Main Article Content
Abstract
Generative artificial intelligence (AI) is revolutionizing digital marketing by enabling content creation, customer engagement, and strategic decision-making at unprecedented speed and scale. Yet, despite its transformative potential, research on the factors driving marketers’ adoption of generative AI tools such as ChatGPT remains scarce, particularly in emerging economies. Against this backdrop, this study aims to investigate the determinants influencing digital marketers’ adoption of ChatGPT and chart directions for future research. Quantitative research design was employed, drawing on constructs from the TAM and the UTAUT, while incorporating contextual variables such as industry influence, organizational culture, and perceived credibility. Data were collected from 500 digital marketers in Bangladesh using convenience sampling and analyzed using PLS-SEM. The findings reveal that performance expectancy, awareness, effort expectancy, and industry influence significantly shape attitudes toward ChatGPT, whereas organizational culture does not play a significant role. Attitude and perceived credibility emerged as the strongest predictors of actual usage, underscoring the centrality of favorable perceptions and trust in adoption behavior. The chapter makes threefold contributions. Academically, it extends adoption models by highlighting contextual variables in the adoption of AI. Practically, it offers guidance for marketers and organizations to build trust and showcase performance benefits. At the policy level, it calls for regulatory frameworks ensuring credibility and responsible use. Collectively, the study enriches understanding of generative AI adoption and lays a foundation for future research in this rapidly evolving field.
Keywords
Article Details
Copyright (c) 2026 Md. Soleman Mollik, Mohammad Faruk, Md. Masudur Rahman

This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.
Authors who publish with this journal agree to the following terms:
- Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a Creative Commons Attribution-ShareAlike 4.0 International License that allows others to share the work with an acknowledgement of the work's authorship and initial publication in this journal.
- Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgement of its initial publication in this journal.
- Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work (See The Effect of Open Access).
References
- Abdelwahed, N. A. A., Al Doghan, M. A., Saraih, U. N., & Soomro, B. A. (2024). Unleashing potential: Islamic leadership’s influence on employee performance via Islamic organizational values, organizational culture and work motivation. International Journal of Law and Management, 67(2), 165-190. https://doi.org/10.1108/IJLMA-01-2024-0019 DOI: https://doi.org/10.1108/IJLMA-01-2024-0019
- Acar, O. A. (2024). Commentary: Reimagining marketing education in the age of generative AI. International Journal of Research in Marketing, 41(3), 489-495. https://doi.org/10.1016/j.ijresmar.2024.06.004 DOI: https://doi.org/10.1016/j.ijresmar.2024.06.004
- Adu Gyamfi, T., Aigbavboa, C. O., & Thwala, W. D. (2022). Risk resources management influence on public–private partnership risk management in construction industry. Confirmatory factor analysis approach. Journal of Engineering, Design and Technology, 22(5), 1544–1569. https://doi.org/10.1108/JEDT-12-2021-0699 DOI: https://doi.org/10.1108/JEDT-12-2021-0699
- Agarwal, P., Swami, S., & Malhotra, S. K. (2024). Artificial intelligence adoption in the post-COVID-19 new normal and role of smart technologies in transforming business: a review. Journal of Science and Technology Policy Management, 15(3), 506–529. https://doi.org/10.1108/JSTPM-08-2021-0122 DOI: https://doi.org/10.1108/JSTPM-08-2021-0122
- Akter, S., Sultana, S., Mariani, M., Wamba, S. F., Spanaki, K., & Dwivedi, Y. K. (2023). Advancing algorithmic bias management capabilities in AI-driven marketing analytics research. Industrial Marketing Management, 114, 243–261. https://doi.org/10.1016/j.indmarman.2023.08.013 DOI: https://doi.org/10.1016/j.indmarman.2023.08.013
- Al-Momani, A. M., Ramayah, T., & Al-Sharafi, M. A. (2024). Exploring the impact of cybersecurity on using electronic health records and their performance among healthcare professionals: A multi-analytical SEM-ANN approach. Technology in Society, 77: Article e102592. https://doi.org/10.1016/j.techsoc.2024.102592 DOI: https://doi.org/10.1016/j.techsoc.2024.102592
- Ali, I., & Warraich, N. F. (2024). Meta-analysis of technology acceptance for mobile and digital libraries in academic settings using technology acceptance model (TAM). Global Knowledge, Memory and Communication, 74(9-10), 3114-3131. https://doi.org/10.1108/GKMC-09-2023-0360 DOI: https://doi.org/10.1108/GKMC-09-2023-0360
- Ali, M., Raza, S. A., Hakim, F., Puah, C. H., & Chaw, L. Y. (2024). An integrated framework for mobile payment in Pakistan: drivers, barriers, and facilitators of usage behavior. Journal of Financial Services Marketing, 29, 257–275. https://doi.org/10.1057/s41264-022-00199-0 DOI: https://doi.org/10.1057/s41264-022-00199-0
- AlQershi, N. A., Thursamy, R., Alzoraiki, M., Ali, G. A., Mohammed Emam, A. S., & Nasir, M. D. B. M. (2024). Is ChatGPT a source to enhance firms’ strategic value and business sustainability? Journal of Science and Technology Policy Management, 16(1), 121-142. https://doi.org/10.1108/JSTPM-05-2023-0064/FULL/XML DOI: https://doi.org/10.1108/JSTPM-05-2023-0064
- Alshuhumi, S. R., Al-Hidabi, D. A., & Al-Refaei, A. A. A. (2024). Unveiling the behavioral nexus of innovative organizational culture: Identification and affective commitment of teachers in primary schools. Journal of Human Behavior in the Social Environment, 34(1), 130–152. https://doi.org/10.1080/10911359.2023.2267600 DOI: https://doi.org/10.1080/10911359.2023.2267600
- Bag, S., Srivastava, G., Bashir, M. M. Al, Kumari, S., Giannakis, M., & Chowdhury, A. H. (2022). Journey of customers in this digital era: Understanding the role of artificial intelligence technologies in user engagement and conversion. Benchmarking; An International Jurnal, 29(7), 2074–2098. https://doi.org/10.1108/BIJ-07-2021-0415 DOI: https://doi.org/10.1108/BIJ-07-2021-0415
- Baig, M. I., & Yadegaridehkordi, E. (2024). ChatGPT in the higher education: A systematic literature review and research challenges. International Journal of Educational Research, 127: Article 102411. https://doi.org/10.1016/j.ijer.2024.102411 DOI: https://doi.org/10.1016/j.ijer.2024.102411
- Balakrishnan, J., Dwivedi, Y. K., Hughes, L., & Boy, F. (2024). Enablers and inhibitors of AI-powered voice assistants: a dual-factor approach by integrating the status quo bias and technology acceptance model. Information Systems Frontiers, 26, 921–942. https://doi.org/10.1007/s10796-021-10203-y DOI: https://doi.org/10.1007/s10796-021-10203-y
- Bashir, I., & Madhavaiah, C. (2015). Consumer attitude and behavioural intention towards Internet banking adoption in India. Journal of Indian Business Research, 7(1), 67-102. https://doi.org/10.1108/JIBR-02-2014-0013 DOI: https://doi.org/10.1108/JIBR-02-2014-0013
- Behera, R. K., Bala, P. K., Rana, N. P., & Irani, Z. (2024). Empowering co-creation of services with artificial intelligence: an empirical analysis to examine adoption intention. Marketing Intelligence and Planning, 42(6), 941–975. https://doi.org/10.1108/MIP-08-2023-0412 DOI: https://doi.org/10.1108/MIP-08-2023-0412
- Bell, E., Harley, B., & Bryman, A. (2022). Business Research Methods. Oxford University Press. DOI: https://doi.org/10.1093/hebz/9780198869443.001.0001
- Bilal, M., Zhang, Y., Cai, S., Akram, U., & Halibas, A. (2024). Artificial intelligence is the magic wand making customer-centric a reality! An investigation into the relationship between consumer purchase intention and consumer engagement through affective attachment. Journal of Retailing and Consumer Services, 77: Article e103674. https://doi.org/10.1016/j.jretconser.2023.103674 DOI: https://doi.org/10.1016/j.jretconser.2023.103674
- Bin-Nashwan, S. A., Sadallah, M., & Bouteraa, M. (2023). Use of ChatGPT in academia: Academic integrity hangs in the balance. Technology in Society, 75: Article e102370. https://doi.org/10.1016/j.techsoc.2023.102370 DOI: https://doi.org/10.1016/j.techsoc.2023.102370
- Cao, Y., & Zhai, J. (2023). Bridging the gap–the impact of ChatGPT on financial research. Journal of Chinese Economic and Business Studies, 21(2), 177–191. https://doi.org/10.1080/14765284.2023.2212434 DOI: https://doi.org/10.1080/14765284.2023.2212434
- Carvalho, I., & Ivanov, S. (2024). ChatGPT for tourism: applications, benefits and risks. Tourism Review, 79(2), 290–303. https://doi.org/10.1108/TR-02-2023-0088 DOI: https://doi.org/10.1108/TR-02-2023-0088
- Chen, C. T., Chen, S. C., Khan, A., Lim, M. K., & Tseng, M. L. (2024). Antecedents of big data analytics and artificial intelligence adoption on operational performance: the ChatGPT platform. Industrial Management and Data Systems, 124(7), 2388–2413. https://doi.org/10.1108/IMDS-10-2023-0778 DOI: https://doi.org/10.1108/IMDS-10-2023-0778
- Cho, H. Y., Yang, H. C., & Hwang, B. J. (2023). The effect of ChatGPT factors & innovativeness on switching intention: using theory of reasoned action (TRA). Journal of Distribution Science, 21(8), 83–96. https://doi.org/10.15722/jds.21.08.202308.83
- Chua, H. W., & Yu, Z. (2024). A systematic literature review of the acceptability of the use of Metaverse in education over 16 years. In Journal of Computers in Education, 11, 615-665. https://doi.org/10.1007/s40692-023-00273-z DOI: https://doi.org/10.1007/s40692-023-00273-z
- Chui, M., Roberts, R., & Yee, L. (2022). Generative AI is here: How tools like ChatGPT could change your business. Quantum Black AI by McKinsey, 20, 1-5.
- Cong-Lem, N., Soyoof, A., & Tsering, D. (2024). A systematic review of the limitations and associated opportunities of ChatGPT. International Journal of Human-Computer Interaction, 41(7), 3851-3866. https://doi.org/10.1080/10447318.2024.2344142 DOI: https://doi.org/10.1080/10447318.2024.2344142
- Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly: Management Information Systems, 13(3), 319–340. https://doi.org/10.2307/249008 DOI: https://doi.org/10.2307/249008
- Dwivedi, Y. K., Balakrishnan, J., Baabdullah, A. M., & Das, R. (2023). Do chatbots establish “humanness” in the customer purchase journey? An investigation through explanatory sequential design. Psychology and Marketing, 40(11), 2244–2271. https://doi.org/10.1002/mar.21888 DOI: https://doi.org/10.1002/mar.21888
- Etikan, I., Musa, S. A., & Alkassim, R. S. (2016). Comparison of convenience sampling and purposive sampling. American journal of theoretical and applied statistics, 5(1), 1-4. https://doi.org/10.11648/j.ajtas.20160501.11 DOI: https://doi.org/10.11648/j.ajtas.20160501.11
- Ferdush, J., Begum, M., & Hossain, S. T. (2024). ChatGPT and clinical decision support: scope, application, and limitations. Annals of Biomedical Engineering, 52, 1119–1124. https://doi.org/10.1007/s10439-023-03329-4 DOI: https://doi.org/10.1007/s10439-023-03329-4
- Gkikas, D. C., & Theodoridis, P. K. (2022). AI in consumer behavior. Learning and Analytics in Intelligent Systems, 22, 147-176. https://doi.org/10.1007/978-3-030-80571-5_10 DOI: https://doi.org/10.1007/978-3-030-80571-5_10
- Guler, N., Kirshner, S. N., & Vidgen, R. (2024). A literature review of artificial intelligence research in business and management using machine learning and ChatGPT. Data and Information Management. 8(3): Article e100076. https://doi.org/10.1016/j.dim.2024.100076 DOI: https://doi.org/10.1016/j.dim.2024.100076
- Gulzar, M., Smolander, K., Ali, A., & Naqvi, B. (2024). Motivational factors and challenges in the adoption of latest digital technology in educational institutes: A thematic analysis. Procedia Computer Science, 239, 1670–1677. https://doi.org/10.1016/j.procs.2024.06.344 DOI: https://doi.org/10.1016/j.procs.2024.06.344
- Gupta, K., Wajid, A., & Gaur, D. (2024). Determinants of continuous intention to use FinTech services: the moderating role of COVID-19. Journal of Financial Services Marketing, 29, 536–552. https://doi.org/10.1057/s41264-023-00221-z DOI: https://doi.org/10.1057/s41264-023-00221-z
- Gupta, V., & Yang, H. (2024). Study protocol for factors influencing the adoption of ChatGPT technology by startups: Perceptions and attitudes of entrepreneurs. PLoS ONE, 19: Article e0298427. https://doi.org/10.1371/journal.pone.0298427 DOI: https://doi.org/10.1371/journal.pone.0298427
- Hair Jr, J. F., & Sarstedt, M. (2021). Data, measurement, and causal inferences in machine learning: opportunities and challenges for marketing. Journal of Marketing Theory and Practice, 29(1), 65-77. https://doi.org/10.1080/10696679.2020.1860683 DOI: https://doi.org/10.1080/10696679.2020.1860683
- Haleem, A., Javaid, M., & Singh, R. P. (2024). Exploring the competence of ChatGPT for customer and patient service management. Intelligent Pharmacy, 2(3), 392–414. https://doi.org/10.1016/j.ipha.2024.03.002 DOI: https://doi.org/10.1016/j.ipha.2024.03.002
- Hampel, N., Sassenberg, K., Scholl, A., & Ditrich, L. (2024). Enactive mastery experience improves attitudes towards digital technology via self-efficacy–a pre-registered quasi-experiment. Behaviour and Information Technology, 43(2), 298–311. https://doi.org/10.1080/0144929X.2022.2162436 DOI: https://doi.org/10.1080/0144929X.2022.2162436
- Jackson, D., & Allen, C. (2024). Technology adoption in accounting: the role of staff perceptions and organisational context. Journal of Accounting and Organizational Change, 20(2), 205–227. https://doi.org/10.1108/JAOC-01-2023-0007 DOI: https://doi.org/10.1108/JAOC-01-2023-0007
- Jiang, Z. (2024). Transforming the finance industry in China with ChatGPT". Frontiers in Business, Economics and Management, 13(1). https://doi.org/10.54097/5p6fk846 DOI: https://doi.org/10.54097/5p6fk846
- Jo, H., & Bang, Y. (2023). Analyzing ChatGPT adoption drivers with the TOEK framework. Scientific Reports, 13(1), 1–17. https://doi.org/10.1038/s41598-023-49710-0 DOI: https://doi.org/10.1038/s41598-023-49710-0
- Hossain, M. K., & Mollik, M. S. (2022). Exploring the impact of social media platforms on instigating tourist’s emotions and behavioral intentions to co-create and visit tourist spots- Bangladesh Perspective. Journal of Business Studies, 3(1), 217–236. https://doi.org/10.58753/jbspust.3.1.2022.13 DOI: https://doi.org/10.58753/jbspust.3.1.2022.13
- Khan, S., Zhang, Q., Khan, S. U., Khan, I. U., & Khan, R. U. (2024). Understanding mobile augmented reality apps in Pakistan: an extended mobile technology acceptance model. Journal of Tourism Futures, 11(2), 217-239. https://doi.org/10.1108/JTF-04-2022-0131 DOI: https://doi.org/10.1108/JTF-04-2022-0131
- Klaic, M., Fong, J., Crocher, V., Davies, K., Brock, K., Sutton, E., Oetomo, D., Tan, Y., & Galea, M. P. (2024). Application of the extended technology acceptance model to explore clinician likelihood to use robotics in rehabilitation. Disability and Rehabilitation: Assistive Technology, 19(1), 52–59. https://doi.org/10.1080/17483107.2022.2060356 DOI: https://doi.org/10.1080/17483107.2022.2060356
- Kulkov, I., Kulkova, J., Rohrbeck, R., Menvielle, L., Kaartemo, V., & Makkonen, H. (2024). Artificial intelligence - driven sustainable development: Examining organizational, technical, and processing approaches to achieving global goals. Sustainable Development, 32(3), 2253–2267. https://doi.org/10.1002/sd.2773 DOI: https://doi.org/10.1002/sd.2773
- Kumar, A., Gupta, N., & Bapat, G. (2024). Who is making the decisions? How retail managers can use the power of ChatGPT. Journal of Business Strategy, 45(3), 161–169. https://doi.org/10.1108/JBS-04-2023-0067 DOI: https://doi.org/10.1108/JBS-04-2023-0067
- Lai, C. Y., Cheung, K. Y., Chan, C. S., & Law, K. K. (2024). Integrating the adapted UTAUT model with moral obligation, trust and perceived risk to predict ChatGPT adoption for assessment support: A survey with students. Computers and Education: Artificial Intelligence, 6: Article e100246. https://doi.org/10.1016/j.caeai.2024.100246 DOI: https://doi.org/10.1016/j.caeai.2024.100246
- Latreche, H., Bellahcene, M., & Dutot, V. (2024). Does IT culture archetypes affect the perceived usefulness and perceived ease of use of e-banking services? A multistage approach of Algerian customers. International Journal of Bank Marketing, 42(7), 1760-1788. https://doi.org/10.1108/IJBM-02-2023-0100 DOI: https://doi.org/10.1108/IJBM-02-2023-0100
- Ledesma-Chaves, P., Gil-Cordero, E., Navarro-García, A., & Maldonado-López, B. (2024). Satisfaction and performance expectations for the adoption of the metaverse in tourism SMEs. Journal of Innovation and Knowledge, 9(3): Article e100535. https://doi.org/10.1016/j.jik.2024.100535 DOI: https://doi.org/10.1016/j.jik.2024.100535
- Li, J., Dada, A., Puladi, B., Kleesiek, J., & Egger, J. (2024). ChatGPT in healthcare: A taxonomy and systematic review. In Computer Methods and Programs in Biomedicine, 245: Article e108013. Elsevier Ireland Ltd. https://doi.org/10.1016/j.cmpb.2024.108013 DOI: https://doi.org/10.1016/j.cmpb.2024.108013
- Liu, Y., Han, T., Ma, S., Zhang, J., Yang, Y., Tian, J., He, H., Li, A., He, M., Liu, Z., Wu, Z., Zhao, L., Zhu, D., Li, X., Qiang, N., Shen, D., Liu, T., & Ge, B. (2023). Summary of ChatGPT-Related research and perspective towards the future of large language models. Meta-Radiology, 1(2): Article e100017. https://doi.org/10.1016/j.metrad.2023.100017 DOI: https://doi.org/10.1016/j.metrad.2023.100017
- Lopes, J. M., Silva, L. F., & Massano-Cardoso, I. (2024). AI meets the shopper: psychosocial factors in ease of use and their effect on e-commerce purchase intention. Behavioral Sciences, 14(7), 616. https://doi.org/10.3390/bs14070616 DOI: https://doi.org/10.3390/bs14070616
- Mahmud, A., Sarower, A. H., Sohel, A., Assaduzzaman, M., & Bhuiyan, T. (2024). Adoption of ChatGPT by university students for academic purposes: Partial least square, artificial neural network, deep neural network and classification algorithms approach. Array, 21: Article e100339. https://doi.org/10.1016/j.array.2024.100339 DOI: https://doi.org/10.1016/j.array.2024.100339
- Mohajan, H. K. (2020). Quantitative research: A successful investigation in natural and social sciences. Journal of economic development, environment and people, 9(4), 50-79. https://doi.org/10.26458/jedep.v9i4.679 DOI: https://doi.org/10.26458/jedep.v9i4.679
- Mollik, M. S., Rahman, S. M., Rahat, M. R., Kulsum, C. U., & Sagir, S. A. M. (2024). Does trustworthiness influence travel service use intentions at an online travel agency? A study on the digitalization of the tourism Sector in Bangladesh. Geojournal of Tourism and Geosites , 52(1), 30–40. https://doi.org/10.30892/gtg.52103-1180 DOI: https://doi.org/10.30892/gtg.52103-1180
- Niloy, A. C., Bari, M. A., Sultana, J., Chowdhury, R., Raisa, F. M., Islam, A., Mahmud, S., Jahan, I., Sarkar, M., Akter, S., Nishat, N., Afroz, M., Sen, A., Islam, T., Tareq, M. H., & Hossen, M. A. (2024). Why do students use ChatGPT? Answering through a triangulation approach. Computers and Education: Artificial Intelligence, 6: Article e100208. https://doi.org/10.1016/J.CAEAI.2024.100208 DOI: https://doi.org/10.1016/j.caeai.2024.100208
- Salloum, S. A., Aljanada, R. A., Alfaisal, A. M., Al Saidat, M. R., & Alfaisal, R. (2024). Exploring the acceptance of ChatGPT for translation: an extended TAM model approach. Studies in Big Data, 144, 527–542. https://doi.org/10.1007/978-3-031-52280-2_33 DOI: https://doi.org/10.1007/978-3-031-52280-2_33
- Shakeel, S. R., Juntunen, J. K., & Rajala, A. (2024). Business models for enhanced solar photovoltaic (PV) adoption: Transforming customer interaction and engagement practices. Solar Energy, 268: Article e112324. https://doi.org/10.1016/j.solener.2024.112324 DOI: https://doi.org/10.1016/j.solener.2024.112324
- Singh, A., Dwivedi, A., Agrawal, D., & Singh, D. (2023). Identifying issues in adoption of AI practices in construction supply chains: towards managing sustainability. Operations Management Research, 16(4), 1667-1683. https://doi.org/10.1007/s12063-022-00344-x DOI: https://doi.org/10.1007/s12063-022-00344-x
- Sudan, T., Hans, A., & Taggar, R. (2024). Transformative learning with ChatGPT: analyzing adoption trends and implications for business management students in India. Interactive Technology and Smart Education, 21(4), 735-772. https://doi.org/10.1108/ITSE-10-2023-0202 DOI: https://doi.org/10.1108/ITSE-10-2023-0202
- Toyon, M. A. S. (2021). Explanatory sequential design of mixed methods research: Phases and challenges. International Journal of Research in Business and Social Science, 10(5), 253-260. https://doi.org/10.20525/ijrbs.v10i5.1262 DOI: https://doi.org/10.20525/ijrbs.v10i5.1262
- Thi Uyen Nguyen, T., Van Nguyen, P., Thi Ngoc Huynh, H., Truong, G. Q., & Do, L. (2024). Unlocking e-government adoption: Exploring the role of perceived usefulness, ease of use, trust, and social media engagement in Vietnam. Journal of Open Innovation: Technology, Market, and Complexity, 10(2): Article e100291. https://doi.org/10.1016/j.joitmc.2024.100291 DOI: https://doi.org/10.1016/j.joitmc.2024.100291
- Ullah, R., Ismail, H. Bin, Islam Khan, M. T., & Zeb, A. (2024). Nexus between Chat GPT usage dimensions and investment decisions making in Pakistan: Moderating role of financial literacy. Technology in Society, 76: Article e102454. https://doi.org/10.1016/J.TECHSOC.2024.102454 DOI: https://doi.org/10.1016/j.techsoc.2024.102454
- 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://www.jstor.org/stable/30036540 DOI: https://doi.org/10.2307/30036540
- Wilendra, W., Nadlifatin, R., & Kusumawulan, C. K. (2024). ChatGPT: the AI game-changing revolution in marketing strategy for the Indonesian cosmetic industry. Procedia Computer Science, 234, 1012–1019. https://doi.org/10.1016/j.procs.2024.03.091 DOI: https://doi.org/10.1016/j.procs.2024.03.091
- Yuan, M., Bao, P., Yuan, J., Shen, Y., Chen, Z., Xie, Y., Zhao, J., Li, Q., Chen, Y., Zhang, L., Shen, L., & Dong, B. (2024). Large language models illuminate a progressive pathway to artificial intelligent healthcare assistant. Medicine Plus, 1(2): Article e100030. https://doi.org/10.1016/j.medp.2024.100030 DOI: https://doi.org/10.1016/j.medp.2024.100030
References
Abdelwahed, N. A. A., Al Doghan, M. A., Saraih, U. N., & Soomro, B. A. (2024). Unleashing potential: Islamic leadership’s influence on employee performance via Islamic organizational values, organizational culture and work motivation. International Journal of Law and Management, 67(2), 165-190. https://doi.org/10.1108/IJLMA-01-2024-0019 DOI: https://doi.org/10.1108/IJLMA-01-2024-0019
Acar, O. A. (2024). Commentary: Reimagining marketing education in the age of generative AI. International Journal of Research in Marketing, 41(3), 489-495. https://doi.org/10.1016/j.ijresmar.2024.06.004 DOI: https://doi.org/10.1016/j.ijresmar.2024.06.004
Adu Gyamfi, T., Aigbavboa, C. O., & Thwala, W. D. (2022). Risk resources management influence on public–private partnership risk management in construction industry. Confirmatory factor analysis approach. Journal of Engineering, Design and Technology, 22(5), 1544–1569. https://doi.org/10.1108/JEDT-12-2021-0699 DOI: https://doi.org/10.1108/JEDT-12-2021-0699
Agarwal, P., Swami, S., & Malhotra, S. K. (2024). Artificial intelligence adoption in the post-COVID-19 new normal and role of smart technologies in transforming business: a review. Journal of Science and Technology Policy Management, 15(3), 506–529. https://doi.org/10.1108/JSTPM-08-2021-0122 DOI: https://doi.org/10.1108/JSTPM-08-2021-0122
Akter, S., Sultana, S., Mariani, M., Wamba, S. F., Spanaki, K., & Dwivedi, Y. K. (2023). Advancing algorithmic bias management capabilities in AI-driven marketing analytics research. Industrial Marketing Management, 114, 243–261. https://doi.org/10.1016/j.indmarman.2023.08.013 DOI: https://doi.org/10.1016/j.indmarman.2023.08.013
Al-Momani, A. M., Ramayah, T., & Al-Sharafi, M. A. (2024). Exploring the impact of cybersecurity on using electronic health records and their performance among healthcare professionals: A multi-analytical SEM-ANN approach. Technology in Society, 77: Article e102592. https://doi.org/10.1016/j.techsoc.2024.102592 DOI: https://doi.org/10.1016/j.techsoc.2024.102592
Ali, I., & Warraich, N. F. (2024). Meta-analysis of technology acceptance for mobile and digital libraries in academic settings using technology acceptance model (TAM). Global Knowledge, Memory and Communication, 74(9-10), 3114-3131. https://doi.org/10.1108/GKMC-09-2023-0360 DOI: https://doi.org/10.1108/GKMC-09-2023-0360
Ali, M., Raza, S. A., Hakim, F., Puah, C. H., & Chaw, L. Y. (2024). An integrated framework for mobile payment in Pakistan: drivers, barriers, and facilitators of usage behavior. Journal of Financial Services Marketing, 29, 257–275. https://doi.org/10.1057/s41264-022-00199-0 DOI: https://doi.org/10.1057/s41264-022-00199-0
AlQershi, N. A., Thursamy, R., Alzoraiki, M., Ali, G. A., Mohammed Emam, A. S., & Nasir, M. D. B. M. (2024). Is ChatGPT a source to enhance firms’ strategic value and business sustainability? Journal of Science and Technology Policy Management, 16(1), 121-142. https://doi.org/10.1108/JSTPM-05-2023-0064/FULL/XML DOI: https://doi.org/10.1108/JSTPM-05-2023-0064
Alshuhumi, S. R., Al-Hidabi, D. A., & Al-Refaei, A. A. A. (2024). Unveiling the behavioral nexus of innovative organizational culture: Identification and affective commitment of teachers in primary schools. Journal of Human Behavior in the Social Environment, 34(1), 130–152. https://doi.org/10.1080/10911359.2023.2267600 DOI: https://doi.org/10.1080/10911359.2023.2267600
Bag, S., Srivastava, G., Bashir, M. M. Al, Kumari, S., Giannakis, M., & Chowdhury, A. H. (2022). Journey of customers in this digital era: Understanding the role of artificial intelligence technologies in user engagement and conversion. Benchmarking; An International Jurnal, 29(7), 2074–2098. https://doi.org/10.1108/BIJ-07-2021-0415 DOI: https://doi.org/10.1108/BIJ-07-2021-0415
Baig, M. I., & Yadegaridehkordi, E. (2024). ChatGPT in the higher education: A systematic literature review and research challenges. International Journal of Educational Research, 127: Article 102411. https://doi.org/10.1016/j.ijer.2024.102411 DOI: https://doi.org/10.1016/j.ijer.2024.102411
Balakrishnan, J., Dwivedi, Y. K., Hughes, L., & Boy, F. (2024). Enablers and inhibitors of AI-powered voice assistants: a dual-factor approach by integrating the status quo bias and technology acceptance model. Information Systems Frontiers, 26, 921–942. https://doi.org/10.1007/s10796-021-10203-y DOI: https://doi.org/10.1007/s10796-021-10203-y
Bashir, I., & Madhavaiah, C. (2015). Consumer attitude and behavioural intention towards Internet banking adoption in India. Journal of Indian Business Research, 7(1), 67-102. https://doi.org/10.1108/JIBR-02-2014-0013 DOI: https://doi.org/10.1108/JIBR-02-2014-0013
Behera, R. K., Bala, P. K., Rana, N. P., & Irani, Z. (2024). Empowering co-creation of services with artificial intelligence: an empirical analysis to examine adoption intention. Marketing Intelligence and Planning, 42(6), 941–975. https://doi.org/10.1108/MIP-08-2023-0412 DOI: https://doi.org/10.1108/MIP-08-2023-0412
Bell, E., Harley, B., & Bryman, A. (2022). Business Research Methods. Oxford University Press. DOI: https://doi.org/10.1093/hebz/9780198869443.001.0001
Bilal, M., Zhang, Y., Cai, S., Akram, U., & Halibas, A. (2024). Artificial intelligence is the magic wand making customer-centric a reality! An investigation into the relationship between consumer purchase intention and consumer engagement through affective attachment. Journal of Retailing and Consumer Services, 77: Article e103674. https://doi.org/10.1016/j.jretconser.2023.103674 DOI: https://doi.org/10.1016/j.jretconser.2023.103674
Bin-Nashwan, S. A., Sadallah, M., & Bouteraa, M. (2023). Use of ChatGPT in academia: Academic integrity hangs in the balance. Technology in Society, 75: Article e102370. https://doi.org/10.1016/j.techsoc.2023.102370 DOI: https://doi.org/10.1016/j.techsoc.2023.102370
Cao, Y., & Zhai, J. (2023). Bridging the gap–the impact of ChatGPT on financial research. Journal of Chinese Economic and Business Studies, 21(2), 177–191. https://doi.org/10.1080/14765284.2023.2212434 DOI: https://doi.org/10.1080/14765284.2023.2212434
Carvalho, I., & Ivanov, S. (2024). ChatGPT for tourism: applications, benefits and risks. Tourism Review, 79(2), 290–303. https://doi.org/10.1108/TR-02-2023-0088 DOI: https://doi.org/10.1108/TR-02-2023-0088
Chen, C. T., Chen, S. C., Khan, A., Lim, M. K., & Tseng, M. L. (2024). Antecedents of big data analytics and artificial intelligence adoption on operational performance: the ChatGPT platform. Industrial Management and Data Systems, 124(7), 2388–2413. https://doi.org/10.1108/IMDS-10-2023-0778 DOI: https://doi.org/10.1108/IMDS-10-2023-0778
Cho, H. Y., Yang, H. C., & Hwang, B. J. (2023). The effect of ChatGPT factors & innovativeness on switching intention: using theory of reasoned action (TRA). Journal of Distribution Science, 21(8), 83–96. https://doi.org/10.15722/jds.21.08.202308.83
Chua, H. W., & Yu, Z. (2024). A systematic literature review of the acceptability of the use of Metaverse in education over 16 years. In Journal of Computers in Education, 11, 615-665. https://doi.org/10.1007/s40692-023-00273-z DOI: https://doi.org/10.1007/s40692-023-00273-z
Chui, M., Roberts, R., & Yee, L. (2022). Generative AI is here: How tools like ChatGPT could change your business. Quantum Black AI by McKinsey, 20, 1-5.
Cong-Lem, N., Soyoof, A., & Tsering, D. (2024). A systematic review of the limitations and associated opportunities of ChatGPT. International Journal of Human-Computer Interaction, 41(7), 3851-3866. https://doi.org/10.1080/10447318.2024.2344142 DOI: https://doi.org/10.1080/10447318.2024.2344142
Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly: Management Information Systems, 13(3), 319–340. https://doi.org/10.2307/249008 DOI: https://doi.org/10.2307/249008
Dwivedi, Y. K., Balakrishnan, J., Baabdullah, A. M., & Das, R. (2023). Do chatbots establish “humanness” in the customer purchase journey? An investigation through explanatory sequential design. Psychology and Marketing, 40(11), 2244–2271. https://doi.org/10.1002/mar.21888 DOI: https://doi.org/10.1002/mar.21888
Etikan, I., Musa, S. A., & Alkassim, R. S. (2016). Comparison of convenience sampling and purposive sampling. American journal of theoretical and applied statistics, 5(1), 1-4. https://doi.org/10.11648/j.ajtas.20160501.11 DOI: https://doi.org/10.11648/j.ajtas.20160501.11
Ferdush, J., Begum, M., & Hossain, S. T. (2024). ChatGPT and clinical decision support: scope, application, and limitations. Annals of Biomedical Engineering, 52, 1119–1124. https://doi.org/10.1007/s10439-023-03329-4 DOI: https://doi.org/10.1007/s10439-023-03329-4
Gkikas, D. C., & Theodoridis, P. K. (2022). AI in consumer behavior. Learning and Analytics in Intelligent Systems, 22, 147-176. https://doi.org/10.1007/978-3-030-80571-5_10 DOI: https://doi.org/10.1007/978-3-030-80571-5_10
Guler, N., Kirshner, S. N., & Vidgen, R. (2024). A literature review of artificial intelligence research in business and management using machine learning and ChatGPT. Data and Information Management. 8(3): Article e100076. https://doi.org/10.1016/j.dim.2024.100076 DOI: https://doi.org/10.1016/j.dim.2024.100076
Gulzar, M., Smolander, K., Ali, A., & Naqvi, B. (2024). Motivational factors and challenges in the adoption of latest digital technology in educational institutes: A thematic analysis. Procedia Computer Science, 239, 1670–1677. https://doi.org/10.1016/j.procs.2024.06.344 DOI: https://doi.org/10.1016/j.procs.2024.06.344
Gupta, K., Wajid, A., & Gaur, D. (2024). Determinants of continuous intention to use FinTech services: the moderating role of COVID-19. Journal of Financial Services Marketing, 29, 536–552. https://doi.org/10.1057/s41264-023-00221-z DOI: https://doi.org/10.1057/s41264-023-00221-z
Gupta, V., & Yang, H. (2024). Study protocol for factors influencing the adoption of ChatGPT technology by startups: Perceptions and attitudes of entrepreneurs. PLoS ONE, 19: Article e0298427. https://doi.org/10.1371/journal.pone.0298427 DOI: https://doi.org/10.1371/journal.pone.0298427
Hair Jr, J. F., & Sarstedt, M. (2021). Data, measurement, and causal inferences in machine learning: opportunities and challenges for marketing. Journal of Marketing Theory and Practice, 29(1), 65-77. https://doi.org/10.1080/10696679.2020.1860683 DOI: https://doi.org/10.1080/10696679.2020.1860683
Haleem, A., Javaid, M., & Singh, R. P. (2024). Exploring the competence of ChatGPT for customer and patient service management. Intelligent Pharmacy, 2(3), 392–414. https://doi.org/10.1016/j.ipha.2024.03.002 DOI: https://doi.org/10.1016/j.ipha.2024.03.002
Hampel, N., Sassenberg, K., Scholl, A., & Ditrich, L. (2024). Enactive mastery experience improves attitudes towards digital technology via self-efficacy–a pre-registered quasi-experiment. Behaviour and Information Technology, 43(2), 298–311. https://doi.org/10.1080/0144929X.2022.2162436 DOI: https://doi.org/10.1080/0144929X.2022.2162436
Jackson, D., & Allen, C. (2024). Technology adoption in accounting: the role of staff perceptions and organisational context. Journal of Accounting and Organizational Change, 20(2), 205–227. https://doi.org/10.1108/JAOC-01-2023-0007 DOI: https://doi.org/10.1108/JAOC-01-2023-0007
Jiang, Z. (2024). Transforming the finance industry in China with ChatGPT". Frontiers in Business, Economics and Management, 13(1). https://doi.org/10.54097/5p6fk846 DOI: https://doi.org/10.54097/5p6fk846
Jo, H., & Bang, Y. (2023). Analyzing ChatGPT adoption drivers with the TOEK framework. Scientific Reports, 13(1), 1–17. https://doi.org/10.1038/s41598-023-49710-0 DOI: https://doi.org/10.1038/s41598-023-49710-0
Hossain, M. K., & Mollik, M. S. (2022). Exploring the impact of social media platforms on instigating tourist’s emotions and behavioral intentions to co-create and visit tourist spots- Bangladesh Perspective. Journal of Business Studies, 3(1), 217–236. https://doi.org/10.58753/jbspust.3.1.2022.13 DOI: https://doi.org/10.58753/jbspust.3.1.2022.13
Khan, S., Zhang, Q., Khan, S. U., Khan, I. U., & Khan, R. U. (2024). Understanding mobile augmented reality apps in Pakistan: an extended mobile technology acceptance model. Journal of Tourism Futures, 11(2), 217-239. https://doi.org/10.1108/JTF-04-2022-0131 DOI: https://doi.org/10.1108/JTF-04-2022-0131
Klaic, M., Fong, J., Crocher, V., Davies, K., Brock, K., Sutton, E., Oetomo, D., Tan, Y., & Galea, M. P. (2024). Application of the extended technology acceptance model to explore clinician likelihood to use robotics in rehabilitation. Disability and Rehabilitation: Assistive Technology, 19(1), 52–59. https://doi.org/10.1080/17483107.2022.2060356 DOI: https://doi.org/10.1080/17483107.2022.2060356
Kulkov, I., Kulkova, J., Rohrbeck, R., Menvielle, L., Kaartemo, V., & Makkonen, H. (2024). Artificial intelligence - driven sustainable development: Examining organizational, technical, and processing approaches to achieving global goals. Sustainable Development, 32(3), 2253–2267. https://doi.org/10.1002/sd.2773 DOI: https://doi.org/10.1002/sd.2773
Kumar, A., Gupta, N., & Bapat, G. (2024). Who is making the decisions? How retail managers can use the power of ChatGPT. Journal of Business Strategy, 45(3), 161–169. https://doi.org/10.1108/JBS-04-2023-0067 DOI: https://doi.org/10.1108/JBS-04-2023-0067
Lai, C. Y., Cheung, K. Y., Chan, C. S., & Law, K. K. (2024). Integrating the adapted UTAUT model with moral obligation, trust and perceived risk to predict ChatGPT adoption for assessment support: A survey with students. Computers and Education: Artificial Intelligence, 6: Article e100246. https://doi.org/10.1016/j.caeai.2024.100246 DOI: https://doi.org/10.1016/j.caeai.2024.100246
Latreche, H., Bellahcene, M., & Dutot, V. (2024). Does IT culture archetypes affect the perceived usefulness and perceived ease of use of e-banking services? A multistage approach of Algerian customers. International Journal of Bank Marketing, 42(7), 1760-1788. https://doi.org/10.1108/IJBM-02-2023-0100 DOI: https://doi.org/10.1108/IJBM-02-2023-0100
Ledesma-Chaves, P., Gil-Cordero, E., Navarro-García, A., & Maldonado-López, B. (2024). Satisfaction and performance expectations for the adoption of the metaverse in tourism SMEs. Journal of Innovation and Knowledge, 9(3): Article e100535. https://doi.org/10.1016/j.jik.2024.100535 DOI: https://doi.org/10.1016/j.jik.2024.100535
Li, J., Dada, A., Puladi, B., Kleesiek, J., & Egger, J. (2024). ChatGPT in healthcare: A taxonomy and systematic review. In Computer Methods and Programs in Biomedicine, 245: Article e108013. Elsevier Ireland Ltd. https://doi.org/10.1016/j.cmpb.2024.108013 DOI: https://doi.org/10.1016/j.cmpb.2024.108013
Liu, Y., Han, T., Ma, S., Zhang, J., Yang, Y., Tian, J., He, H., Li, A., He, M., Liu, Z., Wu, Z., Zhao, L., Zhu, D., Li, X., Qiang, N., Shen, D., Liu, T., & Ge, B. (2023). Summary of ChatGPT-Related research and perspective towards the future of large language models. Meta-Radiology, 1(2): Article e100017. https://doi.org/10.1016/j.metrad.2023.100017 DOI: https://doi.org/10.1016/j.metrad.2023.100017
Lopes, J. M., Silva, L. F., & Massano-Cardoso, I. (2024). AI meets the shopper: psychosocial factors in ease of use and their effect on e-commerce purchase intention. Behavioral Sciences, 14(7), 616. https://doi.org/10.3390/bs14070616 DOI: https://doi.org/10.3390/bs14070616
Mahmud, A., Sarower, A. H., Sohel, A., Assaduzzaman, M., & Bhuiyan, T. (2024). Adoption of ChatGPT by university students for academic purposes: Partial least square, artificial neural network, deep neural network and classification algorithms approach. Array, 21: Article e100339. https://doi.org/10.1016/j.array.2024.100339 DOI: https://doi.org/10.1016/j.array.2024.100339
Mohajan, H. K. (2020). Quantitative research: A successful investigation in natural and social sciences. Journal of economic development, environment and people, 9(4), 50-79. https://doi.org/10.26458/jedep.v9i4.679 DOI: https://doi.org/10.26458/jedep.v9i4.679
Mollik, M. S., Rahman, S. M., Rahat, M. R., Kulsum, C. U., & Sagir, S. A. M. (2024). Does trustworthiness influence travel service use intentions at an online travel agency? A study on the digitalization of the tourism Sector in Bangladesh. Geojournal of Tourism and Geosites , 52(1), 30–40. https://doi.org/10.30892/gtg.52103-1180 DOI: https://doi.org/10.30892/gtg.52103-1180
Niloy, A. C., Bari, M. A., Sultana, J., Chowdhury, R., Raisa, F. M., Islam, A., Mahmud, S., Jahan, I., Sarkar, M., Akter, S., Nishat, N., Afroz, M., Sen, A., Islam, T., Tareq, M. H., & Hossen, M. A. (2024). Why do students use ChatGPT? Answering through a triangulation approach. Computers and Education: Artificial Intelligence, 6: Article e100208. https://doi.org/10.1016/J.CAEAI.2024.100208 DOI: https://doi.org/10.1016/j.caeai.2024.100208
Salloum, S. A., Aljanada, R. A., Alfaisal, A. M., Al Saidat, M. R., & Alfaisal, R. (2024). Exploring the acceptance of ChatGPT for translation: an extended TAM model approach. Studies in Big Data, 144, 527–542. https://doi.org/10.1007/978-3-031-52280-2_33 DOI: https://doi.org/10.1007/978-3-031-52280-2_33
Shakeel, S. R., Juntunen, J. K., & Rajala, A. (2024). Business models for enhanced solar photovoltaic (PV) adoption: Transforming customer interaction and engagement practices. Solar Energy, 268: Article e112324. https://doi.org/10.1016/j.solener.2024.112324 DOI: https://doi.org/10.1016/j.solener.2024.112324
Singh, A., Dwivedi, A., Agrawal, D., & Singh, D. (2023). Identifying issues in adoption of AI practices in construction supply chains: towards managing sustainability. Operations Management Research, 16(4), 1667-1683. https://doi.org/10.1007/s12063-022-00344-x DOI: https://doi.org/10.1007/s12063-022-00344-x
Sudan, T., Hans, A., & Taggar, R. (2024). Transformative learning with ChatGPT: analyzing adoption trends and implications for business management students in India. Interactive Technology and Smart Education, 21(4), 735-772. https://doi.org/10.1108/ITSE-10-2023-0202 DOI: https://doi.org/10.1108/ITSE-10-2023-0202
Toyon, M. A. S. (2021). Explanatory sequential design of mixed methods research: Phases and challenges. International Journal of Research in Business and Social Science, 10(5), 253-260. https://doi.org/10.20525/ijrbs.v10i5.1262 DOI: https://doi.org/10.20525/ijrbs.v10i5.1262
Thi Uyen Nguyen, T., Van Nguyen, P., Thi Ngoc Huynh, H., Truong, G. Q., & Do, L. (2024). Unlocking e-government adoption: Exploring the role of perceived usefulness, ease of use, trust, and social media engagement in Vietnam. Journal of Open Innovation: Technology, Market, and Complexity, 10(2): Article e100291. https://doi.org/10.1016/j.joitmc.2024.100291 DOI: https://doi.org/10.1016/j.joitmc.2024.100291
Ullah, R., Ismail, H. Bin, Islam Khan, M. T., & Zeb, A. (2024). Nexus between Chat GPT usage dimensions and investment decisions making in Pakistan: Moderating role of financial literacy. Technology in Society, 76: Article e102454. https://doi.org/10.1016/J.TECHSOC.2024.102454 DOI: https://doi.org/10.1016/j.techsoc.2024.102454
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://www.jstor.org/stable/30036540 DOI: https://doi.org/10.2307/30036540
Wilendra, W., Nadlifatin, R., & Kusumawulan, C. K. (2024). ChatGPT: the AI game-changing revolution in marketing strategy for the Indonesian cosmetic industry. Procedia Computer Science, 234, 1012–1019. https://doi.org/10.1016/j.procs.2024.03.091 DOI: https://doi.org/10.1016/j.procs.2024.03.091
Yuan, M., Bao, P., Yuan, J., Shen, Y., Chen, Z., Xie, Y., Zhao, J., Li, Q., Chen, Y., Zhang, L., Shen, L., & Dong, B. (2024). Large language models illuminate a progressive pathway to artificial intelligent healthcare assistant. Medicine Plus, 1(2): Article e100030. https://doi.org/10.1016/j.medp.2024.100030 DOI: https://doi.org/10.1016/j.medp.2024.100030