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  • Review Article
  • Open access
  • Published: 07 October 2023

A ten-year review analysis of the impact of digitization on tourism development (2012–2022)

  • Chunyu Jiang   ORCID: orcid.org/0000-0002-6072-8365 1 &
  • Seuk Wai Phoong   ORCID: orcid.org/0000-0002-9925-0901 1  

Humanities and Social Sciences Communications volume  10 , Article number:  665 ( 2023 ) Cite this article

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  • Development studies
  • Science, technology and society

Many tourism-related activities have been suspended due to the nationally enforced lockdown to combat the Coronavirus pandemic. The tourism industry suffered immensely from the lockdown, and as a result of this, digital tourism began gaining traction and attracted public attention. This study analyses the impact of digitalization on the social and economic sustainability of the tourism industry via systematic literature network analysis. The findings indicated that digitalization impacts economic sustainability, encompassing economic benefits in tourism product development, tourism consumption, and industrial development. Moreover, digitalization fosters social development, cultural awareness, and tourism participation in digital technology and cultural heritage. This study identified publication trends and research hotspots using bibliometric analysis, and it was confirmed that Sustainability was the top journal in published digital and tourism sustainability-related articles, followed by the International Journal of Tourism Research, Tourism Management , and Current Issues in Tourism . This study resulted in two implications: identifying the knowledge gap and evidence-based decision-making based on the (previous) literature. Recommendation for future research is also discussed in this study, which is helpful to policymakers, tourism planners, and researchers to develop strategies grounded in research.

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Introduction

From 2019 through 2022, the Coronavirus disease 2019 (COVID-19) wreaked havoc on the world’s tourism business (Navarro-Drazich and Lorenzo, 2021 ). Tourism contributes to many nations’ gross domestic product (GDP) as it is intertwined with various industries (Gössling et al., 2017 ). Examples of tourism products include lodging options such as hotels and Airbnb. Food and drink, theme parks, museum visits, and fashion items such as clothes and bags are additional examples of tourism products that boost the economic health of the individual and the nation.

Tourism is regarded as a complex service-driven industry, one of the characteristics of which is that if external influences disrupt the tourism sector, other industries linked to it will also be directly affected. Tourism development refers to creating and maintaining the tourism industry in a particular location and is closely linked to economic and social progress (Telfer and Sharpley, 2015 ). Over the past four decades, global tourism development has reported intense growth performance and research on tourism development (Capocchi et al., 2019 ). Kreishan ( 2010 ) posited that the impact of tourism development on destination development is a commonly discussed issue, particularly in terms of tourism development improving economic efficiency and local competitiveness. The growth of tourism currently is significant not only from an economic perspective but also from a social perspective, as evidenced by the optimization of the local social structure (Yang et al., 2021 ), increased community participation (W. Li, 2006 ), participation of women (Ferguson, 2011 ), and increased cultural awareness (Carbone, 2017 ). Also, the development of the tourism industry benefits the environment by increasing environmental protection awareness and providing greater funding for initiatives to conserve resources and the environment (Zhao and Li, 2018 ).

However, unmanaged over-tourism can cause serious harm, according to Berselli et al. ( 2022 ). From an economic standpoint, excessive tourism can result in higher prices and imbalanced industrial structure development, which lowers industries’ overall resilience. Social issues arising from over-tourism include the commercialization of culture (Wang et al., 2019 ), the shift in locals’ attitudes from friendliness to hostility towards tourists (Kim and Kang, 2020 ), and the emergence of on-stage authenticity (Taylor, 2001 ). In terms of the environment, issues such as excessive carbon emissions causing global warming (Liu et al., 2022 ), damage to water and soil resources, destruction to flora and fauna (Gössling and Hall, 2006 ), and even harm to cultural heritage (Zhang et al., 2015 ) are some of the effects of over-tourism. Since the development of the tourism industry combines economic, social, and cultural phenomena, as well as the past COVID-19 disruptions, the industry’s suspension for several years presents a significant opportunity for all stakeholders to reposition tourism for sustainable development.

Some studies suggest the tourism industry will recover after COVID-19 (Zhong et al., 2021 ). However, given the abovementioned problems caused by over-tourism, what needs to be considered is the sustainability of the tourism industry post-COVID-19. Researchers and tourism stakeholders are becoming more aware of the importance of the concept of sustainable development (Miceli et al., 2021 ), especially since COVID-19, as the tourism or hospitality industry remains one of the least developed sectors in terms of sustainable tourism practices (Kim and Park, 2017 ). Korstanje and George ( 2020 ) noted that over-tourism is a chronic disease that mere temporary changes cannot treat; it can be minimized via education and training to raise awareness. The tourism industry needs to rethink how to develop in a sustainable and healthy direction (Higgins-Desbiolles et al., 2019 ), not only in terms of ecotourism or green tourism but also in terms of putting the concept of sustainability into practice at a deeper level as it faces multiple pressures and challenges of an overarching environment, economy, and society.

Sustainability is often cited as one of the reasons for improved competitiveness among different tourism destinations (Han et al., 2019 ). The United Nations 2030 (UN, 2030 ) Agenda for Sustainable Development has developed a Sustainable Development Goals (SDGs) plan, defined as a set of global goals for fair and sustainable health at every level, from the planetary biosphere to the local community. The aim is to end poverty, protect the planet, and ensure that everyone enjoys peace and prosperity now and in the future. The basic concept is that productivity can be preserved for future generations. Due to the general emphasis of the United Nations World Tourism Organization (UNWTO) on sustainable tourism and the industry’s economic importance, the SDGs and its associated millennium development goals (MDGs) have become critical elements for research into tourism’s contribution to sustainable development and overall sustainability (Saarinen et al., 2011 ; Saarinen and Rogerson, 2014 ). Winter et al. ( 2020 ) indicated that as sustainable tourism development needs to take complete account of the combined social, economic, and environmental impacts, stakeholders are expected to integrate scientific management and practice for future sustainability using updated and innovative technologies that can provide more tourism opportunities for groups unable to travel directly while enhancing environmentally-friendly behavior. Bramwell and Lane ( 2011 ) suggested that effective policy support is also crucial to implementing sustainable tourism development, as the path to sustainable development is guided and monitored by excellent and progressive policies. From a postmodernist perspective, social media and place brand authenticity in smart tourism are essential to place trust, place identity, and place brand image, while the development of this brand authenticity is one of the critical indicators of the visitor experience (Handayani and Korstanje, 2017 ). As a result, Korstanje et al. ( 2022 ) contended that new paradigms and strategies must be created to confront risks to tourism in the 21st century and satisfy the SDGs by 2030.

Several studies are underway to determine the impact of various programs and strategies on the environmental component of sustainability practices (Goralski and Tan, 2020 ). Yalina and Rozas ( 2020 ) suggested that a digital workplace can promote environmental sustainability. Although there have been studies on the digitalization of tourism and environmental sustainability, such as Loureiro and Nascimento ( 2021 ), who reviewed digital technology on the sustainability of tourism using bibliometric methods, there is a need for a thorough examination of the impact of digital transformation on sustainable tourism growth, particularly in terms of economic and social dimensions (Feroz et al., 2021 ). Therefore, the objective of this study is to review the impact of tourism digital technology development on the economic and social sustainability of tourism development to offer future research guidance.

With the growing literature and the emergence of cross-disciplinary research related to sustainability and digitalization in tourism development, it is critical to analyze the changes in its research, summarize the focus of previous research content, and predict future research prospects. As a result, this study will address the above research gaps by answering the following three questions.

RQ1: What are the prominent documents, authors, sources, organizations, and keywords in digitalization for the economic and social sustainability of tourism development?

RQ2: What are the linkages based on bibliographic coupling, co-authorship, co-occurrence, and citation in digitalization for the economic and social sustainability of tourism development?

RQ3: What is the future research agenda based on the results of this study?

Literature review

Several review papers on tourism research are now available and relevant to this study. Ülker et al. ( 2023 ) assumed that there are currently 136 bibliometric studies in the tourism and hospitality industry, of which the literature review studies on overall trends in the tourism and hospitality industry are continuously being updated (Chang and Katrichis, 2016 ; Wang et al., 2023 ). Also, economic development in the tourism industry (Comerio and Strozzi, 2019 ), tourism marketing (Mwinuka, 2017 ), tourism and education (Goh and King, 2020 ), hospitality (Manoharan and Singal, 2017 ), Airbnb (Andreu et al., 2020 ), and even COVID-19 review articles related to tourism development are available (Bhatia et al., 2022 ).

With the emergence of cross-disciplinary digital-related technologies, the link between tourism and digitalization has become one of the hot topics of research, and as a result, several literature review articles on digitalization and tourism have been published, such as on robotics (Buhalis and Cheng, 2020 ; Ivanov et al., 2019 ; Pizam et al., 2022 ), ICT (Buhalis and Law, 2008 ; Law et al., 2014 ), big data (Li et al., 2018 ; Stylos et al., 2021 ), smart tourism (Buhalis, 2020 ; Mehraliyev et al., 2020 ), social media (Buhalis and Inversini, 2014 ; Mirzaalian and Halpenny, 2019 ), eye-tracking (Muñoz-Leiva et al., 2019 ; Scott et al., 2019 ), AI (Buhalis and Moldavska, 2022 ; Doborjeh et al., 2022 ; Dwivedi et al., 2023 ), VR (Koohang et al., 2023 ; Wei, 2019 ), AR (Jingen Liang and Elliot, 2021 ; Tscheu and Buhalis, 2016 ; Yovcheva et al., 2012 ), MR (Buhalis and Karatay, 2022 ), and the Metaverse (Ahuja et al., 2023 ; Buhalis et al., 2022 , 2023 ; Go and Kang, 2023 ).

Due to the rise of sustainability research, the literature review on sustainability research in tourism has seen a stark increase (León-Gómez et al., 2021 ; Ruhanen et al., 2018 ; Streimikiene et al., 2021 ). The proliferation of studies related to digitalization and sustainable tourism development has led to a considerable number of review articles (Elkhwesky et al., 2022 ; Gössling, 2017 ; Loureiro and Nascimento, 2021 ; Nascimento and Loureiro, 2022 ; Rahmadian et al., 2022 ). Feroz et al. ( 2021 ) conducted a literature study on the environmental aspects of tourism sustainability and digitalization; however, there is a distinct lack of studies on the economic and social dimensions.

Therefore, the study’s unique value is that it presents the first literature review in the field of digitalization and social and tourism economic sustainability development using a novel method of systematic literature network analysis (SLNA), filling a gap in the literature review landscape and addressing the need for more comprehensive, detailed, and up-to-date research endeavor.

Methodology

Colicchia and Strozzi ( 2012 ) proposed a systematic literature review analysis (SLNA) to identify past research trends more sophisticatedly, integrated, and scientifically. This method is currently used in reviews of sustainable development research (Afeltra et al., 2021 ) but is rarely used in reviews of tourism sustainability; therefore, SLNA is used in this study.

Systematic literature review (SLR) and bibliographic network analysis (BNA) are the two phases of SLNA. These actions comprise the first phase of SLR, which includes choosing the study’s final selection, conducting a dialectical examination of the most pertinent articles, and evaluating the results. Next, citation analysis and bibliographic coupling of BNA are also included in this paper to investigate the relationship between the previous literature, assess the research trends, and aid in uncovering future research innovation opportunities. Bibliographic coupling is a scientific mapping technique regarding two articles with a common citation contentedly comparable. This technique permits the segmentation of publications into thematic clusters utilizing published references to understand the most recent developments in current research issues (Donthu et al., 2021 ). Citation analysis reveals which papers are influential and their authors and journals and aids in comprehending what past literature has contributed (Pilkington and Meredith, 2009 ).

First phase: systematic literature review (SLR)

Introduction of slr.

The most widely used and reputable databases are the Web of Science (WOS) and Scopus (Garrigos-Simon et al., 2018 ); thus, both were used in this study to eliminate data search omissions, broaden the search scope, and improve the accuracy of data outputs.

Figure 1 shows the flow diagram for systematic bibliometric analysis. Firstly, this paper takes “virtual reality or augmented reality or artificial intelligence or big data or mobile technology or internet of technology or social platform technology) and (sustainable tourism development or sustainability of tourism or green tourism or ecotourism” as keywords. The search process began by searching topics (including article titles, abstracts, and keywords). The language of the articles was set to English and had to be published between 2012 and 2022. The search process resulted in 91 articles. The data were extracted on February 15, 2022, per Fig. 2 .

figure 1

This figure shows the overall process of this study from database selection until suggestions for future research. Source: Own elaboration.

figure 2

The criteria and steps used to identify the selected target literature are explained in this diagram. Source: Own elaboration.

A review article with scholarly worth and contribution is required to describe the literature’s links and contents and examine and critique it precisely (Hart, 2018 ). As seen in Fig. 3 , the following research topics are divided into two categories: economic sustainability (which includes topics such as economic benefit, industry development, and tourist consumption) and social sustainability (which includes topics such as tourist behavior, social development, cultural awareness, and participation).

figure 3

The research topics are divided into two categories: economic sustainability (which includes topics such as economic benefit, industry development, and tourist consumption) and social sustainability (which includes topics such as tourist behavior, social development, cultural awareness, and participation. Source: Own elaboration.

The SLRs are used to locate, appraise, and synthesize existing, completed, and documented work (Cocchia, 2014 ), facilitating classification and summarization, particularly for micro-profiling within macro-level fields of study.

Digitalization’s impact on economic sustainability

Digitalization’s impact on economic benefits.

Adequately improving the economic development of tourism is also one of the sustainable needs for developing tourism. At a time when tourism has been devastated by COVID-19, the tourism industry has almost ceased to exist. Therefore, one of the most popular research topics is maintaining substantial economic benefits while allowing the tourism industry to flourish sustainably.

Digital technology has piqued researchers’ interest due to its potential benefit to the tourism industry. Technologies that directly improve the economic situation are classed as economic benefits, and per many studies, digitization positively impacts local economic development and may bring objective revenue to tourism (Tables 1 – 7 ).

Digital technology promotes economic development. The growth of information communication technologies (ICT) positively impacts China’s tourism industry while promoting economic growth (Shehzad et al., 2019 ). As a rapidly evolving digital technology, mobile technology has significantly minimized asymmetric information, enhanced local GDP growth, and increased citizens’ financial capital through tourism (Kim and Kim, 2017 ; Phoong et al., 2022 ). Technologies such as 3D virtual, mixed reality (MR), virtual reality (VR), or augmented reality (AR) applied in heritage tourism can effectively increase local economic income and the added value of tourism (Manglis et al., 2021 ; Martinez-Grana et al., 2019 ). Furthermore, marketing tools such as small programs and network technologies confer several advantages to tourism stakeholders, such as the ability to help local communities contribute value and support the tourism economy (Caciora et al., 2021 ; Lin et al., 2020a , b ). Also, smart heritage city tourism technology tools can drive the tourism economy to inaccessible areas (Gomez-Oliva et al., 2019 ).

The increase in income is proportional to increased economic benefits. ICT is often used in the tourism industry, which has an essential impact on the tourism service industry, one of which is the improvement of tourism income (Gomez-Oliva et al., 2019 ; Koukopoulos and Koukopoulos, 2019 ). Virtual tourism technologies, such as AR and VR, are digital tools that can help overcome cultural heritage tourism challenges, such as reviving the tourism industry and resolving funding shortages (Lu et al., 2022 ). Mobile money, such as electronic traveler’s checks and credit cards, can assist low-income people in taking advantage of their marginal savings and encourage implementing a cashless economy for tourism sustainability (Singh, 2017 ).

Second, digital marketing technologies are frequently utilized by hotels to improve hotel performance, which increases profit (Theocharidis et al., 2020 ; Vitezic et al., 2015 ). Another example is Muslim-friendly apps promoting the international trade of products during the tourism process (Cuesta-Valiño et al., 2020 ),

Digitalization’s impact on tourism industrial development

Technological development has driven the tourism industry in local tourist cities, organizations, businesses, and governments. From the perspective of industrial market development, ICT, extensive data network marketing, and other virtual tourism technologies can create market development potential and improve market positioning for companies (Ammirato et al., 2021 ; Filipiak et al., 2020 ; Ma et al., 2021 ).

Adopting and applying information in the tourism industry are commonly regarded as a source of corporate innovation. The implementation of ICT can increase the profitability of tourism enterprises while also increasing organizational productivity (Croitoru and Manoliu, 2016 ; De Lucia et al., 2021 ; Duy et al., 2020 ; Obonyo et al., 2018 ). VR, AR, 3D digital technology, and mobile technology can all be used to improve a company’s performance and competitiveness in the tourism industry (Cranmer et al., 2021 ; Koukopoulos and Koukopoulos, 2018 ; Pavlidis et al., 2022 ; Yuce et al., 2020 ), and these technologies have made significant economic contribution to economic sustainability.

The application and implementation of ICT play an essential role in developing the tourism industry (Adeola and Evans, 2020 ; Tan et al., 2019 ; Zhou and Sotiriadis, 2021 ). Also, digital advanced technologies, such as MR technology adopted by museums, AR technology adopted by destinations, and smart tourism products and tourism ecological reservation systems have made significant contributions in the front-end development stage, providing opportunities to monitor the future development of tourism, as well as being beneficial to the formulation and implementation of tourism industry strategies at later stages (Graziano and Privitera, 2020 ; Tsai et al., 2018 ). The abovementioned electronic environment is an excellent lubricant for tourism’s active and healthy development (Maiorescu et al., 2016 ). Moreover, apps can help customers understand legacy cities more from the standpoint of heritage preservation and help cities promote tourist city development (Briciu et al., 2020 ).

From the perspective of products sold and variations in product types, online services in Muslim-friendly apps can be helpful for market segmentation and promotion of product positioning and sales (Cuesta-Valiño et al., 2020 ). Furthermore, virtual multi-sensory technologies can improve the company’s potential, increase public awareness, and sell products (Martins et al., 2017 ). Undeniably, the development of digitalization enriches the cultural service products of museums in developing heritage tourism (Palumbo, 2021 ), and AR technology also increases the diversification of products in water tourism (Kaźmierczak et al., 2021 ).

Digitalization’s impact on tourism consumption

Tourists’ spending power can reflect the overall economic development of the tourism industry as one of the contributing variables, and the number of tourists and the value of tourist flow are two measurement criteria of tourism consumer spending. Tourism apps, for example, can make traveling more convenient for tourists, increasing tourism consumption (Lin et al., 2020a , b ). Virtual tourism products or augmented reality technology allow tourists to spend more leisure time, increasing consumption (da Silva, 2021 ; Pehlivanides et al., 2020 ).

The application of virtual tourism technology is also helpful in improving the attractiveness of tourists (Cai et al., 2021 ; Manglis et al., 2021 ; Martins et al., 2017 ). Meanwhile, big data analytic tools, e-marketing (WOM), and mobile applications positively influence customers’ intention to travel and contribute to improving tourism sustainability (Gajdosik, 2019 ; Kim and Chang, 2020 ; Pica et al., 2018 ). With the application and construction of ICT, the demand for tourism has increased, and the number of tourists has also increased (Adeola and Evans, 2020 ; Kabassi, 2017 ; Kumar and Kumar, 2020 ). In addition to enhancing tourists’ imagination, virtual tourism technology and 3D digital technology can also be used as practical tools to further develop tourism and increase the number and flow of tourists (Bae et al., 2020 ; Graziano and Privitera, 2020 ; Pavlidis et al., 2022 ). Word-of-mouth marketing has increased the number of tourists (Fernandez-Lores et al., 2022 ; Wang et al., 2020 ).

Digitalization’s impact on social sustainability

Digitalization’s impact on tourist behavior.

Virtual tourism technology is gradually being implemented in the tourism industry, focusing on increasing the satisfaction of the elderly and disabled (Lu et al., 2022 ). Artificial intelligence and virtual reality are integrated into human-computer interaction system equipment, boosting service quality and increasing tourist satisfaction (Van et al., 2020 ). The mixed experience helps enrich tourists’ feelings about the surroundings, thereby boosting tourists’ contentment (Bae et al., 2020 ), and the succinct information and dependable system offered by VR can promote tourists’ satisfaction (Yuce et al., 2020 ). 3D digital technology to build innovative and appealing tourism items can help boost consumer satisfaction and positive feedback (Pavlidis et al., 2022 ).

Tourism stakeholders’ use of tourism apps is critical to increasing tourist satisfaction (Lin et al., 2020a , b ). For example, tourism management in Ho Chi Minh City’s use of Web 4.0 can increase customer satisfaction and loyalty in the long run (Duy et al., 2020 ). The mobile usability and ease of use of social media as a suitable medium directly impact satisfaction (Sharmin et al., 2021 ). It can also serve as a platform for tourists to communicate and contribute to increased satisfaction (Jamshidi et al., 2021 ). Simultaneously, tourism safety is an essential factor that influences tourist satisfaction, and the use of closed-circuit television (CCTV) and unmanned aerial vehicles (UAVs) can help to improve tourism safety (Ko and Song, 2021 ). The use of mobile technologies and payment mechanisms in the tourism process is also a fascinating study. Through electronic technology, two-dimensional code payment techniques improve tourists’ pleasure (Lou et al., 2017 ). Furthermore, incorporating digital innovation into hotel management structures increases hotel performance and client satisfaction (Vitezic et al., 2015 ).

Tourism satisfaction is directly related to tourism experience, and tourism experience is one of the most important criteria to measure in the tourism process. The findings suggest that using virtual immersion technologies such as AR, VR, and MR in the tourism process can significantly improve the tourist experience (Bae et al., 2020 ; Fernandez-Lores et al., 2022 ; Franco and Mota, 2021 ; Lee and Kim, 2021 ; Yin et al., 2021 ).

Additionally, the intention and motivation of tourism drive tourism behavior from the psychological aspect. Digital innovative technology can boost tourists’ interest in tourism products and locations, enrich their understanding of tourism culture, attract more tourists, enhance tourists’ preferences, and strengthen their desire to visit (Caciora et al., 2021 ; Cranmer et al., 2021 ; Gajdosik, 2019 ; Kang, 2020 ; Kaźmierczak et al., 2021 ; Manglis et al., 2021 ; Monterroso-Checa et al., 2020 ;). Digital marketing tools can ramp up customers’ desires and habits (Theocharidis et al., 2020 ), and digital mobile programs can increase tourists’ attention, influencing their overall view of the tourism experience (Wang et al., 2020 ). Big data can also be utilized to foresee client wants and expectations, allowing for a better understanding of customer needs (Del Vecchio et al., 2018 ). For example, Internet of Things technology can scientifically guide and divert tourists to alleviate the problem of local saturation and overload in scenic sites, thus improving the tourist experience (Xie and Zhang, 2021 ). It can also provide various cultural tourism content to enhance and support the experience of active tourists (Ammirato et al., 2021 ).

Digitalization’s impact on social development

Tourism planners and governments can use the analytic hierarchy process (AHP) and geographic information system-remote sensing (GIS-RS) technology to accurately select sites, develop eco-tourism activities, relieve the burden of tourism in the region, and thus help the locals create new employment opportunities (Chaudhary et al., n.d. ). Virtual tourism technology, such as AR, can also aid in analyzing tourist flow and conditions, improve safety, and expand job chances (Franco and Mota, 2021 ). Advances and innovations in tourism ICT can benefit enterprises enough to increase job prospects (De Lucia et al., 2021 ). Virtual tourism, ICT, mobile technology, smart heritage tourism technology, and innovative marketing methods improve stakeholders’ quality of life, increasing the tourism system and community awareness (Lemmi and Deri, 2020 ).

Digitalization’s impact on cultural awareness

Virtual technologies, such as AR, VR, and mobile augmented reality (MAR), are now widely used in cultural heritage tourism, with the potential to protect cultural heritages and enhance the potential of heritage management, thereby contributing to cultural communication (Bec et al., 2019 ; Caciora et al., 2021 ; Graziano and Privitera, 2020 ). Some studies indicate that online engagement platforms, mobile application technologies, and smart tourism models can all support the socially sustainable growth of culture (Bonacini et al., 2018 ; Pica et al., 2018 ; Zubiaga et al., 2019 ).

AR, VR, and other techniques can promote tourists’ behavior in underwater cultural tourism and raise public awareness of natural heritage protection among tourists (Manglis et al., 2021 ). Research on low-carbon travel modes is frequently concerned with tourism sustainability, and big data marketing technology can supply tourists with more low-carbon transport schemes, thus increasing tourists’ environmental consciousness (Ma et al., 2021 ). As a common medium for cultural communication, social media can raise tourists’ awareness of environmental protection (Haque et al., 2021 ).

Digitalization’s impact on participation

Tourists’ active participation in cultural heritage can be enhanced by digital technology, as can people’s feeling of belonging and responsibility to society (Koukopoulos and Koukopoulos, 2019 ; Permatasari et al., 2020 ). Virtual technology can also encourage public participation in preserving and promoting cultural heritages (Caciora et al., 2021 ), while digital media can help tourism businesses improve public relations and social participation (Camilleri, 2018 ; Haque et al., 2021 ). Increased smart tourism destinations optimize the potential for these communities to involve the destinations’ residents and impact their lives due to the improved urban tourism experience.

Stakeholders are closely linked to the sustainable development of tourism. Innovative applications of digital technology can better manage destination stakeholders, strengthening their linkages (Camilleri, 2018 ), help promote their participation in the development of tourist destinations (del Vecchio et al., n.d. ; Gajdosik, 2019 ), and create a democratic and sustainable system when promoting cultural heritage, which balances the opinions of different stakeholders.

The interactive network platform empowers local communities and encourages local inhabitants and tourists to communicate, which promotes the healthy growth of resident-tourism relationships (Dionisio et al., 2019 ). Also, ICT tourism apps influence the ultimate perception of older tourists’ travel experiences, stimulate tourists’ interest in world cultural heritage sites (WCHS), and increase contact and understanding between tourists and destinations (Ramos-Soler et al., 2019 ). Social media can help tourists increase their knowledge of environmental protection, which increases the participation of tourists and citizens and helps formulate sustainable goals (Haque et al., 2021 ).

Second phase: bibliographic network analysis (BNA)

The VOSviewer is the analysis tool used in this work to visualize the impact of digital technology on sustainable tourism development in economic and social aspects. VOSviewer employs the visualization of similarities (VOS) mapping approach to create a map (Moya‐Anegón et al., 2007 ).

Bibliographic coupling network of sources

Bibliographic coupling analysis mainly measures the similarity of documents by the number of identical references cited by documents. Although co-citation refers to the appearance of two documents in the same reference list, bibliographic coupling refers to the number of references that a group of papers share; for example, paper A and paper B are coupled if they both cite document C (Garrigos-Simon et al., 2018 ). In other words, bibliographic coupling happens when two documents quote the same document (Phoong et al., 2022 ; Mulet-Forteza et al., 2018 ), demonstrating the power of one publication in comparison to a group of others (Cavalcante et al., 2021 ). It should be pointed out that the size of the sphere represents the number of similar citations. This paper analyzes the bibliographic coupling network of sources, and the findings are summarized in Fig. 4 . Per Fig. 4 , there are 9 clusters, and the journal source with the highest number of similar citations is Sustainability . It can, therefore, be concluded that this journal has the most citations and published articles on this subject.

figure 4

This figure refers to the number of references shared by a group of papers. Source: Own elaboration.

Citation network of documents

Citations are formed when two documents cite the same document and are used to illustrate the relation between documents and study fields. Figure 5 shows four clusters, each representing the degree of connection and the extent of influence in size. This study has the highest influence, according to the largest green group. It offers insight into the impact of reality and virtual reality on heritage tourism, stating that these technologies favorably impact tourists’ experiences (Bec et al., 2019 ).

figure 5

Cluster size indicates the degree of connection and influence of the literature and research area. There are four groups, with the blue (Encalada et al., 2017 ) and green (Bec et al., 2019 ) groups representing the two articles that are relatively most influential. Source: Own elaboration.

This Blue Group study is also prominent, proposing that the widespread use of information and communication technologies, such as cloud computing, the Internet of Things, and data mining with high processing performance, are the key to tourism’s sustainability (Encalada et al., 2017 ).

The number of citations between documents is used in co-citation analysis to determine their relevance. Figure 6 shows which publications are cited most frequently, and it is clear that tourism management and sustainability are the two commanding the most attention. Generally, the closer two journals are located to each other, the stronger their relatedness. For example, according to an article published in Tourism Management , virtual reality has significantly increased tourism intention and consumption (Tussyadiah et al., 2018 ). Simultaneously, this article presents the finding, which illustrates that combining history with cutting-edge technology in immersive spaces can preserve and manage legacy and enrich the visitor experience and, as a result, engagement with history (Bec et al., 2019 ).

figure 6

This figure represents the citation strength of publications. The circle distance represents relevance. Source: Own elaboration.

Co-occurrence network of Keywords and titles

The significance of keyword co-occurrence analysis in bibliometrics resides in an intuitive understanding of hot subjects in the study field through the frequency and relevance of terms (Phoong et al., 2022 ). Before that, the following considerations must be made.

To begin, each node in the network map indicates a keyword, and the size of the ball represents the number of keywords that appear. The larger the ball, for example, indicates the higher frequency of keywords occurring. Second, the larger the co-occurrence rate between terms, the thicker the curve between the second keywords. In the third, on the network map, different color groups reflect different theme collections, while the same color represents similar subjects (Loureiro and Nascimento, 2021 ).

Figures 7 and 8 illustrate overlay visualization (Fig. 8 ) and network visualization (Fig. 7 ). From Fig. 7 , the keywords of high frequency include tourism (37 occurrences), technology (35 occurrences), tourist (32 occurrences), experience (31 occurrences), information (25 occurrences), application (23 occurrences), data (22 occurrences), analysis (21 occurrences), impact (21 occurrences), sustainability (14 occurrences) and sustainable development (9 occurrences). Some of Red Network Group’s primary keywords are tourism, information, impact, communication technology, virtual reality, new technology, and cultural tourism. The study’s content focuses on the impact of the relationship between information technology and tourism. Yellow Network Group’s primary keywords are destination, tourism destination, environment, and AR, mainly concentrated on destination environment and AR application research. The green network group comprises tourists, analysis, process, big data, management, stakeholders, case studies, innovation, and other topics. This group has conducted more studies on the effect of digital technology on enterprise management from stakeholders’ perspectives. The Blue Network Group focuses on technology, experience, data, service, research, relationships, social media, sustainable development, tourist satisfaction, intention, and other related topics, and this group study is particularly interested in the influence of technology on tourist experience and satisfaction.

figure 7

The same color indicates a close relationship between the keywords. The red network group focuses on tourism and information technology, the yellow network group concentrates on destinations and the environment, and the blue group emphasizes tourists and technology, the green group concerns tourists and analyses. Source: Own elaboration.

figure 8

Darker colors indicate older keywords such as tourists, information, data, research, etc. and lighter colors show the recent hot keywords such as big data, AR, VR, sustainable development, etc. Source: Own elaboration.

After conducting a literature review on digital technology’s economic and social implications on sustainable tourism development over the last ten years and creating a density visualization network map, it can be concluded that tourist experience, information technology, augmented reality, and data are research hotspots. As a result, most studies on tourism sustainability in social and economic dimensions focus on the impact of digital technology on the tourist experience.

Even though they are all co-occurrence analyses of keywords in literature, the emphasis in each network map is different. Generally, overlay visualization and network visualization are comparable to a certain extent; however, the color differs in overlay visualization (Fig. 8 ). In the lower right corner, there is also a quantification table. Purple indicates that the keywords are older, while yellow indicates that they are more modern. For example, keywords such as big data, augmented reality, sustainable development, creation, and intention are yellow, indicating a recent research hotspot, but keywords such as communication technology, information, environment, and service are purple, indicating that these themes were formerly popular.

Results and discussion

The data were collected from 2012 until February 2022. Analysis of the published articles shows a significant increase in publications on digitalization and tourism sustainability development. In 2017, seven articles were published, 10 in 2018, 16 in 2019, and 23 in 2020 and 2021. Furthermore, there are 6 published in the first two months of 2022. These findings illustrate a rise in data availability for digitalization and sustainable tourism development research and suggest that researchers are considering this topic more seriously, demonstrating its value to academic research.

According to the findings, Sustainability was the top journal in published digital and tourism sustainability-related articles. This is followed by the International Journal of Tourism Research , Tourism Management , and Current Issues in Tourism . The number of publications on the relevant subject has increased steadily, particularly in recent years, indicating that this form of research is increasingly gaining attention. Research over the last decade has shown the existence of a certain number of empirical studies on the relationship between digitalization and tourism social and economic sustainability, and from the bibliometric analysis, it emerges that the current research direction on tourism social and economic sustainability has shifted from exploring ICT to AR and VR. Moreover, Tourism Management and Sustainability have the highest citation.

In summary, this study answers RQ1 using the bibliometric literature analysis, while a systematic literature review used to answer RQ2 and RQ3 is discussed in the conclusion and further recommendation sections.

The content of relevant articles published in WOS and Scopus in this research area over the last decade was visually analyzed through bibliometric and systematic literature analysis, and a total of 91 articles meeting the research criteria were selected to provide information on the status of the impact of digitalization on the social and economic aspects of sustainable tourism development, as well as to identify specific research fields and research topics. It can be concluded that the digitalization of the social dimension of tourism sustainability is more richly studied and explored from a more diverse perspective, considering not only the tourists’ but also the residents’ perspectives. There are two implications in the present study. The first is that this study pinpointed the knowledge gaps. Systematic literature review analysis is used in this study to identify the gaps in the existing body of research in tourism development. By reviewing the previous literature and synthesizing the findings, researchers can identify the areas receiving limited or much attention. This insight is valuable for policymakers, tourism planners, and researchers when dealing with specific areas where future research is warranted. Furthermore, the publication trend and popular research themes were also discussed in this study. This enables the policymaker and tourism planner to understand tourism development and the potential for improved policies and practices. The second implication is enabling evidence-based decision-making in tourism development. Researchers can identify patterns, trends, and best practices by synthesizing the findings from multiple studies. This evidence-based approach helps policymakers, destination managers, and tourism stakeholders make informed decisions and develop strategies grounded in research. However, there is a lack of a more comprehensive perspective to explore in an integrated manner. For example, social and economic sustainability development sometimes does not increase simultaneously, and perhaps there is a particular imbalance between the two when using certain digital technologies. Therefore, it can be observed from this study that there is a lack of research in the past ten years that has explored both the economic and social sustainability of tourism comprehensively and that future research could emphasize the integration of social and economic sustainability, even a synthesis study of three dimensions: environmental social, and economic.

Therefore, when considering future developments, several challenges were raised.

Lack of integration study of social and economic dimensions.

Lack of cooperative research among other disciplines.

Lack of suitable theory and conceptual model for sustainable development research in the tourism area.

Lack of universality in different regions based on proposed digital technology.

Lack of research from the perspective of subject education or particular population as the research object.

Based on this literature study, relatively few research topics about this research area are suggested, and the following research scope and questions can be referred to as a priority in the future research process so that research trends can be accurately grasped more quickly and efficiently.

What is the impact of digital technologies on the economic and social sustainability of destinations?

How do digital technologies used in cultural heritage tourism impact tourism sustainability?

What is the impact of digital technology on education?

How can tourism companies improve employee satisfaction, loyalty, and sustainable performance through digital technology?

How can we create a globally accessible and digital system for tourism destinations for sustainable development goals?

How does digitalization impact sustainable development from stakeholders’ perspectives?

The above suggestions and research direction recommendations can provide new research inspiration to researchers in the same field for future research, and this study is expected to help other researchers understand the current research trends related to the digitalization of sustainable tourism development.

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Jiang, C., Phoong, S.W. A ten-year review analysis of the impact of digitization on tourism development (2012–2022). Humanit Soc Sci Commun 10 , 665 (2023). https://doi.org/10.1057/s41599-023-02150-7

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The impacts of ICTs on tourism development: International evidence based on a panel quantile approach

Chien-chiang lee.

1 Research Center of the Central China for Economic and Social Development, Nanchang University, Nanchang, China

2 School of Economics and Management, Nanchang University, Nanchang, China

Mei-Ping Chen

3 Department of Accounting Information, National Taichung University of Science & Technology, Taichung, Taiwan

Information and communication technologies (ICTs) have transformed the travel and leisure sector worldwide, yet until now there are no studies presenting international evidence of the different impacts of ICTs (i.e., Internet usage, secure Internet servers, mobile cellular subscriptions, high-technology export, communications as well as computer, and fixed broadband subscriptions) on tourism development (i.e., international traveler arrivals, increased international tourism receipts, and travel and leisure sector returns) by considering countries with different tourism development processes (e.g., high or low tourism development quantile). It is possible that ICTs have diverse or non-linear impacts on countries undergoing varying tourism development processes. Using international data based on a new panel quantile approach, this research thus aims to explore whether ICTs affect tourism development and looks into the possible asymmetric and non-linear relationships among the many variables. Results show that increasing mobile cellular subscriptions, secure Internet servers, and fixed broadband subscriptions have greater positive effects on traveler arrivals. ICTs also asymmetrically and non-linearly influence tourism across different quantiles. Non-global financial sub-periods and developing nations gain benefits from ICTs’ establishment. Lastly, there are geographic differences in the ICTs-tourism nexus.

Introduction

Information and communication technologies (ICTs) have transformed tourism worldwide and have provided a broad range of novel prospects for tourism growth (Aramendia-Muneta and Ollo-Lopez 2013). According to studies of the resource-based view, technology resources are fundamental drivers to firms’ performance (Ab Wahab et al. 2020 ), and a firm should consider its endowments to ensure that it always can competent with the best in whatever market it chooses to compete (Wernerfelt 1995 ). Currently, there is no research covering international empirical evidence of ICTs’ impact on tourism activities by considering countries with different levels of tourism development. Therefore, this study expands into the global realm and uses a broader array of countries’ data to explore the impacts of six kinds of ICTs on tourism development by examining different national tourism development levels in order to fill the gap in the literature and provide international evidence.

According to the World Travel and Tourism Council (WTTC 2019), one of the world’s biggest economic sectors is travel and leisure, which in 2018 contributed US$8.8 trillion to the worldwide economy, generated 319 million jobs (or 10% of total employment), and improved global GDP by 10.4%. Travel and leisure, the second fastest developing sector in 2018 (only slightly behind manufacturing), has had a remarkable effect on the global economy. Additionally, it is now the most noteworthy service sector, becoming an agent of economic growth that has been broadly approved (Lee and Chang 2008 ; Lee et al. 2021 ; Wu et al. 2021 ; Wang and Lee 2022 ). Moreover, the elements swaying the flow of travelers around the world, such as nations’ infrastructure, will remain and continue to affect tourists’ behavior when choosing their vacation destinations. With approximately all nations seeking to attract global tourists, it is thus imperative to recognize the determining factors of this sector’s receipts, tourists, and stock returns.

Travel and leisure form a highly information-intensive sector, and so its evolution is closely connected to the advance of new information technologies (Velázquez et al. 2015 ). Additionally, greater competition for international tourism has forced related organizations to adopt the latest ICTs in order to achieve a competitive edge as well as satisfactory growth (Abrhám and Wang 2017 ). This sector has broadly applied ICTs to cut costs, save on labor, increase operational efficiency, and most critically improve service quality and customer experience (Law et al. 2009 ). ICTs utilized for or through travel have become much faster, smaller, more intelligent, and more embedded in a user’s situation. Moreover, the travel and leisure sector is characterized significantly by a long value chain affected by information. Hence, the creation, gathering, storage, retrieval, and transfer functions of ICTs remain as vital applications of all tourism companies (Januszewska et al. 2015 ). However, Brynjolfsson ( 1993 ) first proposes the notion of the “IT productivity paradox”, noting that the benefits of spending by tourists are not present in output statistics.

Based on the resource-based view theory by Wernerfelt ( 1995 ), in order to achieve a certain competitive advantage a firm needs to consider its own endowment, its competitors, and its markets. We therefore empirically explore international evidence regarding whether ICTs help to positively attract international traveler arrivals (AR), increase international tourism receipts (RV), and improve travel and leisure sector returns (SR) under different tourism development levels of countries. Research confirms the strong non-linear correlations among ICTs, tourism, and macro-economic variables. For example, Adeola and Evans ( 2020 ) inspect the non-linear impacts of mobile phones and Internet in Africa and present a U-shape relation. Zaballos and López-Rivas ( 2012 ) reveal a non-linear relationship between fixed broadband subscriptions and economic conditions in Latin American and Caribbean countries. Likewise, Ketteni et al. ( 2007 ) present that a non-linear association exists between ICT capital and economic growth. Meo et al. ( 2018 ) show the asymmetric effects of economic factors on tourism demand. Most tourism relevant works utilizing the ordinary least squares (OLS) regression offer only an incomplete picture of a conditional distribution (Mosteller and Tukey 1977 ) and are unable to acquire the coefficients of the independent variables for the entire regression as a function of the change in tourism factors. Thus, this study uses the panel quantile regression (i.e., method of moment quantile regression, MMQR) approach proposed by Machado and Silva ( 2019 ) to explore the ICTs-tourism nexus in a cross-country framework.

Based on data availability, we use six mature ICTs (i.e., Internet usage, secure Internet servers, mobile cellular subscriptions, high-technology exports, communications as well as computer, and fixed broadband subscriptions) of 118 nations for the period 2006–2017. Our research investigates the following. (1) Whether ICTs have substantial impacts on international traveler arrivals. (2) Whether ICTs have substantial impacts on international tourism receipts. (3) Whether ICTs have substantial impacts on travel and leisure sector returns. (4) Does the association between ICTs and tourism development differ at diverse quantiles of the tourism distributions. Figure ​ Figure4 4 depicts our conceptual framework and four hypotheses.

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Research Framework. MMQR analysis is a non-linear model and allows for fixed effects

The contributions of this research to the existing literature of understanding the correlation between ICTs and tourism are articulated as follows. First, scant existing empirical studies explicitly highlight international evidence regarding the impacts of ICTs on tourism across different indicator (arrivals, receipts, and returns) quantiles. For example, Fernández et al. ( 2020 ), Kumar and Kumar ( 2020 ), Patwary et al. ( 2020 ), and Pierdicca et al. ( 2019 ) all use integrated data to explore the ICT-tourism nexus. Thus, our study is a forerunner to consider countries with specific levels of tourism development and provides international evidence in order to identify and formulate specific ICT-related policymaking of tourism destination nations.

Second, prior studies examining the effects of ICT on tourism development employ a limited number of different ICTs at one time for analysis, such as number of Internet users and mobile cellular subscriptions (Adeola and Evans 2020 ); websites, mobile apps, and touch screen (Pierdicca et al. 2019 ); mobile and broadband subscriptions (Kumar and Kumar 2020 ); international telecommunication services, news related transactions among non-residents and residents, computer data, and technical services (Shehzad et al. 2019 ); and mobile subscriptions (Kumar et al. 2019 ). Therefore, the existing literature does not specifically address the impacts of six different ICTs in a destination nation on tourism development (i.e., international traveler arrivals, tourism receipts, and sector returns).

Third, an ICT access and use has been recognized worldwide (Chinn and Fairlie 2007 , 2010 ). However, there is still little international evidence from related literature. Many regional or country-specific related studies do exist—for example, Africa (Adeola and Evans 2020 ), U.S. (Akron et al. 2020 ), 28 countries (Choudhary et al. 2020 ), Latin American countries (Eugenio-Martin et al. 2004 ), Iran (Feshari 2017 ), and Israel (Kumar et al. 2019). Taking advantage of the large amount of worldwide data from World Development Indicators (WDI) issued by the World Bank database, our research employs cross-country data from 118 nations, provides global evidence, and generalizes the findings for wider global ICT applications in order to distinguish the differences in ICTs’ impacts among countries with different tourism development levels.

Fourth and finally, Zaballos and López-Rivas ( 2012 ) pinpoint a non-linear association between fixed broadband subscriptions and economic condition. Ketteni et al. ( 2007 ) also reveal a non-linear association between ICT capital and economic development. Therefore, this study takes advantage of a new panel quantile regression (i.e., method of moment quantile regression, MMQR) approach proposed by Machado and Silva ( 2019 ) to specify how ICTs affect the entire conditional distribution of tourism development. MMQR offers a flexible tool to evaluate panel quantile regression, especially when the parameter estimations are hard or even impossible, thus producing reliable and robust results for policy formulations (Guo et al. 2020 ). This paper is a pioneering tourism study that applies MMQR to beneficially complement the present literature and has vital implications for countries across different tourism development levels.

Our findings show that secure Internet servers, mobile cellular subscriptions, and fixed-line broadband subscriptions have salient positive impacts on international traveler arrivals, while mobile cellular subscriptions and communication, computer notably and negatively affect tourism receipts for countries with the greatest tourism receipts. Mobile cellular subscriptions and high-technology exports (Internet usage, communication, computer, and fixed broadband subscriptions) negatively (positively) impact travel and leisure sector returns at different return quantiles. Thus, our findings support that ICTs in a destination nation determine traveler arrivals, tourism receipts, and sector returns. There is also salient evidence showing how ICTs asymmetrically and non-linearly influence tourism development across different quantiles. Further tests disclose that the relationships between ICTs and tourism development are robust after considering non-global financial sub-periods, endogeneity problems, and the countries’ own economic development situations. European nations exhibit a different ICTs-tourism nexus. Interestingly, we find significantly positive impacts of the global financial crisis on sector returns at intermediate and higher return quantiles, suggesting that the travel and leisure sector can be a safe-haven during the global financial crisis.

The rest of this study is organized as follows. Section  2 briefly reviews the literature and hypotheses. Section  3 illustrates the research methodology. Section  4 analyzes and discusses the empirical findings obtained. Section  5 concludes the research.

Literature review and hypotheses’ development

Regarding the resource-based view, Wernerfelt ( 1995 ) pinpoints that it is a truism that firms have different resource endowments and that it takes time and money to change these endowments. The same saying goes for many game-theoretic analyses (Rotemberg and Saloner 1994 ) that note how a firm employs its own resource endowments to achieve certain competitive goals. Wernerfelt ( 1995 ) argues that game-theoretic analyses are so general that they often depend neither on the identity of the firm nor its competitors, nor on that of its markets. In fact, firms almost always must do better or otherwise they will exit the market. Based on the viewpoint of Wernerfelt ( 1995 ) for considering the different endowments of countries, we expand to the country level, explore ICTs’ impact on those countries with different levels of tourism development, and investigate their endowments, the whole markets, and their competitors in order to provide suggestions for economies undergoing different processes of tourism.

Zhago et al. (2019) note that with increasing technological advancement and its permeation into all aspects of human life, tourism sectors have applied a variety of technologies to facilitate travel activities that enhance travelers’ destination experiences. Tcheng et al. ( 2007 ) disclose that the positive influences of ICT can be felt earlier, since ICT is similar to other utilities such as water, electricity, and transportation. As fixed investment has positive impacts on economic growth, investment in public infrastructure such as ICTs can enhance a country’s overall development (Kpodar and Andrianaivo 2011 ). Waverman et al. ( 2005 ) also state that ICT investment is a form of cost savings, because communication utilities cut down transaction expenses. By decreasing the costs of retrieving information, ICT advances information flows, enables and improves price discovery, permits markets to function better, and helps regulate supply and demand (Kpodar and Andrianaivo 2011 ). The development of more sophisticated ICTs empowers both providers and destinations to increase efficiency and to implement a strategy in which re-engineered forms of communication dominate (Buhalis and Law 2008 ).

There are numerous studies probing the impacts of ICTs on tourism fields. For example, Mavri and Angelies (2009) use five European Union Mediterranean nations and find a salient positive relation between traveler arrivals and Internet usage. Ramos and Rodrigues ( 2013 ) use the number of Internet users in eighteen European nations, and show a positive association between number of online reservations and ICT. Kumar et al. ( 2019 ) note that mobile subscriptions can be utilized as a tool to enlarge tourism markets and visitor arrivals, mainly by keeping prospective tourism source markets informed. Adeola and Evans ( 2020 ) employ the number of Internet users and mobile cellular subscriptions to explore ICT’s effect on tourism growth in African nations and present that ICT infrastructure has a positive and noteworthy influence on traveler arrivals. Kumar and Kumar ( 2020 ) indicate a unidirectional causality from mobile and fixed broadband subscriptions to both tourism demand and the destination nation’s income.

The IT productivity paradox proposed by Brynjolffson (1993) conversely pinpoints the existence of negative impact of ICTs on productivity. The reason for the IT productivity paradox can be explained by the peer effect, time-lagging effect, and commoditization. Specifically, Gangopadhyay and Nilakantan ( 2021 ) explore the bank industry and address that although IT adoption can enhance firm productivity, resource use efficiency, and service quality through strengthening organizational capabilities, a proper assessment of costs and benefits of any type of new technology may be difficult for potential users, because IT has previously overlooked the influence of peer firms. Hwang et al. ( 2015 ) find that computers and Internet usage do not correlate to enhancing a firm’s competitive advantage, since they are both now commoditized, such as IT being a form of infrastructural technology, like railroads and electricity (Carr 2003 ). Moreover, because it takes time for workforces to get adjusted to new ICTs, visitor arrivals only experience a positive impact in the long run, rather than in the short run (Kumar et al. 2019 ), implying the time-age effect of ICTs.

Aramendia-Muneta and Ollo-Lopez (2013) provide evidence that the usage of various ICTs has a slight influence on the level of competition as well as on greater productivity, while they have a positive influence on expanding the market share of companies. Although ICTs as a possible new competitive factor have been tested, Mihalič ( 2007 ) confirms a negative direct impact of ICT, proxied by Internet use, on the productivity of the travel sector and attribute the results to the ICT productivity paradox. Grace et al. ( 2003 ) denote that it may be challenging to form a causal connection between ICT and economic growth, because adverse influences might arise due to the opportunity costs of ICT investments and expenditures rather than in water, food, education, skills, etc. Safaeepour et al. (2015) analyze the influence of ICT on traveler arrivals and show that the effect of ICTs in tourism affairs is not noticeable. Sigala et al. (2004) demonstrate that productivity gains accrue not from investment per se, but from the entire utilization of ICT networking and informationalization abilities. Tsokota et al. ( 2017 ) indicate that simply having ICTs without any co-ordination, integration, and collaboration cannot attain sustainable development in the travel and leisure sector.

There is hence no consensus as to how ICTs impact tourism development. It is also doubtful that ICTs have any salient impact on AR. Thus, we form the following hypotheses to generalize the associations between ICT and AR internationally. Based on the literature mentioned above, we present the hypotheses as follows.

H1: ICTs have substantial impacts on international traveler arrivals.

Using the Granger causality test, Kumar and Kumar ( 2012 ) reveal a unidirectional causality going from capital stock to ICT and from ICT to tourism receipts. Using regression models, Al-Mulali et al. ( 2020 ) show that digital adoption has a positive impact on real tourism receipts for all their sub-sample groups (except high-income countries). Tsaurai and Chimbo ( 2019 ) find ICT has a positive influence on tourism receipts both in the long and short runs. Choudhary et al. ( 2020 ) confirm the importance of ICTs to an increase of tourism receipts. However, the correlation between tourism receipts and tourist arrivals is significant with 0.5 in coefficient’s statistic regarding an unconditional correlation, and thus we realize that there exists differences between tourism receipts and traveler arrivals. Confronting the issue of the IT productivity paradox, it is doubtful that ICTs significantly impact RV via international evidence. Thus, we form the Hypothesis 2.

H2: ICTs have substantial impacts on international tourism receipts.

Using regression analysis, Chen et al. ( 2005 ) indicate that among the macroeconomic variables, only money supply and the unemployment rate significantly explain the movement of hotel stock returns, while all non-macroeconomic factors selected (i.e., presidential elections, the 921 earthquake in Taiwan, the 2003 Iraqi war, the SARS outbreak in 2003, sports mega-events, the Asian financial crisis, and the 911 terrorist attacks) have significant influences on the hotel stock returns. Chen ( 2007 ) reveals that Chinese hotel stock returns are more sensitive to general macro-level variables. Non-macroeconomic events that could significantly impact Chinese hotel stock returns encompass financial crises, natural disasters, wars, terrorist attacks, political events, and sports mega-events. Chen et al. (2012) indicate that the discount rate, unemployment rate, and oil price could significantly affect Japanese hotel stock returns and serve as significant determinants of these returns. Demir et al. ( 2017 ) present that the consumer confidence index, exchange rate, and foreign tourist arrivals could Granger cause tourism stock returns. Until now, few studies have addressed ICTs’ impacts on tourism stock returns. Built on the abovementioned literature, we hypothesize that ICTs influence travel and leisure sector returns and form the following hypothesis.

H3: ICTs have substantial impacts on travel and leisure sector returns.

Most tourism related works utilizing OLS offer only an incomplete picture of a conditional distribution (Mosteller and Tukey 1977 ) and are unable to acquire the coefficients of the independent variables for the entire regression as a function of the change in tourism factors. Additionally, Chiu and Yeh ( 2017 ) discover strong evidence of a non-linear relation between tourism development and economic growth, suggesting that it is not continuous and constant. Adeola and Evans ( 2020 ) find non-linear impacts of mobile phones and Internet usage in Africa’s tourism sector that present a U-shape relation. Zaballos and López-Rivas ( 2012 ) reveal a non-linear relationship between fixed broadband subscriptions and the economic conditions in Latin American and Caribbean countries. Ketteni et al. ( 2007 ) present a non-linear association between ICT capital and economic growth. Meo et al. ( 2018 ) find asymmetric effects of economic factors on tourism demand. Thus, this study uses MMQR to probe the ICTs-tourism nexus under different tourism development quantiles and forms the next hypothesis.

H4: The association between ICTs and tourism development differs at diverse quantiles of the tourism distribution.

Compared to foreign traveler arrivals, Chen ( 2007 ) reveals that general macro-level elements are more sensitive to hotel stock returns. Tourism is also regarded as a vital means at overwhelming the macroeconomic problems via improving the balance of payments and generating income, taxes, hard currency, and jobs (Lee and Brahmasrene 2013 ). Tourism relates closely to economic development and socio-economic growth, not only for numerous developing nations, but also for some developed nations (Shahzad et al. 2017 ). Demir et al. ( 2017 ) present that growths in exchange rate and foreign traveler arrivals have a close correlation. Thus, we comprise GPD per capita growth rate (GDP), real exchange rate (EXG), inflation (INF), and unemployment (UMP) as control variables.

Methodology

Independent variables.

Figure ​ Figure4 4 depicts our research framework. This study examines international evidence of the different impacts of ICTs (i.e., Internet usage, secure Internet servers, mobile cellular subscriptions, high-technology exports, communications as well as computer, and fixed broadband subscriptions) on tourism development (i.e., international traveler arrivals, increased international tourism receipts, and improved travel and leisure sector returns) by considering countries with different tourism development processes (e.g., high or low tourism development quantile). Compared to the large majority of related quantitative studies (e.g., Bethapudi 2013 ; Bizirgianni and Dionysopoulou 2013 ) using questionnaires that suffer the shortcomings of particular populations, self-selection bias, and collected samples from limited sets (Wright 2005 ), our analysis covers data on ICTs from the WDI issued by the World Bank Database. 1

Andrianaivo and Kpodar ( 2011 ) use growth in personal computer users and Internet users to probe the influence of ICT on economic growth in African countries. Adeola and Evans ( 2020 ) use the number of Internet users (% of population) and mobile cellular subscriptions (% of population) to explore the association between ICTs and African tourism development. Kumar and Kumar ( 2020 ) indicate a unidirectional causality from mobile and fixed broadband subscriptions to both tourism demand and the destination nation’s income. Choudhary et al. ( 2020 ) employ computer, communication, and other services , Internet users , secure Internet servers , and mobile cellular subscriptions to explore the relationship between ICTs and tourism in 28 countries. Gooroochurn and Sugiyarto ( 2005 ) discuss an innovative approach for measuring tourism competitiveness using high-technology exports for over 200 countries and find that the factor of high-technology exports has an important influence.

Following these studies, our ICT indices are proxied by six variables: (1) Individuals using the Internet, % of population (INT); (2) Secure Internet servers, per 1 million people (SEC); (3) Mobile cellular subscriptions, per 100 people (MOB); (4) High-technology exports, % of manufactured exports (TEX); (5) Communications, computer, etc., % of service exports (CCE); and (6) Fixed broadband subscriptions, per 100 people (FBS). Table ​ Table10 10 main variable list in Appendix identifies all variables employed by our study.

Main variable list

Notes: All the variables are in log difference form, except for SR, and GDP, INF, and EXG. EXG is in log form. Except for the travel and leisure stock prices of 118 countries, all data are from the World Development Indicators (WDI) by the World Bank database, which is the most comprehensive international database

Dependent variables

Utilizing the ratio of international tourism receipts to total exports, Sreekumar and Parayil ( 2002 ) investigate tourism as a growth choice. Gokovali ( 2010 ) also employs the ratio of international tourism receipts to total exports so as to explore the contribution of tourism to economic growth. Eugenio-Martin et al. ( 2004 ) use the number of traveler arrivals to study the association between that datapoint and economic growth. Chen ( 2011 ) takes tourism sector stock returns to assess the performance of supply-side investments in the tourism sector.

Following the abovementioned literature, the three dependent variables of tourism development used herein are log difference of international traveler arrivals (AR), log difference of international tourism receipts (percentage of total exports) (RV) from the World Bank database, and travel and leisure sector yearly price index from the DataStream database. Sector returns (SR) are estimated by ( P t  −  P t −1 ) / P t −1 , where P t is the adjusted closing price index at time t in US dollars. Because the latest data of AR and RV are for the year 2017, our empirical study uses 118 nations that possess AR and RV data, and our study period is 2006–2017. Table ​ Table11 11 Sample nation list provides the sample nations.

Sample nation list

Notes: We gather the nations that have tourism relevant data in the World Bank database, and the above 118 nations are utilized in this study. The bold nations are in Europe. # signifies developing countries

Control variables

Chiu and Yeh ( 2017 ) denote that tourism development has a salient relation with inflation and exchange rate changes. Chen ( 2007 ) gauges the relationships between macro-level explanatory factors and Chinese hotel stock returns by employing the consumer price index and total foreign traveler arrivals. Castro-Nuño et al. ( 2013 ) show a positive association exists between GDP and tourism. Perles-Ribes et al. ( 2016 ) note the unemployment influence of economic crises on hotel and residential tourism destinations. We thus account for the impact of economic elements by comprising EXG (log of real exchange rate, real exchange rate estimates by the destination country’s official exchange rate*US CPI/destination country’s CPI), GDP (GDP per capita growth, annual %), INF (inflation, consumer prices, annual %), and UMP (log difference of unemployment, total % of total labor force). All data are collected in US dollars. Four control factors are from the World Bank database.

Following Divino and McAleer ( 2010 ) in which the log difference has sensible interpretations, we use the log difference forms of all variables, except for SR, which has negative values and GDP, INF, and EXG. EXG is in log form. As tourism involves discretionary income, it is anticipated during a tough economy that people may choose to save their cash for the necessities of life such as food, shelter, and family supplies (Papatheodorou et al. 2010 ). Therefore, according to Ntim et al. ( 2013 ), we identify the global financial crisis period as 2008–2009. 2 Balli et al. ( 2019 ) estimate traveler arrivals by controlling regional structural changes. Eugenio-Martín et al. (2004) discover that the nexus between the number of traveler arrivals and economic development does exist in developing nations, but not in developed nations. Therefore, to conduct an inclusive investigation we split the sample data into three subgroups: developing nation, non-global financial crisis, and European nations. Most of our sample nations (33) are in Europe.

Descriptive statistics of variables

Table ​ Table1 1 provides summary statistics of our main variables. Results from Table ​ Table1 1 show that SR varies between -0.808% and 5.267% during the sample period, with the median being 0.00% and the average being 0.067%. The travel and leisure sector returns are positively skewed, suggesting that the tail on the right side of the possibility density function is fatter than that on the left side. The kurtosis coefficients are greater than 45.939 for SR, indicating that the series have fatter tails than other dependent variables. Additionally, the distributions are asymmetric. The average RV is 1.109, and the range fluctuates between -27.118 and 43.753 with a 6.589 standard deviation during the sample period, suggesting large dissimilarities among nations’ tourism receipts. The mean AR is 2.454, and the range fluctuates between -24.008 and 27.44 with a 4.988 standard deviation.

Descriptive statistics

Notes: The yearly data in this study span from 2006/01/01 to 2017/12/31. ‘Min’, ‘Max’, and ‘STD’ are respectively the minimum, maximum, and standard deviation. AR (number of international inbound travelers), RV (international tourism receipts, % of total exports), SR (country travel and leisure sector returns), INT (individuals using the Internet, % of population), SEC (secure Internet servers, per 1 million people), MOB (mobile cellular subscriptions, per 100 people), TEX (high-technology exports, % of manufactured exports), CCE (communications, computer, etc., % of service exports), FBS (fixed broadband subscriptions, per 100 people), GDP (GDP per capita growth, annual %), INF (inflation, consumer prices in annual %), EXG (real currency exchange rate per US$), and UMP (unemployment, total % of total labor force). All the variables are in log difference form, except for SR, which has negative values and GDP, INF, and EXG. EXG is in log form. The six ICT factors are INT, SEC, MOB, TEX, CCE, and FBS. The Jarque–Bera (JB) statistics of all variables indicate departures from normality and present the existence of non-linear components in the data-generating process

Table ​ Table2 2 displays the unconditional correlation between variables. The correlation between AR and RV is significantly positive. Among the six ICT variables, SR saliently and negatively relates to SEC. RV notably and negatively relates to CCE, whereas it notably and positively relates to TEX. Nevertheless, AR notably and negatively correlates to CCE. GDP is saliently positive with AR, which is consistent with Saha and Yap ( 2014 ), suggesting that governments in high-income countries can afford to invest funds toward building up and maintaining infrastructures for the tourism industry, which in turn attract more tourists with an expectation that high income increases demand for tourism. Castro-Nuño et al. ( 2013 ) also show a positive relationship between GDP and tourism. We find a negative impact of UMP and AR, which is in line with Inchausti-Sintes ( 2015 ) in that tourism promotes economic growth and reduces unemployment. The positive relation of the real exchange rate with AR and RV is similar to Ghartey ( 2013 ), whereby in the long run, tourism growth causes currency depreciation (an increase in the real exchange rate), suggesting that the depreciation increases traveler arrivals and real expenditures. The negative relation between inflation and SR is in line with Fama ( 1981 ), who says that common stock returns and inflation are negatively related. The positive relation between inflation and RV is inconsistent with Meo et al. ( 2018 ). It is expected that tourism demand responds asymmetrically to inflation, because a rise in inflation increases the travel and living costs of tourists and reduces their purchasing power. On the other hand, a decline in inflation increases purchasing power, and more tourists can visit the host country (Meo et al. 2018 ).

Unconditional correlation

Notes: Yearly data cover the period 2006 to 2017. AR (number of international inbound travelers), RV (international tourism receipts, % of total exports), SR (country travel and leisure sector returns), INT (individuals using the Internet, % of population), SEC (secure Internet servers, per 1 million people), MOB (mobile cellular subscriptions, per 100 people), TEX (high-technology exports, % of manufactured exports), CCE (communications, computer, etc., % of service exports), FBS (fixed broadband subscriptions, per 100 people), GDP (GDP per capita growth, annual %), INF (inflation, consumer prices in annual %), EXG (real currency exchange rate per US$), and UMP (unemployment, total % of total labor force). All the variables are in log difference form, except for SR, which has negative values and GDP, INF, and EXG. EXG is in log form

The panel unit-root test results show a uniform conclusion that the variables are stationary in level form. The probabilities for the Levin, Lin, and Chu tests are computed using an asymptotic Chi-square distribution. All other tests assume asymptotic normality. The maximum lag lengths are automatic selection, and Schwarz Bayesian Criterion is used to determine the optimal lag length. Due to space limitation, results of panel unit-root tests are not shown, but are available from the authors upon request.

Conventional OLS provides summary point estimations for the average results of the explanatory variables (Binder and Coad 2011 ). Focusing on the average impacts may under- or over-estimate the relevant coefficient estimates or may even fail to recognize vital associations (Binder and Coad 2011 ). Taking the unobserved individual heterogeneity and distributional heterogeneity into account, Lv and Xu ( 2017 ) examine the impact of corruption on tourism demand by using the panel quantile regression approach. Menegaki et al. ( 2020 ) explore aggregate tourist demand in Europe with a panel quantile regression approach. Hence, OLS, which can depict the association at the average level, might lead to misspecification, and information around the tails of a distribution will be overlooked.

Meo et al. ( 2018 ) find a long-run asymmetric relationship between inflation and tourism demand and apply a linear symmetric model for tourism demand, which could be misleading. Chiu and Yeh ( 2017 ) pinpoint that if one ignores the probability that the tourism-economic development nexus could be non-linear, then the findings of a linear model often cause bias due to using a false assessment method (Lee et al. 2020 ). Zaballos and López-Rivas ( 2012 ) present a non-linear connection between fixed broadband subscriptions and economic conditions. Ketteni et al. ( 2007 ) also reveal a non-linear association between ICT capital and economic growth.

MMQR offers a flexible tool to evaluate panel quantile regression, especially when the parameter estimations are hard or even impossible to calculate, thus producing reliable and robust results for policy formulations (Guo et al. 2020 ). Using MMQR proposed by Machado and Silva ( 2019 ) to control for distributional heterogeneity, Lee and Chen ( 2020 ) explore the effects of country risks on tourism development. Applying MMQR, Guo et al. ( 2020 ) analyze the impacts of influential factors on CO 2 emissions at various quantiles and control for diverse econometric challenges such as endogeneity and heterogeneity. Elheddad et al. ( 2020 ) employ MMQR to estimate models with fixed effects and models with endogenous explanatory variables.

The MMQR approach is thus applied to appraise whether ICT variables influence AR, RV, and SR by intensifying the descriptive statistics in Table ​ Table1 1 and testing Eqs. ( 1 ), ( 2 ), and ( 3 ) by utilizing AR, RV, and SR as dependent variables, respectively.

Here, tourism development’s AR it , RV it , and SR it represent nation i ’s international traveler arrivals, tourism receipts, and travel and leisure sector returns in time t . ICT it denotes the six ICT proxies: INT (individuals using the Internet, % of population), SEC (secure Internet servers, per 1 million people), MOB (mobile cellular subscriptions, per 100 people), TEX (high-technology exports, % of manufactured exports), CCE (communications, computer, etc., % of service exports), and FBS (fixed broadband subscriptions, per 100 people). CV is the four macroeconomic control variables and three dummy variables (i.e., economic development state, European country, and global crisis period) that might sway AR, RV, and SR: GDP (GDP per capita growth, annual %), INF (inflation, consumer prices in annual %), EXG (real exchange rate), and UMP (unemployment, total % of total labor force). All the variables are in log difference form, except for dummy variables, SR (which has negative values), GDP, INF, and EXG. EXG is in log form.

We estimate Eqs. ( 1 ), ( 2 ), and ( 3 ) by the MMQR models to explore H1-H4. Equations ( 1 )–( 3 ) can answer the question of “whether ICT symmetrically affects tourism development (i.e., H1–H3)”. However, it does not solve the problem of whether “ICT affects tourism development differently for countries with different levels of tourism development (H4)”. From the viewpoint of policy-making, it is more interesting to understand what happens in extreme cases. To answer these questions, quantile regression can be very useful. It is an extensive form based on the traditional regression and offers a complete picture of a conditional distribution. For our study, this method helps obtain the entire influences of ICTs across the full distribution of tourism development. Furthermore, this model is robust to outliers, heteroskedasticity, and skewness (Koenker and Hallock 2001 ).

We write the model as follows:

where 0 <  ∂ <1, M yt ∂ | x t denotes the ∂ th conditional quantile of y t , x t denotes all the determinants, and β ∂ and α ∂ are the estimated parameters and unobserved effects at the ∂ th quantile. It is obvious that the above equation does not account for unobserved individual heterogeneity. 3 Thus, Eq. ( 4 ) is improved as the following a panel quantile regression form:

Machado and Silva ( 2019 ) suggest a new panel quantile regression model via moments. The approach of Machado and Silva ( 2019 ) has a unique advantage in the non-linear model and makes the calculation simpler, particularly when several endogenous variables exist. Following Machado and Silva ( 2019 ), we form the following equation:

where N it is known differentiable (with probability) transformations of x it , ∅ (.) is a known ℓ 2 function such that P ∅ ω i + N it ′ τ = 1 , and H it is an unobserved random variable. Specifically, H it ⊥ x it , E H = 0 , and E H = 1 . From Eq. ( 6 ), we obtain:

where m ∂ = F H - 1 ( ∂ ) , and hence P H < m ∂ = ∂ . When ∅ (.) is the identity function and N it = x it , Eq. ( 7 ) can be simplified to:

where α i ∂ = α i + ω i m ( ∂ ) represents the ∂ th quantile fixed effect for country i . Unlike the usual quantile fixed effect, this differs from the location shift—that is, this approach allows the time-invariant individual characteristic to distinctly affect the conditional distribution of y it across countries. The marginal effect of variable x i t , k on the ∂ th quantile of y it is β k + m ( ∂ ) × ρ ∅ ( ω i + N it ′ τ ) / ρ x i t , k .

Influences of ICTs on international traveler arrivals (H1)

We report the results from quantile analysis in Eq. ( 1 ) in Table ​ Table3 3 in terms of estimates of the MMQR-based international traveler arrival models. Regarding panel quantile regression estimates with 95% confidence intervals for the impacts of the independent variables on international traveler arrivals, Fig.  1 provides summary charts for the MMQR results. We estimate the quantiles, from the lower one (q = 0.1) to the higher one (q = 0.9), all of which divide AR. The non-linear effects of ICT are explored by considering different AR distributions. Figure  1 shows the marginal effect of the six ICT variables for all quantiles within the (0,1) range of AR. Figure  1 offers the non-linear findings that ICT asymmetrically affects AR at lower and upper quantiles.

Estimates of the MMQR-based international traveler arrival models

This table reports the estimation results of ICTs’ impacts on the log difference of international traveler arrivals according to Eq.  1 . Yearly data are used for the period 2006 to 2017. *, **, and *** represent significance at the 10%, 5%, and 1% levels, respectively. The rest of the notes are the same as in Table ​ Table2 2

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Panel quantile regression estimates with 95% confidence intervals for the impacts of the independent variables on international traveler arrivals. The shaded area shows the quantile regression estimates for the quantiles ranging from 0.1 to 0.9, a solid line is the estimates, and the grey area depicts lower and upper bounds of the 95% confidence intervals for the quantile regression estimates

We draw some interesting findings about ICTs’ non-linear effects on AR. First, the effects of FBS are constantly positively significant at all quantiles, and the coefficients of two extreme quantiles are larger than those coefficients of the others, indicating that increasing FBS leads to higher AR for all AR quantiles. Our findings expand the results of Thompson and Garbacz ( 2011 ) in that low-income nations derive considerably benefit from mobile broadband services. Second, INT, TEX, and CCE show no salient impacts on AR. Third, MOB and SEC are considerably positively associated to AR at several quantiles, implying that increasing MOB and SEC non-linearly leads to higher AR at lower to higher quantiles. The MOB finding is consistent with Choudhary et al. ( 2020 ), whereby mobile cellular subscriptions have a positive effect on tourism development. Rajan et al. ( 2016 ) states that an increase in the number of secure Internet servers results in a rise by the number of tourism arrivals. Because of the inconsistent impacts of SEC and MOB, we conclude that the non-linear, positive, and significant effects of MOB and SEC influence AR trends. Taking ICTs into account helps tourism participants to realize the ICT determinants of AR. Thus, our results support Hypothesis H1 in that ICTs have positive and significant effects on international traveler arrivals. Likewise, Adeola and Evans ( 2020 ) find when ICT and infrastructure increase in African nations that the level of traveler arrivals also increases.

Regarding control variables, GDP positively influences AR. Similarly, Saha and Yap ( 2014 ) note that governments in high-income countries can afford to invest funds toward building up and maintaining infrastructures for the tourism industry, which in turn attract more tourists, expecting that high income increases demand for tourism. Castro-Nuño et al. ( 2013 ) also display a positive association between GDP and tourism. INF shows asymmetric correlations with AR; i.e., a negative (positive) relation at lower (higher) quantiles, which is consistent with the finding of Meo et al. ( 2018 ) who present a long-term asymmetric association between inflation and tourism demand. UMP shows no salient link with AR. EXG is positively linked with AR and is consistent with Ghartey ( 2013 ) who note in the long run that tourism growth causes currency depreciation (an increase in the real exchange rate), suggesting that depreciation increases traveler arrivals and real expenditures. Developed countries and European countries show salient positive impacts on AR quantiles, whereas GLCR shows generally salient negative impacts on AR quantiles. Thus, AR is sensitive to macroeconomic variables.

Influences of ICTs on international tourism receipts (H2)

Table ​ Table4 4 displays quantile assessments from Eq. ( 2 ). Figure  2 presents MMQR parameter estimates along with the 95% confidence intervals (solid lines) for the predictive power of ICT variables’ influence on RV. Figure  2 displays that the estimated 95% confidence intervals for the impacts of MOB, TEX, and FBS on international tourism receipts are smaller, signifying that these variables can work as determinants in identifying RV. For the ICT variables in Table ​ Table4 4 regarding the estimates of the MMQR-based international tourism receipt models, MOB remarkably and negatively affects RV at the 25th–50th quantiles, and CCE consistently, notably, and negatively impacts RV for the entire quantiles. This implies that MOB and CCE establishment costs might lead tourism receipts to decrease. Thus, we should explore further as to whether these negative MOB and CCE impacts are consistent with the IT productivity paradox of Brynjolfsson ( 1993 ) in which the benefits of spending do not show up in statistics. TEX and FBS have a positive noteworthy effect at the 90th quantile, meaning that the highest RV nations could increase TEX and FBS to improve RV. Thus, our results partially support Hypothesis H2 that CCE, TEX, and FBS have noteworthy impacts on international tourism receipts. To sum up, we find that CCE negatively affects all RV quantiles.

Estimates of the MMQR -based international tourism receipt models

Notes: This table reports the estimation results of ICTs’ impacts on international tourism receipts according to Eq.  2 . Yearly data are used for the period 2006 to 2017. The rest of the notes are the same as in Table ​ Table2 2

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Panel quantile regression estimates with 95% confidence intervals for the impacts of the independent variables on international tourism receipts. The same as in Fig.  1

We next present that the influences of MOB, TEX, and FBS on RV are non-linear across the quantiles. Comparing the influences of ICT variables in Tables ​ Tables3 3 and ​ and4, 4 , the ICT indices display more noticeable positive effects on AR than on RV. The probable reasons for the significance of ICTs on AR than on RV are followings: First, AR can be more directly and immediately used to estimate tourism development. RV is largely influenced by several macroeconomic factors, such as exchange rate, inflation, oil prices etc. However, for ICTs’ impacts on RV, one needs time to convert ICT capitals into revenues. Second, as mentioned above, the IT productivity paradox whether and how IT investment leads to higher market value and/or performance remains in question. Brynjolfsson ( 1993 ) suggests IT usage should consider the time lag effect, which refers to after IT investment it may take some time to create profits.

Regarding the control variables, GDP and INF display negative influences on RV at some of the quantiles, denoting that lower GDP and an INF economy might inspire greater RV. UMP has positive impacts at some quantiles, which implies that higher UMP can cut costs in the travel and leisure sector, leading to a higher RV. EXG is positively linked with AR, which is consistent with the finding of Table ​ Table3 3 that currency depreciation (an increase in the real exchange rate) increases traveler arrivals and real expenditures. Developed countries show a mixed impact on RV quantiles, while European countries show salient negative impacts on RV quantiles. Interestingly, GLCR show saliently positive impacts on RV at higher quantiles, implying that higher RV countries gain tourism receipts especially during the global financial crisis. Thus, RV is sensitive to the control variables.

Influences of ICTs on travel and leisure sector returns (H3)

Table ​ Table5 5 presents the estimates of the MMQR-based travel and leisure sector return models by Eq. ( 3 ), and in regards to panel quantile regression estimates with 95% confidence intervals for the impacts of the independent variables on travel and leisure sector returns, Fig.  3 graphically represents the point estimates of the model parameters and displays that the estimated confidence intervals of SEC, TEX, and FBS are smaller, signifying that these variables can work as determinants in identifying SR. INT (CCE) has a substantial and positive influence on SR at the 75th (90th) quantile, and FBS has a salient and positive impact on 75th–90th SR quantiles. Likewise, Kotoua and Ilkan ( 2017 ) pinpoint that all types of businesses are supported by Internet marketing, and Internet use has made it easier for e-word of mouth to spread. Vu ( 2011 ) explores the economic effect of ICT and finds that the penetration rate of Internet users has a significant causal effect on economic growth. McDonough ( 2012 ) states that FBS increases the market power of the tourist industry. However, MOB has saliently negative impacts on SR at the 10th–75th quantiles, and TEX has a notably negative impact on the 75th quantile. Thus, our finding partially supports H3 that ICTs have important influences on travel and leisure sector returns.

Estimates of the MMQR– based travel and leisure sector return models

This table reports the estimation results of ICTs’ impacts on travel and leisure sector returns according to Eq.  3 . The rest of the notes are the same as in Table ​ Table2 2

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Panel quantile regression estimates with 95% confidence intervals for the impacts of the independent variables on travel and leisure sector returns. The same as in Fig.  1

Findings for control variables comprised in the model are also informative. INF is negative and significant at the lower and intermediate quantiles, which matches up with Chen et al. ( 2005 ) in that inflation is inversely related to stock returns. The mixed but salient effect of UMP in the highest quantile is in line with Chen et al. ( 2005 ) who probe the relations between macroeconomic variables and hotel stock returns and find that the unemployment rate significantly (and negatively) illuminates the movement of hotel stock returns. GDP and EXG show negative impacts on SR. In sum, one probable reason for the insignificance of ICTs on SR might be due to the lag influence in Bayo-Moriones et al. ( 2013 ), whereby the effects of ICT implementation and all the measures of perceived performance are not always instant since the lag effects and lengths vary according to the type of ICT. In the following robustness checks section, we further evaluate the effect of the time-lag effect, geographic area, and non-global crisis sub-period.

Robustness checks

Equality of slope estimates across different quantiles (h4).

Table ​ Table6 6 displays the associated p -values for the equality of quantile slope coefficients across the various pairs of quantiles. The tests confirm the visual inspection in Table ​ Table6 6 regarding statistic tests of the equality of slope estimates across various quantiles, revealing that F -tests reject the null hypothesis of homogeneous coefficients at the 10% significance level for the MOB-AR, TEX-AR, and FSB-AR pairs of quantiles and indicating that the impacts of the MOB, TEX, and FSB explanatory variables vary across the different parts of the AR; whereas TEX-RV varies across the RV quantile distributions. The findings partially support H4 that the association between ICTs (i.e., MOB, TEX, and FSB) and tourism development saliently differs at diverse quantiles of the tourism development distribution.

Statistic tests of the equality of slope estimates across various quantiles

Note: † denotes P < 0.1 (two-tailed)

Effect of ICTs on subsequent international traveler arrivals

The findings in Table ​ Table3 3 do not report subjects regarding the lag effect and/or endogeneity. To avoid these problems and include the key variables into the equations, we advance AR by one following period to evade simultaneity in Table ​ Table7 7 regarding estimates of the MMQR-based international traveler arrivals for the t + 1 period’s model. This allows for the influence of any alteration in ICTs to be present in AR. Compared to the ICTs’ impact of RV in Tables ​ Tables3 3 and ​ and7 7 for concurrent as well as subsequent periods, we observe the following findings. (1) INT, SEC, and CCE significantly and positively impact AR for the subsequent period at the 90th, 75th, and 25th AR quantiles, respectively. This suggests that INT, SEC, and CCE have non-linear impacts on AR. (2) Consistent with Table ​ Table3, 3 , MOB has a notably positive impact at higher quantiles, but negative impacts at the lowest quantiles in Table ​ Table7, 7 , supporting H4 that the association between ICTs and tourism development differs at diverse quantiles of the development distribution. The subsequent impacts of MOB on AR are also asymmetric. (3) TEX shows no salient impact on AR of the current period, while it shows a saliently negative one in the following period. (4) The salient positive impact of FBS on AR in the current period turns negative in the subsequent period. Whether the disappearing positive impact of FBS from the current to following period is caused by the IT productivity paradox still needs further investigation. (5) The MMQR models of present and subsequent AR have fairly different signs and noteworthy findings. Therefore, we believe that as ICTs improve speedily, their impacts on tourism development should constantly be paid attention to. Additionally, our results show that ICTs have both simultaneous and lagged influences on AR.

Estimates of the MMQR-based international traveler arrivals of t + 1 period’s models

Notes: This table reports the estimation results of ICTs’ impacts on international tourism receipts of t + 1 period according to Eq.  1 . The rest of the notes are the same as in Table ​ Table2 2

Subsample of the non-global financial crisis period

As tourism contains discretionary income, it is considered vulnerable to economic uncertainty and volatility (Papatheodorou et al. 2010 ; Lee et al. 2020 ). Because international tourism statistics showed negative growth in 2008, it was anticipated that they would turn worse during 2009 (Papatheodorou et al. 2010 ). Therefore, we eliminate the influence of the 2008 global financial crisis and set 2006–2007 and 2010–2017 as non-global financial crisis sub-periods to perform MMQR equations in Table ​ Table8 8 in regard to the estimates of international traveler arrivals. The findings in Table ​ Table8 8 reveal similar remarkably positive influences of SEC, MOB, and FBS on AR as in Table ​ Table3. 3 . Therefore, compared to the full period findings and non-global financial crisis period, the impacts of SEC, MOB, and FBS on AR are quite consistent.

Estimates of the MMQR-based international traveler arrivals for non-global financial crisis period models

Notes: This table reports the estimation results of ICTs’ impacts on international tourism receipts according to Eq.  1 . Yearly data are used for the period 2006 to 2017. The rest of the notes are the same as in Table ​ Table3 3

Subsample of developing nations

Eugenio-Martín et al. (2004) discover that the nexus for the number of traveler arrivals and economic development occurs in developing nations, 4 but not in developed nations. We explore whether ICT factors have diverse influences on dependent variables using 79 developing nations as the subsample and present the empirical findings. 5 Consistent with Table ​ Table3, 3 , MOB, SEC, and FBS still show significantly positive impacts at several AR quantiles, and their positive impacts are more salient on developing countries’ AR. We also observe a notably positive influence of TEX on AR for developing countries’ lower AR quantile, while INT and CCE show no salient impact on AR, which is consistent with the findings in Table ​ Table3. 3 . Our findings also concur with Bhat and Shah ( 2014 ) that ICT deployment is especially important for emerging areas. The findings of the developing nation subgroup are similar to those of the full sample.

Subsample of European nations

According to International Tourism Highlights (2019) from the World Tourism Organization, Europe accounts for 50% of global international arrivals and receives almost 40% of international tourism revenues, followed by Asia and the Pacific. Because the relationship between tourism receipt and GDP differs with geographic regions (Çağlayan et al. 2012 ), we employ the biggest sample region of 38 European nations as a subgroup to assess the robustness of ICT factors in specific region samples in Table ​ Table9. 9 . Consistent with Table ​ Table3, 3 , SEC and MOB display considerably positive effects on AR, signifying the upgrade in influence of SEC and MOB on AR in European nations. However, FBS shows a negative impact on AR. Additionally, TEX and CCE show saliently negative impacts on AR in Table ​ Table9. 9 . INT presents asymmetric impacts on AR from positive in higher quantiles to negative in lower quantiles for European nations. The findings of the European nation subgroup are different from those of the entire sample, but are consistent with Çağlayan et al. ( 2012 ) in that the nexus of economic factor and tourism receipt presents different geographic area features. Thus, we further enlarge the findings of Çağlayan et al. ( 2012 ) to the ICT-tourism nexus. Except for the European nation results, we discover no other notable dissimilarities between the main findings and other robustness tests, indicating that ICTs non-linearly impact AR, RV, and SR.

Estimates of the MMQR-based international traveler arrivals of European nation models

Notes: This table reports the estimation results of ICTs’ impacts on international tourism receipts of European nations according to Eq.  1 . Yearly data are used for the period 2006 to 2017. The rest of the notes are the same as in Table ​ Table3 3

We condense the results in Table ​ Table12 12 summary of the empirical results. In short, there are saliently positive impacts of SEC, MOB, and FBS, supporting H1 in that ICTs have positive and substantial impacts on international traveler arrivals, especially for several specific AR quantiles. However, MOB (TEX) has negative impacts on SR at the 10th to 75th (75th) quantiles. Likewise, CCE (MOB) has significantly negative impacts on RV for all (25th–50th) quantiles on tourism receipts. Therefore, the findings support H2 (H3) in that ICTs have substantial impacts on international tourism receipts (travel and leisure sector returns) at specific quantiles.

Summary of the empirical results

Notes: ICT (information and communication technology), SR (travel and leisure sector returns), RV (international tourism receipts as % of total exports), and AR (number of international tourism arrivals). 10, 25, 50, 75, and 90 saliently represent in these quantiles. “–” denotes a negative impact; otherwise it is positive

We infer the negative impacts of CCE and MOB (TEX and MOB) on RV (SR) due to the IT productivity paradox, specifying the possibility of a time-lag effect, peer effect, and ICT commoditization. Moreover, Chen et al. (2012) indicate that economic variables like the discount rate, unemployment rate, and oil price significantly cause Japanese hotel stock returns. Compared with tourism receipts, tourism arrivals can be more directly and immediately used to estimate tourism development. Thus, H1-H3 are supported. We further observe that the influences of ICTs on AR, RV, and SR are salient at some of the quantiles, while not at others. For instance, FBS saliently impacts RV (SR) at the 90th (75th–90th) quantile(s), while TEX impacts RV (SR) at the 90th (75th) quantile. Therefore, H4 is supported, in that the association between ICTs and tourism development saliently differs at diverse quantiles of the tourism distribution.

Implication and discussion

Expanding from the prior studies of Andrianaivo and Kpodar ( 2011 ), Adeola and Evans ( 2020 ), Kumar and Kumar ( 2020 ), and Choudhary et al. ( 2020 ), our research explores more comprehensively ICTs and tourism variables, provides global evidence, and considers the different ICTs’ impacts across varying tourism quantiles. Our positive MOB finding is consistent with Choudhary et al. ( 2020 ) in that mobile cellular subscriptions have a positive effect on tourism development. Moreover, Rajan et al. ( 2016 ) address that an increase in the number of secure Internet servers results in an increase in the number of tourism arrivals, which matches our findings on salient and positive SEC impacts on AR. Therefore, taking ICTs into account helps tourism participants to realize the ICT determinants of AR. Our finding is consistent with Adeola and Evans ( 2020 ) who find when ICT and infrastructure increase in African nations that the level of traveler arrivals also increases. Our findings are also consistent with Bhat and Shah ( 2014 ), whereby ICT deployment is especially important for emerging areas. However, contradictive to the related literature that shows ICTs’ positive impacts, our findings reveal ICTs’ negative impacts, which are consistent with the saying of the IT productivity paradox.

Given the importance of ICTs on AR, RV, and SR, policymakers and/or travel and leisure managers need to consider how to build up ICT infrastructure and applications to develop tourism. Our results are vital to understanding tourism development under the sector’s greatly competitive markets globally. Several implications can be obtained from the empirical findings of this study. First, regarding to increase AR, secure Internet servers, mobile cellular subscriptions, and fixed broadband subscriptions have saliently positive impacts on international traveler arrivals, suggesting that nations and tourism participants that want to attract international travelers should improve these three ICTs. In other words, nations with less international arrivals are positively sensitive to the set-up of secure Internet servers, mobile cellular subscriptions, and fixed broadband subscriptions. The higher the levels of SEC, MOB, and FBS in the nation, the higher the number of AR. This finding infers that SEC, MOB, and FBS can enable tourism destination nations to increase the online presence (i.e., visibility on the Internet and collaboration with related sectors) necessary to be competitive in the global tourism market. This also advocates that as these three ICT infrastructures improve across the nations, the keener will be travelers to visit and realize the opportunities and endowments embedded in the destination country. On the contrary, mobile cellular subscriptions, the percentage of individuals using the Internet, high-technology exports, and communications as well as computer do no notably improve on traveler number.

Second, regarding the negative impacts of ICTs, MOB negatively affects SR (RV) at the 10th to 75th (25th–50th) quantiles, plus TEX (CCE) negatively impacts SR (RV) at the 75th (all) quantile(s). Interestingly, we also notice the positive INT and CCS effects (TEX and FBS effects) on SR (RV) at higher quantile, revealing the diverse features among ICT. Practically, nations with the highest tourism receipts (tourism stock returns) can increase high-technology exports and fixed broadband subscriptions (individual using Internet, communications as well as computer, and fixed broadband subscriptions) to further help raise tourism receipts (tourism stock returns). Nations with lower tourism receipts should not target to increase mobile cellular subscriptions, communication, and computer technologies. Thus, any ICT investment should consider their level of tourism development as well as the target they want to improve in order to avoid any downside risk. Moreover, secure Internet servers (individuals using the Internet) does not affect RV and SR (RV), implying the higher cost of implementing secure Internet servers and individuals using the Internet than revenues.

Third, our research findings allow academic research in related fields to consider the non-linear impacts of ICTs in tourism development. In other words, our findings identify that if one ignores the possibility that the ICTs-tourism nexus could be non-linear, then the results from a linear model could often cause bias due to using a false valuation method. Our evidence confirms that ICTs non-linearly influence AR, RV, and SR across different quantiles, implying countries establishing ICTs should consider different tourism development quantiles to apply different types of ICT.

Fourth, we address the asymmetric impacts of ICTs at different quantiles of tourism development. In other words, mobile cellular subscriptions have a negative impact from the lowest quantile and a positive impact at higher quantiles on the subsequent period’s AR. Additionally, the percentage of Internet usage has a negative impact from the lowest quantile and a positive impact at higher quantiles for European countries. This asymmetry has important implications for the growth strategies of developing tourism (Faber and Gaubert 2019 ) and whether the development of ICTs should be prioritized. Therefore, for nations at varying AR quantiles, different regions, different periods, and different ICTs have varying impacts on tourism development. ICTs can thus serve as tourism development determinants especially for the non-global financial period and for developing nations. Furthermore, instead of upgrading all kinds of ICTs, priority should be given to the tourism development quartile and then toward investing in specific ICTs. Our findings have important implications across different tourism factors’ quantiles for improving this industry, and this can help management strategies during both downside and upside conditions.

Fifth and finally, our research findings validate two theories. First, our findings of ICTs’ positive impacts show that countries with different tourism development levels should consider their diverse influence, which corresponds to the resource-based view theory of Wernerfelt ( 1995 ) in that a firm should consider its endowments to ensure that it always can competent with the best in whatever market it chooses to compete. For example, we suggest tourism managers and policy makers of countries with higher SR (RV) could improve their countries’ INT, CCE, and FBS (TEX and FBS) so as to raise their travel and leisure sector returns (tourism receipts). Our research expands the resource-based view from firm management to country tourism and ICT related fields. However, SEC, MOB, and FBS positively influence tourist arrivals at most of the quantiles, suggesting that tourism managers and policy makers can apply and improve more SEC, MOB, and FBS related technologies in order to increase international tourism arrivals.

Second, regarding our findings of ICTs’ negative impacts, MOB negatively affects SR (RV) at the 10th to 75th (25th–50th) quantiles, while TEX (CCE) negatively impacts SR (RV) at the 75th (all) quantile(s). Our research observes the condition of the IT productivity paradox in the tourism field due to some salient negative and insignificant impacts of ICTs in RV. The reasons for this negative impact might relate to the time-lag effect, peer effect and/or commoditization (i.e., ICTs are like railroads and electricity, as they are necessities and widely used). Our research findings allow academic research in related fields to consider the non-linear impacts of ICTs in tourism development. In other words, our findings identify that if one ignores the possibility that the ICTs-tourism nexus could be non-linear, then the results from a linear model could often cause bias due to using a false valuation method.

This research complements the literature on the relationships between destination nations’ levels of ICTs and tourism development by paying distinctive attention to the distributions of international traveler arrivals, international tourism receipts, and travel and leisure sector returns via yearly data of 118 nations for the period 2006–2017. The main goal is to probe international evidence regarding whether ICTs influence tourism development across the conditional distribution of tourism elements. For this purpose, we use a new quantile regression approach proposed by Machado and Silva ( 2019 ). Additionally, we consider that the correlations might vary during a non-global financial crisis period, by geographic area, and under different economic development states.

Our results suggest that secure Internet servers, mobile cellular subscriptions, and fixed broadband subscriptions have positive impacts on international traveler arrivals, while mobile cellular subscriptions and communication, computer notably and negatively affect tourism receipts for nations with the highest tourism receipts. Mobile cellular subscriptions and high-technology exports (Internet usage, communication, computer, and fixed broadband subscriptions) negatively (positively) impact travel and leisure sector returns at different return quantiles. Thus, our findings support that ICTs of the host nation positively determine traveler arrivals, tourism receipts, and sector returns.

The negative impacts of ICTs are consistent with the IT productivity paradox. The reason for the IT productivity paradox can be explained by the peer effect, time-lagging effect, and commoditization. Specifically, Gangopadhyay and Nilakantan ( 2021 ) explore the bank industry and address that although IT adoption can enhance firm productivity, resource use efficiency, and service quality through strengthening organizational capabilities, a proper assessment of the costs and benefits of any new technology may be difficult for potential users, because IT productivity paradox has previously overlooked the influence of peer firms. Hwang et al. ( 2015 ) find that computer and Internet usage do not relate to enhancing a firm’s competitive advantage, since they are now commoditized, much like railroads and electricity (Carr 2003 ). In other words, computers and Internet usage are not influenced by either product/service performance or business process performance (Hwang et al. 2015 ). Toy ( 2021 ) addresses in the short run that artificial intelligence implementation does not appear to affect overall productivity statistics due to the time-lag explanation presented by Brynjolffson et al. (2019).

There is salient evidence showing how ICTs asymmetrically and non-linearly influence tourism development across different quantiles. Further test results disclose that the relationships between ICTs and tourism development are robust after considering non-global financial sub-periods, endogeneity problems, and economic development conditions. However, the positive impact of fixed broadband subscriptions is insignificant for the European nation group, implying the existence of a geographic region difference in the ICTs-tourism nexus.

We also study whether the impacts of macroeconomic factors correlate with traveler arrivals, tourism receipts, and travel and leisure sector returns. We discover that GDP, real exchange rate, inflation, and unemployment are considerably associated with different quantiles of traveler arrivals, tourism receipts, and sector returns. The GDP per capita growth rate notably and positive correlates with traveler arrivals, while negatively correlates with tourism receipts and sector returns. Unemployment (inflation) is asymmetric and noticeable related with travel and leisure sector returns (traveler arrivals). The results are consistent with the existing literature that there is an asymmetric link between economic factors and tourism (Meo et al. 2018 ). Baur and McDermott (2010) define safe-haven assets as those can help investors build a portfolio that mitigates any downside market risk. Interestingly, we find salient positive impacts of the global financial crisis on sector returns at intermediate and higher return quantiles, suggesting countries with intermediate and higher travel and leisure sector returns can be a safe-haven for assets during the global financial crisis.

Identifying the ICTs and tourism nexus has been a crucial subject in the tourism arena, yet undeniably we merely probe at their association among six ICTs. These are three limitations of this study. First, because we focus the discussion on six kinds of ICTs, there are other new ICT issues we have omitted, such as artificial intelligence (AI) and robotics, which could enhance our understanding of advanced technology’s effects on tourism. Second, the COVID-19 pandemic has resulted in serious ongoing challenges to the travel and tourism sector, but we do not consider the pandemic’s impacts on this sector. It would be interesting for studies to examine the possible benefits of new ICTs on the travel and tourism sector during serous pandemic periods. Third, this study mainly covers the non-linear effects of ICT on tourism development across different quantiles, and omits the causal relationships between ICT and tourism development. We leave these three topics for future endeavors.

Acknowledgements

The authors are grateful for the insightful comments and suggestions received from the Editor-in-chief Dr. Zheng Xiang and three anonymous referees on an earlier of this paper. This work was supported by National Taichung University of Science and Technology in Taiwan.

See Tables ​ Tables10, 10 , ​ ,11, 11 , ​ ,12; 12 ; Fig.  4 .

Chien-Chiang Lee is grateful to the Social Science Foundation of Jiangxi Province of China for financial support through Grant No: 21JL02.

Declarations

The authors declare no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

1 World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially recognized international sources. It presents the most current and accurate global development data available and includes national, regional, and global estimates. The ICTs and tourism related literature use WDI data, such as Kumar and Kumar ( 2012 ), Kumar and Kumar ( 2020 ), Al-Mulali et al. ( 2020 ), and Choudhary et al. ( 2020 ).

2 Regarding the defined period of the global financial crisis, we use information on system banking crises to establish the crisis year (Allen et al., 2012 ; Bretschger et al., 2012 ; Laeven and Valencia, 2012 ; Chen et al., 2019 ), and the starting years for the banking crises are as follows: the crisis in the U.S. and U.K. commenced in 2007, started in 2008 for all other countries, and followed through in 2009. The crisis data are given by a simple binary variable that equals one if country i had the crisis start in years 2008 and 2009 and zero otherwise.

3 Compared to time series data, the advantages of panel data include an increased amount of observations and corresponding variations and a reduction of noise caused by individual time series regression (Westerlund et al., 2015 ).

4 Data source: Table C developing economies by region of World Economic Situation and Prospects from the United Nations. We present this data source from: 2014wesp_country_classification.pdf.

5 Due to space limitation and a reviewer’s suggestion, we omit the table of the MMQR-based international traveler arrivals for developing nations.

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Contributor Information

Chien-Chiang Lee, Email: moc.liamg@1016eelcc .

Mei-Ping Chen, Email: wt.ude.ctun@gnipiem .

Wenmin Wu, Email: moc.qq@7415004152 .

Wenwu Xing, Email: [email protected] .

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  • Published: 24 October 2018

Integration of ICT and tourism for improved promotion of tourist attractions in Ethiopia

  • Mekonnen Wagaw   ORCID: orcid.org/0000-0001-9367-7528 1 &
  • Feven Mulugeta 1  

Applied Informatics volume  5 , Article number:  6 ( 2018 ) Cite this article

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Information and communication technology (ICT) is revolutionizing the lives of people and operations of organizations. ICT has become a major driver of touristic sectors to effectively promote tourist attractions and services. As a result, many countries have succeeded in using ICTs and more precisely the internet to develop their tourism industries. However, the use of ICT in promoting tourist attractions in Ethiopia is still low. Hence, this survey research empirically studied the factors affecting the integration of ICT and tourism. The findings show that social influence, perceived usefulness, perceived ease of use, cost effectiveness, competitive advantage, and facilitating conditions such as experience, ICT resources and skill significantly affect behavioral intention to use ICT in the tourism sector of Ethiopia.

Information and communication technology (ICT) is revolutionizing the lives of people and operations of business organizations. Business organizations use ICT to process, store, disseminate, and promote their products and services globally. Beginning from the introduction of the internet, people have been accessing any information at anytime from anywhere. Hence, it is becoming inevitable to live without the aid of ICT.

Being the world’s largest economic endeavor, tourism is enhancing economies of countries. It accounts for 10% of the global gross domestic product (GDP) and 8.7% of the world’s jobs (Meriague 2014 ). Furthermore, due to globalization, strong tourism sector is considered to be a sign of a country’s social development, evolution, and progression (Meriague 2014 ).

Since tourism is one of the major sectors in today’s world, many countries are competing to attract tourists through all means of communication, and such communication has become a major driver of touristic sectors all over the world. The role of communication is to inform prospective tourists and influence their choices regarding touristic destinations and the type of touristic products they purchase.

Many countries have succeeded in using ICTs and more precisely the internet to develop their tourism industries. For example, Malaysia and Australia have been very successful in attracting many tourists through these means (Mohsin 2005 ). On the other hand, countries such as Iran have not been able to increase their number of international visitors, largely due to a lack of ICTs and internet development (Salavati and Hashim 2015 ).

Although Ethiopia possesses numerous natural, religious, historical, and cultural tourist attractions, utilization of tourism as a sector of the country’s economy goes five decades back. Considering the economic contribution of tourism to Ethiopia, the first tourism office was established in 1962 during the imperial regime (Ali 2017 ). During the military regime, the sector’s contribution reduced drastically but beginning from the 1990s, the number of tourists increased. Among Ethiopia’s fascinating tourist attractions, nine of them are UNESCO world heritage sites (Ali 2017 ). However, the tourism sector’s economic contribution and its potential are incomparable. According to research findings, unless a country promotes its tourist attractions to the rest of the world, it is impossible to increase the number of visitors. Hence, the integration of well-crafted ICT solutions is needed, and since we are living in a digitized world, it is necessary for the tourism industry to rely on ICTs and especially the internet as tool of international communication.

Problem statement

Since tourism is one of the major sectors in today’s world, many countries are competing to attract tourists through all means of communication and such communication has become a major driver of touristic sectors all over the world. The role of communication is to inform prospective tourists and influence their choices regarding touristic destinations and the type of touristic products they purchase.

To attract prospective tourists in this digitized world, modern ICT strategies are needed, and it is necessary for the tourism industry to rely on ICTs and especially the internet as tools of international communication.

Ethiopia has been attracting a huge number of foreign tourists visiting a variety of magnificent natural, cultural, historical, and religious heritages found in the country. However, the potential of those tourist attractions and number of visitors are incomparable. Moreover, provision of sufficient information to tourists and promotion using modern ICT services is very low. As a result of this, the sector’s contribution to the nation’s GDP is insignificant. The sector’s contribution to the nation’s GDP was 4.1% in 2015 (WTTC 2016 ).

Hence, this research has the objective of investigating the integration of ICT in the tourism sector for improved promotion of the Ethiopian tourist attractions so as to enhance the sector’s contribution to the country’s GDP. To empirically measure the factors affecting the integration of ICT and tourism, this research work adopted the Unified Technology Acceptance Theory (UTAUT) developed by Venkatesh et al. in 2003 and two additional constructs were included from related literature.

To investigate the integration of ICT in the Ethiopian tourism sector for improved promotion of the Ethiopian tourist attractions so as to enhance the sector’s contribution to the country’s development.

This research work empirically investigated sample tourism organizations to answer the following research questions: (1) what is the current status of the integration of ICT in the Ethiopian tourism sector? (2) What are the factors affecting the integration of ICT and tourism in the Ethiopian context? and (3) To what extent do these factors affect the integration of ICT and tourism in Ethiopia?

Theoretical framework

The fundamental theoretical framework of this research arises from a body of research in integration of ICT and tourism. With the objective of identifying determinants that affect integration of ICT and tourism for improved promotion of tourist attractions in Ethiopia, highly related and relevant literature on the issue are reviewed.

There are many theories on technology acceptance. For instance, Theory of Reasoned Action (TRA) developed by Fishbein and Ajzen ( 1975 ) predicted that subjective norms and attitudes determine our behavioral intentions. Then, in 1989, Davis et al. came up with Technology Acceptance Model (TAM). As stated by this theory, intention to use a technology is determined by individual’s perceived usefulness and perceived ease of use and intention to use determines actual use of a technology. Next, diffusion of innovation (DOI) was created by (Rogers 1995 ). This theory states that “Individuals are seen as possessing different degrees of willingness to adopt innovations and thus it is generally observed that the portion of the population adopting an innovation is approximately normally distributed over time. Breaking this normal distribution into segments leads to the segregation of individuals into the following five categories of individual innovativeness (from earliest to latest adopters): innovators, early adopters, early majority, late majority, and laggards” (Rogers 1995 ). Besides, Task Technology Fit Theory (TTF) was developed by Goodhue and Thompson in 1995 . According to this theory, if information technology is capable to match with the tasks of users, IT is more likely to have positive impact on individual performance. Moreover, the Unified Technology Acceptance Theory (UTAUT) was developed by Venkatesh et al. in 2003. This theory states that users’ technology acceptance and subsequent usage behavior is determined by performance expectancy, effort expectancy, social influence, and facilitating conditions. According to Venkatesh et al., this theory used gender, experience, age and voluntariness of use as moderators for intention of use and behavior.

On the basis of UTAUT, the researchers of this study included two more constructs to increase the study’s scope. Hence, this research hypothesized that integration of ICT and tourism in promoting tourist attractions is affected by perceived usefulness, social influence, perceived ease of use, cost effectiveness, competitive advantage, and facilitating conditions, see Table  1 .

Based on the theoretical propositions of UTAUT and related relevant literature, this study proposed 11 hypotheses with regard to the integration of ICT and tourism for improved promotion of tourist attractions.

This research work is proposed to measure the following 11 hypotheses so as address research questions and achieve the stated objective. Table  2 summarizes these hypotheses.

Study design

In this empirical study, organizations in Ethiopia working at tourism were surveyed in consideration of positivist philosophical assumptions.

Positivist epistemology assumes that knowledge is measurable and it is objectively described (Heyman 2009 ). Thus, this survey research used quantitative approach throughout the data collection, analysis, and interpretation phases.

The primary data collection instrument was standardized questionnaire which constituted structured questions for each of the constructs using a 5-Likert scale ranging from 1 “strongly disagree” to 5 “strongly agree”. From the distributed 453 questionnaires, 429 were filled and returned back, yielding a response rate of 94.6%.

The research participants were selected based on stratified sampling technique. This is because the tourism sector encompasses varied institutes such as national and regional tourism and culture organizations, tour operators, travel agents, and destination marketing organizations. The criteria for stratification were (1) type of tourism enterprise, (2) service type, (3) experience, and (4) location.

The research population included all tour and travel operators in the country, and federal and regional tourism and culture offices were included. From this population, a sample of 429 samples was studies. The data analysis process started immediately after measuring the validity and reliability of the collected data. Since this research work deployed quantitative research, deductive data analysis method was used. The theory-based quantitative data were analyzed using the SPSS statistical software.

The data were collected from research participants after getting informed consents from study participants using an attachment on the research questionnaire. Their privacy and the information they provide were kept confidential. Most of the study participants were male and between the age of 35 and 45 whom account 73% and 33%, respectively (see Table  3 ). About 68% of the study participants were selected from privately owned tourism organizations. Most of these organizations have spent between 6 and 10 years (34%) providing tour and travel services which accounted 32% (Fig.  1 ).

figure 1

Proposed research model

The analyzed data showed that a higher number of both computer and internet skilled workers were found in private touristic service providers than governmental providers (see Fig.  2 ). Most these workers have basic computer and internet skills than intermediate and advance skills in private and governmental touristic sectors. Study participants in private touristic organizations had better computer and internet skills than their counter parts.

figure 2

Basic Computer and Internet Skills (n = 429)

Only 16% of the study participants working in touristic organizations reported that they had know-how of advanced computer and internet use skills. This implies that most of the employs do not know the intermediate and advanced services of their computers and the internet.

According to the respondents’ responses, touristic organizations use some promotional mechanisms to promote tourist attractions and touristic services (see Fig.  3 ). They use magazines, newspapers, flyers, websites, social media, and television and radio. However, flyer (31%) and magazine (26%) are the dominant tools. Although websites, social media, and television/radio have higher capability to be accessed by higher number of tourists globally, the percentage of these tools being used by participants low. According to the analysis result, website users are 23%, while social media and television/radio users are 8% and 2%, respectively.

figure 3

Promotional Mechanisms (n = 429)

Reliability and validity of the model

Cronbach Alpha Coefficient was used for measuring the validity of the study. As per the Psychometric Theory (Nunnally and Bernstein 1978 ), the acceptable Cronbach Alpha value has to be greater than 0.7. The analyzed data of this study revealed that the seven constructs had above 0.7 (see Table  4 ). Similarly, although an acceptable composite reliability has to exceed 0.7, the result of this study showed that the seven constructs scored above 0.7. Furthermore, Average Variance Extracted (AVE) was used to evaluate convergent validity. Assuming that 50 or more of the variance of the indicators ought to be accounted, a study’s AVE result has to exceed 0.5 (Fornell and Larcker 1981 ). All constructs in this study resulted in AVE above 0.5.

The Pearson Product-momentum correlation coefficient ( r ) was used to test the hypotheses of this study. According to Kothari ( 2004 ), in case of measuring association between variables, Karl Pearson’s coefficient of correlation is the widely used measure. In correlation analysis, if the correlation coefficient exceeds 0.5 ( r  > 0.5), it shows significant relationship between variables.

To measure factors affecting ICT integration in the Ethiopian tourism, this study empirically analyzed eleven hypotheses. Subsequently, the analysis result showed that positive relationship between the variables at a significance level of 0.05 (see Table  5 ).

The first hypothesis (H1) states that there would be a significant positive association between social influence (SI) and behavioral intention (BI) to use ICT in the tourism sector. The correlation coefficient between these two variables is r  = 0.80 at p  < 0.05, which shows strong positive correlation. The second hypothesis (H2a) states that there would be a significant positive association between perceived usefulness (PU) and behavioral intention (BI) to use ICT in the tourism sector. The correlation coefficient between these two variables is r  = 0.84 at p  < 0.05, which shows strong positive correlation. The third hypothesis (H2b) states that there would be a significant positive association between perceived usefulness (PU) and social influence (SI) to use ICT in the tourism sector. The correlation coefficient between these two variables is r  = 0.85 at p  < 0.05, which shows strong positive correlation. The fourth hypothesis (H3) states that there would be a significant positive association between perceived ease of use (PEU) and behavioral intention (BI) to use ICT in the tourism sector. The correlation coefficient between these two variables is r  = 0.79 at p  < 0.05, which shows strong positive correlation. The fifth hypothesis (H4a) states that there would be a significant positive association between cost effectiveness (CE) and behavioral intention (BI) to use ICT in the tourism sector. The correlation coefficient between these two variables is r  = 0.78 at p  < 0.05, which shows strong positive correlation. The sixth hypothesis (H4b) states that there would be a significant positive association between cost effectiveness (CE) and perceived usefulness (PU) to use ICT in the tourism sector. The correlation coefficient between these two variables is r  = 0.83 at p  < 0.05, which shows strong positive correlation. The seventh hypothesis (H5a) states that there would be a significant positive association between competitive advantage (CA) and behavioral intention (BI) to use ICT in the tourism sector. The correlation coefficient between these two variables is r  = 0.75 at p  < 0.05, which shows strong positive correlation. The eight hypothesis (H5b) states that there would be a significant positive association between competitive advantage (CA) and cost effectiveness (CE) to use ICT in the tourism sector. The correlation coefficient between these two variables is r  = 0.66 at p  < 0.05, which shows moderate positive correlation. The ninth hypothesis (H5c) states that there would be a significant positive association between competitive advantage (CA) and perceived usefulness (PU) to use ICT in the tourism sector. The correlation coefficient between these two variables is r  = 0.68 at p  < 0.05, which shows moderate positive correlation. The tenth hypothesis (H5d) states that there would be a significant positive association between competitive advantage (CA) and social influence (SI) to use ICT in the tourism sector. The correlation coefficient between these two variables is r  = 0.62 at p  < 0.05, which shows moderate positive correlation. The ninth hypothesis (H6) states that there would be a significant positive association between facilitating conditions (FC) and behavioral intention (BI) to use ICT in the tourism sector. The correlation coefficient between these two variables is r  = 0.82 at p  < 0.05, which shows strong positive correlation.

Furthermore, using multiple regression analysis between the dependent and independent variables, the standardized weights of predictors of behavioral intention (BI) were determined (see Eq.  1 ):

where Y  = variable to be predicted or dependent variable (DV), X  = variable that predicts Y , α  = intercept, β  = coefficient of X , ɛ  = regression residual (error).

The regression analysis revealed that, see Table  6 , standardized weights of the independent variables such as social influence (SI), perceived usefulness (PU), perceived ease of use (PEU), cost effectiveness (CE), competitive advantage (CA) and facilitating conditions (FC), and the dependent variable behavioral intention (BI):

According to McKelvey and Zavoina ( 1975 ), the coefficient of determination ( R 2 ) determines the proportion of variance in the dependent variable which is predictable from the independent variable. High coefficient of determination shows greater explanatory power of a regression model. Accordingly, the coefficient of determination of behavioral intention (BI) to use ICT in Ethiopian tourism is 0.844, which means that the regression model explained 84.4% of the variance in BI. Thus, this high value of R 2 depicts that the regression model is very good and the model statistically significant at F  = 381.1, confidence interval 95%, and p  < 0.001. Figure  4 shows the standardized coefficients or determination weights of the independent variables (SI, PU, PEU, CE, CA, and FC) on the dependent variable (BI).

figure 4

Coefficient of regression analysis

The empirical demonstration of the proposed model enabled to identify predictors that determine intention to use ICT in tourism. Social influence has significant impact on the study participants’ behavioral intention to use ICT in tourism. As social influence to use ICT in tourism increases, the behavioral intention to use it also increases. There is also strong positive association between perceived usefulness and behavioral intention to use ICT in the tourism. This shows that users are more interested to integrate ICT in their tourism activities when they think that such technologies will be helpful. The finding also showed significant positive relationship between perceived ease of use and behavioral intention to use ICT in tourism. That means tourism organizations are motivated to use ICTs when such technologies are easy to use letting them to have more time for other activities. There was significant association between cost effectiveness and behavioral intention to use ICT in tourism. Cost-effective ICT facilities are more preferable by tourism organizations. Moreover, there is significant relationship between competitive advantage and behavioral intention to use ICT in tourism. This suggests that users’ behavioral intention to use ICT in tourism increases when they believe that the technology will improve their competitive advantages over their counter parts. Besides, the research illustrated significant association between facilitating conditions and behavioral intention to use ICT in tourism. Tourism organizations’ behavioral intention to use ICT increases when facilitating conditions such as users’ experience, resources, and background ICT skill increases.

Implications and conclusions

Using an extended Unified Technology Acceptance Theory (UTAUT), this empirical research found out factors affecting integration of ICT in tourism for promoting Ethiopian tourist attractions. Consequently, the study addressed the three research questions raised in the beginning of the research work. The first question was “What is the current status of the integration of ICT in the Ethiopian tourism sector?”. Although ICT plays significant role in promoting tourist attraction, particularly in the developed world and some developing countries, this research result shows that the integration of ICT in the tourism sector of Ethiopia is low. This shows that major improvements in the integration of ICT in promotion of tourist attractions in Ethiopia is required by the tourism stakeholders such as national and regional tourism and culture organizations, tour operators, travel agents, and destination marketing organizations. The second research questions states that “What are the factors affecting the integration of ICT and tourism in the Ethiopian context?”. The result showed that social influence, perceived usefulness, perceived ease of use, competitive advantage, cost effectiveness, and facilitating conditions were significantly associated with integration of ICT in tourism in Ethiopia. This implies that the improved model could be applicable to other developing nations that have similar settings or context with Ethiopia. The last research question was “To what extent do these factors affect the integration of ICT and tourism in Ethiopia?”. According to the analysis result, social influence, perceived usefulness, perceived ease of use, cost effectiveness, competitive advantage and facilitating conditions significant predictors of organizations perceived behavioral intention to use ICT in the tourism sector for promoting Ethiopian tourist attractions. Take a look at the correlation coefficients from Table  5 .

Limitations

This empirical study was carried out using data gathered from tourism organizations in Ethiopia. However, it would be better if data from other countries were included.

Future works

This improved model is a foundation for future research works on acceptance, adoption, or assimilation of ICT in tourism organizations particularly in the settings of developing nations. Future study could also focus on the technology or ICT adoption strategies of tourism organizations. Moreover, to measure the long-term effect of ICT adoption in the tourism sector, longitudinal study could be required.

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Authors’ contributions

The corresponding author, MW, worked from initiation to close out of the research work. The co-author, FM, also included her valuable contribution to this research particularly in reviewing related literature, data gathering and encoding activities.

Acknowledgements

Our first respected gratitude goes to those research participants who devoted their valuable time and effort and contributed their valuable experiences to this study. Second, our gratitude goes to Bahir Dar University for its financial support and ambitious plan and encouragement of researchers to engage in research. Finally, we would like to dedicate this research work to our families for their love, encouragement, patience, and unconditional support.

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We confirm that this research is an original work and there is no any individual or organization having competing interest on this study.

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Wagaw, M., Mulugeta, F. Integration of ICT and tourism for improved promotion of tourist attractions in Ethiopia. Appl Inform 5 , 6 (2018). https://doi.org/10.1186/s40535-018-0053-x

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Information technology (IT) has become a strategic weapon on tourism products’ identification, presentation, dissemination and getting a sustainable competitive advantage. Tourism management is the most important candidate for using IT with the need for gathering information in large quantities and diffusion of tourism management. The heterogeneous nature of these businesses means that information-communication Technologies’ uses change from sector to sector and from management to management in the tourism sector. The development of IT has created new application areas for tourism industry managers especially in efficient cooperation and provided tools for real globalization, IT is unexpectedly part of tourism management because of information creation processing and transmission which are important in daily activities. Therefore, both rapid development of tourism demand and tourism supply have become a compulsory partner of IT; and for this reason, IT plays an important role in the tourism marketing, distribution, promotion, and coordination. Due to this importance; the impact of IT on tourism sector is valued to be investigated. This chapter stresses that IT’s uses play an efficient role in choosing the management on behalf of the consumer. Within this context, this chapter composes of the information society; IT development and tourism; the usage of IT on travel, hospitality, tourism sector, its challenges, and advantages. This chapter mostly emphasizes on these subjects that will be examined deeply.

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Georgia Nikoli is a Phd student of the Digital Health Applications and Health Economics Analytics Laboratory - DigiTHEA Lab ( http://digithea.uop.gr ) at the Department of Economics at the University of Peloponnese in Greece. She did her undergraduate studies at the Business Administration with Specialization in Human resources management at Piraeus University of Applied Sciences (Greece) and received her postgraduate degree in Tourism Management at the Hellenic Open University of Greece.

Athina Lazakidou currently works at the Department of Economics at the University of Peloponnese in Greece as an Associate Professor and Director of the DigiTHEA Lab ( http://digithea.uop.gr ). She did her undergraduate studies at the Athens University of Economics and Business (Greece) and received her BSc in Computer Science in 1996. In 2000, she received her Ph.D. in Medical Informatics from the Department of Medical Informatics at the Free University of Berlin in Germany. 

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The influences of Information Communication Technology (ICT)

The advancement of ICT influences the growth of the travel and tourism industry in every kind of business. First, multimedia is a way to promote the travel industry, such as Instagram, Facebook, and Tripadviser. Second, ICT can create photo and graphic designs which tourism suppliers need to advertise their products. It has Canva, Adobe, and Davinci. Third, it provides GPS which tourists use to find the tourist destination. Mostly, they use Google Maps. Fourth, ICT contributes real-time crowd control in tourist attractions such as alert systems and emergency notification. Last but not least, it developed to track visitor movement by using GPS and smartphone. It is important for tourism suppliers, especially during this COVID-19 pandemic.

ict impact on tourism industry

Pros and cons of ICT in tourism sector

ict impact on tourism industry

The advantages of using ICT in the tourism sector. First, it was used as E-commerce to promote tourism through online platforms. Second, in the hotel industry, it was used to manage employee’s productivity and hotel’s revenue. Third, in the tourism industry over the world use ICT for the business transaction by trading and providing information to consumers about the product. Last, ICT helps tourists who have not experienced traveling by providing the information, recommendation and booking information that is related with tourist destinations on online applications such as Booking.com, Agoda, and Google services.

The disadvantages of using ICT in the tourism sector. First, not all the online information is true and efficient. Second, the fake information goes viral very fast through the internet and it will affect the business. Third, not every firm in the tourism business has funds to support the technology device. Fourth, if we implement the high end technology into the natural destination, it will affect natural resources and it seems not to be a natural destination anymore. Last but not least, if everything is replaced with technology, it may affect the number of employees. As we can see some hotel industries in the developed countries are replacing people with robotech.

The strategies to limit the risk by Using ICT

There are a few strategies which can be implemented to limit risk and disadvantages of using ICT in the tourism industry. Firstly, provide what the firm advertises to the consumer without fail, so when tourists meet their expectations they will not share the fake information about your business. Secondly, tourism suppliers have to think about how to implement the technology properly into their company in order to prevent money wasted without getting any profit back. Lastly, limited technology devices in some tourist destinations because not all tourists are satisfied with using technology to guide them. For example when they visit a history place they need a tour guide to describe what has happened in the past, they want to feel naturally, not just listening to the recording devices.

Information Communication Technology can aid the tourism sector in facing the COVID-19 pandemic for 2 reasons. First, social media play an important role to share information which relates to the pandemic very fast and recently update data to everyone to be aware of the virus. Second, due to the internet service provider being everywhere along with the COVID-19 application, it can track people movement and alert them about the safety and danger of where they should go or not.

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“Technology Application in Tourism Fairs, Festivals and Events in Asia”

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ICT impact on tourism industry

Profile image of Maria Elena Aramendia-Muneta

2013, International Journal of Management Cases

The goal of this paper is to analyze the effects of ICT on firms’ competitiveness, as well as on their level of innovation, productivity and on the market share depending on the tourism area: Accommodation, Gastronomy and Travel Agencies. On the whole, it has been proved that the use of diverse ICTs has little effect on the level of competition as well as on increasing productivity, while in general, they have a positive effect on increasing the market share of the firms.

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Mergers and Acquisitions, M & As has become a trend for the growth of Mexican companies. Although the diverse, all companies seeking the ultimate goal of growth of the firm. Through the job description in the three largest companies in Mexico and the results we achieved demonstrate the profitability of this kind of strategic alliances and detected elements which may be useful for growing companies that are selecting the appropriate strategy to their resources and goals. This article aims to describe the execution of mergers and acquisitions as a strategy for Mexican companies best positioned within the major world rankings to achieve growth. The corporate strategy is critical to achieving the higher rank and must be set out clearly and according to their needs.

José G. Vargas-Hernández

The corporate strategy is critical to achieving the goals of the firm and must be set out clearly and according to their needs. M & As have become a trend for the growth of Mexican companies, despite having diverse motivations through the description of their implementations in the three largest Mexican firms and the results we achieved demonstrate the effectiveness of this type strategic alliances and other useful items detected less consolidated companies.

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Experiences (i.e. interactions with time, space, people, products and services) are the essence of cultural heritage (CH) - a cornerstone of every civilized society. As an indicative example, 77% of the European Union citizens consider cultural heritage an important driver of their everyday lives (Eurostat, 2011). In turn, CH consumers share their experiences (both positive and negative) through social media platforms, thus influencing other CH consumers’ decisions and affecting supply-demand curves. This becomes even more important for CH providers when considering the profile of CH consumers: they are skilled individuals who ride en masse the wave of self-designing collaborative consumption at heritage places (Harvey and Lorenzen, 2006; Chan and Goldthorpe, 2007; Lizardo and Skiles, 2008). At the same time, the strongly subsidized CH institutions (e.g. museums) are very slow in developing value propositions and business models that can satisfy the new demands, expectations and lifestyles of CH consumers (Caserta and Russo, 2002; Council of Europe, 2009). Bridging this gap is not an easy fix. It will require transformation of the CH supply side along three axes, corresponding to three major challenges: a) CH supply-side fragmentation; b) cultural communication; and c) value innovation (Papathanasiou-Zuhrt, 2011; Dümcke, 2012; Dümcke and Gnedofski, 2013; Lagos et al, 2005). In this article, we provide an analysis of these challenges and discuss their transformative potential for boosting growth in the CH sector. We then present different pragmatic approaches in addressing different combinations of these challenges, based on relevant international research and development projects that we engaged in. Finally, we showcase our research road path and future activities, for further investigating the aforementioned growth challenges.

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Many natural and cultural heritage resources that are supposed to create revenue generation and employment opportunity through tourism are nonchalantly abandoned without any developmental attention given to them. This has really deprived the community and the nation as a whole the economic growth, and recognition they deserve. To mitigate this problem, presented in this paper is the impact of Information and Communications Technology (ICT) in enhancing the management of the natural and cultural heritage resources in Idanre Hills and its environs. A detail assessment of the level of development of the hills’ cultural and natural features was carried out based on the four components of tourism, namely: (1) Attraction, (2) accessibility, (3) accommodation, and (4) amenities. A conceptual e-tourism designed for the hills has the basic component of e-commerce. The stratified random sampling technique was used to collect the primary data, with the assistance of a semi-structured questionnaire. A 4-point Likert-type scale was employed in the questionnaire to illustrate the impacts of ICT in tourism. Analysis of variance perception of respondents about the impact of ICT on tourism business showed generalized additive model Group Arithmetic Mean (GAM) of 167.4; this simply means that the arithmetic means of respondents that accepted the application of ICT were more than the arithmetic means of respondents that rejected the application.

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Tourism Beast

Role of ICT in Tourism

Role of ICT in Tourism: The application of ICTs is an appropriate prospect for improvising the tourism industry from an area perspective. Towards the event of destinations economies technology driven systems are very crucial. Precisely, ICTs have the potential to upsurge destination revenue for supporting the economic and social development.

Role of ICT in Tourism

Perhaps, evolving and strengthening the local tourism and tourism oriented activities with application driven mechanisms can offshoot the local entrepreneurship and connected activities. Fundamentally, ICTs consent destinations to progress and expand the web presence with better and global visibility and participation through Internet market. To build efficacy and destination competency, it’s very essential to travel beyond offline connectivity involving collaboration, clustering and inter-sect oral associations among local public and personal tourism and other tourism-related actors. In fact, it’s imperative and highly required to compete in today’s global tourism market. More precisely the advantageous effects of ICTs are to be found within the prospects to condense the traditional drawbacks of SMEs and native operators.

Primarily, ICTs deliver direct, cheap and operative access to the particular and potential customers. along side , ICTs make profitable to use various distribution channels and target niche markets. Beforehand it had been almost difficult for SMEs to spread, attend and even to be recognized. Nonetheless, for this to happen a standard improvement of ICT infrastructures isn’t adequate.

Even an appropriate benefaction of e-skills, as promoted by international organizations is by now an important factor. Towards, every new technology, the overview ICTs cannot create the assured paybacks if it’s not supplemented by balancing modifications within the current organizational settings and structures to right fit them with its typical features. Developmental paybacks of ICTs, and destination’s management activities must be relooked and newfangled ICT-enabled organizational representations are to be developed. However, to usher in change is never easy, and during a disjointed, SMEsdriven business such tourism, it’d be even tougher . Hence what must be re-examined is how traditional destination management structures are often redefined to influence ICTs and the way officious tools, resulting into the new representations and practices are often spread within tourism destinations.

Examining the contextual on the approaching benefits of ICTs towards destination management, one major aspect might be examined because the new role of the organizations responsible of the management of destinations – mentioned as Destination Management Organizations (DMOs) and grants the most features of an ICT-enabled system for the management of destinations denoted as “cybernetic incoming agency”.

At that time critical outlook on the most barriers and pertinent international policy directions connected to the diffusion strategy of integrating e-skills creation, ICT development and native interacting and cooperation projects might be implemented. it’s vital to craft measures for the sensitization tools and initiatives wont to activate ICTs acceptance in local organizations and firms.

Particularly, a radical explanation of the e-business methodology created for diffusion of ICT awareness and therefore the scholastic approach accomplished to supply the essential competencies to endure the agreement and usage of such technologies are going to be presented. ICT responsiveness and competences are often well-thought-out, because it may look very complicated for the appliance of more multifaceted and beneficial ICT enabled models like the “cybernetic incoming agency”. Theoretically watching it identifies a probable progression within the management of destinations prompted by ICTs and a complicated organizational model within the current scenario.

It also deals with wider insights in the way to device this model, not only as a group of guidelines, but with facilitation of a longtime step-by-step approach and interrelated tools developed because the results of continuing field investigations. Correspondingly, a special standpoint within the procedure of technologies, not merely as a tool, but as a framework for erudition and therefore the base of advanced learning methods aimed toward the formation of latest tourism professionals is supported and explained.

Background for the ICT Enabled Systems in commission Sector with DMO

ICTs are in varying archetypes, knowingly the techniques during which traditional destination management activities in terms of designing , Development, Marketing, Management, Coordination and Monitoring of destinations are being conceded out. as an example , within the earlier times, few DMOs were well-found and self-possessed and capable combat marketing research .

Indeed, these initiatives were quite costly consultancies. Nowadays with e-mail or web-based questionnaires the entire process is relaxed and cheap to hold out consumer analysis. Perhaps, with internet sites , it’s promising and can quantify the efficiency of a marketing operation and would examine virtually all the opposite destination management activities.

Therefore, ICTs can create variety of advantages for destination management activities with regard to; dropping costs, reducing the necessity to print brochures, less time for undertaking activities, and at an equivalent time increasing their effectiveness Additionally, ICTs can enhance new-fangled sources of incomes to fund the activities of DMOs like selling of services like; training, design and development of internet sites , consultancy and assistance for e-marketing activities and applications and technologies developed.

The discussed benefits spell out as ICTs can deliver local tourism public and personal actors who are involved in destination management with the implements, the applications and eventually with the prospect to require on these activities in additional cost effective, self-governing, and in additional eligible manner. ICT-driven development is advantageous for tourism not only in rising employment but also in creating the prospects for more high-skilled professions.

Role of ICT in Tourism

ICTs can therefore turn as ultimate drivers for tourism-driven development in developing destinations. to require hold of those benefits, there’s the necessity for a leeway of the role of DMOs beyond the outmoded promotion of the destination, the pool and dispersal of knowledge and therefore the organization of tourism activities within the destination.

In this perception DMOs become the key players within the usage and dispersion of ICT culture and with better responsiveness within the creation of the required organizational capabilities and infrastructures to line in ICTs within the local tourism industry setting.

DMOs can combat another revolution, from crucial actors to only among the multitude of actors intricate in destination’s management. This foreseen repositioning requires an enhancement of resources and capabilities mainly the event of managerial and technological competences, the capabilities to elaborate and manage complex processes and to scout for the required funding, both within the public sector and within the market. Accordingly, the cohesive ICTs Systems are actuality wont to upkeep cybernetic incoming agency to uphold and commercialize destination offering on a worldwide scale.

1. Describing Governance within the Tourism Sector

The uses and solicitation of ICT based approaches in tourism may be a answer based upon the normal way in tourism. Societies from across the world , with different magnitude are the potential tourist, so complete domain is that the marketplace for tourism. The tourism industry is assorted from micro level to global bounds.

Several means of ICT like Computer Reservation System (CRS), Global Distribution System (GDS) and knowledge System (IS) are used now days. the foremost imperative feature of ICT based tourism is that the supply end and unrestricted information to the patrons at their seats. Information is known by sizable amount of clienteles.

The supplementary drive of ICT based tourism is that it incapacitates the dissociated and geographical obstacles. the buyer and vender from anywhere of world are competent enough to share information. Travelers can access all information which is translucent.

Technology based tourism is extremely thoroughly associated to economy growth. Going deeper it’s a sort of industry where services are rendered to customers or tourist. it’s a completely interrelated business which is interlinked with food and transportation industries. it’s various activities involved in it.

Technology and tourism has revealed the transition within the industry as a results of ICT impact and have explored its possibility and potential. the main challenges facing tourism industry are immensely explored and outlined by some experts and therefore the nexus between tourism and ICT are clearly indicated.

The rapid shift-taking place between ‘traditional tourism sector’ and ‘new tourism industry’ is quiet studied. Technology features a premeditated role in restructuring the worth chain within the industry and within the process, customers are regularly acclimating to the new values, lifestyles and new tourism products, which has re-assessed by the new technologies. albeit a number of the technologies designated are now outdated, the implied missive is pertinent and provides an overall review of the changing face of the tourism industry.

Examining the core features of the industry structure and therefore the operation of the new technologies in it, ICT applications in several sectors like airlines, hotels, tour operators, road and rail transport etc. are dealt intimately . a number of the world’s largest GDS (Global Distribution System) namely Sabre, Galileo, Amadeus and World span are examined.

Besides analyzing the telecommunication technologies within the industry, the hospitality sector, entertainment sector, transport sector, management sector and other intermediaries are diligently explored. Information Technology, information management, intelligent applications and system integration etc. are examined carefully. Additional information on business strategy exploring the connection between ICT, strategy and organization is additionally articulated.

2. Tools for Governance

There are two tools especially that ought to be utilized in the tourism sector with reference to ICT and its implications: Virtual Incoming Agency Model and therefore the creation of integrated ICT system. Developed as a results of variety of research projects undertaken globally, implies a virtual incoming agency (or VIA) model which is conceived as an evolution of the concept of DMO.

Explicitly, as per the considerations beyond the virtual incoming agency is conceptualized because the organization responsible of the promotion and coordination of an integrated tourism system within a tourism destination – along side the establishment of the essential cultural, organization and technological conditions to make sure its effective implementation – that reality relates with applying the graphic organizer technique with an ICT enabled mechanism to undertake its functions . It is a technological and organizational (ICT-enabled and ICT-native) representation for the management of tourism destinations. These mechanisms are often considered with the appliance of virtual incoming agencies with all the general public or public private destination management organizations that comprehends a mission to form use of integrated ICT system.

The objectives of innovative ICT enabled systems are:

• To effectively propose the advantages of tourism for the local economy (incomes, employment, investments • To systematize the local tourism supply chain to be attention for visitors and meet their expectations while maximizing their spending and its distribution • To maintain tourism consultants in increasing the standard of their offerings and their profitability.

Consequently the integrated ICTs Systems are getting used to support virtual incoming agency within the achievement of these objectives and especially . the method is systemic and deducts iteration and indicates mechanisms to captivate on infusion of technology within the concurrent context.

India Needs National Standards Strategy- A Governance with Conformity Assessment

Designed and realized during a modular manner, to create and enrich progressively as per the requirements and capabilities of current and potential users. the thought underneath the platform is to make an open and scalable system, with a coffee porch in terms of costs and complexity, which permit access to actors at different levels of ICT system and technological capabilities. The platform is made to support the increasing in time, number and typologies of operators, users and services.

The platform has as purpose to take care of the consolidation of tourism information, attractions and services providers in solitary rational point of access. An actor (a public authority, consortia of public and personal tourism operators or a public-private company) need to have the accountability to function as a value-adding mediator between local tourism services providers and potential customers, on condition that the facilities are to distribute and sell offerings to the purchasers .

ICT-Enabled Models for the Management of Destinations

The convention of ICTs in tourism, the dissemination of ICT tools and practices in institutions, enterprises and destinations as an entire is way to be automatic, and therefore the results of this process aren’t certain. Therefore, through effective strategies for enabling ICT, tourism can perform well within the global market and emerge very successful.

A scientific application of ICT system can largely enhance the general effectiveness of the destination. Low responsiveness of the advantages and usefulness of ICTs particularly in decision-makers is beneath the inadequate attitude to endow the required time and money. A noteworthy insight among the travel consultants and tourism operators, of being untrained to the organizational changes are desirable from the prologue of ICTs, and thus to endow with the essential competences to use productively such tools. The conception of a constructive background towards innovation is essentially by incorporating the event of ICT solutions and promoting interoperability and therefore the definition of standards.

Therefore sensitization, competences development, organizational change and collaboration, are complementary elements for the diffusion of ICTs and related ICTenabled models in destinations, but also necessary factors for the creation of the specified ‘human’ and ‘social’ infrastructure for the amalgamation and competitiveness of local tourism supply.

These factors, along side the usage of technologies and context/laboratories for the creation of human and social capital and therefore the recognition of the indissoluble link between digital and organizational innovation, are the pillars of the strategy found out for the diffusion of ICTs and therefore the integration of local tourism offering in an integrated supply system.

For competent destination management and technology contribution tourism destinations is in synthesis an integrated strategy, being realized through a series of initiatives focused on: • The design and development of applications and solutions enabling advanced ICT services for the management of destinations • The usage of an equivalent ICT applications and solutions for the event of competences necessary to their productive usage, also as for the belief of local cooperation projects for his or her diffusion adoption in firms and institutions, and therefore the integration of the local tourism system. This strategy is predicated on the convention of ICT solutions’ development projects, for instance the event of a Destination Management System is to trigger the creation of competences and therefore the necessary organizational changes to start-up a process aimed toward fostering interactions and collaboration dynamics among local actors, with the ultimate aim to make the required prerequisites for the mixing of the local tourism system.

Preliminary from these premise, ICTs and especially the projects associated with their comprehension and diffusion, are conceived because the mechanisms necessary to the formation of the cultural collaboration attitudes and behaviors), organizational (business and ICT management competences) and technological (infrastructures and applications) environment for the effective implementation of pioneering models for the management of destinations. This strategy is articulated in three main phases which is portrayed by specific initiatives with defined objectives and roles.

The aim of those initiatives is to make local public and personal tourism operators conscious of the necessity to cooperate within the development of comprehensive propositions which will attract tourists to the destination and therefore the benefits of ICT solutions in doing so.

The intention of this segment is to interact a primary nucleus of actors, interested but not necessarily equipped, within the realization of an e-business cases that demonstrates the advantages within the usage of ICTs for local tourism institutions, enterprises and therefore the destinations overall. The e-business case will then be used for further and simpler sensitization initiatives and within the next phases. The focus is usually on increasing local ICT and e- Business competences (e-skills creation). Second, an ‘evaluation’ phase through the experimentation of ICT applications and solutions Identified previously with the aim to possess people ‘touch with their hands’ the potential benefits of such technologies; to gather the wants for the belief and/or the implementation of the technological platform and to check the business model defined. the target of this phase is to understand a pilot program for the event and implementation of an ICT platform for the management of the destination ICT development and diffusion).

The pilot program are going to be the tool for involving all the opposite relevant stakeholders, on the idea of local experiences and documented leads to the launch and realization of a virtual incoming agency (local networking and cooperation projects) within the destination. this is often the third phase, the ‘implementation’ phase.

During this phase research institutions leave the initiative to non-public enterprises – for the event and therefore the industrialization of the experimented solution – and to local public and personal tourism operators, which will use and manage the answer realized for his or her activities of organizing, promoting and commercializing the destination.

So, as previously highlighted, the event and diffusion of ICT applications and solutions aren’t the top , but rather the means of an overarching innovation policy, aimed toward facilitating the evolution of destinations’ tourism supply systems from fragmented towards integrated configurations.

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COMMENTS

  1. The impacts of ICTs on tourism development: International evidence

    There is hence no consensus as to how ICTs impact tourism development. It is also doubtful that ICTs have any salient impact on AR. Thus, we form the following hypotheses to generalize the associations between ICT and AR internationally. ... (2020) Dissemination of Information and Communication Technology (ICT) in tourism industry: pros and ...

  2. Full article: Tourism, technology and ICT: a critical review of

    The digital information age has changed global tourism in profound ways. Information and Communication Technologies (ICT) are pervasive, and they have become inextricably linked with contemporary consumer cultures. ICTs represent affordances: to apprise, plan, order, network, socialize, stream, transact and rate.

  3. A ten-year review analysis of the impact of digitization on tourism

    ICT is often used in the tourism industry, which has an essential impact on the tourism service industry, one of which is the improvement of tourism income (Gomez-Oliva et al., 2019; Koukopoulos ...

  4. (PDF) ICT impact on tourism industry

    ICT in tourism industry affects the change of internal strategies, rendering them more flexible to changes, helping them to adapt to the new needs of the market (Vilaseca et al., 2006, 2007).

  5. Technology, ICT and tourism: from big data to the big picture

    A sprawling ICT economy in the middle of a global crisis. Technology innovations and in particular Information and Communication Technologies (ICT) have changed tourism in very fundamental ways. The magnitude of these changes is not only evident in their degree of disruptiveness, upsetting long-established economic models, it is also ...

  6. Strategic Use of Information Technologies in Tourism: A Review and

    Consequently, although ICT adoption and use in tourism is highly driven by the interorganizational and international scope and features of the tourism product and industry, research on the strategic value of ICT in tourism is limited to measuring impacts at an organizational rather than an ecosystem level.

  7. The impacts of ICTs on tourism development: International evidence

    Notes: ICT (information and communication technology), SR (travel and leisure sector returns), RV (international tourism receipts as % of total exports), and AR (number of international tourism arrivals). 10, 25, 50, 75, and 90 saliently represent in these quantiles. "-" denotes a negative impact; otherwise it is positive

  8. The Emerald Handbook of ICT in Tourism and Hospitality

    Tourism industry has extensively embraced technologies to enhance operational competencies, service quality over and above customer satisfaction. ... The application of regression analysis indicated positive and significant impact of ICT-based marketing on functional competencies and profitability of tourism and hospitality organizations in ...

  9. ICTs and well-being: challenges and opportunities for tourism

    There are also growing numbers of applications that try to help tourists be either more physically active, mentally engaged or more relaxed to harness the health benefits of vacations (Kang and Gretzel 2012; Stankov et al. 2020a, b).On the other hand, ICT use can also significantly disrupt tourism experiences and challenge well-being goals for the tourists and those around them (Stankov and ...

  10. Exploring and Evaluating the Impact of ICTs on Culture and Tourism

    The second field is the ICT's role in the tourism industry. Extant literature indicates that ICTs in general and the internet in particular have transformed the interaction between tourism ... M.G. The economic growth impact of tourism in Small Island Developing States—Evidence from the Caribbean. Tour. Econ. 2019, 25, 85-108. [Google ...

  11. Impact of technology on travel and tourism

    One of the most recent technology trends shaping the tourism market is the use of Artificial Intelligence (AI) in the travel industry. Although AI adoption is still in its early stages, many key ...

  12. The role of technology in enhancing the tourism experience in smart

    Security/privacy concerns negatively impact the tourism experience in smart destinations. Additionally, several moderating variables can help to explain the differences in effect sizes across studies (Borenstein et al., 2009): the year of publication, the study's geographical origin and the country's level of ICT readiness. Therefore, the ...

  13. Integration of ICT and tourism for improved promotion of tourist

    Information and communication technology (ICT) is revolutionizing the lives of people and operations of organizations. ICT has become a major driver of touristic sectors to effectively promote tourist attractions and services. As a result, many countries have succeeded in using ICTs and more precisely the internet to develop their tourism industries. However, the use of ICT in promoting ...

  14. ICT and the future of tourist management

    Conclusions: to infinity and beyond. The existing discussion of ICT and tourism has mostly focused on ways in which new technologies can automate or make existing tasks more efficient (doing old things better) or ways that expand and alter existing tasks (doing old things in new ways).

  15. Impact of Information Technology on Tourism

    Abstract. Information technology (IT) has become a strategic weapon on tourism products' identification, presentation, dissemination and getting a sustainable competitive advantage. Tourism management is the most important candidate for using IT with the need for gathering information in large quantities and diffusion of tourism management.

  16. The Impact of Information and Communication Technology on the Tourism

    Information and Communication Technology (ICT) has changed the global businesses environment by a wide range of tools, methodologies and functions, facilitating the strategic management and supporting firms to achieve a long term competitive advantage. The aim of this paper is to provide an overview of the new applications of Information Communication Technology in tourism industry, the ...

  17. (PDF) Information Technology in Tourism & Hospitality Industry: A

    The study showed that IT in tourism and hospitality industry is most commonly used in fulfilling information need, studying behavior & performance, managing operation process and innovation ...

  18. (PDF) THE ROLE OF ICT IN TOURISM INDUSTRY

    Gradually, the Information Communications Technologies (ICTs) have assumed an increasingly important role in tourism, travel and the hospitality industry (Bethapudi 2013), as well as an impact on ...

  19. [PDF] THE ROLE OF ICT IN TOURISM INDUSTRY

    The gaps between tourism business and ICT influence are explained, measures to fill the gaps are suggested and the strategic goal is to integrate ICT with tourism that will enable more accessibility, visibility of information, availability of variety of products and satisfaction. The Information Communications Technologies (ICT) plays a major role in tourism, travel and hospitality industry.

  20. [KIT] How does ICT Impact in Tourism Industry?

    The advantages of using ICT in the tourism sector. First, it was used as E-commerce to promote tourism through online platforms. Second, in the hotel industry, it was used to manage employee's productivity and hotel's revenue. Third, in the tourism industry over the world use ICT for the business transaction by trading and providing ...

  21. "Technology Application in Tourism Fairs, Festivals and ...

    The chapter of this part highlights the impact of Web 2.0 and social media, such as Instagram, Facebook, and Twitter, on tourist behavior. ... (ICT) within the tourism sector. Part VI explores the transformative role of technology in the tourism industry across various countries. It highlights the way of technological advancements to improve ...

  22. ICT Impact on tourism industry

    TLDR. A number of key changes in Information Communication Technologies (ICT) that gradually revolutionize the tourism industry are identified and it is demonstrated that future of e-Tourism will be focused on consumer centric technologies to ensure that the new sophisticated and experienced consumers are served. 404.

  23. ICT impact on tourism industry

    ICT in tourism industry affects the change of internal strategies, rendering them more flexible to changes, helping them to adapt to the new needs of the market (Vilaseca et al., 2006, 2007). E-innovation taken as part of an innovative strategy has the potential to change tourism industry processes (Hipp & Grupp, 2005; Martin, 2004).

  24. Role of ICT in Tourism » Tourism Beast

    Technology and tourism has revealed the transition within the industry as a results of ICT impact and have explored its possibility and potential. the main challenges facing tourism industry are immensely explored and outlined by some experts and therefore the nexus between tourism and ICT are clearly indicated.

  25. Museveni unveils plan to propel tourism sector

    President Museveni has affirmed the government's commitment to supporting the Ministry of Tourism and Antiquities, articulating ten key areas of investment aimed at bolstering the sector's ...