The Impact of the ChatGPT Platform on Consumer Experience in Digital Marketing and User Satisfaction
Abstract
ChatGPT, an artificial intelligence (AI) chat platform, facilitates conversation between humans and bots. By integrating machine learning and natural language processing, it revolutionizes the way people interact with AI. Many people are excited about using ChatGPT because it has numerous potential applications and advantages compared to other similar programs. Therefore, this paper demonstrates that, in line with specific ethical considerations, ChatGPT has enormous potential to revolutionize and shape the future of marketing. We begin by questioning whether ChatGPT has a significant impact on consumer experience in digital marketing and overall user satisfaction. The methods used in the study include descriptive and inferential statistical methods, as well as the OLS method. The results show that the use of ChatGPT is continuously rising and increasingly being implemented in various industry segments, particularly in the field of digital marketing. Automation of customer care, increased productivity, automated research, and better understanding of consumers are ways it can assist marketing professionals.
References
[1] Aceto, G., Persico, V. and Pescapé, A. (2018). The role of Information and Communication Technologies in healthcare: taxonomies, perspectives, and challenges. Journal of Network and Computer Applications, 107, 125-154. DOI: https://doi.org/10.1016/j.jnca.2018.02.008
[2] Araujo, T. (2018). Living up to the chatbot hype: the influence of anthropomorphic de-sign cues and communicative agency framing on conversational agent and company perceptions. Comput. Hum. Behav., 85: 183–189. DOI: https://doi.org/10.1016/j. chb.2018.03.051
[3] Ashfaq, M., Yun, J., Yu, S. and Loureiro, S. M. C. I. (2020). Chatbot: Modeling the determinants of users’ satisfaction and continuance intention of AI-powered service agents. Telematics and Informatics, 54, 101473. DOI: https://doi.org/10.1016/j.tele.2020.101473
[4] Buhalis, D. and Karatay, N. (2022). Mixed reality (MR) for generation Z in cultural heritage tourism towards metaverse. In Information and Communication Technologies in Tourism 2022: Proceedings of the ENTER 2022 eTourism Conference, Springer International Publishing, 16-27. DOI: https://doi.org/10.1007/978-3-030-94751-4_2
[5] Buhalis, D., Leung, D. and Lin, M. (2023). Metaverse as a disruptive technology revolutionising tourism management and marketing. Tourism Management, 97, 104724. DOI: https://doi.org/10.1016/j.tourman.2023.104724
[6] Chen, Q., Yin, C. and Gong, Y. (2023). Would an AI chatbot persuade you: An empirical answer from the elaboration likelihood model. Information Technology and People. DOI: https://doi.org/10.1108/ITP-10-2021-0764
[7] Chen, Y. and Xie, J. (2008). Online consumer review: Word-of-mouth as a new element of marketing communication mix. Management science, 54(3): 477-491. DOI: http://dx.doi.org/10.5958/2249-877X.2021.00117.X
[8] Chiu, W., Cho, H. and Chi, C.G. (2021). Consumers’ continuance intention to use fitness and health apps: an integration of the expectation–confirmation model and investment model. Inf. Technol. People, 34 (3): 978–998. DOI: https://doi.org/10.1108/ITP-09-2019- 0463
[9] Chopra, S.S. (2020). Helping Entrepreneurs and Small Businesses Make the Digital Transformation. In The Evolution of Business in the Cyber Age. Apple Academic Press, 39-51.
[10] Davis, A. et al. (2009). Avatars, people, and virtual worlds: Foundations for research in metaverses. Journal of the Association for In-formation Systems, 10(2), 1.
[11] Denić, N., et al. (2018). A survey of internet marketing by small and medium-sized enterprises for placing wine on the market. Physica A: Statistical Mechanics and its Applications. DOI:https://doi.org/10.1016/j.physa.2018.04.095
[12] Dwivedi, Y. K. et al. (2017). “So what if ChatGPT wrote it?” Multidisciplinary perspectives on opportunities, challenges and implications of generative conversational AI for research, practice and policy. International Journal of Information Management, 2023, 71, 102642. DOI: https://doi.org/10.1016/j.ijinfomgt.2023.102642
[13] Dwivedi, Y.K. et al. (2021). Setting the Future of Digital and Social Media Marketing Research: Perspectives and Research Propositions. Int. J. Inf. Manag., 59. DOI:https://doi.org/10.1016/j.ijinfomgt.2020.102168
[14] Edwards, C., Edwards, A., Spence, P. R. and Shelton, A. K. (2014). Is that a bot running the social media feed? Testing the differences in perceptions of communication quality for a human agent and a bot agent on Twitter. Computers in Human Behavior, 33: 372-376. DOI: https://doi.org/10.1016/j.chb.2013.08.013
[15] Fu, C. J., et al. (2024). Balancing Satisfaction and Clarity: Enhancing User Information Satisfaction with AI-Powered ChatGPT in Higher Education. Preprints. DOI:https://doi.org/10.20944/preprints202402.0040.v1
[16] Goralski, M. A. and Tan, T. K. (2022). Artificial intelligence and poverty alleviation: Emerging innovations and their implications for management education and sustainable development. The International Journal of Management Education, 20(3). DOI: https://doi.org/10.1016/j.ijme.2022.100662
[17] Gordijn, B. and Have, H. T. (2023). ChatGPT: evolution or revolution? Medicine, Health Care and Philosophy, 26(1): 1-2. DOI: https://doi.org/10.1007/s11019-023-10136-0
[18] Guha, A. et al. (2021). How artificial intelligence will affect the future of retailing. Journal of Retailing, 97(1): 28-41. DOI: https://doi.org/10.1016/j.jretai.2021.01.005
[19] Hew, J. J., Lee, V. H., Ooi, K. B. and Lin, B. (2016). Mobile social commerce: The booster for brand loyalty? Computers in Human Behavior, 59: 142-154. DOI: https://doi.org/10.1016/j.chb.2016.01.027
[20] Jang, M., Jung, Y. and Kim, S. (2021). Investigating managers’ understanding of chatbots in the Korean financial industry. Computers in Human Behavior, 120, 106747. DOI:https://doi.org/10.1016/j.chb.2021.106747
[21] Johari, N.M., Zaman, H.B. and Nohuddin, P.N.E. (2019). Ascertain quality attributes for de-sign and development of new improved chatbots to assess customer satisfaction index (CSI): a preliminary study. In: Lecture Notes in Computer Science. Springer, Singapore, pp. 135–146. DOI: https://doi.org/10.1007/978-3-030-34032-2_13
[22] Kaur, P. et al. (2020). Why do people purchase virtual goods? A uses and gratification (UandG) theory perspective. Telemat. Inform., 53, 101376. DOI: https://doi.org/10.1016/j.tele.2020.101376
[23] Kim, B. (2010). An empirical investigation of mobile data service continuance: incorporating the theory of planned behavior into the expectation-confirmation model. Expert Syst. Appl, 37 (10): 7033–7039. DOI:https://doi.org/10.1016/j. eswa.2010.03.015
[24] Klang, E. and Levy-Mendelovich, S. (2023). Evaluation of OpenAI’s large language model as a new tool for writing papers in the field of thrombosis and hemostasis. Journal of Thrombosis and Haemostasis, 21(4): 1055-1058. DOI: https://doi.org/10.1016/j.jtha.2023.01.011
[25] Kumar, S. et al. (2024). Will artificial intelligence drive the advancements in higher education? A tri-phased exploration. Techno-logical Forecasting and Social Change, 201, 123258. DOI:https://doi.org/10.1016/j.techfore.2024.123258
[26] Lee, Y. and Kwon, O. (2011). Intimacy, familiarity and continuance intention: an extended expectation–confirmation model in web-based services. Electron. Commer. Res. Appl., 10 (3): 342–357. DOI:https://doi.org/10.1016/j.elerap.2010.11.005
[27] Li, L., Lee, K.Y., Emokpae, E. and Yang, S.B. (2021). What makes you continuously use chatbot services? Evidence from Chinese online travel agencies. Electronic Markets, 21(1): 1-25. DOI:https://doi.org/10.1007/s12525-020-00454-z
[28] Lim, W. M., Kumar, S., Verma, S. and Chaturvedi, R. (2022). Alexa, what do we know about conversational commerce? Insights from a systematic literature review. Psychology and Marketing, 39(6): 1129–1155. DOI:https://doi.org/10.1002/mar.21654
[29] Limayem, M. and Cheung, C. (2008). Understanding information systems continuance: the case of Internet-based learning technologies. Inf. Manag., 45 (4): 227–232. DOI: https://doi.org/10.1016/j.im.2008.02.005
[30] Lin, W.S. (2012). Perceived fit and satisfaction on web learning performance: IS continuance intention and task-technology fit perspectives. Int. J. Hum. Comput. Stud, 70 (7): 498–507. DOI:https://doi.org/10.1016/j.ijhcs.2012.01.006
[31] Liu, C. and Lee, C. (2020). Chatbots in marketing: overview, classification, and recommendations for future research, J. Bus. Res., 109: 340–351. DOI: https://doi.org/10.1016/j.jbusres.2019.11.019
[32] Lowry, P. B., Romano, N. C., Jenkins, J. L. and Guthrie, R. W. (2009). The CMC interactivity model: How interactivity enhances communication quality and process satisfaction in lean-media groups. Journal of Management Information Systems, 26(1): 155-196. DOI: https://doi.org/10.2753/MIS0742-1222260107
[33] Lu, C. C., Wu, L., and Hsiao, W. H. (2019). Developing customer product loyalty through mobile advertising: Affective and cognitive perspectives. International Journal of Information Management, 47: 101-111. DOI:https://doi.org/10.1016/j.ijinfomgt.2018.12.020
[34] Lundmark, P. (2022). The real future of the metaverse is not for consumers. Accessed at: https://www.ft.com/content/af0c9de8-d36e-485b-9db5-5ee1e57716cb
[35] Luo, M.M., Remus, W. and Chea, S. (2006). Technology Acceptance of Internet-based Information Services: An Integrated Model of TAM and UandG Theory. AMCIS (2006), 153.
[36] Mimoun, M. S. B., Poncin, I. and Garnier, M. (2017). Animated conversational agents and e-consumer productivity: The roles of agents and individual characteristics. Information and Management, 54(5): 545-559. DOI: https://doi.org/10.1016/j.im.2016.11.008
[37] Moy, C. and Gadgil, A. (2022). Opportunities in the metaverse. JP Morgan and chase. Available at: https://www.jpmorgan.com/content/dam/jpm/treasuryservices/documents/opportuni-ties-in-the-metaverse.pdf
[38] Nagy, S. and Hajdú, N. (2021). Consumer Acceptance of the Use of Artificial Intelligence in Online Shopping: Evidence from Hungary. Amfiteatru Economic, 23(56).
[39] Ramaul, L. (2021). Role of AI in marketing through CRM integration with specific reference to chatbots. Available at: http://urn.fi/URN:NBN:fi:jyu-202106143690
[40] Rese, A., Ganster, L. and Baier, D. (2020). Chatbots in retailers’ customer communication: How to measure their acceptance? J. Retail. Consum. Serv., 56, 102176. DOI:https://doi.org/10.1016/j.jretconser.2020.102176
[41] Rivas, P. and Zhao, L. (2023). Marketing with chatgpt: Navigating the ethical terrain of gpt-based chatbot technology. AI, 4(2): 375-384. DOI: https://doi.org/10.3390/ai4020019
[42] Roggeveen, A.L. et al. (2021). Forging meaningful consumer-brand relationships through creative merchandise offerings and innovative merchandising strategies. Journal of Retailing, 97(1): 81-98. DOI:https://doi.org/10.1016/j.jretai.2020.11.006
[43] Rossmann, A., Zimmermann, A. and Hertweck, D. (2020). The impact of chatbots on customer service performance. In: Advances in Intelligent Systems and Computing. Springer, Singapore, pp. 237–243. DOI:https://doi.org/10.1007/978-3-030-51057-2_33
[44] Roy, S., Gupta, V. and Ray, S. (2023). Adoption of ai chat bot like chat gpt in higher education in India: a semi analysis approach. Economic environment, 130-149. DOI: https://doi.org/10.36683/2306-1758/2023-4-46/130-149
[45] Siregar, F. H., Hasmayni, B. and Lubis, A. H. (2023). The Analysis of Chat GPT Usage Impact on Learning Motivation among Scout Students. International Journal of Research and Review, 10(7): 632-638. DOI:https://doi.org/10.52403/ijrr.20230774
[46] Tebenkov, E. and Prokhorov, I. (2021). Machine learning algorithms for teaching AI chat bots. Procedia Computer Science, 190: 735-744. DOI: https://doi.org/10.1016/j.procs.2021.06.086
[47] Van Esch, P. and Stewart Black, J. (2021). Artificial intelligence (AI): revolutionizing digital marketing. Australasian Marketing Journal, 29(3): 199-203. DOI: https://doi.org/10.1177/18393349211037684
[48] Zhang, L. and Zhu, Y. (2020). Chatbot service quality, customer satisfaction, and loyalty: the moderating role of service type. J. Serv. Theor. Prac., 30(5): 646–663. DOI: https://doi.org/10.1108/JSTP-12-2019-0316
[49] Ziakis, C. and Vlachopoulou, M. (2023). Artificial intelligence in digital marketing: Insights from a comprehensive review. Information, 14(12), 664. DOI: https://doi.org/10.3390/info14120664
[50] Zielinski, C. et al. (2023). Chatbots, ChatGPT, and Scholarly Manuscripts-WAME Recommendations on ChatGPT and Chatbots in Relation to Scholarly Publications. Afro-Egypt. J. Infect. Endem. Dis, 13: 75–79. DOI: https://dx.doi.org/10.21608/aeji.2023.282
[51] https://www.intercom.com/learning-center/best-ai-chatbot
[2] Araujo, T. (2018). Living up to the chatbot hype: the influence of anthropomorphic de-sign cues and communicative agency framing on conversational agent and company perceptions. Comput. Hum. Behav., 85: 183–189. DOI: https://doi.org/10.1016/j. chb.2018.03.051
[3] Ashfaq, M., Yun, J., Yu, S. and Loureiro, S. M. C. I. (2020). Chatbot: Modeling the determinants of users’ satisfaction and continuance intention of AI-powered service agents. Telematics and Informatics, 54, 101473. DOI: https://doi.org/10.1016/j.tele.2020.101473
[4] Buhalis, D. and Karatay, N. (2022). Mixed reality (MR) for generation Z in cultural heritage tourism towards metaverse. In Information and Communication Technologies in Tourism 2022: Proceedings of the ENTER 2022 eTourism Conference, Springer International Publishing, 16-27. DOI: https://doi.org/10.1007/978-3-030-94751-4_2
[5] Buhalis, D., Leung, D. and Lin, M. (2023). Metaverse as a disruptive technology revolutionising tourism management and marketing. Tourism Management, 97, 104724. DOI: https://doi.org/10.1016/j.tourman.2023.104724
[6] Chen, Q., Yin, C. and Gong, Y. (2023). Would an AI chatbot persuade you: An empirical answer from the elaboration likelihood model. Information Technology and People. DOI: https://doi.org/10.1108/ITP-10-2021-0764
[7] Chen, Y. and Xie, J. (2008). Online consumer review: Word-of-mouth as a new element of marketing communication mix. Management science, 54(3): 477-491. DOI: http://dx.doi.org/10.5958/2249-877X.2021.00117.X
[8] Chiu, W., Cho, H. and Chi, C.G. (2021). Consumers’ continuance intention to use fitness and health apps: an integration of the expectation–confirmation model and investment model. Inf. Technol. People, 34 (3): 978–998. DOI: https://doi.org/10.1108/ITP-09-2019- 0463
[9] Chopra, S.S. (2020). Helping Entrepreneurs and Small Businesses Make the Digital Transformation. In The Evolution of Business in the Cyber Age. Apple Academic Press, 39-51.
[10] Davis, A. et al. (2009). Avatars, people, and virtual worlds: Foundations for research in metaverses. Journal of the Association for In-formation Systems, 10(2), 1.
[11] Denić, N., et al. (2018). A survey of internet marketing by small and medium-sized enterprises for placing wine on the market. Physica A: Statistical Mechanics and its Applications. DOI:https://doi.org/10.1016/j.physa.2018.04.095
[12] Dwivedi, Y. K. et al. (2017). “So what if ChatGPT wrote it?” Multidisciplinary perspectives on opportunities, challenges and implications of generative conversational AI for research, practice and policy. International Journal of Information Management, 2023, 71, 102642. DOI: https://doi.org/10.1016/j.ijinfomgt.2023.102642
[13] Dwivedi, Y.K. et al. (2021). Setting the Future of Digital and Social Media Marketing Research: Perspectives and Research Propositions. Int. J. Inf. Manag., 59. DOI:https://doi.org/10.1016/j.ijinfomgt.2020.102168
[14] Edwards, C., Edwards, A., Spence, P. R. and Shelton, A. K. (2014). Is that a bot running the social media feed? Testing the differences in perceptions of communication quality for a human agent and a bot agent on Twitter. Computers in Human Behavior, 33: 372-376. DOI: https://doi.org/10.1016/j.chb.2013.08.013
[15] Fu, C. J., et al. (2024). Balancing Satisfaction and Clarity: Enhancing User Information Satisfaction with AI-Powered ChatGPT in Higher Education. Preprints. DOI:https://doi.org/10.20944/preprints202402.0040.v1
[16] Goralski, M. A. and Tan, T. K. (2022). Artificial intelligence and poverty alleviation: Emerging innovations and their implications for management education and sustainable development. The International Journal of Management Education, 20(3). DOI: https://doi.org/10.1016/j.ijme.2022.100662
[17] Gordijn, B. and Have, H. T. (2023). ChatGPT: evolution or revolution? Medicine, Health Care and Philosophy, 26(1): 1-2. DOI: https://doi.org/10.1007/s11019-023-10136-0
[18] Guha, A. et al. (2021). How artificial intelligence will affect the future of retailing. Journal of Retailing, 97(1): 28-41. DOI: https://doi.org/10.1016/j.jretai.2021.01.005
[19] Hew, J. J., Lee, V. H., Ooi, K. B. and Lin, B. (2016). Mobile social commerce: The booster for brand loyalty? Computers in Human Behavior, 59: 142-154. DOI: https://doi.org/10.1016/j.chb.2016.01.027
[20] Jang, M., Jung, Y. and Kim, S. (2021). Investigating managers’ understanding of chatbots in the Korean financial industry. Computers in Human Behavior, 120, 106747. DOI:https://doi.org/10.1016/j.chb.2021.106747
[21] Johari, N.M., Zaman, H.B. and Nohuddin, P.N.E. (2019). Ascertain quality attributes for de-sign and development of new improved chatbots to assess customer satisfaction index (CSI): a preliminary study. In: Lecture Notes in Computer Science. Springer, Singapore, pp. 135–146. DOI: https://doi.org/10.1007/978-3-030-34032-2_13
[22] Kaur, P. et al. (2020). Why do people purchase virtual goods? A uses and gratification (UandG) theory perspective. Telemat. Inform., 53, 101376. DOI: https://doi.org/10.1016/j.tele.2020.101376
[23] Kim, B. (2010). An empirical investigation of mobile data service continuance: incorporating the theory of planned behavior into the expectation-confirmation model. Expert Syst. Appl, 37 (10): 7033–7039. DOI:https://doi.org/10.1016/j. eswa.2010.03.015
[24] Klang, E. and Levy-Mendelovich, S. (2023). Evaluation of OpenAI’s large language model as a new tool for writing papers in the field of thrombosis and hemostasis. Journal of Thrombosis and Haemostasis, 21(4): 1055-1058. DOI: https://doi.org/10.1016/j.jtha.2023.01.011
[25] Kumar, S. et al. (2024). Will artificial intelligence drive the advancements in higher education? A tri-phased exploration. Techno-logical Forecasting and Social Change, 201, 123258. DOI:https://doi.org/10.1016/j.techfore.2024.123258
[26] Lee, Y. and Kwon, O. (2011). Intimacy, familiarity and continuance intention: an extended expectation–confirmation model in web-based services. Electron. Commer. Res. Appl., 10 (3): 342–357. DOI:https://doi.org/10.1016/j.elerap.2010.11.005
[27] Li, L., Lee, K.Y., Emokpae, E. and Yang, S.B. (2021). What makes you continuously use chatbot services? Evidence from Chinese online travel agencies. Electronic Markets, 21(1): 1-25. DOI:https://doi.org/10.1007/s12525-020-00454-z
[28] Lim, W. M., Kumar, S., Verma, S. and Chaturvedi, R. (2022). Alexa, what do we know about conversational commerce? Insights from a systematic literature review. Psychology and Marketing, 39(6): 1129–1155. DOI:https://doi.org/10.1002/mar.21654
[29] Limayem, M. and Cheung, C. (2008). Understanding information systems continuance: the case of Internet-based learning technologies. Inf. Manag., 45 (4): 227–232. DOI: https://doi.org/10.1016/j.im.2008.02.005
[30] Lin, W.S. (2012). Perceived fit and satisfaction on web learning performance: IS continuance intention and task-technology fit perspectives. Int. J. Hum. Comput. Stud, 70 (7): 498–507. DOI:https://doi.org/10.1016/j.ijhcs.2012.01.006
[31] Liu, C. and Lee, C. (2020). Chatbots in marketing: overview, classification, and recommendations for future research, J. Bus. Res., 109: 340–351. DOI: https://doi.org/10.1016/j.jbusres.2019.11.019
[32] Lowry, P. B., Romano, N. C., Jenkins, J. L. and Guthrie, R. W. (2009). The CMC interactivity model: How interactivity enhances communication quality and process satisfaction in lean-media groups. Journal of Management Information Systems, 26(1): 155-196. DOI: https://doi.org/10.2753/MIS0742-1222260107
[33] Lu, C. C., Wu, L., and Hsiao, W. H. (2019). Developing customer product loyalty through mobile advertising: Affective and cognitive perspectives. International Journal of Information Management, 47: 101-111. DOI:https://doi.org/10.1016/j.ijinfomgt.2018.12.020
[34] Lundmark, P. (2022). The real future of the metaverse is not for consumers. Accessed at: https://www.ft.com/content/af0c9de8-d36e-485b-9db5-5ee1e57716cb
[35] Luo, M.M., Remus, W. and Chea, S. (2006). Technology Acceptance of Internet-based Information Services: An Integrated Model of TAM and UandG Theory. AMCIS (2006), 153.
[36] Mimoun, M. S. B., Poncin, I. and Garnier, M. (2017). Animated conversational agents and e-consumer productivity: The roles of agents and individual characteristics. Information and Management, 54(5): 545-559. DOI: https://doi.org/10.1016/j.im.2016.11.008
[37] Moy, C. and Gadgil, A. (2022). Opportunities in the metaverse. JP Morgan and chase. Available at: https://www.jpmorgan.com/content/dam/jpm/treasuryservices/documents/opportuni-ties-in-the-metaverse.pdf
[38] Nagy, S. and Hajdú, N. (2021). Consumer Acceptance of the Use of Artificial Intelligence in Online Shopping: Evidence from Hungary. Amfiteatru Economic, 23(56).
[39] Ramaul, L. (2021). Role of AI in marketing through CRM integration with specific reference to chatbots. Available at: http://urn.fi/URN:NBN:fi:jyu-202106143690
[40] Rese, A., Ganster, L. and Baier, D. (2020). Chatbots in retailers’ customer communication: How to measure their acceptance? J. Retail. Consum. Serv., 56, 102176. DOI:https://doi.org/10.1016/j.jretconser.2020.102176
[41] Rivas, P. and Zhao, L. (2023). Marketing with chatgpt: Navigating the ethical terrain of gpt-based chatbot technology. AI, 4(2): 375-384. DOI: https://doi.org/10.3390/ai4020019
[42] Roggeveen, A.L. et al. (2021). Forging meaningful consumer-brand relationships through creative merchandise offerings and innovative merchandising strategies. Journal of Retailing, 97(1): 81-98. DOI:https://doi.org/10.1016/j.jretai.2020.11.006
[43] Rossmann, A., Zimmermann, A. and Hertweck, D. (2020). The impact of chatbots on customer service performance. In: Advances in Intelligent Systems and Computing. Springer, Singapore, pp. 237–243. DOI:https://doi.org/10.1007/978-3-030-51057-2_33
[44] Roy, S., Gupta, V. and Ray, S. (2023). Adoption of ai chat bot like chat gpt in higher education in India: a semi analysis approach. Economic environment, 130-149. DOI: https://doi.org/10.36683/2306-1758/2023-4-46/130-149
[45] Siregar, F. H., Hasmayni, B. and Lubis, A. H. (2023). The Analysis of Chat GPT Usage Impact on Learning Motivation among Scout Students. International Journal of Research and Review, 10(7): 632-638. DOI:https://doi.org/10.52403/ijrr.20230774
[46] Tebenkov, E. and Prokhorov, I. (2021). Machine learning algorithms for teaching AI chat bots. Procedia Computer Science, 190: 735-744. DOI: https://doi.org/10.1016/j.procs.2021.06.086
[47] Van Esch, P. and Stewart Black, J. (2021). Artificial intelligence (AI): revolutionizing digital marketing. Australasian Marketing Journal, 29(3): 199-203. DOI: https://doi.org/10.1177/18393349211037684
[48] Zhang, L. and Zhu, Y. (2020). Chatbot service quality, customer satisfaction, and loyalty: the moderating role of service type. J. Serv. Theor. Prac., 30(5): 646–663. DOI: https://doi.org/10.1108/JSTP-12-2019-0316
[49] Ziakis, C. and Vlachopoulou, M. (2023). Artificial intelligence in digital marketing: Insights from a comprehensive review. Information, 14(12), 664. DOI: https://doi.org/10.3390/info14120664
[50] Zielinski, C. et al. (2023). Chatbots, ChatGPT, and Scholarly Manuscripts-WAME Recommendations on ChatGPT and Chatbots in Relation to Scholarly Publications. Afro-Egypt. J. Infect. Endem. Dis, 13: 75–79. DOI: https://dx.doi.org/10.21608/aeji.2023.282
[51] https://www.intercom.com/learning-center/best-ai-chatbot
Published
2024-09-30
How to Cite
PAVLOVIĆ, Nikola; SAVIĆ, Marko.
The Impact of the ChatGPT Platform on Consumer Experience in Digital Marketing and User Satisfaction.
Theoretical and Practical Research in Economic Fields, [S.l.], v. 15, n. 3, p. 636 - 646, sep. 2024.
ISSN 2068-7710.
Available at: <https://journals.aserspublishing.eu/tpref/article/view/8593>. Date accessed: 21 dec. 2024.
doi: https://doi.org/10.14505/tpref.v15.3(31).10.
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