A business model adoption based on tourism innovationapplying a gratification theory to mobile applications

  1. Pedro Palos-Sanchez 1
  2. Jose Ramon Saura 2
  3. Felix Velicia-Martin 1
  4. Gabriel Cepeda-Carrion 3
  1. 1 university of Seville, Spain
  2. 2 University King Juan Carlos, Spain
  3. 3 niversity of Seville, Spain
Revista:
European Research on Management and Business Economics

ISSN: 2444-8834

Año de publicación: 2021

Volumen: 27

Número: 2

Páginas: 30-40

Tipo: Artículo

DOI: 10.1016/J.IEDEEN.2021.100149 DIALNET GOOGLE SCHOLAR lock_openIdus editor

Otras publicaciones en: European Research on Management and Business Economics

Resumen

The purpose of this paper is to improve understanding of Tourism Innovation by using a Uses and Gratifica-tion Theory model to investigate tourist intention to visit a city after reading other users'valuations of thedestination on Mobile Applications.The Uses and Gratification Theory (U&G) model was adapted to investigate the factors which influence tour-ist intention to visit a city. Satisfaction and Tourism Experience were added as external variables to the U&Gmodel. The original Convenience construct for mobile tourism applications was changed to Mobile Conve-nience for this study.A survey was carried out to investigate the factors which influence tourist intention to visit a City. 261 userswith different nationalities were asked about their experiences and feelings when using Runnin'City, whichwas the mobile tourism application used in this study. The results were analyzed with Partial Least SquaresStructural Equation Modeling (PLS-SEM). All the relationships of U&G were supported, except for Informationfor Tourism Experience.Self-Expression was found to be especially relevant and was moderated by Entertainment, Information andMobile Convenience which in turn influence Satisfaction, Tourism Experience and Intention to visit a City.The Gender and Running frequency variables were also investigated using multi-group analysis. The influ-ence of Mobile Convenience on Satisfaction was seen to be moderated by Gender, and the relationships ofInformation and Entertainment on satisfaction are moderated by Running Frequency.The results obtained with the proposed changes in the U&G model will be very useful for academics and alsofor designers and developers of mobile tourism apps as they show the special role played by Self-Expressionand Entertainment as relevant factors for the success of a mobile tourism app

Referencias bibliográficas

  • Ardissono, L., Kuflik, T., & Petrelli, D. (2012). Personalization in cultural heritage: theroad travelled and the one ahead. User modeling and user-adapted.int,22(1−2),73–99.
  • Bankole, F. O., Bankole, O. O., & Brown, I. (2011). Mobile banking adoption in Nigeria..The Electronic Journal of Information Systems in Developing Countries, 47.
  • Barclay, D., Higgins, C., & Thompson, R. (1995). The Partial Least Squares (PLS) a roachto causal modelling: Personal computer adoption and use as an illustration.Tech-nology Studies, Special Issue on Research Methodology, 285–309.
  • Bilgihan, A., Barreda, A., Okumus, F., & Nusair, K. (2016). Consumer perception ofknowledge-sharing in travel-related online social networks.Tourism Management,52, 287–296.
  • Bollen, K. A. (1989).Structural Equations with Latent Variables. New York: Willey.
  • Brooker, E., & Joppe, M. (2014). Developing a tourism innovation typology: Leveragingliminal insights.Journal of Travel Research,53(4), 500–508.
  • Carmines, E. G., & Zeller, R. A. (1979).Reliability and Validity Assessment. Beverly Hills,CA: Sage.
  • Cepeda-Carrion, G., Cegarra-Navarro, J. G., & Cillo, V. (2019). Tips to use partial leastsquares structural equation modelling (PLS-SEM) in knowledge management.Jour-nal of Knowledge Management.
  • Chang, Y., & Thorson, E. (2004). Television and web advertising synergies.Journal ofadvertising,33(2), 75–84.
  • Chin, W. W., & Newsted, P. R. (1999). Structural equation modeling analysis with smallsamples using partial least squares.Statistical Strategies for Small Sample Research,2, 307–342.
  • Chin, W. W. (1998). The partial least squares approach to structural equation modeling.[ed.], In G. A. Marcoulides (Ed.),Modern Methods for Business Research[ed.].(pp. 295−336). Mahwah, NJ: Lawrence Erlbaum Associates, Publisher.
  • Choi, E. K., Fowler, D., Goh, B., & Yuan, J. (2016a). Social media marketing: Applying theuses and gratifications theory in the hotel industry.Journal of Hospitality Marketing& Management,25(7), 771–796.
  • Choi, E. K., Fowler, D., Goh, B., & Yuan, J. (2016b). Social media marketing: Applying theuses and gratifications theory in the hotel industry.Journal of Hospitality Marketing& Management,25(7), 771–796.
  • Corrocher, N. (2011). The adoption of Web 2.0 services: An empirical Investigation.Technological Forecasting and Social Change,78(4), 547–558.
  • Dijkstra, T. K., & Henseler, J. (2015). Consistent and asymptotically normal PLS estima-tors for linear structural equations.Computational Statistics & Data Analysis,81(1),10–23.
  • Ducoffe, R. H. (1995). How consumers assess the value of advertising.Journal of CurrentIssues & Research in Advertising,17(1), 1–18.
  • Falk, R. F., & Miller, N. B. (1992).A Primer for Soft Modeling. Akron, OH: University ofAkron Press.
  • Felipe, C., Rold an, J., & Leal-Rodríguez, A. (2017). Impact of organizational culture val-ues on organizational agility.Sustainability,9(12), 2354.
  • Fornell, C., & Larcker, D. F. (1981). Evaluating structural equation models with unob-servable variables and measurement error.Journal of marketing research,18(1),39–50.
  • García-Magari~no, I., Palacios-Navarro, G., & Lacuesta, R. (2017). TABSAOND: A tech-nique for developing agent-based simulation apps and online tools with nondeter-ministic decisions.Simulation Modelling Practice and Theory,77,84–107.doi:10.1016/j.simpat.2017.05.006.
  • Garsous, G., Corderi, D., Velasco, M., & Colombo, A. (2017). Tax incentives and job crea-tion in the tourism sector of Brazil’s SUDENE area.World Development,96,87–101. G€otz, O., Liehr-Gobbers, K., & Krafft, M. (2010). Evaluation of structural equation mod-els using the partial least squares (PLS) approach. Handbook of partial least squares(pp. 691−711). Berlin, Heidelberg: Springer.
  • Gretzel, U., Sigala, M., Xiang, Z., & Koo, Ch. (2015). Smart tourism: Foundations anddevelopments.Electronic Markets,25(3), 179–188.
  • Ha, Y. W., Kim, J., Libaque-Saenz, C. F., Chang, Y., & Park, M. C. (2015). Use and gratifica-tions of mobile SNSs: Facebook and KakaoTalk in Korea.Telematics and Informatics,32(3), 425–438.
  • Hair, F., Sarstedt, J., Hopkins, L., & Kuelwieser, V. (2014). Partial least squares structuralequation modeling (PLS-SEM) An emerging tool in business research.EuropeanBusiness Review,26(2), 106–121.
  • Hair, J. F., Ringle, C. M., & Sarstedt, M. (2011). PLS-SEM: Indeed a silver bullet.Journal ofMarketing Theory and Practice,19(2), 139–151.
  • Hair, J., Babin, B., Money, A., & Samouel, P. (2005).Fundamentos de m etodos de pesquisaem administra ̧c~ao. Porto Alegre Bookman.
  • Hall, C. M., & G€ossling, S. (Eds.). (2013).Sustainable Culinary Systems: Local Foods, Inno-vation, and Tourism & Hospitality. Routledge.
  • Hardy, A., Hyslop, S., Booth, K., Robards, B., Aryal, J., Gretzel, U., & Eccleston, R. (2017).Tracking tourists’travel with smartphone-based GPS technology: a methodologi-cal discussion.Information Technology & Tourism,17(3), 255–274.
  • Henseler, J., Hubona, G., & Ray, P. A. (2016a). Using PLS path modeling in new technol-ogy research: Updated guidelines.Industrial Management & Data Systems,116(1),2–20.
  • Henseler, J., Ringle, C. M.&, & Sarstedt, M. (2016b). Testing measurement invariance of com-posites using partial least squares.International Marketing Review,33,405–431.P.
  • Henseler, J., Ringle, C. M., & Sinkovics, R. R. (2009). The use of partial least squares pathmodeling in international marketing.Advances in International Marketing,20(1),277–319.
  • Hew, J. J., Lee, V. H., Ooi, K. B., & Wei, J. (2015). What catalyses mobile apps usage intention:An empirical analysis.Industrial Management & Data Systems,115(7), 1269–1291.
  • Hjalager, A. M. (2010). A review of innovation research in tourism.Tourism Manage-ment,31(1), 1–12.
  • Ho, K. K., & See-To, E. W. (2018). The impact of the uses and gratifications of touristattraction fan page.Internet Research,28(3), 587–603.
  • Hoyer, W. D., & MacInnis, D. J. (2001).Consumer behavior. (2nd ed.). Boston, MA:Houghton Mifflin.
  • Hulland, J. (1999). Use of partial least squares (PLS) in strategic management research:A review of four recent studies.Strategic Management Journal,20, 195–204.
  • Katz, E., Blumler, J. G., & Gurevitch, M. (1973). Uses and gratifications research.The Pub-lic Opinion Quarterly,37(4), 509–523.
  • Leong, L. Y., Ooi, K. B., Chong, A. Y. L., & Lin, B. (2013). Modeling the stimulators of thebehavioral intention to use mobile entertainment: Does gender really matter?Computers in Human Behavior,29(5), 2109–2121.
  • Li, H., Liu, Y., Xu, X., Heikkil€a, J., & Van Der Heijden, H. (2015). Modeling hedonic is con-tinuance through the uses and gratifications theory: An empirical study in onlinegames.Computers in Human Behavior,48, 261–272.
  • Liang, S., Schuckert, M., Law, R., & Masiero, L. (2017). The relevance of mobile tourismand information technology: an analysis of recent trends and future researchdirections.Journal of Travel & Tourism Marketing,34(6), 732–748.
  • Malik, A., Dhir, A., & Nieminen, M. (2016). Uses and gratifications of digital photo shar-ing on Facebook.Telematics and Informatics,33(1), 129–138.
  • Matos, N., Mendes, J., & Valle, P. (2012). Revisiting the destination image constructthrough a conceptual model.Dos Algarves,21, 101–117.
  • Moscardo, G. (2008). Sustainable tourism innovation: Challenging basic assumptions.Tourism and Hospitality Research,8(1), 4–13.
  • Okazaki, S., Díaz-Martín, A. M., Rozano, M., & Men endez-Benito, H. D. (2015).UsingTwitter to engage with customers: a data mining approach. Internet Research.
  • Paget, E., Dimanche, F., & Mounet, J. P. (2010). A tourism innovation case: An actor-net-work approach.Annals of Tourism Research,37(3), 828–847.
  • Palos-Sanchez, P. R., Hernandez-Mogollon, J. M., & Campon-Cerro, A. M. (2017). Thebehavioral response to location based services: An examination of the influence ofsocial and environmental benefits, and privacy.Sustainability,9(11), 1988.doi:10.3390/su9111988.
  • Palos-Sanchez, P. R., Saura, J. R., & Correia, M. B. (2020).Do Tourism Applications’Qualityand User Experience Influence its Acceptance by Tourists?Review of Managerial Sci-ence. Springer. doi:10.1007/s11846-020-00396-y.
  • Palos-Sanchez, P., Saura, J. R., & Correia, M. B. (2021). Do tourism applications’qualityand user experience influence its acceptance by tourists?. Review of ManagerialScience, 1-37.xPalos-Sanchez, P., Saura, J. R., & Correia, M. B. (2021). Do tourismapplications’quality and user experience influence its acceptance by tourists?.Review of Managerial Science, 1-37.
  • Pantelidis, I. S. (2010). Electronic meal experience: A content analysis of online restau-rant comments.Cornell Hospitality Quarterly,51(4), 483–491.
  • Raacke, J., & Bonds-Raacke, J. (2008). MySpace and Facebook: Applying the uses andgratifications theory to exploring friend-networking sites.Cyberpsychology &behavior,11(2), 169–174.
  • Rauschnabel, P. A., Rossmann, A., & Dieck, tom. (2017). An adoption framework formobile augmented reality games: The case of Pok emon Go.Computers in HumanBehavior,76, 276–286.
  • Reyes-Menendez, A., Saura, J. R., & Stephen, B. T. (2020). Exploring key indicators of socialidentity in the #MeToo Era: Using discourse analysis in UGC.International Journal ofInformation Management,54, 102129. doi:10.1016/j.ijinfomgt.2020.102129. Rodríguez, I., Williams, A. M., & Hall, C. M. (2014). Tourism innovation policy: Imple-mentation and outcomes.Annals of Tourism Research,49(1), 76–93.
  • Saura, J. R. (2020). Using data sciences in digital marketing: Framework, methods, andperformance metrics.Journal of Innovation and Knowledge,1(2020). doi:10.1016/j.jik.2020.08.001.
  • Shorfuzzaman, M., & Alhussein, M. (2016). Modeling Learners’readiness to adoptmobile learning: A perspective from a GCC higher education institution.MobileInformation Systems. doi:10.1155/2016/6982824.
  • Smock, A. D., Ellison, N. B., Lampe, C., & Wohn, D. Y. (2011). Facebook as a toolkit: Auses and gratification approach to unbundling feature use.Computers in HumanBehavior,27(6), 2322–2329.
  • Soares, P. S. (2019).New Business Models in the Digital Economy Applied to the SmartTourism Sector-the Case of U. Porto s Digital Museum App.
  • Tajeddini, K., Ratten, V., & Denisa, M. (2017). Female tourism entrepreneurs in Bali,Indonesia.Journal of Hospitality and Tourism Management,31(1), 52–58.
  • Thakran, K., & Verma, R. (2013). The emergence of hybrid online distribution channelsin travel, tourism and hospitality.Cornell Hospitality Quarterly,54(3), 240–247.
  • Tsiotsou, R., & Ratten, V. (2010). Future research directions in tourism marketing.Mar-keting Intelligence & Planning,28(4), 533–544.
  • Verma, R., Stock, D., & McCarthy, L. (2012). Customer preferences for online, socialmedia, and mobile innovations in the hospitality industry.Cornell Hospitality Quar-terly,53(3), 183–186.
  • Xiang, Z., & Gretzel, U. (2010). Role of social media in online travel information search.Tourism management,31(2), 179–188.
  • Xiang, Z., Magnini, V. P., & Fesenmaier, D. R. (2015). Information technology and con-sumer behavior in travel and tourism: Insights from travel planning using theinternet.Journal of Retailing and Consumer Services,22, 244–249.
  • Zhou, T. (2011). The impact of privacy concern on user adoption of location-based serv-ices.Industrial Management & Data Systems,111, 212–226.
  • Zhou, T., Lu, Y., & Wang, B. (2010). Integrating TTF and UTAUT to explain mobile bank-ing user adoption.Computers in Human Behavior,26(4), 760–767.P. Palos-Sanchez, J.R. Saura, F. Velicia-Martin et al.European research on management and business economics 27 (2021) 10014911-