literature review on tourism management system

• Open access
• Published: 25 November 2023

Systematic review and research agenda for the tourism and hospitality sector: co-creation of customer value in the digital age

• T. D. Dang   ORCID: orcid.org/0000-0003-0930-381X 1 , 2 &
• M. T. Nguyen 1  

Future Business Journal volume  9 , Article number:  94 ( 2023 ) Cite this article

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This article has been updated

The tourism and hospitality industries are experiencing transformative shifts driven by the proliferation of digital technologies facilitating real-time customer communication and data collection. This evolution towards customer value co-creation demands a paradigm shift in management attitudes and the adoption of cutting-edge technologies like artificial intelligence (AI) and the Metaverse. A systematic literature review using the PRISMA method investigated the impact of customer value co-creation through the digital age on the tourism and hospitality sector. The primary objective of this review was to examine 27 relevant studies published between 2012 and 2022. Findings reveal that digital technologies, especially AI, Metaverse, and related innovations, significantly enhance value co-creation by allowing for more personalized, immersive, and efficient tourist experiences. Academic insights show the exploration of technology’s role in enhancing travel experiences and ethical concerns, while from a managerial perspective, AI and digital tools can drive industry success through improved customer interactions. As a groundwork for progressive research, the study pinpoints three pivotal focal areas for upcoming inquiries: technological, academic, and managerial. These avenues offer exciting prospects for advancing knowledge and practices, paving the way for transformative changes in the tourism and hospitality sectors.

Introduction

The tourism and hospitality industry is constantly evolving, and the digital age has brought about numerous changes in how businesses operate and interact with their customers [ 1 ]. One such change is the concept of value co-creation, which refers to the collaborative process by which value is created and shared between a business and its customers [ 2 , 3 ]. In order to facilitate the value co-creation process in tourism and hospitality, it is necessary to have adequate technologies in place to enable the participation of all stakeholders, including businesses, consumers, and others [ 4 , 5 ]. Thus, technology serves as a crucial enabler for value co-creation. In the tourism and hospitality industry, leading-edge technology can be crucial in co-creation value processes because it can facilitate the creation and exchange of value among customers and businesses [ 6 , 7 ]. For example, the development of cloud computing and virtual reality technologies has enabled new forms of collaboration and co-creation that were not possible before [ 8 , 9 , 10 ]. Recent technologies like AI, Metaverse, and robots have revolutionized tourism and hospitality [ 11 , 12 , 13 ]. These technologies are used in various ways to enhance the customer experience and drive business success. AI can personalize the customer experience using customer data and personalized recommendations [ 14 ]. It can also optimize operations by automating tasks and improving decision-making. The metaverse, or virtual reality (VR) and augmented reality (AR) technologies, are being used to offer immersive and interactive experiences to customers [ 10 , 11 ]. For example, VR and AR can create virtual tours of hotels and destinations or offer interactive experiences such as virtual cooking classes or wine tastings [ 15 ]. Robots are being used to aid and interact with customers in various settings, including hotels, restaurants, and tourist attractions. For example, robots can provide information, answer questions, and even deliver room services [ 12 , 16 ]. The COVID-19 pandemic has underscored the crucial interplay between public health, sustainable development, and digital innovations [ 17 ]. Globally, the surge in blockchain applications, particularly in the business, marketing and finance sectors, signifies the technological advancements reshaping various industries [ 18 ]. These developments, coupled with integrating digital solutions during the pandemic, highlight the pervasive role of technology across diverse sectors [ 19 , 20 , 21 ]. These insights provide a broader context for our study of the digital transformation in the tourism and hospitality sectors. Adopting new technologies such as AI, the Metaverse, blockchain and robots is helping the tourism and hospitality industry deliver customers a more personalized, convenient, and immersive experience [ 22 ]. As these technologies continue to evolve and become more prevalent, businesses in the industry need to stay up-to-date and consider how they can leverage these technologies to drive success [ 23 , 24 ].

Despite the growing body of literature on customer value co-creation in the tourism and hospitality sector, it remains scattered and fragmented [ 2 , 25 , 26 ]. To consolidate this research and provide a comprehensive summary of the current understanding of the subject, we conducted a systematic literature review using the PRISMA 2020 (“ Preferred Reporting Items for Systematic Reviews and Meta-Analyses ”) approach [ 27 , 28 ]. This systematic review aims to explore three primary areas of inquiry related to the utilization of AI and new technologies in the tourism and hospitality industry: (i) From a technology perspective, what are the main types of AI and latest technologies that have been used to enhance co-creation values in tourism and hospitality?; (ii) From an academic viewpoint—What are the future research directions in this sector?; (iii) From a managerial standpoint—How can these technologies be leveraged to enhance customer experiences and drive business success?. In essence, this study contributes valuable insights into the dynamic realm of customer value co-creation in the digital age within the tourism and hospitality sector. By addressing the research questions and identifying gaps in the literature, our systematic literature review seeks to provide novel perspectives on leveraging technology to foster industry advancements and enhance customer experiences.

The remaining parts of this article are structured in the following sections: “ Study background ” section outlines pertinent background details for our systematic literature review. In “ Methodology ” section details our research objectives, queries, and the systematic literature review protocol we used in our study design. In “ Results ” section offers the findings based on the analyzed primary research studies. Lastly, we conclude the article, discuss the outstanding work, and examine the limitations to the validity of our study in “ Discussion and implications ” section.

Study background

Amidst the COVID-19 pandemic, the tourism sector is experiencing significant transformations. Despite the substantial impact on the tourism industry, the demand for academic publications about tourism remains unabated. In this recovery phase, AI and novel technologies hold immense potential to assist the tourism and hospitality industry by tackling diverse challenges and enhancing overall efficiency. In this section, the study provides some study background for the review processes.

The relationship between tourism and hospitality

Tourism and hospitality are closely related industries, as the hospitality industry plays a crucial role in the tourism industry [ 29 ]. Academics and practitioners often examine tourism and hospitality because they are related industries [ 2 , 30 ]. Hospitality refers to providing travelers and tourists accommodation, food, and other services [ 31 ]. These can include hotels, resorts, restaurants, and other types of establishments that cater to the needs of travelers [ 32 ]. On the other hand, the tourism industry encompasses all the activities and services related to planning, promoting, and facilitating travel [ 31 ]; transportation, tour operators, travel agencies, and other businesses that help facilitate tourist travel experiences [ 33 ]. Both industries rely on each other to thrive, as travelers need places to stay and eat while on vacation, and hospitality businesses rely on tourists for their income [ 32 , 33 , 34 ].

In recent years, the tourism industry has undergone significant changes due to the increasing use of digital technologies, enabling the development of new forms of tourism, such as “smart tourism” [ 8 , 10 ]. Smart tourism refers to using digital technologies to enhance the customer experience and improve the efficiency and effectiveness of the industry [ 1 ]. These technologies, including AI and Metaverse, can be used in various aspects of the tourism industry, such as booking and reservation processes, customer service, and the management of tourist attractions [ 4 , 11 ]. The hospitality industry, which includes hotels and restaurants, is closely linked to the tourism industry and is also adopting intelligent technologies to improve the customer experience and increase efficiency [ 1 , 22 ]. Recent studies have explored the impact of these technologies on the tourism and hospitality sectors and have identified both benefits and challenges for stakeholders [ 10 , 35 , 36 ].

Customer value co-creation in tourism and hospitality

Customer value co-creation in tourism and hospitality refers to the process by which customers and businesses collaborate to create value by exchanging services, information, and experiences [ 2 , 33 ]. This process involves the customer and the business actively creating value rather than simply providing a product or service to the customer [ 37 ]. Studies have found that customer value co-creation in tourism and hospitality can increase customer satisfaction and loyalty [ 2 ]. When customers feel that they can contribute to the value of their experience, they are more likely to feel a sense of ownership and involvement, which can lead to a more positive overall evaluation of the experience [ 5 , 38 ]. In the tourism industry, customer value co-creation can increase satisfaction with the destination, trips, accommodation, services, and overall experiences [ 4 ]. These can be achieved by allowing customers to choose their room amenities or providing opportunities to interact with staff and other guests [ 5 , 39 ]. Customer value co-creation in tourism and hospitality can be a powerful solution for businesses to increase customer satisfaction and loyalty. By actively involving customers in creating value, businesses can create a more personalized and engaging experience for their customers.

AI, Metaverse, and new technologies in tourism and hospitality

The impact of AI, the Metaverse, and new technologies on the tourism and hospitality industries is an area of active research and debate [ 2 , 4 , 29 , 40 ]. First, using AI and new technology in tourism and hospitality can improve the customer experience, increase efficiency, and reduce costs [ 13 , 41 , 42 , 43 ]. For instance, chatbots and virtual assistants facilitate tasks like room bookings or restaurant reservations for customers. Concurrently, machine learning (ML) algorithms offer optimized pricing and marketing strategies and insights into customer perceptions within the tourism and hospitality sectors [ 44 , 45 , 46 , 47 ]. However, there are also concerns about the potential negative impact of AI on employment in the industry [ 48 ]. Second, The emergence of the Metaverse, a virtual shared space where people can interact in real time, can potentially revolutionize the tourism and hospitality industries [ 10 ]. For example, VR and AR experiences could allow travelers to visit and explore destinations without leaving their homes [ 15 , 49 ], while online events and social gatherings could provide new business opportunities to connect with customers [ 11 ]. However, it is unclear how the Metaverse will evolve and its long-term impact on the tourism and hospitality industries [ 4 , 10 , 11 ]. Last, other emerging technologies, such as blockchain, AI-Robotics, and the Internet of Things (IoT), can potentially transform the tourism and hospitality industries [ 18 , 45 , 48 ]. For example, blockchain could be used to secure and track the movement of travel documents [ 18 ], while IoT-enabled devices could improve the efficiency and personalization of the customer experience [ 50 ]. As with AI and the Metaverse, it is difficult to predict the exact impact of these technologies on the industry, but they are likely to play a significant role in shaping its future [ 18 , 40 ]. In the aftermath of the pandemic, the healthcare landscape within the tourism and hospitality sector is undergoing significant transformations driven by the integration of cutting-edge AI and advanced technologies [ 38 , 51 , 52 ]. These technological advancements have paved the way for personalized and seamless experiences for travelers, with AI-powered chatbots playing a pivotal role in addressing medical inquiries and innovative telemedicine solutions ensuring the well-being of tourists [ 52 , 53 ].

This study background provides essential context for the subsequent systematic literature review, as it contextualizes the field’s key concepts, frameworks, and emerging technologies. By examining these aspects, the study aims to contribute valuable insights into the post-pandemic recovery of the tourism and hospitality industry, paving the way for future research opportunities and advancements in the field.

Methodology

This study meticulously adopted a systematic literature review process grounded in a pre-defined review protocol to provide a thorough and objective appraisal [ 54 ]. This approach was geared to eliminate potential bias and uphold the integrity of study findings. The formulation of the review protocol was a collaborative effort facilitated by two researchers. This foundational document encompasses (i) Clear delineation of the study objectives, ensuring alignment with the research aim; (ii) A thorough description of the methods used for data collection and assessment, which underscores the replicability of our process; (iii) A systematic approach for synthesizing and analyzing the selected studies, promoting consistency and transparency.

Guiding the current review process was the PRISMA methodology, a renowned and universally esteemed framework that has set a gold standard for conducting systematic reviews in various scientific disciplines [ 27 , 28 ]. The commendable efficacy of PRISMA in service research substantiates its methodological robustness and reliability [ 55 ]. It is not only the rigorous nature of PRISMA but also its widespread acceptance in service research that accentuates its fittingness for this research. Given tourism and hospitality studies’ intricate and evolving nature, PRISMA is a robust compass to guide our SLR, ensuring methodological transparency and thoroughness [ 56 , 57 ]. In essence, the PRISMA approach does not merely dictate the procedural intricacies of the review but emphasizes clarity, precision, and transparency at every phase. The PRISMA methodology presents the research journey holistically, from its inception to its conclusions, providing readers with a clear and comprehensive understanding of the approach and findings [ 58 ].

Utilizing the goal-question-metrics approach [ 59 ], our study aims to analyze current scientific literature from the perspectives of technicians, researchers, and practitioners to comprehend customer value co-creation through the digital age within the Tourism and Hospitality sector. In order to accomplish this goal, we formulated the following research questions:

What are the main types of AI and new technologies used to enhance value co-creation in the tourism and hospitality industries?

What are the future research directions in customer value co-creation through AI and new technologies in the tourism and hospitality sector?

How do managers in the tourism and hospitality sector apply AI and new technologies to enhance customer co-creation value and drive business success?

The subsequent subsections will provide further details regarding our search and analysis strategies.

Search strategy and selection criteria

We collected our data by searching for papers in the Scopus and Web of Science databases, adhering to rigorous scientific standards. We included only international peer-reviewed academic journal articles, excluding publications like books, book chapters, and conference proceedings [ 60 , 61 , 62 ]. The research process covered the period from 2009 to 2022, as this timeframe aligns with the publication of the first studies on value co-creation in the tourism industry in 2009 and the first two studies on value co-creation in general in 2004 [ 63 , 64 ]. The selection of sources was based on criteria such as timelines, availability, quality, and versatility, as discussed by Dieste et al. [ 2 ]. We employed relevant keywords, synonyms, and truncations for three main concepts: tourism and hospitality, customer value co-creation, and AI and new technologies in smart tourism and hospitality. To ensure transparency and comprehensiveness, we followed the PRISMA inclusion criteria, detailed in Table 1 , and utilized topic and Boolean/phrase search modes to retrieve papers published from 2009 to 2022. The final search string underwent validation by experts to ensure accuracy and comprehensiveness:

A PRISMA diagram was produced to understand better this study’s search strategy and record selection.

Study selection and analysis procedure

The current study utilized the PRISMA framework to document our review process. One hundred two papers were retrieved during the initial search across the databases. Table 1 outlines the criteria for selecting the studies based on scope and quality. The study adhered to the PRISMA procedure (as shown in Fig.  1 ) and applied the following filters:

We identified and removed 17 duplicate records during the ‘identification’ step.

We excluded 27 publications in the ‘Screening’ step based on the title and abstract.

We excluded 31 publications based on the entire text in the eligibility step.

PRISMA flow diagram

As a result, we were left with a final collection of 27 journal articles for downloading and analysis. Two trained research assistants conducted title and abstract screenings separately, and any disagreements about inclusion were resolved by discussing them with the research coordinator until an agreement was reached. Papers not in English, papers from meetings, books, editorials, news, reports, and patents were excluded, as well as unrelated or incomplete papers and studies that did not focus on the tourism and hospitality domain. A manual search of the reference lists of each paper was conducted to identify relevant papers that were not found in the database searches. After this process, 27 papers were left for a full-text review.

This study used the Mixed Methods Appraisal Tool (MMAT) to evaluate the quality of qualitative, quantitative, and mixed methods research studies included [ 65 , 66 ]. According to the findings, the quality of the study met the standards of a systematic review. Additional information can be obtained from Additional file 1 : Appendix 1.

In this section, we will report the results of our data analysis for each research question. We will begin by describing the characteristics of the studies included in the systematic literature review, such as (1) publication authors, titles, years and journals, topics, methods, and tools used in existing studies. Then each facet was elaborated by the following questions: (i) What are the main types of AI and new technologies used to enhance value co-creation in the tourism and hospitality industries? (ii) What are the future research directions in customer value co-creation through AI and new technologies in the tourism and hospitality sector? (iii) How do managers in the tourism and hospitality sector apply AI and new technologies to enhance customer co-creation value and drive business success?

Studies demographics

Figure  2 shows the yearly publication of articles on customer co-creation of value in tourism and hospitality through AI and new technologies. The chart’s data suggests two main findings. Firstly, the research on customer value co-creation in tourism and hospitality through AI and new technologies is still in its early stages (1 paper in 2012). However, the annual number of published articles from 2017 to the present appears to be generally increasing. This trend implies that the application of value co-creation in this field is gaining academic attention and is becoming an emerging research area. Based on this trend, we anticipate seeing more studies on this topic published in the following years.

Publication Years with research methods

Regarding research type, 14 papers (52%) conducted quantitative research, employing statistical analysis, structural equation modeling, and data mining methods. Meanwhile, 11 papers (41%) conducted qualitative research using interviews, thematic analysis, and descriptive analysis. Only two papers (7%) used mixed research (combining quantitative and qualitative methods). The survey and interview methods (both individual and group) were found to be more common than other research methods. This suggests that interviews provide greater insight into participant attitudes and motivations, enhancing accuracy in quantitative and qualitative studies. Additionally, certain studies employed content analysis, big data analysis using UGC, and data from online platforms, social media, and big data.

Regarding the publishing journals, we found that 27 papers were published in 22 journals (refer to Table 2 ), where three journals had more than one paper on co-creation value through AI and new technologies in tourism and hospitality, indicating their keen interest in this topic. Most publications were in the Journal of Business Research, with four studies on co-creation value through AI and new technologies in tourism and hospitality. Two related studies were published in the Tourism Management Perspectives and Journal of Destination Marketing & Management. This distribution indicates that most current research on co-creation value through AI and new technologies in tourism and hospitality was published in journals in the tourism and hospitality management field. However, some journals in the computer and AI field have also published papers on co-creation value through AI and new technologies in tourism and hospitality, including Computers in Industry, Computers in Human Behavior, Computational Intelligence, and Neuroscience.

Regarding data analytics tools, SmartPLS, AMOS, NVivo and PROCESS tools are the 5 most popular software graphic tools used in studies, while Python and R are the two main types of programming languages used. In total, 27 studies, 14 refer to using AI applications and data analytics in this research flow. Metaverse and relative technologies such as AR and VR were included in 8 studies. Three studies used service robots to discover the value co-creation process. There are include two studies that have used chatbots and virtual assistants.

Publication years and journals

In recent systematic literature reviews focusing on general services, tourism, and hospitality, there has been a notable emphasis on traditional factors shaping customer experience [ 26 , 67 , 68 ]. However, this study uniquely positions itself by emphasizing the digital age’s profound impact on value co-creation within this sector. The subsequent part digs more into the specifics of this study, building on these parallels. The detailed findings offer nuanced insights into how value co-creation in tourism and hospitality has evolved, providing a more extensive understanding than previous works.

Result 1—technology viewpoints: What are the main types of AI and new technologies used to enhance value co-creation in the tourism and hospitality industries?

Several types of AI and new technologies have been used to enhance co-creation values in the tourism and hospitality industry. Nowadays, AI, ML, and deep learning can all be used to enhance customer value co-creation in the tourism and hospitality industry [ 42 , 69 , 70 ]. There are some AI applications identified through the review process:

First, personalization and customized recommendations: AI and ML can be used to analyze customer data, such as their past bookings, preferences, and reviews, to personalize recommendations and experiences for them [ 7 , 69 , 71 , 72 ]. Cuomo et al. examine how data analytics techniques, including AI and ML, can improve traveler experience in transportation services. Applying AI and ML can help customers discover new experiences and activities they may not have considered otherwise [ 13 ]. Relating to data mining applications, Ngamsirijit examines how data mining can be used to create value in creative tourism. Moreover, the study also discusses the need for co-creation to create a successful customer experience in creative tourism and ways data mining can enhance the customer experience [ 73 ].

Second, user-generated content and sentiment analysis: ML and Natural Language Processing (NLP) can be used to analyze user-generated content such as reviews and social media posts to understand customer needs and preferences [ 12 , 37 ]. This can help businesses identify opportunities to create customer value [ 74 ]. NLP can analyze customer reviews and feedback to understand the overall sentiment toward a hotel or destination [ 75 ]. This can help businesses identify areas for improvement and create a better customer experience [ 70 ]. In the study using NLP to analyze data from Twitter, Liu et al. examine the impact of luxury brands’ social media marketing on customer engagement. The authors discuss how big data analytics and NLP can be used to analyze customer conversations and extract valuable insights about customer preferences and behaviors [ 74 ].

Third, recent deep learning has developed novel models that create business value by forecasting some parameters and promoting better offerings to tourists [ 71 ]. Deep learning can analyze large amounts of data and make more accurate predictions or decisions [ 39 , 41 ]. For example, a deep learning model could predict the likelihood of a customer returning to a hotel based on their past bookings and interactions with the hotel [ 72 ].

Some applications of the latest technologies that have been used to enhance co-creation values in tourism and hospitality include

Firstly, Chatbots and virtual assistants can enhance customer value co-creation in the tourism and hospitality industry in several ways: (i) Improved customer service: Chatbots and virtual assistants can be used to answer customer questions, provide information, and assist with tasks such as booking a room or making a reservation [ 45 ]. These tools can save customers and staff time and improve customer experience [ 76 ]; (ii) Increased convenience: Chatbots and virtual assistants can be accessed 24/7, meaning customers can get help or assistance anytime [ 50 ]. These tools can be handy for traveling customers with questions or who need assistance outside regular business hours [ 44 ]; (iii) Personalization: Chatbots and virtual assistants can use natural language processing (NLP) to understand and respond to customer inquiries in a more personalized way [ 45 , 70 ]. This can help improve the customer experience and create a more favorable impression of the business. Moreover, this can save costs and improve customers [ 16 ].

Secondly, metaverse technologies can enhance customer value co-creation in the tourism and hospitality industry in several ways: (i) Virtual tours and experiences: Metaverse technologies can offer virtual tours and experiences to customers, allowing them to visit and explore destinations remotely [ 77 ]. This technology can be beneficial for customers who are unable to travel due to pandemics or who want to preview a destination before deciding to visit in person [ 49 ]; (ii) Virtual events: Metaverse technologies can be used to host virtual events, such as conferences, workshops, or trade shows, which can be attended by customers from anywhere in the world [ 9 ]. This can save time and money for businesses and customers and increase the reach and impact of events; (iii) Virtual customer service: Metaverse technologies can offer virtual customer service, allowing customers to interact with businesses in a virtual setting [ 25 ]. This can be especially useful for customers who prefer to communicate online or in remote areas; (iv) Virtual training and education : Metaverse technologies can offer virtual training and education to employees and customers [ 41 ]. Metaverse can be an effective and convenient way to deliver training and can save time and money for both businesses and customers [ 7 ]; (v) Virtual reality (VR) experiences: Metaverse technologies can be used to offer VR experiences to customers, allowing them to immerse themselves in virtual environments and participate in activities that would be difficult or impossible to do in the real world [ 77 ]. This can enhance the customer experience and create new business opportunities to offer unique and memorable experiences [ 71 ].

Thirdly, IoT and robots can enhance customer value co-creation in the tourism and hospitality sector in several ways: (i) One way is by providing personalized and convenient customer experiences [ 12 ]. For example, hotels can use IoT-enabled devices to allow guests to control the temperature and lighting in their rooms, as well as access hotel amenities such as room service and concierge services [ 50 ]; (ii) In addition, robots can be used to provide assistance and enhance the customer experience in various ways [ 16 , 40 ]. For example, robots can be used to deliver items to guest rooms, assist with check-in and check-out processes, and provide information and directions to guests [ 12 ]; (iii) Both IoT and robots can be used to gather customer feedback and data in real-time, which can help to improve the quality and effectiveness of tourism and hospitality services [ 76 ]. For example, hotels can use IoT-enabled devices to gather data on guest preferences and needs, which can be used to tailor services and experiences to individual customers. This can help to improve customer satisfaction and loyalty [ 76 ]. Overall, using IoT and robots in the tourism and hospitality sector can help improve the industry’s efficiency and effectiveness and enhance the customer experience.

Result 2—academic viewpoints: What are the future research directions in customer value co-creation through AI and new technologies in the tourism and hospitality sector?

From an academic perspective, there are several potential future research directions in customer value co-creation through the digital age in the tourism and hospitality sector. Some possibilities include: (1) Understanding how different technologies and platforms facilitate co-creation: Researchers could investigate how different technologies and platforms, such as social media, mobile apps, or virtual reality, enable or inhibit co-creation in the tourism and hospitality industry; (2) Investigating the impact of co-creation on business performance: Researchers could examine the relationship between co-creation and business performance in the tourism and hospitality sector and identify the factors that drive success in co-creation initiatives; (3) Investigating the impact of AI and automation on co-creation: As AI and automation technologies become more prevalent in the industry, research could focus on the impact these technologies have on co-creation and value creation, including the potential for AI to facilitate or hinder co-creation; (4) Investigating the impact of the Metaverse on customer behaviour: Research could focus on understanding how the Metaverse affects customer behaviour and decision-making, and how companies can use this information to facilitate co-creation and value creation [ 9 ]; (5) Analysing the use of social media and other digital platforms for co-creation: Researchers could study how companies in the tourism and hospitality sector use social media and other digital platforms to facilitate co-creation with customers, and the impact that these platforms have on value creation [ 7 , 45 , 78 ]. Researchers could investigate how social interactions and communities in the Metaverse enable or inhibit co-creation in the tourism and hospitality industry and the impact on customer satisfaction and loyalty; (6) Examining the ethical implications of the Metaverse and AI: Researchers could explore the ethical considerations surrounding the use of the Metaverse and AI in the tourism and hospitality sector, such as issues related to privacy and data security, and the potential for these technologies to perpetuate or exacerbate societal inequalities [ 48 , 75 , 77 ].

Result 3—Management viewpoints: How do managers in the tourism and hospitality sector apply AI and new technologies to enhance customer co-creation value and drive business success?

There are several ways managers in the tourism and hospitality industry can apply AI and new technologies to enhance customer experiences and drive business success. We suggest four main possibilities: (1) Implementing chatbots or virtual assistants to encourage customer co-creation: Managers can use chatbots or virtual assistants to provide quick and convenient customer service, helping businesses respond to customer inquiries and resolve issues more efficiently [ 76 ]. Then, encourage customer co-creation by inviting customers to participate in the creation of new experiences and products by gathering feedback and ideas through online forums and focus groups [ 45 ]. This can help build a sense of community and engagement and can also lead to the development of new, innovative products and experiences that will attract more customers [ 50 , 79 ]; (2) Leveraging personalization technologies and using predictive analytics: Managers can use AI-powered personalization technologies to analyze customer data and preferences and offer personalized recommendations and experiences [ 42 , 72 , 80 ]. This can help businesses better understand and anticipate customer needs and create more tailored and satisfying experiences that drive co-creation value. Managers can leverage AI-powered predictive analytics technologies to analyze data and predict future customer behavior or trends [ 75 ]. This can help businesses anticipate customer needs and make informed decisions about resource allocation and planning, enhancing co-creation value. Managers can use personalization technologies and predictive analytics to analyze customer feedback and identify areas for improvement [ 37 ]. These can help businesses better understand customer needs and preferences and create more satisfying and valuable experiences that drive co-creation value [ 7 , 36 , 41 ]; (3) Using the Metaverse to facilitate co-creation: Managers can leverage the Metaverse to allow customers to design and customize their own experiences, which can help create value in collaboration with customers [ 25 , 71 , 77 ]. Managers can use VR and AR technologies to create immersive and interactive customer experiences in the Metaverse [ 81 ]. This can help businesses differentiate themselves and stand out in a competitive market. Managers can use data analysis tools to understand how customers behave in the Metaverse and use this information to create more personalized and satisfying experiences [ 9 ]. Managers can leverage the Metaverse to facilitate co-creation with customers, for example, by enabling customers to design and customize their own experiences [ 49 , 81 ]. This can help businesses create value in collaboration with customers; (4) Integrating AI-robotics into operations to support value co-creation: Analyse your business processes to identify tasks that can be automated using AI-powered robotics, such as check-in and check-out, room service, or concierge services [ 12 , 82 ]. Managers can consider using AI-powered robots for tasks such as check-in and check-out or for delivering amenities to guests. Use AI and the latest technologies to streamline the booking and check-in process, making it faster and more convenient for customers [ 16 ]. This can include using virtual assistants to handle booking inquiries or facial recognition technology to allow customers to check in at their hotel simply by showing their faces. These can help businesses reduce labor costs and improve efficiency, enhancing co-creation value [ 16 ]. We summarize three viewpoints in Fig.  3 below.

Summary of value co-creation through the Digital Age in Tourism and Hospitality

Combining these three viewpoints as a research agenda for tourism and hospitality in the AI and digital age holds immense potential. It addresses critical aspects such as customer experience enhancement, leveraging customer-generated content, and exploring cutting-edge technologies to create value co-creation opportunities. Researching these areas allows the industry to stay at the forefront of the digital revolution and deliver exceptional customer experiences that drive business success in the next few years.

Discussion and implications

This study aimed to develop a systematic literature review of customer value co-creation in the hospitality and tourism industry using the PRISMA protocol [ 27 ]. The study findings highlighted that tourism and hospitality should take advantage of AI and new technologies, as it brings significant advantages. Value co-creation in the tourism and hospitality sector refers to creating value through the collaboration and participation of multiple stakeholders, including tourists, employees, and the industry [ 2 ]. AI, Metaverse, and other new technologies can significantly enhance value co-creation in this sector by enabling more personalized, immersive, and efficient tourist experiences [ 40 , 80 , 81 ].

From a technology viewpoint, the study reveals that manifestations of customer value co-creation through the digital age are related to AI and the latest technologies such as Metaverse, robots, IoT, chatbots, intelligence systems, and others that shape co-creation [ 42 ]. AI applications and new technologies can help shape customer value co-creation in this sector. AI can follow the rules, think like an expert, learn from data, and even create virtual and augmented reality experiences [ 4 , 10 ]. Chatbots, personalization, predictive analytics, and robotics are examples of how AI and technology can create unique and fun travel experiences [ 16 , 40 , 74 , 83 ].

From an academic viewpoint, researchers look at ways technology can help people enjoy their travels and stay in hotels by boosting the value co-creation process [ 2 ]. They are looking at how different technologies, like social media, can help people create value for themselves and others [ 45 , 84 ]. They are also looking at how AI and the virtual world can change people’s decisions and how companies can use this information to help people [ 77 , 80 ]. Finally, researchers are looking into the ethical issues of using technology in tourism and hospitality [ 48 , 75 , 77 ].

From the manager’s viewpoint, managers in the tourism and hospitality industry can use AI and new technologies to create better customer experiences and drive success [ 70 , 80 ]. These can include using chatbots or virtual assistants to help customers and get their feedback [ 50 , 76 ], using personalization technologies to understand customer needs [ 69 ], using the Metaverse to have customers design their own experiences [ 10 ], and using AI-robotics to automate tasks [ 16 , 82 ].

In light of the findings from this systematic literature review, policymakers in the tourism and hospitality sectors must revisit and revitalize current strategies. Embracing digital age technologies, especially AI and metaverse tools, can significantly enhance customer value co-creation. This necessitates targeted investments in technology upgradation, capacity-building, and skilling initiatives. While the initial resource allocation may appear substantial, the long-term returns regarding elevated customer satisfaction, increased tourism inflow, and industry-wide growth are undeniable. Policymakers must ensure a collaborative approach, engaging stakeholders across the value chain for streamlined adoption and implementation of these advancements.

Overall, the use of AI, Metaverse, and other new technologies can significantly enhance co-creation value in the tourism and hospitality sector by enabling more personalized, immersive, and efficient experiences for tourists and improving the efficiency and effectiveness of the industry as a whole [ 15 ].

Theoretical implications

The systematic literature review using the PRISMA method on customer value co-creation through the digital age in the tourism and hospitality sector has several theoretical implications.

First, this research paper addresses earlier suggestions that emphasize the significance of further exploring investigations on customer value co-creation in the hospitality and tourism sector [ 2 , 85 ].

Second, the review highlights the importance of adopting a customer-centric approach in the tourism and hospitality industry, in which customers’ needs and preferences are central to the design and delivery of services [ 35 , 86 ]. This shift towards customer value co-creation is driven by the increasing use of digital technologies, such as the IoT, AI, and ML, which enable real-time communication and data gathering from customers [ 1 , 40 ].

Third, the review highlights the role of digital technologies in enabling personalized and convenient customer experiences, which can help improve satisfaction and loyalty [ 87 ]. Using AI-powered chatbots and personalized recommendations based on customer data can enhance the customer experience, while using IoT-enabled devices can allow guests to control and access hotel amenities conveniently [ 12 ].

Fourth, the review suggests that adopting digital technologies in the tourism and hospitality sector can increase the industry’s efficiency and effectiveness [ 88 ]. Businesses use ML algorithms to automate tasks and analyze customer data, which can help streamline processes and identify areas for improvement [ 39 , 80 ].

Overall, the systematic literature review using the PRISMA method sheds light on adopting a customer-centric approach and leveraging digital technologies for customer value co-creation in tourism and hospitality. Over the next five years, researchers should focus on exploring the potential of emerging technologies, developing conceptual frameworks, and conducting applied research to drive meaningful transformations in the industry. By aligning strategies with these implications, organizations can thrive in the dynamic digital landscape and deliver exceptional customer experiences, ultimately contributing to their success and competitiveness in the market [ 2 , 4 , 15 , 29 , 33 , 89 ].

Practical implications

The systematic literature review using the PRISMA method on customer value co-creation through the digital age in the tourism and hospitality sector has several management implications for organizations in this industry.

First, the review suggests that adopting a customer-centric approach, in which customers’ needs and preferences are central to the design and delivery of services, is crucial for success in the digital age [ 40 , 86 ]. Therefore, managers should focus on understanding and meeting the needs and preferences of their customers and consider how digital technologies can be leveraged to enable real-time communication and data gathering from customers [ 15 , 80 ].

Second, the review highlights the importance of using digital technologies like the IoT, AI, and ML to enable personalized and convenient customer experiences [ 40 , 50 ]. Managers should consider how these technologies can enhance the customer experience and improve satisfaction and loyalty [ 36 , 39 ].

Third, the review suggests that adopting digital technologies in the tourism and hospitality sector can lead to increased efficiency and effectiveness in the industry [ 7 , 16 ]. Therefore, managers should consider how these technologies can streamline processes and identify areas for improvement [ 42 ]. Further, regarding privacy concerns, managers must spend enough resources to secure their customers’ data to help boost the customer value co-creation process [ 48 , 77 ].

Fourth, policymakers can foster an environment conducive to value co-creation by incorporating customer-centric strategies and leveraging digital technologies. Effective policies can enhance customer experiences, promote sustainable growth, and drive economic development, ensuring a thriving and competitive industry in the digital age.

The practical implications of applying AI and new technology for managerial decision-making in the tourism and hospitality industry are vast and promising [ 90 ]. Managers can navigate the dynamic digital landscape and drive meaningful co-creation with customers by embracing a customer-centric approach, leveraging personalized technologies, addressing efficiency and data security considerations, and strategically adopting AI-powered tools. By staying abreast of technological advancements and harnessing their potential, businesses can thrive in the next five years and beyond, delivering exceptional customer experiences and enhancing value co-creation in the industry.

Limitations and future research

The research, anchored in the PRISMA methodology, significantly enhances the comprehension of customer value co-creation within the digital ambit of the tourism and hospitality sectors. However, it is essential to underscore certain inherent limitations. Firstly, there might be publication and language biases, given that the criteria could inadvertently favor studies in specific languages, potentially sidelining seminal insights from non-English or lesser-known publications [ 91 ]. Secondly, the adopted search strategy, governed by the choice of keywords, databases, and inclusion/exclusion guidelines, might have omitted pertinent literature, impacting the review’s comprehensiveness [ 57 ]. Furthermore, the heterogeneous nature of the studies can challenge the synthesized results’ generalizability. Finally, the swiftly evolving domain of this research underscores the ephemeral nature of the findings.

In light of these limitations, several recommendations can guide subsequent research endeavors. Scholars are encouraged to employ a more expansive and diverse sampling of studies to curtail potential biases. With the digital technology landscape in constant flux, it becomes imperative to delve into a broader spectrum of innovations to discern their prospective roles in customer value co-creation [ 18 ]. Additionally, varied search strategies encompassing multiple databases can lend a more holistic and inclusive character to systematic reviews [ 27 ]. Moreover, future research could investigate the interplay between political dynamics and the integration of novel technologies, enriching the understanding of value co-creation in a broader socio-political context. Lastly, integrating sensitivity analyses can ascertain the findings’ robustness, ensuring the conclusions remain consistent across diverse search paradigms, thereby refining the review’s overall rigor.

In conclusion, this review highlights the pivotal role of digital technologies in customer value co-creation within the tourism and hospitality sectors. New AI, blockchain and IoT technology applications enable real-time communication and personalized experiences, enhancing customer satisfaction and loyalty. Metaverse technologies offer exciting opportunities for immersive interactions and virtual events. However, privacy and data security challenges must be addressed. This study proposed a comprehensive research agenda addressing theoretical, practical, and technological implications. Future studies should aim to bridge research gaps, investigate the impact of co-creation on various stakeholders, and explore a more comprehensive array of digital technologies in the tourism and hospitality sectors. This study’s findings provide valuable insights for fostering innovation and sustainable growth in the industry’s digital age. Despite the valuable insights gained, we acknowledge certain limitations, including potential biases in the search strategy, which underscore the need for more inclusive and diverse samples in future research.

Availability of data and materials

The review included a total of 27 studies published between 2012 and 2022.

Change history

07 february 2024.

A Correction to this paper has been published: https://doi.org/10.1186/s43093-023-00293-2

Abbreviations

• Artificial intelligence

Augmented reality

Internet of Things

Machine learning

Preferred Reporting Items for Systematic Reviews and Meta-Analyses

Virtual reality

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Dang, T.D., Nguyen, M.T. Systematic review and research agenda for the tourism and hospitality sector: co-creation of customer value in the digital age. Futur Bus J 9 , 94 (2023). https://doi.org/10.1186/s43093-023-00274-5

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• Customer value co-creation
• Tourism and hospitality

Internet of Things (IoT) in smart tourism: a literature review

Spanish Journal of Marketing - ESIC

ISSN : 2444-9695

Article publication date: 21 September 2022

Issue publication date: 13 December 2022

Although there has been a significant amount of research on Smart Tourism, the articles have not yet been combined into a thorough literature review that can examine research streams and the scope of future research. The purpose of this study is to examine the literature on the impact of deploying the Internet of Things (IoT) in tourism sector development to attract more visitors using a text mining technique and citation based bibliometric analysis for the first time.

Design/methodology/approach

This study uses R programming to do a full-text analysis of 36 publications on IoT in tourism and visualization of similarities viewer software to conduct a bibliometric citation analysis of 469 papers from the Scopus database. Aside from that, the documents were subjected to a longitudinal study using Excel and word frequency using a trending topic using the R-tool.

Results from the bibliometric study revealed the networks that exist in the literature of Tourism Management. With the use of log-likelihood, the findings from text mining identified nine theme models on the basis of relevancy, which is presented alongside an overview of the existing papers and a list of the primary authors with posterior probability using latent Dirichlet allocation.

Originality/value

This study examines tourism literature in which IoT plays a significant role. To the best of the authors’ knowledge, this study is the first to combine text mining with a bibliometric review. It significantly analyzes and discusses the impact of technology in the tourism sector development on attracting tourists while presenting the most important and frequently discussed topics and research in these writings. These findings provide researchers, tourism managers and technology professionals with a complete understanding of e-tourism and to provide smart devices to attract tourists.

Aunque ha habido un número importante de estudios sobre el turismo inteligente, todavía no se dispone de una revisión bibliográfica exhaustiva que permita examinar las corrientes de investigación y las sugerencias de investigación futuras. Este estudio examina la literatura sobre el impacto del Internet de las cosas en el desarrollo del sector turístico para atraer más visitantes utilizando una técnica de minería de textos y un análisis bibliométrico basado en citas.

Metodología

Este estudio utiliza la programación R para hacer un análisis de texto completo de 36 publicaciones sobre IoT en el turismo y el software de visualización de similitudes (VOS) para realizar un análisis bibliométrico de citas de 469 documentos de la base de datos Scopus. Además, los documentos fueron sometidos a un estudio longitudinal mediante Excel y a la frecuencia de palabras mediante un tema de tendencia utilizando la herramienta R.

Los resultados del estudio bibliométrico revelaron las redes existentes en la literatura de la Gestión Turística. Con el uso de la log-verosimilitud, los resultados de la minería de textos identificaron nueve modelos temáticos sobre la base de la relevancia, que se presentan junto con una visión general de los documentos existentes y una lista de los autores principales con probabilidad posterior utilizando la asignación latente de dirichlets.

Originalidad

Este estudio examina la literatura sobre turismo en la que la IoT desempeña un papel importante. Este estudio es el primero que combina la minería de textos con una revisión bibliométrica. Analiza y discute de forma significativa el impacto de la tecnología en el desarrollo del sector turístico para atraer a los turistas, a la vez que presenta los temas e investigaciones más importantes y más frecuentemente discutidos en estos escritos. Estos resultados proporcionan a los investigadores, gestores turísticos y profesionales de la tecnología una comprensión integral del turismo electrónico y los dispositivos inteligentes para atraer a los turistas.

虽然已经有大量关于智慧旅游的研究, 但这些文章尚未整合成一个全面的文献综述, 可以检阅目前的研究流和未来研究的范畴。本研究首次使用文本挖掘技术和基于引文的文献计量分析, 来研究有关在旅游业发展中部署物联网对吸引更多游客的影响的文献。

本研究使用R编程对36篇关于旅游业物联网的文章进行全文分析, 并使用相似性可视化（VOS）查看器软件对Scopus数据库中的469篇论文进行文献计量引文分析。除此之外, 还利用Excel对这些文献进行了纵向研究, 并使用R工具对趋势主题进行了词频分析。

文献计量研究的结果揭示了旅游管理文献中现有的网络。通过使用对数似然, 文本挖掘的结果根据相关性确定了9个主题模型, 这些模型与现有论文的概述和主要作者名单在使用潜在狄里奇分配（LDA）的后验概率一起呈现。

本研究对旅游物联网相关文献进行了分析研究, 它首次将文本挖掘与文献计量学审查相结合。这项研究着重分析和讨论了技术在旅游行业发展中对吸引游客的影响, 同时介绍了这些文章中最重要和经常讨论的主题和研究。这些发现为研究人员、旅游管理者和技术专家提供了对科技与旅游的全面了解, 并提供关于智能设备来吸引游客的建议。

• Text mining
• Bibliometric
• Internet of Things (IoT)
• Inteligente
• Internet de las cosas (IoT)
• Bibliometría
• Minería de textos

Novera, C.N. , Ahmed, Z. , Kushol, R. , Wanke, P. and Azad, M.A.K. (2022), "Internet of Things (IoT) in smart tourism: a literature review", Spanish Journal of Marketing - ESIC , Vol. 26 No. 3, pp. 325-344. https://doi.org/10.1108/SJME-03-2022-0035

Emerald Publishing Limited

Copyright © 2022, Chowdhury Noushin Novera, Zobayer Ahmed, Rafsanjany Kushol, Peter Wanke and Md. Abul Kalam Azad.

Published in Spanish Journal of Marketing – ESIC . 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 maybe seen at http://creativecommons.org/licences/by/4.0/legalcode

1. Introduction

The Internet of Things (IoT) is a revolutionary technology that is progressively gaining traction in today’s wireless telecommunications environment. The IoT concept’s key strength is the significant impact it will have on various elements of everyday life and on potential user behavior ( Atzori et al. , 2010 ). IoT is rapidly playing an essential role in services, where it is undoubtedly essential for the tourism industry, and one of the biggest drivers of internet use in the economy has been tourism ( Hjalager, 2002 ). The tourist industry is made up of several stakeholders and has an influence on a country’s overall gross domestic product (GDP); thus, expanding the tourism industry will slowly increase its GDP. As a result, the use of IoT in the tourism business is an important topic to consider. Innovation is still in its early stages of development and has seen both positive and negative effects, as well as various challenges ( Verma and Shukla, 2019 ). Especially in hotels, transportation and attractions, the tourist industry is trying to keep up with the pace to be effectively linked with its guests all of the time.

IoT has evolved into a useful and practical tool for promoting evidence-based practice in tourism management. The way IoT has shown its uses in other sectors has also shown its magic in the tourism sector, such as smart applications, smart services and smart management. But this blessing can also turn into a curse if smart applications, data security or the data infrastructure are not used properly or are not user-friendly. All these positive and negative uses create conflicts about using IoT in tourism management, so the focus of this study is to analyze the previous papers and find out which use is more in practice.

In this paper, the lack of a comprehensive literature review on IoT in tourism is fulfilled through the bibliometric and text mining review methods. While technology continues to advance, the tourist sector has developed to become one of the most important sectors globally in this modern period. These facts have transformed the notion of “Smart Tourism”, which is a step forward from heritage tourism. As a consequence of this smart tourism, a variety of review papers have been published. To the best of our knowledge, there is a substantial quantity of study on the topic of Smart Tourism, but the papers have not yet been compiled into a comprehensive literature review ( Kontogianni and Alepis, 2020 ). As a result, a literature evaluation encompassing the majority of the documents published, including the application of IoT in the tourism business, are required.

Since there are no literature reviews on IoT in tourism, whether using the bibliometric or text mining approach, we decided to use both these methods to do the review. The complete list of documents related to the IoT-based tourism literature is studied in the first phase of the study using a citation mapping approach known as bibliometric analysis. The findings of this bibliometric study containing the co-occurrence network and bibliometric coupling demonstrate the importance of this research regarding deciding on an IoT application to enhance the tourist business. But for covering the maximum documents on IoT in tourism and having an effective analysis with a detailed review, the text mining technique is also used on a selection of 36 papers. So, in this paper, the text mining approach is a need side by side bibliometric analysis for uncovering the overall opinion of the authors about the use of IoT in tourism. Although both approaches are done using software, the visualization of similarities (VOS)-viewer software for the bibliometric approach has the limitation of not supporting other databases other than Scopus and the R software, whereas the text mining approach has the limitation of not taking many papers due to the time consumed.

The main aim of the paper is to examine the literature on the impact of deploying the IoT in the tourism sector to attract more visitors by using a text mining technique and citation-based bibliometric analysis. So, the people who will be benefitted from the paper are the tourists and people researching or involved with tourism and IoT. The demand for IoT is increasing day by day, bringing special advantages to our daily life. Using IoT has impressed and impacted people greatly, and that is why tourism management through IoT is a topic worth reading as people will get to know new insights and directions. Since the tourism sector plays a great role in a nation’s income, this motivates analyzing how IoT is used in tourism management. This study evaluated 469 papers through bibliometric analysis and 36 papers through text mining analysis. Both these methods have been the recent center of attraction ( Ikra et al. , 2021 ; Jarin et al. , 2021 ; Loureiro et al. , 2020 ; Quatrini et al. , 2022 ), being used to analyze a huge number of articles, through which our knowledge will be enriched with new insights about tourism management through IoT.

The paper is divided into six sections. Section 1 provides an introduction, whereas the methodological elements and a brief overview of the procedures of text mining, bibliometric analysis and sentiment analysis used in this study are presented in Section 2. Section 3 explains the network analysis as well as a longitudinal review of the literature on using IoT in the tourism industry dubbed “smart tourism”. Section 4 demonstrates the advanced review, including the text mining approach, results and discoveries, as well as the description. Section 5 discusses the limitations, research gap and future research objectives, followed by Section 6, conclusions.

2. Methodology

A literature review is a summary of previously published works on a particular subject. The bibliometric review system is used in this report as one of the numerous techniques of literature evaluation because of its ability to generate study items in a research subject based on citation mapping within newly published documents. According to past evaluations, a bibliometric approach is required for a more thorough and comprehensive literature review ( Saúl et al. , 2012 ), but like all other research methods, the bibliometric review has a few significant drawbacks where, according to Justicia De La Torre et al. (2018) , text mining allows researchers to efficiently evaluate large amounts of data, revealing key connections between entities that could not have been discovered otherwise. As a result, the text mining approach is also used side by side along with bibliometric review to take this in-depth evaluation to the advanced level.

Text mining, also known as knowledge discovery, is a subprocess of data mining that is commonly used to uncover hidden patterns and important information in large amounts of unstructured textual data. This study covers text mining techniques using latent Dirichlet allocation (LDA) analysis for assessing articles because of these sophisticated characteristics.

The keyword “IoT” OR “Internet of Thing*” was initially searched inside the title, abstract and keywords of articles in the Scopus database, resulting in a total of 121,845 papers being retrieved. The keyword “hospitality” OR “hotel” OR “tourist” was used to narrow down the number of paper which resulted in a total of 475 most relevant papers to the study. Finally, only articles published in English were chosen for the longitudinal research, resulting in a total of 469 papers. Among these documents, there are 142 articles, 232 conference papers, 22 book chapters, 65 conference reviews, five reviews, two editorial notes and one retracted article. Only 236 papers were discovered as advancing documents inside the topic limit after the authors manually observed them. The writers then manually selected 128 documents from those 236 based on their relevance to the issue. Only 36 papers were picked manually for text mining based on a five-year journal impact factor larger than 1.36. Figure 1 depicts the selection procedure of the articles.

Why 36 publications were picked for the study is addressed below. We began by searching for articles related to the issue using key terms, and we discovered 475 papers, considering only the 469 papers that were in English. We looked at articles on text mining approaches by Loureiro et al. (2020) and Quatrini et al. (2022) and noticed that there were less of them because LDA is a time-consuming technique. These articles were also published in prestigious publications, so as a result, we decided to follow their lead and attempted to sort and minimize the number of documents, deciding to analyze 36 studies. It took 20 h to analyze these 36 publications.

After the selection of papers, the methods used in this literature review paper are presented in the form of a tree in Figure 2 . Here the tree is divided into four parts: source of the documents, techniques used to do the analysis, indicators included in the techniques and the result of the analysis. The tree first takes the retrieved articles from the Scopus database and reveals that Excel is used for the documents’ longitudinal overview, which includes the number of publications, mean total citation per article and year. The result shows the development of the number of publications per year. Second, VOS-viewer is used for Bibliometric Networks, including bibliographic coupling analysis and co-occurrence network, and the result shows relevance in author keywords and top citation overview per article. Finally, the main focus of this paper, the R-tool for text mining, is used to do sentiment analysis and latent Dirichlet analysis, and the result shows the positive sentiments and topic models with relevant topic terms per article.

3. Analysis

Next, some analyses on the papers selected are discussed, including the trending topics of the documents per year. Taking the term frequency (freq) levels from 2012 to 2021, the trending topics are found with the help of biblioshiny of R tool. The motive behind finding the list of trending topics is to know which words used by the authors were trendier at the time of the publications of the papers so that we could understand the depth of the topic relevant to the importance of IoT use in tourism management. The words are counted from the year 2013 to the year 2021, and their trend is represented in the given frequency level of 50, 100, 150 and 200. The higher the frequency, the more the topic is trendy. For example, from 2012 to 2014, the frequency level was less than 50, which proves the topics were less trendy. Gradually in recent years, the topic gets trendier as the frequency level increases. Noteworthy trendy topics were “IoT”, “information management”, “AI”, “tourism”, “big data”, “leisure industry”, “privacy by design” and so on, which proves the necessity and effort of developing smart tourism to attract the tourist more.

3.1 Longitudinal overview

The longitudinal overview of the documents selected is discussed, which includes the mean total citation per article and per year of the papers selected, along with the number of publications. Excel was used to find the data for this discussion. The result shows that the highest number of mean citations per article and per year was reached in 2015. In total, 15 articles were published that year. The papers discussed that a smart tourist spot is a connection of stakeholders and their digital depictions that prove smart tourism to be more efficient and effective ( Del Chiappa and Baggio, 2015 ). There is also a platform called smart scenic spot service that will improve tourist visits, make tourism management more scientific and standard, and boost tourism enterprise profits ( Yin and Wang, 2015 ). Though in the early years, the number of publications was less, the numbers began to rise gradually beginning in 2016 and the number was highest in 2020.

3.2 References network analysis

The bibliometric technique is used to provide an overview of the information for IoT in the tourism industry to provide a faster and more effective literature review. For this, references of published papers are gathered to undertake a network analysis of the document relationships. The references were acquired from the Scopus library’s reference section, and the network analysis of the associated papers was performed using VOS-viewer software.

Bibliographic coupling is a similarity metric that uses citation analysis to build a similar relationship between texts. Figure 3(a) shows a document-based bibliometric coupling analysis. When the minimum number of local citations is 3, only 40 documents out of 390 matches the criteria. The bibliographic coupling resulted in 40 nodes divided into nine clusters. The size of the node represents how many times the papers have been cited. Red, green, blue, yellow, purple, cyan, orange and brown are the eight clusters available here.

Co-occurrence networks are a set of graphs that show the probable connections between persons, organizations, concepts and other entities depicted in the textual content. The co-occurrence network of author keywords is presented in Figure 3(b) , which shows keywords used by authors in documents that are similar but not identical, and are based on the same topic showing the relation with the papers in Figure 3(a) . Here, when the least number of occurrences for a keyword is seven, 14 out of 1,002 keywords meet the criteria. The co-occurrence network of using IoT in the tourism industry may be described as a total of 14 nodes of 4 clusters with 46 links and 142 link strengths. The term “clusters” also refers to the interconnection of research streams. The keyword occurrence number is determined by the size of the node. The four clusters (red, green, blue and yellow) explain why similar-themed keywords appear in the same color nodes. Figure 3(a) and (b) presents that the findings are in accordance.

In Figure 3(a) , cluster 1 (red) deals with the digitalization of the tourism industry. Mohamed et al. (2020) were curious to learn more about existing big data platforms and their applications in the tourism industry, along with the benefits and drawbacks of big data tools, big data analytics methodologies and new research opportunities in the future development of big data systems. Pencarelli (2020) intended to present a point of view on the impact of the digital revolution on tourism along with parallels and contrasts between tourism 4.0 and smart tourism using a conceptual technique and focusing on the tourism business. Cluster 2 (green) in Figure 3(a) indicates the attributes and evolution of smart tourism. Tripathy et al. (2018) offered iTour, an IoT-based framework for independent tourist mobility, as a potential IoT-based solution. They examined the challenges in efforts and lessons learned, as well as IoT’s potential possibilities. Kulakov (2017) discussed a method for evaluating the effectiveness of services with smart qualities. For each attribute used, the execution situation, conventional (nonsmart) service for comparison and the estimates used are presented. The method shown here may be used for smart services that take advantage of big data analytics. Cluster 3 (blue) in Figure 3(a) discusses the smart space of IoT. A smart space improves a networked computing environment by allowing digital devices to share information. The role of wireless communication and mobile participation becomes critical in the rising case of IoT ecosystems. Korzun et al. (2016) investigated the smart places that may be generated by using a semantic information broker. The primary terms in Cluster 3 (blue) IoT – 83 times; smart city – 15 times) in Figure 3(b) are related to Clusters 1 (red), 2 (green) and 3 (blue) in Figure 3(a) .

Cluster 4 (yellow) in Figure 3(a) deals with the smartness of e-tourism and the development of smart tourism. Social network, content marketing and wearable IoT devices will all be required in IoT big data tourist applications. Wise and Heidari (2019) presented practical foundations for destination organizers and stakeholders in this new smart tourism paradigm after establishing a basic understanding of the IoT and its promise for smart cities. Hamid et al. (2021) offered a cutting-edge e-tourism data management categorization taxonomy based on smart concepts, and they assessed works in many disciplines against it. In Figure 3(b) , the primary terms in Cluster 4 (yellow) (e-tourism – 10 times) are related to Cluster 4 (yellow) in Figure 3(a) .

Cluster 5 (purple) in Figure 3(a) discusses smart homes and health care vicinity for smart tourism destinations. Aung and Tantidham (2017) outlined a private Blockchain deployment strategy for a smart home system (SHS) to address its privacy and security concerns. Based on smart contract capabilities for network access, storage systems and data flow control, they assessed Ethereum Blockchain solutions for SHS. Almobaideen et al. (2017) provided a novel method for determining which geographical routes were best supported by nearby medical clinics. Their method, known as Geographical Routing for Mobile Tourists, chooses a route that is well-served by medical clinics and follows the shortest path possible in terms of distance. In Figure 3(b) , the primary terms in cluster 1 (red) (IoT – 60 times; big data – 24 times; tourism – 23 times; hospitality – 9 times; security – 7 times) are related to Cluster 5 (purple) in Figure 3(a) .

The security framework and potential of IoT for smart tourism with fifth-generation (5G) and AI are discussed in Cluster 6 (cyan) in Figure 3(a) . The 5G wireless system will support the IoT, increasing the interconnectivity of electronic devices to support a variety of new and promising networked applications. There is still no proven technique for creating security frameworks with device authentication and access control. Huang et al. (2016) tried to solve the problem by creating a prototype security architecture that provides reliable and transparent security protection. Cluster 7 (orange) and Cluster 8 (brown) in Figure 3(a) both discussed the smart city ecosystem that is IoT equipped. Few research studies have addressed the accompanying business models because the IoT and other enabling technologies are still in their early stages of adoption around the world. Díaz-Díaz et al. (2017) intended to fill this void. Their main goal was to learn more about actual business models that can be integrated into a real-world smart city ecosystem. Nolich et al. (2019) showed how the proposed system works in a demo cruise cabin where the E-Cabin application can be used to create different atmospheres based on the users and activities in the cabin. In Figure 3(b) , the primary terms in Cluster 2 (green) (smart tourism – 33 times; smart cities – 12 times; artificial intelligence – 7 times) are related to Cluster 6 (purple), 7 (orange) and 8 (brown) in Figure 3(a) .

4. Text mining

4.1 sentiment analysis.

The opinion expressed in constructive comments, criticism and critiques can be used for a variety of reasons. These feelings can be classified into two groups: positive and negative or on a Likert scale including very good, good, neutral, bad and very bad ( Prabowo and Thelwall, 2009 ). Sentiment analysis is used in this section to detect positive and negative sentiments stated throughout the review to evaluate the overall sentiment trend of the IoT’s impact on tourism management. As previously stated, sentiment analysis was performed on the 36 papers that were selected for final evaluation, which were converted into text files manually and a corpus was created with the files. The cleaning of data in the corpus was done using the statistical package R’s string, tm and topic model tools. After cleaning the data, the retrieved text was assessed for positive and negative emotions by comparing it with the lexicon reference using the R tool. The relevance of the Lexicon used in the process includes 2,006 positive terms and 4,783 negative words, which are referred to in the summary of positive and negative emotions. A few examples of positive words (reference) are accommodative, beautiful, delighted and freedom, whereas a few examples of negative words (reference) are absurdness, cheating, exaggerate and hypocrite.

The sentiment scores for each document were calculated separately. The quantity of matching positive and negative terms per document is displayed, demonstrating the papers’ positive and negative feelings. Then the final score shows the difference between the positive and negative sentiments of each document. The score shows that there is only one document with a negative score and the rest are positive. For example, the highest score is (246) for a document ( Li and Cao, 2018 ) which expresses a more positive sentiment. This suggests that using IoT in tourism might be one of the greatest ways to attract tourists and improve a country’s tourism sector economically according to them. The lowest score is (–4) for a document ( Prandi et al. , 2021 ), which is the only negatively scored document. These sentiment scores prove that the authors support the use of smart technology more since their studies focused on the positive aspects.

4.2 Latent Dirichlet allocation analysis

One of the most powerful text mining approaches for data mining is latent data discovery while detecting links between data and text documents is topic modeling. Topic modeling can be done in a variety of ways, with LDA being one of the most prominent ( Jelodar et al. , 2019 ), which is the main focus of this research. The number of latent themes was determined through the R tool using the measures of log-likelihood and perplexity ( Arun et al. , 2010 ; Cao et al. , 2009 ; Griffiths and Steyvers, 2004 ). Perplexity is a measure that shows if “the model predicts the remaining words in a given subject after witnessing a portion of it”, whereas log-likelihood evaluates how well the latent topics represent the data observed ( Guerreiro et al. , 2016 ). The list of possible topics evaluated in the current work spanned from K = 2 to K = 60, generated by the R tool. The findings of the models suggest that the measure has a first inflexion on K = 9, and the documents used K = 9 to evaluate the groups given that the variance described has the first inflexion and to use a small cluster for the explanation ( Cao et al. , 2009 ).

Then the corpus is analyzed using R packages (tm, topicmodels, LDAvis, stringr and stringi) to find the posterior probability and word frequency in each document using LDA. Where K is the topic model number, and the rest are functionality parameters, the values used were K = 9, alpha = 1, eta = 0.001 and iterations = 1,000. Nine topic models were generated, each with its own set of topic terms, which are the most frequently used words in each document that are separated into topic models according to their relevance ( Ramage et al. , 2009 ). Then the connected papers of the topic terms are determined using the posterior probability calculated for each document under each topic model.

4.3 Text mining experiments, result and analysis

The parameters for LDA functionality are chosen when the sentiment analysis is complete. The functions of the parameters chosen ( K = 9, alpha = 1, eta = 0.001 and iterations = 1,000) are listed above. The computer runs the instructions given with the help of the R tool, selects the most frequently used phrases, and distributes them across the nine topic models ( k = 9) according to relevance. There are a maximum of nine co-related words in each topic model (lda fit. terms [1:9,]). Table 1 depicts the subject phrases in each document’s topic model.

R programming commands for obtaining the posterior probability of each article using the same parameters are provided while generating the topic models. The R software ran for about 20 h and produced an accurate posterior probability result for the publications. The topic models are given names based on the topics that they cover. Table 1 shows the linked documents of the topic models created with the generated post. Prob. (posterior probability) and manually identified the journal, impact factor and paper type. The optimal number of clusters/topics is identified when the variability justification does not change significantly when more clusters are added. The present profiles only contain subjects having at least two publications related to them (posterior probability > 0.1327) to have a discourse based on themes embracing a broad spectrum of research available. Case studies and phenomenology (e.g. focus group) research are examples of qualitative methods, whereas experimental methods are examples of quantitative procedures.

Table 1 shows the LDA results, which reveal nine key topics. First, “Technological application” reveals the implementation of e-tourism with the help of the digital revolution. Dickinson et al. (2014) (post. Prob.=0.162) assessed the existing functions in using the domestic tourism travel domain and identified the areas where the most significant changes were likely to occur. On a more theoretical level, the article looks at how the smartphone governs tourism travel and what role it may play in more cooperative and flexible travel decisions to promote sustainable travel. A cutting-edge e-tourism data management classification taxonomy based on smart concepts, as well as a review of works in many domains in comparison to that classification, were presented by Hamid et al. (2021) (post. Prob.= 0.1399). They looked through the ScienceDirect, IEEE Xplore and Web of Science databases to do this. Buhalis et al. (2019) (post. Prob.= 0.206) used a value co-creation lens to look at significant technical breakthroughs and provided insights into service innovations that have an impact on ecosystems. As an information-dependent service management setting, the study uses examples from the tourist and hospitality industries.

“e-tourism services” indicates the smart services provided toward tourists. Lin et al. (2019) (post. Prob. = 0.222) investigated the 3D deployment of an IoT system in a forest recreational area with ideal service management benefits depicted as a weighting factor of service quality index, and managerial setting attributes index so that the framework collected data from tourists wearing wearable devices and applied it to tasks such as physiological sensing and placement. The purpose of Navio-Marco et al. (2019) (post. Prob.= 0.219) was to examine the evolution of wireless technology in tourism and hospitality. Wireless technologies are a group of information and communication technologies (ICTs) that involve radio transmission, such as mobile or satellite technologies and are widely used in the tourist and hospitality industries. The goal of Mehraliyev et al. (2019) (post. Prob.= 0.176) was to undertake a quantitative and comprehensive review of published articles on smart tourism. The paper seeks to define the smart tourism research life cycle, collaborative trends, main social structure, disciplinary methods and foundations, research themes and methodological approaches in more detail.

“Smart tourism application” deals with implementing smart tourism through various technological revolutions in a dynamic environment. Prandi et al. (2021) (post. Prob. = 0.200) presented the design and development of a real-world experience in which a low-cost cooperative platform allowed local communities to feel and display tourist flows and urban data in a rich interactive map-based visualization. Babli et al. (2016) (post. Prob. = 0.190) described a smart tourism system that creates a tourist itinerary and monitors its execution. A recommendation system provides a list of sites that best suit the tourist’s specific tastes, and a planner creates a customized itinerary or plan that includes visit dates and durations. In the context of a Smart Tourism Region, Baralla et al. (2021) (post. Prob. = 0.204) suggested a blockchain-based network for ensuring the origin and provenance of food items. Local food and drink can, in fact, be a fantastic combination for attracting tourists and promoting the area if their provenance is clearly documented.

“Tourist review on e-tourism” describes the opinion of the visitors or travelers about e-tourism services. Chang et al. (2019) (post. Prob.= 0.163) proposed a text mining-based approach for identifying nonrevisit characteristics in online textual evaluations on social media. As detecting whether a passenger plans to return is impossible, this study created a text mining-based approach that determined the passenger’s motivations by analyzing the mood of text reviews. Tripathy et al. (2018) (post. Prob.= 0.146) introduced iTour, a potential IoT-based solution for tourist autonomous mobility. In the process, this paper examined the challenges of initiatives and lessons learned, as well as the potential roles of IoT. To accomplish the tasks of sports tourism service internal management control, external collaboration and information release, Zheng et al. (2021) (post. Prob. = 0.221) developed a sports tourism service application model based on Internet technology. The two tiers of feature words were used to identify the similarity of sports tourism resources as well as the context in which sports tourism resources may be discovered.

“Smart tourism management” indicates the proper management of e-tourism. By applying a network analytic technique to the instance of three tourism locations, Del Chiappa and Baggio (2015) (post. Prob. = 0.155) contributed to the scientific debate on this topic. According to their findings, efficient knowledge-based destination management studies should consider both the virtual and physical components of the destination’s network structure. The goal of Bevolo (2019) (post. Prob. = 0.224) was to provide a conceptual basis for architectural design transformations while also informing the reader about some new trends in placemaking and digital destination management. The aim of Tung et al. (2019) (post. Prob. = 0.154) was to examine smart mobility’s past and future prospects in the context of destinations and reached the conclusion that smart mobility will transform tourism management in ways never seen before, notably in terms of tourist travel patterns and decision-making.

“e-tourism progress” deals with the development of e-tourism based on IoT. By examining neural networks, this research investigates the growth and use of large data. The primary goal of Gao (2021) (post. Prob. = 0.151) was to improve the big data system and platform. In big data, several technical and software requirements increasingly adjust to the consistency of the data platform and data system. The increase in people’s living conditions has assisted tourism’s rapid growth. The demand for tourism has risen significantly. The fast growth of ICTs such as cloud computing, the internet, the IoT and mobile intelligent terminals has resulted in intelligent tourism. Zhang and Dong (2021) (post. Prob. = 0.2095) wanted to accurately extract the image monitoring data of tourist sites, generate the correlating tourism routes using all of the applicant destination sets, generate all of the locations formed by the location sets and return the recommendation results to the visitors to overcome the issue experienced in the growth of tourism.

“User friendly smart services” describes the foundation developments of smart tourism to make it easy for the customers to adopt feasibly. The goal of Byun et al. (2017) (post. Prob. = 0.251) was to make it easier for IoT mobile virtual network operators to gain access to the market to provide the IoT services needed to implement more intelligent tourism in the tourism sector. This is inspired not just by the internet but also by information and communications technology in the most recent generation of long-term evolution networks. Gretzel et al. (2015) (post. Prob.=0.167) defined smart tourism, discussed current smart tourism trends and laid out the technological and business underpinnings for smart tourism. A small review of the benefits and downsides of smart tourism followed. The study also emphasized the critical necessity for research to guide smart tourism growth and management.

“Big data and artificial intelligence (AI) evolution” discusses the evolution of big data and AI in 5G smart tourism. The purpose of Mariani (2019) (post. Prob. = 0.193) was to examine the progress of Big Data and Analytics in the tourist and hospitality industry. It examined the significant role that Big Data has played in tourism and hospitality research thus far as well as how it may evolve in the future. Based on visitor selection behavior, Peng et al. (2020) (post. Prob. = 0.144) presented a human-guided machine learning categorization method that can effectively aid travelers in deciding which tourist attraction to visit. The results of cross-validation trials and performance evaluations showed that this method is effective. For smart tourism, Wang et al. (2020) (post. Prob. = 0.178) outlined 5G and AI-powered IoT technologies. To enable IoT-based smart tourism applications, effective data communication based on 5G technology and smart data analysis based on AI innovation are critical.

“Sustainable e-tourism” deals with the emerging sustainable tourism concept. Nitti et al. (2017) (post. Prob = 0.231) conducted the first examination of the viability of using an IoT method for a sustainable tourism application and offered a specific architecture. The architecture was designed to optimize cruise ship passenger mobility in Cagliari, Italy, by considering aspects such as transportation information and queue waiting periods. Gomez-Oliva et al. (2019) (post. Prob = 0.181) discussed the goal of creating an innovative communication channel between a tourist and a point of interest, which enabled the production and delivery of flexible experiences as well as the expanded distribution of cultural heritage through new technologies, all while considering the regions’ real-world demands and the needs of new digital visitors. To solve these issues, this paper suggests Be Memories, an innovative and co-created progressive Web-app for visitors that aims to share the intangible history of a tourist site through material co-created by local residents.

These nine topics created different types of opinions about tourism management through IoT for smart tourism, although most of them gave their opinion in favor of smart tourism. Now the nine topics are divided into three groups manually on the basis of relation to representing the previous research information.

Group 1 consists of “Technological application”, “Smart tourism application” and “Big Data and AI evolution”. Model 1 introduced the technological applications to be used and how to use technology in managing the tourism sector positively. Model 3, however, did state a few negative aspects of IoT, describing that smart tourism applications can also cause loss of data security and data infrastructure if not properly used. Model 8 is somewhat related to Models 1 and 3 through the evolution of Big Data and Artificial Intelligence in e-tourism, making the technology system more advanced.

Group 2 consists of “e-tourism services”, “e-tourism progress” and “User friendly smart services”. Model 2 introduced e-tourism services using IoT, which advanced the tourism sector one step ahead. Model 6 normally discussed the progress of e-tourism and how it is developing day by day due to the introduction of new technology every day. Model 7 ensured whether e-tourism is being a user-friendly application or not, as the development mostly depends on the use of the application system.

Group 3 consists of “Tourist review on e-tourism”, “Smart tourism management” and “Sustainable e-tourism”. Model 4 introduced the fact that tourists are satisfied with using e-tourism as they have to face less hassle now. Model 5 discussed the management of e-tourism, which is a must to maintain the development of this sector as this attracts more tourists and the economy is impacted. Finally, Model 9 made awareness to maintain all these management systems to maintain the sustainability of e-tourism.

Here the models built different opinions about e-tourism management to create awareness about the tourism sector. The suggestions for future research for these three groups are shown in Table 2 .

5. Implications and future research directions

The current study’s results prove to contribute to the appropriate direction for this research’s goal. The posterior probability in nine latent topics is calculated here, allowing future investigations on any of these topics to be undertaken in a way that catches researchers’ attention. The articles on Topic 7 (user-friendly smart services) and Topic 9 (sustainable e-tourism) have the highest posterior probability, which is larger than 0.22, proving that these two subjects have a good possibility of being chosen for additional research. Researchers can review the smart tourism services that are user-friendly or not for maintaining sustainability. Whether the smart devices are user-friendly or not, whether they are being properly or easily used or not, can be a better direction for future research. Again, proper maintenance of e-tourism is a must to keep it sustainable. These topics having the highest posterior probability indicate that the application of IoT in tourism has many advantages. These topics will be interesting to do additional research on as quality maintenance of e-tourism services toward valuable tourists is very important.

The relevance between the overall bibliometric analysis and trend topics allows researchers to focus on terms such as “internet of things”, “information management”, “AI”, “tourism”, “big data”, “leisure industry” and “privacy by design” for future research. Again, researchers can emphasize the techniques of developing e-tourism in their papers as many developing countries are still forming e-tourism but may not apply the principles properly. If e-tourism is not created correctly, it may cause a hassle for tourists, but if the entire e-tourism administration impresses the tourists, they will leave positive evaluations and urge other tourists to return. This will impact the economic condition of the country also. So, the future research impact of proper e-tourism on tourists and the country itself can also open exciting perspectives.

6. Conclusions

Tourism is becoming more and more popular as economic progress opens up new options for it to be consumed as a lifestyle across cultures ( Holden, 2016 ). So, considering this demand, the tourism industry should be driven through a proper management system, and all these hassles can be solved through smart tourism ( Sebastia et al. , 2009 ). According to the conclusions of this study, smart tourism using IoT would attract more visitors, including a smart hotel with a smart communication system and all of the fundamental necessities in a smart management system. This has already become easy for developed countries in this century, and the developing countries are trying to get better at this. This research paper used both bibliometric analysis and a text mining approach to bring this impact of applying e-tourism to the people. This study’s findings include LDA, sentiment analysis and citation mapping of the publications chosen.

The most frequently used words are shown in the topic trend, which includes more technology, showing that technological advances play a significant part in smart tourism in making a country’s tourism business more advanced and developed to attract tourists. Following that, a bibliometric analysis assists in gaining a thorough understanding of document bibliographic coupling analysis and author keyword co-occurrence network. The findings, in this case, had to do with connected authors, papers and keyword co-occurrence. The document’s sentiment analysis was used to describe the overall positive and negative sentiment of the articles, with the bulk of positive opinions being noted. Finally, LDA was used to determine the frequency level of the terms used the most and assign them to topic models on the basis of the relevancy of the papers using posterior probability.

The VOS-viewer software could not support other databases other than Scopus, so other databases could be used in future studies to ensure the review of more papers. Future research can also be done on the trend topics found with the help of the R-tool because the significance of the topics is not elaborately explained. Smart tourism is shown to have overwhelming positive opinions, which leaves interesting scopes for researchers to have thoughts of future research on this.

Selection of papers

Logical tree presentation of the methods used

(a) Bibliographic coupling analysis of documents; (b) co-occurrence network of author keywords

Latent topics

Future research suggestions

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The authors wish to thank the SJM-ESIC editorial team and the anonymous reviewers for their constructive reflections and comments to enable the publication of this paper.

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Integrating Tourism and Recreation Travel with Transportation Planning and Project Delivery (2004)

Chapter: chapter two - literature review.

Below is the uncorrected machine-read text of this chapter, intended to provide our own search engines and external engines with highly rich, chapter-representative searchable text of each book. Because it is UNCORRECTED material, please consider the following text as a useful but insufficient proxy for the authoritative book pages.

8 CHAPTER TWO LITERATURE REVIEW This chapter provides an overview of technical research regarding the application and effectiveness of various types of transportation projects to support tourism and recrea- tional activities. A few examples of research addressing the tourism travel needs of specific user groups are included. This chapter also reviews available policy research on multi-agency collaboration processes in transportation planning and decision making. The reports cited here focus primarily on roads, except for transit systems within na- tional parks. TRANSPORTATION TO SUPPORT PARKS AND OTHER TOURIST ATTRACTIONS In the context of tourism planning, investment in new and expanded transportation facilities can serve to either sup- port the operation and development of attractions (such as national parks) or function as attractions in their own right (such as scenic byways). For both types of situations, tech- nical studies can serve to identify needs, analyze proposed alternatives, and evaluate the impacts of built projects. More focus has recently been given to the transportation needs in national parks as a result of the levels of visitor demand exceeding the transportation infrastructure within many of the parks. The National Parks Service (NPS) mandates that park plans and planning activities address transportation aspects related to and affecting the park. As a result, various studies have assessed the cost-effective- ness and practicality of alternative transportation solutions, including roads, parking, bus service, trams, and other forms of transit facilities. Representative studies relating to national parks include the following: • “Transportation Needs of National Parks and Public Lands” (Eck and Wilson 2001) is a memorandum produced by TRB’s Task Force on Transportation Needs for National Parks and Public Lands (A5T55). It summarizes the concerns posed by the increasing number of peak-period visits by automobile travelers to national parks and other public lands. The memo discusses the need for federal land management agencies to balance open access to these sites with environmental stewardship of these resources. It notes that the use of alternative transportation sys- tems for national parks was first studied in 1994 and a report was submitted to the U.S. Congress. Three years later the U.S. Department of Interior and the U.S.DOT established an MOU to implement efficient transportation systems for national park access (a copy of the MOU can be found on the NPS website under the link for “Alternative Transportation”). This document also highlights the difficulties that remain in bringing tourism interests into the transportation planning process and stresses the need for a forum where these different stakeholder perspectives can be brought to bear in joint solutions for tourism-serving interests. • “Visitor Transportation at U.S. National Parks” (Turnbull 2001) is an article from TRB’s TR News summarizing some current alternative transportation initiatives now underway at Acadia, Zion, and Grand Canyon National Parks. • The NPS’s Transportation Planning Guidebook (2000) acknowledges that transportation planning is an “integral, defining feature of the national park ex- perience and a means by which the park mission of protecting resources for the enjoyment of future gen- erations can be realized.” This comprehensive guide is a resource for park managers and staff, as well as community partners to understand the types of TEA-21 funds that can be put to use, how to go about an inter- agency planning process, and who to involve in the transportation planning and design for the national park setting. Project implementation is also addressed by providing examples of how project partners can help raise funds from state and local matching sources to cover capital costs and future operating costs. The guidebook provides several successful case studies on the topics of successful partnerships, transporta- tion analysis within the context of park needs, and innovative solutions to transportation challenges aris- ing from traffic in and around national parks. • The Federal Lands Alternative Transportation Sys- tems (ATS) Study (Ecker et al. 2001), conducted by Cambridge Systematics on behalf of the FHWA, FTA, NPS, the Bureau of Land Management (BLM), and the U.S. Fish and Wildlife Service, reported that many issues are addressed by the application of ATS, including transportation, resource preservation, eco- nomic and community development, tribal matters, and recreational needs. The study includes an as- sessment of ATS needs on federal lands to mitigate current and anticipated transportation challenges, and explores opportunities for securing implementation funding. The study contains an appendix addressing guidelines for a conceptual transit planning process.

9 • Proceedings from the 1999 conference on “National Parks: Transportation Alternatives and Advanced Technology for the 21st Century” (1999) reflect not only the broad sponsorship of this conference but of those in attendance as well, including private-sector vendors showcasing prototypes of relevant technolo- gies. The Proceedings contain presentations as well as workshop summaries focused on regional trans- portation planning and coordination, traffic and de- mand management alternatives, transit alternatives (from shuttles to light rail), traveler and visitor in- formation needs, and alternative fuels. • “Tourist Transport Management,” an on-line digest of the Victoria Transport Policy Institute (2002), high- lights case studies of transportation solutions to tour- ist automobile congestion. Included are Seattle’s “Car Smart” Communities (car-free getaway tour pack- ages) and Acadia National Park’s Island Explorer shuttle service with advanced information systems. Also described is the city of Sedona, Arizona’s pro- posed transit solution to mitigate automobile conges- tion to and from Red Rocks State Park. This project has involved Sedona, two counties, the Coconino Na- tional Forest, the Northern Arizona Council of Gov- ernments, the Arizona DOT, and the Community Trans- portation Association of America. Finally, it discusses Miami’s proposed South Beach shuttle system, designed to serve the national historic district as well as other destinations in South Beach, Florida. This project includes pedestrian and bikeway improvements and the development of promotional and marketing materials on new mobility options for Miami Beach. • Access to Acadia National Park was examined in Bangor to Trenton Transportation Alternatives Study, Phase I (2001), a Maine DOT study that had the stated objective “to create an integrated, multi-modal passenger transportation system in Maine that sup- ports and promotes tourism.” The Phase I study ex- plored alternatives for car-based travel between Ban- gor and Trenton, a heavily traveled 50-mile corridor carrying predominantly tourist and recreational trav- elers between I-95 and Mt. Desert Island, home of Acadia National Park. This study was one piece of the “Explore Maine” initiative implemented by the Maine DOT. The goal of “Explore Maine” is to cre- ate a network of travel options that do not require a car. Three destination packages (Acadia, Freeport, and the Western Mountains) have been designed in a setting of public–private passenger transportation so- lutions involving intercity bus, chartered motor coach, rail, and international ferries. TRANSPORTATION FACILITIES AS SCENIC ATTRACTIONS In addition to serving traveler movements, transportation facilities can function as attractions in their own right. The primary example of this is the scenic byway, which is typi- cally a rural road that serves as a scenic attraction as well as a travel route. Much of the scenic byways literature has focused on documenting potential demand for proposed fa- cilities and then measuring the impacts of completed facili- ties. Representative studies relating to scenic byways in- clude the following: • Valuing Changes in Scenic Byways—VT Pilot Study (Tyrrell and Devitt 2000), a study for the Vermont Agency of Transportation, specifies an econometric modeling approach to measure the effect of different design elements of various road features along scenic byways on travelers willingness-to-pay. The report was designed to help guide future efforts of road designers and engineers in context-sensitive design that would be desirable for road users. This study measured the willingness-to-pay of various traveler segments, including leisure visits from both in- and out-of-state travelers, as well as the personal travel of area residents. • Holmes County Scenic Byways: The Value of Viewshed—Economics and Related Aspects of Sign- age (Strouse 1999) is a study from Ohio State Uni- versity. It assesses the impact that signage manage- ment and “viewshed” preservation have on tourists’ willingness-to-pay. • Scenic Byway Development on the Oregon Coast— Economic Benefits and User Preferences (1990) is an Oregon DOT corridor study. It was the basis for the eventual development of a master plan along Ore- gon’s Coastal Highway, US-101. The report exam- ined possible changes in direct visitor (nonresident) expenditures for the year 2000 under four different scenic highway scenarios involving differing degrees of corridor development along the coast. • Scenic Byways Data Needs, Resources, and Issues (Smith 1990) is a primer on data for evaluating sce- nic byways. This report defines the specific data that needs to be collected for different decision-making considerations, which depends on whether the objec- tive is to support scenic byways designation of a given route, to design enhancements to the route, or to evaluate a scenic byways route nomination based on either the attributes of the road or potential eco- nomic impact of attracting visitors. The author stresses the need for transportation and tourism inter- ests to work together to collect needed data to better support current and future scenic byway research. • Economic Analysis of Scenic Byways in Iowa, Kan- sas, Missouri, and Nebraska (Olson and Babcock 1991) is a Midwest Transportation Center study illus- trating how a travel demand and supply analysis model can be calibrated specifically to the scenic byway user travel segment. In this econometric model, the incremental increase in visitor trips owing

10 to scenic route designation is estimated by consider- ing traffic trends, cyclical economic factors, known seasonal factors, and a component for traffic move- ment changes not explained by the other three fac- tors. The latter aspect is thought to capture the re- sponse to design elements of the route and promotional success. • Scenic Byways as a Rural Economic Development Strategy—The Development of a GIS Model of Tour- ism and Recreation in Montana (Thompson et al. 1995) applied traffic analysis models to forecast trip and visitor spending impacts for a future year under alternative scenarios regarding the various assump- tions concerning traffic, marketing, visitor expendi- tures, and tourism capture rates associated with the new designation of US-89 as a scenic byway. • Identifying, Evaluating, and Preserving Minnesota’s Historic Roadside Facilities (Walton and Anderson 2003) examined the eligibility of 102 properties throughout the state for the National Register of His- toric Places. The study, on behalf of the Minnesota DOT, found that 51 of these roadside facilities, in- cluding scenic overlooks, hiking trails, picnic areas and historic markers, and one district are eligible for the register based on two sets of evaluations. The Minnesota DOT is preparing planning documents to address preservation (in light of other potential de- velopment pressures or planning activities), rehabili- tation, and maintenance for these sites and to tap eli- gible funding sources. All of these literature examples focus on scenic roads because they simultaneously represent transportation ac- cess routes as well as visitor attractions. There are also cases of scenic railroads, bikeways, and hiking trails around the country; however, they have primarily been planned and implemented as recreational or tourist attrac- tions, rather than jointly as transportation facilities. INFORMATION SYSTEMS AND OTHER TRAVELER SUPPORT SERVICES Information centers, welcome centers, and information displays are all ways in which visitors can be informed and guided to use appropriate travel routes and transportation facilities. Many articles have summarized the characteris- tics of such information projects. Several representative examples of this type of article are provided here. • Regional Transportation Connector Newsletter (2000, 2001) is the National Association of Devel- opment Organizations on-line newsletter. It show- cases state and regional projects with multi-agency collaboration and with tourism relevance, including “511 Virginia,” the Northern Shenandoah Valley Re- gional Commission’s ITS project. First implemented in the spring of 2000, with the help of the Virginia DOT (VDOT) and the Virginia Tech Transportation Institute, it features a traveler information service that provides tourist site information along the I-81 corridor that can be accessed by telephone. The re- search also showcased the unique role of New Mex- ico’s rural Council of Governments to spearhead transportation solutions to better service remote areas for residents and visitors. Finally, it has showcased how the South Central Council of Governments (and affiliated regional planning organization) has pro- posed creating a scenic byway loop to strengthen the base for economic development opportunities and provide experience in building regional partnerships. • WTI Newsletter (2003) from the Western Transporta- tion Institute presents recent developments for trav- eler information systems and other visitor informa- tion resources. Included is the “511” implementation for Montana and the deployment of information ki- osks for the Greater Yellowstone area. These are dis- cussed in chapter three under case studies pertaining to “Visitor Information Products and Services.” • 511 Case Studies: Kentucky (Schuman and Walden 2000) traces the early planning stages and coordina- tion efforts to transfer two of the more essential transportation caller services offered by the Kentucky Transportation Cabinet to a 511 traveler information service. The Advanced Regional Traffic Interactive Management and Information System coupled with the Traffic Advisory Telephone Service, and the Ken- tucky Road Report were the first of 10 transportation traveler services to be converted over to the 511 sys- tem. The ultimate vision is that Kentucky would es- tablish four metropolitan/regional 511 systems and all four would connect into a statewide system for the Kentucky Road Report. • “Travel Shenandoah: Lessons Learned in a Pub- lic/Private ATIS Partnership” (Cross 2000) examines how VDOT, Virginia Tourism Corporation, Virginia Tech, and the Shenandoah Telecommunications Company implemented a rural pilot advanced travel information services (ATIS) program seeking to minimize traffic problems associated with the widen- ing of I-81 through the Shenandoah Valley and, sec- ond, improve dissemination of travel information to residents, tourist and business travelers, and motor freight carriers. Information would be available on demand through landlines, cellular phones, websites, cable television, radio, variable messaging signs, and subscription-based technologies (such as pagers.) Six classes of information were chosen for the ATIS— travel alerts; traffic and travel conditions; travel ser- vices; tourism, attractions, events; emergency ser- vices; and route guidance. The decision to distribute specific types of travel information through the me-

11 dia was a deliberate part of the business model con- struct designed for multiple revenue streams to be generated, thereby guaranteeing sufficient funding for the ongoing maintenance of the ATIS system. Seven key lessons were highlighted from the imple- mentation of this rural ITS project: • Flexibility of partnering relationships; • Investment in data collection and maintenance; • Value of rapid prototyping and staged development; • Working with stakeholders; • System design should consider multiple markets, delivery modes, and revenue streams; • Design systems suited for their particular geogra- phy; and • Plan a system based on realistic financial objectives. RESEARCH ADDRESSING SPECIFIC TRAVELER GROUPS Understanding the demographics of the current pool (and potential) of visitors to a region is crucial to many tourism- oriented functions (e.g., marketing and developing visitor information resources), as well as to managing existing and planning for transportation facilities that link visitors to at- tractions throughout the region. There are many traveler segments that may be of particular relevance to the compo- sition of a region’s visits (e.g., international visitors, empty-nesters, and the elderly) and an understanding of any special needs or the group’s travel behavior and pref- erences can assist in more successful tourism outcomes and transportation solutions that offer greater safety and accessibility. Two studies are included here that address the travel needs and preferences of the elderly and the physi- cally challenged. Two additional modeling studies are also briefly mentioned here; however, the highlights of their findings are presented as case studies in chapter three, un- der “Data Analysis and Evaluation.” • “Accessible Tourism: Transportation to and Accessibil- ity of Historic Buildings and Other Recreational Areas in the City of Galveston, Texas” (Sen and Mayfield 2003) examines the unique characteristics of this barrier island destination with many historic buildings [not yet Americans with Disabilities Act (ADA) compliant] and the challenges to provide access to and into these sites. Travel to the island is predominantly by automobile and few transit options exist that can serve the disabled. A projection of tourist visits segmented by different groups will help to define the need for public transit ca- pable of serving those with physical mobility limita- tions. • “Departure Time Choices for Recreational Activities by Elderly Nonworkers” (Okola 2003) examines flexible travel behavior of the elderly through a dis- crete choice modeling analysis. Using national data from the Nationwide Personal Transportation Survey (1995), and focusing on suburban and rural travel, the modeling confirmed that the elderly do exhibit different travel preferences from the nonaged popula- tion for nonwork trips (e.g., the elderly prefer early morning travel). Such findings may be useful to those areas seeking transport alternatives for their elderly visitors who would otherwise arrive by car. • Also relevant to this category of literature are “Trans- portation Modeling for the 2002 Winter Olympic Games” (Kaczorowski 2003) and “Optimization of a Feeder Bus Service to Sandy Hook” (Cardone and Myers 2003). Both are presented in chapter three as case studies, under “Data Analysis and Evaluation,” of analyses contributing to advancing the knowledge base required to better plan transportation resources for spe- cial events or recreation destinations. INTERAGENCY COLLABORATION IN TRANSPORTATION PLANNING PROCESSES One of the challenging aspects of tourism and transporta- tion planning is the potential complexity involved in bring- ing a variety of federal, state, regional, and local parks, and recreation and tourism agencies into a collaborative trans- portation planning process. A variety of studies have taken on the general topic of interagency collaboration. Key studies include the following: • NCHRP Report 419: Tourism Travel and Transporta- tion System Development (Frechtling et al. 1998) identified the current state of practice in coordinating and integrating statewide transportation system de- velopment with tourism program goals. It provided an overview of the wide variation in the degree of dialogue occurring between state DOTs and state tourism and recreation agencies within the statewide transportation planning process. It also reviewed the limited track record of tourism-related transportation projects that have been undertaken and completed through a collaborative process. NCHRP Report 419 created a framework for evaluating different types of institutional arrange- ments that may exist in a given state. This framework also represents a means for understanding how the nature of working relationships can facilitate or hin- der joint projects between state transportation and tourism agencies. Additionally, the report identified three major areas where tourism objectives can best be integrated into transportation system development: policy coordination, the transportation planning process, and project development. The researchers presented principles to guide these three activities and promote stronger interagency coordination of

12 tourism travel issues in statewide transportation planning. The use of these guidelines was reexam- ined 4 years later and the results are shown in chapter three. • NCHRP Synthesis of Highway Practice 286: Multi- modal Aspects of Statewide Transportation Planning (Peyrebrune 2000) explores state-level multi-modal planning practices with respect to alternatives identi- fied, resultant modal mixes, and degree of integration into three aspects of the planning process—state planning, corridor studies, and the financing/budget- ing/programming process. A key finding from this study is that involvement of customers and stake- holders of the transportation system is necessary to identify the range of mobility needs (e.g., goods or passenger movement, resident or visitor trip) that any multi-modal planning process should begin with. It also shows why the multi-modal planning process can prosper under directives concerning sustainable land-use or economic development goals. Although this research does not specifically focus on tourism and transportation planning it is highly relevant to that topic. A crucial part of the dialogue to integrate tourism travel concerns into state and re- gional transportation planning processes and decision making involves multi-modal solutions. Not only is this consistent with the intent of federal legislation and guidelines, but a growing number of tourism re- gions are constrained in their capacity to handle more visitors arriving by car owing to land scarcity or con- cerns over environmental degradation and quality of life. (The previously reviewed studies of transit at na- tional parks illustrate such situations.) Therefore, planning that considers transit, ferries, rail, air, bicy- cle, and pedestrian facilities (in addition to roads) can be quite relevant for the process of integrating trans- portation and tourism and recreation planning. • NCHRP Synthesis of Highway Practice 297: Building Effective Relationships Between Central Cities and Regional, State, and Federal Agencies (Schaller 2001) provides examples of multi-agency transporta- tion projects to show how organizations with differ- ent mandates, jurisdictions, constituents, and author- ity have cooperated and collaborated. Although its’ focus is on central city transportation systems in the largest metropolitan areas, the issues of multi-agency coordination can apply anywhere. The study recom- mends guidelines for improving intergovernmental coordination in the face of various political and jurisdictional barriers. Two of the nine case studies in NCHRP Synthesis of Highway Practice 297 pertain specifically to tour- ism. One is the Walk Philadelphia/Direction Phila- delphia signage project that involved the FHWA, state DOT, and local organizations (nonprofits, city business associations, and Philadelphia’s Commerce and Streets departments). The other case study is the Woodward Avenue Heritage Route, a combined cor- ridor revitalization, historic preservation, and road improvement project in Detroit. This latter project was undertaken to spur economic development and tourism while also preserving historic and cultural as- sets. Coordination by the state DOT, 2 counties, 11 cities, the MPO, 2 nonprofits, and 1 business associa- tion made this project possible. • “Working Together on Transportation Planning—An Approach to Collaborative Decision-Making” (NACE 1995) was developed by the National Asso- ciation of Regional Councils as an exploration of innovative methods of enhancing public- and private- sector participation in the MPO transportation plan- ning process. This study is process-oriented and fo- cuses on the development of long-range plans or transportation improvement plans. It describes strate- gies for the MPO to engage the public and concludes, after a review of case studies, that MPOs that have had the greatest success in effective public participa- tion programs got there by first developing a public participation plan tied into the long-range planning and decision-making process. • Implementation Strategies for the NH Route 16 Cor- ridor Between Ossipee and Conway, NH (2002) high- lights a robust process undertaken by the Lakes Re- gional Planning Commission of how public and multi- jurisdictional participation affected the New Hamp- shire DOT’s State Transportation Improvement Plan. Detail is presented as a case study in chapter three, un- der “Multi-Agency Coordination.” • NCHRP Synthesis of Highway Practice 267: Transportation Development Process (Mickelson 1998) charts the evolution of the transportation development process from the initial “3C” paradigm (continuous, coordinated, and cooperative) in the early 1960s to the subsequent federal requirements (e.g., environ- mental, and cultural, historic, and biological preser- vation), emphasizing ISTEA legislation that went into effect in the early 1990s. This study examines how different states and regions are currently adjust- ing to the requirements of ISTEA as they plan new highway facilities (or improvements) and transit pro- jects. • NCHRP Synthesis of Highway Practice 217: Consid- eration of the 15 Factors in the Metropolitan Plan- ning Process (Humphrey 1995) examines the suc- cesses and challenges of a sample of MPOs in fulfilling the 15 required planning factors 3 years af- ter these ISTEA requirements went into effect. The study’s findings were drawn from interviews with 16 MPOs around the nation, from larger and smaller ju- risdictions, and with diverse air quality ratings

13 among those classified as transportation management areas. Early consensus was that although MPOs must deal with numerous requirements, ISTEA’s emphasis on improved planning (with dedicated resources available to do so) is a positive goal, along with fis- cally constrained plan development (implying effi- ciency) and a commitment to existing highway and transit infrastructure through preservation programs. The opportunity for a greater role in state- and fed- eral-level decision-making processes was a benefit also reported by the MPOs. The stated needs arising during this early stage of ISTEA implementation in- cluded technical assistance from state DOT and fed- eral staff to assist MPOs in meeting the ISTEA objec- tives fully and effectively and resources to update technical models and data no longer adequate for the type of analysis now required in a more comprehend- sive planning environment. Case studies document- ing progress on each of the 15 factors are included for Albany, New York; Boston, Massachusetts; Char- lotte, North Carolina; and Pittsburgh, Pennsylvania. The study also examined a case study of how the Wisconsin DOT is meeting the 23 factors required of state DOTs in the ISTEA legislation. Altogether, the literature cited in this report should be viewed as a cross section of issues being faced by local, state, and federal agencies and local stakeholder groups. They re- flect the range of transportation applications in which trans- portation investments can represent either a form of access support for separate tourism attractions or as simultaneous access routes and scenic attractions on their own.

TRB’s National Cooperative Highway Research Program (NCHRP) Synthesis 329: Integrating Tourism and Recreation Travel with Transportation Planning and Project Delivery provides an overview of current practice at transportation agencies, metropolitan planning organizations, state tourism and parks departments, federal land management agencies, and regional planning agencies. Overall, findings reveal that many state departments of transportation (DOTs) are now actively involved in tourism-related planning issues -- either proactively or in building solutions to infrastructure, access, or environmental issues that impinge on the success of tourism in the region.

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SME resilience as a catalyst for tourism destinations: a literature review

• Published: 29 March 2022
• Volume 12 , pages 23–44, ( 2022 )

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• Blesilda P. Badoc-Gonzales   ORCID: orcid.org/0000-0002-6670-2457 1 , 2 ,
• Ma. Belinda S. Mandigma 2 , 3 &
• Jackson J. Tan 4  

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This study proposes a holistic framework, which synthesized the literature on resilience, tourism, and tourism micro small and medium enterprises (MSMEs). The dimensions of resilience were used as lens to highlight the role played by tourism small and medium enterprises (SMEs) and extract strategies for tourism destination resilience amid various disasters. The systematic integrative literature review of 107 documents covered six books and 101 papers. Seven sources are chapters from 6 books and 94 articles from 47 journals. The literature review uses thematic analysis to extract dimensional concepts from extant literature on resilience, tourism resilience, and tourism MSMEs. Key insights on limitations and strategies on resilience emerged from the review. These addressed aspects of governance, economics, environment, and social resilience. This analysis led to the formulation of a framework that underscored the dimensions of tourism. It provides insights for tourism policymakers in drafting strategies to address limitations, which anchored on a more comprehensive perspective. As a contribution to theory, this study expanded the scope of resilience dimensions to address limitations. The strategies intend to fortify MSME resilience as a dominant part of tourism resilience. The insights from the study offer an enhanced view of tourism MSME resilience as crisis and disaster management literature.

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Introduction

As a collection of suppliers, the tourism industry lays subject to movements in people, weather events, and economic changes that may cause it to flourish (when times are good), or debilitate it (in times of disaster). The tourism industry is reliant on the movement of people (Yang et al., 2020 ) subjecting the industry to be susceptible to various threats of natural disasters, health pandemics (Dayour et al., 2020a , 2020b ), and economic and political upheaval (Cheer & Lew, 2018a , 2018b ). When crisis (due to natural disasters, economic downturn, terrorism, and internal chaos) occur, self-employed individuals and owners of small-scale enterprises in tourism and tourism-related ventures feel the brunt due to dependence on international and domestic tourist arrivals and destination marketing agencies (Dahles & Susilowati, 2015 ; Romão et al., 2016 ; Chowdhury et al., 2019 ). Post-disaster impacts hound the tourism industry in terms of tourist flows cessation (Espiner et al., 2017 ) causing decreases in demand (Romão et al., 2016 ), a prolonged decrease of visitors (Orchiston, 2013 ; Calgaro et al., 2014 ), destruction to critical infrastructures including accommodation capacity (Orchiston, 2013 ; Calgaro et al., 2014 ) and negative image from the media (Orchiston, 2013 ). Hence, the need for post-disaster recovery aims to bring tourism destinations either to their pre-disaster condition or an improved state through the development of strategies and pertinent implementation (Mair et al., 2016 ). The concept is similar to resilience defined as the ability to cope and persist amidst external shocks, disruption, and disturbances (Folke, 2016 ; Shimada, 2015 ; Kaufmann, 2017 ; Oliva & Lazzeretti, 2017 ) brought about by various disasters. In the same thread, tourism resilience involves the employment of actions for disaster-stricken tourism destinations to recover from the impacts of either various disasters and/or tourism-induced stresses.

However, compared to sustainability, resilience in its exercise of a range of responses that may be pragmatic and inclusive may not be sufficient nor align with sustainability endeavors (Espiner et al., 2017 ). Sustainability aims for sustained provision through responsible utilization of resources. Tourism resilient systems may implement new norms to continue functioning in the short period, albeit not sustainably long lasting (Brown et al., 2017 ). Nonetheless, the thoughts on resilience and sustainability are significant in the interpretation of environmental, economic, and social factors of tourism communities. Resilience is necessary though not sufficient to attain sustainability (Espiner et al., 2017 ), but achieving tourism sustainability necessitates tourism resilience as an important factor (Saarinen & Gill, 2019a , 2019b ).

The tourism industry is comprised of a considerable number of micro small- and-medium-sized enterprises (MSME), but there is a dearth of studies about these organizations (Thomas, 2015 ; Mair et al., 2016 ). The tourism sector and tourism operators are mostly composed of small enterprises and micro-businesses (Mair et al., 2016 ; Coles et al., 2014 ; Orchiston, 2013 ). Small-medium hotel enterprises (SMHEs) hold an important position in both the traditional tourism destination and hotel sector (Buffa et al., 2018 ). Despite the inadequate perceptions of MSMEs on the impacts of disasters and pertinent implementation of resilience development activities (Pandy & Rogerson, 2019 ), small tourism firms play a substantial part in the socio-cultural and economic health of tourism societies (Prayag et al., 2019 ). Most economic activities of rural tourism destinations are driven by micro and small tourism businesses (Ismail et al., 2019 ). Small tourism businesses add value in terms of community engagement and promotion and sustain other businesses, thus boosting the local economy and communities (Steiner & Atterton, 2015 ). Nonetheless, current literature reviews do not seem to include studies on tourism MSME resilience, even as its concepts inform operational policies at tourism destinations. There are limited papers that cover a comprehensive scope anchored on the dimensions of resilience by the Organization for Economic Co-operation and Development (OECD) and included in the study of Jamalia and Powell et al. ( 2018 ) covering economic, social, environmental, and institutional/governance resilience. Achieving tourism MSME resilience, therefore, requires identifying limitations on tourism MSME resilience and extracting a comprehensive range of strategies in addressing such limitations culled from both tourism and tourism MSME literature. A framework with a particular focus on tourism MSMEs compared to other generic and community-centered tourism frameworks highlight the considerable role played by the sector in enhancing tourism destination and community resilience.

In the face of various disasters, there is a need for tourism resilience in tourism destinations. There is also a need for tourism resilience to be inclusive of tourism MSMEs in a comprehensive scope (economic, social, environmental, and institutional/governance resilience), especially so that limitations hound tourism MSMEs, hindering growth and consequent potential substantial contribution towards tourism industry. However, despite the capacity to achieve tourism resilience in destinations, resilience theories are not given much attention by tourism scholars. Most frameworks borne out of literature reviews are quite generic in nature and do not seem to emphasize tourism MSMEs. More so, in the coverage of this review, most studies covering both tourism and tourism MSME resilience favor social and economic resilience with environmental resilience given least attention despite the need for a balanced approach to equip tourism communities with the comprehensive dimension of tourism resilience. The majority of the frameworks included in this study was not comprehensive enough to involve all-encompassing tourism resilience dimensions and have the convergence of these dimensions trickle down to benefit tourism MSMEs. The gap is addressed in this study with the proposed framework capturing a balanced stance in all four dimensions and giving emphasis on how tourism resilience could in turn address the limitations affecting tourism MSME resilience. The COVID era brings to fore the necessity for tourism MSME resilience encompassing all four dimensions (governance, environmental, social, and economic) as major catalysts for tourism destination development. The findings delved into a more detailed understanding on how various tourism and tourism MSME literature covers these dimensions with emphasis on the limitations and strategies. The aim is to highlight the importance of these strategies to address limitations besetting tourism MSMEs and bring forward a proposed framework enabling tourism MSMEs to spur resilient tourism destinations.

The purpose of this discourse is to extract how these dimensions are implied in tourism and MSME resilience literature toward tourism destination resilience. Bridging resilience and tourism dimensions in the scope of governance, environmental, social, and economic resilience reveal how applications of dimensions in the tourism resilience literature bring advantage for tourism MSMEs as catalysts of tourism destinations and community development (Biggs et al., 2015 ; Dahles & Susilowati, 2015 ; Mendoza et al., 2018 ; and Ismail et al., 2019 ). The second section provides a literature review. A subsequent section expounds on the research methodology. The fourth part presents the research results. The fifth part offers insights and discussion from the findings where there is a more detailed presentation of the key insights. Then, a proposed framework based on the in-depth analysis is forwarded. The final sections of the paper discuss future perspectives and debates, conclusion, and limitations.

Literature review

There is an increase in the body of literature on disaster and tourism over the past 20 years (Brown et al., 2017 ). However, among the current literature review studies, only a few fused the concepts of resilience, tourism, and pertinent strategies, and these are more specific to hotels (Brown et al., 2017 ) or propose a framework with strategies particular to heritage sites (Chong & Balasingam, 2019 ). Literature review on resilience covers a range of topics from social-ecological perspectives (Folke, 2016 ), regional resilience (Fröhlich & Hassink, 2018 ), resilience of organizations by Annarelli and Nonino ( 2016 ), and to hotel sector resilience (Brown et al., 2017 ). Recent literature review on tourism focus on innovation research (Pikkemaat et al., 2019 ), environmental ethics (Holden, 2019 ), sustainable tourism (Ruhanen et al., 2019 ; Chong & Balasingam, 2019 ), and hotel sector resilience (Brown et al., 2017 ). In light of the COVID-19 pandemic, pieces of literature become focused on research notes and critical reviews on the impact of the pandemic on tourism resilience (Gössling et al., 2020 ). These reviews provide post-crisis strategies as with the studies of Yang et al. ( 2020 ) and Nicola et al. ( 2020 ), Gössling et al.’s ( 2020 ) push for tourism sustainability and socializing tourism by Higgins-Desbiolles ( 2020 ).

Literature reviews from 2015 to 2020 have little consideration on tourism MSMEs and do not seem to extend the strategies and resilience framework for MSMEs that are operating in tourism destinations. Furthermore, the frameworks presented are quite generic to socio-ecological systems resilience (Folke, 2016 ), tourism innovation studies (Pikkemaat et al., 2019 ), sustainable strategies for heritage sites (Chong & Balasingam, 2019 ), and a community-centered tourism framework (Higgins-Desbiolles, 2020 ). The framework of Steiner and Atterton ( 2015 ) used in-depth interviews and systematic analysis as a basis to formulate a framework that aims to achieve a coherent balance of environmental, social, and economic resilience. The overlapping core in which these three dimensions converge is deemed to achieve strengthened local community resilience. However, this framework does not emphasize tourism MSME resilience nor does it include governance resilience in achieving community resilience. Folke ( 2016 ) used scenario planning with the framework on the principles to enhance resilience through management and governance in the pursuit of a social-ecological system to preserve humanity. The resilience dimensions that were dominant in the framework were governance, environmental, and social resilience. Nonetheless, the framework was not so keen on economic resilience nor with tourism MSMEs. With a systematic literature analysis, Pikkemaat et al. ( 2019 ) delved into the pillars of studies involving tourism innovation. The framework espoused the idea that the competitiveness of tourism MSMEs was best enhanced with social capital and innovation. Nonetheless, there was less emphasis on the other dimensions of resilience. Chong and Balasingam ( 2019 ) on the other hand focused on the sustainability of heritage sites borne out of systematic literature review. The framework touched on governance and economic aspects but none on tourism MSMEs. With a conceptual analysis, Higgins-Desbiolles ( 2020 ) formulated a community-centered tourism framework that seems to promote social and governance resilience but with less emphasis on tourism MSMEs. In summary, limitations on the various related frameworks covered in this study include the inability to cover all four comprehensive scope (economic, environmental, social, governance resilience) and to utilize these dimensions in promoting tourism MSME resilience. The proposed framework in this study is addressing this gap. The convergence and overlapping benefits of these dimensions can strengthen community and tourism resilience that is substantial towards tourism MSME resilience, which in turn can contribute towards resilient tourism destinations as espoused in the framework proposed by this study. Hence, by drawing out the concepts of the comprehensive dimensions of resilience from the current literature on resilience, tourism, and tourism MSME resilience, this paper proposes a framework that bridges resilience and tourism dimensions intended for MSMEs as catalysts towards destination resilience.

This paper uses the integrative review that considers different perspectives and insights (Snyder, 2019 ) on MSME resilience concerning that of tourism for theoretical framework development. The method utilizes a systematic review process. This is part of the integrative review, albeit devoid of statistical synthesis methods (Toronto, 2020 ) in the identification, evaluation, annotation, and synthesis (Rahimi et al., 2017 ; Holden, 2019 ; Chong & Balasingam, 2019 ; Pikkemaat et al., 2019 ) of literature to provide an explicit evaluation of findings.

Specifically, this paper adapts the integrative literature review methodology of Shuck ( 2011 ) where authors searched for Google Scholar, Web of Science/Clarivate, SAGE Publications, Taylor and Francis, Emerald Insight, Science Direct/Elsevier, and JSTOR databases. The keywords used were “resilience,” “tourism resilience,” and “tourism MSME resilience.” Articles with substantive relevance (David & Han, 2004 ) particularly those studies concerned with resilience dimensions namely, governance, economic, environmental, and social resilience in the presence of disasters within the tourism industry and tourism MSMEs context. The exclusion of documents was based on publications that are not within the 2010–2022 observation horizon to accommodate currency in the research field (Cottrell & McKenzie, 2011 ). The review focused on papers from Web of Science and Scopus databases that are considered widely used sources (Singh et al., 2021 ). However, due to scarcity of literature, articles from Scimago indexed and seven studies from book chapters were included in the review. There was independent verification of the inclusion and exclusion criteria by other authors.

One hundred seven documents were identified, broken down into six books and 101 studies, seven were from book chapters from 6 books, and 94 from 47 journals. Most of the manuscripts are Scopus indexed (Rayan, 2018 ), while others are Scimago Indexed and part of Web of Science coverage. According to Singh et al. ( 2021 ), Scopus includes a big number of documents while most of Web of Science coverage is also included in Scopus. Each article was then read and organized using the deductive method of thematic analysis (Pikkemaat et al., 2019 ). The papers were first categorized into resilience, tourism resilience, and tourism MSME resilience in an Excel file throughout the data analysis. Then, the papers were subjected to a refined manual categorization of how the dimensions of resilience were defined by various articles either in manifest or in the latent presentation. Lastly, the limitations and strategies under tourism resilience and tourism MSME resilience articles respectively were extracted in the context of the four dimensions of resilience. The applied thematic analysis goes through an iterative process of theme identification and outlining the fences around those content themes (Guest et al., 2012 ). The synthesis of the limitations and strategies themes led to the formulation of the proposed framework.

Most definitions of resilience acknowledge change (Folke, 2016 ) in the form of external shocks (Shimada, 2015 ) or disruption (Kaufmann, 2017 ) or simply a disturbance or interruption (Oliva & Lazzeretti, 2017 ) and the mechanism to cope and persist. Resilience allows for a recovery towards an original state or alternative stability considered as a new normal (Fröhlich & Hassink, 2018 ). For most authors, resilience is present in different fields of study such as engineering (Oliva & Lazzeretti, 2017 ; Shimada, 2015 ), psychology (Oliva & Lazzeretti, 2017 ; Shimada, 2015 ), emergency management (Oliva & Lazzeretti, 2017 ), and business continuity planning in business (Shimada, 2015 ). Business resilience, otherwise known as enterprise resilience (Cheer & Lew, 2018a , 2018b ) equips businesses with survival, adaptability, and continued growth despite changes (Dahles & Susilowati, 2015 ) caused by disasters.

Dimensions of resilience (Fig. 1 ) for resilient cities according to the OECD, include economic (diverse products/services and novelty in industries), social (unified and all-encompassing communities), environmental (ecological development of infrastructures and natural resources preservation), and institutional/governance (increased involvement and concerted efforts of leaders) by Figueiredo et al. ( 2018 ) and Jamalia and Powell et al. ( 2018 ). However, Oliva and Lazzeretti ( 2017 ) claim that resilience literature offers few insights on communities’ resilience. Social resilience pertains to the endurance and recovery of human communities while community resilience resembles an organization (Cheer & Lew, 2018a , 2018b ). To achieve community resilience, as indicated by Cheer and Lew ( 2018a , 2018b ), processes that bridge networked adaptive capacities with the functional adaptation of basic populations after a disruption must be in place.

A graphic overview of resilience dimensions

The development of resilience literature in tourism

As shown in Table 1 , various authors address resilience as a whole with a particular focus on tourism resilience and tourism MSME resilience. However, the list of authors dwindles regarding the discourse on tourism MSME resilience. The impacts of COVID-19 however on tourism MSMEs seemed to increase articles on the subject. Several researchers made mention of the limitations of both tourism and MSME resilience. Literature is fecund with suggestions of strategies that would address limitations on tourism and tourism MSME resilience and boost tourism resilience in general and tourism MSME resilience in particular.

• Tourism resilience

Resilience and tourism topics gained attention past 2010 (Hall et al., 2018 ). Authors claim that most articles before that year were on environmental, social sciences, and business studies (Orchiston et al., 2016 ; and Hall et al., 2018 ). Authors are commonly united in framing tourism resilience within the sustainable development perspective (Cochrane, 2010 ; Becken, 2013 ; Luthe & Wyss, 2014 ; Lew & Cheer, 2018 ; Orchiston et al., 2016 ). However, though the approach in resilience is more on adaptation and transformation (Lew et al., 2017 ), it is not tantamount to sustainability. Nonetheless, Saarinen and Gill ( 2019a , 2019b ) posit that tourism resilience is a significant element of sustainable tourism.

A summary of the definition of tourism resilience from most authors connotes the tourism destinations’ ability to alleviate and expedite recovery from both the negative effects of disasters and stresses caused by tourism activities. Lew ( 2014 ) categorizes the contexts of tourism resilience in two major changes, such as slow and sudden (Cheer & Lew, 2018a , 2018b ) impacting both site/individual tourism and community/collective tourism. However, Cheer and Lew ( 2018a , 2018b ) posit that tourism scholars have slow adoption of resilience theories.

The four domains of sustainability in the context of resilience in tourism include social, governance, economic, and ecological (Jamaliah & Powell, 2018 ; Powell et al., 2018 ; Holladay & Powell, 2016 ). Tables 2 , 3 , 4 , and 5 show these domains as the theoretical constructs in which definitions were culled from different sources of the review. The definitions provide the variables extracted from the review to represent each construct or key theme.

The collaboration of social resilience ensures a strong community linkage (Jamaliah & Powell, 2018 ; Powell et al., 2018 ) and a high level of conviction that propels people to work together. The network leads to the inclusion of social (Powell et al., 2018 ; Biggs et al., 2012 ) human and cultural capital (Brown et al., 2018 ). Stakeholder participation, commitment, and cohesion may come in the form of associative work (Cochrane, 2010 ; Pyke et al., 2018 ) and strong community public-private sector collaboration (Orchiston, 2013 ; van der Veeken et al., 2016 ; Chong & Balasingam, 2019 ; Orchiston et al., 2016 ; Njoroge et al., 2018 ). Social interaction involves the promotion of human capital (Biggs et al., 2015 ; Fyall & Garrod, 2019 ; van der Veeken et al., 2016 ) through knowledge sharing (Mair et al., 2016 ; Holladay & Powell, 2016 ; Mahadew & Appadoo, 2018 ; Steiner & Atterton, 2015 ) and marketing collaboration (Mair et al., 2016 ; Tervo-Kankare, 2018 ). Collective actions should incorporate resilient culture and values (Becken, 2013 ; Yang et al., 2020 ; Prayag, 2018 ; Puri et al., 2019 ) in community-centered socialized tourism (Higgins-Desbiolles, 2020 ). Articles within the COVID-19 era underscored tourism MSME support and more collaborations (Dayour et al., 2020a , 2020b ; Ngo et al., 2020 ; Haneberg, 2021a , 2021b ; Pyke et al., 2021 ) and networking (Orhan, 2021 ; Coles et al., 2021 ) towards system transformation (Kastenholz et al., 2021 ) through technological connectivity (Foris et al., 2021 ) while navigating the new normal.

Economic resilience involves harnessing market forces (Cochrane, 2010 ) and innovative tourism product diversification (Cashman et al., 2012 ; Biggs et al., 2012 ; Luthe & Wyss, 2014 ; van der Veeken et al., 2016 ; Holladay & Powell, 2016 ; Romão et al., 2016 ; Powell et al., 2018 ; Jamaliah & Powell, 2018 ; Njoroge et al., 2018 ; Dogru et al., 2019 ). Resilient organizations (Brown et al., 2017 ; Prayag, 2018 ; Mendoza et al., 2018 ; Brown et al., 2018 ) are also significant in damage assessment of local communities, services, supply chain (Prayag, 2018 ), and business capability through insurance uptake (Ghaderi et al., 2015 ; Dayour et al., 2020a , 2020b ). At the macroeconomic level, economic resources can be accessed through facilitative structures and processes (Brown et al., 2018 ; Steiner & Atterton, 2015 ; Cumming et al., 2015 ; Bellini et al., 2017 ; Eckerberg et al., 2015 ; Puri et al., 2019 ; Calgaro et al., 2014 ; Yang et al., 2020 ). Tourism-led growth (Seetanah & Fauzel, 2019 ; Walker, 2019 ; Holden, 2019 ; Gössling et al., 2020 ) can be enhanced with technology (Fyall & Garrod, 2019 ) and temporary state funding (Nicola et al., 2020 ) amidst crises and disasters to promote small business economic resilience as resilient organizations towards business continuity (Brown et al., 2018 ). Current studies emphasized the need for more economic support (Dayour et al., 2020a , 2020b ; Zhai & Shi, 2021 ) for tourism MSMEs as the sector struggles with experimentation, diversification, and business shift (Nuñez & Musteen, 2020 ; Dayour et al., 2020a , 2020b ; Pyke et al., 2021 ; Cahyanto et al., 2021 ) to maximize scarce resources (Coles et al., 2021 ).

Regarding environmental resilience, good practices (Calgaro et al., 2014 ; Cashman et al., 2012 ; Schiappacasse & Müller, 2015 ; Cumming et al., 2015 ; Tervo-Kankare, 2018 ; Buffa et al., 2018 ; Holladay & Powell, 2016 ; Njoroge et al., 2018 ; Spenceley, 2019 ) address local proximal impacts and environment-friendly products influence the values and attitudes of vacation consumers (Pereira et al., 2012 ). However, global measures (van der Veeken et al., 2016 ; Lew & Cheer, 2018 ; Powell et al., 2018 ; De Leon & Kim, 2017 ; Mahadew & Appadoo, 2018 ; Choi et al., 2017 ; Koninx, 2018 ; Brown et al., 2018 ; Pandy & Rogerson, 2019 ) give attention to the long-term impact of climate change (Jones, 2019 ). Strategies on climate change mitigation (Seetanah & Fauzel, 2019 ; Puri et al., 2019 ; Holden, 2019 ; Torres-Bagur et al., 2019 ; Gössling et al., 2020 ; Fyall & Garrod, 2019 ) enhance tolerance by mitigating the level of disturbance (Jamaliah & Powell, 2018 ). The COVID-19 era however, seemed to highlight the importance of a sustainable environment (Nuñez & Musteen, 2020 ; Kastenholz et al., 2021 ) more with emphasis on health safety (Li et al., 2021 ; Duan et al., 2021 ).

Strong and consistent leadership (Cochrane, 2010 ; Jamaliah & Powell, 2018 ) encourages joint problems and power-sharing flexibility (Luthe & Wyss, 2014 ; Holladay & Powell, 2016 ) of governance resilience in both the tourism industry and tourism-related businesses. Appropriate policies and plans (Orchiston, 2013 ; Steiner & Atterton, 2015 ; Ghaderi et al., 2015 ; Tervo-Kankare, 2018 ; Romão et al., 2016 ; van der Veeken et al., 2016 ; Brown et al., 2017 ; Musavengane, 2019 ; Choi et al., 2017 ; Buffa et al., 2018 ; De Leon & Kim, 2017 ; Mahadew & Appadoo, 2018 ; Nicola et al., 2020 ) propel resilient actions (Mair et al., 2016 ). More so, supportive government structures (Luthe & Wyss, 2014 ; Cumming et al., 2015 ; Biggs et al., 2012 ; Coles et al., 2014 ; Biggs et al., 2015 ; Pyke et al., 2018 ; Eckerberg et al., 2015 ; Mendoza et al., 2018 ; Njoroge et al., 2018 ; Torres-Bagur et al., 2019 ; Shou-Tsung et al., 2019 ; Gössling et al., 2020 ) strengthen tourism and tourism MSME resilience. This may come in the form of training (Tanana et al., 2019 ) subsidies (Yang et al., 2020 ) and social safety nets, caring, and networks (Higgins-Desbiolles, 2020 ). Struggling with COVID necessitates governance focusing on policies tackling economic support (Nuñez & Musteen, 2020 ; Dayour et al., 2020b ; Pyke et al., 2021 ; Palrão et al., 2021 ) and safety measures (Foris et al., 2021 ; Li et al., 2021 ; Duan et al., 2021 ).

Figure 2 shows the graphical presentation of studies that delved into the key themes of the dimensions of tourism and tourism MSME resilience. Looking at the coverage, most of the studies touched on social, governance, and economic resilience. More so, the graph shows that there seem to be the least studies involving environmental resilience among tourism and tourism MSMEs within the period covered.

Graphical illustration of studies delving on dimensions of tourism resilience

Tourism micro small and medium enterprises resilience

Micro small and medium enterprises (MSMEs) are major contributors in terms of employment and livelihood generation in the developing world. This sector holds the potential to enhance community-based resilience against disasters through economic opportunities according to United Nations Development Programme (UNDP, 2016 ). According to Mair et al. ( 2016 ), MSMEs occupy a significant proportion in the industry for tourism and yet they are subject to high levels of vulnerability (UNDP, 2016 ). They often find it difficult to understand responsible social, environmental, governance, and economic tourism guidelines (Musavengane, 2019 ). Dahles and Susilowati ( 2015 ) pointed out that business resilience involves surviving the crises, adapting to the new normal and embracing innovation. However, from the 107 articles covered in this review, only about 35% included topics covering both tourism and tourism MSME resilience where studies on tourism MSMEs gained more popularity during the COVID era. The developing countries, in particular, offer limited attention to how small tourism businesses fare during crisis (Dahles & Susilowati, 2015 ). Yet, tourism businesses that employed diversification within and across the tourism sector seemed most sustainable (Dahles, 2018 ).

Community-related activities participated in by small business operators develop networking (Orchiston, 2013 ). More so, they encourage rural business owners to partake in responsible means of operations (Steiner & Atterton, 2015 ). The physical exposure and tourism-specific attributes, however, shape tourism destination vulnerability (Calgaro et al., 2014 ). Structures and processes determine destination vulnerability on governance, human capital, socio-political, and economic that can either ease or restrain resources accessibility (Calgaro et al., 2014 ).

Key insights and Limitations on tourism resilience and MSMEs resilience

Table 6 shows key insights on the limitations of tourism resilience as a whole as well as specific tourism MSME resilience from existing studies. The insights on tourism and tourism MSME limitations are anchored on the key themes presented in Tables 2 , 3 , 4 , and 5 especially that which fits into the respective variables either in the manifest or latent presentation. Regarding social resilience, limitations include the dearth of studies on organizational resilience (Prayag, 2018 ) and the gap between awareness and attitude concerning tourism consumers (Antimova et al., 2012 ). Tourism MSMEs, on the other hand, lack awareness (Musavengane, 2019 ) attributed to limitations on entrepreneurial orientation (Prayag et al., 2019 ). The adverse effects of natural disasters on tourist arrivals (Bhati et al., 2016 ) and the strain on businesses to avail insurance (Ghaderi et al., 2015 ) in the bigger scope of the tourism industry aggravate limitations on economic resilience. Small businesses, on the other hand, showed resource limitations (Prayag et al., 2019 ) made worse by restricted access to credit and limited insurance coverage (Calgaro et al., 2014 ), thus the difficulty to rebound quickly (Mair et al., 2016 ). The COVID-19 pandemic, on the other hand, increased limitations on economic resilience and highlighted several limitations on governance resilience too.

Tourism limitations on environmental resilience include inadequacy of ecotourism research (Puri et al., 2019 ), climate change unawareness (Torres-Bagur et al., 2019 ), and the conflict between urban natural resource protection and development (De Leon & Kim, 2017 ). Small enterprises can only afford low-budget soft infrastructural, environmental management practices (Buffa et al., 2018 ) due to lacking facilities and resources (Musavengane, 2019 ). Inadequate coordination (De Leon & Kim, 2017 ), failure to come up with favorable methods (Cheer et al. 2019), and a restrictive top-down decision strategy (Holladay & Powell, 2016 ) are limitations of governance resilience. These limitations may affect small tourism businesses lacking long-term (Prayag et al., 2019 ) contingency planning (Mair et al., 2016 ) due to limited government support (Buffa et al., 2018 ; Coles et al., 2014 ).

Table 7 presents tourism resilience strategies suggested by studies and tourism strategies for MSMEs. Promoting social tourism resilience necessitates a focus on human capital (Biggs et al., 2015 ), particularly on learning that could translate to culture and lifestyle values on responsible (Becken, 2013 ) and ethical tourism (Ruhanen et al., 2019 ). This, in turn, could enhance community network and wellbeing (Sheppard & Williams, 2016 ; Lew & Cheer, 2018 ). More so, in times of pandemic, Higgins-Desbiolles ( 2020 ) suggests community-centered and socialized tourism. For tourism MSMEs, incorporation of planning, culture, and innovation factors (Orchiston et al., 2016 ), inherent ability to adapt (Ismail et al., 2019 ), knowledge sharing (Mair et al., 2016 ), social network development (Musavengane, 2019 ) resource allocation for resilience of employees (Prayag et al., 2019 ), and strengthening firm resilience (Mendoza et al., 2018 ) are strategies to promote social resilience. To achieve economic tourism resilience, studies recommend social collaboration (Pyke et al., 2018 ; Choi et al., 2017 ), stakeholder engagement (Eckerberg et al., 2015 ), and according to Cochrane ( 2010 ) harnessing market forces through innovative and ecologically sustaining livelihoods and substitution of domestic over foreign demand during crises (Cellini & Cuccia, 2015 ). Moreover, Yang et al. ( 2020 ) recommend transformation of the health sector alongside with an emphasis on tourism consumption through comprehensive policies in times of pandemic. Tourism MSMEs, on the other hand, can resort to the diversification of livelihood opportunities (Walker, 2019 ) to complement the maximization of available economic, social, and environmental resources (Steiner & Atterton, 2015 ). More so, promoting resilient firms (Mendoza et al., 2018 ) in the form of affordable and tailored insurance packages (Dayour et al., 2020a , 2020b ) loans and emergency grants (Nicola et al., 2020 ) can facilitate small and medium enterprises even at the heights of a pandemic to attain just and sustainable tourism (Higgins-Desbiolles, 2020 ). The onset of the pandemic pushed for more measures that are drastic to promote economic resilience with the necessity for more collaborations, economic diversification, and increased digitization in the new normal.

Tables 6 and 7 both serve as the bases for the proposed conceptual framework in Fig. 3 . They show that tourism resilience is a component of community resilience that can be fortified with the combination of resilience strategies involving governance, economic, social and environmental aspects. These, in turn, could strengthen tourism MSME resilience that will contribute towards resilient tourism destination communities even amid adverse impacts from disasters and tourism activities.

A framework bridging resilience and tourism dimensions for MSMEs

The framework bridging resilience and tourism dimensions for MSMEs (Fig. 3 ), approaches issues with MSME resiliency. Arrows in the framework indicate a flow of resources (in terms of financial, legal, human, organizational, informational, and relational) between individuals, firms, and the government. From the framework, to achieve environmental tourism resilience, innovative structures (Schiappacasse & Müller, 2015 ) must occur.

Furthermore, government, enforcement of existing regulations (Cashman et al., 2012 ), environmental certification (Spenceley, 2019 ), fund provision (Choi et al., 2017 ), and harmonious stakeholder relationship (Koninx, 2018 ) provide policy structures by which to encourage MSME resilience. According to Gössling et al. ( 2020 ), unmitigated climate change relates to the COVID pandemic, thus the need for the conversion of the global tourism system with the pursuit of attaining sustainable development goals. Tourism MSMEs, on the other hand, can resort to external subsidies from public actors for expensive infrastructural practices such as building insulations and solar installations (Buffa et al., 2018 ). Governance resilience strategies in tourism include supportive governance structures (Cumming et al., 2015 ; Torres-Bagur et al., 2019 ; Eckerberg et al., 2015 ) and policies (Biggs et al., 2015 ; Shou-Tsung et al., 2019 ; Choi et al., 2017 ; Tanana et al., 2019 ). A legal framework (Mahadew & Appadoo, 2018 ) on environmentally friendly actions (Tervo-Kankare, 2018 ) and the formulation of a tourism disaster management plan (Ghaderi et al., 2015 ) are significant to promote governance resilience. Furthermore, in the face of a pandemic, social buffer, and prevalence of social caring and linkages are necessary (Higgins-Desbiolles, 2020 ), supported by comprehensive socio-economic development plans (Nicola et al., 2020 ). For tourism MSMEs policymakers need holistic, cross-sectoral approaches for businesses and communities to achieve maximum benefits and encourage co-opetition (Steiner & Atterton, 2015 ; Mair et al., 2016 ).

The integration of economic, social, and environmental processes create strong local community resilience (Steiner & Atterton, 2015 ). The balanced approach equips communities with social, economic, and environmental capitals. The comprehensive framework of this study is a departure from the community resilience key elements of Steiner and Atterton ( 2015 ) which focuses on the integrated balance of environmental, social, and economic resilience albeit with less emphasis on governance and tourism MSMEs. In this paper, the framework included governance resilience along with economic, social, and environmental resilience where the integrated balance promotes tourism resilience as part of community resilience. The interaction of various strategies through the lens of these aforementioned dimensions can create tourism MSME resilience, which in turn is an essential component towards resilient tourism destinations. The employment of resilient strategies and actions by tourism MSMEs that comprise a considerable number of tourism destinations to enhance recovery from various disasters (both natural and human-induced) contributes toward overall tourism resilience. In the same vein, tourism resilient practices in the macro level, with a particular focus on tourism MSMEs strengthen resilience in tourism destinations as well and help mitigate disaster impacts (decrease in tourist demands, infrastructure damages, and negative location image). Post-disaster recovery measures that encompass the comprehensive scope of governance, social, environmental, and economic resilience may gradually diminish the negative impacts of crisis brought about by economic decline, natural disasters, political upheavals, terrorism, and health pandemics in tourism destinations.

Tourism MSME resilience is important as family-owned enterprises particularly those under small- and medium-sized categories dominate the tourism industry (Pikkemaat et al., 2019 ). The resilience of small-scale tourism businesses during crisis contributes to local development (Dahles & Susilowati, 2015 ) and allows the community to rebound (Mendoza et al., 2018 ), even in coastal societies (Biggs et al., 2015 ). Moreover, the “resilient factor” of transgenerational enterprises embedded in small family businesses at tourism destinations can achieve local community empowerment and sustainable tourism development (Ismail et al., 2019 ). The holistic perspective of the dimensions of resilience for tourism MSMEs as espoused in the framework (Fig. 3 ) intends to enrich the rural and urban family firms’ resilience capacity (Brewton et al., 2010 ; Pikkemaat et al., 2019 ; Gunasekaran et al., 2011 ) and small family-owned businesses. The comprehensive stance of the strategies and the framework intended for tourism MSMEs expand the scope of strong family networks in the paper of Calgaro et al. ( 2014 ), local embeddedness of family business resilience (Dahles & Susilowati, 2015 ) informal tourism enterprise resilience (Biggs et al., 2015 ; Biggs et al., 2012 ) and SME resilience of Mendoza et al. ( 2018 ). More so, the strategies from the review are inclusive of the currently recommended strategies such as insurance, loans, and grants for MSMEs (Dayour et al., 2020a , 2020b ; Nicola et al., 2020 ; Higgins-Desbiolles, 2020 ) amidst COVID-19. Compared to the scope of the community-centered tourism framework of Higgins-Desbiolles ( 2020 ) with its focus on social resilience and the sustainable strategies for heritage sites by Chong and Balasingam ( 2019 ), the proposed framework of this study extends to other dimensions of resilience and tailors the concept for MSMEs especially so during the COVID era.

This paper acknowledges the detrimental impact of various disasters on tourism destinations. Hence, it is important to develop tourism resilience that covers a comprehensive scope (economic, social, governance, and environmental) and inclusive of tourism MSMEs. This study brings to fore the significance of resilient tourism MSMEs in promoting resilient destinations. The limitations affecting both tourism and tourism MSMEs and pertinent strategies from various related studies were highlighted to facilitate the formulation of a framework that brings tourism MSMEs to the fore in improving tourism destination resilience. Governments and tourism administrators particularly in developing countries where MSMEs abound can take note of the various dominant strategies that can minimize limitations hindering tourism MSME growth. More so, the insights forwarded by the framework will encourage these institutions to strike a balanced convergence of tourism resilience’s four dimensions to promote community and tourism resilience. Policies and programs can take the path of promoting a resilient tourism community that will in turn be conducive for resilient tourism MSMEs to thrive towards resilient tourism destinations.

The framework of this study is a departure from the current frameworks (Folke, 2016 ; Pikkemaat et al., 2019 ; Chong & Balasingam, 2019 ; Higgins-Desbiolles, 2020 ; Steiner & Atterton, 2015 ) involving tourism and tourism MSME resilience by capturing the four dimensions of tourism resilience and taking special attention towards the development of tourism MSME resilience. The proposed framework acknowledges the role played by tourism MSMEs in achieving resilient tourism destinations borne out of resilient tourism communities. This operates on the concept that tourism resilience can best be dealt with, with a set of comprehensive strategies and an optimal balance among four dimensions of resilience to achieve all-inclusive goals.

Future Perspectives and Debates

Future studies should emphasize the best practices such as the comprehensive scope of strategies of MSMEs in tourism industries of disaster-prone and developing countries. They should also include discussions on how sector-specific MSMEs (accommodation, food and beverage, tourism support, and others) fared, amidst the COVID-19 pandemic in the light of the comprehensive context of governance, economic, environmental, and social resilience. In particular, the studies should look into the significance of network collaboration on the performance and business continuity of tourism MSMEs before, during, and after disasters. There can also be an exploration of the comparison of resilience strategies between sector-specific tourism MSMEs.

Conclusions

Analyses of this review through the synthesis of the literature on resilience, tourism, and tourism MSMEs using the lens of resilience dimensions, brought to light limitations of tourism and tourism MSME resilience amidst disasters and pertinent strategies necessary to minimize these limitations. Major themes on limitations and pertinent strategies emerged from the review. Both limitations and strategies are evident from the perspective of tourism destinations as a whole and tourism MSMEs in particular. Tourism MSMEs are vulnerable to disasters and face the difficulty of recovery after a particular catastrophe, exacerbated by the limitations of both the tourism industry in general and tourism MSME specific inadequacies. Key insights on limitations are inadequate human capital, scant resources, low activities on environmental resilience, and insufficient coordination in governance resilience. However, this sector can equip itself with resilient strategies on human capital and strengthened networks. The effort can enhance social resilience, efficient use of resources, and provision of funds to boost environmental resilience, strong legal framework, collaboration, and government support for governance resilience, which could translate towards strengthened stakeholder engagement and innovative diversification of ecologically sustaining livelihood opportunities for economic resilience. These strategies are significant, as there seems to be a lack of empirical evidence of network collaboration in tourist destinations (Żemła, 2016 ). Moreover, the leaning of destination studies is more on environmental aspects (Fyall & Garrod, 2019 ), thus pushing destination competitiveness to dwell on tangible natural resources. Intangible aspects involving human and social capital have earned less attention. The limited existing evidence on the involvement of MSMEs in adapting to climate change (Linnenluecke & Smith, 2018 ; Pauw & Chan, 2018 ) and other disasters is another aggravating factor. Thus, the aforementioned strategies could enhance network collaboration and develop tourism MSMEs’ full prospects in providing tourism livelihood opportunities in disaster-prone tourism destinations. The dimensions of tourism resilience provide a holistic mindset that can work for the best advantage of tourism MSMEs as they take on the role of catalysts towards tourism community development (Dahles & Susilowati, 2015 ; Mendoza et al., 2018 ; Biggs et al., 2015 ; Ismail et al., 2019 ). More so, the results highlighted the necessity of a comprehensive take on all resilience dimensions in promoting community and tourism resilience as a major determining factor in boosting tourism MSME resilience and enhancing tourism resilient destinations.

The results of the review are limited to relevant Scopus, Scimago Indexed, and Web of Science studies. There are studies on resilience, tourism resilience, and tourism MSME resilience that are not included based on the exclusion criteria. Thus, further literature reviews should include other important studies and documents to have a broader take on tourism MSME resilience.

Abbreviations

micro small and medium enterprises

organization for economic co-operation and development

small medium enterprises

sustainable development goals

small-medium hotel enterprises

United Nations Development Programme

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Badoc-Gonzales, B.P., Mandigma, M.B.S. & Tan, J.J. SME resilience as a catalyst for tourism destinations: a literature review. J Glob Entrepr Res 12 , 23–44 (2022). https://doi.org/10.1007/s40497-022-00309-1

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Tourism cloud management system: the impact of smart tourism

• Fang Yin 1 ,
• Xiong Yin 2 ,
• Jincheng Zhou 3 ,
• Xinli Zhang 1 ,
• Ruihua Zhang 3 , 4 ,
• Ebuka Ibeke 5 ,
• Marvellous GodsPraise Iwendi 6 &
• Mohammad Shah 7  

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This study investigates the possibility of supporting tourists in a foreign land intelligently by using the Tourism Cloud Management System (TCMS) to enhance and better their tourism experience. Some technologies allow tourists to highlight popular tourist routes and circuits through the visualisation of data and sensor clustering approaches. With this, a tourist can access the shared data on a specific location to know the sites of famous local attractions, how other tourists feel about them, and how to participate in local festivities through a smart tourism model. This study surveyed the potential of smart tourism among tourists and how such technologies have developed over time while proposing a TCMS. Its goals were to make physical/paper tickets redundant via the introduction of a mobile app with eTickets that can be validated using camera and QR code technologies and to enhance the transport network using Bluetooth and GPS for real-time identification of tourists’ presence. The results show that a significant number of participants engage in tourist travels, hence the need for smart tourism and tourist management. It was concluded that smart tourism is very appealing to tourists and can improve the appeal of the destination if smart solutions are implemented. This study gives a first-hand review of the preference of tourists and the potential of smart tourism. 

Introduction

Destinations like China are primed for successful performance in incoming tourism, with China set to overtake France as the leading destination worldwide by 2030 [ 1 ]. Similarly, tourism in the city of Mumbai, India, also increases yearly. Between 2009 and 2017, Mumbai saw an increase of 10.6%— the second highest growth rate in tourism for European tourists. The World Travel Awards awarded India and Mumbai the ‘Best Destination’ and ‘Best Destination City’, respectively, in 2018. However, China is primed to take over this position. As tourism steadily grows, so does the use of smartphones. As observed in [ 2 ], the cellphone has been adopted as a regular tourist travel device because of its ubiquity capabilities and progressive computing. With exponential growth in its users and its growing variety of applications, the mobile phone is changing the perspective of tourist travel and transport networks. The capacity to carry over 8 sensors with context-awareness opportunities is what has made smartphones so valuable in tourism [ 3 ]. The camera and microphone, the first features of the smartphone, have quickly been joined by GPS, compasses, proximity sensors, accelerometers, and gyroscopes. These proximity sensors allow system-adaptive devices to develop and function effectively as smart personal assistants. The two examples below could make the experience easier:

A smartphone with a mobile app which uses the camera and QR code technology for the validation of tickets, making the use of paper tickets redundant.

The use of Bluetooth and GPS for real-time identification of tourists’ presence, following dynamic patterns and enhancing the transport network.

The main contribution of this paper is the analysis of methodologies that include the features mentioned above in already existing technologies while proposing a Tourism Cloud Management System (TCMS). We consider a mobile which could be used to sell reserves for the transport of tourists, using a QR code as an identifier for validation. We also consider a mobile app which gives tourists access to the digital form of their travel reservations and makes it easy for them to find stops for transport [ 4 ].

Following the growth and development of the tourism industry, innovations in finding customers, linking them, and assuring their satisfaction need to be enhanced. The competition for prices, especially for holiday destinations, is high. Information Technology allows for greater efficiency, swift reaction time, and reduced operational costs. Recent advancements have inspired extreme changes in the tourism industry. A useful development in tourism is the redesign of the booking interaction, which would allow shoppers to save time in the acquisition and reservation of tourist items. Thus, tourism organizations need to adopt cutting-edge innovations to enhance their all-around productivity.

Literature review

Information and Communication Technology (ICT) has given people access to infinite digital content on leisure, culture, education, etc., on their portable devices [ 5 ]. The architecture of the Tourism Cloud Management System (TCMS) is shown in Fig.  1 . The evolution of technology has changed consumer behavior in various fields, and the tourism industry isn't an exception. ICT brings several advantages, including automation of processes which increases speed, reduced errors, and lowered expenses, all of which are of prime importance in the tourism industry. Secure processes which allow the purchase and marketing of products and services, and the transfer of videos, images, etc., are things which generate motivation for leisure-seeking consumers [ 6 ]. The tourist market is dynamic in terms of demand trends of tourists, which varies consumption habits and allows the generation of various products. This led to the creation of a route model called the intelligent tourist route to address this need.

Tourism Cloud Management System (TCMS) Architecture

The concept of smart territory in recent years has become popular among researchers and scholars of sustainable development. From the point of view of architecture and urbanism, the authors in [ 7 ] came up with the concept of smart territory and defined it as innovative territories with the ability to build competitive advantages for their surroundings, in the framework of a complicated and interconnected world. These smart territories try to find a balance between sustainability, social cohesion, and economic competition. Any territory, notwithstanding its level of infrastructure or size, can be a smart territory.

The definition of smart territory evokes a novel concept of the confluence of various related disciplines including culture, heritage, architecture, environment, regional development, urban planning, and the economy of innovation. The multidisciplinary approach of distinct sciences is applied and generates a synergy to consolidate a framework for tourism to be used in smart tourist destinations [ 8 ].

The multidisciplinary capacity and the integration of various areas need to be focused on the development of infrastructure for sensitization and connectivity. The concept of smart territory is especially relevant when one considers that the field of social and economic development needs to be approached from different perspectives. This means that the existing approach to the economy needs to have a holistic system with attractions, facilities with local management, quality and affordable pricing. This would allow the concept of a product in a destination, where circuits and routes form part of the activities.

Data visualization as a consolidation tool for smart routes

An essential part of the work done in tourism is the data visualization from the inventory of tourist attractions. It is important because it allows for a practical alternative for the conceptualization of the activity from the view of technological innovation and development in the conventional approach to tourism [ 9 ]. A good approach to the generation and consolidation of tourism science is the integration of different disciplines, with the view of creating synergy. This is exemplified by the research of evaluation and registration of tourist heritage elements (PT), connected to the data visualization (open data) created by computer graphics. Computer graphics allow the use of the most advanced technology; sensory interpretation through the perception, modelling, and representation of objects in 2D and 3D animation. These computer apps are not applied in tourist activities.

Visualization of data is a concept which uses the large correspondence force of pictures to clarify the cause, reliance, and importance found in the conceptual masses of data produced by social and logical cycles. It has not yet been fully explored in the field of tourism. It is a technological experiment in tourism management and planning as a result of its structure and the order of cultural and natural attractions. They are usually applied with the view that they can determine their possible uses [ 10 ]. An important part of the process of analyzing the tourist potential of a territory is the categorization, ranking, and inventory of tourist attractions. These processes determine how the real tourist vocation of territories would be. Based on its scope of application, it is the basis for organizing the tourist space of a community, region, department, country, or municipality. Thus, it is essential to consider tourist inventory for the generation of circuits and routes.

The only way to verify the tourist potential of the territory and justify possible investments is through a strict examination of the demand, supply, market trends, competition, and attractions of the territory. All these factors make up a comprehensive assessment of the territory and a basis for development agencies to make their decisions.

The valuation of the tourist territory consists of three primary stages:

Evaluation of the existing supply, resources, demand, market trends, and competition in the territory.

Comparison of the results of the evaluation and identifying the strengths, weaknesses, risks, and opportunities of the territory.

If there is potential, a strategy needs to be defined and followed for the development of tourism in the territory [ 11 ].

These three stages consist of the collation, treatment, and evaluation of external and internal information about the territory with strong tourism potential for the Tourism Cloud Management System.

Implementation of augmented reality and TCMS

The internet has caused a revolution in companies, tourism, the population, and the world in general. In the tourism space, it has facilitated a change in the sales and consumer channel, which reduces third-party participation and enhances competition. Consumers who are connected to the digital world with smartphones and can decide what they want have also revolutionized the world. Agents in the tourism industry have had to adapt to novel innovative technologies and the reformation of their customary products. These new technological advances make the products more valuable, allowing for a better experience [ 12 ]. Success in the management of a tourist destination can only be done with the detection of changes in the environment and their effects [ 13 ]. Adapting to new technologies is important because of the ease of promoting a destination.

TCMS shows that tourists in search of pleasurable experiences employ technological devices to speed up the selection process of what they are looking for. The perception of textual and graphical information of mobile disposition is very essential for this, as well as the possibility of reading other people’s opinions from their reviews. The options for accessing this information are numerous, including augmented reality which is on the rise [ 14 ]. For instance, a foreign tourist, a single male of higher education and 36 years of age would use the internet for planning his trip because he has spent most of his life in the technological era. It is important to know your tourist destination before getting there.

Augmented reality is an innovative tool that integrates the virtual world with the real one. It displays the content in real-time through a gadget. The difference between virtual reality and augmented reality is that the former displays elements virtually, while the latter displays real elements in a space. Although this technology has been in use since the 90 s, it is only recently adapted to mobile devices. The incorporation of this technology into tourism allows for the massive promotion of destinations and includes media information which complements the visit of the tourists in real-time. The application of augmented reality in tourist routes would allow easy access to information that can be obtained from the web. There are infinite possibilities for obtaining tourist information. This is a step towards an intelligent destination [ 15 ] in line with other state-of-the-art procedures in big data analysis [ 16 , 17 , 18 , 19 , 20 ].

Application of the smart tourist destination management model

The concept of a smart tourist destination should not be considered only as the application of the smart city model to the tourism industry. Structural variations in the tourism industry, which integrate with the consolidation of the smart city model, form the basis of the need for novel approaches to managing tourist destinations [ 21 ]. Thus, it is important to analyze some definitions of the concept. The India Tourism Ministry defined Smart Tourist Destination (STD) as an accessible innovative space, integrated with state-of-the-art technology that ensures the territory’s sustainable development, accelerates the interaction of the visitor and the environment, and enhances the quality of their trip. The basis of this definition is the principle that innovation is an essential space and operates as the centre of all proposals. According to [ 3 ], it inaugurates innovative spaces such as STDs that use novel technologies for development.

This methodology combines the novel framework of the tourist region with the climate and communication of the guests to expand the nature of their experience. It uses ICT to improve administration, reduce costs, and enhance residents’ satisfaction. The White Book on STDs emphasizes the development and innovation of ICT as the basis for novel mechanisms for the promotion of STDs. The goal is to create various differential competitive services with profitability and sustainability that turns risk into opportunity, promote diversification, fights against seasonality, and integrates success.

Gretzel et al. [ 2 ] defined STD as novel models of business management, forms of communication, and the quest for the consumer’s well-being. They use ICT for the promotion of the sustainable development of the territory, efficient management of resources, facilitation of interaction between the environment and visitors, and enhancing the citizens’ quality of life [ 3 ]. An STD’s configuration must correspond to the needs of every destination and their benefits because the mere application of technology doesn’t automatically make a destination an STD. It must be followed by a series of changes at all levels. An STD must use the available tools to satisfy the market, and because technology is not a means to an end, issues regarding accessibility, innovation, and sustainability must still be considered. Authors in [ 3 ] considered the concept of STD as a generic architecture that consists of principles originating from smart cities and includes sustainability and competitiveness at its base. The aim is to provide a holistic structure for smart tourist destinations. The idea is to revolutionize the management of tourism according to local capacity and technological possibilities.

Summary of the related recent works

Analysis of smart tourism using scopus.

The term ‘smart tourism’ was searched in the keywords, abstract, and titles of the extant SCOPUS literature. Between 2008 and 2022, 710 documents were published. These documents were studied for analysis. Figure  2 shows the published papers related to ‘smart tourism’ from 2008 to January 2022.

Number of documents related to ‘smart tourism’ from 2008 to 2022 in the SCOPUS database

Figure  3 illustrates the top 15 countries that have published work linked to smart tourism from 2008 to 2022.

Documents by country related to ‘smart tourism’

Figure  4 illustrates the comparison of published papers on smart tourism per year.

Documents per year by source related to ‘smart tourism’

The data collated from SCOPUS was further examined with the VOS viewer. Table 1 shows the list of countries with 5 or more publications on smart tourism.

Figure  5 visualizes the citations by country in Table 1 .

Citations by country

Figure  6 illustrates the keywords used in the published works of smart tourism, including the recent research of 2020. Some of these keywords include smart tourism, city, climate change, e-tourism [ 22 ], etc.

Keywords: Overlay visualization

Methodology

The TCMS study in this research uses a descriptive approach: a survey with a questionnaire to collect the required data. We formed a respondent base of 200 tourists in China selected based on the reviews of popular tourist portals including Trip Advisor. All tourists were given a link to a Google form (questionnaire) they were to fill out. 66 completed responses were used for the analysis. The questionnaire comprised close-ended questions using Likert’s five-point scale. The collated data were evaluated statistically with SPSS (Statistical Package for the Social Sciences), a statistical software used for advanced analytics, data management, business intelligence and multivariate analysis.

Table 2 shows the percentage of people who admitted they take trips to unknown destinations very often.

Table 3 shows the percentage of consumers who believed that tourist interests would increase and the percentage of consumers who believed the level of interest would remain static.

Table 4 illustrates the percentage of respondents who said they would be satisfied with the quality of smart tourism application services.

Table 5 shows the percentage of respondents who believe they would communicate better in a foreign land with smart tourism applications.

Table 6 shows the mean for males and females and the mean difference at the threshold p-value of lower than 0.05 level. The F-test value was 0.536, indicating it was significant at 0.465, and that the variance of both groups is equal. The equal variance was used as per the T-test that was conducted. The T value for the equal variances was 2.774, meaning it was significant at 0.006, which indicates a difference in male and female behavior regarding the preference for smart tourism.

Many people go to tourist destinations annually and believe that their interest may increase if smart solutions are available. The majority agreed that the quality of service may be enhanced if there are smart tourism applications. However, most did not believe that smart tourism applications may result in better communication in foreign lands. From the results presented above, it is obvious that the implementation of smart tourism applications would result in better patronage from tourists for tourist destinations. The results illustrate that in comparison with state-of-the-art existing work, there are several possibilities and applications of it in multiple fields.

This paper proposes a Tourism Cloud Management System (TCMS) and discusses the infinite possibilities of the comprehensive approach that integrates different disciplines for the consolidation of a multi-and transdisciplinary concept based on limited action and functionality. It includes several possibilities in design, tourism, ICT, economy, and multimedia, among others. The implementation and application of the TCMS would enable intelligent and smart management of tourism and enhance tourists' experiences. It is necessary to take local action to integrate the proposed Smart Tourist Destination Management model. In the future, this paper aims to systemize and homogenize the collection of information on various tourist attractions, i.e., making the collection of information on tourist attractions easier. Another objective is to propose its use in preparing sustainable development plans for tourism and to convince private and public individuals to support the use of technological innovation in tourism.

Availability of data and materials

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Acknowledgements

This work was supported by the National Natural Science Foundation of China (No.61862051), the Science and Technology Foundation of Guizhou Province (No.[2019],1299, No.ZK[2022]550), the Top-notch Talent Program of Guizhou province (No.KY[2018]080), the Natural Science Foundation of Education of Guizhou province(No.[2019]203) and the Funds of Qiannan Normal University for Nationalities (No. qnsy2018003, No. qnsy2019rc09, No. qnsy2018JS013, No. qnsyrc201715).

This work was supported by the National Natural Science Foundation of China (No.61862051), the Science and Technology Foundation of Guizhou Province (No.[2019],1299, No.ZK[2022]550), the Top-notch Talent Program of Guizhou province (No.KY[2018]080), the Natural Science Foundation of Education of Guizhou province(No.[2019]203) and the Funds of Qiannan Normal University for Nationalities (No. qnsy2018003, No. qnsy2019rc09, No. qnsy2018JS013, No. qnsyrc201715). 

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Fang Yin & Xinli Zhang

Business School, Geely University of China, Chengdu, 641400, China

School of Computer and Information and Key Laboratory of Complex Systems and Intelligent Optimization of Guizhou, Qiannan Normal University for Nationalities, Duyun, Guizhou, 558000, China

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Faculty of Education, Language and Psychology Postgraduate Department, Segi University, Petaling Jaya, Malaysia

Ruihua Zhang

School of Creative and Cultural Business, Robert Gordon University, Aberdeen, AB10 7AQ, UK

Ebuka Ibeke

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Conceptualization by Fang Yin, Jincheng Zhou; Questionnaire by Xiong Yin, Xinli Zhang, and Ruihua Zhang; Formal Analysis by Ebuka Ibeke and Marvellous GodsPraise Iwendi; Investigation by Mohammad Shah and Ebuka Ibeke; Resources and Data collection by Xiong Yin, Xinli Zhang, and Ruihua Zhang; Writing by: Jincheng Zhou and Fang Yin; Validation by: Ebuka Ibeke and Marvellous GodsPraise Iwendi; Funding Acquisition by Jincheng Zhou and Mohammad Shah. The authors read and approved the final manuscript. 

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Yin, F., Yin, X., Zhou, J. et al. Tourism cloud management system: the impact of smart tourism. J Cloud Comp 11 , 37 (2022). https://doi.org/10.1186/s13677-022-00316-3

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DOI : https://doi.org/10.1186/s13677-022-00316-3

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