Araştırma Makalesi
BibTex RIS Kaynak Göster

Investigation of Consumers' Attitudes and Trusts Towards Chatbots within the Framework of Technology Acceptance Model and Uses and Gratifications Theory

Yıl 2025, Cilt: 10 Sayı: 3, 1167 - 1200
https://doi.org/10.25229/beta.1669811

Öz

The digital transformation brought by the technology age has increased the importance of customer experience and made the use of artificial intelligence-supported digital intelligent systems mandatory in the strategic decisions of businesses. One such intelligent system is chatbots, which are dialogue-based computer programs designed to meet users' needs quickly and efficiently. In this study, it is aimed to examine the attitudes of online shoppers towards chatbots within the framework of Technology Acceptance Model, Use and Satisfaction Theory and trust in chatbots. The research was conducted using data from a survey of 399 participants, analyzed through the Structural Equation Modeling (SEM) method using SPSS and LISREL software packages. The findings indicate that consumers' attitudes, behaviors, trust, and satisfaction toward chatbots have increased. Additionally, it was found that consumers' attitudes toward chatbots with secure features related to health have also improved. As a result, it can be concluded that as people accept and trust new technologies, their attitudes toward chatbots and their satisfaction with using these technologies improve.

Kaynakça

  • Adıgüzel, A. (2012). Okula ilişkin tutum ölçeğinin geçerlik ve güvenirlik çalışması. Elektronik Sosyal Bilimler Dergisi, 11(40), 30–45.
  • Alikılıç, Ö., Gülay, G., & Binbir, S. (2013). Kullanımlar ve doyumlar kuramı çerçevesinde Facebook uygulamalarının incelenmesi: Yaşar Üniversitesi öğrencileri üzerine bir araştırma. İletişim Kuram ve Araştırma Dergisi, 1(37), 41–67.
  • Alt, M. A., Vizeli, I., & Săplăcan, Z. (2021). Banking with a chatbot – A study on technology acceptance. Studia Universitatis Babeș-Bolyai Oeconomica, 66, 13–35. https://doi.org/10.2478/subboec-2021-0002
  • Arsenijevic, U., & Jovic, M. (2019, September 30–October 4). Artificial intelligence marketing: Chatbots [Conference presentation]. 2019 International Conference on Artificial Intelligence: Applications and Innovations, Belgrade, Serbia. https://doi.org/10.1109/IC-AIAI48757.2019.00010
  • Atwal, G., & Bryson, D. (2021). Antecedents of intention to adopt artificial intelligence services by consumers in personal financial investing. Strategic Change, 30(3), 293-298. https://doi.org/10.1002/jsc.2412
  • Ayhan, B., & Çavuş, S. (2014). İzleyici araştırmalarında değişim: kullanımlar ve doyumlardan bağımlılığa. Selçuk İletişim, 8(2), 32-60.
  • Barry, B., & Crant, J. M. (2000). Dyadic communication relationships in organizations: An attribution/expectancy approach. Organization Science, 11(6), 648-664.
  • Brandtzaeg, P. B., & Følstad, A. (2017). Trust and distrust in online fact-checking servicesi. Communications of the ACM, 60(9), 65-71. https://doi.org/10.1145/3122803
  • Brill, T. M., Munoz, L., & Miller, R. J. (2019). Siri, Alexa, and other digital assistants: a study of customer satisfaction with artificial intelligence applications. Journal of Marketing Management, 35(15-16), 1401-1436. https://doi.org/10.1080/0267257X.2019.1687571
  • Brachten, F., Kissmer, T., & Stieglitz, S. (2021). The acceptance of chatbots in an enterprise context–A survey study. International Journal of Information Management, 60, 102375. https://doi.org/10.1016/j.ijinfomgt.2021.102375
  • Broeck, E., Zarouali, B., & Poels, K. (2019). Chatbot advertising effectiveness: When does the message get through? Computers in Human Behavior, 98, 150–157.
  • Browne, M. W., & Cudeck, R. (1993). Alternative ways of assessing model fit. In K. A. Bollen & J. S. Long (Eds.), Testing structural equation models (pp. 136-162). Newbury Park, CA: Sage.
  • Bollen, K. A. (1989). Structural equations with latent variables. John Wiley & Sons.
  • Bolton, G., Greiner, B., & Ockenfels, A. (2013). Engineering trust: reciprocity in the production of reputation information. Management Science, 59(2), 265-285.
  • Buabeng-Andoh, C. (2018). Predicting students’ intention to adopt mobile learning: A combination of theory of reasoned action and technology acceptance model. Journal of Research in Innovative Teaching & Learning, 11(2), 178-191. https://doi.org/10.1108/JRIT-03-2017-0004
  • Candela, E. (2018). Consumers’ perception and attitude towards chatbots’ adoption: A focus on the Italian market [Unpublished master’s dissertation]. Aalborg University.
  • Chen, G. M. (2011). Tweet this: a uses and gratifications perspective on how active twitter use gratifies a need to connect with others. Computers in Human Behavior, 27(2): 755-762.
  • Cheng, Y., & Jiang, H. (2022). Customer–brand relationship in the era of artificial intelligence: Understanding the role of chatbot marketing efforts. Journal of Product & Brand Management, 31(2), 252-264. https://doi.org/10.1108/JPBM-05-2020-2907
  • Childers, T. L., Carr, C. L., Peck, J., & Carson, S. (2001). Hedonic and utilitarian motivations for online retail shopping behavior. Journal of Retailing, 77(4), 511-535.
  • Colby, K. M. (1975). Artificial Paranoia: A Computer Simulation of Paranoid Processes. Pergamon Press.
  • Chung, M., Ko, E., Joung, H., & Kim, S. J. (2020). Chatbot e-service and customer satisfaction regarding luxury brands. Journal of Business Research, 117, 587-595. https://doi.org/10.1016/j.jbusres.2018.10.004
  • Çokluk, Ö., Şekercioğlu,G. & Büyüköztürk, Ş. (2010). Sosyal bilimler için çok değişkenli istatistik, SPSS ve LISREL uygulamaları. Ankara: Pegem
  • Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Auarterly, 319-340.
  • de Cosmo, L. M., Piper, L., & Di Vittorio, A. (2021). The role of attitude toward chatbots and privacy concern on the relationship between attitude toward mobile advertising and behavioral intent to use chatbots. Italian Journal of Marketing, 2021(1), 83-102. https://doi.org/10.1007/s43039-021-00020-1
  • Fishbein, M., & Ajzen, I. (1975). Belief, attitude, intention, and behavior: An introduction to theory and research. Reading, MA: Addison-Wesley.
  • Frost & Sullivan. (2025, January 12). Artificial intelligence in e-commerce: Current trends and future projections. https://www.frost.com
  • Gefen, D., Karahanna, E., & Straub, D. W. (2003). Trust and TAM in online shopping: An integrated model. MIS Quarterly, 27(1), 51–90. https://doi.org/10.2307/30036519
  • Ghazali, E., Mutum, D. S., & Lun, N. K. (2024). Expectations and beyond: The nexus of AI instrumentality and brand credibility in voice assistant retention using extended expectation-confirmation model. Journal of Consumer Behaviour, 23(2), 655–675. https://doi.org/10.1002/cb.2228
  • Gümüş, N., & Çark, Ö. (2021). The effect of customers’ attitudes towards chatbots on their experience and behavioural intention in Turkey. Interdisciplinary Description of Complex Systems: INDECS, 19(3), 420–436. https://doi.org/10.7906/indecs.19.3.6
  • Hair, J. F., Black, W. R., Babin, B. J., & Anderson, R. E. (2010). Multivariate data analysis (7th ed., pp. 41–86). Pearson Prentice Hall.
  • Hair Jr, J. F., Gabriel, M. L., & Patel, V. K. (2014). AMOS covariance-based structural equation modeling (CB-SEM): Guidelines on its application as a marketing research tool. REMark: Revista Brasileira de Marketing, 13(2).
  • Hildebrand, C., & Bergner, A. (2019). AI-driven sales automation: Using chatbots to boost sales. NIM Marketing Intelligence Review, 11(2), 36–41. https://doi.org/10.2478/nimmir-2019-0014
  • Hoy, M. B. (2018). Alexa, Siri, Cortana, and More: An ıntroduction to voice assistants. Medical Reference Services Quarterly, 37(1), 81-88. https://doi.org/10.1080/02763869.2018.1404391
  • Ikumoro, A. O., & Jawad, M. S. (2019). Intention to use ıntelligent conversational agents in ecommerce among malaysian smes, use of technology (UTAUT), and T-O-E. International Journal of Academic Research in Business and Social Sciences, 9(11), 205–235. http://dx.doi.org/10.6007/IJARBSS/v9-i11/6544
  • Joshi, H. (2021). Perception and adoption of customer service chatbots among millennials: An empirical validation in the Indian context [Conference presentation]. Proceedings of the 17th International Conference on Web Information Systems and Technologies (WEBIST 2021). https://doi.org/10.5220/0010718400003058
  • Joo, J., & Sang, Y. (2013). Exploring Koreans’ smartphone usage: An integrated model of the technology acceptance model and uses and gratifications theory. Computers in Human Behavior, 29(6), 2512–2518.
  • Kane, D. A. (2016). The role of chatbots in teaching and learning. In S. Rice & M. N. Gregor (Eds.), E-learning and the academic library: Essays on innovative initiatives (pp. 131–147). McFarland. https://dash.lib.uci.edu/stash/dataset/doi:10.7280/D1P075
  • Kasilingam, D. L. (2020). Understanding the attitude and intention to use smartphone chatbots for shopping. Technology in Society, 62, 101280. https://doi.org/10.1016/j.techsoc.2020.101280
  • Katz, E., Blumler, J. G., & Gurevitch, M. (1973). Uses and gratifications research. Public Opinion Quarterly, 37(4), 509–523.
  • Khan, M. M. (2020, December). Development of an e-commerce sales chatbot. In 2020 IEEE 17th International Conference on Smart Communities: Improving Quality of Life Using ICT, IoT and AI (HONET) (pp. 173–176). IEEE.
  • Kim, C., Mirusmonov, M., & Lee, I. (2010). An empirical examination of factors influencing the intention to use mobile payment. Computers in Human Behavior, 26(3), 310–322.
  • Kline, R. B. (2011). Principles and practice of structural equation modeling. Guilford Press.
  • Kline, R. B. (2018). Assessing statistical aspects of test fairness with structural equation modelling. In Fairness issues in educational assessment (pp. 116–134). Routledge.
  • Lappeman, J., Marlie, S., Johnson, T., & Poggenpoel, S. (2022). Trust and digital privacy: Willingness to disclose personal information to banking chatbot services. Journal of Financial Services Marketing, 28(2), 337–347. https://doi.org/10.1057/s41264-022-00154-z
  • Letheren, K., Russell-Bennett, R., & Whittaker, L. (2020). Black, white or grey magic? Our future with artificial intelligence. Journal of Marketing Management, 36(3–4), 216–232. https://doi.org/10.1080/0267257X.2019.1706306
  • Li, L., Lee, K. Y., Emokpae, E., & Yang, S. B. (2021). What makes you continuously use chatbot services? Evidence from Chinese online travel agencies. Electronic Markets, 31, 1–25. https://doi.org/10.1007/s12525-020-00454-z
  • Lin, C. H., Shih, H. Y., & Sher, P. J. (2007). Integrating technology readiness into technology acceptance: The TRAM model. Psychology & Marketing, 24(7), 641–657.
  • Luo, M. M., Chea, S., & Chen, J. S. (2011). Web-based information service adoption: A comparison of the motivational model and the uses and gratifications theory. Decision Support Systems, 51(1), 21–30. https://doi.org/10.1016/j.dss.2010.11.015
  • Luo, S. F., & Lee, T. Z. (2011). The influence of trust and usefulness on customer perceptions of e-service quality. Social Behavior and Personality: An International Journal, 39(6), 825–837.
  • Marangunić, N., & Granić, A. (2015). Technology acceptance model: A literature review from 1986 to 2013. Universal Access in the Information Society, 14, 81–95. https://doi.org/10.1007/s10209-014-0348-1
  • Markets Insider. (2025, January 6). Global chatbot market (2020 to 2026) – Rise in demand for AI-based chatbots to deliver enhanced customer experience presents opportunities. https://markets.businessinsider.com/news/stocks/global-chatbot-market-2020-to-2026-rise-in-demand-for-ai-based-chatbots-to-deliver-enhanced-customer-experience-presents-opportunities-1030269345
  • McLean, G., & Osei-Frimpong, K. (2019). Hey Alexa… Examine the variables influencing the use of artificial intelligent in-home voice assistants. Computers in Human Behavior, 99, 28–37. https://doi.org/10.1016/j.chb.2019.05.009
  • McLean, G., Osei-Frimpong, K., & Barhorst, J. (2021). Alexa, do voice assistants influence consumer brand engagement? Examining the role of AI powered voice assistants in influencing consumer brand engagement. Journal of Business Research, 124, 312–328. https://doi.org/10.1016/j.jbusres.2020.11.045
  • Minge, M., Bürglen, J., & Cymek, D. H. (2014). Exploring the potential of gameful interaction design of ICT for the elderly [Conference presentation]. HCI International 2014 Posters’ Extended Abstracts, Heraklion, Greece.
  • Mohammadi, H. (2015). A study of mobile banking usage in Iran. International Journal of Bank Marketing, 33(6), 733–759. https://doi.org/10.1108/IJBM-08-2014-0114
  • Mohebbi, S., Khatibi, V., & Keramati, A. (2012). A household internet adoption model based on integration of technology acceptance model, theory of planned behavior, and uses and gratifications theory: An empirical study on Iranian households. International Journal of E-Adoption, 4(1), 51–69.
  • Muchran, M., & Ahmar, A. S. (2019). Application of TAM model to the use of information technology. arXiv Preprint. https://doi.org/10.48550/arXiv.1901.11358
  • Murtarelli, G., Collina, C., & Romenti, S. (2023). “Hi! How can I help you today?” Investigating the quality of chatbots–millennials relationship within the fashion industry. The TQM Journal, 35(3), 719–733. https://doi.org/10.1108/TQM-01-2022-0010
  • Nguyen, X., Tran, H., Phan, H., & Phan, T. (2020). Factors influencing customer satisfaction: The case of Facebook chatbot Vietnam. International Journal of Data and Network Science, 4(2), 167–178. https://doi.org/10.5267/j.ijdns.2020.2.001
  • Palmgreen, P. (1984). Uses and gratifications: A theoretical perspective. Annals of the International Communication Association, 8(1), 20–55.
  • Pantano, E., & Pizzi, G. (2020). Forecasting artificial intelligence on online customer assistance: Evidence from chatbot patents analysis. Journal of Retailing and Consumer Services, 55, 102096. https://doi.org/10.1016/j.jretconser.2020.102096
  • Rahmayanti, R., Haryati, T., Miyono, N., & Safitri, A. (2021). Pengaruh kompetensi profesional, motivasi kerja dan disiplin kerja terhadap kinerja guru sekolah menengah atas negeri se-Kabupaten Pemalang. Jurnal Manajemen Pendidikan: Jurnal Ilmiah Administrasi, Manajemen dan Kepemimpinan Pendidikan, 3(1), 43–55.
  • Reisinger, Y., & Turner, L. (1999). Structural equation modeling with LISREL: Application in tourism. Tourism Management, 20(1), 71–88. https://doi.org/10.1016/S0261-5177(98)00104-6.
  • Renaud, K., & Ramsay, J. (2007). Now what was that password again? A more flexible way of identifying and authenticating our seniors. Behaviour & Information Technology, 26(4), 309–322.
  • Renaud, K., & Van Biljon, J. (2008, October). Predicting technology acceptance and adoption by the elderly: A qualitative study [Conference presentation]. Proceedings of SAICSIT ’08, Wilderness, South Africa.
  • Rese, A., Ganster, L., & Baier, D. (2020). Chatbots in retailers’ customer communication: How to measure their acceptance? Journal of Retailing and Consumer Services, 56, 102176. https://doi.org/10.1016/j.jretconser.2020.102176
  • Rzepka, C., Berger, B., & Hess, T. (2020). Why another customer channel? Consumers’ perceived benefits and costs of voice commerce. [Manuscript/working paper – yayın bilgisi eksik].
  • Rigdon, E. E. (1998). Structural equation modeling. In G. A. Marcoulides (Ed.), Modern methods for business research (pp. 251–294). Lawrence Erlbaum.
  • Sánchez-Prieto, J. C., Olmos-Migueláñez, S., & García-Peñalvo, F. J. (2017). M-learning and pre-service teachers: An assessment of the behavioral intention using an expanded TAM model. Computers in Human Behavior, 72, 644–654. https://doi.org/10.1016/j.chb.2016.09.061
  • Severin, W. J., & Tankard, J. W. Jr. (2001). Communication theories: Origins, methods, and uses in the mass media (5th ed.). Addison Wesley Longman.
  • Schierz, P. G., Schilke, O., & Wirtz, B. W. (2010). Understanding consumer acceptance of mobile payment services: An empirical analysis. Electronic Commerce Research and Applications, 9(3), 209–216.
  • Schumacker, R. E., & Lomax, R. G. (2004). A beginner’s guide to structural equation modeling (2nd ed.). Lawrence Erlbaum.
  • Singh, A., Shivam, S., & Ramasubramanian, K. (2019). Building an enterprise chatbot: Work with protected enterprise data using open source frameworks. Apress.
  • Statista. (2025, January 12). AI investment and funding worldwide. https://www.statista.com/statistics/966893/worldwide-chatbot-market-value/
  • Statista. (2025, May 12). Chatbot recommendations influencing purchase decisions in 2024, by frequency.https://www.statista.com/statistics/1538267/chatbot-influence-on-purchase-decisions/
  • Sundar, S. S. (2008). The MAIN model: A heuristic approach to understanding technology effects on credibility. In Digital media, youth, and credibility (pp. 73–100). MacArthur Foundation.
  • Turja, T., Aaltonen, I., Taipale, S., & Oksanen, A. (2020). Robot acceptance model for care (RAM-care): A principled approach to the intention to use care robots. Information & Management, 57(5), 103220. https://doi.org/10.1016/j.im.2019.103220
  • Uzun, N. B., Gelbal, S., & Öğretmen, T. (2010). TIMMS-R başarı ve duyuşsal özellikler arasındaki ilişkinin modellenmesi ve modelin cinsiyetler bakımından karşılaştırılması. Kastamonu Eğitim Dergisi, 18(2), 531–544.
  • Venkatesh, V., & Bala, H. (2008). Technology acceptance model 3 and a research agenda on interventions. Decision Sciences, 39(2), 273–315.
  • Wallace, R. S. (2009). The anatomy of A.L.I.C.E. In R. Epstein, G. Roberts, & G. Beber (Eds.), Parsing the Turing test (pp. 181–210). Springer. https://doi.org/10.1007/978-1-4020-6710-5_13
  • Wang, Q., & Sun, X. (2016). Investigating gameplay intention of the elderly using an extended technology acceptance model (ETAM). Technological Forecasting and Social Change, 107, 59–68. https://doi.org/10.1016/j.techfore.2015.10.024
  • Weizenbaum, J. (1966). ELIZA—A computer program for the study of natural language communication between man and machine. Communications of the ACM, 9(1), 36–45.
  • Xiao, S., & Benbasat, I. (2002). The impact of internalization and familiarity on trust and adoption of recommendation agents. Unpublished working paper (02-MIS-006). University of British Columbia, Vancouver, Canada.
  • Yagoda, R. E., & Gillan, D. J. (2012). You want me to trust a robot? The development of a human–robot interaction trust scale. International Journal of Social Robotics, 4, 235–248.
  • Yaylagül, L. (2010). Kitle iletişim kuramları: Egemen ve eleştirel yaklaşımlar. Dipnot Yayınları.
  • Youn, S. Y., Lee, J. E., & Ha-Brookshire, J. (2021). Fashion consumers’ channel switching behavior during the COVID-19: Protection motivation theory in the extended planned behavior framework. Clothing and Textiles Research Journal, 39(2), 139–156. https://doi.org/10.1177/0887302X20986521
  • Zumstein, D., & Hundertmark, S. (2017). Chatbots—An interactive technology for personalized communication, transactions and services. IADIS International Journal on WWW/Internet, 15(1), 96–109.

Tüketicilerin Sohbet Robotlarına (Chatbots) Karşı Tutum ve Güvenlerinin Teknoloji Kabul Modeli ve Kullanım ve Doyumlar Teorisi Çerçevesinde İncelenmesi

Yıl 2025, Cilt: 10 Sayı: 3, 1167 - 1200
https://doi.org/10.25229/beta.1669811

Öz

Teknoloji çağının getirdiği dijital dönüşüm, müşteri deneyiminin önemini artırmış ve işletmelerin stratejik kararlarında yapay zekâ destekli dijital akıllı sistemlerin kullanımını zorunlu hale getirmiştir. Bu akıllı sistemlerden biri de kullanıcıların ihtiyaçlarını hızlı ve verimli bir şekilde karşılamak amacıyla geliştirilen diyalog tabanlı bilgisayar programları olan sohbet robotlarıdır. Bu çalışmada, çevrim içi alışveriş yapan tüketicilerin sohbet robotlarına yönelik tutumları; Teknoloji Kabul Modeli, Kullanım ve Doyumlar Teorisi ve sohbet robotlarına duyulan güven değişkenleri çerçevesinde incelenmek amaçlanmıştır. Bu amaç doğrultusunda 399 kişiden anket yöntemiyle toplanan veriler SPSS ve LISREL paket programları aracılığıyla Yapısal Eşitlik Modeli kullanılarak analiz edilmiştir. Çalışmanın bulgularına göre tüketicilerin teknoloji kabul modeli tutumları ile sohbet robotlarına olan güven ve doyumları arasında pozitif bir ilişki olduğu görülmüştür. Ayrıca tüketicilerin sohbet robotlarına duydukları güven arttıkça da kullanım ve doyumlar teorisi tutumlarının arttığı ortaya konmuştur. Sonuç olarak tüketicilerin yeni teknolojileri kabul etmeleri ve güven duymaları durumunda, sohbet robotlarına yönelik tutumlarının ve bu teknolojileri kullanma doyumlarının arttığını söylemek mümkündür.

Kaynakça

  • Adıgüzel, A. (2012). Okula ilişkin tutum ölçeğinin geçerlik ve güvenirlik çalışması. Elektronik Sosyal Bilimler Dergisi, 11(40), 30–45.
  • Alikılıç, Ö., Gülay, G., & Binbir, S. (2013). Kullanımlar ve doyumlar kuramı çerçevesinde Facebook uygulamalarının incelenmesi: Yaşar Üniversitesi öğrencileri üzerine bir araştırma. İletişim Kuram ve Araştırma Dergisi, 1(37), 41–67.
  • Alt, M. A., Vizeli, I., & Săplăcan, Z. (2021). Banking with a chatbot – A study on technology acceptance. Studia Universitatis Babeș-Bolyai Oeconomica, 66, 13–35. https://doi.org/10.2478/subboec-2021-0002
  • Arsenijevic, U., & Jovic, M. (2019, September 30–October 4). Artificial intelligence marketing: Chatbots [Conference presentation]. 2019 International Conference on Artificial Intelligence: Applications and Innovations, Belgrade, Serbia. https://doi.org/10.1109/IC-AIAI48757.2019.00010
  • Atwal, G., & Bryson, D. (2021). Antecedents of intention to adopt artificial intelligence services by consumers in personal financial investing. Strategic Change, 30(3), 293-298. https://doi.org/10.1002/jsc.2412
  • Ayhan, B., & Çavuş, S. (2014). İzleyici araştırmalarında değişim: kullanımlar ve doyumlardan bağımlılığa. Selçuk İletişim, 8(2), 32-60.
  • Barry, B., & Crant, J. M. (2000). Dyadic communication relationships in organizations: An attribution/expectancy approach. Organization Science, 11(6), 648-664.
  • Brandtzaeg, P. B., & Følstad, A. (2017). Trust and distrust in online fact-checking servicesi. Communications of the ACM, 60(9), 65-71. https://doi.org/10.1145/3122803
  • Brill, T. M., Munoz, L., & Miller, R. J. (2019). Siri, Alexa, and other digital assistants: a study of customer satisfaction with artificial intelligence applications. Journal of Marketing Management, 35(15-16), 1401-1436. https://doi.org/10.1080/0267257X.2019.1687571
  • Brachten, F., Kissmer, T., & Stieglitz, S. (2021). The acceptance of chatbots in an enterprise context–A survey study. International Journal of Information Management, 60, 102375. https://doi.org/10.1016/j.ijinfomgt.2021.102375
  • Broeck, E., Zarouali, B., & Poels, K. (2019). Chatbot advertising effectiveness: When does the message get through? Computers in Human Behavior, 98, 150–157.
  • Browne, M. W., & Cudeck, R. (1993). Alternative ways of assessing model fit. In K. A. Bollen & J. S. Long (Eds.), Testing structural equation models (pp. 136-162). Newbury Park, CA: Sage.
  • Bollen, K. A. (1989). Structural equations with latent variables. John Wiley & Sons.
  • Bolton, G., Greiner, B., & Ockenfels, A. (2013). Engineering trust: reciprocity in the production of reputation information. Management Science, 59(2), 265-285.
  • Buabeng-Andoh, C. (2018). Predicting students’ intention to adopt mobile learning: A combination of theory of reasoned action and technology acceptance model. Journal of Research in Innovative Teaching & Learning, 11(2), 178-191. https://doi.org/10.1108/JRIT-03-2017-0004
  • Candela, E. (2018). Consumers’ perception and attitude towards chatbots’ adoption: A focus on the Italian market [Unpublished master’s dissertation]. Aalborg University.
  • Chen, G. M. (2011). Tweet this: a uses and gratifications perspective on how active twitter use gratifies a need to connect with others. Computers in Human Behavior, 27(2): 755-762.
  • Cheng, Y., & Jiang, H. (2022). Customer–brand relationship in the era of artificial intelligence: Understanding the role of chatbot marketing efforts. Journal of Product & Brand Management, 31(2), 252-264. https://doi.org/10.1108/JPBM-05-2020-2907
  • Childers, T. L., Carr, C. L., Peck, J., & Carson, S. (2001). Hedonic and utilitarian motivations for online retail shopping behavior. Journal of Retailing, 77(4), 511-535.
  • Colby, K. M. (1975). Artificial Paranoia: A Computer Simulation of Paranoid Processes. Pergamon Press.
  • Chung, M., Ko, E., Joung, H., & Kim, S. J. (2020). Chatbot e-service and customer satisfaction regarding luxury brands. Journal of Business Research, 117, 587-595. https://doi.org/10.1016/j.jbusres.2018.10.004
  • Çokluk, Ö., Şekercioğlu,G. & Büyüköztürk, Ş. (2010). Sosyal bilimler için çok değişkenli istatistik, SPSS ve LISREL uygulamaları. Ankara: Pegem
  • Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Auarterly, 319-340.
  • de Cosmo, L. M., Piper, L., & Di Vittorio, A. (2021). The role of attitude toward chatbots and privacy concern on the relationship between attitude toward mobile advertising and behavioral intent to use chatbots. Italian Journal of Marketing, 2021(1), 83-102. https://doi.org/10.1007/s43039-021-00020-1
  • Fishbein, M., & Ajzen, I. (1975). Belief, attitude, intention, and behavior: An introduction to theory and research. Reading, MA: Addison-Wesley.
  • Frost & Sullivan. (2025, January 12). Artificial intelligence in e-commerce: Current trends and future projections. https://www.frost.com
  • Gefen, D., Karahanna, E., & Straub, D. W. (2003). Trust and TAM in online shopping: An integrated model. MIS Quarterly, 27(1), 51–90. https://doi.org/10.2307/30036519
  • Ghazali, E., Mutum, D. S., & Lun, N. K. (2024). Expectations and beyond: The nexus of AI instrumentality and brand credibility in voice assistant retention using extended expectation-confirmation model. Journal of Consumer Behaviour, 23(2), 655–675. https://doi.org/10.1002/cb.2228
  • Gümüş, N., & Çark, Ö. (2021). The effect of customers’ attitudes towards chatbots on their experience and behavioural intention in Turkey. Interdisciplinary Description of Complex Systems: INDECS, 19(3), 420–436. https://doi.org/10.7906/indecs.19.3.6
  • Hair, J. F., Black, W. R., Babin, B. J., & Anderson, R. E. (2010). Multivariate data analysis (7th ed., pp. 41–86). Pearson Prentice Hall.
  • Hair Jr, J. F., Gabriel, M. L., & Patel, V. K. (2014). AMOS covariance-based structural equation modeling (CB-SEM): Guidelines on its application as a marketing research tool. REMark: Revista Brasileira de Marketing, 13(2).
  • Hildebrand, C., & Bergner, A. (2019). AI-driven sales automation: Using chatbots to boost sales. NIM Marketing Intelligence Review, 11(2), 36–41. https://doi.org/10.2478/nimmir-2019-0014
  • Hoy, M. B. (2018). Alexa, Siri, Cortana, and More: An ıntroduction to voice assistants. Medical Reference Services Quarterly, 37(1), 81-88. https://doi.org/10.1080/02763869.2018.1404391
  • Ikumoro, A. O., & Jawad, M. S. (2019). Intention to use ıntelligent conversational agents in ecommerce among malaysian smes, use of technology (UTAUT), and T-O-E. International Journal of Academic Research in Business and Social Sciences, 9(11), 205–235. http://dx.doi.org/10.6007/IJARBSS/v9-i11/6544
  • Joshi, H. (2021). Perception and adoption of customer service chatbots among millennials: An empirical validation in the Indian context [Conference presentation]. Proceedings of the 17th International Conference on Web Information Systems and Technologies (WEBIST 2021). https://doi.org/10.5220/0010718400003058
  • Joo, J., & Sang, Y. (2013). Exploring Koreans’ smartphone usage: An integrated model of the technology acceptance model and uses and gratifications theory. Computers in Human Behavior, 29(6), 2512–2518.
  • Kane, D. A. (2016). The role of chatbots in teaching and learning. In S. Rice & M. N. Gregor (Eds.), E-learning and the academic library: Essays on innovative initiatives (pp. 131–147). McFarland. https://dash.lib.uci.edu/stash/dataset/doi:10.7280/D1P075
  • Kasilingam, D. L. (2020). Understanding the attitude and intention to use smartphone chatbots for shopping. Technology in Society, 62, 101280. https://doi.org/10.1016/j.techsoc.2020.101280
  • Katz, E., Blumler, J. G., & Gurevitch, M. (1973). Uses and gratifications research. Public Opinion Quarterly, 37(4), 509–523.
  • Khan, M. M. (2020, December). Development of an e-commerce sales chatbot. In 2020 IEEE 17th International Conference on Smart Communities: Improving Quality of Life Using ICT, IoT and AI (HONET) (pp. 173–176). IEEE.
  • Kim, C., Mirusmonov, M., & Lee, I. (2010). An empirical examination of factors influencing the intention to use mobile payment. Computers in Human Behavior, 26(3), 310–322.
  • Kline, R. B. (2011). Principles and practice of structural equation modeling. Guilford Press.
  • Kline, R. B. (2018). Assessing statistical aspects of test fairness with structural equation modelling. In Fairness issues in educational assessment (pp. 116–134). Routledge.
  • Lappeman, J., Marlie, S., Johnson, T., & Poggenpoel, S. (2022). Trust and digital privacy: Willingness to disclose personal information to banking chatbot services. Journal of Financial Services Marketing, 28(2), 337–347. https://doi.org/10.1057/s41264-022-00154-z
  • Letheren, K., Russell-Bennett, R., & Whittaker, L. (2020). Black, white or grey magic? Our future with artificial intelligence. Journal of Marketing Management, 36(3–4), 216–232. https://doi.org/10.1080/0267257X.2019.1706306
  • Li, L., Lee, K. Y., Emokpae, E., & Yang, S. B. (2021). What makes you continuously use chatbot services? Evidence from Chinese online travel agencies. Electronic Markets, 31, 1–25. https://doi.org/10.1007/s12525-020-00454-z
  • Lin, C. H., Shih, H. Y., & Sher, P. J. (2007). Integrating technology readiness into technology acceptance: The TRAM model. Psychology & Marketing, 24(7), 641–657.
  • Luo, M. M., Chea, S., & Chen, J. S. (2011). Web-based information service adoption: A comparison of the motivational model and the uses and gratifications theory. Decision Support Systems, 51(1), 21–30. https://doi.org/10.1016/j.dss.2010.11.015
  • Luo, S. F., & Lee, T. Z. (2011). The influence of trust and usefulness on customer perceptions of e-service quality. Social Behavior and Personality: An International Journal, 39(6), 825–837.
  • Marangunić, N., & Granić, A. (2015). Technology acceptance model: A literature review from 1986 to 2013. Universal Access in the Information Society, 14, 81–95. https://doi.org/10.1007/s10209-014-0348-1
  • Markets Insider. (2025, January 6). Global chatbot market (2020 to 2026) – Rise in demand for AI-based chatbots to deliver enhanced customer experience presents opportunities. https://markets.businessinsider.com/news/stocks/global-chatbot-market-2020-to-2026-rise-in-demand-for-ai-based-chatbots-to-deliver-enhanced-customer-experience-presents-opportunities-1030269345
  • McLean, G., & Osei-Frimpong, K. (2019). Hey Alexa… Examine the variables influencing the use of artificial intelligent in-home voice assistants. Computers in Human Behavior, 99, 28–37. https://doi.org/10.1016/j.chb.2019.05.009
  • McLean, G., Osei-Frimpong, K., & Barhorst, J. (2021). Alexa, do voice assistants influence consumer brand engagement? Examining the role of AI powered voice assistants in influencing consumer brand engagement. Journal of Business Research, 124, 312–328. https://doi.org/10.1016/j.jbusres.2020.11.045
  • Minge, M., Bürglen, J., & Cymek, D. H. (2014). Exploring the potential of gameful interaction design of ICT for the elderly [Conference presentation]. HCI International 2014 Posters’ Extended Abstracts, Heraklion, Greece.
  • Mohammadi, H. (2015). A study of mobile banking usage in Iran. International Journal of Bank Marketing, 33(6), 733–759. https://doi.org/10.1108/IJBM-08-2014-0114
  • Mohebbi, S., Khatibi, V., & Keramati, A. (2012). A household internet adoption model based on integration of technology acceptance model, theory of planned behavior, and uses and gratifications theory: An empirical study on Iranian households. International Journal of E-Adoption, 4(1), 51–69.
  • Muchran, M., & Ahmar, A. S. (2019). Application of TAM model to the use of information technology. arXiv Preprint. https://doi.org/10.48550/arXiv.1901.11358
  • Murtarelli, G., Collina, C., & Romenti, S. (2023). “Hi! How can I help you today?” Investigating the quality of chatbots–millennials relationship within the fashion industry. The TQM Journal, 35(3), 719–733. https://doi.org/10.1108/TQM-01-2022-0010
  • Nguyen, X., Tran, H., Phan, H., & Phan, T. (2020). Factors influencing customer satisfaction: The case of Facebook chatbot Vietnam. International Journal of Data and Network Science, 4(2), 167–178. https://doi.org/10.5267/j.ijdns.2020.2.001
  • Palmgreen, P. (1984). Uses and gratifications: A theoretical perspective. Annals of the International Communication Association, 8(1), 20–55.
  • Pantano, E., & Pizzi, G. (2020). Forecasting artificial intelligence on online customer assistance: Evidence from chatbot patents analysis. Journal of Retailing and Consumer Services, 55, 102096. https://doi.org/10.1016/j.jretconser.2020.102096
  • Rahmayanti, R., Haryati, T., Miyono, N., & Safitri, A. (2021). Pengaruh kompetensi profesional, motivasi kerja dan disiplin kerja terhadap kinerja guru sekolah menengah atas negeri se-Kabupaten Pemalang. Jurnal Manajemen Pendidikan: Jurnal Ilmiah Administrasi, Manajemen dan Kepemimpinan Pendidikan, 3(1), 43–55.
  • Reisinger, Y., & Turner, L. (1999). Structural equation modeling with LISREL: Application in tourism. Tourism Management, 20(1), 71–88. https://doi.org/10.1016/S0261-5177(98)00104-6.
  • Renaud, K., & Ramsay, J. (2007). Now what was that password again? A more flexible way of identifying and authenticating our seniors. Behaviour & Information Technology, 26(4), 309–322.
  • Renaud, K., & Van Biljon, J. (2008, October). Predicting technology acceptance and adoption by the elderly: A qualitative study [Conference presentation]. Proceedings of SAICSIT ’08, Wilderness, South Africa.
  • Rese, A., Ganster, L., & Baier, D. (2020). Chatbots in retailers’ customer communication: How to measure their acceptance? Journal of Retailing and Consumer Services, 56, 102176. https://doi.org/10.1016/j.jretconser.2020.102176
  • Rzepka, C., Berger, B., & Hess, T. (2020). Why another customer channel? Consumers’ perceived benefits and costs of voice commerce. [Manuscript/working paper – yayın bilgisi eksik].
  • Rigdon, E. E. (1998). Structural equation modeling. In G. A. Marcoulides (Ed.), Modern methods for business research (pp. 251–294). Lawrence Erlbaum.
  • Sánchez-Prieto, J. C., Olmos-Migueláñez, S., & García-Peñalvo, F. J. (2017). M-learning and pre-service teachers: An assessment of the behavioral intention using an expanded TAM model. Computers in Human Behavior, 72, 644–654. https://doi.org/10.1016/j.chb.2016.09.061
  • Severin, W. J., & Tankard, J. W. Jr. (2001). Communication theories: Origins, methods, and uses in the mass media (5th ed.). Addison Wesley Longman.
  • Schierz, P. G., Schilke, O., & Wirtz, B. W. (2010). Understanding consumer acceptance of mobile payment services: An empirical analysis. Electronic Commerce Research and Applications, 9(3), 209–216.
  • Schumacker, R. E., & Lomax, R. G. (2004). A beginner’s guide to structural equation modeling (2nd ed.). Lawrence Erlbaum.
  • Singh, A., Shivam, S., & Ramasubramanian, K. (2019). Building an enterprise chatbot: Work with protected enterprise data using open source frameworks. Apress.
  • Statista. (2025, January 12). AI investment and funding worldwide. https://www.statista.com/statistics/966893/worldwide-chatbot-market-value/
  • Statista. (2025, May 12). Chatbot recommendations influencing purchase decisions in 2024, by frequency.https://www.statista.com/statistics/1538267/chatbot-influence-on-purchase-decisions/
  • Sundar, S. S. (2008). The MAIN model: A heuristic approach to understanding technology effects on credibility. In Digital media, youth, and credibility (pp. 73–100). MacArthur Foundation.
  • Turja, T., Aaltonen, I., Taipale, S., & Oksanen, A. (2020). Robot acceptance model for care (RAM-care): A principled approach to the intention to use care robots. Information & Management, 57(5), 103220. https://doi.org/10.1016/j.im.2019.103220
  • Uzun, N. B., Gelbal, S., & Öğretmen, T. (2010). TIMMS-R başarı ve duyuşsal özellikler arasındaki ilişkinin modellenmesi ve modelin cinsiyetler bakımından karşılaştırılması. Kastamonu Eğitim Dergisi, 18(2), 531–544.
  • Venkatesh, V., & Bala, H. (2008). Technology acceptance model 3 and a research agenda on interventions. Decision Sciences, 39(2), 273–315.
  • Wallace, R. S. (2009). The anatomy of A.L.I.C.E. In R. Epstein, G. Roberts, & G. Beber (Eds.), Parsing the Turing test (pp. 181–210). Springer. https://doi.org/10.1007/978-1-4020-6710-5_13
  • Wang, Q., & Sun, X. (2016). Investigating gameplay intention of the elderly using an extended technology acceptance model (ETAM). Technological Forecasting and Social Change, 107, 59–68. https://doi.org/10.1016/j.techfore.2015.10.024
  • Weizenbaum, J. (1966). ELIZA—A computer program for the study of natural language communication between man and machine. Communications of the ACM, 9(1), 36–45.
  • Xiao, S., & Benbasat, I. (2002). The impact of internalization and familiarity on trust and adoption of recommendation agents. Unpublished working paper (02-MIS-006). University of British Columbia, Vancouver, Canada.
  • Yagoda, R. E., & Gillan, D. J. (2012). You want me to trust a robot? The development of a human–robot interaction trust scale. International Journal of Social Robotics, 4, 235–248.
  • Yaylagül, L. (2010). Kitle iletişim kuramları: Egemen ve eleştirel yaklaşımlar. Dipnot Yayınları.
  • Youn, S. Y., Lee, J. E., & Ha-Brookshire, J. (2021). Fashion consumers’ channel switching behavior during the COVID-19: Protection motivation theory in the extended planned behavior framework. Clothing and Textiles Research Journal, 39(2), 139–156. https://doi.org/10.1177/0887302X20986521
  • Zumstein, D., & Hundertmark, S. (2017). Chatbots—An interactive technology for personalized communication, transactions and services. IADIS International Journal on WWW/Internet, 15(1), 96–109.
Toplam 87 adet kaynakça vardır.

Ayrıntılar

Birincil Dil Türkçe
Konular İşletme
Bölüm Araştırma Makaleleri
Yazarlar

Reyhan Bahar 0000-0001-5872-6275

Erken Görünüm Tarihi 20 Ekim 2025
Yayımlanma Tarihi 27 Ekim 2025
Gönderilme Tarihi 3 Nisan 2025
Kabul Tarihi 9 Temmuz 2025
Yayımlandığı Sayı Yıl 2025 Cilt: 10 Sayı: 3

Kaynak Göster

APA Bahar, R. (2025). Tüketicilerin Sohbet Robotlarına (Chatbots) Karşı Tutum ve Güvenlerinin Teknoloji Kabul Modeli ve Kullanım ve Doyumlar Teorisi Çerçevesinde İncelenmesi. Bulletin of Economic Theory and Analysis, 10(3), 1167-1200. https://doi.org/10.25229/beta.1669811

OA_transp.png

by-nc.png
Bu dergide yayımlanan eserler Creative Commons Atıf 4.0 Uluslararası Lisansı ile lisanslanmaktadır.