Understanding tourism consumer behavior using biometric technologies: bibliographic review and research agenda
DOI:
https://doi.org/10.18089/tms.2024SI02Keywords:
Corpus Linguistics (CL), consumer behavior, biometric analysis, tourism, research agendaAbstract
Recent technological advances, particularly in biometrics, have significantly impacted the tourism industry. Amidst the COVID-19 pandemic, these technologies have grown rapidly, posing challenges and opportunities in utilizing the resulting data. This study aims to develop a research agenda concerning biometrics in tourism consumer behavior, detailing what biometric data entails and outlining its diverse applications. Through a bibliographic review of 422 recent papers, employing machine learning and artificial intelligence techniques, we extracted keywords, topics, and frequencies using the methodological approach of corpus linguistics and latent Dirichlet allocation algorithm. The results identified 26 topics, including “KPIs”,” Techniques”, “Personalization”, “Health”, and “Travel and transport”. Furthermore, we observed that the COVID-19 pandemic has dramatically impacted the tourism sector, with “Health” present in four categories. The practical implications of our study suggest that companies can find the issues that most concern the tourism consumer in the lines of research presented in the research agenda, paying particular attention to the lines developed in the research agenda involving “personalization”, "travel and transport" and "health".
References
Al-Ababneh, M. M., Al-Shakhsheer, F. J., Habiballah, M. A., & Al-Badarneh, M. B. (2022). Assessing the ımpact of the COVID-19 pandemic on tourism workers’ health and well-being in Jordan. Tourism & Management Studies, 18(2), 19-38. https://doi.org/10.18089/tms.2022.180202
Ali Gaafar, H., & Al-Romeedy, B. (2022). Neuromarketing as a novel method to tourism destination marketing: Evidence from Egypt. Journal of Association of Arab Universities for Tourism and Hospitality, 22(1), 48-74. https://doi.org/10.21608/JAAUTH.2021.109864.1275
Al-Nakeeb, O. A. M. S., & Mufleh, B. A. H. (2018). Collocations and collocational networks of characters: a corpus-based feminist stylistic analysis. Language in India, 18(9).
Amankwah-Amoah, J. (2021). COVID‐19 pandemic and innovation activities in the global airline industry: A review. Environment International, 156, 106719. https://doi.org/10.1016/j.envint.2021.106719
Arbelaitz, O., Gurrutxaga, I., Lojo, A., Muguerza, J., Pérez, J. M., & Perona, I. (2013). Web usage and content mining to extract knowledge for modelling the users of the Bidasoa Turismo website and to adapt it. Expert Systems with Applications, 40(18), 7478-7491. https://doi.org/10.1016/j.eswa.2013.07.040
Ariely, D., & Berns, G. S. (010). Neuromarketing: the hope and hype of neuroimaging in business. Nature Reviews Neuroscience, 11(4), 284-292. https://doi.org/doi:10.1038/nrn2795
Babaç, E., & Yüncü, H.R. (2022). Determination of user experience on foodbusiness websites using neuromarketing techniques. Tourism & Management Studies, 18(3), 49-64. https://doi.org/10.18089/tms.2022.180304
Baker, P. (2006). Glossary of corpus linguistics. Edinburgh: Edinburgh University Press.
Baker, P. (2014). Corpus linguistics in sociolinguistics. Research Methods in Sociolinguistics: A Practical Guide. Hoboken, NJ: Wiley-Blackwell.
Baker, P., Gabrielatos, C., Khosravinik, M., Krzyżanowski, M., McEnery, T., & Wodak, R. (2008). A useful methodological synergy? Combining critical discourse analysis and corpus linguistics to examine discourses of refugees and asylum seekers in the UK press. Discourse & Society, 19(3), 273-306. https://doi.org/10.1177/0957926508088962
Barari, M., Ross, M., Thaichon, S., & Surachartkumtonkun, J. (2021). A meta‐analysis of customer engagement behavior. International Journal of Consumer Studies, 45(4), 457-477. https://doi.org/10.1111/ijcs.12609
Bastiaansen, M., Straatman, S., Driessen, E., Mitas, O., Stekelenburg, J., & Wang, L. (2018). My destination in your brain: A novel neuromarketing approach for evaluating the effectiveness of destination marketing. Journal of destination marketing & management, 7, 76-88. https://doi.org/10.1016/j.jdmm.2016.09.003
Blasco-Arcas, L., Lee, H. H. M., Kastanakis, M. N., Alcañiz, M., & Reyes-Menendez, A. (2022). The role of consumer data in marketing: A research agenda. Journal of Business Research, 146, 436-452. https://doi.org/10.1016/j.jbusres.2022.03.054
Blei, D. M., Ng, A. Y., & Jordan, M. I. (2003). Latent dirichlet allocation. The Journal of Machine Learning Research, 3, 993-1022.
Boo, H. C., & Chua, B. L. (2022). An integrative model of facial recognition check-in technology adoption intention: the perspective of hotel guests in Singapore. International Journal of Contemporary Hospitality Management, 34(11), 4052-4079. https://doi.org/10.1108/IJCHM-12-2021-1471
Borgman, C. L., & Furner, J. (2002). Scholarly communication and bibliometrics. Annual Review of İnformation Science and Technology, 36(1), 2-72. https://doi.org/10.1002/aris.1440360102
Bouma, G. (2009). Normalized (pointwise) mutual information in collocation extraction. Proceedings of GSCL, Potsdam, Germany, pp. 31-40.
Boz, H., & Koç, E. (2022). Using neuromarketing tools in hospitality and tourism research. In Hakan Boz & Erdogan Koç (Eds.), Advanced research methods in hospitality and tourism (pp. 87-109). Bingley, UK: Emerald Publishing Limited. https://doi.org/10.1108/978-1-80117-550-020221005
Büschken, J., & Allenby, G. M. (2016). Sentence-based text analysis for customer reviews. Marketing Science, 35(6), 953-975. https://doi.org/10.1287/mksc.2016.0993
Büschken, J., & Allenby, G. M. (2020). Improving text analysis using sentence conjunctions and punctuation. Marketing Science, 39(4), 727-742. https://doi.org/10.1287/mksc.2019.1214
Cascio, C., O'Donnell, M., Tinney, F., Lieberman, M., Taylor, S., Strecher, V., & Falk, E. (2015). Self-affirmation activates brain systems associated with self-related processing and reward and is reinforced by future orientation. Social Cognitive and Affective Neuroscience, 11(4), 621-629. https://doi.org/10.1093/scan/nsv136.
Chang, C. L., McAleer, M., & Ramos, V. (2020). A charter for sustainable tourism after COVID-19. Sustainability, 12(9), 3671. https://doi.org/10.3390/su12093671
Chen, X., Duan, Y., Ali, L., Duan, Y., & Ryu, K. (2021). Understanding consumer travel behavior during covid-19. Sustainability, 13(23), 13330. https://doi.org/10.3390/su132313330
Chen, Y. Y., Cheng, A. J., & Hsu, W. H. (2013). Travel recommendation by mining people attributes and travel group types from community-contributed photos. IEEE Transactions on Multimedia, 15(6), 1283-1295. https://doi.org/10.1109/TMM.2013.2265077
Chen, Y., Mandler, T., & Meyer-Waarden, L. (2021). Three decades of research on loyalty programs: A literature review and future research agenda. Journal of Business Research, 124, 179-197. https://doi.org/10.1016/j.jbusres.2020.11.057
Chi, O. H., Denton, G., & Gursoy, D. (2020). Artificially intelligent device use in service delivery: a systematic review, synthesis, and research agenda. Journal of Hospitality Marketing & Management, 29(7), 757-786. https://doi.org/10.1080/19368623.2020.1721394
Chiu, W., & Cho, H. (2022). The model of goal-directed behavior in tourism and hospitality: A meta-analytic structural equation modeling approach. Journal of Travel Research, 61(3), 637-655. https://doi.org/10.1177/0047287521991242
Coba, L., Rook, L., & Zanker, M. (2020). Choosing between hotels: impact of bimodal rating summary statistics and maximizing behavioral tendency. Information Technology & Tourism, 22(1), 167-186. https://doi.org/10.1007/s40558-019-00156-z
Crampton, Jeremy. (2019). Platform Biometrics. Surveillance & Society, 17, 54-62. https://doi.org/10.24908/ss.v17i1/2.13111
De Keyser, A., Bart, Y., Gu, X., Liu, S. Q., Robinson, S. G., & Kannan, P. K. (2021). Opportunities and challenges of using biometrics for business: Developing a research agenda. Journal of Business Research, 136, 52-62. https://doi.org/10.1016/j.jbusres.2021.07.028
De-Frutos-Arranz, S., & López, M. F. B. (2022). The state of the art of emotional advertising in tourism: A neuromarketing perspective. Tourism Review International, 26(2), 139-162. https://doi.org/10.3727/154427221X16317419620246
Desai, K. K., & Mahajan, V. (1998). Strategic role of affect-based attitudes in the acquisition, development, and retention of customers. Journal of Business Research, 42(3), 309-324. https://doi.org/10.1016/S0148-2963(97)00127-6
Devkota, N., Kmeco, L., Thapa, S., Houška, P., & Paudel, U.R. (2022). Tourists’ perception of travel risk and management in destination amid Covid-19 pandemic: empirical evidence from Nepal. Journal of Tourism and Services, 13(25), 90–119. https://doi.org/10.29036/jots.v13i25.388
Dimanche, F., & Havitz, M. E. (1995). Consumer behavior and tourism: Review and extension of four study areas. Journal of Travel & Tourism Marketing, 3(3), 37-57. https://doi.org/10.1300/J073v03n03_03
Ding, N. (2020). The effectiveness of evacuation signs in buildings based on eye tracking experiment. Natural Hazards, 103, 1201-1218. https://doi.org/10.1016/j.jnlssr.2022.11.001
El Fkharany, H. M. (2022). Applying biometric technology for enhancing airports efficiency during Covid-19 pandemic: A case study of Egyptian destination. The International Journal of Tourism and Hospitality Studies, 3(2), 104-117.
Femenia-Serra, F., & Neuhofer, B. (2018). Smart tourism experiences: Conceptualisation, key dimensions and research agenda. Investigaciones Regionales-Journal of Regional Research, (42), 129-150.
Gartner (2022). Hype cycle for emerging technologies, 2022. Retrieved online March, 2023 from https://www.gartner.com/en/documents/4016848
González-Rodríguez, M. R., Díaz-Fernández, M. C., & Gómez, C. P. (2020). Facial-expression recognition: an emergent approach to the measurement of tourist satisfaction through emotions. Telematics and Informatics, 51, 101404. https://doi.org/10.1016/j.tele.2020.101404
Google Trends. 2021. Retrieved 05 May 2021 from www.google.com/trends
Grazziotin, L. S., Klaus, V., & Pereira, A. P. M. (2022). Documentary historical analysis and bibliographic research: study subjects and methodology. Pro-Posições, 33, e20200141. http://dx.doi.org/10.1590/1980-6248-2020-0141EN
Halkiopoulos, C., Antonopoulou, H., Gkintoni, E., & Aroutzidis, A. (2022). Neuromarketing as an indicator of cognitive consumer behavior in decision-making process of tourism destination—An overview. In Transcending Borders in Tourism Through Innovation and Cultural Heritage: 8th International Conference, IACuDiT, Hydra, Greece, 2021 (pp. 679-697). Cham: Springer International Publishing.
Han, H. (2021). Consumer behavior and environmental sustainability in tourism and hospitality: A review of theories, concepts, and latest research. Journal of Sustainable Tourism, 29(7), 1021-1042. https://doi.org/10.1080/09669582.2021.1903019
Hao, Q., Cai, R., Wang, C., Xiao, R., Yang, J. M., Pang, Y., & Zhang, L. (2010). Equip tourists with knowledge mined from travelogues. In Proceedings of the 19th international conference on World wide web (pp. 401-410). https://doi.org/10.1145/1772690.1772732
Hardaker, C., & McGlashan, M. (2016). “Real men don’t hate women”: Twitter rape threats and group identity. Journal of Pragmatics, 91, 80-93. https://doi.org/10.1016/j.pragma.2015.11.005
Hassan, S. M., Rahman, Z., & Paul, J. (2021). Consumer ethics: A review and research agenda. Psychology & Marketing, 39, 111-130. https://doi.org/10.1002/mar.21580
Holmes, M. R., Dodds, R., & Frochot, I. (2021). At home or abroad, does our behavior change? Examining how everyday behavior influences sustainable travel behavior and tourist clusters. Journal of Travel Research, 60(1), 102-116. https://doi.org/10.1177/0047287519894070
Huang, C., Wang, Q., Yang, D., & Xu, F. (2018). Topic mining of tourist attractions based on a seasonal context aware LDA model. Intelligent Data Analysis, 22(2), 383-405. https://doi.org/10.3233/IDA-173364
Huang, G. I., Karl, M., Wong, I. A., & Law, R. (2023). Tourism destination research from 2000 to 2020: A systematic narrative review in conjunction with bibliographic mapping analysis. Tourism management, 95, 104686. https://doi.org/10.1016/j.tourman.2022.104686
Hultman, M., Skarmeas, D., Oghazi, P., & Beheshti, H. M. (2015). Achieving tourist loyalty through destination personality, satisfaction, and identification. Journal of Business Research, 68(11), 2227-2231. https://doi.org/10.1016/j.jbusres.2015.06.002
IBIA (2018). Glossary: Biometrics. Retrieved 02 March 2023 from https://www.ibia.org/biometrics/glossary
Ioannides, D., & Gyimóthy, S. (2020). The COVID-19 crisis as an opportunity for escaping the unsustainable global tourism path. Tourism Geographies, 22(3), 624-632. https://doi.org/10.1080/14616688.2020.1763445
Ioannou, A., Tussyadiah, I., & Miller, G. (2021). That’s private! Understanding travelers’ privacy concerns and online data disclosure. Journal of Travel Research, 60(7), 1510-1526. https://doi.org/10.1177/0047287520951642
Ivanov, S. H., & Umbrello, S. (2021). The ethics of artificial intelligence and robotisation in tourism and hospitality–a conceptual framework and research agenda. Journal of Smart Tourism, 1(4), 9-18. https://doi.org/10.52255/smarttourism.2021.1.4.3
Ivanov, S., & Webster, C. (2020). Robots in tourism: A research agenda for tourism economics. Tourism Economics, 26(7), 1065-1085. https://doi.org/10.1177/1354816619879583
Ivanov, S., Webster, C., Stoilova, E., & Slobodskoy, D. (2020). Biosecurity, automation technologies and economic resilience of travel, tourism and hospitality companies. Sorarxiv Pap, 1-34. https://doi.org/10.31235/osf.io/2hx6f
Iyengar, S., Sood, G., & Lelkes, Y. (2012). Affect, not ideologya social identity perspective on polarization. Public Opinion Quarterly, 76(3), 405-431.
Jacobi, C., Van Atteveldt, W., & Welbers, K. (2016). Quantitative analysis of large amounts of journalistic texts using topic modelling. Digital Journalism, 4(1), 89-106. https://doi.org/10.1080/21670811.2015.1093271
Jia, S. (S. (2018). Leisure motivation and satisfaction: A text mining of yoga centres, yoga consumers, and their interactions. Sustainability, 10(12), 4458. https://doi.org/10.3390/su10124458
Jiang, S., Qian, X., Shen, J., Fu, Y., & Mei, T. (2015). Author topic model-based collaborative filtering for personalized POI recommendations. IEEE Transactions on Multimedia, 17(6), 907-918. https://doi.org/10.1109/TMM.2015.2417506
Jun, S. P., Yoo, H. S., & Choi, S. (2018). Ten years of research change using Google Trends: From the perspective of big data utilizations and applications. Technological Forecasting and Social Change, 130, 69-87. https://doi.org/10.1016/j.techfore.2017.11.009
Khalid, U., Okafor, L. E., & Burzynska, K. (2021). Does the size of the tourism sector influence the economic policy response to the COVID-19 pandemic?. Current Issues in Tourism, 24(19), 2801-2820. https://doi.org/10.1080/13683500.2021.1874311
Kim, M. J., Bonn, M., & Hall, C. M. (2022). What influences COVID-19 biosecurity behaviour for tourism?. Current İssues in Tourism, 25(1), 21-27. https://doi.org/10.1080/13683500.2021.1883558
Kim, M. J., Hall, C. M., & Bonn, M. (2021). Does ınternational travel frequency affect Covid-19 biosecurity behavior in the United States?. International Journal of Environmental Research and Public Health, 18(8), 4111. https://doi.org/10.3390/ijerph18084111
Knani, M., Echchakoui, S., & Ladhari, R. (2022). Artificial intelligence in tourism and hospitality: Bibliometric analysis and research agenda. International Journal of Hospitality Management, 107, 103317. https://doi.org/10.1016/j.ijhm.2022.103317
Krajčík, V., Novotný, O., Civelek, M., & Zvolánková, S. S. (2023). Digital literacy and digital transformation activities of service and manufacturing SMEs. Journal of Tourism and Services, 14(26), 242–262. https://doi.org/10.29036/jots.v14i26.551
Lai, T-C., Hsieh, C-L., & Ku, S.C.S. (2022). The gorgeous brand: understanding consumer’ conspicuous consumption for luxury tourism products. Journal of Tourism and Services, 24(13), 108-127. https://doi.org/10.29036/jots.v13i24.308
Lee, M. (2021). Evolution of hospitality and tourism technology research from Journal of Hospitality and Tourism Technology: a computer-assisted qualitative data analysis. Journal of Hospitality and Tourism Technology, 13(1), 62-84. https://doi.org/10.1108/JHTT-10-2020-0276
Leonidou, C. N., & Leonidou, L. C. (2011). Research into environmental marketing/management: a bibliographic analysis. European Journal of Marketing, 45(1/2), 68-103. https://doi.org/10.1108/03090561111095603
Leonidou, L. C., Katsikeas, C. S., & Coudounaris, D. N. (2010). Five decades of business research into exporting: A bibliographic analysis. Journal of International Management, 16(1), 78-91. https://doi.org/10.1016/j.intman.2009.06.001
Li, S., Walters, G., Packer, J., & Scott, N. (2018). Using skin conductance and facial electromyography to measure emotional responses to tourism advertising. Current Issues in Tourism, 21(15), 1761-1783. https://doi.org/10.1080/13683500.2016.1223023
Li, X., Li, X. R., & Hudson, S. (2013). The application of generational theory to tourism consumer behavior: An American perspective. Tourism Management, 37, 147-164. https://doi.org/10.1016/j.tourman.2013.01.015
Lim, K. W., & Buntine, W. (2016). Bibliographic analysis on research publications using authors, categorical labels and the citation network. Machine Learning, 103(2), 185-213. https://doi.org/10.1007/s10994-016-5554-z
Liu, Q., Chen, E., Xiong, H., Ge, Y., Li, Z., & Wu, X. (2012). A cocktail approach for travel package recommendation. IEEE Transactions on Knowledge and Data Engineering, 26(2), 278-293. https://doi.org/10.1109/TKDE.2012.233
Liu, R., An, E., & Zhou, W. (2021). The effect of online search volume on financial performance: Marketing insight from Google trends data of the top five US technology firms. Journal of Marketing Theory and Practice, 29(4), 423-434. https://doi.org/10.1080/10696679.2020.1867478
Liu, X., Burns, A. C., & Hou, Y. (2017). An investigation of brand-related user-generated content on Twitter. Journal of Advertising, 46(2), 236-247. https://doi.org/10.1080/00913367.2017.1297273
Loureiro, S. M. C., Guerreiro, J., & Tussyadiah, I. (2020). Artificial intelligence in business: State of the art and future research agenda. Journal of Business Research, 46(2), 236-247. https://doi.org/10.1080/00913367.2017.1297273
Lu, H. M. (2015). Detecting short-term cyclical topic dynamics in the user-generated content and news. Decision Support Systems, 70, 1-14. https://doi.org/10.1016/j.dss.2014.11.006
Lustigova, Z., Jarolímková, L., & Žufan, J. (2021). Evaluation of tourist decision-making process by eye-tracking method – focused on methodology gap and cross-national comparison. Journal of Tourism and Services, 12(22), 89–104. https://doi.org/10.29036/jots.v12i22.258
Machová, R., Korcsmáros, E., Esseová, M., & Marča, R. (2021). Changing trends of shopping habits and tourism during the second wave of COVID-19 – ınternational comparison. Journal of Tourism and Services, 12(22), 131–149. https://doi.org/10.29036/jots.v12i22.256
Maltoni, D., Maio, D., Jain, A. K., & Prabhakar, S. (2009). Handbook of fingerprint recognition. Berlin: Springer Science & Business Media.
Mazov, N. A., & Gureyev, V. N. (2023). Open access bibliographic resources for maintaining a bibliographic database of research organization. Scientific and Technical Information Processing, 50(3), 211-223. https://doi.org/10.3103/S0147688223030115
McEnery, T., & Hardie, A. (2013). The history of corpus linguistics. In The Oxford handbook of the history of linguistics. Oxford: Oxford University Press. https://doi.org/10.1093/oxfordhb/9780199585847.001.0001
Melis, D. J., Silva, J. M., & Yeun, R. C. (2018). Impact of biometric and anthropometric characteristics of passengers on aircraft safety and performance. Transport Reviews, 38(5), 602-624. https://doi.org/10.1080/01441647.2017.1396264
Minhas, S., & Hussain, A. (2014). Linguistic correlates of deception in financial text a corpus linguistics based approach. Psychology Review, 19, 307-342.
Morosan, C. (2018). Information disclosure to biometric e-gates: The roles of perceived security, benefits, and emotions. Journal of Travel Research, 57(5), 644-657. https://doi.org/10.1177/0047287517711256
Moutinho, L., Ballantyne, R., & Rate, S. (2011). Consumer behavior in tourism. Strategic Management in Tourism, 2(2), 83-126. https://doi.org/10.1079/9781845935887.0083
Mustak, M., Salminen, J., Plé, L., & Wirtz, J. (2021). Artificial intelligence in marketing: Topic modeling, scientometric analysis, and research agenda. Journal of Business Research, 124, 389-404. https://doi.org/10.1016/j.jbusres.2020.10.044
Negri, N. A. R., Borille, G. M. R., & Falcão, V. A. (2019). Acceptance of biometric technology in airport check-in. Journal of Air Transport Management, 81, 101720. https://doi.org/10.1016/j.jairtraman.2019.101720
Neo, H. F., & Teo, C. C. (2022). Biometrics in Tourism: Issues and Challenges. In Handbook of e-Tourism (pp. 1835-1849). Berlin: Springer. https://doi.org/10.1007/978-3-030-05324-6_137-1
Nikolenko, S. I., Koltcov, S., & Koltsova, O. (2017). Topic modelling for qualitative studies. Journal of Information Science, 43(1), 88-102. https://doi.org/10.1177/0165551515617393
Norfolk, L., & O’Regan, M. (2020). Biometric technologies at music festivals: An extended technology acceptance model. Journal of Convention & Event Tourism, 22(1), 36-60. https://doi.org/10.1080/15470148.2020.1811184
Oliveira, P. M., Guerreiro, J., & Rita, P. (2022). Neuroscience research in consumer behavior: A review and future research agenda. International Journal of Consumer Studies, 46(5), 2041-2067. https://doi.org/10.1111/ijcs.12800
Paul, J., & Benito, G. R. (2018). A review of research on outward foreign direct investment from emerging countries including China: What do we know? How do we know? and Where should we be heading? Asia Pacific Business Review, 24(1), 90–115. https://doi.org/10.1080/13602381.2017.1357316
Paul, J., Lim, W. M., O'Cass, A., Hao, A. W., & Bresciani, S. (2021a). Scientific procedures and rationales for systematic literature reviews (SPAR‐4‐SLR). International Journal of Consumer Studies, 45(4). https://doi.org/10.1111/ijcs.12695
Paul, J., Merchant, A., Dwivedi, Y. K., & Rose, G. (2021b). Writing an impactful review article: What do we know and what do we need to know?. Journal of Business Research, 133, 337-340. https://doi.org/10.1016/j.jbusres.2021.05.005
Putri, I. R., & Kusumaningrum, R. (2017). Latent Dirichlet allocation (LDA) for sentiment analysis toward tourism review in Indonesia. Journal of Physics: Conference Series, Volume 801, International Conference on Computing and Applied Informatics 2016 14–15 December 2016, Medan, Indonesia. IOP Publishing. https://doi.org/10.1088/1742-6596/801/1/012073
Radhakrishnan, S., Erbis, S., Isaacs, J. A., & Kamarthi, S. (2017). Novel keyword co-occurrence network-based methods to foster systematic reviews of scientific literature. PloS one, 12(3), e0172778. https://doi.org/10.1371/journal.pone.0172778
Rama-Maneiro, E., Vidal, J. C., & Lama, M. (2020). Collective disambiguation in entity linking based on topic coherence in semantic graphs. Knowledge-Based Systems, 199, 105967. https://doi.org/10.1016/j.knosys.2020.105967
Randhawa, K., Wilden, R., & Hohberger, J. (2016). A bibliometric review of open innovation: Setting a research agenda. Journal of Product Innovation Management, 33(6), 750-772. https://doi.org/10.1111/jpim.12312
Reyes-Menendez, A., Palos-Sanchez, P. R., Saura, J. R., & Martin-Velicia, F. (2018). Understanding the influence of wireless communications and Wi-Fi access on customer loyalty: a behavioral model system. Wireless Communications and Mobile Computing, 3487398. https://doi.org/10.1155/2018/3487398
Reyes-Menendez, A., Saura, J. R., & Filipe, F. (2019). The importance of behavioral data to identify online fake reviews for tourism businesses: A systematic review. Peer Journal of Computer Science, 5, e219. https://doi.org/10.7717/peerj-cs.219
Reyes-Menendez, A., Saura, J. R., & Thomas, S. B. (2020). Exploring key indicators of social identity in the #MeToo era: Using discourse analysis in UGC. International Journal of Information Management, 54, 102129. https://doi.org/10.1016/j.ijinfomgt.2020.102129
Reyes-Menéndez, A., Žiaran, P., Antolín-Prieto, R., & Ruiz-Lacaci, N. (2023). How eye tracking can predict consumer behavior preferences on mobile devices. Applied Marketing Analytics, 8(3), 239-254.
Rosado-Serrano, A., Paul, J., & Dikova, D. (2018). International franchising: A literature review and research agenda. Journal of Business Research, 85, 238-257. https://doi.org/10.1016/j.jbusres.2017.12.049
Saura, J. R., & Bennett, D. R. (2019). A three-stage method for data text mining: Using UGC in business intelligence analysis. Symmetry, 11(4), 519. https://doi.org/10.3390/sym11040519
Saura, J. R., Reyes-Menendez, A., & Alvarez-Alonso, C. (2018). Do online comments affect environmental management? Identifying factors related to environmental management and sustainability of hotels. Sustainability, 10(9), 3016. https://doi.org/10.3390/su10093016
Scott, N., Le, D., Becken, S., & Connolly, R. M. (2020). Measuring perceived beauty of the Great Barrier Reef using eye-tracking technology. Current Issues in Tourism, 23(20), 2492-2502. https://doi.org/10.1080/13683500.2019.1626812
Scott, N. & Zhang, R. & Le, D. & Moyle, B. (2017). A review of eye-tracking research in tourism. Current Issues in Tourism, 22(10), 1244–1261. https://doi.org/10.1080/13683500.2017.1367367.
Sharma, G. D., Thomas, A., & Paul, J. (2021). Reviving tourism industry post-COVID-19: A resilience-based framework. Tourism Management Perspectives, 37, 100786. https://doi.org/10.1016/j.tmp.2020.100786
Shen, J., Deng, C., & Gao, X. (2016). Attraction recommendation: Towards personalized tourism via collective intelligence. Neurocomputing, 173, 789-798. https://doi.org/10.1016/j.neucom.2015.08.030
Shokishalov, Z. H., & Wang, H. (2019). Applying eye tracking in information security. Procedia Computer Science, 150, 347-351. https://doi.org/10.1016/j.procs.2019.02.062
Sigala, M. (2020). Tourism and COVID-19: Impacts and implications for advancing and resetting industry and research. Journal of Business Research, 117, 312-321. https://doi.org/10.1016/j.jbusres.2020.06.015
Sigala, M., Kumar, S., Donthu, N., Sureka, R., & Joshi, Y. (2021). A bibliometric overview of the Journal of Hospitality and Tourism Management: Research contributions and influence. Journal of Hospitality and Tourism Management, 47, 273-288. https://doi.org/10.1016/j.jhtm.2021.04.005
Strömberg, H., Rexfelt, O., Karlsson, I. M., & Sochor, J. (2016). Trying on change–Trialability as a change moderator for sustainable travel behavior. Travel Behavior and Society, 4, 60-68. https://doi.org/10.1016/j.tbs.2016.01.002
Syed, S., & Spruit, M. (2017, October). Full-text or abstract? examining topic coherence scores using latent dirichlet allocation. In 2017 IEEE International conference on data science and advanced analytics (DSAA) (pp. 165-174), Tokyo, Japan. https://doi.org/10.1109/DSAA.2017.61
Talafidaryani, M. (2020). A text mining-based review of the literature on dynamic capabilities perspective in information systems research. Management Research Review, 44(2), 236-267. https://doi.org/10.1108/MRR-03-2020-0139
Trip, D., & Badulescu, D. (2020). Touchless Tourism: How New Tourism Will Look like. In Griffiths School of Management and IT Annual Conference on Business, Entrepreneurship and Ethics (pp. 85-100). Berlin: Springer. https://doi.org/10.1007/978-3-030-82755-7_6
Unguren, E., & Arslan, S. (2022). How does COVID-19 fear affect job insecurity and stress for hospitality employees? A moderated mediation model for age and financial status. Tourism & Management Studies, 18(3), 2022, 7-20. https://doi.org/10.18089/tms.2022.180301
van der Lans, R., & Wedel, M. (2017). Eye movements during search and choice. In Wierenga, B., van der Lans, R. (Eds.), Handbook of Marketing Decision Models. International Series in Operations Research & Management Science, vol 254. Berlin: Springer, Cham. https://doi.org/10.1007/978-3-319-56941-3_11
Vanhala, M., Lu, C., Peltonen, J., Sundqvist, S., Nummenmaa, J., & Järvelin, K. (2020). The usage of large data sets in online consumer behavior: A bibliometric and computational text-mining–driven analysis of previous research. Journal of Business Research, 106, 46-59. https://doi.org/10.1016/j.jbusres.2019.09.009
Walters, G., Jiang, Y., & Li, S. (2023). Physiological measurements in hospitality and tourism research: a systematic review and new theoretical directions. Journal of Hospitality & Tourism Research, 10963480231199990. https://doi.org/10.1177/10963480231199990
World Health Organization (WHO). Coronavirus disease (COVID-19) pandemic. Retrieved 12 March 2023 from https://www.who.int/emergencies/diseases/novel-coronavirus-2019
World Travel and Tourism Council (2020). Biometrics Importance and Benefits. Retrieved 12 March 2023 from https://wttc.org/Research/Insights/moduleId/1834/itemId/196/controller/DownloadRequest/action/QuickDownload
World Travel and Tourism Council (2022). Global economic impact trends. Retrieved 12 March 2023 from https://wttc.org/research/economic-impact
Wu, M. W., & Su, K. Y. (1993, September). Corpus-based automatic compound extraction with mutual information and relative frequency count. In Proceedings of Rocling VI Computational Linguistics Conference VI (pp. 207-216), Nantou, Taiwan.
Zamorano, M. M., Fernández-Laso, M. C., & de Esteban Curiel, J. (2020). Smart aırports: acceptance of technology by passengers. Cuadernos de Turismo, (45), 567-570.
Zhao, J., Feng, Q., Wu, P., Warner, J. L., Denny, J. C., & Wei, W. Q. (2019). Using topic modeling via non-negative matrix factorization to identify relationships between genetic variants and disease phenotypes: A case study of Lipoprotein (a)(LPA). PloS one, 14(2), e0212112. https://doi.org/10.1371/journal.pone.0212112
Zuboff, S. (2019) The age of surveillance capitalism. The fight for a human future at the new frontier of power. New York: Public Affairs.
Downloads
Published
Issue
Section
License
Copyright (c) 2024 Tourism & Management Studies
This work is licensed under a Creative Commons Attribution-NoDerivatives 4.0 International License.
The journal retains published articles’ copyrights, but they are simultaneously licensed under the Creative Commons Attribution License (CC BY-NC-ND), which allows individuals’ to share the relevant papers as long as authorship and publication in this journal are duly acknowledged.
