The intention of consumers to use augmented reality apps in gastronomy – case of Málaga

References

• Ahn, J. (2021a). Impact of cognitive aspects of food mobile application on customers’ behaviour. Current Issues in Tourism, 1–8. https://doi.org/10.1080/13683500.2021.1890700
   Google Scholar
• Ahn, J. (2021b). Promotion of customer patronizing behaviour by utilizing fairness experience in the food delivery application. Current Issues in Tourism, 24(17), 2386–2391. https://doi.org/10.1080/13683500.2020.1839026
   Web of Science ®Google Scholar
• Al Amin, M., Arefin, M. S., Alam, M. R., Ahammad, T., & Hoque, M. R. (2021). Using mobile food delivery applications during COVID-19 pandemic: An extended model of planned behavior. Journal of Food Products Marketing, 27(2), 105–126. https://doi.org/10.1080/10454446.2021.1906817
   Google Scholar
• Ajzen, I. (1991). The theory of planned behavior. Organizational Behaviour and Human Decision Processes, 50(2), 179–211. https://doi.org/10.1016/0749-5978(91)90020-T
   Web of Science ®Google Scholar
• Annaraud, K., & Berezina, K. (2020). Predicting satisfaction and intentions to use online food delivery: What really makes a difference? Journal of Foodservice Business Research, 23(4), 305–323. https://doi.org/10.1080/15378020.2020.1768039
   Google Scholar
• Azuma, R. T. (1997). A survey of augmented reality. Presence: Teleoperators y Virtual Environments, 6(4), 355–385. https://doi.org/10.1162/pres.1997.6.4.355
   Google Scholar
• Bankole, F. O., Bankole, O. O., & Brown, I. (2017). Influences on cell phone banking adoption in South Africa: An updated perspective. Journal of Internet Banking and Commerce, 22(3), 1–16.
   Google Scholar
• Barclay, D., Higgins, C., y Thompson, R. (1995). The partial least squares (PLS) a roach to causal modeling: Personal computer adoption and use as an illustration. Technology Studies, Special Issue on Research Methodology, 285–309.
   Google Scholar
• Batat, W. (2021). How augmented reality (AR) is transforming the restaurant sector: Investigating the impact of ‘Le Petit Chef’ on customers’ dining experiences.
   Google Scholar
• Beltrán, A. M., Vicente, A. F., y Peruzzi, G. (2021). Del viajero al turista hiperconectado. RECERCA. Revista de Pensament i Anàlisi, 26(1), 111–132. https://doi.org/10.6035/Recerca.2021.26.1.6
   Google Scholar
• Blattgerste, J., Renner, P., y Pfeiffer, T. (2018, June 15). Advantages of eye-gaze over head-gaze-based selection in virtual and augmented reality under varying field of views. Proceedings of the workshop on communication by gaze interaction.
   Google Scholar
• Broll, W., Lindt, I., Herbst, I., Ohlenburg, J., Braun, A. K., & Wetzel, R. (2008). Toward next-gen mobile AR games. IEEE Computer Graphics and Applications, 28(4), 40–48. https://doi.org/10.1109/MCG.2008.85
   Web of Science ®Google Scholar
• Brown, S. A., y Venkatesh, V. (2005). Model of adoption of technology in households: A baseline model test and extension incorporating household life cycle. MIS Quarterly, 29, 399–426. https://doi.org/10.2307/25148690
   Web of Science ®Google Scholar
• Bruner, G. C., y Kumar, A. (2005). Explaining consumer acceptance of handheld internet devices. Journal of Business Research, 58(5), 553–558. https://doi.org/10.1016/j.jbusres.2003.08.002
   Web of Science ®Google Scholar
• Byrne, B. M. (2001). Structural equation modeling with AMOS: Basic concepts, applications, and programming. Lawrence Erlbaum.
   Google Scholar
• Carmines, E. G., y Zeller, R. A. (1979). Reliability and validity assessment. Sage.
   Google Scholar
• Chang, S. J., Van Witteloostuijn, A., y Eden, l. (2010). From the editors: Common method variance in international business research. Journal of International Business Studies, 41(2), 178–184. https://doi.org/10.1057/jibs.2009.88
   Web of Science ®Google Scholar
• Chin, W. W. (1998). Comentario: Problemas y opinión sobre el modelado de ecuaciones estructurales. Mis Quarterly, 22(1), vii–xvi.
   Web of Science ®Google Scholar
• Choi, S. (2016). The flipside of ubiquitous connectivity enabled by smartphone-based social networking service: Social.
   Google Scholar
• Chong, A. Y. L. (2013). Predicting m-commerce adoption determinants: A neural network approach. Expert Systems with Applications, 40(2), 523–530. https://doi.org/10.1016/j.eswa.2012.07.068
   Web of Science ®Google Scholar
• Davis, F. D. (1989). Utilidad percibida, facilidad de uso percibida y aceptación del usuario de la tecnología de la información. MIS Quarterly, 13(3), 319–340. https://doi.org/10.2307/249008
   Web of Science ®Google Scholar
• Davis, F. D., Bagozzi, R. P., & Warshaw, P. R. (1989). User acceptance of computer technology: A comparison of two theoretical models. Management Science, 35(8), 982–1003. https://doi.org/10.1287/mnsc.35.8.982
   Web of Science ®Google Scholar
• De Cicco, R., Silva, S. C. L. D. C. E., & Alparone, F. R. (2021). ‘It’s on its way’: Chatbots applied for online food delivery services, social or task-oriented interaction style? Journal of Foodservice Business Research, 24(2), 140–164. https://doi.org/10.1080/15378020.2020.1826268
   Google Scholar
• DEEPFO. 2021 Base de datos de establecimientos de hostelería en la provincia de Málaga Fuente: Tripadvisor. Categoría: Base de datos de pago, recuperado el 4 agosto 2021.
   Google Scholar
• Delre, S. A., Jager, W., Bijmolt, T. H., y Janssen, M. A. (2010). Will it spread or not? The effects of social influences and network topology on innovation diffusion. Journal of Product Innovation Management, 27(2), 267–282. https://doi.org/10.1111/j.1540-5885.2010.00714.x
   Web of Science ®Google Scholar
• Dodds, W. B., Monroe, K. B., & Grewal, D. (1991). Effects of price, brand, and store information on buyers’ product evaluations. Journal of Marketing Research, 307–319. https://doi.org/10.1177/002224379102800305
   Web of Science ®Google Scholar
• Falk, R. F., y Miller, N. B. (1992). A primer for soft modeling. University of Akron Press.
   Google Scholar
• Fishbein, M., & Ajzen, I. (1975). Belief, attitude, intention, and behavior: An introduction to theory and research. Addison-Wesley.
   Google Scholar
• Fornell, C., y Larcker, D. F. (1981). Evaluación de modelos de ecuaciones estructurales con variables no observables y error de medición. Journal of Marketing Research, 18(1), 39–50. https://doi.org/10.1177/002224378101800104
   Web of Science ®Google Scholar
• Gârdan, D. A., Epuran, G., Paștiu, C. A., Gârdan, I. P., Jiroveanu, D. C., Tecău, A. S., & Prihoancă, D. M. (2021). Enhancing consumer experience through development of implicit attitudes using food delivery applications. Journal of Theoretical and Applied Electronic Commerce Research, 16(7), 2858–2882. https://doi.org/10.3390/jtaer16070157
   Web of Science ®Google Scholar
• Georgakopoulos, V. (2010). Food safety training: A model HACCP instructional technique. tourismos, 5(1), 55–72. https://doi.org/10.26215/tourismos.v5i1.160
   Google Scholar
• Götz, O., Liehr-Gobbers, K., & Krafft, M. (2010). Evaluation of structural equation models using the partial least squares (PLS) approach. In V. Esposito Vinzi, W. Chin, J. Henseler, & H. Wang (Eds.), Handbook of partial least squares (pp. 691–711). Springer.
   Google Scholar
• Gretzel, U., Sigala, M., Xiang, Z., & Koo, C. (2015). Turismo inteligente: Fundamentos y desarrollos. Electronic Mercados, 25(3), 179–188. https://doi.org/10.1007/s12525-015-0196-8
   Web of Science ®Google Scholar
• GWI agency and the Statista portal. (2021). https://www.gwi.com/data
   Google Scholar
• Ha, S., y Stoel, L. (2009). Consumer e-shopping acceptance: Antecedents in a technology acceptance model. Journal of Business Research, 62(5), 565–571. https://doi.org/10.1016/j.jbusres.2008.06.016
   Web of Science ®Google Scholar
• Haenlein, M., & Kaplan, A. M. (2004). A beginner’s guide to partial least squares analysis. Understanding Statistics, 3(4), 283–297. https://doi.org/10.1207/s15328031us0304_4
   Google Scholar
• Hair, J. F., Anderson, R. E., Tatham, R. L., & Black, W. C. (1999). Análisis multivariante (Vol. 491). Prentice Hall.
   Google Scholar
• Hair, J. F., Ringle, C. M., y Sarstedt, M. (2011). PLS-SEM: Indeed, a Silver Bullet.
   Google Scholar
• Hair, J. F., Ringle, C. M., & Sarstedt, M. (2014). Corrigendum to ‘editorial partial least squares structural equation modeling: Rigorous applications, better results and higher acceptance’ [LRP 46/1-2 (2013) 1–12]. Long Range Planning, 47(6), 392. https://doi.org/10.1016/j.lrp.2013.08.016
   Web of Science ®Google Scholar
• Hair, J. F., Sarstedt, M., & Ringle, C. M. (2019). Rethinking some of the rethinking of partial least squares. European Journal of Marketing, 53(4), 566–584. https://doi.org/10.1108/EJM-10-2018-0665
   Web of Science ®Google Scholar
• Henseler, J., Ringle, C. M., y Sinkovics, R. R. (2009). The use of partial least squares path modeling in international marketing. Advances in International Marketing, 20(1), 277–319. https://doi.org/10.1108/S1474-7979(2009)0000020014
   Google Scholar
• Hwang, J., Yoon, S. Y., & Bendle, L. J. (2012). Desired privacy and the impact of crowding on customer emotions and approach-avoidance responses: Waiting in a virtual reality restaurant. International Journal of Contemporary Hospitality Management. https://doi.org/10.1108/09596111211206150
   Google Scholar
• Jiang, S., Moyle, B., Yung, R., Tao, L., & Scott, N. (2022). Augmented reality and the enhancement of memorable tourism experiences at heritage sites. Current Issues in Tourism, 1–16. https://doi.org/10.1080/13683500.2022.2026303
   Google Scholar
• Karjaluoto, H., Jayawardhena, C., Leppäniemi, M., & Pihlström, M. (2012). How value and trust influence loyalty in wireless telecommunications industry. Telecommunications Policy, 36(8), 636–649. https://doi.org/10.1016/j.telpol.2012.04.012
   Web of Science ®Google Scholar
• Kim, S. S., y Malhotra, N. K. (2005). Predicting system usage from intention and past use: Scale issues in the predictors. Decision Sciences, 36(1), 187–196. https://doi.org/10.1111/j.1540-5915.2005.00070.x
   Web of Science ®Google Scholar
• Kim, S. S., Malhotra, N. K., y Narasimhan, S. (2005). Research note – two competing perspectives on automatic use: A theoretical and empirical comparison. Information Systems Research, 16(4), 418–432. https://doi.org/10.1287/isre.1050.0070
   Web of Science ®Google Scholar
• Kock, N. (2015). Sesgo de método común en PLS-SEM: Un enfoque de evaluación de colinealidad completa. En t. J. e Collab, 11(4), 1–10. https://doi.org/10.4018/ijec.2015100101
   Google Scholar
• Limayem, M., Hirt, S. G., y Cheung, C. M. (2007). How habit limits the predictive power of intention: The case of information systems continuance. Mis Quarterly, 31, 705–737. https://doi.org/10.2307/25148817
   Web of Science ®Google Scholar
• Loijens, L. W. (2017). Augmented reality for food marketers and consumers.
   Google Scholar
• Loureiro, S. M. C., Guerreiro, J., & Ali, F. (2020). 20 years of research on virtual reality and augmented reality in tourism context: A text-mining approach. Tourism Management, 77, 104028. https://doi.org/10.1016/j.tourman.2019.104028
   Web of Science ®Google Scholar
• Malaquias, R. F., y Hwang, Y. (2019). Uso de banca móvil: Un estudio comparativo con participantes brasileños y estadounidenses. International Journal of Information Management, 44, 132–140. https://doi.org/10.1016/j.ijinfomgt.2018.10.004
   Web of Science ®Google Scholar
• Manchanda, M., & Deb, M. (2021). Effects of multisensory virtual reality on virtual and physical tourism during the COVID-19 pandemic. Current Issues in Tourism, 1–19. https://doi.org/10.1080/13683500.2021.1978953
   Web of Science ®Google Scholar
• Mateos, M. R. (2013). El turismo experiencial como forma de turismo responsable e intercultural. In relaciones interculturales en la diversidad (pp. 199-217). Cátedra Intercultural.
   Google Scholar
• Milgram, P., & Kishino, F. (1994). A taxonomy of mixed reality visual displays. IEICE TRANSACTIONS on Information and Systems, 77(12), 1321–1329.
   Google Scholar
• Milgram, P., Takemura, H., Utsumi, A., y Kishino, F. (1995). Augmented reality: A class of displays on the reality-virtuality continuum. In Telemanipulator and Telepresence Technologies, 2351, 282–292. International Society for Optics and Photonics. https://doi.org/10.1117/12.197321
   Google Scholar
• Özkul, E., & Kumlu, S. T. (2019). Augmented reality applications in tourism. International Journal of Contemporary Tourism Research, 3(2), 107–122. https://doi.org/10.30625/ijctr.625192
   Google Scholar
• Panou, C., Ragia, L., Dimelli, D., y Mania, K. (2018). An architecture for mobile outdoors augmented reality for cultural heritage. ISPRS International Journal of Geo-Information, 7(12), 463. https://doi.org/10.3390/ijgi7120463
   Web of Science ®Google Scholar
• Park, J., Gunn, F., Lee, Y., & Shim, S. (2015). Consumer acceptance of a revolutionary technology-driven product: The role of adoption in the industrial design development. Journal of Retailing and Consumer Services, 26, 115–124. https://doi.org/10.1016/j.jretconser.2015.05.003
   Web of Science ®Google Scholar
• Park, S., & Stangl, B. (2020). Augmented reality experiences and sensation seeking. Tourism Management, 77, 104023. https://doi.org/10.1016/j.tourman.2019.104023
   Web of Science ®Google Scholar
• Podsakoff, P. M., MacKenzie, S. B., Lee, J. Y., y Podsakoff, N. P. (2003). Common method biases in behavioral research: A critical review of the literature and recommended remedies. Journal of Applied Psychology, 88(5), 879–903. https://doi.org/10.1037/0021-9010.88.5.879
   PubMed Web of Science ®Google Scholar
• Ringle, C. M., Wende, S., & Will, A. (2010). Finite mixture partial least squares analysis: Methodology and numerical examples. In V. Esposito Vinzi, W. Chin, J. Henseler, & H. Wang (Eds.), Handbook of partial least squares (pp. 195–218). Springer.
   Google Scholar
• Son, J. Y., y Benbasat, I. (2007). Organizational buyers’ adoption and use of B2B electronic marketplaces: Efficiency-and legitimacy-oriented perspectives. Journal of Management Information Systems, 24(1), 55–99. https://doi.org/10.2753/MIS0742-1222240102
   Web of Science ®Google Scholar
• Spence, C., Okajima, K., Cheok, A. D., Petit, O., & Michel, C. (2016). Eating with our eyes: From visual hunger to digital satiation. Brain and Cognition, 110, 53–63. https://doi.org/10.1016/j.bandc.2015.08.006
   PubMed Web of Science ®Google Scholar
• Strategic Plan of the City of Málaga (Plan estratégico de Málaga). (2021–2024). Recuperado de. http://s3.malagaturismo.com/files/933/933/plan-estrategico-turismo-2021-2024-def.pdf
   Google Scholar
• Su, D. N., Nguyen, N. A. N., Nguyen, L. N. T., Luu, T. T., & Nguyen-Phuoc, D. Q. (2022). Modeling consumers’ trust in mobile food delivery apps: Perspectives of technology acceptance model, mobile service quality and personalization-privacy theory. Journal of Hospitality Marketing & Management, 1–35. https://doi.org/10.1080/19368623.2022.2020199
   Web of Science ®Google Scholar
• Suhartanto, D., Helmi Ali, M., Tan, K. H., Sjahroeddin, F., & Kusdibyo, L. (2019). Loyalty toward online food delivery service: The role of e-service quality and food quality. Journal of Foodservice Business Research, 22(1), 81–97. https://doi.org/10.1080/15378020.2018.1546076
   Google Scholar
• Tsai, S. P. (2020). Augmented reality enhancing place satisfaction for heritage tourism marketing. Current Issues in Tourism, 23(9), 1078–1083. https://doi.org/10.1080/13683500.2019.1598950
   Web of Science ®Google Scholar
• Van der Heijden, H. (2004). User acceptance of hedonic information systems. MIS Quarterly, 28, 695–704. https://doi.org/10.2307/25148660
   Web of Science ®Google Scholar
• Venkatesh, V., y Bala, H. (2008). Technology acceptance model 3 and a research agenda on interventions. Decision Sciences, 39(2), 273–315. https://doi.org/10.1111/j.1540-5915.2008.00192.x
   Web of Science ®Google Scholar
• Venkatesh, V., & Davis, F. D. (2000). A theoretical extension of the technology.
   Google Scholar
• Venkatesh, V., Morris, M. G., Davis, G. B., & Davis, F. D. (2003). User acceptance of information technology: Toward a unified view. MIS Quarterly, 27, 425–478. https://doi.org/10.2307/30036540
   Web of Science ®Google Scholar
• Venkatesh, V., Thong, J. Y., y Xu, X. (2012). Consumer acceptance and use of information technology: Extending the unified theory of acceptance and use of technology. MIS Quarterly, 36(1), 157–178. https://doi.org/10.2307/41410412
   Web of Science ®Google Scholar
• Villalba, M. (2015). ‘Sublimotion renueva experiencia con gafas de realidad virtual’ [artículo en línea]. Diario Abierto (2 de marzo). [Fecha de consulta: 22 de diciembre de 2017] https://www.diarioabierto.es/254027/sublimotion-renueva-experiencia-con- gafas-de-realidad-virtual
   Google Scholar
• Wixom, B. H., y Todd, P. A. (2005). A theoretical integration of user satisfaction and technology acceptance. Information Systems Research, 16(1), 85–102. https://doi.org/10.1287/isre.1050.0042
   Web of Science ®Google Scholar
• Yuan, D., Lin, Z., Filieri, R., Liu, R., y Zheng, M. (2020). Manejo de la crisis de daños a los productos en la era digital: El papel del compromiso de la comunidad de marcas en línea del consumidor. Journal of Business Research, 115, 38–47. https://doi.org/10.1016/j.jbusres.2020.04.044
   Web of Science ®Google Scholar
• Yung, R., & Khoo-Lattimore, C. (2019). New realities: A systematic literature review on virtual reality and augmented reality in tourism research. Current Issues in Tourism, 22(17), 2056–2081. https://doi.org/10.1080/13683500.2017.1417359
   Web of Science ®Google Scholar