Research Article
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Investigation of Online Purchasing Behavior According to Different Generations with Technology Acceptance Model

Year 2025, Issue: 38, 136 - 155, 20.01.2025
https://doi.org/10.54600/igdirsosbilder.1562479

Abstract

The main aim of this study is to comparatively examine the intention to purchase online in the context of Generation X, Y and Z consumers within the framework of the Consumer Technology Acceptance Model. This study was studied in a quantitative pattern and was conducted for 661 consumers in Mersin province, determined by convenience sampling method. Normality and deviation analyses, validity and reliability analyses, and factor analyzes were conducted with the data obtained. Structural equation modeling was used to test the determined hypotheses, and all analyzes were carried out using SPSS 24.0 and AMOS 23.0 software packages. Individuals in the generations X, Y and Z discussed within the scope of the study may show different characteristics depending on the generations they belong to. The prediction that generations whose habits and perceptions regarding purchasing behavior may differ will differ in terms of adopting technological innovations has been confirmed according to the results obtained from the research. One of the main limitations of this study is that it was collected through convenience sampling. The other is to reach the target generation age groups in the study. The managerial contribution of this research is that internet purchasing tools should not be designed solely based on ease of use and usefulness and emotional dimensions should be evaluated together with the target market and target consumer groups (Generation X, Y and Z) during market research to more accurately assess the level of acceptance of the innovation. According to literature analysis, no study was found examining the relationship between the generations of the consumer technology acceptance model. The aim of this research is to add to the literature by examining the relationship between generations with the consumer technology acceptance model and to provide a more general conceptual basis in consumer behavior.

References

  • Ajzen, I. (1985). From Intentions to Actions: A Theory of Planned Behavior, J. Kuhl ve J. Beckmen (Eds.). Action Control from Cognition to Behavior içinde (11-39). Berlin: Springer-Verlag. 1. Baskı.
  • Bagozzi, R. P., Baumgartner, H., & Yi, Y. (1992). State versus action orientation and the theory of reasoned action: An application to coupon usage. Journal of consumer research, 18(4), 505-518.
  • Barutçu, S. (2010). Mobil Pazarlama. İ. Varinli ve K. Çatı (Ed.), Güncel Pazarlama Yaklaşımlarından Seçmeler içinde (259-285). 2. Baskı, Ankara: Detay Yayıncılık.
  • Basu, A. & S. Muylle. (2003). Online Support for Commerce Processes by Web Retailers, Decision Support Systems, 34(4), 379‐95.
  • Bruner II, G. C., & Kumar, A. (2005). Applying T.A.M. to consumer usage of handheld Internet devices. Journal of Business Research, 58, 553–558.
  • Chang, M. K., & Cheung, W. (2001). Determinants of the intention to use Internet/ WWW at work: A confirmatory study. Information & Management, 39, 1–14.
  • Childers, T. L., Carr, C. L., Peck, J., & Carson, S. (2001). Hedonic and utilitarian motivations for online retail shopping behavior. Journal of Retailing, 77, 511–536.
  • Cohen, J., & Areni, C. (1991). Affect and consumer behavior. In T. S. Robertson & H. H. Kassarjian (Eds.), Handbook of consumer behavior (pp. 188–240). Englewoo Cliffs, NJ: Prentice-Hall.
  • Dabholkar, P. A., & Bagozzi, R. P. (2002). An attitudinal model of technology based self-service: Moderating effects of consumer traits and situational factors. Journal of the Academy of Marketing Science, 30, 184–202.
  • Davis, F. D. (1989). Perceived Usefulness, Perceived Ease of Use and User Acceptance of Information Technology. MIS Quarterly, 13, 319-340.
  • Davis, F.D. (1986). Technology acceptance model for emprically testing new end user information systems: Theory and results. Doctoral dissertation, MT.
  • Davis, F.D., R. Bagozzi & P. Warshaw. (1989). User Acceptance of Computer Technology: A Comparison of Two Theoretical Models. Management Science. 35. 8, 982-1003.
  • Dimitriadis, S., & Kyrezis, N. (2010). Linking trust to use intention for technology enabled bank channels: The role of trusting intentions. Psychology and Marketing, 27(8), 799–820.
  • Donovan, R. J. & Rossiter, J. R. (1982). Store atmosphere: an environmental psychology approach. Journal of Retailing, 58, 34-57.
  • Donovan, R. J., & Rossiter, J. R., Marcoolyn, G., & Nesdale, A. (1994). Store atmosphere and purchasing behavior. Journal of Retailing, 70, 283–295.
  • Donovan, R. J., & Rossiter, J. R., Marcoolyn, G., & Nesdale, A. (1994). Store atmosphere and purchasing behavior. Journal of Retailing, 70, 283–295.
  • Ferreira, J.B., Rocha, A. & Silva, J. F. (2014). Impacts of technology readiness on emotions and cognition in Brazil, Journal of Business Research 67, 865–873.
  • Fishbein, M., & Ajzen, I. (1975). Belief, Attitude, Intention and Behavior: An Introduction to Theory and Research. Reading, MA: Addison-Wesley Publishing.
  • Gentry, L., & Calantone, R. (2002). A comparison of three models to explain shop-bot use on the web. Psychology & Marketing, 19, 945–956.
  • Hair, J. F. Jr., Black, W. C., Babin, B. J., & Anderson, R. E. (2010). Multivariate data analysis. (7th ed.). Upper Saddle River, NJ: Prentice Hall.
  • Harris, R., & Davison, R. (1999). Anxiety and involvement: Cultural dimensions of attitudes toward computers in developing societies. Journal of Global Information Management, 7, 26–38.
  • Hartman, J. B., Shim, S. Barber, B., & O’Brien, M. (2006). Adolescents’ utilitarian and hedonic web-consumption behavior: Hierarchical influence of personal values and innovativeness. Psychology & Marketing, 23, 813–839.
  • Havlena,W. J., & Holbrook, M. B. (1986). The varieties of consumption experience: Comparing two typologies of emotion in consumer behavior. Journal of Consumer Research, 13, 394–404.
  • Holbrook, M. B., &Hirschman, E. C. (1982). The experiential aspects of consumption: Consumer fantasies, feelings, and fun. Journal of Consumer Research, 9, 132–140.
  • Holbrook, M.B., & Batra, R. (1987). Assessing the role of emotions as mediators of consumer responses to advertising. Journal of Consumer Research, 14, 404–421.
  • Hu, P., Chau, P., Sheng, O. L., ve Tam, K. Y. (1999). Examining the technolog acceptance model using physician acceptance of telemedicine technology. Journal of Management Information Systems, 16, 91–113.
  • Igbaria, M., & Parasuraman, S. (1989). A path analytic study of individual characteristics, computer anxiety and attitudes towards microcomputers. Journal of Management, 15(3), 373–388.
  • Ko, E., Kim, E. Y., & Lee, E. K. (2009). Modeling consumer adoption of mobile shopping for fashion products in Korea. Psychology and Marketing, 26, 669–687.
  • Koufaris, M. (2002). Applying the technology acceptance model and flow theory to online consumer behavior. Information Systems Research, 13, 19–28.
  • Kulviwat, S., Bruner, G. C., II, Kumar, A., Nasco, S. A., & Clark, T. (2007). Toward a unified theory of consumer acceptance of technology. Psychology and Marketing, 24(12), 1059–1084.
  • Lam, S. Y., Chiang, J., & Parasuraman, A. (2008). The effects of the dimensions of technology readiness on technology acceptance: An empirical analysis. Journal of Interactive Marketing, 22(4), 19–39.
  • Lee, M. B., Suh, K. S., & Whang, J. (2003). The impact of situation awareness information on consumer attitudes in the internet shopping mall. Electronic Commerce Research and Applications, 2, 254–265.
  • Lee, S., Ha, S., & Widdows, R. (2011). Consumer responses to high-technology products: Product attributes, cognition and emotions. Journal of Business Research, 64(11), 1195–1200.
  • Lee,W. J., Kim,T.U., & Chung, J.Y. (2003). User acceptance of the mobile internet. Working Paper.
  • Lin, C., Shih, H., & Sher, P. J. (2007). Integrating technology readiness into technology acceptance: The TRAM model. Psychology & Marketing, 24, 641–657.
  • Lindgren, M., J. Jedbratt & E. Svensson. (2002). Beyond Mobile People, Communication and Marketing in a Mobilized World. New York: Palgrave.
  • MacKenzie, S. B., Lutz, R. J., & Belch, G. E. (1986). The role of attitude toward the ad as a mediator of advertising effectiveness: A test of competing explanations. Journal of marketing research, 23(2), 130-143.
  • Mathieson, K. (1991). Predicting user intentions: Comparing the technology acceptance model with the theory of planned behavior. Information Systems Research, 2, 173–192.
  • Mehrabian, A., & Russell, J. A. (1974). An approach to environmental psychology. Cambridge, MA: MIT Press.
  • Mick, D.G., & Fournier, S. (1998). Paradoxes of technology: Consumer cognizance, emotions, and coping strategies. Journal of Consumer Research, 25, 123–143.
  • Nasco, S. A., Kulviwat, S., Kumar, A., ve Bruner Ii, G. C. (2008a). The CAT model: Extensions and moderators of dominance in technology acceptance. Psychology & marketing, 25(10), 987-1005.
  • Nasco, S., Grandón, E., & Mykytyn, P. (2008b). Predicting electronic commerce adoption in Chilean SMEs. Journal of Business Research, 61(6), 697–705.
  • O’Donnell, K. A., & Wardlow, D. L. (2000). A theory on the origins of coolness. Advances in Consumer Research, 27, 13–18.
  • Oh, S. H., Kim, Y. M., Lee, W. C., Shim, G. Y., Park, M. S., &Jung, H. S. (2009). Consumer adoption of virtual stores in Korea: Focusing on the role of trust and playfulness. Psychology and Marketing, 26, 652–668.
  • Özmen, Ş. (2013). Ağ Ekonomisinde Yeni Ticaret Yolu E-Ticaret (Genişletilmiş 5. Baskı). İstanbul: İstanbul Bilgi Üniversitesi Yayınları.
  • Parasuraman, A. (2000). Technology Readiness Index (TRI): A multiple-item scale to measure readiness to embrace new technologies. Journal of Service Research, 2, 307–320.
  • Parasuraman, A., & Colby, C. (2001). Techno-ready Marketing: How and Why Your Customers Adopt Technology. New York: The Free Press.
  • Rogers, E. M. (1983). Diffusion Of Innovation (3rd Edition). New York: The Free Pre
  • Shih, H. P. (2004). An empirical study on predicting user acceptance of e-shopping on the web. Information Management, 41(3), 351–369.
  • Solomon, M. (2003). Conquering consumerspace. New York: AMACOM.
  • Taylor, S. & P. A. Todd. (1995). Understanding Information Technology Usage: A test of Competing Models. Information System Research, 6: 2, 144-176.
  • Taylor, S. &P. A. Todd. (1995). Understanding Information Technology Usage: A test of Competing Models. Information System Research, 6: 2, 144-176.
  • Trevino, L. K., & Webster, J. (1992). Flow in computer-mediated communication: Electronic mail and voice mail evaluation and impacts. Communication research, 19(5), 539-573.
  • Turban, E., King, D. R., Liang, T.-P., & Turban, D. C. (2015). Electronic Commerce: a Managerial and Social Networks Perspective. Cham: Springer.
  • Venkatesh, V. (2000). Determinants of perceived ease-of-use: Integrating control, intrinsic motivation, and emotion into the technology acceptance model. Information Systems Research, 11, 342–365.
  • Venkatesh, V., & Davis, F. D. (2000). A theoretical extension of the technology acceptance model: Four longitudinal field studies. Management science, 46(2), 186-204.
  • Venkatesh, V., Morris, M. G., Davis, G. B. & Davis, F. D. (2003). User Acceptance of Information Technology: Toward A Unifed View. MIS Quarterly, 27(3), 425-478.
  • Venkatesh, V. (1999). Creation of favorable user perceptions: Exploring the role of intrinsic motivation. MIS Quarterly, 23, 239–260.
  • Wood, S. L., & Moreau, P. C. (2006). From fear to loathing? How emotion influence the evaluation and early use of innovations. Journal of Marketing, 70 44–57.
  • Yılmaz, V., & Çelik, E. H. (2009). Lisrel ile yapısal eşitlik modellemesi 1, temel kavramlar, uygulamalar, programlama. Ankara: Pegem Akademi.
  • Zarouali, B., Broeck, E., Walrave, M. & Poels, K. (2018). Predicting Consumer Responses to a Chatbot on Facebook, Cyberpsychology. Behavıor, And Socıal Networkıng, 21(8), 491-497.

Teknoloji Kabul Modeli ile Farklı Nesillere Göre Çevrimiçi Satın Alma Davranışının İncelenmesi

Year 2025, Issue: 38, 136 - 155, 20.01.2025
https://doi.org/10.54600/igdirsosbilder.1562479

Abstract

Bu çalışmanın temel amacı, X, Y ve Z kuşağı tüketicileri bağlamında internetten satın alma niyetini Tüketici Teknoloji Kabul Modeli çerçevesinde karşılaştırmalı olarak incelemektir. Bu çalışma nicel bir desende çalışılmış ve Mersin ilinde kolayda örnekleme yöntemi ile belirlenen 661 tüketici üzerinde yürütülmüştür. Elde edilen veriler ile normallik ve sapma analizleri, geçerlilik ve güvenilirlik analizleri ve faktör analizleri yapılmıştır. Belirlenen hipotezleri test etmek için yapısal eşitlik modellemesi kullanılmış ve tüm analizler SPSS 24.0 ve AMOS 23.0 paket programları kullanılarak gerçekleştirilmiştir. Çalışma kapsamında ele alınan X, Y ve Z kuşaklarında yer alan bireyler, ait oldukları kuşaklara bağlı olarak farklı özellikler gösterebilmektedir. Satın alma davranışına ilişkin alışkanlıkları ve algıları farklılaşabilen kuşakların teknolojik yenilikleri benimseme konusunda da farklılaşacağı öngörüsü araştırmadan elde edilen sonuçlara göre doğrulanmıştır. Bu çalışmanın temel kısıtlarından biri kolayda örnekleme yoluyla toplanmış olmasıdır. Diğeri ise çalışmada hedef kuşak yaş gruplarına ulaşılmasıdır. Bu araştırmanın yönetsel katkısı, internet satın alma araçlarının sadece kullanım kolaylığı ve kullanışlılığa dayalı olarak tasarlanmaması ve yeniliğin kabul düzeyini daha doğru değerlendirmek için pazar araştırması sırasında duygusal boyutların hedef pazar ve hedef tüketici grupları (X, Y ve Z kuşağı) ile birlikte değerlendirilmesi gerektiğidir. Literatür analizine göre, tüketici teknoloji kabul modelinin kuşaklar arasındaki ilişkisini inceleyen bir çalışmaya rastlanmamıştır. Bu araştırmanın amacı, tüketici teknolojisi kabul modeli ile kuşaklar arasındaki ilişkiyi inceleyerek literatüre katkıda bulunmak ve tüketici davranışlarında daha genel bir kavramsal temel sağlamaktır.

References

  • Ajzen, I. (1985). From Intentions to Actions: A Theory of Planned Behavior, J. Kuhl ve J. Beckmen (Eds.). Action Control from Cognition to Behavior içinde (11-39). Berlin: Springer-Verlag. 1. Baskı.
  • Bagozzi, R. P., Baumgartner, H., & Yi, Y. (1992). State versus action orientation and the theory of reasoned action: An application to coupon usage. Journal of consumer research, 18(4), 505-518.
  • Barutçu, S. (2010). Mobil Pazarlama. İ. Varinli ve K. Çatı (Ed.), Güncel Pazarlama Yaklaşımlarından Seçmeler içinde (259-285). 2. Baskı, Ankara: Detay Yayıncılık.
  • Basu, A. & S. Muylle. (2003). Online Support for Commerce Processes by Web Retailers, Decision Support Systems, 34(4), 379‐95.
  • Bruner II, G. C., & Kumar, A. (2005). Applying T.A.M. to consumer usage of handheld Internet devices. Journal of Business Research, 58, 553–558.
  • Chang, M. K., & Cheung, W. (2001). Determinants of the intention to use Internet/ WWW at work: A confirmatory study. Information & Management, 39, 1–14.
  • Childers, T. L., Carr, C. L., Peck, J., & Carson, S. (2001). Hedonic and utilitarian motivations for online retail shopping behavior. Journal of Retailing, 77, 511–536.
  • Cohen, J., & Areni, C. (1991). Affect and consumer behavior. In T. S. Robertson & H. H. Kassarjian (Eds.), Handbook of consumer behavior (pp. 188–240). Englewoo Cliffs, NJ: Prentice-Hall.
  • Dabholkar, P. A., & Bagozzi, R. P. (2002). An attitudinal model of technology based self-service: Moderating effects of consumer traits and situational factors. Journal of the Academy of Marketing Science, 30, 184–202.
  • Davis, F. D. (1989). Perceived Usefulness, Perceived Ease of Use and User Acceptance of Information Technology. MIS Quarterly, 13, 319-340.
  • Davis, F.D. (1986). Technology acceptance model for emprically testing new end user information systems: Theory and results. Doctoral dissertation, MT.
  • Davis, F.D., R. Bagozzi & P. Warshaw. (1989). User Acceptance of Computer Technology: A Comparison of Two Theoretical Models. Management Science. 35. 8, 982-1003.
  • Dimitriadis, S., & Kyrezis, N. (2010). Linking trust to use intention for technology enabled bank channels: The role of trusting intentions. Psychology and Marketing, 27(8), 799–820.
  • Donovan, R. J. & Rossiter, J. R. (1982). Store atmosphere: an environmental psychology approach. Journal of Retailing, 58, 34-57.
  • Donovan, R. J., & Rossiter, J. R., Marcoolyn, G., & Nesdale, A. (1994). Store atmosphere and purchasing behavior. Journal of Retailing, 70, 283–295.
  • Donovan, R. J., & Rossiter, J. R., Marcoolyn, G., & Nesdale, A. (1994). Store atmosphere and purchasing behavior. Journal of Retailing, 70, 283–295.
  • Ferreira, J.B., Rocha, A. & Silva, J. F. (2014). Impacts of technology readiness on emotions and cognition in Brazil, Journal of Business Research 67, 865–873.
  • Fishbein, M., & Ajzen, I. (1975). Belief, Attitude, Intention and Behavior: An Introduction to Theory and Research. Reading, MA: Addison-Wesley Publishing.
  • Gentry, L., & Calantone, R. (2002). A comparison of three models to explain shop-bot use on the web. Psychology & Marketing, 19, 945–956.
  • Hair, J. F. Jr., Black, W. C., Babin, B. J., & Anderson, R. E. (2010). Multivariate data analysis. (7th ed.). Upper Saddle River, NJ: Prentice Hall.
  • Harris, R., & Davison, R. (1999). Anxiety and involvement: Cultural dimensions of attitudes toward computers in developing societies. Journal of Global Information Management, 7, 26–38.
  • Hartman, J. B., Shim, S. Barber, B., & O’Brien, M. (2006). Adolescents’ utilitarian and hedonic web-consumption behavior: Hierarchical influence of personal values and innovativeness. Psychology & Marketing, 23, 813–839.
  • Havlena,W. J., & Holbrook, M. B. (1986). The varieties of consumption experience: Comparing two typologies of emotion in consumer behavior. Journal of Consumer Research, 13, 394–404.
  • Holbrook, M. B., &Hirschman, E. C. (1982). The experiential aspects of consumption: Consumer fantasies, feelings, and fun. Journal of Consumer Research, 9, 132–140.
  • Holbrook, M.B., & Batra, R. (1987). Assessing the role of emotions as mediators of consumer responses to advertising. Journal of Consumer Research, 14, 404–421.
  • Hu, P., Chau, P., Sheng, O. L., ve Tam, K. Y. (1999). Examining the technolog acceptance model using physician acceptance of telemedicine technology. Journal of Management Information Systems, 16, 91–113.
  • Igbaria, M., & Parasuraman, S. (1989). A path analytic study of individual characteristics, computer anxiety and attitudes towards microcomputers. Journal of Management, 15(3), 373–388.
  • Ko, E., Kim, E. Y., & Lee, E. K. (2009). Modeling consumer adoption of mobile shopping for fashion products in Korea. Psychology and Marketing, 26, 669–687.
  • Koufaris, M. (2002). Applying the technology acceptance model and flow theory to online consumer behavior. Information Systems Research, 13, 19–28.
  • Kulviwat, S., Bruner, G. C., II, Kumar, A., Nasco, S. A., & Clark, T. (2007). Toward a unified theory of consumer acceptance of technology. Psychology and Marketing, 24(12), 1059–1084.
  • Lam, S. Y., Chiang, J., & Parasuraman, A. (2008). The effects of the dimensions of technology readiness on technology acceptance: An empirical analysis. Journal of Interactive Marketing, 22(4), 19–39.
  • Lee, M. B., Suh, K. S., & Whang, J. (2003). The impact of situation awareness information on consumer attitudes in the internet shopping mall. Electronic Commerce Research and Applications, 2, 254–265.
  • Lee, S., Ha, S., & Widdows, R. (2011). Consumer responses to high-technology products: Product attributes, cognition and emotions. Journal of Business Research, 64(11), 1195–1200.
  • Lee,W. J., Kim,T.U., & Chung, J.Y. (2003). User acceptance of the mobile internet. Working Paper.
  • Lin, C., Shih, H., & Sher, P. J. (2007). Integrating technology readiness into technology acceptance: The TRAM model. Psychology & Marketing, 24, 641–657.
  • Lindgren, M., J. Jedbratt & E. Svensson. (2002). Beyond Mobile People, Communication and Marketing in a Mobilized World. New York: Palgrave.
  • MacKenzie, S. B., Lutz, R. J., & Belch, G. E. (1986). The role of attitude toward the ad as a mediator of advertising effectiveness: A test of competing explanations. Journal of marketing research, 23(2), 130-143.
  • Mathieson, K. (1991). Predicting user intentions: Comparing the technology acceptance model with the theory of planned behavior. Information Systems Research, 2, 173–192.
  • Mehrabian, A., & Russell, J. A. (1974). An approach to environmental psychology. Cambridge, MA: MIT Press.
  • Mick, D.G., & Fournier, S. (1998). Paradoxes of technology: Consumer cognizance, emotions, and coping strategies. Journal of Consumer Research, 25, 123–143.
  • Nasco, S. A., Kulviwat, S., Kumar, A., ve Bruner Ii, G. C. (2008a). The CAT model: Extensions and moderators of dominance in technology acceptance. Psychology & marketing, 25(10), 987-1005.
  • Nasco, S., Grandón, E., & Mykytyn, P. (2008b). Predicting electronic commerce adoption in Chilean SMEs. Journal of Business Research, 61(6), 697–705.
  • O’Donnell, K. A., & Wardlow, D. L. (2000). A theory on the origins of coolness. Advances in Consumer Research, 27, 13–18.
  • Oh, S. H., Kim, Y. M., Lee, W. C., Shim, G. Y., Park, M. S., &Jung, H. S. (2009). Consumer adoption of virtual stores in Korea: Focusing on the role of trust and playfulness. Psychology and Marketing, 26, 652–668.
  • Özmen, Ş. (2013). Ağ Ekonomisinde Yeni Ticaret Yolu E-Ticaret (Genişletilmiş 5. Baskı). İstanbul: İstanbul Bilgi Üniversitesi Yayınları.
  • Parasuraman, A. (2000). Technology Readiness Index (TRI): A multiple-item scale to measure readiness to embrace new technologies. Journal of Service Research, 2, 307–320.
  • Parasuraman, A., & Colby, C. (2001). Techno-ready Marketing: How and Why Your Customers Adopt Technology. New York: The Free Press.
  • Rogers, E. M. (1983). Diffusion Of Innovation (3rd Edition). New York: The Free Pre
  • Shih, H. P. (2004). An empirical study on predicting user acceptance of e-shopping on the web. Information Management, 41(3), 351–369.
  • Solomon, M. (2003). Conquering consumerspace. New York: AMACOM.
  • Taylor, S. & P. A. Todd. (1995). Understanding Information Technology Usage: A test of Competing Models. Information System Research, 6: 2, 144-176.
  • Taylor, S. &P. A. Todd. (1995). Understanding Information Technology Usage: A test of Competing Models. Information System Research, 6: 2, 144-176.
  • Trevino, L. K., & Webster, J. (1992). Flow in computer-mediated communication: Electronic mail and voice mail evaluation and impacts. Communication research, 19(5), 539-573.
  • Turban, E., King, D. R., Liang, T.-P., & Turban, D. C. (2015). Electronic Commerce: a Managerial and Social Networks Perspective. Cham: Springer.
  • Venkatesh, V. (2000). Determinants of perceived ease-of-use: Integrating control, intrinsic motivation, and emotion into the technology acceptance model. Information Systems Research, 11, 342–365.
  • Venkatesh, V., & Davis, F. D. (2000). A theoretical extension of the technology acceptance model: Four longitudinal field studies. Management science, 46(2), 186-204.
  • Venkatesh, V., Morris, M. G., Davis, G. B. & Davis, F. D. (2003). User Acceptance of Information Technology: Toward A Unifed View. MIS Quarterly, 27(3), 425-478.
  • Venkatesh, V. (1999). Creation of favorable user perceptions: Exploring the role of intrinsic motivation. MIS Quarterly, 23, 239–260.
  • Wood, S. L., & Moreau, P. C. (2006). From fear to loathing? How emotion influence the evaluation and early use of innovations. Journal of Marketing, 70 44–57.
  • Yılmaz, V., & Çelik, E. H. (2009). Lisrel ile yapısal eşitlik modellemesi 1, temel kavramlar, uygulamalar, programlama. Ankara: Pegem Akademi.
  • Zarouali, B., Broeck, E., Walrave, M. & Poels, K. (2018). Predicting Consumer Responses to a Chatbot on Facebook, Cyberpsychology. Behavıor, And Socıal Networkıng, 21(8), 491-497.
There are 61 citations in total.

Details

Primary Language English
Subjects Innovation Management
Journal Section Research Article
Authors

Resul Çelik 0000-0001-7605-5698

Sevilay Uslu Divanoğlu 0000-0001-8210-2622

Publication Date January 20, 2025
Submission Date October 6, 2024
Acceptance Date November 11, 2024
Published in Issue Year 2025 Issue: 38

Cite

APA Çelik, R., & Uslu Divanoğlu, S. (2025). Investigation of Online Purchasing Behavior According to Different Generations with Technology Acceptance Model. Iğdır Üniversitesi Sosyal Bilimler Dergisi(38), 136-155. https://doi.org/10.54600/igdirsosbilder.1562479