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Revisiting the Technology Acceptance Model in the Age of Artificial Intelligence: A Bibliometric Analysis of TAM in Business and Marketing Literature

Yıl 2025, Cilt: 10 Sayı: 2, 497 - 517, 12.12.2025
https://doi.org/10.54452/jrb.1615746

Öz

This study presents a comprehensive bibliometric analysis of research on the Technology Acceptance Model (TAM) in the marketing and business literature. Publications between 2000 and 2024 were selected from the Scopus database, and keyword concurrency and cluster analysis were performed using VOSviewer. The study is analyzed in three periods (2000-2008, 2009-2017, 2018-2024) to examine the evolution of TAM over time. The results show that in the first period, basic e-commerce and consumer behavior issues were at the forefront, while trust and risk perception gained importance in the second period. The last period emphasizes the increasing role of TAM in innovative areas such as artificial intelligence, cloud computing and financial technology. This study reveals how TAM adapts to current technological developments in the marketing and business context and provides direction for future research.

Kaynakça

  • Aboelmaged, M. G., & Gebba, T. R. (2013). Mobile banking adoption: an examination of technology acceptance model and theory of planned behavior. International journal of business research and development, 2(1), 35-50.
  • Agag, G., & El-Masry, A. A. (2016). Understanding consumer intention to participate in online travel community and effects on consumer intention to purchase travel online and WOM: An integration of innovation diffusion theory and TAM with trust. Computers in human behavior, 60, 97-111. http:// dx.doi.org/10.1016/j.chb.2016.02.038
  • Agarwal, A., Durairajanayagam, D.(2016), Tatagari, S., Esteves, S.C., Harlev, A., Henkel, R., Roychoudhury, S., Homa, S., Puchalt, N.G., Ramasamy, R.: Bibliometrics: tracking research impact by selecting the appropriate metrics. Asian J. Androl. 18(2), 296.
  • Ajzen, I. (1985). From intentions to actions: A theory of planned behavior. In Action control: From cognition to behavior (pp. 11-39). Berlin, Heidelberg: Springer Berlin Heidelberg.
  • Bagozzi, R. P., & Warshaw, P. R. (1990). Trying to consume. Journal of consumer research, 17(2), 127-140. https:// doi.org/10.1086/208543
  • Beale, D. A., & Manstead, A. S. (1991). Predicting Mothers’ Intentions to Limit Frequency of Infants’ Sugar Intake: Testing the Theory of Planned Behavior 1. Journal of Applied Social Psychology, 21(5), 409-431. https://doi.org/10.1111/j.1559-1816.1991.tb00528.x
  • Boldero, J., Moore, S., & Rosenthal, D. (1992). Intention, context, and safe sex: Australian adolescents’ responses to AIDS. Journal of Applied Social Psychology, 22(17), 1374-1396. https://doi.org/10.1111/j.1559-1816.1992. tb00955.x
  • Chen, K., Chen, J. V., & Yen, D. C. (2011). Dimensions of self-efficacy in the study of smart phone acceptance. Computer Standards & Interfaces, 33(4), 422-431. https://doi.org/10.1016/J.CSI.2011.01.003
  • Choe, J. Y., Kim, J. J., & Hwang, J. (2021). Innovative marketing strategies for the successful construction of drone food delivery services: Merging TAM with TPB. Journal of Travel & Tourism Marketing, 38(1), 16- 30. https://doi.org/10.1080/10548.408.2020.1862023
  • Copeland, L. R., Bhaduri, G., & Huang, O. (2023). Understanding Chinese Gen Z and their online shopping intentions through TAM. Asia Pacific Journal of Marketing and Logistics, 35(10), 2361-2376. https://doi. org/10.1108/APJML-03-2022-0241
  • Davis, F. D. (1989). Technology acceptance model: TAM. Al-Suqri, MN, Al-Aufi, AS: Information Seeking Behavior and Technology Adoption, 205, 219.
  • Donthu, N., Kumar, S., Mukherjee, D., Pandey, N., & Lim, W. M. (2021). How to conduct a bibliometric analysis: An overview and guidelines. Journal of business research, 133, 285-296.
  • Elsevier: SCOPUS Content Coverage Guide (2023). https:// www.elsevier. com/__ data/ assets/ pdf_ file/ 0007/ 69451/ Scopus_ ContentCov erage_ Guide_ WEB. Pdf
  • Elshafey, A., Saar, C. C., Aminudin, E. B., Gheisari, M., & Usmani, A. (2020). Technology acceptance model for Augmented Reality and Building Information Modeling integration in the construction industry. Journal of information technology in construction, 25. https://doi.org/10.36680/j.itcon.2020.010
  • Featherman, M. S., & Pavlou, P. A. (2003). Predicting e-services adoption: a perceived risk facets perspective. International journal of human-computer studies, 59(4), 451-474. https://doi.org/10.1016/ S1071-5819(03)00111-3
  • Fishbein, M., & Ajzen, I. (1977). Belief, attitude, intention, and behavior: An introduction to theory and research.
  • Gefen, D., Karahanna, E., & Straub, D. W. (2003). Trust and TAM in online shopping: An integrated model. MIS quarterly, 51-90. https://doi.org/10.2307/30036519
  • Ha, N. (2020). The impact of perceived risk on consumers’ online shopping intention: An integration of TAM and TPB. Management science letters, 10(9), 2029-2036. https://doi.org/10.5267/j.msl.2020.2.009
  • Hootsuite Global Digital Report, (2020). https://datareportal.com/reports/digital-2020-july-global-statshot
  • Hubert, M., Blut, M., Brock, C., Zhang, R. W., Koch, V., & Riedl, R. (2019). The influence of acceptance and adoption drivers on smart home usage. European journal of marketing, 53(6), 1073-1098.
  • Kim, K. J., & Shin, D. H. (2015). An acceptance model for smart watches: Implications for the adoption of future wearable technology. Internet Research, 25(4), 527-541. https://doi.org/10.1108/IntR-05-2014-0126
  • Na, S., Heo, S., Han, S., Shin, Y., & Roh, Y. (2022). Acceptance model of artificial intelligence (AI)-based technologies in construction firms: Applying the Technology Acceptance Model (TAM) in combination with the Technology–Organisation–Environment (TOE) framework. Buildings, 12(2), 90. https://doi. org/10.3390/buildings12020090
  • Nasir, S., & Yurder, Y. (2015). Consumers’ and physicians’ perceptions about high tech wearable health products. Procedia-Social and Behavioral Sciences, 195, 1261-1267. https://doi.org/10.1016/j. sbspro.2015.06.279
  • Ooi, K. B., & Tan, G. W. H. (2016). Mobile technology acceptance model: An investigation using mobile users to explore smartphone credit card. Expert Systems with Applications, 59, 33-46. https://doi.org/10.1016/j. eswa.2016.04.015
  • Page, M. J., McKenzie, J. E., Bossuyt, P. M., Boutron, I., Hoffmann, T. C., Mulrow, C. D., ... & Moher, D. (2021). The PRISMA 2020 statement: An updated guideline for reporting systematic reviews. BMJ, 372, n71. https://doi.org/10.1136/bmj.n71
  • Park, E., Cho, Y., Han, J., & Kwon, S. J. (2017). Comprehensive approaches to user acceptance of Internet of Things in a smart home environment. IEEE Internet of Things Journal, 4(6), 2342-2350. https://doi. org/10.1109/JIOT.2017.275.0765
  • Purwanto, E., & Budiman, V. (2020). Applying the technology acceptance model to investigate the intention to use e-health: a conceptual framework. Technology Reports of Kansai University, 62(05), 2569-2580.
  • Sweileh, W.M.(2018). Research trends on human trafficking: a bibliometric analysis using Scopus database. Glob. Health 14(1), 1–12. https://doi.org/10.1186/s12992.018.0427-9
  • Van Eck, N.J., Waltman, L.: Software survey: VOSviewer, a computer program for bibliometric mapping. Scientometrics 84(2), 523–538 (2010)
  • Venkatesh, V., Morris, M. G., Davis, G. B., & Davis, F. D. (2003). User acceptance of information technology: Toward a unified view. MIS Quarterly, 27(3), 425–478. https://doi.org/10.2307/30036540
  • Wong, W. P. M., Lo, M. C., & Ramayah, T. (2014). The effects of technology acceptance factors on customer e-loyalty and e-satisfaction in Malaysia. International Journal of Business and Society, 15(3), 477.
  • Xia, M., Zhang, Y., & Zhang, C. (2018). A TAM-based approach to explore the effect of online experience on destination image: A smartphone user’s perspective. Journal of destination marketing & management, 8, 259-270. https://doi.org/10.1016/j.jdmm.2017.05.002
  • Yas, H., Jusoh, A., Abbas, A.F., Mardani, A., Nor, K.M.(2020).A review and bibliometric analysis of service quality and customer satisfaction by using Scopus database. Int. J. Manag. (IJM) 11(8), 459–470. https:// doi.org/10.34218/IJM.11.8.2020.044
  • Yu, Y., Li, Y., Zhang, Z., Gu, Z., Zhong, H., Zha, Q., Yang, L., Zhu, C., Chen, E. (2020). A bibliometric analysis using VOSviewer of

Yapay Zeka Çağında Teknoloji Kabul Modelinin Yeniden Gözden Geçirilmesi: İşletme ve Pazarlama Literatüründe TAM'ın Bibliyometrik Analizi

Yıl 2025, Cilt: 10 Sayı: 2, 497 - 517, 12.12.2025
https://doi.org/10.54452/jrb.1615746

Öz

Bu çalışma, pazarlama ve işletme literatüründe Teknoloji Kabul Modeli (TAM) üzerine yapılan araştırmaların kapsamlı bir bibliyometrik analizini sunmaktadır. Scopus veri tabanından 2000-2024 yılları arasındaki yayınlar seçilmiş ve VOSviewer kullanılarak anahtar kelime eşzamanlılığı ve küme analizi yapılmıştır. Çalışma, TAM'ın zaman içindeki evrimini incelemek için üç dönemde (2000-2008, 2009-2017, 2018-2024) analiz edilmiştir. Sonuçlar, ilk dönemde temel e-ticaret ve tüketici davranışı konularının ön planda olduğunu, ikinci dönemde ise güven ve risk algısının önem kazandığını göstermektedir. Son dönem ise yapay zekâ, bulut bilişim ve finansal teknoloji gibi yenilikçi alanlarda TAM'ın artan rolüne vurgu yapıyor. Bu çalışma, TAM'ın pazarlama ve iş bağlamında güncel teknolojik gelişmelere nasıl uyum sağladığını ortaya koymakta ve gelecekteki araştırmalar için yön göstermektedir.

Kaynakça

  • Aboelmaged, M. G., & Gebba, T. R. (2013). Mobile banking adoption: an examination of technology acceptance model and theory of planned behavior. International journal of business research and development, 2(1), 35-50.
  • Agag, G., & El-Masry, A. A. (2016). Understanding consumer intention to participate in online travel community and effects on consumer intention to purchase travel online and WOM: An integration of innovation diffusion theory and TAM with trust. Computers in human behavior, 60, 97-111. http:// dx.doi.org/10.1016/j.chb.2016.02.038
  • Agarwal, A., Durairajanayagam, D.(2016), Tatagari, S., Esteves, S.C., Harlev, A., Henkel, R., Roychoudhury, S., Homa, S., Puchalt, N.G., Ramasamy, R.: Bibliometrics: tracking research impact by selecting the appropriate metrics. Asian J. Androl. 18(2), 296.
  • Ajzen, I. (1985). From intentions to actions: A theory of planned behavior. In Action control: From cognition to behavior (pp. 11-39). Berlin, Heidelberg: Springer Berlin Heidelberg.
  • Bagozzi, R. P., & Warshaw, P. R. (1990). Trying to consume. Journal of consumer research, 17(2), 127-140. https:// doi.org/10.1086/208543
  • Beale, D. A., & Manstead, A. S. (1991). Predicting Mothers’ Intentions to Limit Frequency of Infants’ Sugar Intake: Testing the Theory of Planned Behavior 1. Journal of Applied Social Psychology, 21(5), 409-431. https://doi.org/10.1111/j.1559-1816.1991.tb00528.x
  • Boldero, J., Moore, S., & Rosenthal, D. (1992). Intention, context, and safe sex: Australian adolescents’ responses to AIDS. Journal of Applied Social Psychology, 22(17), 1374-1396. https://doi.org/10.1111/j.1559-1816.1992. tb00955.x
  • Chen, K., Chen, J. V., & Yen, D. C. (2011). Dimensions of self-efficacy in the study of smart phone acceptance. Computer Standards & Interfaces, 33(4), 422-431. https://doi.org/10.1016/J.CSI.2011.01.003
  • Choe, J. Y., Kim, J. J., & Hwang, J. (2021). Innovative marketing strategies for the successful construction of drone food delivery services: Merging TAM with TPB. Journal of Travel & Tourism Marketing, 38(1), 16- 30. https://doi.org/10.1080/10548.408.2020.1862023
  • Copeland, L. R., Bhaduri, G., & Huang, O. (2023). Understanding Chinese Gen Z and their online shopping intentions through TAM. Asia Pacific Journal of Marketing and Logistics, 35(10), 2361-2376. https://doi. org/10.1108/APJML-03-2022-0241
  • Davis, F. D. (1989). Technology acceptance model: TAM. Al-Suqri, MN, Al-Aufi, AS: Information Seeking Behavior and Technology Adoption, 205, 219.
  • Donthu, N., Kumar, S., Mukherjee, D., Pandey, N., & Lim, W. M. (2021). How to conduct a bibliometric analysis: An overview and guidelines. Journal of business research, 133, 285-296.
  • Elsevier: SCOPUS Content Coverage Guide (2023). https:// www.elsevier. com/__ data/ assets/ pdf_ file/ 0007/ 69451/ Scopus_ ContentCov erage_ Guide_ WEB. Pdf
  • Elshafey, A., Saar, C. C., Aminudin, E. B., Gheisari, M., & Usmani, A. (2020). Technology acceptance model for Augmented Reality and Building Information Modeling integration in the construction industry. Journal of information technology in construction, 25. https://doi.org/10.36680/j.itcon.2020.010
  • Featherman, M. S., & Pavlou, P. A. (2003). Predicting e-services adoption: a perceived risk facets perspective. International journal of human-computer studies, 59(4), 451-474. https://doi.org/10.1016/ S1071-5819(03)00111-3
  • Fishbein, M., & Ajzen, I. (1977). Belief, attitude, intention, and behavior: An introduction to theory and research.
  • Gefen, D., Karahanna, E., & Straub, D. W. (2003). Trust and TAM in online shopping: An integrated model. MIS quarterly, 51-90. https://doi.org/10.2307/30036519
  • Ha, N. (2020). The impact of perceived risk on consumers’ online shopping intention: An integration of TAM and TPB. Management science letters, 10(9), 2029-2036. https://doi.org/10.5267/j.msl.2020.2.009
  • Hootsuite Global Digital Report, (2020). https://datareportal.com/reports/digital-2020-july-global-statshot
  • Hubert, M., Blut, M., Brock, C., Zhang, R. W., Koch, V., & Riedl, R. (2019). The influence of acceptance and adoption drivers on smart home usage. European journal of marketing, 53(6), 1073-1098.
  • Kim, K. J., & Shin, D. H. (2015). An acceptance model for smart watches: Implications for the adoption of future wearable technology. Internet Research, 25(4), 527-541. https://doi.org/10.1108/IntR-05-2014-0126
  • Na, S., Heo, S., Han, S., Shin, Y., & Roh, Y. (2022). Acceptance model of artificial intelligence (AI)-based technologies in construction firms: Applying the Technology Acceptance Model (TAM) in combination with the Technology–Organisation–Environment (TOE) framework. Buildings, 12(2), 90. https://doi. org/10.3390/buildings12020090
  • Nasir, S., & Yurder, Y. (2015). Consumers’ and physicians’ perceptions about high tech wearable health products. Procedia-Social and Behavioral Sciences, 195, 1261-1267. https://doi.org/10.1016/j. sbspro.2015.06.279
  • Ooi, K. B., & Tan, G. W. H. (2016). Mobile technology acceptance model: An investigation using mobile users to explore smartphone credit card. Expert Systems with Applications, 59, 33-46. https://doi.org/10.1016/j. eswa.2016.04.015
  • Page, M. J., McKenzie, J. E., Bossuyt, P. M., Boutron, I., Hoffmann, T. C., Mulrow, C. D., ... & Moher, D. (2021). The PRISMA 2020 statement: An updated guideline for reporting systematic reviews. BMJ, 372, n71. https://doi.org/10.1136/bmj.n71
  • Park, E., Cho, Y., Han, J., & Kwon, S. J. (2017). Comprehensive approaches to user acceptance of Internet of Things in a smart home environment. IEEE Internet of Things Journal, 4(6), 2342-2350. https://doi. org/10.1109/JIOT.2017.275.0765
  • Purwanto, E., & Budiman, V. (2020). Applying the technology acceptance model to investigate the intention to use e-health: a conceptual framework. Technology Reports of Kansai University, 62(05), 2569-2580.
  • Sweileh, W.M.(2018). Research trends on human trafficking: a bibliometric analysis using Scopus database. Glob. Health 14(1), 1–12. https://doi.org/10.1186/s12992.018.0427-9
  • Van Eck, N.J., Waltman, L.: Software survey: VOSviewer, a computer program for bibliometric mapping. Scientometrics 84(2), 523–538 (2010)
  • Venkatesh, V., Morris, M. G., Davis, G. B., & Davis, F. D. (2003). User acceptance of information technology: Toward a unified view. MIS Quarterly, 27(3), 425–478. https://doi.org/10.2307/30036540
  • Wong, W. P. M., Lo, M. C., & Ramayah, T. (2014). The effects of technology acceptance factors on customer e-loyalty and e-satisfaction in Malaysia. International Journal of Business and Society, 15(3), 477.
  • Xia, M., Zhang, Y., & Zhang, C. (2018). A TAM-based approach to explore the effect of online experience on destination image: A smartphone user’s perspective. Journal of destination marketing & management, 8, 259-270. https://doi.org/10.1016/j.jdmm.2017.05.002
  • Yas, H., Jusoh, A., Abbas, A.F., Mardani, A., Nor, K.M.(2020).A review and bibliometric analysis of service quality and customer satisfaction by using Scopus database. Int. J. Manag. (IJM) 11(8), 459–470. https:// doi.org/10.34218/IJM.11.8.2020.044
  • Yu, Y., Li, Y., Zhang, Z., Gu, Z., Zhong, H., Zha, Q., Yang, L., Zhu, C., Chen, E. (2020). A bibliometric analysis using VOSviewer of
Toplam 34 adet kaynakça vardır.

Ayrıntılar

Birincil Dil İngilizce
Konular İşletme
Bölüm Araştırma Makalesi
Yazarlar

Yiğit Yurder 0000-0002-3064-374X

Yayımlanma Tarihi 12 Aralık 2025
Gönderilme Tarihi 8 Ocak 2025
Kabul Tarihi 14 Kasım 2025
Yayımlandığı Sayı Yıl 2025 Cilt: 10 Sayı: 2

Kaynak Göster

APA Yurder, Y. (2025). Revisiting the Technology Acceptance Model in the Age of Artificial Intelligence: A Bibliometric Analysis of TAM in Business and Marketing Literature. Journal of Research in Business, 10(2), 497-517. https://doi.org/10.54452/jrb.1615746