Marketing research trends using technology acceptance model (TAM): a comprehensive review of researches (2002–2022)

References

• Adomavicius, G., Curley, S. P., Gupta, A., & Sanyal, P. (2013). User acceptance of complex electronic market mechanisms: Role of information feedback. Journal of Operations Management, 31(6), 1–17. https://doi.org/10.1016/j.jom.2013.07.015
   Web of Science ®Google Scholar
• Ahn, T., Ryu, S., & Han, I. (2004). The impact of the online and offline features on the user acceptance of Internet shopping malls. Electronic Commerce Research and Applications, 3(4), 405–420. https://doi.org/10.1016/j.elerap.2004.05.001
   Google Scholar
• Akbari, M., Khodayari, M., Danesh, M., Davari, A., & Padash, H. (2020). A bibliometric study of sustainable technology research. Cogent Business & Management, 7(1), 1751906. https://doi.org/10.1080/23311975.2020.1751906
   Web of Science ®Google Scholar
• Akbari, M., Rezvani, A., Shahriari, E., Zúñiga, M. A., & Pouladian, H. (2020). Acceptance of 5 G technology: The mediation role of trust and concentration. Journal of Engineering and Technology Management, 57, 101585. https://doi.org/10.1016/j.jengtecman.2020.101585
   Web of Science ®Google Scholar
• Al-Adwan, A. S. (2020). Investigating the drivers and barriers to MOOCs adoption: The perspective of TAM. Education and Information Technologies, 25(6), 5771–5795. https://doi.org/10.1007/s10639-020-10250-z
   Web of Science ®Google Scholar
• Al-Ansi, A. (2022). Investigating characteristics of learning environments during the COVID-19 pandemic: A systematic review. Canadian Journal of Learning and Technology, 48(1), 51. https://doi.org/10.21432/cjlt28051
   Google Scholar
• Al-Ansi, A. M., & Al-Ansi, A. (2023). An Overview of Artificial Intelligence (AI) in 6G: Types, Advantages, challenges, and recent applications. Buletin Ilmiah Sarjana Teknik Elektro, 5(1), 67–75.
   Google Scholar
• Al-Ansi, A. M., & Fatmawati, I. (2023). Integration of ICT in higher education during Covid-19 pandemic: A case study. International Journal of Learning and Change, 15(4), 430–442. https://doi.org/10.1504/IJLC.2023.132132
   Google Scholar
• Al-Ansi, A. M., Hazaimeh, M., Hendi, A., Al-Hrinat, J., & Adwan, G. (2023). How do social media influencers change adolescents’ behavior? Evidence from Middle Eastern countries. Heliyon, 9(5), e15983. https://doi.org/10.1016/j.heliyon.2023.e15983
   PubMed Web of Science ®Google Scholar
• Al-Ansi, A. M., Jaboob, M., Garad, A., & Al-Ansi, A. (2023). Analyzing augmented reality (AR) and virtual reality (VR) recent developments in education. Social Sciences & Humanities Open, 8(1), 100532. https://doi.org/10.1016/j.ssaho.2023.100532
   Google Scholar
• Al-Ansi, A. M., Suprayogo, I., & Abidin, M. (2019). Impact of information and communication technology (ICT) on different settings of the learning process in developing countries. Science and Technology, 9(2), 19–28.
   Google Scholar
• Alhassan, A., Li, L., Reddy, K., & Duppati, G. (2020). Consumer acceptance and continuance of mobile money: Secondary data insights from Africa using the technology acceptance model. Australasian Journal of Information Systems, 24, 2579. https://doi.org/10.3127/ajis.v24i0.2579
   Web of Science ®Google Scholar
• Alkhowaiter, W. A. (2023). The role of the Internet of Things content in branding: A framework designed from the technology perspective. Journal of the Knowledge Economy, 1–37. https://doi.org/10.1007/s13132-023-01383-w
   Web of Science ®Google Scholar
• Alqayed, Y., Foroudi, P., Kooli, K., Foroudi, M., & Ferri, M. A. (2021). Exploring value co-creation concept: A bibliometric analysis of 20 years of research and theory. Sustainable Branding: Ethical, Social, and Environmental Cases and Perspectives, Routledge, 2021, 291–309.
   Google Scholar
• Amaro, S., Andreu, L., & Huang, S. (2017). Generation Y travelers’ intentions to book Airbnb accommodation: An abstract. https://doi.org/10.1007/978-3-319-47331-4_10Retrieved from www.scopus.com.
   Google Scholar
• Arango-Botero, D., Valencia-Arias, A., Bermúdez-Hernández, J., & Duque-Cano, L. (2021). Factors that promote social media marketing in retail companies [Factores que promueven el mercadeo de redes sociales en las empresas del comercio minorista]. Contaduria y Administracion, 66(1), 475. https://doi.org/10.22201/fca.24488410e.2021.2475
   Google Scholar
• Bandara, U. C., & Amarasena, T. S. M. (2019). Impact of relative advantage perceived behavioral control and perceived ease of use on intention to adopt solar energy technology in Sri Lanka. In Paper presented at the Proceedings of the Conference on the Industrial and Commercial Use of Energy, ICUE, 2018-October Retrieved from www.scopus.com https://doi.org/10.23919/ICUE-GESD.2018.8635706
   Google Scholar
• Barakat, S., & El Sheikh, A. (2010). Trust and user acceptance of mobile advertising. Paper presented at the Proceedings of the European, Mediterranean, and Middle Eastern Conference on Information Systems: Global Information Systems Challenges in Management, EMCIS 2010, Retrieved from www.scopus.com.
   Google Scholar
• Bhardwaj, D., & Bharadwaj, S. S. (2017). Understanding the impact of social media on marketing strategies of organizations in India. Paper presented at the SIGMIS-CPR 2017 – Proceedings of the 2017 ACM SIGMIS Conference on Computers and People Research, 105–108. Retrieved from www.scopus.com https://doi.org/10.1145/3084381.3084394
   Google Scholar
• Bujanov, S., & Maier-Speredelozzi, V. (2021). (2021). Technology acceptance for partially automated vehicles in the United States and Germany. Paper presented at the IISE Annual Conference and Expo 1112–1117. Retrieved from www.scopus.com.
   Google Scholar
• Cao, L. (2021). Artificial intelligence in retail: Applications and value creation logics. International Journal of Retail & Distribution Management, 49(7), 958–976. https://doi.org/10.1108/IJRDM-09-2020-0350
   Web of Science ®Google Scholar
• Chen, W., Geng, Y., Zhong, S., Zhuang, M., & Pan, H. (2020). A bibliometric analysis of ecosystem services evaluation from 1997 to 2016. Environmental Science and Pollution Research International, 27(19), 23503–23513. https://doi.org/10.1007/s11356-020-08760-x
   PubMed Web of Science ®Google Scholar
• Chen, Y., Hsu, T., & Lu, Y. (2018). Impact of flow on mobile shopping intention. Journal of Retailing and Consumer Services, 41, 281–287. https://doi.org/10.1016/j.jretconser.2017.04.004
   Web of Science ®Google Scholar
• Cheng, T. C. E., Lam, D. Y. C., & Yeung, A. C. L. (2006). Adoption of internet banking: An empirical study in Hong Kong. Decision Support Systems, 42(3), 1558–1572. https://doi.org/10.1016/j.dss.2006.01.002
   Web of Science ®Google Scholar
• Davis, E. L. (1986). Marta: A stimulant to Atlanta development? Transportation Planning and Technology, 10(4), 241–256. https://doi.org/10.1080/03081068608717319
   Google Scholar
• Dethe, H. S., & Joy, E. (2023, May). Revolutionizing E-commerce with 3D Visualization: An experimental assessment of behavioural shopper responses to augmented reality in online shopping. In 2023 4th International Conference for Emerging Technology (INCET) (pp. 1–6). IEEE. https://doi.org/10.1109/INCET57972.2023.10170472
   Google Scholar
• Dey, B. L., Binsardi, B., & Ahmed, M. (2013). The acceptance and adoption of mobile telephony by Bangladeshi farmers: A qualitative inquiry. International Journal of Management Practice, 6(2), 178–198. https://doi.org/10.1504/IJMP.2013.055830
   Google Scholar
• Dincelli, E., & Yayla, A. (2022). Immersive virtual reality in the age of the Metaverse: A hybrid-narrative review based on the technology affordance perspective. The Journal of Strategic Information Systems, 31(2), 101717. https://doi.org/10.1016/j.jsis.2022.101717
   Web of Science ®Google Scholar
• Dutot, V. (2014). Adoption of social media using technology acceptance model: The generational effect. International Journal of Technology and Human Interaction, 10(4), 18–35. https://doi.org/10.4018/ijthi.2014100102
   Google Scholar
• Finney, W., & Davis, R. (1989). Flue gas cleanup technology utilizing energetic electrons (No. DOE/PC/91021-T9). Florida State Univ., Tallahassee, FL (USA). Dept. of Physics.
   Google Scholar
• Garad, A., Al-Ansi, A. M., & Qamari, I. N. (2021). The Role of e-learning infrastructure and cognitive competence in distance learning effectiveness during the COVID-19 pandemic. Jurnal Cakrawala Pendidikan, 40(1), 81–91. https://doi.org/10.21831/cp.v40i1.33474
   Google Scholar
• Ghorbani, Z., Kargaran, S., Saberi, A., Haghighinasab, M., Jamali, S. M., & Ale Ebrahim, N. (2021). Trends and patterns in digital marketing research: Bibliometric analysis. Journal of Marketing Analytics, 10(2), 158–172. https://doi.org/10.1057/s41270-021-00116-9
   Google Scholar
• Hakimi, T. I., Jaafar, J. A., & Aziz, N. A. A. (2023). What factors influence the usage of mobile banking among digital natives? Journal of Financial Services Marketing, 28(4), 763–778. https://doi.org/10.1057/s41264-023-00212-0
   Web of Science ®Google Scholar
• Hassan, M., Kazmi, S., Rehman, M. A., Amaad, H., & Padlee, S. F. (2021). The online shoppers’ behavioral intentions, e-satisfaction, the pathway to repurchase behavior: A quantitative analysis. Estudios De Economia Aplicada, 39(4), 493. https://doi.org/10.25115/eea.v39i4.4493
   Web of Science ®Google Scholar
• Hidayat, Rahmat, Rohana, Tulus, Febrianty, Divianto, Fatmariani, (2019). The perception of technology acceptance to the behaviors on the use of social media for marketing and its implications on the turnover of creative industry MSMEs in villages. Journal of Physics: Conference Series, 1175(1), 2216. https://doi.org/10.1088/1742-6596/1175/1/012216
   Google Scholar
• Hofacker, C., Golgeci, I., Pillai, K. G., & Gligor, D. M. (2020). Digital marketing and business-to-business relationships: A close look at the interface and a roadmap for the future. European Journal of Marketing, 54(6), 1161–1179.
   Google Scholar
• Hur, H. J., Lee, H. K., & Choo, H. J. (2017). Understanding usage intention in innovative mobile app service: Comparison between millennial and mature consumers. Computers in Human Behavior, 73, 353–361. https://doi.org/10.1016/j.chb.2017.03.051
   Web of Science ®Google Scholar
• Iv, Y., Wang, L., & Zhang, Y. (2017). The analysis of rural consumer adoption behavior of the mobile electronic business platform. Paper presented at the 2017 3rd International Conference on Information Management, ICIM 2017, 88–92. Retrieved from www.scopus.com. https://doi.org/10.1109/INFOMAN.2017.7950352
   Google Scholar
• Jayasingh, S., & Eze, U. C. (2009). Exploring the factors affecting the acceptance of mobile coupons in Malaysia. Paper presented at the 2009 8th International Conference on Mobile Business, 329–334. Retrieved from www.scopus.com https://doi.org/10.1109/ICMB.2009.63
   Google Scholar
• Kamarulzaman, Y. (2008). Modeling consumer adoption of Internet shopping. Paper presented at the Innovation and Knowledge Management in Business Globalization: Theory and Practice. – Proceedings of the 10th International Business Information Management Association Conference, 1–2. 1025–1035. Retrieved from www.scopus.com.
   Google Scholar
• Kaur, A., & Malik, G. (2019). Modeling customer intention by integrating corporate image into technology adoption model in Indian internet banking context. International Journal of Innovative Technology and Exploring Engineering, 8(7), 1331–1339. Retrieved from www.scopus.com
   Google Scholar
• Kim, J., & Forsythe, S. (2008). Adoption of virtual try-on technology for online apparel shopping. Journal of Interactive Marketing, 22(2), 45–59. https://doi.org/10.1002/dir.20113
   Web of Science ®Google Scholar
• Ko, H., & Lu, H. (2012). Determinants of adopting intelligent broadband services in the residential community. International Journal of E-Adoption, 4(1), 11–32. https://doi.org/10.4018/jea.2012010102
   Google Scholar
• Kumar, A., Dhingra, S., Batra, V., & Purohit, H. (2020). A framework of mobile banking adoption in India. Journal of Open Innovation, 6(2), 40. https://doi.org/10.3390/joitmc6020040
   Google Scholar
• Lee, J., Kim, J., & Choi, J. Y. (2019). The adoption of virtual reality devices: The technology acceptance model integrating enjoyment, social interaction, and strength of the social ties. Telematics and Informatics, 39, 37–48. https://doi.org/10.1016/j.tele.2018.12.006
   Web of Science ®Google Scholar
• Legris, P., Ingham, J., & Collerette, P. (2003). Why do people use information technology? A critical review of the technology acceptance model. Information & Management, 40(3), 191–204. https://doi.org/10.1016/s0378-7206(01)00143-4
   Web of Science ®Google Scholar
• Leng, J., & Ali, T. (2022). The impact of live streaming features on consumers’ purchase intention – The case of agricultural products. Paper presented at the IMCEC 2022 – IEEE 5th Advanced Information Management, Communicates, Electronic and Automation Control Conference, 1512–1517. Retrieved from www.scopus.com https://doi.org/10.1109/IMCEC55388.2022.10019855
   Google Scholar
• Lewis, R. B. (1999). SIMSTAT with WORDSTAT: A comprehensive statistical package with a content analysis module. Field Methods, 11(2), 166–179. https://doi.org/10.1177/1525822X9901100207
   Google Scholar
• Li, C. (2010). Groundswell. Winning in a world transformed by social technologies. Strategic Direction, 26(8), 2. https://doi.org/10.1108/sd.2010.05626hae.002
   Google Scholar
• Li, Y., Wang, K., Xiao, Y., & Froyd, J. E. (2020). Research and trends in STEM education: A systematic review of journal publications. International Journal of STEM Education, 1(1), 1–16. https://doi.org/10.1186/2196-7822-1-1
   Google Scholar
• Lin, C., Shih, H., & Sher, P. J. (2007). Integrating technology readiness into technology acceptance: The TRAM model. Psychology & Marketing, 24(7), 641–657. 20177 https://doi.org/10.1002/Mar
   Web of Science ®Google Scholar
• Mailangkay, A., Indrajit, E., Kosala, R., & Hidayat, A. (2019). Analysis of the factors that affect intention to use tourism online booking. International Journal of Advanced Trends in Computer Science and Engineering, 8(6), 2710–2715. https://doi.org/10.30534/ijatcse/2019/04862019
   Google Scholar
• Moro, S., Rita, P., & Cortez, P. (2017). A text mining approach to analyzing annals literature. Annals of Tourism Research, 66, 208–210. https://doi.org/10.1016/j.annals.2017.07.011
   Web of Science ®Google Scholar
• Narjabadifam, N., Fouladvand, J., & Gül, M. (2023). Critical review on community-shared solar – Advantages, challenges, and future directions. Energies, 16(8), 3412. https://doi.org/10.3390/en16083412
   Web of Science ®Google Scholar
• Narjabadifam, N., Fouladvand, J., Gül, M., Alqahtani, A., Alhakami, H., Alsubait, T., & Baz, A. (2021). A survey of text-matching techniques. Engineering, Technology & Applied Science Research, 11(1), 6656–6661. https://doi.org/10.48084/etasr.3968
   Web of Science ®Google Scholar
• Nave, M., Rita, P., & Guerreiro, J. (2018). A decision support system framework to track consumer sentiments in social media. Journal of Hospitality Marketing & Management, 27(6), 693–710. https://doi.org/10.1080/19368623.2018.1435327
   Web of Science ®Google Scholar
• Naved, K., & Mohammed, A. (2021). Determining mobile payment adoption: A systematic literature search and bibliometric analysis. Cogent Business & Management, 8(1), 1893245. https://doi.org/10.1080/23311975.2021.1893245
   Web of Science ®Google Scholar
• Online Financial Service Adoption. (2010). The impact of physical banking services on Internet banking acceptance. Behavior and Information Technology, 31(9), 859–871. https://doi.org/10.1080/0144929X.2010.549509
   Web of Science ®Google Scholar
• Rashmi, K., & Kataria, A. (2022). Work–life balance: A systematic literature review and bibliometric analysis. International Journal of Sociology and Social Policy, 42(11/12), 1028–1065. https://doi.org/10.1108/IJSSP-06-2021-0145
   Web of Science ®Google Scholar
• Rowley, J. (1996). Libraries and the electronic information marketplace. Library Review, 45(7), 6–18. https://doi.org/10.1108/00242539610128872
   Google Scholar
• Sharma, D., Taggar, R., Bindra, S., & Dhir, S. (2020). A systematic review of responsiveness to develop future research agenda: A TCCM and bibliometric analysis. Benchmarking, 27(9), 2649–2677. https://doi.org/10.1108/BIJ-12-2019-0539
   Web of Science ®Google Scholar
• Statista. (2020). Revenues from the Artificial Intelligence (AI) Software Market Worldwide from 2018 to 2025.
   Google Scholar
• Wang, Y., Kyriakidis, M., & Dang, V. N. (2021). Incorporating human factors in emergency evacuation – An overview of behavioral factors and models. International Journal of Disaster Risk Reduction, 60, 102254. https://doi.org/10.1016/j.ijdrr.2021.102254
   Web of Science ®Google Scholar