Araştırma Makalesi
BibTex RIS Kaynak Göster

Restoranlar için İnsansı Robotların Kabulünde Kuşaklar Arası Farklılığın Düzenleyici Rolü: Sosyalleşme ve Yenilikçilik ile BTKKT Modeline Yönelik Bir Genişletme Çalışması

Yıl 2022, Cilt: 6 Sayı: 2, 635 - 663, 29.09.2022
https://doi.org/10.32572/guntad.1037791

Öz

Bu araştırmanın amacı, birleştirilmiş teknoloji kabul ve kullanım teorisi’ni [BTKKT (UTAUT)] insansı robot bağlamında ve restoran özelinde doğrulamak ile birlikte turistik sosyalleşme ve turistik yenilikçilik değişkenleri aracılığıyla teoriye katkıda bulunmaktır. Bu kapsamda, restoran deneyimi olan 363 katılımcıdan elde edilen veriler, yapısal eşitlik modellemesine tabi tutulmuştur. Araştırma sonucunda, BTKKT modeline dair yordayıcı değişkenler olan performans beklentisi, çaba beklentisi, sosyal etki ve kolaylaştırıcı koşullar değişkenlerinin tamamının restoranlarda insansı robotları deneyimlemeye yönelik davranışsal niyeti pozitif ve anlamlı yönde etkilediği tespit edilmiştir. Bunlar içerisinde, kolaylaştırıcı koşulların en güçlü etki düzeyine sahip olan değişken olarak ön plana çıktığı görülmüştür. Performans beklentisi ve sosyal etki, davranışsal niyeti açıklayan diğer en güçlü iki öncül değişken olarak ortaya çıkmıştır. Bununla birlikte, yenilikçiliğin davranışsal niyeti pozitif yönde etkilediği görülmüş, sosyalleşme değişkeninin ise herhangi bir etkiye sahip olmadığı görülmüştür. Yine, sosyal etki, X kuşağı için en güçlü açıklayıcı olarak tespit edilmiştir. Düzenleyici değişken olarak, Y-Z kuşağındaki katılımcıların, insansı robotları benimsemede kullanım kolaylığına X kuşağına kıyasla daha fazla ehemmiyet gösterdikleri görülmüştür.

Kaynakça

  • Aharony, N. (2015). Why do students use What’s App? – an exploratory study. Aslib Journal of Information Management, 67(2), 136–158. doi:10.1108/AJIM-11-2014-0148/FULL/PDF
  • Akdim, K., Belanche, D. ve Flavián, M. (2021). Attitudes toward service robots: analyses of explicit and implicit attitudes based on anthropomorphism and construal level theory. International Journal of Contemporary Hospitality Management. doi:10.1108/IJCHM-12-2020-1406
  • Aslantürk, E. ve Erdem, A. (2021). Teknoloji Kullanımına Yönelik Tutumun Otellerde Robot Kabul Edilebilirliği Üzerine Etkisi. Journal of Global Tourism and Technology Research, 2(2), 102–115.
  • Asoba, S. N. ve Mefi, N. P. (2022). The Generational Dimensıon of Technology Acceptance: The Case of Generatıon X and Millennial Managers. Journal of Management Information and Decision Sciences, 25(4), 1–7.
  • Balcı, A. (2011). Sosyal Bilimlerde Araştırma: Yöntem, Teknik ve İlkeler (9th bs.). Ankara: Pegem.
  • Belanche, D., Casaló, L. V. ve Flavián, C. (2020). Frontline robots in tourism and hospitality: service enhancement or cost reduction? Electronic Markets, 1–16. doi:10.1007/S12525-020-00432-5
  • Brown, M. A. (1984). Change mechanisms in the diffusion of residential energy conservation practices: an empirical study. Technological Forecasting and Social Change, 25(2), 123–138. doi:10.1016/0040-1625(84)90087-8
  • Buhalis, D. ve Leung, R. (2018). Smart hospitality—Interconnectivity and interoperability towards an ecosystem. International Journal of Hospitality Management, 71, 41–50. doi:10.1016/J.IJHM.2017.11.011
  • Büyüköztürk, Ş., Kılıç-Çakmak, E., Akgün, Ö. E., Karadeniz, Ş. ve Demirel, F. (2013). Bilimsel Araştırma Yöntemleri (15.). Ankara: Pegem.
  • Byrd, K., Fan, A., Her, E. S., Liu, Y., Almanza, B. ve Leitch, S. (2021). Robot vs human: expectations, performances and gaps in off-premise restaurant service modes. International Journal of Contemporary Hospitality Management. doi:10.1108/IJCHM-07-2020-0721
  • Cai, W., Richter, S. ve McKenna, B. (2019). Progress on technology use in tourism. Journal of Hospitality and Tourism Technology, 10(4), 651–672. doi:10.1108/JHTT-07-2018-0068
  • Çakır, İ. ve Kazançoğlu, İ. (2020). Sanal Market Alışverişi Yapma Niyetinde Genişletilmiş Teknoloji Kabul Modeli Bileşenleri ile Risk Algılarının Etkisi. Manisa Celal Bayar Üniversitesi Sosyal Bilimler Dergisi, 18(2), 305–326.
  • Calvo-Porral, C. ve Pesqueira-Sanchez, R. (2020). Generational differences in technology behaviour: comparing millennials and Generation X. Kybernetes, 49(11), 2755–2772. doi:10.1108/K-09-2019-0598/FULL/PDF
  • Campbell, S., Greenwood, M., Prior, S., Shearer, T., Walkem, K., Young, S., Bywaters, D. ve Walker, K. (2020). Purposive sampling: complex or simple? Research case examples: Journal of Research in Nursing, 25(8), 652–661. doi:10.1177/1744987120927206
  • Cha, S. S. (2020). Customers’ intention to use robot-serviced restaurants in Korea: relationship of coolness and MCI factors. International Journal of Contemporary Hospitality Management, 32(9), 2947–2968. doi:10.1108/IJCHM-01-2020-0046
  • Choi, Y., Choi, M., Oh, M. (Moon) ve Kim, S. (Sam). (2019). Service robots in hotels: understanding the service quality perceptions of human-robot interaction. Journal of Hospitality Marketing & Management, 29(6), 613–635. doi:10.1080/19368623.2020.1703871
  • Christou, P., Simillidou, A. ve Stylianou, M. C. (2020). Tourists’ perceptions regarding the use of anthropomorphic robots in tourism and hospitality. International Journal of Contemporary Hospitality Management, 32(11), 3665–3683. doi:10.1108/IJCHM-05-2020-0423
  • Cohen, E. (1972). Toward a sociology of international tourism. Social Research, 164–182. https://www.jstor.org/stable/pdf/40970087.pdf adresinden erişildi.
  • Compeau, D. R. ve Higgins, C. A. (1995). Computer self-efficacy: Development of a measure and initial test. MIS Quarterly: Management Information Systems, 19(2), 189–210. doi:10.2307/249688
  • Dai, B., Larnyo, E., Tetteh, E. A., Aboagye, A. K. ve Musah, A.-A. I. (2019). Factors Affecting Caregivers’ Acceptance of the Use of Wearable Devices by Patients With Dementia: An Extension of the Unified Theory of Acceptance and Use of Technology Model: American Journal of Alzheimer’s Disease and Other Dementias, 35, 1–11. doi:10.1177/1533317519883493
  • Davis, F. D. (1993). User acceptance of information technology: System characteristics, user perceptions and behavioral impacts. International Journal of Man-Machine Studies. doi:10.1006/imms.1993.1022
  • Durna, E. C. ve Taşçıoğlu-Baysal, H. (2021). Ziyaretçilerin Otel İşletmelerine Yönelik Yorum ve Şikayetlerinin İncelenmesi: Dünyanın İlk Robotik Oteli Olan “Henn na Otel” Örneği. Turizm ve İşletme Bilimleri Dergisi, 1(2), 85–102.
  • Escobar-Rodríguez, T. ve Carvajal-Trujillo, E. (2014). Online purchasing tickets for low cost carriers: An application of the unified theory of acceptance and use of technology (UTAUT) model. Tourism Management, 43, 70–88. doi:10.1016/J.TOURMAN.2014.01.017
  • Fabrigar, L. R. ve Wegener, D. T. (2012). Exploratory Factor Analysis: Understanding Statistics. New York: Oxford University Press.
  • Fakfare, P., Talawanich, S. ve Wattanacharoensil, W. (2020). A scale development and validation on domestic tourists’ motivation: the case of second-tier tourism destinations. https://doi.org/10.1080/10941665.2020.1745855, 25(5), 489–504. doi:10.1080/10941665.2020.1745855
  • Fan, W., Liu, J., Zhu, S. ve Pardalos, P. M. (2020). Investigating the impacting factors for the healthcare professionals to adopt artificial intelligence-based medical diagnosis support system (AIMDSS). Annals of Operations Research, 294(1–2), 567–592. doi:10.1007/S10479-018-2818-Y/FIGURES/3
  • Faul, F., Erdfelder, E., Lang, A.-G. ve Buchner, A. (2007). G*Power 3: A flexible statistical power analysis program for the social, behavioral, and biomedical sciences. Behavior Research Methods, 39(2), 175–191. doi:10.3758/BF03193146
  • Fernández-Llamas, C., Conde, M. A., Rodríguez-Lera, F. J., Rodríguez-Sedano, F. J. ve García, F. (2018). May I teach you? Students’ behavior when lectured by robotic vs. human teachers. Computers in Human Behavior, 80, 460–469. doi:10.1016/J.CHB.2017.09.028
  • Fornell, C. ve Larcker, D. F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research, 18(1), 39. doi:10.2307/3151312
  • Foxall, G. R., Goldsmith, R. E. ve Brown, S. (1998). Consumer Psychology for Marketing. Cengage Learning EMEA, 1.
  • Fuentes-Moraleda, L., Díaz-Pérez, P., Orea-Giner, A., Muñoz- Mazón, A. ve Villacé-Molinero, T. (2020). Interaction between hotel service robots and humans: A hotel-specific Service Robot Acceptance Model (sRAM). Tourism Management Perspectives, 36, 100751. doi:10.1016/J.TMP.2020.100751
  • Ghazali, A. S., Ham, J., Barakova, E. ve Markopoulos, P. (2020). Persuasive Robots Acceptance Model (PRAM): Roles of Social Responses Within the Acceptance Model of Persuasive Robots. International Journal of Social Robotics, 12, 1075–1092.
  • Go, H., Kang, M. ve Suh, S. B. C. (2020). Machine learning of robots in tourism and hospitality: interactive technology acceptance model (iTAM) – cutting edge. Tourism Review, 75(4), 625–636. doi:10.1108/TR-02-2019-0062
  • Hair, F. H., Black, W. C., Babin, B. J. ve Anderson, R. E. (2019). Multivariate Data Analysis (Eighth Edi.). Andover: Cengage.
  • Hair, J. (2009). Multivariate Data Analysis: A Global Perspective. Faculty Publications (7. bs.). Prentice Hall. https://digitalcommons.kennesaw.edu/facpubs/2925 adresinden erişildi.
  • Hair, J. F., Sarstedt, M., Ringle, C. M. ve Gudergan, S. P. (2018). Advanced Issues in Partial Least Squares Structural Equation Modeling. California: Sage Publications.
  • Hair, J., Howard, M. C. ve Nitzl, C. (2020). Assessing measurement model quality in PLS-SEM using confirmatory composite analysis. Journal of Business Research, 109, 101–110. doi:10.1016/j.jbusres.2019.11.069
  • Hair, J., Hult, G. T. M., Ringle, C. M. ve Sarstedt, M. (2017). A primer on partial least squares structural equation modeling (PLS-SEM) (2. bs.). Los Angeles: Sage.
  • Hair, J., Risher, J. J., Sarstedt, M. ve Ringle, C. M. (2019). When to use and how to report the results of PLS-SEM. European Business Review, 31(1), 2–24. doi:10.1108/EBR-11-2018-0203
  • Henseler, J., Ringle, C. M. ve Sarstedt, M. (2015). A new criterion for assessing discriminant validity in variance-based structural equation modeling. Journal of the Academy of Marketing Science, 43(1), 115–135. doi:10.1007/s11747-014-0403-8
  • Hsu, C. L. ve Lin, J. C. C. (2008). Acceptance of blog usage: The roles of technology acceptance, social influence and knowledge sharing motivation. Information & Management, 45(1), 65–74. doi:10.1016/J.IM.2007.11.001
  • Hui-Wen Chuah, S., Cheng-Xi Aw, E. ve Cheng, C.-F. (2021). A silver lining in the COVID-19 cloud: examining customers’ value perceptions, willingness to use and pay more for robotic restaurants. Journal of Hospitality Marketing & Management. doi:10.1080/19368623.2021.1926038
  • Hwang, J., Kim, J. J. ve Lee, K. W. (2021). Investigating consumer innovativeness in the context of drone food delivery services: Its impact on attitude and behavioral intentions. Technological Forecasting and Social Change, 163, 120433. doi:10.1016/J.TECHFORE.2020.120433
  • Hwang, J., Park, S. ve Kim, I. (2020). Understanding motivated consumer innovativeness in the context of a robotic restaurant: The moderating role of product knowledge. Journal of Hospitality and Tourism Management, 44, 272–282. doi:10.1016/J.JHTM.2020.06.003
  • İbiş, S. (2019). Turizm Endüstrisinde Robotlaşma. Türk Turizm Araştırmaları Dergisi, 3(3), 403–420.
  • Im, I., Hong, S. ve Kang, M. S. (2011). An international comparison of technology adoption: Testing the UTAUT model. Information & Management, 48(1), 1–8. doi:10.1016/J.IM.2010.09.001 Ivanov, S. ve Webster, C. (2019). Perceived appropriateness and intention to use service robots in tourism. In Pesonen, J. & Neidhardt, J. (Ed.) Information and Communication Technologies in Tourism 2019, Proceedings of the International Conference içerisinde, Nicosia, Cyprus, 30.01-01.02.2019, sf. 237-248.
  • Jeon, H. M., Sung, H. J. ve Kim, H. Y. (2020). Customers’ acceptance intention of self-service technology of restaurant industry: expanding UTAUT with perceived risk and innovativeness. Service Business, 14(4), 533–551. doi:10.1007/S11628-020-00425-6/TABLES/4
  • Kaba, B. ve Touré, B. (2014). Understanding information and communication technology behavioral intention to use: Applying the UTAUT model to social networking site adoption by young people in a least developed country. Journal of the Association for Information Science and Technology, 65(8), 1662–1674. doi:10.1002/ASI.23069
  • Kağıtçıbaşı, C. (1983). Women and development in Turkey. International Journal of Turkish Studies, 2, 59–70.
  • Kamboj, S. ve Joshi, R. (2020). Examining the factors influencing smartphone apps use at tourism destinations: a UTAUT model perspective. International Journal of Tourism Cities, 7(1), 135–157. doi:10.1108/IJTC-05-2020-0094
  • Khalilzadeh, J., Ozturk, A. B. ve Bilgihan, A. (2017). Security-related factors in extended UTAUT model for NFC based mobile payment in the restaurant industry. Computers in Human Behavior, 70, 460–474. doi:10.1016/J.CHB.2017.01.001
  • Khechine, H., Lakhal, S., Pascot, D. ve Bytha, A. (2014). UTAUT Model for Blended Learning: The Role of Gender and Age in the Intention to Use Webinars. Interdisciplinary Journal of E-Learning and Learning Objects, 10, 33–52.
  • Kim, D. Y., Park, J. ve Morrison, A. M. (2008). A model of traveller acceptance of mobile technology. International Journal of Tourism Research, 10(5), 393–407. doi:10.1002/jtr.669
  • Kim, D. Y. ve Park, S. (2019). Rethinking millennials: how are they shaping the tourism industry? Asia Pacific Journal of Tourism Research, 25(1), 1–2. doi:10.1080/10941665.2019.1667607
  • Kim, J. J., Choe, J. Y. (Jacey) ve Hwang, J. (2020). Application of consumer innovativeness to the context of robotic restaurants. International Journal of Contemporary Hospitality Management, 33(1), 224–242. doi:10.1108/IJCHM-06-2020-0602
  • Kim, M. J. ve Hall, C. M. (2020). What drives visitor economy crowdfunding? The effect of digital storytelling on unified theory of acceptance and use of technology. Tourism Management Perspectives, 34, 100638. doi:10.1016/J.TMP.2020.100638
  • Kim, S., Kim, J., Badu-Baiden, F., Giroux, M. ve Choi, Y. (2021). Preference for robot service or human service in hotels? Impacts of the COVID-19 pandemic. International Journal of Hospitality Management, 93, 102807. doi:10.1016/J.IJHM.2020.102795
  • Kizir, E. ve Bozbay, Z. (2021). Moda Ürünleri Satan Mobil Alışveriş Uygulamalarının Kabulünün Birleştirilmiş Teknoloji Kabul ve Kullanım Teorisi Çerçevesinde İncelenmesi. Marmara Üniversitesi Öneri Dergisi, 16(55), 286–310.
  • Lian, J. W. ve Yen, D. C. (2014). Online shopping drivers and barriers for older adults: Age and gender differences. Computers in Human Behavior, 37, 133–143. doi:10.1016/J.CHB.2014.04.028
  • Lu, L., Cai, R. ve Gursoy, D. (2019). Developing and validating a service robot integration willingness scale. International Journal of Hospitality Management, 80, 36–51. doi:10.1016/J.IJHM.2019.01.005
  • Magsamen-Conrad, K., Upadhyaya, S., Joa, C. Y. ve Dowd, J. (2015). Bridging the divide: Using UTAUT to predict multigenerational tablet adoption practices. Computers in Human Behavior, 50, 186–196. doi:10.1016/J.CHB.2015.03.032
  • Mang, C. F., Piper, L. A. ve Brown, N. R. (2016). The Incidence of Smartphone Usage among Tourists. International Journal of Tourism Research, 18(6), 591–601. doi:10.1002/JTR.2076
  • Mo, C. min, Howard, D. R. ve Havitz, M. E. (1993). Testing an international tourist role typology. Annals of Tourism Research, 20(2), 319–335. doi:10.1016/0160-7383(93)90058-B
  • Neuhofer, B., Buhalis, D. ve Ladkin, A. (2014). A Typology of Technology-Enhanced Tourism Experiences. International Journal of Tourism Research, 16(4), 340–350. doi:10.1002/JTR.1958
  • Nüfusu. (2022). Ankara Nüfusu 2021 2022. 4 Haziran 2022 tarihinde https://www.nufusu.com/il/ankara-nufusu adresinden erişildi.
  • Özekici, Y. K. (2019). Yerli Halk-Turist Etkileşimi ve Bir Model Önerisi. Gazi University.
  • Özgürel, G. ve Kılınç-Şahin, S. (2021). Turizmde Robotlaşma: Yiyecek-İçecek Sektöründe Robot Şefler ve Robot Garsonlar. OPUS, 11(8), 1849–1882. doi:10.26466/opus.899296
  • Palos-Sanchez, P., Jose, ·, Saura, R., Correia, M. B., Saura, J. R. ve Pt, M. (2021). Do tourism applications’ quality and user experience influence its acceptance by tourists? Review of Managerial Science, 15, 1205–1241. doi:10.1007/s11846-020-00396-y
  • Pan, S. ve Jordan-Marsh, M. (2010). Internet use intention and adoption among Chinese older adults: From the expanded technology acceptance model perspective. Computers in Human Behavior, 26(5), 1111–1119. doi:10.1016/J.CHB.2010.03.015
  • Parasuraman, A. (2000). Technology Readiness Index (Tri): A multiple-item scale to measure readiness to embrace new technologies. Journal of Service Research, 2(4), 307–320.
  • Park, C. (2004). Efficient or enjoyable? Consumer values of eating-out and fast food restaurant consumption in Korea. International Journal of Hospitality Management, 23(1), 87–94. doi:10.1016/J.IJHM.2003.08.001
  • Park, S. ve Stangl, B. (2020). Augmented reality experiences and sensation seeking. Tourism Management, 77(October 2019), 104023. doi:10.1016/j.tourman.2019.104023
  • Pourfakhimi, S., Duncan, T. ve Coetzee, W. (2019). A critique of the progress of eTourism technology acceptance research: time for a hike? Journal of Hospitality and Tourism Technology, 10(4), 689–746.
  • Rahman, M. M., Lesch, M. F., Horrey, W. J. ve Strawderman, L. (2017). Assessing the utility of TAM, TPB, and UTAUT for advanced driver assistance systems. Accident Analysis & Prevention, 108, 361–373.
  • Ramadan, Z. B., Farah, M. F. ve Mrad, M. (2017). An adapted TPB approach to consumers’ acceptance of service-delivery drones. Technology Analysis and Strategic Management, 29(7), 817–828. doi:10.1080/09537325.2016.1242720
  • Revfine. (2020). 8 Examples of Robots Being Used in the Hospitality Industry. 16 Aralık 2021 tarihinde https://www.revfine.com/robots-hospitality-industry/ adresinden erişildi.
  • Ringle, C. M., Wende, S. ve Becker, J.-M. (2015). SmartPLS 3. Boenningstedt: SmartPLS GmbH, http://www. smartpls. com.
  • Robinson, L., Marshall, G. W. ve Stamps, M. B. (2005). Sales force use of technology: Antecedents to technology acceptance. Journal of Business Research, 58(12), 1623–1631. doi:10.1016/j.jbusres.2004.07.010
  • Ryan, T. ve Xenos, S. (2011). Who uses Facebook? An investigation into the relationship between the Big Five, shyness, narcissism, loneliness, and Facebook usage. Computers in Human Behavior, 27(5), 1658–1664. doi:10.1016/j.chb.2011.02.004
  • San Martín, H. ve Herrero, Á. (2012). Influence of the user’s psychological factors on the online purchase intention in rural tourism: Integrating innovativeness to the UTAUT framework. Tourism Management, 33(2), 341–350. doi:10.1016/J.TOURMAN.2011.04.003
  • Seo, K. H. ve Lee, J. H. (2021). The Emergence of Service Robots at Restaurants: Integrating Trust, Perceived Risk, and Satisfaction. Sustainability, 13(8), 4431. doi:10.3390/SU13084431
  • Seyitoğlu, F., Ivanov, S., Atsız, O. ve Çifçi, İ. (2021). Robots as restaurant employees - A double-barrelled detective story. Technology in Society, 67, 101779. doi:10.1016/J.TECHSOC.2021.101779
  • Shin, H. H. ve Jeong, M. (2020). Guests’ perceptions of robot concierge and their adoption intentions. International Journal of Contemporary Hospitality Management, 32(8), 2613–2633. doi:10.1108/IJCHM-09-2019-0798
  • Siang, T. G., Ahmad, Z. B., Bin, K., Aziz, K. B. ve Suhaifi, S. B. (2019). Augmented reality mobile application for museum: A technology acceptance study. 6th International Conference on Research and Innovation in Information Systems (ICRIIS) içerisinde, Londra, 26-28.07.2019, sf. 1-6.
  • Sohn, K. ve Kwon, O. (2020). Technology acceptance theories and factors influencing artificial Intelligence-based intelligent products. Telematics and Informatics, 47, 101324. doi:10.1016/J.TELE.2019.101324
  • Su, K. W., Tseng, H. H., Wu, A. T. ve Lien, C. Y. (2016). Exploring User Behavioral Intention of the Tourist Guiding System by Users' Perspective. Proceedings of the International MultiConference of Engineers and Computer Scientists (Sayı 1) içerisinde, Hong Kong, 16-18.03.2016, sf. 169-173.
  • Tan, G. W. H., Lee, V. H., Lin, B. ve Ooi, K. B. (2017). Mobile applications in tourism: The future of the tourism industry? Industrial Management and Data Systems, 117(3), 560–581. doi:10.1108/IMDS-12-2015-0490/FULL/PDF
  • Tan, G. W. H. ve Ooi, K. B. (2018). Gender and age: Do they really moderate mobile tourism shopping behavior? Telematics and Informatics, 35(6), 1617–1642. doi:10.1016/J.TELE.2018.04.009
  • Teng, C. C., Lu, A. C. C. ve Huang, T. T. (2018). Drivers of consumers’ behavioral intention toward green hotels. International Journal of Contemporary Hospitality Management, 30(2), 1134–1151. doi:10.1108/IJCHM-04-2017-0203
  • Tolbize, A. (2008). Generational differences in the workplace. Minnesota. http://dwashingtonllc.com/pdf/generational_differences_workplace.pdf adresinden erişildi.
  • Tull, M. T., Edmonds, K. A., Scamaldo, K. M., Richmond, J. R., Rose, J. P. ve Gratz, K. L. (2020). Psychological outcomes associated with stay-at-home orders and the perceived impact of COVID-19 on daily life. Psychiatry Research, 289(April), 113098. doi:10.1016/j.psychres.2020.113098
  • Tung, V. W. S. ve Au, N. (2018). Exploring customer experiences with robotics in hospitality. International Journal of Contemporary Hospitality Management, 30(7), 2680–2697. doi:10.1108/IJCHM-06-2017-0322/FULL/PDF
  • Tuomi, A., Tussyadiah, I. P. ve Stienmetz, J. (2020). Applications and Implications of Service Robots in Hospitality: Cornell Hospitality Quarterly, 62(2), 232–247. doi:10.1177/1938965520923961
  • Tussyadiah, I. (2020). A review of research into automation in tourism: Launching the Annals of Tourism Research Curated Collection on Artificial Intelligence and Robotics in Tourism. Annals of Tourism Research, 81, 102883. doi:10.1016/J.ANNALS.2020.102883
  • Usakli, A. ve Küçükergin, K. G. (2018). Using partial least squares structural equation modeling in hospitality and tourism: Do researchers follow practical guidelines? International Journal of Contemporary Hospitality Management, 30(11), 3462–3512. doi:10.1108/IJCHM-11-2017-0753
  • Venkatesh, V. (2021). Adoption and use of AI tools: a research agenda grounded in UTAUT. Annals of Operations Research, 1–12. doi:10.1007/S10479-020-03918-9/TABLES/1
  • Venkatesh, V., Morris, M. G., Davis, G. B. ve Davis, F. D. (2003). User acceptance of information technology: Toward a unified view. MIS Quarterly: Management Information Systems, 27(3), 425–478.
  • Warde, A. ve Martens, L. (2000). Eating out: Social differentiation, consumption and pleasure. Cambridge: Cambridge University Press.
  • Xu, S., Stienmetz, J. ve Ashton, M. (2020). How will service robots redefine leadership in hotel management? A Delphi approach. International Journal of Contemporary Hospitality Management, 32(6), 2217–2237. doi:10.1108/IJCHM-05-2019-0505/FULL/PDF
  • Yazıcı-Ayyıldız, A. ve Eroğlu, E. (2021). Restoranlarda Kullanılan Akıllı Teknolojiler ve Robot Restoranlar Hakkında Tripadvisor’da Yapılan Yorumların Değerlendirilmesi. Journal of Tourism and Gastronomy Studies, 9(2), 1102–1122.
  • Yu, C.-E. (2019). Humanlike robots as employees in the hotel industry: Thematic content analysis of online reviews. Journal of Hospitality Marketing & Management, 29(1), 22–38. doi:10.1080/19368623.2019.1592733
  • Zaremohzzabieh, Z., Samah, B. A., Omar, S. Z., Bolong, J. ve Hayrol Azril, M. S. (2014). Fisherman’s acceptance of information and communication technology integration in Malaysia: exploring the moderating effect of age and experience. Journal of Applied Sciences, 14(9), 873–882.
  • Zemke, D. M. V., Tang, J., Raab, C. ve Kim, J. (2020). How To Build a Better Robot . . . for Quick-Service Restaurants: Journal of Hospitality & Tourism Research, 44(8), 1235–1269. doi:10.1177/1096348020946383
  • Zeng, Z., Chen, P.-J. J. ve Lew, A. A. (2020). From high-touch to high-tech: COVID-19 drives robotics adoption. Tourism Geographies, 22(3), 724–734. doi:10.1080/14616688.2020.1762118
  • Zhong, L., Zhang, X., Rong, J., Chan, H. K., Xiao, J. ve Kong, H. (2020). Construction and empirical research on acceptance model of service robots applied in hotel industry. Industrial Management & Data Systems, 121(6), 1325–1352.

The Moderating Role of Generational Difference in Adoption of Anthropomorphic Robots for Restaurants: An Extension to the UTAUT model with Socialization and Innovativeness

Yıl 2022, Cilt: 6 Sayı: 2, 635 - 663, 29.09.2022
https://doi.org/10.32572/guntad.1037791

Öz

The aim of this research is to confirm the unified technology acceptance and utilization theory (UTAUT) in the context of humanoid robot and restaurant, and to contribute to the theory through touristic socialization and touristic innovativeness variables. In this context, the data obtained from 363 participants with restaurant experience were subjected to structural equation modeling. As a result of the study, it was determined that performance expectancy, effort expectancy, social influence and facilitating conditions, which are the predictive variables of the UTAUT model, are seen to positively and significantly affect the behavioral intention to experience humanoid robots in restaurants. Among these, it was seen that facilitating conditions came to the fore as the variable with the strongest predictive power. Performance expectancy and social influence emerged as the other two strongest antecedents explaining behavioral intention. Besides, it was observed that tourist innovativeness positively affected behavioral intention, while the tourist socialization variable were seen to have any significant effect on behavioral intention. Also, social influence was determined as the most effective variable for X generation. As a moderating variable, it was seen that the participants within Y-Z generations give more importance to the facilitating conditions in adopting humanoid robots compared to the X generation.

Kaynakça

  • Aharony, N. (2015). Why do students use What’s App? – an exploratory study. Aslib Journal of Information Management, 67(2), 136–158. doi:10.1108/AJIM-11-2014-0148/FULL/PDF
  • Akdim, K., Belanche, D. ve Flavián, M. (2021). Attitudes toward service robots: analyses of explicit and implicit attitudes based on anthropomorphism and construal level theory. International Journal of Contemporary Hospitality Management. doi:10.1108/IJCHM-12-2020-1406
  • Aslantürk, E. ve Erdem, A. (2021). Teknoloji Kullanımına Yönelik Tutumun Otellerde Robot Kabul Edilebilirliği Üzerine Etkisi. Journal of Global Tourism and Technology Research, 2(2), 102–115.
  • Asoba, S. N. ve Mefi, N. P. (2022). The Generational Dimensıon of Technology Acceptance: The Case of Generatıon X and Millennial Managers. Journal of Management Information and Decision Sciences, 25(4), 1–7.
  • Balcı, A. (2011). Sosyal Bilimlerde Araştırma: Yöntem, Teknik ve İlkeler (9th bs.). Ankara: Pegem.
  • Belanche, D., Casaló, L. V. ve Flavián, C. (2020). Frontline robots in tourism and hospitality: service enhancement or cost reduction? Electronic Markets, 1–16. doi:10.1007/S12525-020-00432-5
  • Brown, M. A. (1984). Change mechanisms in the diffusion of residential energy conservation practices: an empirical study. Technological Forecasting and Social Change, 25(2), 123–138. doi:10.1016/0040-1625(84)90087-8
  • Buhalis, D. ve Leung, R. (2018). Smart hospitality—Interconnectivity and interoperability towards an ecosystem. International Journal of Hospitality Management, 71, 41–50. doi:10.1016/J.IJHM.2017.11.011
  • Büyüköztürk, Ş., Kılıç-Çakmak, E., Akgün, Ö. E., Karadeniz, Ş. ve Demirel, F. (2013). Bilimsel Araştırma Yöntemleri (15.). Ankara: Pegem.
  • Byrd, K., Fan, A., Her, E. S., Liu, Y., Almanza, B. ve Leitch, S. (2021). Robot vs human: expectations, performances and gaps in off-premise restaurant service modes. International Journal of Contemporary Hospitality Management. doi:10.1108/IJCHM-07-2020-0721
  • Cai, W., Richter, S. ve McKenna, B. (2019). Progress on technology use in tourism. Journal of Hospitality and Tourism Technology, 10(4), 651–672. doi:10.1108/JHTT-07-2018-0068
  • Çakır, İ. ve Kazançoğlu, İ. (2020). Sanal Market Alışverişi Yapma Niyetinde Genişletilmiş Teknoloji Kabul Modeli Bileşenleri ile Risk Algılarının Etkisi. Manisa Celal Bayar Üniversitesi Sosyal Bilimler Dergisi, 18(2), 305–326.
  • Calvo-Porral, C. ve Pesqueira-Sanchez, R. (2020). Generational differences in technology behaviour: comparing millennials and Generation X. Kybernetes, 49(11), 2755–2772. doi:10.1108/K-09-2019-0598/FULL/PDF
  • Campbell, S., Greenwood, M., Prior, S., Shearer, T., Walkem, K., Young, S., Bywaters, D. ve Walker, K. (2020). Purposive sampling: complex or simple? Research case examples: Journal of Research in Nursing, 25(8), 652–661. doi:10.1177/1744987120927206
  • Cha, S. S. (2020). Customers’ intention to use robot-serviced restaurants in Korea: relationship of coolness and MCI factors. International Journal of Contemporary Hospitality Management, 32(9), 2947–2968. doi:10.1108/IJCHM-01-2020-0046
  • Choi, Y., Choi, M., Oh, M. (Moon) ve Kim, S. (Sam). (2019). Service robots in hotels: understanding the service quality perceptions of human-robot interaction. Journal of Hospitality Marketing & Management, 29(6), 613–635. doi:10.1080/19368623.2020.1703871
  • Christou, P., Simillidou, A. ve Stylianou, M. C. (2020). Tourists’ perceptions regarding the use of anthropomorphic robots in tourism and hospitality. International Journal of Contemporary Hospitality Management, 32(11), 3665–3683. doi:10.1108/IJCHM-05-2020-0423
  • Cohen, E. (1972). Toward a sociology of international tourism. Social Research, 164–182. https://www.jstor.org/stable/pdf/40970087.pdf adresinden erişildi.
  • Compeau, D. R. ve Higgins, C. A. (1995). Computer self-efficacy: Development of a measure and initial test. MIS Quarterly: Management Information Systems, 19(2), 189–210. doi:10.2307/249688
  • Dai, B., Larnyo, E., Tetteh, E. A., Aboagye, A. K. ve Musah, A.-A. I. (2019). Factors Affecting Caregivers’ Acceptance of the Use of Wearable Devices by Patients With Dementia: An Extension of the Unified Theory of Acceptance and Use of Technology Model: American Journal of Alzheimer’s Disease and Other Dementias, 35, 1–11. doi:10.1177/1533317519883493
  • Davis, F. D. (1993). User acceptance of information technology: System characteristics, user perceptions and behavioral impacts. International Journal of Man-Machine Studies. doi:10.1006/imms.1993.1022
  • Durna, E. C. ve Taşçıoğlu-Baysal, H. (2021). Ziyaretçilerin Otel İşletmelerine Yönelik Yorum ve Şikayetlerinin İncelenmesi: Dünyanın İlk Robotik Oteli Olan “Henn na Otel” Örneği. Turizm ve İşletme Bilimleri Dergisi, 1(2), 85–102.
  • Escobar-Rodríguez, T. ve Carvajal-Trujillo, E. (2014). Online purchasing tickets for low cost carriers: An application of the unified theory of acceptance and use of technology (UTAUT) model. Tourism Management, 43, 70–88. doi:10.1016/J.TOURMAN.2014.01.017
  • Fabrigar, L. R. ve Wegener, D. T. (2012). Exploratory Factor Analysis: Understanding Statistics. New York: Oxford University Press.
  • Fakfare, P., Talawanich, S. ve Wattanacharoensil, W. (2020). A scale development and validation on domestic tourists’ motivation: the case of second-tier tourism destinations. https://doi.org/10.1080/10941665.2020.1745855, 25(5), 489–504. doi:10.1080/10941665.2020.1745855
  • Fan, W., Liu, J., Zhu, S. ve Pardalos, P. M. (2020). Investigating the impacting factors for the healthcare professionals to adopt artificial intelligence-based medical diagnosis support system (AIMDSS). Annals of Operations Research, 294(1–2), 567–592. doi:10.1007/S10479-018-2818-Y/FIGURES/3
  • Faul, F., Erdfelder, E., Lang, A.-G. ve Buchner, A. (2007). G*Power 3: A flexible statistical power analysis program for the social, behavioral, and biomedical sciences. Behavior Research Methods, 39(2), 175–191. doi:10.3758/BF03193146
  • Fernández-Llamas, C., Conde, M. A., Rodríguez-Lera, F. J., Rodríguez-Sedano, F. J. ve García, F. (2018). May I teach you? Students’ behavior when lectured by robotic vs. human teachers. Computers in Human Behavior, 80, 460–469. doi:10.1016/J.CHB.2017.09.028
  • Fornell, C. ve Larcker, D. F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research, 18(1), 39. doi:10.2307/3151312
  • Foxall, G. R., Goldsmith, R. E. ve Brown, S. (1998). Consumer Psychology for Marketing. Cengage Learning EMEA, 1.
  • Fuentes-Moraleda, L., Díaz-Pérez, P., Orea-Giner, A., Muñoz- Mazón, A. ve Villacé-Molinero, T. (2020). Interaction between hotel service robots and humans: A hotel-specific Service Robot Acceptance Model (sRAM). Tourism Management Perspectives, 36, 100751. doi:10.1016/J.TMP.2020.100751
  • Ghazali, A. S., Ham, J., Barakova, E. ve Markopoulos, P. (2020). Persuasive Robots Acceptance Model (PRAM): Roles of Social Responses Within the Acceptance Model of Persuasive Robots. International Journal of Social Robotics, 12, 1075–1092.
  • Go, H., Kang, M. ve Suh, S. B. C. (2020). Machine learning of robots in tourism and hospitality: interactive technology acceptance model (iTAM) – cutting edge. Tourism Review, 75(4), 625–636. doi:10.1108/TR-02-2019-0062
  • Hair, F. H., Black, W. C., Babin, B. J. ve Anderson, R. E. (2019). Multivariate Data Analysis (Eighth Edi.). Andover: Cengage.
  • Hair, J. (2009). Multivariate Data Analysis: A Global Perspective. Faculty Publications (7. bs.). Prentice Hall. https://digitalcommons.kennesaw.edu/facpubs/2925 adresinden erişildi.
  • Hair, J. F., Sarstedt, M., Ringle, C. M. ve Gudergan, S. P. (2018). Advanced Issues in Partial Least Squares Structural Equation Modeling. California: Sage Publications.
  • Hair, J., Howard, M. C. ve Nitzl, C. (2020). Assessing measurement model quality in PLS-SEM using confirmatory composite analysis. Journal of Business Research, 109, 101–110. doi:10.1016/j.jbusres.2019.11.069
  • Hair, J., Hult, G. T. M., Ringle, C. M. ve Sarstedt, M. (2017). A primer on partial least squares structural equation modeling (PLS-SEM) (2. bs.). Los Angeles: Sage.
  • Hair, J., Risher, J. J., Sarstedt, M. ve Ringle, C. M. (2019). When to use and how to report the results of PLS-SEM. European Business Review, 31(1), 2–24. doi:10.1108/EBR-11-2018-0203
  • Henseler, J., Ringle, C. M. ve Sarstedt, M. (2015). A new criterion for assessing discriminant validity in variance-based structural equation modeling. Journal of the Academy of Marketing Science, 43(1), 115–135. doi:10.1007/s11747-014-0403-8
  • Hsu, C. L. ve Lin, J. C. C. (2008). Acceptance of blog usage: The roles of technology acceptance, social influence and knowledge sharing motivation. Information & Management, 45(1), 65–74. doi:10.1016/J.IM.2007.11.001
  • Hui-Wen Chuah, S., Cheng-Xi Aw, E. ve Cheng, C.-F. (2021). A silver lining in the COVID-19 cloud: examining customers’ value perceptions, willingness to use and pay more for robotic restaurants. Journal of Hospitality Marketing & Management. doi:10.1080/19368623.2021.1926038
  • Hwang, J., Kim, J. J. ve Lee, K. W. (2021). Investigating consumer innovativeness in the context of drone food delivery services: Its impact on attitude and behavioral intentions. Technological Forecasting and Social Change, 163, 120433. doi:10.1016/J.TECHFORE.2020.120433
  • Hwang, J., Park, S. ve Kim, I. (2020). Understanding motivated consumer innovativeness in the context of a robotic restaurant: The moderating role of product knowledge. Journal of Hospitality and Tourism Management, 44, 272–282. doi:10.1016/J.JHTM.2020.06.003
  • İbiş, S. (2019). Turizm Endüstrisinde Robotlaşma. Türk Turizm Araştırmaları Dergisi, 3(3), 403–420.
  • Im, I., Hong, S. ve Kang, M. S. (2011). An international comparison of technology adoption: Testing the UTAUT model. Information & Management, 48(1), 1–8. doi:10.1016/J.IM.2010.09.001 Ivanov, S. ve Webster, C. (2019). Perceived appropriateness and intention to use service robots in tourism. In Pesonen, J. & Neidhardt, J. (Ed.) Information and Communication Technologies in Tourism 2019, Proceedings of the International Conference içerisinde, Nicosia, Cyprus, 30.01-01.02.2019, sf. 237-248.
  • Jeon, H. M., Sung, H. J. ve Kim, H. Y. (2020). Customers’ acceptance intention of self-service technology of restaurant industry: expanding UTAUT with perceived risk and innovativeness. Service Business, 14(4), 533–551. doi:10.1007/S11628-020-00425-6/TABLES/4
  • Kaba, B. ve Touré, B. (2014). Understanding information and communication technology behavioral intention to use: Applying the UTAUT model to social networking site adoption by young people in a least developed country. Journal of the Association for Information Science and Technology, 65(8), 1662–1674. doi:10.1002/ASI.23069
  • Kağıtçıbaşı, C. (1983). Women and development in Turkey. International Journal of Turkish Studies, 2, 59–70.
  • Kamboj, S. ve Joshi, R. (2020). Examining the factors influencing smartphone apps use at tourism destinations: a UTAUT model perspective. International Journal of Tourism Cities, 7(1), 135–157. doi:10.1108/IJTC-05-2020-0094
  • Khalilzadeh, J., Ozturk, A. B. ve Bilgihan, A. (2017). Security-related factors in extended UTAUT model for NFC based mobile payment in the restaurant industry. Computers in Human Behavior, 70, 460–474. doi:10.1016/J.CHB.2017.01.001
  • Khechine, H., Lakhal, S., Pascot, D. ve Bytha, A. (2014). UTAUT Model for Blended Learning: The Role of Gender and Age in the Intention to Use Webinars. Interdisciplinary Journal of E-Learning and Learning Objects, 10, 33–52.
  • Kim, D. Y., Park, J. ve Morrison, A. M. (2008). A model of traveller acceptance of mobile technology. International Journal of Tourism Research, 10(5), 393–407. doi:10.1002/jtr.669
  • Kim, D. Y. ve Park, S. (2019). Rethinking millennials: how are they shaping the tourism industry? Asia Pacific Journal of Tourism Research, 25(1), 1–2. doi:10.1080/10941665.2019.1667607
  • Kim, J. J., Choe, J. Y. (Jacey) ve Hwang, J. (2020). Application of consumer innovativeness to the context of robotic restaurants. International Journal of Contemporary Hospitality Management, 33(1), 224–242. doi:10.1108/IJCHM-06-2020-0602
  • Kim, M. J. ve Hall, C. M. (2020). What drives visitor economy crowdfunding? The effect of digital storytelling on unified theory of acceptance and use of technology. Tourism Management Perspectives, 34, 100638. doi:10.1016/J.TMP.2020.100638
  • Kim, S., Kim, J., Badu-Baiden, F., Giroux, M. ve Choi, Y. (2021). Preference for robot service or human service in hotels? Impacts of the COVID-19 pandemic. International Journal of Hospitality Management, 93, 102807. doi:10.1016/J.IJHM.2020.102795
  • Kizir, E. ve Bozbay, Z. (2021). Moda Ürünleri Satan Mobil Alışveriş Uygulamalarının Kabulünün Birleştirilmiş Teknoloji Kabul ve Kullanım Teorisi Çerçevesinde İncelenmesi. Marmara Üniversitesi Öneri Dergisi, 16(55), 286–310.
  • Lian, J. W. ve Yen, D. C. (2014). Online shopping drivers and barriers for older adults: Age and gender differences. Computers in Human Behavior, 37, 133–143. doi:10.1016/J.CHB.2014.04.028
  • Lu, L., Cai, R. ve Gursoy, D. (2019). Developing and validating a service robot integration willingness scale. International Journal of Hospitality Management, 80, 36–51. doi:10.1016/J.IJHM.2019.01.005
  • Magsamen-Conrad, K., Upadhyaya, S., Joa, C. Y. ve Dowd, J. (2015). Bridging the divide: Using UTAUT to predict multigenerational tablet adoption practices. Computers in Human Behavior, 50, 186–196. doi:10.1016/J.CHB.2015.03.032
  • Mang, C. F., Piper, L. A. ve Brown, N. R. (2016). The Incidence of Smartphone Usage among Tourists. International Journal of Tourism Research, 18(6), 591–601. doi:10.1002/JTR.2076
  • Mo, C. min, Howard, D. R. ve Havitz, M. E. (1993). Testing an international tourist role typology. Annals of Tourism Research, 20(2), 319–335. doi:10.1016/0160-7383(93)90058-B
  • Neuhofer, B., Buhalis, D. ve Ladkin, A. (2014). A Typology of Technology-Enhanced Tourism Experiences. International Journal of Tourism Research, 16(4), 340–350. doi:10.1002/JTR.1958
  • Nüfusu. (2022). Ankara Nüfusu 2021 2022. 4 Haziran 2022 tarihinde https://www.nufusu.com/il/ankara-nufusu adresinden erişildi.
  • Özekici, Y. K. (2019). Yerli Halk-Turist Etkileşimi ve Bir Model Önerisi. Gazi University.
  • Özgürel, G. ve Kılınç-Şahin, S. (2021). Turizmde Robotlaşma: Yiyecek-İçecek Sektöründe Robot Şefler ve Robot Garsonlar. OPUS, 11(8), 1849–1882. doi:10.26466/opus.899296
  • Palos-Sanchez, P., Jose, ·, Saura, R., Correia, M. B., Saura, J. R. ve Pt, M. (2021). Do tourism applications’ quality and user experience influence its acceptance by tourists? Review of Managerial Science, 15, 1205–1241. doi:10.1007/s11846-020-00396-y
  • Pan, S. ve Jordan-Marsh, M. (2010). Internet use intention and adoption among Chinese older adults: From the expanded technology acceptance model perspective. Computers in Human Behavior, 26(5), 1111–1119. doi:10.1016/J.CHB.2010.03.015
  • Parasuraman, A. (2000). Technology Readiness Index (Tri): A multiple-item scale to measure readiness to embrace new technologies. Journal of Service Research, 2(4), 307–320.
  • Park, C. (2004). Efficient or enjoyable? Consumer values of eating-out and fast food restaurant consumption in Korea. International Journal of Hospitality Management, 23(1), 87–94. doi:10.1016/J.IJHM.2003.08.001
  • Park, S. ve Stangl, B. (2020). Augmented reality experiences and sensation seeking. Tourism Management, 77(October 2019), 104023. doi:10.1016/j.tourman.2019.104023
  • Pourfakhimi, S., Duncan, T. ve Coetzee, W. (2019). A critique of the progress of eTourism technology acceptance research: time for a hike? Journal of Hospitality and Tourism Technology, 10(4), 689–746.
  • Rahman, M. M., Lesch, M. F., Horrey, W. J. ve Strawderman, L. (2017). Assessing the utility of TAM, TPB, and UTAUT for advanced driver assistance systems. Accident Analysis & Prevention, 108, 361–373.
  • Ramadan, Z. B., Farah, M. F. ve Mrad, M. (2017). An adapted TPB approach to consumers’ acceptance of service-delivery drones. Technology Analysis and Strategic Management, 29(7), 817–828. doi:10.1080/09537325.2016.1242720
  • Revfine. (2020). 8 Examples of Robots Being Used in the Hospitality Industry. 16 Aralık 2021 tarihinde https://www.revfine.com/robots-hospitality-industry/ adresinden erişildi.
  • Ringle, C. M., Wende, S. ve Becker, J.-M. (2015). SmartPLS 3. Boenningstedt: SmartPLS GmbH, http://www. smartpls. com.
  • Robinson, L., Marshall, G. W. ve Stamps, M. B. (2005). Sales force use of technology: Antecedents to technology acceptance. Journal of Business Research, 58(12), 1623–1631. doi:10.1016/j.jbusres.2004.07.010
  • Ryan, T. ve Xenos, S. (2011). Who uses Facebook? An investigation into the relationship between the Big Five, shyness, narcissism, loneliness, and Facebook usage. Computers in Human Behavior, 27(5), 1658–1664. doi:10.1016/j.chb.2011.02.004
  • San Martín, H. ve Herrero, Á. (2012). Influence of the user’s psychological factors on the online purchase intention in rural tourism: Integrating innovativeness to the UTAUT framework. Tourism Management, 33(2), 341–350. doi:10.1016/J.TOURMAN.2011.04.003
  • Seo, K. H. ve Lee, J. H. (2021). The Emergence of Service Robots at Restaurants: Integrating Trust, Perceived Risk, and Satisfaction. Sustainability, 13(8), 4431. doi:10.3390/SU13084431
  • Seyitoğlu, F., Ivanov, S., Atsız, O. ve Çifçi, İ. (2021). Robots as restaurant employees - A double-barrelled detective story. Technology in Society, 67, 101779. doi:10.1016/J.TECHSOC.2021.101779
  • Shin, H. H. ve Jeong, M. (2020). Guests’ perceptions of robot concierge and their adoption intentions. International Journal of Contemporary Hospitality Management, 32(8), 2613–2633. doi:10.1108/IJCHM-09-2019-0798
  • Siang, T. G., Ahmad, Z. B., Bin, K., Aziz, K. B. ve Suhaifi, S. B. (2019). Augmented reality mobile application for museum: A technology acceptance study. 6th International Conference on Research and Innovation in Information Systems (ICRIIS) içerisinde, Londra, 26-28.07.2019, sf. 1-6.
  • Sohn, K. ve Kwon, O. (2020). Technology acceptance theories and factors influencing artificial Intelligence-based intelligent products. Telematics and Informatics, 47, 101324. doi:10.1016/J.TELE.2019.101324
  • Su, K. W., Tseng, H. H., Wu, A. T. ve Lien, C. Y. (2016). Exploring User Behavioral Intention of the Tourist Guiding System by Users' Perspective. Proceedings of the International MultiConference of Engineers and Computer Scientists (Sayı 1) içerisinde, Hong Kong, 16-18.03.2016, sf. 169-173.
  • Tan, G. W. H., Lee, V. H., Lin, B. ve Ooi, K. B. (2017). Mobile applications in tourism: The future of the tourism industry? Industrial Management and Data Systems, 117(3), 560–581. doi:10.1108/IMDS-12-2015-0490/FULL/PDF
  • Tan, G. W. H. ve Ooi, K. B. (2018). Gender and age: Do they really moderate mobile tourism shopping behavior? Telematics and Informatics, 35(6), 1617–1642. doi:10.1016/J.TELE.2018.04.009
  • Teng, C. C., Lu, A. C. C. ve Huang, T. T. (2018). Drivers of consumers’ behavioral intention toward green hotels. International Journal of Contemporary Hospitality Management, 30(2), 1134–1151. doi:10.1108/IJCHM-04-2017-0203
  • Tolbize, A. (2008). Generational differences in the workplace. Minnesota. http://dwashingtonllc.com/pdf/generational_differences_workplace.pdf adresinden erişildi.
  • Tull, M. T., Edmonds, K. A., Scamaldo, K. M., Richmond, J. R., Rose, J. P. ve Gratz, K. L. (2020). Psychological outcomes associated with stay-at-home orders and the perceived impact of COVID-19 on daily life. Psychiatry Research, 289(April), 113098. doi:10.1016/j.psychres.2020.113098
  • Tung, V. W. S. ve Au, N. (2018). Exploring customer experiences with robotics in hospitality. International Journal of Contemporary Hospitality Management, 30(7), 2680–2697. doi:10.1108/IJCHM-06-2017-0322/FULL/PDF
  • Tuomi, A., Tussyadiah, I. P. ve Stienmetz, J. (2020). Applications and Implications of Service Robots in Hospitality: Cornell Hospitality Quarterly, 62(2), 232–247. doi:10.1177/1938965520923961
  • Tussyadiah, I. (2020). A review of research into automation in tourism: Launching the Annals of Tourism Research Curated Collection on Artificial Intelligence and Robotics in Tourism. Annals of Tourism Research, 81, 102883. doi:10.1016/J.ANNALS.2020.102883
  • Usakli, A. ve Küçükergin, K. G. (2018). Using partial least squares structural equation modeling in hospitality and tourism: Do researchers follow practical guidelines? International Journal of Contemporary Hospitality Management, 30(11), 3462–3512. doi:10.1108/IJCHM-11-2017-0753
  • Venkatesh, V. (2021). Adoption and use of AI tools: a research agenda grounded in UTAUT. Annals of Operations Research, 1–12. doi:10.1007/S10479-020-03918-9/TABLES/1
  • Venkatesh, V., Morris, M. G., Davis, G. B. ve Davis, F. D. (2003). User acceptance of information technology: Toward a unified view. MIS Quarterly: Management Information Systems, 27(3), 425–478.
  • Warde, A. ve Martens, L. (2000). Eating out: Social differentiation, consumption and pleasure. Cambridge: Cambridge University Press.
  • Xu, S., Stienmetz, J. ve Ashton, M. (2020). How will service robots redefine leadership in hotel management? A Delphi approach. International Journal of Contemporary Hospitality Management, 32(6), 2217–2237. doi:10.1108/IJCHM-05-2019-0505/FULL/PDF
  • Yazıcı-Ayyıldız, A. ve Eroğlu, E. (2021). Restoranlarda Kullanılan Akıllı Teknolojiler ve Robot Restoranlar Hakkında Tripadvisor’da Yapılan Yorumların Değerlendirilmesi. Journal of Tourism and Gastronomy Studies, 9(2), 1102–1122.
  • Yu, C.-E. (2019). Humanlike robots as employees in the hotel industry: Thematic content analysis of online reviews. Journal of Hospitality Marketing & Management, 29(1), 22–38. doi:10.1080/19368623.2019.1592733
  • Zaremohzzabieh, Z., Samah, B. A., Omar, S. Z., Bolong, J. ve Hayrol Azril, M. S. (2014). Fisherman’s acceptance of information and communication technology integration in Malaysia: exploring the moderating effect of age and experience. Journal of Applied Sciences, 14(9), 873–882.
  • Zemke, D. M. V., Tang, J., Raab, C. ve Kim, J. (2020). How To Build a Better Robot . . . for Quick-Service Restaurants: Journal of Hospitality & Tourism Research, 44(8), 1235–1269. doi:10.1177/1096348020946383
  • Zeng, Z., Chen, P.-J. J. ve Lew, A. A. (2020). From high-touch to high-tech: COVID-19 drives robotics adoption. Tourism Geographies, 22(3), 724–734. doi:10.1080/14616688.2020.1762118
  • Zhong, L., Zhang, X., Rong, J., Chan, H. K., Xiao, J. ve Kong, H. (2020). Construction and empirical research on acceptance model of service robots applied in hotel industry. Industrial Management & Data Systems, 121(6), 1325–1352.
Toplam 105 adet kaynakça vardır.

Ayrıntılar

Birincil Dil Türkçe
Konular Turizm (Diğer)
Bölüm Makaleler
Yazarlar

Y. Kemal Özekici 0000-0003-2482-7355

Yayımlanma Tarihi 29 Eylül 2022
Kabul Tarihi 10 Haziran 2022
Yayımlandığı Sayı Yıl 2022 Cilt: 6 Sayı: 2

Kaynak Göster

APA Özekici, Y. K. (2022). Restoranlar için İnsansı Robotların Kabulünde Kuşaklar Arası Farklılığın Düzenleyici Rolü: Sosyalleşme ve Yenilikçilik ile BTKKT Modeline Yönelik Bir Genişletme Çalışması. Güncel Turizm Araştırmaları Dergisi, 6(2), 635-663. https://doi.org/10.32572/guntad.1037791

Değerli Araştırmacılar,

Dergimize gönderilen çalışmalar geliş sırasına ve konusuna göre öncelikle editör değerlendirmesinden geçmekte, editör görüşü doğrultusunda hakem değerlendirmesine karar verilmektedir. Değerlendirme süreci tamamlanan çalışmalar da aynı şekilde değerlendirmenin tamamlanma tarihlerine, türlerine ve kapsamlarına göre yayıma kabul edilmektedir. Bu yüzden GTAD'a gönderilen çalışmaların herhangi bir sayıda yayıma kabul edileceğinin planlanarak önerilmemesi gerektiğini tekrar hatırlatmak isteriz. Detaylı bilgi için yayın politkası incelenebilir.