ATNA-Journal Of Tourism Studies

Volume 5 of "ATNA-Journal of Tourism Studies" contains eight different articles covering various aspects of tourism. The scholarly articles range from wild life tourism, agri-tourism, ecotourism, heritage and sustainable tourism, destination marketing and information technology in tourism. The current issue makes an earnest effort to present varied dimensions of tourism

Smart destinations and the evolution of ICTs: a new scenario for destination management?

[EN] The impact of information and communication technologies (ICTs) on tourism and their foreseeable future evolution seem to be shaping a new scenario for destination management. This new context has given rise to the need for new management models. One of these models is the emerging smart tourism destination (STD), although it requires greater conceptual precision in order to become a new paradigm for destination management. This paper proposes a systemic model for STDs which facilitates the interpretation of the role of ICTs in the management of tourism destinations. Accordingly, the Delphi technique has been applied so as to determine the opinion of experts regarding the feasibility of the STD approach, its advantages and limitations and also the size of the impact of ICTs on the management and marketing of tourism destinations. This prospective exercise highlights the intensification of the impact of ICTs over the coming years which will shape a new scenario for management characterised by technology and data management. However, the efficiency of the STD approach will not depend exclusively only on technology but also on an appropriate governance of the destination that systematically incorporates the three levels of the STD, namely the strategic¿relational, instrumental and applied levels.This research has been carried out within the framework of the project "New approaches for tourism destinations planning and management: conceptualization, case studies and problems. Definition of smart tourist destinations models" (CSO2014-59193-R) under the Spanish National R&D&I Plan financed by the Ministry of Economy and Competitiveness.Ivars-Baidal, JA.; Celdrán-Bernabeu, MA.; Mazón, JN.; Perles Ivars, A. (2019). Smart destinations and the evolution of ICTs: a new scenario for destination management?. Current Issues in Tourism (Online). 22(13):1581-1600. https://doi.org/10.1080/13683500.2017.1388771S158116002213Benckendorff, P. J., Sheldon, P. J., & Fesenmaier, D. R. (Eds.). (2014). Tourism information technology. doi:10.1079/9781780641850.0000BERGER, S., LEHMANN, H., & LEHNER, F. (2003). LOCATION-BASED SERVICES IN THE TOURIST INDUSTRY. Information Technology & Tourism, 5(4), 243-256. doi:10.3727/109830503108751171Boes, K., Buhalis, D., & Inversini, A. (2014). Conceptualising Smart Tourism Destination Dimensions. Information and Communication Technologies in Tourism 2015, 391-403. doi:10.1007/978-3-319-14343-9_29Buhalis, D., & Amaranggana, A. (2014). Smart Tourism Destinations Enhancing Tourism Experience Through Personalisation of Services. Information and Communication Technologies in Tourism 2015, 377-389. doi:10.1007/978-3-319-14343-9_28Buhalis, D., & Foerste, M. (2015). SoCoMo marketing for travel and tourism: Empowering co-creation of value. Journal of Destination Marketing & Management, 4(3), 151-161. doi:10.1016/j.jdmm.2015.04.001Buhalis, D., & Law, R. (2008). Progress in information technology and tourism management: 20 years on and 10 years after the Internet—The state of eTourism research. Tourism Management, 29(4), 609-623. doi:10.1016/j.tourman.2008.01.005Buhalis, D., & Matloka, J. (2013). 24. Technology-enabled Tourism Destination Management and Marketing. Trends in European Tourism Planning and Organisation, 339-350. doi:10.21832/9781845414122-028Caragliu, A., & Del Bo, C. (2012). Smartness and European urban performance: assessing the local impacts of smart urban attributes. Innovation: The European Journal of Social Science Research, 25(2), 97-113. doi:10.1080/13511610.2012.660323Cetin, G., Aydogan Cifci, M., Istanbullu Dincer, F., & Fuchs, M. (2016). Coping with reintermediation: the case of SMHEs. Information Technology & Tourism, 16(4), 375-392. doi:10.1007/s40558-016-0063-2Chung, N., & Koo, C. (2015). The use of social media in travel information search. Telematics and Informatics, 32(2), 215-229. doi:10.1016/j.tele.2014.08.005Cole, Z. D., Donohoe, H. M., & Stellefson, M. L. (2013). Internet-Based Delphi Research: Case Based Discussion. Environmental Management, 51(3), 511-523. doi:10.1007/s00267-012-0005-5Del Chiappa, G., & Baggio, R. (2015). Knowledge transfer in smart tourism destinations: Analyzing the effects of a network structure. Journal of Destination Marketing & Management, 4(3), 145-150. doi:10.1016/j.jdmm.2015.02.001Donohoe, H. M., & Needham, R. D. (2009). Moving best practice forward: Delphi characteristics, advantages, potential problems, and solutions. International Journal of Tourism Research, 11(5), 415-437. doi:10.1002/jtr.709Fuchs, M., Höpken, W., & Lexhagen, M. (2014). Big data analytics for knowledge generation in tourism destinations – A case from Sweden. Journal of Destination Marketing & Management, 3(4), 198-209. doi:10.1016/j.jdmm.2014.08.002Garrod, B., & Fyall, A. (2000). Managing heritage tourism. Annals of Tourism Research, 27(3), 682-708. doi:10.1016/s0160-7383(99)00094-8Geels, F. W. (2002). Technological transitions as evolutionary reconfiguration processes: a multi-level perspective and a case-study. Research Policy, 31(8-9), 1257-1274. doi:10.1016/s0048-7333(02)00062-8Gretzel, U., Sigala, M., Xiang, Z., & Koo, C. (2015). Smart tourism: foundations and developments. Electronic Markets, 25(3), 179-188. doi:10.1007/s12525-015-0196-8Gretzel, U. (2011). Intelligent systems in tourism. Annals of Tourism Research, 38(3), 757-779. doi:10.1016/j.annals.2011.04.014Gretzel, U., Werthner, H., Koo, C., & Lamsfus, C. (2015). Conceptual foundations for understanding smart tourism ecosystems. Computers in Human Behavior, 50, 558-563. doi:10.1016/j.chb.2015.03.043Gretzel, U., Yuan, Y.-L., & Fesenmaier, D. R. (2000). Preparing for the New Economy: Advertising Strategies and Change in Destination Marketing Organizations. Journal of Travel Research, 39(2), 146-156. doi:10.1177/004728750003900204Hall, M. C. (2008). Tourism and Innovation. doi:10.4324/9780203938430Hjalager, A.-M. (2013). 100 Innovations That Transformed Tourism. Journal of Travel Research, 54(1), 3-21. doi:10.1177/0047287513516390Ivars Baidal, J. A., Solsona Monzonís, F. J., & Giner Sánchez, D. (2016). Gestión turística y tecnologías de la información y la comunicación (TIC): El nuevo enfoque de los destinos inteligentes. Documents d’Anàlisi Geogràfica, 62(2), 327. doi:10.5565/rev/dag.285Jolly, D., & Dimanche, F. (2009). Investing in technology for tourism activities: Perspectives and challenges. Technovation, 29(9), 576-579. doi:10.1016/j.technovation.2009.05.004Jovicic, D. Z. (2016). Key issues in the conceptualization of tourism destinations. Tourism Geographies, 18(4), 445-457. doi:10.1080/14616688.2016.1183144Kanama, D., Kondo, A., & Yokoo, Y. (2008). Development of technology foresight: integration of technology roadmapping and the Delphi method. International Journal of Technology Intelligence and Planning, 4(2), 184. doi:10.1504/ijtip.2008.018316Kitchin, R. (2014). Making sense of smart cities: addressing present shortcomings. Cambridge Journal of Regions, Economy and Society, 8(1), 131-136. doi:10.1093/cjres/rsu027Law, R., Buhalis, D., & Cobanoglu, C. (2014). Progress on information and communication technologies in hospitality and tourism. International Journal of Contemporary Hospitality Management, 26(5), 727-750. doi:10.1108/ijchm-08-2013-0367Li, Y., Hu, C., Huang, C., & Duan, L. (2017). The concept of smart tourism in the context of tourism information services. Tourism Management, 58, 293-300. doi:10.1016/j.tourman.2016.03.014March, H., & Ribera-Fumaz, R. (2016). Smart contradictions: The politics of making Barcelona a Self-sufficient city. European Urban and Regional Studies, 23(4), 816-830. doi:10.1177/0969776414554488Munar, A. M., & Jacobsen, J. K. S. (2014). Motivations for sharing tourism experiences through social media. Tourism Management, 43, 46-54. doi:10.1016/j.tourman.2014.01.012Neuhofer, B., Buhalis, D., & Ladkin, A. (2012). Conceptualising technology enhanced destination experiences. Journal of Destination Marketing & Management, 1(1-2), 36-46. doi:10.1016/j.jdmm.2012.08.001NIININEN, O. (2006). Consumer Centric Tourism Marketing. Tourism Management Dynamics, 175-186. doi:10.1016/b978-0-7506-6378-6.50029-9Okoli, C., & Pawlowski, S. D. (2004). The Delphi method as a research tool: an example, design considerations and applications. Information & Management, 42(1), 15-29. doi:10.1016/j.im.2003.11.002Saraniemi, S., & Kylänen, M. (2010). Problematizing the Concept of Tourism Destination: An Analysis of Different Theoretical Approaches. Journal of Travel Research, 50(2), 133-143. doi:10.1177/0047287510362775Wang, X., Li, X. (Robert), Zhen, F., & Zhang, J. (2016). How smart is your tourist attraction?: Measuring tourist preferences of smart tourism attractions via a FCEM-AHP and IPA approach. Tourism Management, 54, 309-320. doi:10.1016/j.tourman.2015.12.00

Metaverse in the tourism domain – introduction to the special issue

In times of technological innovation and digital transformation, the convergence of Metaverse and tourism emerges as a compelling and revolutionary intersection. As we stand on the edge of a new frontier in information technology, we introduce this special issue of the Journal of Information Technology and Tourism, dedicated to the multifaceted exploration of the Metaverse’s impact on the tourism industry. The Metaverse comprises interconnected digital spaces where users can engage through computer-generated environments. This convergence of cutting-edge tech- nologies, including artificial Intelligence (AI) systems, digital twins, augmented reality (AR), virtual reality (VR), blockchain, non-fungible tokens (NFTs), 3D mod- elling and simulation, cloud computing, and edge computing, defines the Metaverse’s potential. The Metaverse’s profound Influence on the tourism domain is well attested by the rigorous examinations, insightful analyses, and innovative research contributions in this issue. As we embark on this exploration, we encourage researchers, scholars, and industry experts to contribute their expertise and insights, forging a path toward a deeper understanding of the Metaverse’s implications for the future of tourism

Consumers' Use of Smartphone Technology for Travel and Tourism in a COVID Era: A Scoping Review

Mobile phone technology has become a necessary component for today's travellers. Information and communication technologies (ICTs) have substantially affected tourism and hospitality consumers over the past two decades. Mobile technologies such as smartphones, tablets, and mobile applications have become travellers' primary access to information. This study focuses on mobile technologies such as smartphones and mobile applications (apps) and consumers' use of mobile technology when travelling. A scoping review following PRISMA guidelines was used to answer the research question; "How do tourism consumers use mobile technologies for travel and tourism during the COVID era?" This study will identify and analyse any relationships, patterns, trends, and gaps in the literature. Peer-reviewed journal articles from the COVID era (2020 to 2022) were included in this study. Articles were sourced using the keywords listed below. The full articles were imported into NVivo, and the main themes and subthemes were extracted from the data and reported using an inductive qualitative thematic analysis. The results from this study identified "food" as the main theme and "food delivery" as the most frequent subtheme. Food, tourism, transportation, Fourth Industrial Revolution (4IR), Hotel Operations, and Shopping were the top 6 themes. The 4IR is changing how smartphone consumers use their devices for travel and tourism. In the COVID Era, Smartphone technology has been recognised as a solution to maintaining safe distancing and contactless transactions. This research will benefit tourism operators and policymakers to remain competitive in an ever-changing environment during the COVID er

The Value of Cluster Association for Digital Marketing in Tourism Regional Development

[EN] This paper analyses the advantages of membership in a cluster in the effective use of digital marketing tools and in a general way, in the performance, especially for the small and medium firms in underdeveloped regions. For this purpose, a case method research was conducted in the tourism sector, specifically in the hotels in the La Guajira Department, Colombia, where there is a regional tourism cluster. The tourism sector especially depends on digital marketing and the proper use of available digital marketing tools play an essential role in the performance. To conduct the study, 40 hotels in La Guajira were analyzed, whether or not they were members in the cluster. The obtained data were assessed by means of fuzzy set Qualitative Comparative Analysis to check the hypotheses. The results reveal the most effective combinations of digital marketing tools and the activities in which especially small and medium firms must engage in the cluster to obtain better results.Tarazona-Montoya, R.; Peris-Ortiz, M.; Devece Carañana, CA. (2020). The Value of Cluster Association for Digital Marketing in Tourism Regional Development. Sustainability. 12(23):1-18. https://doi.org/10.3390/su12239887S1181223Furukawa, Y., Kondoh, K., & Yabuuchi, S. (2019). Tourism, Capital and Labor Inflows and Regional Development. International Advances in Economic Research, 25(2), 221-233. doi:10.1007/s11294-019-09733-8Kim, K., Park, O., Yun, S., & Yun, H. (2017). What makes tourists feel negatively about tourism destinations? Application of hybrid text mining methodology to smart destination management. Technological Forecasting and Social Change, 123, 362-369. doi:10.1016/j.techfore.2017.01.001Jackson, J., & Murphy, P. (2006). Clusters in regional tourism An Australian case. Annals of Tourism Research, 33(4), 1018-1035. doi:10.1016/j.annals.2006.04.005Mathew, V., & Soliman, M. (2020). Does digital content marketing affect tourism consumer behavior? An extension of t echnology acceptance model. Journal of Consumer Behaviour, 20(1), 61-75. doi:10.1002/cb.1854Bassano, C., Barile, S., Piciocchi, P., Spohrer, J. C., Iandolo, F., & Fisk, R. (2019). Storytelling about places: Tourism marketing in the digital age. Cities, 87, 10-20. doi:10.1016/j.cities.2018.12.025Lee, Y.-J. A., Jang, S., & Kim, J. (2020). Tourism clusters and peer-to-peer accommodation. Annals of Tourism Research, 83, 102960. doi:10.1016/j.annals.2020.102960Alford, P., & Jones, R. (2020). The lone digital tourism entrepreneur: Knowledge acquisition and collaborative transfer. Tourism Management, 81, 104139. doi:10.1016/j.tourman.2020.104139Key Findings from U.S. Digital Marketing Spending Surveyhttps://www.gartner.com/en/documents/2360615/key-findings-from-u-s-digital-marketing-spending-survey-Metasearch Growth Reflects Travelers’ Appetite for Informationhttps://www.emarketer.com/Article/Metasearch-Growth-Reflects-Travelers-Appetite-Information/1009853Speldekamp, D., Knoben, J., & Saka-Helmhout, A. (2020). Clusters and firm-level innovation: A configurational analysis of agglomeration, network and institutional advantages in European aerospace. Research Policy, 49(3), 103921. doi:10.1016/j.respol.2020.103921Koka, B. R., & Prescott, J. E. (2002). Strategic alliances as social capital: a multidimensional view. Strategic Management Journal, 23(9), 795-816. doi:10.1002/smj.252Chan, L.-Y., Lin, H.-L., & Wang, C.-L. (2012). Industry-region Position and Economic Performance of Travel and Tourism Service Industry: An Agglomeration Perspective. Asia Pacific Journal of Tourism Research, 17(5), 562-576. doi:10.1080/10941665.2011.627928Chung, W., & Kalnins, A. (2001). Agglomeration effects and performance: a test of the Texas lodging industry. Strategic Management Journal, 22(10), 969-988. doi:10.1002/smj.178Alcacer, J., & Chung, W. C. (2010). Location Strategies for Agglomeration Economies. SSRN Electronic Journal. doi:10.2139/ssrn.1555111Torres, E. N., Singh, D., & Robertson-Ring, A. (2015). Consumer reviews and the creation of booking transaction value: Lessons from the hotel industry. International Journal of Hospitality Management, 50, 77-83. doi:10.1016/j.ijhm.2015.07.012Levy, S. E., Duan, W., & Boo, S. (2012). An Analysis of One-Star Online Reviews and Responses in the Washington, D.C., Lodging Market. Cornell Hospitality Quarterly, 54(1), 49-63. doi:10.1177/1938965512464513Gu, B., & Ye, Q. (2013). First Step in Social Media: Measuring the Influence of Online Management Responses on Customer Satisfaction. Production and Operations Management, 23(4), 570-582. doi:10.1111/poms.12043Devece, C., Garcia-Agreda, S., & Ribeiro-Navarrete, B. (2015). The Value of Trust for Travel Agencies in Achieving Customers’ Attitudinal Loyalty. Journal of Promotion Management, 21(4), 516-529. doi:10.1080/10496491.2015.1051409Amblee, N., & Bui, T. (2011). Harnessing the Influence of Social Proof in Online Shopping: The Effect of Electronic Word of Mouth on Sales of Digital Microproducts. International Journal of Electronic Commerce, 16(2), 91-114. doi:10.2753/jec1086-4415160205Gavilan, D., Avello, M., & Martinez-Navarro, G. (2018). The influence of online ratings and reviews on hotel booking consideration. Tourism Management, 66, 53-61. doi:10.1016/j.tourman.2017.10.018Papathanassis, A., & Knolle, F. (2011). Exploring the adoption and processing of online holiday reviews: A grounded theory approach. Tourism Management, 32(2), 215-224. doi:10.1016/j.tourman.2009.12.005Hennig-Thurau, T., Malthouse, E. C., Friege, C., Gensler, S., Lobschat, L., Rangaswamy, A., & Skiera, B. (2010). The Impact of New Media on Customer Relationships. Journal of Service Research, 13(3), 311-330. doi:10.1177/1094670510375460Novelli, M., Schmitz, B., & Spencer, T. (2006). Networks, clusters and innovation in tourism: A UK experience. Tourism Management, 27(6), 1141-1152. doi:10.1016/j.tourman.2005.11.011Yang, Y., & Wong, K. K. F. (2012). A Spatial Econometric Approach to Model Spillover Effects in Tourism Flows. Journal of Travel Research, 51(6), 768-778. doi:10.1177/0047287512437855Marco-Lajara, B., Úbeda-García, M., Sabater-Sempere, V., & García-Lillo, F. (2014). Territory Impact on the Performance of Spanish Vacation Hotels. Tourism Economics, 20(4), 779-796. doi:10.5367/te.2013.0301Cohen, J. P., & Paul, C. J. M. (2005). Agglomeration economies and industry location decisions: the impacts of spatial and industrial spillovers. Regional Science and Urban Economics, 35(3), 215-237. doi:10.1016/j.regsciurbeco.2004.04.005Peiró-Signes, A., Segarra-Oña, M.-V., Miret-Pastor, L., & Verma, R. (2014). The Effect of Tourism Clusters on U.S. Hotel Performance. Cornell Hospitality Quarterly, 56(2), 155-167. doi:10.1177/1938965514557354Canina, L., Enz, C. A., & Harrison, J. S. (2005). Agglomeration Efects and Strategic Orientations: Evidence From The U.S. Lodging Industry. Academy of Management Journal, 48(4), 565-581. doi:10.5465/amj.2005.17843938Bruhn, M., Schoenmueller, V., & Schäfer, D. B. (2012). Are social media replacing traditional media in terms of brand equity creation? Management Research Review, 35(9), 770-790. doi:10.1108/01409171211255948Palacios-Marqués, D., Devece-Carañana, C., & Llopis-Albert, C. (2016). Examining the Effects of Online Social Networks and Organizational Learning Capability on Innovation Performance in the Hotel Industry. Psychology & Marketing, 33(12), 1126-1133. doi:10.1002/mar.20948Thelwall, M., & Vis, F. (2017). Gender and image sharing on Facebook, Twitter, Instagram, Snapchat and WhatsApp in the UK. Aslib Journal of Information Management, 69(6), 702-720. doi:10.1108/ajim-04-2017-0098Dehghani, M., & Tumer, M. (2015). A research on effectiveness of Facebook advertising on enhancing purchase intention of consumers. Computers in Human Behavior, 49, 597-600. doi:10.1016/j.chb.2015.03.051Bharadwaj, A. S. (2000). A Resource-Based Perspective on Information Technology Capability and Firm Performance: An Empirical Investigation. MIS Quarterly, 24(1), 169. doi:10.2307/3250983Devece, C. (2013). The value of business managers’ ‘Information Technology’ competence. The Service Industries Journal, 33(7-8), 720-733. doi:10.1080/02642069.2013.740463Bassellier, G., Benbasat, I., & Reich, B. H. (2003). The Influence of Business Managers’ IT Competence on Championing IT. Information Systems Research, 14(4), 317-336. doi:10.1287/isre.14.4.317.24899Bassellier, & Benbasat. (2004). Business Competence of Information Technology Professionals: Conceptual Development and Influence on IT-Business Partnerships. MIS Quarterly, 28(4), 673. doi:10.2307/25148659Huarng, K.-H., & Roig-Tierno, N. (2016). Qualitative comparative analysis, crisp and fuzzy sets in knowledge and innovation. Journal of Business Research, 69(11), 5181-5186. doi:10.1016/j.jbusres.2016.04.109Using fsQCA A Brief Guide and Workshop for Fuzzy-Set Qualitative Comparative Analysishttp://citeseerx.ist.psu.edu/viewdoc/download;jsessionid=9BDDD1E1375E3C1368E1C2AE205D1006?doi=10.1.1.603.1854&rep=rep1&type=pdfTippins, M. J., & Sohi, R. S. (2003). IT competency and firm performance: is organizational learning a missing link? Strategic Management Journal, 24(8), 745-761. doi:10.1002/smj.337Ongsakul, V., Ali, F., Wu, C., Duan, Y., Cobanoglu, C., & Ryu, K. (2020). Hotel website quality, performance, telepresence and behavioral intentions. Tourism Review, 76(3), 681-700. doi:10.1108/tr-02-2019-0039Woodside, A. G. (2013). Moving beyond multiple regression analysis to algorithms: Calling for adoption of a paradigm shift from symmetric to asymmetric thinking in data analysis and crafting theory. Journal of Business Research, 66(4), 463-472. doi:10.1016/j.jbusres.2012.12.021Smithson, S., Devece, C. A., & Lapiedra, R. (2011). Online visibility as a source of competitive advantage for small- and medium-sized tourism accommodation enterprises. The Service Industries Journal, 31(10), 1573-1587. doi:10.1080/02642069.2010.48564

Can Tourist Attractions Boost Other Activities Around? A Data Analysis through Social Networks

[EN] Promoting a tourist destination requires uncovering travel patterns and destination choices, identifying the profile of visitors and analyzing attitudes and preferences of visitors for the city. To this end, tourism-related data are an invaluable asset to understand tourism behaviour, obtain statistical records and support decision-making for business around tourism. In this work, we study the behaviour of tourists visiting top attractions of a city in relation to the tourist influx to restaurants around the attractions. We propose to undertake this analysis by retrieving information posted by visitors in a social network and using an open access map service to locate the tweets in a influence area of the city. Additionally, we present a pattern recognition based technique to differentiate visitors and locals from the collected data from the social network. We apply our study to the city of Valencia in Spain and Berlin in Germany. The results show that, while in Valencia the most frequented restaurants are located near top attractions of the city, in Berlin, it is usually the case that the most visited restaurants are far away from the relevant attractions of the city. The conclusions from this study can be very insightful for destination marketers.This work is supported by the Spanish MINECO project TIN2017-88476-C2-1-R.Bustamante, A.; Sebastiá Tarín, L.; Onaindia De La Rivaherrera, E. (2019). Can Tourist Attractions Boost Other Activities Around? A Data Analysis through Social Networks. Sensors. 19(11):1-25. https://doi.org/10.3390/s19112612S1251911Travel and Tourism Competitiveness Report 2017http://reports.weforum.org/travel-and-tourism-competitiveness-report-2017/OECD Datahttps://data.oecd.org/Travel &Tourism: Economic Impact 2019 Worldhttps://www.wttc.org/-/media/files/reports/economic-impact-research/regions-2019/world2019.pdfCohen, S. A., Prayag, G., & Moital, M. (2013). Consumer behaviour in tourism: Concepts, influences and opportunities. Current Issues in Tourism, 17(10), 872-909. doi:10.1080/13683500.2013.850064Yoo, C.-K., Yoon, D., & Park, E. (2018). Tourist motivation: an integral approach to destination choices. Tourism Review, 73(2), 169-185. doi:10.1108/tr-04-2017-0085Cohen, E. (1979). A Phenomenology of Tourist Experiences. Sociology, 13(2), 179-201. doi:10.1177/003803857901300203Decrop, A., & Snelders, D. (2005). A grounded typology of vacation decision-making. Tourism Management, 26(2), 121-132. doi:10.1016/j.tourman.2003.11.011Servidio, R., & Ruffolo, I. (2016). Exploring the relationship between emotions and memorable tourism experiences through narratives. Tourism Management Perspectives, 20, 151-160. doi:10.1016/j.tmp.2016.07.010Prayag, G., Hosany, S., Muskat, B., & Del Chiappa, G. (2016). Understanding the Relationships between Tourists’ Emotional Experiences, Perceived Overall Image, Satisfaction, and Intention to Recommend. Journal of Travel Research, 56(1), 41-54. doi:10.1177/0047287515620567Valls, J.-F., Sureda, J., & Valls-Tuñon, G. (2014). Attractiveness Analysis of European Tourist Cities. Journal of Travel & Tourism Marketing, 31(2), 178-194. doi:10.1080/10548408.2014.873310García-Palomares, J. C., Gutiérrez, J., & Mínguez, C. (2015). Identification of tourist hot spots based on social networks: A comparative analysis of European metropolises using photo-sharing services and GIS. Applied Geography, 63, 408-417. doi:10.1016/j.apgeog.2015.08.002Lu, Y., Wu, H., Liu, X., & Chen, P. (2019). TourSense: A Framework for Tourist Identification and Analytics Using Transport Data. IEEE Transactions on Knowledge and Data Engineering, 31(12), 2407-2422. doi:10.1109/tkde.2019.2894131Buhalis, D. (2000). Marketing the competitive destination of the future. Tourism Management, 21(1), 97-116. doi:10.1016/s0261-5177(99)00095-3Indicators for Measuring Competitiveness in Tourism: A Guidance Documenthttp://dx.doi.org/10.1787/5k47t9q2t923-enLonghi, C., Titz, J.-B., & Viallis, L. (2014). Open Data: Challenges and Opportunities for the Tourism Industry. Tourism Management, Marketing, and Development, 57-76. doi:10.1057/9781137354358_4Open Data in Tourismhttps://www.europeandataportal.eu/en/highlights/open-data-tourismCox, C., Burgess, S., Sellitto, C., & Buultjens, J. (2009). The Role of User-Generated Content in Tourists’ Travel Planning Behavior. Journal of Hospitality Marketing & Management, 18(8), 743-764. doi:10.1080/19368620903235753Lu, W., & Stepchenkova, S. (2014). User-Generated Content as a Research Mode in Tourism and Hospitality Applications: Topics, Methods, and Software. Journal of Hospitality Marketing & Management, 24(2), 119-154. doi:10.1080/19368623.2014.907758Pantano, E., Priporas, C.-V., & Stylos, N. (2017). ‘You will like it!’ using open data to predict tourists’ response to a tourist attraction. Tourism Management, 60, 430-438. doi:10.1016/j.tourman.2016.12.020Hawelka, B., Sitko, I., Beinat, E., Sobolevsky, S., Kazakopoulos, P., & Ratti, C. (2014). Geo-located Twitter as proxy for global mobility patterns. Cartography and Geographic Information Science, 41(3), 260-271. doi:10.1080/15230406.2014.890072Girardin, F., Calabrese, F., Fiore, F. D., Ratti, C., & Blat, J. (2008). Digital Footprinting: Uncovering Tourists with User-Generated Content. IEEE Pervasive Computing, 7(4), 36-43. doi:10.1109/mprv.2008.71Alivand, M., & Hochmair, H. H. (2016). Spatiotemporal analysis of photo contribution patterns to Panoramio and Flickr. Cartography and Geographic Information Science, 44(2), 170-184. doi:10.1080/15230406.2016.1211489Bassolas, A., Lenormand, M., Tugores, A., Gonçalves, B., & Ramasco, J. J. (2016). Touristic site attractiveness seen through Twitter. EPJ Data Science, 5(1). doi:10.1140/epjds/s13688-016-0073-5Mariani, M., Baggio, R., Fuchs, M., & Höepken, W. (2018). Business intelligence and big data in hospitality and tourism: a systematic literature review. International Journal of Contemporary Hospitality Management, 30(12), 3514-3554. doi:10.1108/ijchm-07-2017-0461Francalanci, C., & Hussain, A. (2015). Discovering social influencers with network visualization: evidence from the tourism domain. Information Technology & Tourism, 16(1), 103-125. doi:10.1007/s40558-015-0030-3Williams, N. L., Inversini, A., Ferdinand, N., & Buhalis, D. (2017). Destination eWOM: A macro and meso network approach? Annals of Tourism Research, 64, 87-101. doi:10.1016/j.annals.2017.02.007Salas-Olmedo, M. H., Moya-Gómez, B., García-Palomares, J. C., & Gutiérrez, J. (2018). Tourists’ digital footprint in cities: Comparing Big Data sources. Tourism Management, 66, 13-25. doi:10.1016/j.tourman.2017.11.001Padilla, J. J., Kavak, H., Lynch, C. J., Gore, R. J., & Diallo, S. Y. (2018). Temporal and spatiotemporal investigation of tourist attraction visit sentiment on Twitter. PLOS ONE, 13(6), e0198857. doi:10.1371/journal.pone.0198857Maeda, T., Yoshida, M., Toriumi, F., & Ohashi, H. (2018). Extraction of Tourist Destinations and Comparative Analysis of Preferences Between Foreign Tourists and Domestic Tourists on the Basis of Geotagged Social Media Data. ISPRS International Journal of Geo-Information, 7(3), 99. doi:10.3390/ijgi7030099Wöber, K. W. (2003). Information supply in tourism management by marketing decision support systems. Tourism Management, 24(3), 241-255. doi:10.1016/s0261-5177(02)00071-7Sabou, M., Onder, I., Brasoveanu, A. M. P., & Scharl, A. (2016). Towards cross-domain data analytics in tourism: a linked data based approach. Information Technology & Tourism, 16(1), 71-101. doi:10.1007/s40558-015-0049-5Adamiak, C., Szyda, B., Dubownik, A., & García-Álvarez, D. (2019). Airbnb Offer in Spain—Spatial Analysis of the Pattern and Determinants of Its Distribution. ISPRS International Journal of Geo-Information, 8(3), 155. doi:10.3390/ijgi8030155Padron Municipal de Habitantes [Statistical Report: Residents in Valencia in 2018]https://bit.ly/2JnNNE

Relationship between Information and Communication Technology and competitiveness in the tourism industry: A mapping review

[EN] The main goal of this study is to review several previously published papers about the relationship between Information and Communication Technology and competitiveness in the tourism industry, to determine trends, research approaches and contextualization of former studies. Ninety papers were selected from the most visited journal databases of scientist papers related to tourism and technology: ScienceDirect, Scopus, Web of Science, ProQuest, EBSCO, DOAJ, and Emerald. Once applied the Systematic Mapping Review methodology, it was found that there are four major categories in which the relationship between the constructs can be grouped competitiveness and Information and Communication Technology; direct positive relationship, negative relationship, no relationship and positive relationship through other factors. Currently, there is consensus between researchers and professionals about the positive relationship between Information and Communication Technology and competitiveness on the tourism industry from the macroeconomic point of view. However, at a microeconomic level, the discussion has not yet been resolved since the adoption of technology or any other type of resource can generate dissimilar results in different companies given the characteristics of each firm. Future lines of research should focus on determining what the factors are,and under what conditions the digitalization of firms translates into improvements in their productivity and competitiveness.Villa-Espinosa, DM.; González-Ladrón-De-Guevara, F.; Miñana Terol, JL. (2018). Relationship between Information and Communication Technology and competitiveness in the tourism industry: A mapping review. Revista Iberoamericana de Turismo. 8(2):143-173. https://doi.org/10.2436/20.8070.01.106S1431738

The economic sustainability of tourism growth through leakage calculation

The development and growth of tourism depend on its sustainability over time and on its benefits for destinations as a whole. However, calculating sustainability is not an easy task. This article focuses on the economic sustainability of tourism growth and, after an exhaustive review of the literature, proposes a quantitative mathematical model to measure it by analysing and calculating leakage in the hotel sector. Leakage analyses the amount of revenue generated by tourists that does not remain in the destination economy. Through a sample of 204 interviews with managers, this study validates the model created and calculates leakage in a mass tourism destination (the Valencian Region in Spain). The paper opens new areas of research in sustainability literature and will be of value to tourism planners and governments in their efforts to implement appropriate tourism development policies.Garrigós Simón, FJ.; Galdón Salvador, JL.; Gil Pechuán, I. (2015). The economic sustainability of tourism growth through leakage calculation. Tourism Economics. 21(4):721-739. doi:10.5367/te.2014.0372S721739214Abelson, P. (2011). Evaluating Major Events and Avoiding the Mercantilist Fallacy*. Economic Papers: A journal of applied economics and policy, 30(1), 48-59. doi:10.1111/j.1759-3441.2011.00096.xAdams, P. D., & Parmenter, B. R. (1995). An applied general equilibrium analysis of the economic effects of tourism in a quite small, quite open economy. Applied Economics, 27(10), 985-994. doi:10.1080/00036849500000079Archer, B. (1995). Importance of tourism for the economy of Bermuda. Annals of Tourism Research, 22(4), 918-930. doi:10.1016/0160-7383(95)00018-1Archer, B., & Fletcher, J. (1996). The economic impact of tourism in the Seychelles. Annals of Tourism Research, 23(1), 32-47. doi:10.1016/0160-7383(95)00041-0Arrow, K., Bolin, B., Costanza, R., Dasgupta, P., Folke, C., Holling, C. S., … Pimentel, D. (1995). Economic Growth, Carrying Capacity, and the Environment. Science, 268(5210), 520-521. doi:10.1126/science.268.5210.520Asiedu, A. B. (2008). Participants’ characteristics and economic benefits of visiting friends and relatives (VFR) tourism - an international survey of the literature with implications for Ghana. International Journal of Tourism Research, 10(6), 609-621. doi:10.1002/jtr.698Blake, A., & Sinclair, M. T. (2003). TOURISM CRISIS MANAGEMENT. Annals of Tourism Research, 30(4), 813-832. doi:10.1016/s0160-7383(03)00056-2Blake, A., Arbache, J. S., Sinclair, M. T., & Teles, V. (2008). Tourism and poverty relief. Annals of Tourism Research, 35(1), 107-126. doi:10.1016/j.annals.2007.06.013Buhalis, D., & Law, R. (2008). Progress in information technology and tourism management: 20 years on and 10 years after the Internet—The state of eTourism research. Tourism Management, 29(4), 609-623. doi:10.1016/j.tourman.2008.01.005Correspondence. (1999). Annals of Tourism Research, 26(3), 705-708. doi:10.1016/s0160-7383(99)00011-0Budeanu, A. (2007). Sustainable tourist behaviour ? a discussion of opportunities for change. International Journal of Consumer Studies, 31(5), 499-508. doi:10.1111/j.1470-6431.2007.00606.xBUTLER, R. W. (1980). THE CONCEPT OF A TOURIST AREA CYCLE OF EVOLUTION: IMPLICATIONS FOR MANAGEMENT OF RESOURCES. The Canadian Geographer/Le Géographe canadien, 24(1), 5-12. doi:10.1111/j.1541-0064.1980.tb00970.xButler, R. W. (1999). Sustainable tourism: A state‐of‐the‐art review. Tourism Geographies, 1(1), 7-25. doi:10.1080/14616689908721291Carbone, M. (2005). Sustainable Tourism in Developing Countries: Poverty Alleviation, Participatory Planning, and Ethical Issues. The European Journal of Development Research, 17(3), 559-565. doi:10.1080/09578810500209841Cawley, M., & Gillmor, D. A. (2008). Integrated rural tourism: Annals of Tourism Research, 35(2), 316-337. doi:10.1016/j.annals.2007.07.011Cernat, L., & Gourdon, J. (2012). Paths to success: Benchmarking cross-country sustainable tourism. Tourism Management, 33(5), 1044-1056. doi:10.1016/j.tourman.2011.12.007Chhabra, D., Sills, E., & Cubbage, F. W. (2003). The Significance of Festivals to Rural Economies: Estimating the Economic Impacts of Scottish Highland Games in North Carolina. Journal of Travel Research, 41(4), 421-427. doi:10.1177/0047287503041004012Dritsakis, N. (2004). Tourism as a Long-Run Economic Growth Factor: An Empirical Investigation for Greece Using Causality Analysis. Tourism Economics, 10(3), 305-316. doi:10.5367/0000000041895094Dritsakis, N. (2012). Tourism Development and Economic Growth in Seven Mediterranean Countries: A Panel Data Approach. Tourism Economics, 18(4), 801-816. doi:10.5367/te.2012.0140Dwyer, L., Forsyth, P., Madden, J., & Spurr, R. (2000). Economic Impacts of Inbound Tourism under Different Assumptions Regarding the Macroeconomy. Current Issues in Tourism, 3(4), 325-363. doi:10.1080/13683500008667877Dwyer, L., Forsyth, P., & Spurr, R. (2006). Assessing the Economic Impacts of Events: A Computable General Equilibrium Approach. Journal of Travel Research, 45(1), 59-66. doi:10.1177/0047287506288907Frechtling, D. C., & Horváth, E. (1999). Estimating the Multiplier Effects of Tourism Expenditures on a Local Economy through a Regional Input-Output Model. Journal of Travel Research, 37(4), 324-332. doi:10.1177/004728759903700402Simón, F. J. G., Narangajavana, Y., & Marqués, D. P. (2004). Carrying capacity in the tourism industry: a case study of Hengistbury Head. Tourism Management, 25(2), 275-283. doi:10.1016/s0261-5177(03)00089-xGartner, W. C. (s. f.). SMALL SCALE ENTERPRISES IN THE TOURISM INDUSTRY IN GHANA’S CENTRAL REGION. CONTEMPORARY ISSUES IN TOURISM DEVELOPMENT, 158-175. doi:10.4324/9780203380307_chapter_10Gooroochurn, N., & Thea Sinclair, M. (2005). Economics of tourism taxation. Annals of Tourism Research, 32(2), 478-498. doi:10.1016/j.annals.2004.10.003Haddad, E. A., Porsse, A. A., & Rabahy, W. (2013). Domestic Tourism and Regional Inequality in Brazil. Tourism Economics, 19(1), 173-186. doi:10.5367/te.2013.0185Hjerpe, E. E., & Kim, Y.-S. (2007). Regional economic impacts of Grand Canyon river runners. Journal of Environmental Management, 85(1), 137-149. doi:10.1016/j.jenvman.2006.08.012Hohl, A. E., & Tisdell, C. A. (1995). Peripheral tourism. Annals of Tourism Research, 22(3), 517-534. doi:10.1016/0160-7383(95)00005-qHughes, H. L. (1994). Tourism multiplier studies: a more judicious approach. Tourism Management, 15(6), 403-406. doi:10.1016/0261-5177(94)90059-0Huse, M., Gustavsen, T., & Almedal, S. (1998). Tourism impact comparisons among norwegian towns. Annals of Tourism Research, 25(3), 721-738. doi:10.1016/s0160-7383(98)00019-xKim, S. S., Chon, K., & Chung, K. Y. (2003). Convention industry in South Korea: an economic impact analysis. Tourism Management, 24(5), 533-541. doi:10.1016/s0261-5177(03)00006-2Klijs, J., Heijman, W., Maris, D. K., & Bryon, J. (2012). Criteria for Comparing Economic Impact Models of Tourism. Tourism Economics, 18(6), 1175-1202. doi:10.5367/te.2012.0172Kokkranikal, J., McLellan, R., & Baum, T. (2003). Island Tourism and Sustainability: A Case Study of the Lakshadweep Islands. Journal of Sustainable Tourism, 11(5), 426-447. doi:10.1080/09669580308667214Kweka, J., Morrissey, O., & Blake, A. (2003). The economic potential of tourism in Tanzania. Journal of International Development, 15(3), 335-351. doi:10.1002/jid.990Lacher, R. G., & Nepal, S. K. (2010). From Leakages to Linkages: Local-Level Strategies for Capturing Tourism Revenue in Northern Thailand. Tourism Geographies, 12(1), 77-99. doi:10.1080/14616680903493654Lee, C.-C., & Chang, C.-P. (2008). Tourism development and economic growth: A closer look at panels. Tourism Management, 29(1), 180-192. doi:10.1016/j.tourman.2007.02.013Lejárraga, I., & Walkenhorst, P. (2010). On linkages and leakages: measuring the secondary effects of tourism. Applied Economics Letters, 17(5), 417-421. doi:10.1080/13504850701765127Mbaiwa, J. E. (2005). Enclave tourism and its socio-economic impacts in the Okavango Delta, Botswana. Tourism Management, 26(2), 157-172. doi:10.1016/j.tourman.2003.11.005Mihalič, T. (2000). Environmental management of a tourist destination. Tourism Management, 21(1), 65-78. doi:10.1016/s0261-5177(99)00096-5Morrison, A., & Thomas, R. (1999). The future of small firms in the hospitality industry. International Journal of Contemporary Hospitality Management, 11(4), 148-154. doi:10.1108/09596119910263531Mowforth, M. (2003). Tourism and Sustainability. doi:10.4324/9780203422779Mshenga, P. M., & Richardson, R. B. (2012). Micro and small enterprise participation in tourism in coastal Kenya. Small Business Economics, 41(3), 667-681. doi:10.1007/s11187-012-9449-5Patterson, T. M., Niccolucci, V., & Marchettini, N. (2008). Adaptive environmental management of tourism in the Province of Siena, Italy using the ecological footprint. Journal of Environmental Management, 86(2), 407-418. doi:10.1016/j.jenvman.2006.04.017Pratt, S. (2011). Economic linkages and impacts across the talc. Annals of Tourism Research, 38(2), 630-650. doi:10.1016/j.annals.2010.11.014Pratt, S., & Blake, A. (2009). The Economic Impact of Hawaii’s Cruise Industry. Tourism Analysis, 14(3), 337-351. doi:10.3727/108354209789704977Rid, W., Ezeuduji, I. O., & Pröbstl-Haider, U. (2014). Segmentation by motivation for rural tourism activities in The Gambia. Tourism Management, 40, 102-116. doi:10.1016/j.tourman.2013.05.006Saarinen, J. (2006). Traditions of sustainability in tourism studies. Annals of Tourism Research, 33(4), 1121-1140. doi:10.1016/j.annals.2006.06.007Sandbrook, C. G. (2008). Putting leakage in its place: The significance of retained tourism revenue in the local context in Rural Uganda. Journal of International Development, 22(1), 124-136. doi:10.1002/jid.1507Shaalan, I. M. (2005). Sustainable tourism development in the Red Sea of Egypt threats and opportunities. Journal of Cleaner Production, 13(2), 83-87. doi:10.1016/j.jclepro.2003.12.012Sheng, L., & Tsui, Y. (2009). Taxing tourism: enhancing or reducing welfare? Journal of Sustainable Tourism, 17(5), 627-635. doi:10.1080/09669580902855828Simpson, P., & Wall, G. (1999). Consequences of resort development. A comparative study. Tourism Management, 20(3), 283-296. doi:10.1016/s0261-5177(99)00025-4Slee, B., Farr, H., & Snowdon, P. (1997). THE ECONOMIC IMPACT OF ALTERNATIVE TYPES OF RURAL TOURISM. Journal of Agricultural Economics, 48(1-3), 179-192. doi:10.1111/j.1477-9552.1997.tb01144.xTorres, R. (2003). Linkages between tourism and agriculture in Mexico. Annals of Tourism Research, 30(3), 546-566. doi:10.1016/s0160-7383(02)00103-2Wagner, J. E. (1997). Estimating the economic impacts of tourism. Annals of Tourism Research, 24(3), 592-608. doi:10.1016/s0160-7383(97)00008-xWalpole, M. J., & Goodwin, H. J. (2000). Local economic impacts of dragon tourism in Indonesia. Annals of Tourism Research, 27(3), 559-576. doi:10.1016/s0160-7383(99)00088-2Zhang, J., Madsen, B., & Jensen-Butler, C. (2007). Regional Economic Impacts of Tourism: The Case of Denmark. Regional Studies, 41(6), 839-854. doi:10.1080/00343400701281733Zhou, D., Yanagida, J. F., Chakravorty, U., & Leung, P. (1997). Estimating economic impacts from tourism. Annals of Tourism Research, 24(1), 76-89. doi:10.1016/s0160-7383(96)00035-

BITOUR: A Business Intelligence Platform for Tourism Analysis

[EN] Integrating collaborative data in data-driven Business Intelligence (BI) system brings an opportunity to foster the decision-making process towards improving tourism competitiveness. This article presents BITOUR, a BI platform that integrates four collaborative data sources (Twitter, Openstreetmap, Tripadvisor and Airbnb). BITOUR follows a classical BI architecture and provides functionalities for data transformation, data processing, data analysis and data visualization. At the core of the data processing, BITOUR offers mechanisms to identify tourists in Twitter, assign tweets to attractions and accommodation sites from Tripadvisor and Airbnb, analyze sentiments in opinions issued by tourists, and all this using geolocation objects in Openstreetmap. With all these ingredients, BITOUR enables data analysis and visualization to answer questions like the most frequented places by tourists, the average stay length or the view of visitors of some particular destination.This work has been supported by COLCIENCIAS through a PhD scholarship. This work is supported by the Spanish MINECO project TIN2017-88476-C2-1-R.Bustamante, A.; Sebastiá Tarín, L.; Onaindia De La Rivaherrera, E. (2020). BITOUR: A Business Intelligence Platform for Tourism Analysis. ISPRS International Journal of Geo-Information. 9(11):1-23. https://doi.org/10.3390/ijgi9110671S123911Nakahira, K. T., Akahane, M., & Fukami, Y. (2012). The Difference and Limitation of Cognition for Piano Playing Skill with Difference Educational Design. Smart Innovation, Systems and Technologies, 609-617. doi:10.1007/978-3-642-29934-6_59Chua, A., Servillo, L., Marcheggiani, E., & Moere, A. V. (2016). Mapping Cilento: Using geotagged social media data to characterize tourist flows in southern Italy. Tourism Management, 57, 295-310. doi:10.1016/j.tourman.2016.06.013Karagiannakis, N., Giannopoulos, G., Skoutas, D., & Athanasiou, S. (2015). OSMRec Tool for Automatic Recommendation of Categories on Spatial Entities in OpenStreetMap. Proceedings of the 9th ACM Conference on Recommender Systems. doi:10.1145/2792838.2796555Burcher, M., & Whelan, C. (2017). Social network analysis as a tool for criminal intelligence: understanding its potential from the perspectives of intelligence analysts. Trends in Organized Crime, 21(3), 278-294. doi:10.1007/s12117-017-9313-8Alcabnani, S., Oubezza, M., & Elkafi, J. (2019). An approach for the implementation of semantic Big Data Analytics in the Social Business Intelligence process on distributed environments (Cloud computing). Proceedings of the 4th International Conference on Big Data and Internet of Things. doi:10.1145/3372938.3373003Zeng, B., & Gerritsen, R. (2014). What do we know about social media in tourism? A review. Tourism Management Perspectives, 10, 27-36. doi:10.1016/j.tmp.2014.01.001Lalicic, L. (2018). Open innovation platforms in tourism: how do stakeholders engage and reach consensus? International Journal of Contemporary Hospitality Management, 30(6), 2517-2536. doi:10.1108/ijchm-04-2016-0233Dwyer, L., & Kim, C. (2003). Destination Competitiveness: Determinants and Indicators. Current Issues in Tourism, 6(5), 369-414. doi:10.1080/13683500308667962Gomezelj, D. O., & Mihalič, T. (2008). Destination competitiveness—Applying different models, the case of Slovenia. Tourism Management, 29(2), 294-307. doi:10.1016/j.tourman.2007.03.009Zhong, L., Deng, J., & Xiang, B. (2008). Tourism development and the tourism area life-cycle model: A case study of Zhangjiajie National Forest Park, China. Tourism Management, 29(5), 841-856. doi:10.1016/j.tourman.2007.10.002Fernández, J. I. P., & Rivero, M. S. (2009). Measuring Tourism Sustainability: Proposal for a Composite Index. Tourism Economics, 15(2), 277-296. doi:10.5367/000000009788254377Cibinskiene, A., & Snieskiene, G. (2015). Evaluation of City Tourism Competitiveness. Procedia - Social and Behavioral Sciences, 213, 105-110. doi:10.1016/j.sbspro.2015.11.411Business Intelligence (BI)—Glossaryhttps://www.gartner.com/it-glossary/business-intelligence-bi/Mariani, M., Baggio, R., Fuchs, M., & Höepken, W. (2018). Business intelligence and big data in hospitality and tourism: a systematic literature review. International Journal of Contemporary Hospitality Management, 30(12), 3514-3554. doi:10.1108/ijchm-07-2017-0461Maeda, T. N., Yoshida, M., Toriumi, F., & Ohashi, H. (2016). Decision Tree Analysis of Tourists’ Preferences Regarding Tourist Attractions Using Geotag Data from Social Media. Proceedings of the Second International Conference on IoT in Urban Space. doi:10.1145/2962735.2962745Guy, I., Mejer, A., Nus, A., & Raiber, F. (2017). Extracting and Ranking Travel Tips from User-Generated Reviews. Proceedings of the 26th International Conference on World Wide Web. doi:10.1145/3038912.3052632Peng, M. Y.-P., Tuan, S.-H., & Liu, F.-C. (2017). Establishment of Business Intelligence and Big Data Analysis for Higher Education. Proceedings of the International Conference on Business and Information Management - ICBIM 2017. doi:10.1145/3134271.3134296Castellanos, M., Gupta, C., Wang, S., Dayal, U., & Durazo, M. (2012). A platform for situational awareness in operational BI. Decision Support Systems, 52(4), 869-883. doi:10.1016/j.dss.2011.11.011Cohen, L. (2017). Impacts of business intelligence on population health. Proceedings of the South African Institute of Computer Scientists and Information Technologists on - SAICSIT ’17. doi:10.1145/3129416.3129441Love, M., Boisvert, C., Uruchurtu, E., & Ibbotson, I. (2016). Nifty with Data. Proceedings of the 2016 ACM Conference on Innovation and Technology in Computer Science Education. doi:10.1145/2899415.2899431Berndt, D. J., Hevner, A. R., & Studnicki, J. (s. f.). Hospital discharge transactions: a data warehouse component. Proceedings of the 33rd Annual Hawaii International Conference on System Sciences. doi:10.1109/hicss.2000.926791Musa, G. J., Chiang, P.-H., Sylk, T., Bavley, R., Keating, W., Lakew, B., … Hoven, C. W. (2013). Use of GIS Mapping as a Public Health Tool–-From Cholera to Cancer. Health Services Insights, 6, HSI.S10471. doi:10.4137/hsi.s10471Mooney, S. J., Westreich, D. J., & El-Sayed, A. M. (2015). Commentary. Epidemiology, 26(3), 390-394. doi:10.1097/ede.0000000000000274Wisniewski, M. F., Kieszkowski, P., Zagorski, B. M., Trick, W. E., Sommers, M., & Weinstein, R. A. (2003). Development of a Clinical Data Warehouse for Hospital Infection Control. Journal of the American Medical Informatics Association, 10(5), 454-462. doi:10.1197/jamia.m1299Miah, S. J., Vu, H. Q., Gammack, J., & McGrath, M. (2017). A Big Data Analytics Method for Tourist Behaviour Analysis. Information & Management, 54(6), 771-785. doi:10.1016/j.im.2016.11.011Li, D., Deng, L., & Cai, Z. (2019). Statistical analysis of tourist flow in tourist spots based on big data platform and DA-HKRVM algorithms. Personal and Ubiquitous Computing, 24(1), 87-101. doi:10.1007/s00779-019-01341-xKrawczyk, M., & Xiang, Z. (2015). Perceptual mapping of hotel brands using online reviews: a text analytics approach. Information Technology & Tourism, 16(1), 23-43. doi:10.1007/s40558-015-0033-0Alaei, A. R., Becken, S., & Stantic, B. (2017). Sentiment Analysis in Tourism: Capitalizing on Big Data. Journal of Travel Research, 58(2), 175-191. doi:10.1177/0047287517747753Thelwall, M. (2019). Sentiment Analysis for Tourism. Big Data and Innovation in Tourism, Travel, and Hospitality, 87-104. doi:10.1007/978-981-13-6339-9_6Höpken, W., Fuchs, M., Höll, G., Keil, D., & Lexhagen, M. (2013). Multi-Dimensional Data Modelling for a Tourism Destination Data Warehouse. Information and Communication Technologies in Tourism 2013, 157-169. doi:10.1007/978-3-642-36309-2_14Sabou, M., Onder, I., Brasoveanu, A. M. P., & Scharl, A. (2015). Towards Cross-Domain Decision Making in Tourism: A Linked Data Based Approach. SSRN Electronic Journal. doi:10.2139/ssrn.2580242Fermoso, A. M., Mateos, M., Beato, M. E., & Berjón, R. (2015). Open linked data and mobile devices as e-tourism tools. A practical approach to collaborative e-learning. Computers in Human Behavior, 51, 618-626. doi:10.1016/j.chb.2015.02.032Wöber, K. W. (2003). Information supply in tourism management by marketing decision support systems. Tourism Management, 24(3), 241-255. doi:10.1016/s0261-5177(02)00071-7Vajirakachorn, T., & Chongwatpol, J. (2017). Application of business intelligence in the tourism industry: A case study of a local food festival in Thailand. Tourism Management Perspectives, 23, 75-86. doi:10.1016/j.tmp.2017.05.003Diakopoulos, N., Naaman, M., & Kivran-Swaine, F. (2010). Diamonds in the rough: Social media visual analytics for journalistic inquiry. 2010 IEEE Symposium on Visual Analytics Science and Technology. doi:10.1109/vast.2010.5652922Bustamante, A., Sebastia, L., & Onaindia, E. (2019). Can Tourist Attractions Boost Other Activities Around? A Data Analysis through Social Networks. Sensors, 19(11), 2612. doi:10.3390/s19112612Yasseri, T., Quattrone, G., & Mashhadi, A. (2013). Temporal analysis of activity patterns of editors in collaborative mapping project of OpenStreetMap. Proceedings of the 9th International Symposium on Open Collaboration. doi:10.1145/2491055.2491068Jilani, M., Corcoran, P., & Bertolotto, M. (2013). Multi-granular Street Network Representation towards Quality Assessment of OpenStreetMap Data. Proceedings of the Sixth ACM SIGSPATIAL International Workshop on Computational Transportation Science - IWCTS ’13. doi:10.1145/2533828.2533833Luxen, D., & Vetter, C. (2011). Real-time routing with OpenStreetMap data. Proceedings of the 19th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems - GIS ’11. doi:10.1145/2093973.2094062Baumbach, S., Rubel, C., Ahmed, S., & Dengel, A. (2019). Geospatial Customer, Competitor and Supplier Analysis for Site Selection of Supermarkets. Proceedings of the 2019 2nd International Conference on Geoinformatics and Data Analysis. doi:10.1145/3318236.3318264Milot, J., Munroe, P., Beaudry, E., Grondin, F., & Bourdeau, G. (2016). Lookupia. Proceedings of the 25th International Conference Companion on World Wide Web - WWW ’16 Companion. doi:10.1145/2872518.2890485Ciepluch, B., Mooney, P., Jacob, R., & Winstanley, A. C. (2009). Using OpenStreetMap to deliver location-based environmental information in Ireland. SIGSPATIAL Special, 1(3), 17-22. doi:10.1145/1645424.1645428Del Pilar Salas-Zárate, M., López-López, E., Valencia-García, R., Aussenac-Gilles, N., Almela, Á., & Alor-Hernández, G. (2014). A study on LIWC categories for opinion mining in Spanish reviews. Journal of Information Science, 40(6), 749-760. doi:10.1177/0165551514547842Gambino, O. J., & Calvo, H. (2016). A Comparison Between Two Spanish Sentiment Lexicons in the Twitter Sentiment Analysis Task. Advances in Artificial Intelligence - IBERAMIA 2016, 127-138. doi:10.1007/978-3-319-47955-2_11Mooney, P., Corcoran, P., & Winstanley, A. C. (2010). Towards quality metrics for OpenStreetMap. Proceedings of the 18th SIGSPATIAL International Conference on Advances in Geographic Information Systems - GIS ’10. doi:10.1145/1869790.1869875El-Ashmawy, K. l. A. (2016). TESTING THE POSITIONAL ACCURACY OF OPENSTREETMAP DATA FOR MAPPING APPLICATIONS. Geodesy and cartography, 42(1), 25-30. doi:10.3846/20296991.2015.116049

Quality in Tourism Literature: A Bibliometric Review

[EN] The literature about quality has experienced an important expansion in the tourism sector in the last decade. This is a result of the importance of quality issues when attempting to maintain and expand sustainable business models for tourism organizations and destinations, which are critical to strengthen competitiveness in the new framework. This relevance has been reflected in the tourism literature, with numerous papers focusing on the topic of quality. Nevertheless, despite its importance, there is a lack of studies and reviews of this literature. In order to overcome this problem, this paper develops a bibliometric and visualization analysis of the literature that examines the topics of tourism and quality together. Specifically, the article studies the 4625 documents on this issue published until the end of 2018 in the Web of Science Core Collection database, by using the co-occurrence of keywords, co-citation, bibliographic coupling, and co-authorship analyses. In addition, the VOSviewer program was used to map the diverse clusters or relationships among the literature. The results showed the trends and impact of this literature, and also the main papers, authors, journals, institutions, and even countries that focus on tourism and quality aspects together. They are useful for researchers and practitioners when dealing with this topic, in order to better understand the situation of this issue and its development.This research was funded by Universitat Politecnica de Valencia, Universitat Jaume I. and The APC was funded by Walailak University.Garrigós Simón, FJ.; Narangajavana-Kaosiri, Y.; Narangajavana, Y. (2019). Quality in Tourism Literature: A Bibliometric Review. Sustainability. 11(14):1-22. https://doi.org/10.3390/su11143859S1221114Armenski, T., Dwyer, L., & Pavluković, V. (2017). Destination Competitiveness: Public and Private Sector Tourism Management in Serbia. Journal of Travel Research, 57(3), 384-398. doi:10.1177/0047287517692445Broadus, R. N. (1987). Toward a definition of «bibliometrics». Scientometrics, 12(5-6), 373-379. doi:10.1007/bf02016680Garrigos-Simon, F., Narangajavana-Kaosiri, Y., & Lengua-Lengua, I. (2018). Tourism and Sustainability: A Bibliometric and Visualization Analysis. Sustainability, 10(6), 1976. doi:10.3390/su10061976Michael Hall, C. (2011). Publish and perish? Bibliometric analysis, journal ranking and the assessment of research quality in tourism. Tourism Management, 32(1), 16-27. doi:10.1016/j.tourman.2010.07.001Benckendorff, P., & Zehrer, A. (2013). A NETWORK ANALYSIS OF TOURISM RESEARCH. Annals of Tourism Research, 43, 121-149. doi:10.1016/j.annals.2013.04.005Yuan, Y., Gretzel, U., & Tseng, Y.-H. (2014). Revealing the Nature of Contemporary Tourism Research: Extracting Common Subject Areas through Bibliographic Coupling. International Journal of Tourism Research, 17(5), 417-431. doi:10.1002/jtr.2004Barrios, M., Borrego, A., Vilaginés, A., Ollé, C., & Somoza, M. (2008). A bibliometric study of psychological research on tourism. Scientometrics, 77(3), 453-467. doi:10.1007/s11192-007-1952-0De la Hoz-Correa, A., Muñoz-Leiva, F., & Bakucz, M. (2018). Past themes and future trends in medical tourism research: A co-word analysis. Tourism Management, 65, 200-211. doi:10.1016/j.tourman.2017.10.001García-Lillo, F., Claver-Cortés, E., Úbeda-García, M., Marco-Lajara, B., & Zaragoza-Sáez, P. C. (2018). Mapping the «intellectual structure» of research on human resources in the «tourism and hospitality management scientific domain». International Journal of Contemporary Hospitality Management, 30(3), 1741-1768. doi:10.1108/ijchm-04-2017-0187Buhalis, D. (2000). Marketing the competitive destination of the future. Tourism Management, 21(1), 97-116. doi:10.1016/s0261-5177(99)00095-3Hoegh-Guldberg, O., Mumby, P. J., Hooten, A. J., Steneck, R. S., Greenfield, P., Gomez, E., … Hatziolos, M. E. (2007). Coral Reefs Under Rapid Climate Change and Ocean Acidification. Science, 318(5857), 1737-1742. doi:10.1126/science.1152509Baker, D. A., & Crompton, J. L. (2000). Quality, satisfaction and behavioral intentions. Annals of Tourism Research, 27(3), 785-804. doi:10.1016/s0160-7383(99)00108-5Bigné, J. E., Sánchez, M. I., & Sánchez, J. (2001). Tourism image, evaluation variables and after purchase behaviour: inter-relationship. Tourism Management, 22(6), 607-616. doi:10.1016/s0261-5177(01)00035-8Parasuraman, A., Zeithaml, V. A., & Berry, L. L. (1985). A Conceptual Model of Service Quality and Its Implications for Future Research. Journal of Marketing, 49(4), 41-50. doi:10.1177/002224298504900403Reeves, C. A., & Bednar, D. A. (1994). DEFINING QUALITY: ALTERNATIVES AND IMPLICATIONS. Academy of Management Review, 19(3), 419-445. doi:10.5465/amr.1994.9412271805Kandampully, J. (2000). The impact of demand fluctuation on the quality of service: a tourism industry example. Managing Service Quality: An International Journal, 10(1), 10-19. doi:10.1108/09604520010307012“Quality”http://sdt.unwto.org/en/content/qualityUysal, M., Sirgy, M. J., Woo, E., & Kim, H. (Lina). (2016). Quality of life (QOL) and well-being research in tourism. Tourism Management, 53, 244-261. doi:10.1016/j.tourman.2015.07.013Garrigós-Simón, F. J., Galdón-Salvador, J. L., & Gil-Pechuán, I. (2015). The Economic Sustainability of Tourism Growth through Leakage Calculation. Tourism Economics, 21(4), 721-739. doi:10.5367/te.2014.0372Honarpour, A., Jusoh, A., & Md Nor, K. (2017). Total quality management, knowledge management, and innovation: an empirical study in R&D units. Total Quality Management & Business Excellence, 29(7-8), 798-816. doi:10.1080/14783363.2016.1238760Prayag, G. (2009). TOURISTS’ EVALUATIONS OF DESTINATION IMAGE, SATISFACTION, AND FUTURE BEHAVIORAL INTENTIONS—THE CASE OF MAURITIUS. Journal of Travel & Tourism Marketing, 26(8), 836-853. doi:10.1080/10548400903358729Zeithaml, V. A., Berry, L. L., & Parasuraman, A. (1996). The Behavioral Consequences of Service Quality. Journal of Marketing, 60(2), 31. doi:10.2307/1251929Lynn Shostack, G. (1982). How to Design a Service. European Journal of Marketing, 16(1), 49-63. doi:10.1108/eum0000000004799Crompton, J. L., & Love, L. L. (1995). The Predictive Validity of Alternative Approaches to Evaluating Quality of a Festival. Journal of Travel Research, 34(1), 11-24. doi:10.1177/004728759503400102Wu, H.-C., Li, M.-Y., & Li, T. (2014). A Study of Experiential Quality, Experiential Value, Experiential Satisfaction, Theme Park Image, and Revisit Intention. Journal of Hospitality & Tourism Research, 42(1), 26-73. doi:10.1177/1096348014563396Atilgan, E., Akinci, S., & Aksoy, S. (2003). Mapping service quality in the tourism industry. Managing Service Quality: An International Journal, 13(5), 412-422. doi:10.1108/09604520310495877Merigó, J. M., & Yang, J.-B. (2016). Accounting Research: A Bibliometric Analysis. Australian Accounting Review, 27(1), 71-100. doi:10.1111/auar.12109Delgado López-Cózar, E., Robinson-García, N., & Torres-Salinas, D. (2013). The Google scholar experiment: How to index false papers and manipulate bibliometric indicators. Journal of the Association for Information Science and Technology, 65(3), 446-454. doi:10.1002/asi.23056Cancino, C., Merigó, J. M., Coronado, F., Dessouky, Y., & Dessouky, M. (2017). Forty years of Computers & Industrial Engineering: A bibliometric analysis. Computers & Industrial Engineering, 113, 614-629. doi:10.1016/j.cie.2017.08.033Blanco-Mesa, F., Merigó, J. M., & Gil-Lafuente, A. M. (2017). Fuzzy decision making: A bibliometric-based review. Journal of Intelligent & Fuzzy Systems, 32(3), 2033-2050. doi:10.3233/jifs-161640Merigó, J. M., Gil-Lafuente, A. M., & Yager, R. R. (2015). An overview of fuzzy research with bibliometric indicators. Applied Soft Computing, 27, 420-433. doi:10.1016/j.asoc.2014.10.035Hirsch, J. E. (2005). An index to quantify an individual’s scientific research output. Proceedings of the National Academy of Sciences, 102(46), 16569-16572. doi:10.1073/pnas.0507655102Van Eck, N. J., & Waltman, L. (2009). Software survey: VOSviewer, a computer program for bibliometric mapping. Scientometrics, 84(2), 523-538. doi:10.1007/s11192-009-0146-3Small, H. (1973). Co-citation in the scientific literature: A new measure of the relationship between two documents. Journal of the American Society for Information Science, 24(4), 265-269. doi:10.1002/asi.4630240406Kessler, M. M. (1963). Bibliographic coupling between scientific papers. American Documentation, 14(1), 10-25. doi:10.1002/asi.5090140103Liao, H., Tang, M., Luo, L., Li, C., Chiclana, F., & Zeng, X.-J. (2018). A Bibliometric Analysis and Visualization of Medical Big Data Research. Sustainability, 10(2), 166. doi:10.3390/su10010166Chen, C.-F., & Chen, F.-S. (2010). Experience quality, perceived value, satisfaction and behavioral intentions for heritage tourists. Tourism Management, 31(1), 29-35. doi:10.1016/j.tourman.2009.02.008Fornell, C., & Larcker, D. F. (1981). Evaluating Structural Equation Models with Unobservable Variables and Measurement Error. Journal of Marketing Research, 18(1), 39-50. doi:10.1177/002224378101800104Yoon, Y., & Uysal, M. (2005). An examination of the effects of motivation and satisfaction on destination loyalty: a structural model. Tourism Management, 26(1), 45-56. doi:10.1016/j.tourman.2003.08.016Zeithaml, V. A. (1988). Consumer Perceptions of Price, Quality, and Value: A Means-End Model and Synthesis of Evidence. Journal of Marketing, 52(3), 2-22. doi:10.1177/002224298805200302Cronin, J. J., Brady, M. K., & Hult, G. T. M. (2000). Assessing the effects of quality, value, and customer satisfaction on consumer behavioral intentions in service environments. Journal of Retailing, 76(2), 193-218. doi:10.1016/s0022-4359(00)00028-2Anderson, J. C., & Gerbing, D. W. (1988). Structural equation modeling in practice: A review and recommended two-step approach. Psychological Bulletin, 103(3), 411-423. doi:10.1037/0033-2909.103.3.411Reyes-Gonzalez, L., Gonzalez-Brambila, C. N., & Veloso, F. (2016). Using co-authorship and citation analysis to identify research groups: a new way to assess performance. Scientometrics, 108(3), 1171-1191. doi:10.1007/s11192-016-2029-8Lai, K., Li, J., & Scott, N. (2015). Tourism problemology: Reflexivity of knowledge making. Annals of Tourism Research, 51, 17-33. doi:10.1016/j.annals.2014.12.00