

Burgess, S., Sellitto, C., Cox, C., & Buultjens, J. (2009). Trust perceptions of online travel information by different content creators: Some social and legal implications. Information Systems Frontiers , 1–15.

Byers, R. E., & Lederer, P. J. (2001). Retail bank services strategy: A model of traditional, electronic, and mixed distribution choices. Journal of Management Information Systems, 18 (2), 133–156.

Cao, Q., Duan, W., & Gan, Q. (2010). Exploring Determinants of Voting for the. Decision Support Systems .

Cao, Y., Gruca, T. S., & Klemz, B. R. (2003). Internet pricing, price satisfaction, and customer satisfaction. International Journal of Electronic Commerce, 8 (2), 31–50.

Castañeda, J. A., Muñoz-Leiva, F., & Luque, T. (2007). Web Acceptance Model (WAM): Moderating effects of user experience. Information & Management, 44 (4), 384–396.

Cazier, J. A., Shao, B. B. M., & Louis, R. D. S. (2007). Sharing information and building trust through value congruence. Information Systems Frontiers, 9 (5), 515–529.

Chang, H. H., & Chen, S. W. (2009). Consumer perception of interface quality, security, and loyalty in electronic commerce. Information & Management, 46 (7), 411–417.

Chang, M. K., Cheung, W. M., & Lai, V. S. (2005). Literature derived reference models for the adoption of online shopping. Information & Management, 42 (4), 543–559. doi: 10.1016/s0378-7206(04)00051-5

Changa, K. C., Jackson, J., & Grover, V. (2003). E-commerce and corporate strategy: an executive perspective. Information & Management, 40 (7), 663–675. doi: 10.1016/s0378-7206(02)00095-2

Chellappa, R. K., & Kumar, K. R. (2005). Examining the role of “Free” product-augmenting Online services in pricing and customer retention strategies. Journal of Management Information Systems, 22 (1), 355–377.

Chellappa, R. K., & Shivendu, S. (2003). Economic implications of variable technology standards for movie piracy in a global context. Journal of Management Information Systems, 20 (2), 137–168.

Chellappa, R. K., Sin, R. G., & Siddarth, S. (2011). Price Formats as a Source of Price Dispersion: A Study of Online and Offline Prices in the Domestic US Airline Markets. Information Systems Research, 22 (1), 83–98. doi: 10.1287/isre.1090.0264

Chen, C. C., Wu, C. S., & Wu, R. C. F. (2006). e-Service enhancement priority matrix: The case of an IC foundry company. Information & Management, 43 (5), 572–586. doi: 10.1016/j.im.2006.01.002

Chen, L. D., Gillenson, M. L., & Sherrell, D. L. (2002). Enticing online consumers: an extended technology acceptance perspective. Information & Management, 39 (8), 705–719. doi: 10.1016/s0378-7206(01)00127-6

Chen, P. Y., & Hitt, L. M. (2002). Measuring switching costs and the determinants of customer retention in Internet-enabled businesses: A study of the Online brokerage industry. Information Systems Research, 13 (3), 255–274. doi: 10.1287/isre.13.3.255.78

Cheng, F. F., & Wu, C. S. (2010). Debiasing the framing effect: The effect of warning and involvement. Decision Support Systems, 49 (3), 328–334.

Cheng, H. K., & Dogan, K. (2008). Customer-centric marketing with Internet coupons. Decision Support Systems, 44 (3), 606–620. doi: 10.1016/j.dss.2007.09.001

Cheng, T. C. E., Lam, D. Y. C., & Yeung, A. C. L. (2006). Adoption of Internet banking: An empirical study in Hong Kong. Decision Support Systems, 42 (3), 1558–1572. doi: 10.1016/j.dss.2006.01.002

Cheng, Z., & Nault, B. R. (2007). Internet channel entry: retail coverage and entry cost advantage. Information Technology & Management, 8 (2), 111–132. doi: 10.1007/s10799-007-0015-9

Cheung, K. W., Kwok, J. T., Law, M. H., & Tsui, K. C. (2003). Mining customer product rating for personalized marketing. Decision Support Systems, 35 (2), 231–243. doi: 10.1016/s0167-9236(02)00108-2

Chiou, W. C., Lin, C. C., & Perng, C. (2010). A strategic framework for website evaluation based on a review of the literature from 1995–2006. Information & Management, 47 (5–6), 282–290.

Chircu, A. M., & Kauffman, R. J. (2000a). Limits to value in electronic commerce-related IT investments. Journal of Management Information Systems, 17 (2), 59–80.

Chircu, A. M., & Kauffman, R. J. (2000b). Reintermediation strategies in business-to-business electronic commerce. International Journal of Electronic Commerce, 4 (4), 7–42.

Chircu, A. M., & Mahajan, V. (2006). Managing electronic commerce retail transaction costs for customer value. Decision Support Systems, 42 (2), 898–914. doi: 10.1016/j.dss.2005.07.011

Cho, V. (2006a). Factors in the adoption of third-party B2B portals in the textile industry. Journal of Computer Information Systems, 46 (3), 18–31.

Cho, V. (2006b). A study of the roles of trusts and risks in information-oriented online legal services using an integrated model. Information & Management, 43 (4), 502–520. doi: 10.1016/j.im.2005.12.002

Choi, J., Lee, S. M., & Soriano, D. R. (2009). An empirical study of user acceptance of fee-based online content. Journal of Computer Information Systems, 49 (3), 60–70.

Choudhary, V. (2010). Use of pricing schemes for differentiating information goods. Information Systems Research, 21 (1), 78.

Choudhury, V., & Karahanna, E. (2008). The relative advantage of electronic channels: A multidimensional view. MIS Quarterly, 32 (1), 179–200.

Christiaanse, E., Van Diepen, T., & Damsgaard, J. (2004). Proprietary versus Internet technologies and the adoption and impact of electronic marketplaces. Journal of Strategic Information Systems, 13 (2), 151–165. doi: 10.1016/j.jsis.2004.02.004

Chua, C. E. H., & Wareham, J. (2008). Parasitism and Internet auction fraud: An exploration. Information and Organization, 18 (4), 303–333. doi: 10.1016/j.infoandorg.2008.01.001

Chua, C. E. H., Wareham, J., & Robey, D. (2007). The role of online trading communities in managing Internet auction fraud. MIS Quarterly, 31 (4), 759–781.

Chun, S. H., & Kim, J. C. (2005). Pricing strategies in B2C electronic commerce: analytical and empirical approaches. Decision Support Systems, 40 (2), 375–388. doi: 10.1016/j.dss.2004.04.012

Clemons, E. K. (2009a). Business models for monetizing Internet applications and Web sites: Experience, theory, and predictions. Journal of Management Information Systems, 26 (2), 15–41.

Clemons, E. K. (2009b). The complex problem of monetizing virtual electronic social networks. Decision Support Systems, 48 (1), 46–56.

Crowston, K., & Myers, M. D. (2004). Information technology and the transformation of industries: three research perspectives. Journal of Strategic Information Systems, 13 (1), 5–28. doi: 10.1016/j.jsis.2004.02.001

Currie, W. L., & Parikh, M. A. (2006). Value creation in web services: An integrative model. Journal of Strategic Information Systems, 15 (2), 153–174. doi: 10.1016/j.jsis.2005.10.001

Cyr, D., Bonanni, C., Bowes, J., & Ilsever, J. (2005). Beyond trust: Web site design preferences across cultures. Journal of Global Information Management, 13 (4), 25.

Dai, Q. Z., & Kauffman, R. J. (2002). Business models for Internet-based B2B electronic markets. International Journal of Electronic Commerce, 6 (4), 41–72.

Datta, P. (2011). A preliminary study of ecommerce adoption in developing countries. Information Systems Journal, 21 (1), 3–32. doi: 10.1111/j.1365-2575.2009.00344.x

Datta, P., & Chatterjee, S. (2008). The economics and psychology of consumer trust in intermediaries in electronic markets: the EM-Trust Framework. European Journal of Information Systems, 17 (1), 12–28. doi: 10.1057/palgrave.ejis.3000729

Davis, A., & Khazanchi, D. (2008). An empirical study of online word of mouth as a predictor for multi product category e-Commerce Sales. Electronic Markets, 18 (2).

de Valck, K., van Bruggen, G. H., & Wierenga, B. (2009). Virtual communities: A marketing perspective. Decision Support Systems, 47 (3), 185–203. doi: 10.1016/j.dss.2009.02.008

De Wulf, K., Schillewaert, N., Muylle, S., & Rangarajan, D. (2006). The role of pleasure in web site success. Information & Management, 43 (4), 434–446.

Dehning, B., Richardson, V. J., Urbaczewski, A., & Wells, J. D. (2004). Reexamining the value relevance of e-commerce initiatives. Journal of Management Information Systems, 21 (1), 55–82.

Dellaert, B. G. C., & Dabholkar, P. A. (2009). Increasing the attractiveness of mass customization: The role of complementary on-line services and range of options. International Journal of Electronic Commerce, 13 (3), 43–70.

Dellarocas, C., Gao, G. D., & Narayan, R. (2010). Are consumers more likely to contribute online reviews for hit or niche products? Journal of Management Information Systems, 27 (2), 127–157. doi: 10.2753/mis0742-1222270204

Devaraj, S., Fan, M., & Kohli, R. (2006). Examination of online channel preference: Using the structure-conduct-outcome framework. Decision Support Systems, 42 (2), 1089–1103. doi: 10.1016/j.dss.2005.09.004

Dewan, R., Jing, B., & Seidmann, A. (2000). Adoption of Internet-based product customization and pricing strategies. Journal of Management Information Systems, 17 (2), 9–28.

Dewan, R. M., & Freimer, M. L. (2003). Consumers prefer bundled add-ins. Journal of Management Information Systems, 20 (2), 99–111.

Dewan, R. M., Freimer, M. L., Seidmann, A., & Zhang, J. (2004). Web portals: Evidence and analysis of media concentration. Journal of Management Information Systems, 21 (2), 181–199.

Dewan, S., & Ren, F. (2007). Risk and return of information technology initiatives: Evidence from electronic commerce announcements. Information Systems Research, 18 (4), 370–394. doi: 10.1287/isre.1070.0120

Dhar, V., & Ghose, A. (2010). Sponsored Search and Market Efficiency. Information Systems Research, 21 (4), 760–772. doi: 10.1287/isre.1100.0315

Dos Santos, B. L., & Peffers, K. (1998). Competitor and vendor influence on the adoption of innovative applications in electronic commerce. Information & Management, 34 (3), 175–184. doi: 10.1016/s0378-7206(98)00053-6

Dou, W. Y., Lim, K. H., Su, C. T., Zhou, N., & Cui, N. (2010). Brand positioning strategy using search engine marketing. MIS Quarterly, 34 (2), 261–279.

Du, A. Y., Geng, X. J., Gopal, R. D., Ramesh, R., & Whinston, A. B. (2008). Topographically discounted Internet infrastructure resources: a panel study and econometric analysis. Information Technology & Management, 9 (2), 135–146. doi: 10.1007/s10799-007-0034-6

Du, T. C., Li, E. Y., & Wei, E. (2005). Mobile agents for a brokering service in the electronic marketplace. Decision Support Systems, 39 (3), 371–383.

Duan, W., Gu, B., & Whinston, A. B. (2009). Informational cascades and software adoption on the internet: an empirical investigation. MIS Quarterly, 33 (1), 23–48.

Duan, W. J. (2010). Analyzing the impact of intermediaries in electronic markets: an empirical investigation of online consumer-to-consumer (C2C) auctions. Electronic Markets, 20 (2), 85–93. doi: 10.1007/s12525-010-0034-y

Dutta, A. (2001). Business planning for network services: A systems thinking approach. Information Systems Research, 12 (3), 260–285. doi: 10.1287/isre.12.3.260.9713

Dwivedi, Y. K., Papazafeiropoulou, A., Brinkman, W. P., & Lal, B. (2010). Examining the influence of service quality and secondary influence on the behavioural intention to change Internet service provider. Information Systems Frontiers, 12 (2), 207–217. doi: 10.1007/s10796-008-9074-7

Easley, R. F., Wood, C. A., & Barkataki, S. (2010). Bidding Patterns, Experience, and Avoiding the Winner’s Curse in Online Auctions. Journal of Management Information Systems, 27 (3), 241–268. doi: 10.2753/mis0742-1222270309

Edelman, B., & Ostrovsky, M. (2007). Strategic bidder behavior in sponsored search auctions. Decision Support Systems, 43 (1), 192–198. doi: 10.1016/j.dss.2006.08.008

El Sawy, O. A., Malhotra, A., Gosain, S., & Young, K. M. (1999). IT-intensive value innovation in the electronic economy: Insights from Marshall Industries. MIS Quarterly, 23 (3), 305–335.

Erat, P., Desouza, K. C., Schafer-Jugel, A., & Kurzawa, M. (2006). Business customer communities and knowledge sharing: exploratory study of critical issues. European Journal of Information Systems, 15 (5), 511–524. doi: 10.1057/palgrave.ejis.3000643

Even, A., Shankaranarayanan, G., & Berger, P. D. (2010). Evaluating a model for cost-effective data quality management in a real-world CRM setting. Decision Support Systems .

Flavián, C., Guinalíu, M., & Gurrea, R. (2006). The role played by perceived usability, satisfaction and consumer trust on website loyalty. Information & Management, 43 (1), 1–14.

Forman, C., Ghose, A., & Wiesenfeld, B. (2008). Examining the relationship between reviews and sales: The role of reviewer identity disclosure in electronic markets. Information Systems Research, 19 (3), 291–313. doi: 10.1287/isre.1080.0193

Gallaugher, J. M., Auger, P., & BarNir, A. (2001). Revenue streams and digital content providers: an empirical investigation. Information & Management, 38 (7), 473–485. doi: 10.1016/s0378-7206(00)00083-5

Gao, S. J., Wang, H. Q., Xu, D. M., & Wang, Y. F. (2007). An intelligent agent-assisted decision support system for family financial planning. Decision Support Systems, 44 (1), 60–78. doi: 10.1016/j.dss.2007.03.001

Garcia, R., & Gil, R. (2008). A web ontology for copyright contract management. International Journal of Electronic Commerce, 12 (4), 99–113. doi: 10.2753/jec1086-4415120404

Gauzente, C. (2009). Information search and paid results—proposition and test of a hierarchy-of-effect model. Electronic Markets, 19 (2), 163–177.

Gefen, D., Rose, G. M., Warkentin, M., & Pavlou, P. A. (2005). Cultural diversity and trust in IT adoption: A comparison of potential e-voters in the USA and South Africa. Journal of Global Information Management, 13 (1), 54–78. doi: 10.4018/jgim.2005010103

Ghose, A. (2009). Internet exchanges for used goods: an empirical analysis of trade patterns and adverse selection. MIS Quarterly, 33 (2), 263–291.

Ghose, A., Mukhopadhyay, T., & Rajan, U. (2007). The impact of Internet referral services on a supply chain. Information Systems Research, 18 (3), 300–319. doi: 10.1287/isre.1070.0130

Ghose, A., Smith, M. D., & Telang, R. (2006). Internet exchanges for used books: An empirical analysis of product cannibalization and welfare impact. Information Systems Research, 17 (1), 3–19. doi: 10.1287/isre.1050.0072

Ghose, A., & Yao, Y. L. (2011). Using Transaction Prices to Re-Examine Price Dispersion in Electronic Markets. Information Systems Research, 22 (2), 269–288. doi: 10.1287/isre.1090.0252

Glover, S., & Benbasat, I. (2010). A Comprehensive Model of Perceived Risk of E-Commerce Transactions. International Journal of Electronic Commerce, 15 (2), 47–78.

Gopal, R. D., Ramesh, R., & Whinston, A. B. (2003). Microproducts in a digital economy: Trading small, gaining large. International Journal of Electronic Commerce, 8 (2), 9–29.

Gopal, R. D., Tripathi, A. K., & Walter, Z. D. (2006). Economics of first-contact email advertising. Decision Support Systems, 42 (3), 1366–1382.

Gorman, M. F., Salisbury, W. D., & Brannon, I. (2009). Who wins when price information is more ubiquitous? An experiment to assess how infomediaries influence price. Electronic Markets, 19 (2–3), 151–162. doi: 10.1007/s12525-009-0009-z

Granados, N., Gupta, A., & Kauffman, R. J. (2008). Designing online selling mechanisms: Transparency levels and prices. Decision Support Systems, 45 (4), 729–745. doi: 10.1016/j.dss.2007.12.005

Granados, N., Gupta, A., & Kauffman, R. J. (2010). Information Transparency in Business-to-Consumer Markets: Concepts, Framework, and Research Agenda. Information Systems Research, 21 (2), 207–226. doi: 10.1287/isre.1090.0249

Granados, N. F., Gupta, A., & Kauffman, R. J. (2006). The impact of IT on market information and transparency: A unified theoretical framework. Journal of the Association for Information Systems, 7 (3), 148–178.

Granados, N. F., Kauffman, R. J., & King, B. (2008). How has electronic travel distribution been transformed? A test of the theory of newly vulnerable markets. Journal of Management Information Systems, 25 (2), 73–95. doi: 10.2753/mis0742-1222250204

Gregg, D. G., & Scott, J. E. (2006). The role of reputation systems in reducing on-line auction fraud. International Journal of Electronic Commerce, 10 (3), 95–120. doi: 10.2753/jec1086-4415100304

Gregor, S., & Jones, K. (1999). Beef producers online: Diffusion theory applied. Information Technology & People, 12 (1), 71–85.

Grenci, I. T. (2004). An adaptable customer decision support system for custom configurations. Journal of Computer Information Systems, 45 (2), 56–62.

Grover, V., & Saeed, K. A. (2004). Strategic orientation and performance of Internet-based businesses. Information Systems Journal, 14 (1), 23–42. doi: 10.1111/j.1365-2575.2004.00161.x

Gundepudi, P., Rudi, N., & Seidmann, A. (2001). Forward versus spot buying of information goods. Journal of Management Information Systems, 18 (2), 107–131.

Gupta, A., Su, B., & Walter, Z. (2004). Risk profile and consumer shopping behavior in electronic and traditional channels. Decision Support Systems, 38 (3), 347–367.

Gupta, A., Su, B. C., & Walter, Z. (2004). An empirical study of consumer switching from traditional to electronic channels: A purchase-decision process perspective. International Journal of Electronic Commerce, 8 (3), 131–161.

Gupta, S., & Kim, H. W. (2007). The moderating effect of transaction experience on the decision calculus in on-line repurchase. International Journal of Electronic Commerce, 12 (1), 127–158.

Hansen, H. R. (1995). Conceptual-framework and guidelines for the implementation of mass information-systems. Information & Management, 28 (2), 125–142. doi: 10.1016/0378-7206(95)94021-4

Harrison McKnight, D., Choudhury, V., & Kacmar, C. (2002). The impact of initial consumer trust on intentions to transact with a web site: a trust building model. The Journal of Strategic Information Systems, 11 (3–4), 297–323.

Harrison, T., & Waite, K. (2006). A time-based assessment of the influences, uses and benefits of intermediary website adoption. Information & Management, 43 (8), 1002–1013.

Hassanein, K., & Head, M. (2005). The impact of infusing social presence in the web interface: An investigation across product types. International Journal of Electronic Commerce, 10 (2), 31–55.

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Corley, J.K., Jourdan, Z. & Ingram, W.R. Internet marketing: a content analysis of the research. Electron Markets 23 , 177–204 (2013). https://doi.org/10.1007/s12525-012-0118-y

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Received : 08 November 2011

Accepted : 14 September 2012

Published : 31 January 2013

Issue Date : September 2013

DOI : https://doi.org/10.1007/s12525-012-0118-y

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Research Article

Tourism marketing in the metaverse: A systematic literature review, building blocks, and future research directions

Contributed equally to this work with: Eva Sánchez-Amboage, Verónica Crespo-Pereira, Matías Membiela-Pollán, João Paulo Jesús Faustino

Roles Conceptualization, Data curation, Formal analysis, Funding acquisition, Investigation, Methodology, Project administration, Resources, Software, Supervision, Validation, Visualization, Writing – original draft, Writing – review & editing

* E-mail: [email protected]

Affiliation Business Department, University of A Coruña, A Coruña, Spain

Roles Conceptualization, Data curation, Methodology, Supervision, Validation, Writing – review & editing

Roles Conceptualization, Data curation, Methodology, Supervision, Writing – review & editing

Roles Visualization, Writing – review & editing

Affiliation Faculdade de Letras, University of Porto, Porto, Portugal

Eva Sánchez-Amboage,
Verónica Crespo-Pereira,
Matías Membiela-Pollán,
João Paulo Jesús Faustino

Published: May 10, 2024
https://doi.org/10.1371/journal.pone.0300599
Reader Comments

The aim of this research is to investigate tourist marketing within the embryonic context of the metaverse in order to comprehend the building blocks and the primary technologies employed in the sector. A systematic literature review (SLR) was conducted on 386 articles, with an overall qualitative approach that included 86 references, all of which dealt with the topic of the metaverse and had direct or potential implications for the tourism sector (hotels, restaurants, means of transport, leisure activities and destination itself). The articles are taken from: Science Direct, Taylor & Francis, Emerald, Springer and Google Scholar. The SLR was carried out according to the PRISMA search protocol. The results indicate the technologies that have been most thoroughly studied at the confluence of marketing, tourism, and the metaverse (AI, virtual reality, augmented reality, mixed reality, blockchain, tokens (NFTs) and digital twins). Moreover, they establish the foundational components of tourism marketing in the metaverse for the first time (tourism products, the metaverse as a distribution and branding channel for tourism and, tourist customer as protagonist). Finally, the study exposes research gaps and recommends future directions for exploration (monetization of products in the metaverse, promotion and marketing strategies in the metaverse, new profiles for marketing professionals, policy development that regulates commercial activity in the metaverse).

Citation: Sánchez-Amboage E, Crespo-Pereira V, Membiela-Pollán M, Jesús Faustino JP (2024) Tourism marketing in the metaverse: A systematic literature review, building blocks, and future research directions. PLoS ONE 19(5): e0300599. https://doi.org/10.1371/journal.pone.0300599

Editor: Barbara Guidi, University of Pisa, ITALY

Received: August 3, 2023; Accepted: February 23, 2024; Published: May 10, 2024

Copyright: © 2024 Sánchez-Amboage 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: Data relevant to this study are available from Zenodo at https://doi.org/10.5281/zenodo.10782765 .

Funding: The article is funded by the Luis Fernández Somoza Chair and the research iMARKA Research Group, both from the University of A Coruña to ESA.

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

Introduction

The COVID-19 pandemic changed how societies and economies developed around the world [ 1 ]. No other previous global crisis has affected every country and every industry [ 2 ]. In addition to economic losses, the quarantine and social isolation have been detrimental to our social and psychological well-being [ 3 ]. At the root of all this, the contactless culture has been firmly established in society and in our daily lives [ 4 ]. Tourists have exhibited new behaviors, such as taking precautionary health measures when traveling or avoiding crowded places, events and/or group travel, for example. We are faced with a “new tourist” who demands touchless/contactless travel [ 5 ] that matches their lifestyle, consisting of leisure, remote work, family obligations and hybrid activities (both virtual and real) [ 6 ].

Technology is serving as a vector of change in this post-COVID society. In the tourism industry, technological innovation is playing a fundamental role in the post-pandemic recovery [ 7 ]. Without information technology (IT), there would have been no tourism during and after COVID-19 [ 8 ]. The traditional service experience is changing "high-touch and low-tech” processes into “low-touch and high-tech” ones [ 9 ]. For example, in the hotel sector, technology has made it possible to reduce interactions between customers and staff through contactless check-in and check-out systems, digital key systems, face recognition systems, cleaning robot systems [ 7 ], as well as creating new promotion options through livestreaming [ 10 ]. Furthermore, during the main quarantine period, several tourism services and activities changed from on-site to totally digital and virtual formats. Major brands opted to reformulate communication and digital marketing strategies to boost interaction with their audiences. Companies like Airbnb created an “online experience” section [ 11 ]; restaurants have adopted new measures to maintain their income and retain employment levels [ 12 ]; museums around the world conducted live visits, primarily through the social media [ 8 ] and tourist destinations shared their history and areas of interest over the Internet, with the main goal being to connect with future tourists at an extremely complicated time worldwide. The pandemic has triggered and accelerated change [ 13 , 14 ], however, these practices were already latent in the tourism industry even before the pandemic [ 15 ].

This is where metaverse comes into play, an interconnected ecosystem of digital and physical environments that can be experienced simultaneously, seamlessly blending physical and technological realities [ 16 ]. The concept of the metaverse and the virtual experiences related to it have emerged in society and have radically changed the future of technology and its potential impact on the hospitality and tourism industry [ 6 , 17 , 18 ].

Although, the metaverse is positioned as one of the most popular research agendas [ 19 ], only two articles related to tourism and the metaverse have been published in specialized tourism journals until 2022: [ 20 , 21 ]. Authors such as [ 22 ] understand that the metaverse will be the marketing platform of the future, where communication with customers will be different from what we know now. [ 6 , 22 ] discuss the foundations and building blocks for marketing in the metaverse, while [ 23 ] consider the building blocks of tourism in the metaverse. There are no references to the building blocks of tourism marketing in the metaverse.

This systematic literature review (SLR) was conducted to address these gaps, to expand the framework for tourism marketing in the metaverse, and to identify areas for future research.

This paper presents a systematic literature review (SLR) of academic publications related to the metaverse that have direct or potential impact on tourism. The aim of this research is to investigate tourist marketing within the embryonic context of the metaverse in order to comprehend the building blocks and the primary technologies employed in the sector.

The results obtained from both objectives can be employed in other research areas within the creative industries. Across various sectors, companies share common characteristics. Those within the creative industries particularly emphasize the creation of original and innovative content, spanning products, services, or experiences. Creativity and originality serve as foundational values in these enterprises. Examples of businesses in the creative industry encompass various areas such as visual arts, traditional culture, cultural sites, publications, new media, etc.

Preliminary metaverse studies will be able to share their findings to create knowledge about the metaverse marketing discipline.

Next, the research is structured into three sections: methodology, which provides a detailed explanation of the systematic literature review; results, focusing on the most studied metaverse technologies in tourism research and the building blocks of tourist marketing in the metaverse. Finally, the research concludes with a section on conclusions, limitations, and future research directions.

Methodology

Review works are widely accepted in the academic field. Since 2012, journals focused on tourism have increased the number of review articles published, which reflects the growing popularity of this type of studies. In terms of their repercussion, the review articles most frequently cited by other authors fall under the topics of economics and finance and marketing [ 24 ].

Within review works, systematic reviews aim to summarize and analyze evidence with regard to an objective or research question. Systematic reviews are based on specifying the method used to find, select, analyze and synthesize the primary sources used in the research [ 25 ].

The present research is conducted considering the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) search protocol [ 26 ].

PRISMA is a protocol for conducting systematic reviews that consists of a 27-item checklist and a four-phase flow chart ( Fig 1 ). It was developed in the field of medicine by a group of 29 scholars with the intention of increasing the transparency and precision of literature reviews. The reason for choosing PRISMA over other existing protocols lies in its recognition and use by various disciplines throughout the world beyond the medical fields, as well as its potential for improving the validity and confidence of the systematic reviews in hospitality services and tourism [ 27 ].

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https://doi.org/10.1371/journal.pone.0300599.g001

The prior publication of the protocol reduces the impact of inherent biases by the author and promotes transparency about the methods and process, as well as preventing redundant reviews. Among the many options that exist for evaluating bias risk, PRISMA promotes a system based on the evaluation of different key design components and the execution of studies so that there is solid empirical evidence of its relationship to the bias [ 29 ].

Eligibility criteria and search strategy

Several searches in different databases were carried out to decide which were the most pertinent, in terms of the number of articles revealed and the affinity of these articles to the proposed research topic. The search equation that ultimately presented the most beneficial search results was: marketing AND (metaverse OR "metaverse platform") AND (tourism OR travel OR hospitality).

It was decided to perform the search on the collections of publications most used in the fields of research on marketing, hospitality services and tourism: Science Direct, Taylor & Francis, Emerald and Springer. This search was complemented by the results from the Google Scholar search engine, since in recent years it has significantly expanded its coverage [ 30 ]. The filters used in the search of publication collections and Google Scholar were: scientific articles, English language and any date. Those references that come from non-indexed journals are eliminated. The research has examined articles on marketing and the metaverse, with direct or indirect relevance to the tourism sector, from 1992 to 2022, with a specific focus on the years 2020–2022 due to the significance of these years of publication, as explained later in "reports excluded, reason 1".

The Scopus and Web of Science databases were ruled out as they contain a small number of articles for analysis, 2 and 6, respectively; and for these not being totally related to the research objective. The same search equation was used in Proquest, obtaining a total of 293 records (doctoral theses), which after the analysis of the title, abstract and key words demonstrated that the results were not closely linked to the research proposal and thus this database was also ruled out.

An Excel document was developed to save the results, organized based on: code, title, author, key words, abstract, year, journal, DOI and origin of the corresponding author. The document has been registered on Zenodo and can be accessed through the following link: https://doi.org/10.5281/zenodo.10782765

The “code” cell helps structure the study selection process as follows and reduces the risk of researcher bias. The inclusion or exclusion of each reference has been validated by all four authors of this article.

Records excluded : (n = 162) reviewing the title, abstract, key words and determining that the topic does not match: metaverse, blockchain, XR, AR, VR, second life, IA, virtual world.
Reports excluded , reason 1 : (n = 44) articles prior to 2020. No filter is used with regard to the search date (“anytime”). However, after the first analyses, it was decided that the studies that would form part of the SLR would be those that were published in the last two years (2020–2022). Authors like Kim (2021) explain that the term metaverse has gained ground in the world of technology since 2020, becoming popular since 2021 when it coincided with the change of the Facebook brand to Meta, among other events.
Reports excluded , reason 2 : (n = 54) lack of agreement with the topic. These are articles that include the word metaverse, but are not considered to fall under the social sciences (e.g. the field of medicine), or articles that address the topic but do not offer pertinent information for our research.
Reports Included , reason 1 : (n = 10) articles that coincided with the study topic: tourism, metaverse, marketing. Also considered were those articles that, in spite of not including the word metaverse, second life or virtual word, deal with their technologies: blockchain, XR, AR, VR, IA, IoT and NFT.
Reports Included , reason 2 : (n = 53) articles that deal with marketing and the metaverse, but that are not focused on the tourism industry, however, their information can potentially be applied in the field of tourism.

As the SLR progressed and due to the scarce number of references, it became necessary to include articles that are complementary to the research. These are articles that have been references in the SLR articles, using the “snowball” strategy.

Reports Included , reason 3 : (n = 14) articles from the complementary search that coincide with the study topic: tourism, metaverse, marketing.
Reports Included , reason 4 : (n = 9) articles from the complementary search on marketing and the metaverse from other sectors, with an implication for tourism.

In complementary research there are four articles that date back to before the year 2020. The inclusion of these articles poses an important bias risk. In order to avoid this, each reference has had to pass a review by all four authors.

Search protocol registration

A search protocol registration has been developed for research on OSF registries.
Registration name: tourism marketing in the metaverse: a systematic review
Registration type: OSF Preregistration
Registration DOI: https://doi.org/10.17605/OSF.IO/B9V75

SLR general statistics

The findings from this review have indicated that the articles focused on the tourism sector and the metaverse are few (n = 24) (reports included reason 1 (n = 10) and reports included reason 3 (n = 14)), which indicates that for the time being, the topic of study is novel and more knowledge on the subject is needed.

Publications on marketing and the metaverse have been fairly recent. Most of them have been concentrated in the year 2022 ( Fig 2 ). Through screening the SLR, it was observed that the main themes about the metaverse evolve over time. Articles published before 2020 focus on topics such as Second Life, virtual world, and 3D, while articles after 2020 cover topics like metaverse, blockchain, XR, AR, VR, Second Life, AI, virtual world, IoT, and NFTs.

https://doi.org/10.1371/journal.pone.0300599.g002

Table 1 shows that, 43% of the articles on the metaverse analyzed are from European universities, primarily the United Kingdom (12) and Germany (4). The topic is also studied in Asia (29%), notably in universities in South Korea (8) and China (7). The United States appears as the leading country in research in this area, with 11 publications. These statistics show that the metaverse is a topic of global interest, with research efforts concentrated in Europe, Asia, and the United States. This distribution reflects the widespread curiosity and exploration of the metaverse concept across different regions and academic institutions.

https://doi.org/10.1371/journal.pone.0300599.t001

Metaverse concept

Most of the studies analyzed agree that the word metaverse is not a recent one, as it was referenced in the science fiction novel “Snow Crash” by Neal Stephenson in 1992 [ 31 ]. Even [ 20 ] remind us that the concept could date back as far as 1909, since it is also mentioned in the work “Machine Stops” by E. M. Foster. In any case, its popularity has grown with the release of Second Life in 2003 [ 22 ], only to take off in 2021, supported by a more developed technological scenario and after different brands began to propose their activity in the metaverse (e.g. Facebook rebrand itself as Meta) [ 32 ]. Several articles analyzed also expose the idea that the term Metaverse combines “meta” (meaning post, after or beyond) and “verse” (universe) [ 4 , 6 , 33 ] and it is defined as an ecosystem of shared and interconnected digital and physical environments that can be experienced in a synchronous manner, where physical and technological realities are seamlessly combined [ 16 ]. Enabled by Internet 3.0, the metaverse refers to a three-dimensional virtual space that focuses on social connections [ 20 ] or in a reductionist definition of the metaverse: a space designed for users by users, which can satisfy whomever, whatever, however, wherever and whenever [ 34 ].

However, in the RSL we find authors who consider that the conception of a true metaverse, in the sense of a digital universe parallel to our analogic world (where the participants can engage in social, economic, artistic or leisure activities beyond just videogames), has yet to be created and is pending the development of the technologies that would make it possible [ 35 ]. That’s why numerous companies, such as Meta, Microsoft, Epic Games, and Google, are working on and investing in crucial emerging technologies for the metaverse, such as virtual reality headsets, augmented reality sensors, and blockchain [ 36 ]. In any event, the challenges presented by the metaverse, its technology, and its prospective evolution remain largely unknown [ 37 ]. This pertains equally to the physical and psychological well-being of both individuals and collectives [ 38 ].

The RSL indicates that there are three terms to refer directly to tourism activity in the metaverse: “metaverse tourism” [ 21 ], “metaversal tourism” [ 39 ] or a more indirect option, “Metaleisure” [ 40 ]. The metaverse, when associated with tourism, uses physical reality in combination with mixed reality (MR), with the latter consisting of augmented reality (AR) and virtual reality (VR). So far, the more extensively used terms in the field of tourism research is virtual tourism [ 3 , 41 ], also referred to as “cloud tourism”, which uses both VR and AR technologies, as well as live video streaming [ 3 ].

Finally, related to the metaverse concept, a substantial body of evidence suggests that the contactless culture driven by the COVID-19 pandemic [ 5 , 6 ] has promoted the development of the metaverse and, concurrently, has spurred research into the enabling virtual technology of the metaverse [ 37 , 42 , 43 ]. More specifically, some references delve into its impact on financial markets and the use of NFTs and cryptocurrencies for payment [ 44 ], the digital economy [ 37 ], or virtual museums [ 42 ].

Statistics on tourism in the metaverse

Through the SLR and complementary research, information is gathered regarding the impact of the metaverse on the tourism sector.

The metaverse is so new that the earliest statistics and estimates date back to 2022. It is predicted that income from a single metaverse performance, such as the Travis Scott concert, would amount to at least $1 million, with a total of $20 million [ 44 ]. According to the International Congress and Convention Association [ 45 ] the market share for virtual and hybrid gatherings has doubled since 2020. In addition, 61% of presenters, while acknowledging the importance of on-site events, believe that there is a push toward hybrid (on-site and online) events [ 46 ]. Thomas Cook, as part of its “Try Before You Fly” campaign, produced a variety of immersive 360º VR contents lasting 5 minutes each, with the goal of presenting New York as a destination. These views allowed the agency to increase reservations for excursions to New York by 190% [ 47 , 48 ]. The figures from Kang’s study [ 49 ] also confirm the effectiveness of VR for the tourism sector. VR devices (head-mounted displays (HMD) had a 47% greater telepresence than video and promoted engagement, thus increasing the client’s desire to purchase by 75%. In 2019, 20% of potential tourists expressed interest in VR devices in order to receive travel-related content [ 50 ]. In 2021, 9.54 million shipments of augmented reality (AR) and virtual reality (VR) helmets were recorded. In 2022, it is expected that the AR/VR headset shipments to consumers will amount to 13.24 million units [ 51 ].

Most studied technologies for tourism marketing in metaverse

The word cloud generated from the 86 articles analyzed in the SLR ( Fig 3 ) serves to illustrate the central technologies and systems involved in the development of tourism marketing in the metaverse.

https://doi.org/10.1371/journal.pone.0300599.g003

RSL reveals the core technologies, systems, and applications associated with tourism marketing, including but not limited to tokens (NFTs), blockchain, virtual reality, augmented reality, mixed reality, AI, and digital twins. Fig 4 shows the results of a tag cloud analysis of 86 articles (based on their keywords). In addition, Internet of Things (IoT), gamification and new payment systems such as cryptocurrencies are also detected as predominant themes (outside the keywords).

https://doi.org/10.1371/journal.pone.0300599.g004

Blockchain technology and Non-Fungible Tokens (NFT).

The findings from the existing literature have shown that digital technologies play a crucial role in gaining a competitive edge in marketing [ 52 ]. Specifically, the application of NFT technology revolutionizes the way in which the content is created, marketed, exchanged, stored, and authenticated, both for the content creators themselves and for their fans.

Non-fungible tokens (NFTs) are transferable rights to digital assets, such as art, collectables, music or game elements. This phenomenon and its markets have grown significantly since early 2021 [ 53 ]. NFTs are uniquely certified with blockchain (a set of technologies that make it possible to keep a secure, decentralized, synchronized and distributed register of digital operations without the need for third-party intermediation) authentication [ 54 , 55 ]). There is even mention of a new type of marketing, “NFT marketing”, which is focused on the creation, promotion and strategic use of NFTs to achieve marketing objectives [ 56 ].

Fungible goods, such as money or commercial goods, can be exchanged for the same type of goods. On the contrary, non-fungible items cannot be exchanged for a similar product because their value exceeds the real value of the material [ 53 ]. NFTs can include the offer of products or services of either a digital or physical nature, with markets for their sale, such as OpenSea and Rarible. Authors like [ 57 ] introduced a transformative category in NFTs known as Dynamic Non-Fungible Tokens (dNFTs), representing a pioneering advancement within the NFT landscape. These dNFTs extend the scope of NFTs to include a broad spectrum of products and services, encompassing both digital and physical offerings.

For the travel sector, offering NFT-based services to passengers by travel companies is a savvy approach that allows these companies to track passengers, gather and analyze customer data, and enhance service levels [ 58 ].

Cryptocurrencies are used to make purchases, primarily in Ethereum (ETH), as a payment and negotiation option, which demonstrates a close relationship between the cryptocurrency market and the NFT market [ 59 ]. Cryptocurrencies are modifying the very nature of how travelers use and manage payment systems [ 60 ]. The adoption of new payment methods by companies in the tourism sector poses a series of clear advantages: differentiation from companies that do not accept them, an increased conversion rate related to offering more alternatives for reservations and the security offered by collecting non-reimbursable fees [ 61 ].

VR, AR and MR technology.

The literature is clear that virtual reality is making progressive advancements and becoming increasingly adopted. It is widely acknowledged in the SLR that virtual reality (VR) technologies are being used by millions of people. This is especially true after the outbreak of Covid-19, as VR platforms like VR Chat, Facebook Horizon, and Rec Room experienced exponential growth due to its secure and attractive way of connecting with others, when travel and social gatherings were heavily restricted. Through virtual reality, users can experience interacting with others in seemingly infinite worlds, creating their own avatars, and enjoying a social atmosphere comparable to reality [ 62 ]. VR creates a completely digital environment that is cut off from the outside world [ 63 ], in which the user (or their avatar) navigates through a virtual environment [ 49 ]. Authors, such as Jaung [ 64 ] in the field of natural sciences, explain how metaverse technologies, including VR, provide a new way of interacting with nature through immersive three-dimensional virtual worlds.

In terms of marketing, VR can be employed by specialists to co-create value with consumers and promote consumer-brand engagement [ 65 ].

Augmented reality (AR) is another essential technology for metaverse tourism activities. AR has emerged as an innovative communication device that adds virtual information to a user’s real-world environment [ 63 ]. It enhances the real-world atmosphere by providing context-sensitive data [ 66 ], such as numbers, letters, symbols, audio, video and graphics [ 67 ]. AR and VR are the most prominent examples of immersive technologies [ 68 ]. Mixed reality (MR) intertwines real and virtual worlds [ 63 ], while extended reality (XR) serves as an umbrella term encompassing previous technologies [ 69 ].

Artificial intelligence (AI) and digital twins.

Other common themes observed in the SLR included artificial intelligence and digital twins. AI can offer highly precise information to assist an organization in making better decisions based on collected data [ 70 ]. The global pandemic has spurred many organizations to accelerate investments in AI to optimize production capacity, logistics, and customer management [ 71 ]. An example of this is the use of digital twins. These are digital replicas of physical objects, processes, or services which allow the collection of data to create simulations that model, test, and predict the performance of a product, process, or service in the real world [ 72 – 74 ]. Digital twins can be developed for objects, buildings, services, systems, and even cities. By combining big data, Internet of Things (IoT) solutions, AI, and data analysis, digital twins allow us to analyze data and simulate potential future scenarios.

Practical cases of tourism marketing in the metaverse

Most of the articles analyzed in this research provide examples that help to understand how metaverse technologies are incorporated into the tourism marketing. While the metaverse (or metaverses) is still in development [ 75 ], the tourism industry is already using its technologies. Those involved, such as hotels, restaurants, transport, leisure activities, and destinations, “tangibilize” their services and offer immersive experiences to the public [ 21 ]. Table 2 offers a summary of the examples presented in the SLR and supplementary research, regarding the implementation of metaverse technologies, systems and applications in the tourism marketing, covering destinations, hotels, restaurants, transportation, and leisure/cultural activities (e.g., concerts, theatre and museums).

https://doi.org/10.1371/journal.pone.0300599.t002

Metaverse building blocks

In the SLR, two articles ([ 6 , 22 ]) were found that discussed the fundations and the building blocks of marketing in the metaverse. These early contributions shed light on the beginning stages of marketing activities within the metaverse.

Dwivedi et al. [ 6 ] describe the foundations of metaverse marketing, based on five key elements: product, branding, distribution channels, consumer interaction, and customer information. NFTs allow for unique virtual products, VR and AR offer new branding opportunities, AI agents provide personalized consumer interactions, and the metaverse itself is a treasure trove of consumer information.

Hollensen, Kotler & Opresnik [ 22 ], on the other hand, explain the nine building blocks of marketing in the metaverse, including hardware, networking, computers, virtual platforms, interchange standards and tools, payments, content, services and assets, consumer and business behaviours. Hardware such as VR headsets, mobile phones and haptic gloves provides access to the metaverse, networking ensures data transmission and reliability, computing power providing the necessary resources for metaverse to function properly, virtual platforms enable users to interact with the metaverse, interchange standards allow for interoperability, payments (cryptocurrencies and digital currencies) cover purchases and transfer of money, content and services provide experiences, and consumer and business behaviours are shaped by the metaverse.

Outside the SLR, [ 93 ] outlines the key building blocks and future challenges of the metaverse as: 1) ethical, regulatory, governance, security, and privacy challenges; 2) an ecosystem including enterprise and consumer use cases, content creation, virtual economy, and avatars; and 3) the underlying technologies, such as extended reality (VR/AR), user interfaces, AR, blockchain, and edge computing.

Furthermore, outside of the RSL, [ 94 ] mention the major technological building blocks: networks, computing, 3D modeling, IoT, AI, blockchain, XR, and interface devices, each of which is explored in brief.

Buhalis, Leung & Lin [ 23 ] emphasize that the development and success of tourism in the metaverse is dependent upon certain key building blocks: 1) networking infrastructure (hardware devices, software applications, and network services), 2) enabling devices (such as MR/VR headsets and environment rendering devices), 3) empowering platforms or virtual worlds (with high-fidelity graphics and immersive experiences), and 4) technology-ready users (there is an increasing demand for users who are willing to engage in the metaverse).

This search revealed a gap in the literature regarding the building blocks of tourism marketing within the metaverse.

A proposal of the building blocks of tourism marketing in the metaverse

This article seeks to fill the gap by proposing the foundations of tourism marketing in the metaverse. For this purpose, [ 6 ] and [ 22 ] are taken as a starting point, which is then supplemented by the insights drawn from the SLR and complementary research. The information in this section can be completed with the practical examples presented in Table 2 .

Examples found in 2022 mainly focused on the use of NFTs (blockchain technology) and virtual reality (VR), augmented reality (AR), and mixed reality (MR) (see Table 2 ).
Virtual Reality (VR) is enabling immersive experiences that can create avatars that embody a new traveller identity for the tourism industry. This allows them to virtually explore destinations they have visited as well as new ones and engage in creative fantasy experiences in the metaverse [ 21 ]. Also, thanks to gamification, new tourist products can be created, with greater interaction even than the real tourist product, as is the case of the virtual Museum Renaissance (see Table 2 ).
Companies in the tourism sector are increasingly adopting new payment methods to differentiate themselves from their competitors, improve customer conversion rates, and gain the security of collecting non-refundable fees [ 61 ]. For instance, the Nomo Soho Hotel in New York offers tourism packages in NFT format for sale on the OpenSea token marketplace through the Ethereum cryptocurrency [ 84 ]. This serves as another example of a novel type of tourism product.
But it should also be understood as a new sales channel, a touchpoint so brands can communicate with their customers [ 96 ]; a way to offer innovative omnichannel experiences that allow brands to position themselves in the minds of consumers and open up new markets. It is possible, thanks to metaverse, for brands to penetrate a digital worldwide market, through virtual communication, digital branding, and online marketing [ 97 ].
Brands have the opportunity to adopt totally new ways of interacting with users in the metaverse and launch fully customized offers through immersive virtual spaces [ 22 , 98 ]. Emerging specialties such as avatar marketing are gaining traction as a brand reinforcement strategy [ 99 ]. Also, advertisements for a brand will be interactive and customized. AR and VR technologies will allow users try out the product or service before they buy it [ 97 ], through strategies like “try before you buy” [ 3 ].
NFTs also play a crucial role in brand positioning in the metaverse. Promoting storytelling and collectable assets in token format, even prior to the product launch (which can be digital or physical), will create interest in the product and the brand being marketed, as well as a new flow of income even before the product is available for sale. In the years to come, NFT could be the central touchpoint between brands and their consumers [ 100 ].
From the distribution point of view, NFT can break down the barriers between the physical and virtual worlds in a way that is similar to how modern omnichannel marketing systems integrate traditional distribution channels with online shopping. NFTs eliminate the barrier of the intermediary, thanks to blockchain technology. AI will be used to automate smart contracts, decentralized accounting books and other blockchain technologies to allow virtual transactions. In this terrain free of intermediaries or control, there will be a need to establish the rules of the game that make it possible to comply with the stipulated ethical codes [ 101 ].
Metaverse technologies allow for new and immersive interaction with customers, as well as providing useful data on customers beyond social media [ 6 ]. Enriched data about buyers and analytical capacities help to define customer profile and therefore to improve the sopping experience in virtual environments, promoting brand loyalty in the worlds of the metaverse [ 98 , 102 ].
Analytic marketing helps companies optimize campaigns, segment markets, reduce costs [ 103 ] and make better decisions [ 104 ]. Artificial Intelligence (AI) is being used to create digital twins that can provide data to simulate scenarios and further develop customer experience [ 105 ]. Blockchain technology is also being employed to promote ethical marketing strategies such as loyalty programs, traceable online advertising, brand transparency in online markets [ 86 , 89 ] or to claim ownership of original digital works and build loyalty [ 92 ].

The Fig 4 shows a graphical summary of Building Blocks of tourism marketing in the metaverse.

Discussions, conclusions and future research directions

Research into the topic of the metaverse, especially within the tourism sector, addresses an important priority because the impact of the metaverse in tourism marketing is still novel. The tourism industry is an interesting and relevant field of study due to its influence on the economy, society, culture, and environmental aspects of nations worldwide.

Screening of the SLR reveals that topics related to the metaverse evolve over time. Articles published prior to 2020 mainly focus on topics like Second Life, virtual world, and 3D, while more recent articles discuss concepts such as metaverse, blockchain, XR, AR, VR, Second Life, AI, virtual world, IoT, and NFTs. The majority of publications come from European universities, with the United Kingdom (12) and Germany (4) leading the way in research. Asia is also a major source of research, with South Korea (8) and China (7) being notable contributors. Finally, in America, United States produced the most number of publications, with 11 articles present in the literature review. Overall, these findings indicate that research into the metaverse and its implications for the tourism sector is an emergent research topic, with universities in European and North American countries leading the scientific research in this field, alongside Asian countries like South Korea and China, possibly driven by their growing interest in technological advancement.

Connecting the topic with existing theory, this research is presented as the first to conduct a SLR on tourism marketing in metaverse. The technologies that have been most thoroughly studied at the confluence of marketing, tourism, and the metaverse are: AI, virtual reality, augmented reality, mixed reality, blockchain, tokens (NFTs) and digital twins. Dwivedi et al. [ 6 ] and Hollensen, Kotler & Opresnik [ 22 ] explore the fundamental concepts and elements of marketing within the metaverse, whereas Buhalis, Leung & Lin [ 23 ] delve into the components of tourism in the metaverse. However, there is an absence of references pertaining to the building blocks of tourism marketing within the metaverse.

Given the embryonic stage of metaverse development and the limited knowledge surrounding its impact on society [ 106 ], an analysis of its evolution and adaptation to different sectors is needed to ensure it is established securely. The metaverse has already begun to transform the way people buy, work, socialize, and entertain, particularly for young early adopters. This article proposes the tourism industry as a case study to investigate marketing in the metaverse. In recent years, technology and creativity have been the driving forces behind the sector’s development. Creative industries are vital, accounting for 3% of the world’s GDP, and the current pandemic has caused them to grow and become more digitalized with the help of advanced technologies. Results from this research can be applied to other fields in the creative industries and will help to create knowledge around metaverse marketing.

Consequently, our research seeks to establish the building blocks of tourism marketing in the metaverse, by combining insights from the literature review with complimentary research, based on: the tourism product; the metaverse as a distribution and branding channel for tourism; tourist customer as protagonist. The research results show how the tourism product changes with the metaverse. Tourism products can be adapted to the metaverse with digital offerings, such as blockchain technology (e.g., NFTs) and virtual reality, and gamification allowing for creative fantasy experiences. The metaverse can be used as a sales channel and touchpoint between brands and their customers, with technologies such as AR, VR and NFTs enabling immersive experiences and personalized offers. Additionally, AI and blockchain can be used to create customer interaction, experience, and collect customer data in the metaverse. Tourism sector can benefit from the use of blockchain technology to claim ownership of digital works and build loyalty.

The systematic literature review points toward prospective research directions. Investigating tourism marketing in the metaverse should encompass several key areas:

Evaluating customer engagement and virtual experiences [ 98 ]. For example, the introduction of smart glasses by Ray-Ban, equipped with advanced features like a 5MP camera, three microphones, speakers, Bluetooth, and Wi-Fi capabilities, has the potential to transform the way travel experiences are captured and shared. This innovation also impacts the role of social media in sharing tourism experiences [ 107 ].
To keep customers motivated and engaged in the metaverse, gamification programs are expected to play a crucial role [ 108 ].
The use of blockchain technology can significantly contribute to creating a secure, decentralized, synchronized, and distributed record of digital transactions, eliminating the need for third-party intermediaries. This has the potential to revolutionize various aspects of the metaverse [ 54 , 55 ], including the potential of blockchain integration with the Internet of Things [ 109 ].
Research is also needed to explore the monetization of products in the metaverse, including the adoption of NFTs [ 53 ] the digital payment systems (DPS 2.0) [ 103 , 110 ]. It is essential to investigate which payment methods will be used in the metaverse and what new VR experiences will enable future tourists to experience [ 21 , 111 ].
The use of metaverses introduces new ways of business-to-consumer interaction that enable the simulation of the physical world in the virtual world [ 112 ]. Research should explore how metaverse distribution channels can become replacements for physical channels.
Additionally, research should investigate the potential for experience-based strategies instead of price strategies, as well as how intermediaries may be redefined in the metaverse.
It will also be necessary to consider what happens to companies and tourist destinations that don’t opt to use metaverse technologies.
The new profiles of marketing professionals and policy development that regulates commercial activity in the metaverse necessitates skills and knowledge focused on technology, predictive analytics, innovative strategies, and new mechanisms [ 113 ]. Tourism marketing professionals will need to adapt to the demands of the metaverse, as well as their corresponding training, skills and abilities.
Finally, research is needed to determine the ethical challenges associated with the development of virtual reality [ 114 ] as well as measures to protect customer data in the metaverse and how users can control, share, or monetize their data online [ 70 , 115 ].

Limitations

Due to its novelty, the research presents certain limitations in terms of the number of references analyzed. In addition, the fast evolution of both technology and publications on the metaverse means that is will be necessary to update the number of published articles on a monthly basis.

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Positioning – a literature review

Design/methodology/approach

Research limitations/implications

Social implications

Originality/value

1. Introduction

2. Concept of positioning

2.1 Issues in positioning research

3. Research method

3.1 Search strategy

3.2 Sample selection

3.3 Data analysis

4. Analysis and results

4.1 Journal-wise distribution of articles

4.2 Year-wise distribution of articles

4.3 Conceptualization of positioning in the marketing discipline

4.3.1 P1 – Competition.

4.3.2 P2 – Empty slot/mind.

4.3.3 P3 – consumers’ perception.

4.3.4 P4 – Differentiation.

4.3.5 P5 – Competitive advantage.

5. Research implications

6. Conclusion and limitations

Further reading

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Phase 1: accumulation of article pool

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Phase 3: categorization by internet marketing research topic

Results of phase 1

Results of phase 2

Results of phase 3

Investigating the marketing literature

Limitations and directions for future research

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Appendix A – data sample (411 information systems articles)

Appendix B – data sample (22 marketing articles)

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Tourism marketing in the metaverse: A systematic literature review, building blocks, and future research directions

Introduction

Methodology

Eligibility criteria and search strategy

SLR general statistics

Metaverse concept

Statistics on tourism in the metaverse

Most studied technologies for tourism marketing in metaverse

Blockchain technology and Non-Fungible Tokens (NFT).

VR, AR and MR technology.

Artificial intelligence (AI) and digital twins.

Practical cases of tourism marketing in the metaverse

Metaverse building blocks

A proposal of the building blocks of tourism marketing in the metaverse

Discussions, conclusions and future research directions

Limitations

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