The Darkside of Artificial Intelligence to Consumer Behavior: Bibliometric Review
DOI:
https://doi.org/10.38035/jafm.v5i6.1286Keywords:
Consumer Behavior, Artificial Intelligence, Darkside, Bibliometric, RstudioAbstract
Artificial Intelligence (AI) is a technology that continues to be developed today. Providing a positive impact on life in facilitating human work, unfortunately AI also has a bad side that causes anxiety. The purpose of this research is to explain the negative impacts associated with AI in the world of business management. This research is expected to provide an understanding of the dark side of AI on consumer behavior and its implications through a systematic literature review and in-depth content analysis. The data used in this study were taken from Scopus and Web of Science using bibliometric methods. Using the help of RStudio and biblioshiny applications to manage data. The results showed that there is a significant correlation between the negative impact of Artificial Intelligence (AI) on consumer behavior, where the negative impact of AI significantly affects consumer behavior. This study provides important new knowledge for researchers and the public who seek information about the relationship between the negative impact of AI and consumer behavior.
References
A. Garofalo et al. (2022). Darkside: 2.6GFLOPS, 8.7mW Heterogeneous RISC-V Cluster for Extreme-Edge On-Chip DNN Inference and Training,. ESSCIRC 2022- IEEE 48th European Solid State Circuits Conference (ESSCIRC), 273–276.
Agrawal, A. K., Gans, J. S., & Goldfarb, A. (2018). Economic Policy for Artificial Intelligence. http://www.nber.org/papers/w24690
Alawadh, M., & Barnawi, A. (2024). A Consumer Behavior Analysis Framework toward Improving Market Performance Indicators: Saudi’s Retail Sector as a Case Study. Journal of Theoretical and Applied Electronic Commerce Research, 19(1), 152–171. https://doi.org/10.3390/jtaer19010009
Aldoseri, A., Al-Khalifa, K. N., & Hamouda, A. M. (2023). Re-Thinking Data Strategy and Integration for Artificial Intelligence: Concepts, Opportunities, and Challenges. In Applied Sciences (Switzerland) (Vol. 13, Issue 12). MDPI. https://doi.org/10.3390/app13127082
Ameen, N., Tarhini, A., Reppel, A., & Anand, A. (2021). Customer experiences in the age of artificial intelligence. Journal of Computers in Human Behavior, 114. https://doi.org/10.1016/j.chb.2020.106548
Baber, R., Upadhyay, Y., Baber, P., & Kaurav, R. P. S. (2023). Three Decades of Consumer Ethnocentrism Research: A Bibliometric Analysis . Business Perspectives and Research, 11(1), 37-158.
Belanche, D., Belk, R. W., Casaló, L. V., & Flavián, C. (2024). The dark side of artificial intelligence in services. Service Industries Journal, 44(3–4), 149–172. https://doi.org/10.1080/02642069.2024.2305451
Bhukya, R., & Paul, J. (2023). Social influence research in consumer behavior: What we learned and what we need to learn? – A hybrid systematic literature review. Journal of Business Research, 162. https://doi.org/10.1016/j.jbusres.2023.113870
Bilas Roy, S., & Basak, M. (2013). Journal of Documentation?: a Bibliometric Study. https://digitalcommons.unl.edu/libphilprac
Braun, M., de Langhe, B., Puntoni, S., & Schwartz, E. M. (2024). Leveraging Digital Advertising Platforms for Consumer Research. Journal of Consumer Research, 51(1), 119–128. https://doi.org/10.1093/jcr/ucad058
Chen, S., Qiu, H., Zhao, S., Han, Y., He, W., Siponen, M., Mou, J., & Xiao, H. (2022). When more is less: The other side of artificial intelligence recommendation. Journal of Management Science and Engineering, 7(2), 213–232. https://doi.org/10.1016/j.jmse.2021.08.001
Du, S., & Xie, C. (2021). Paradoxes of artificial intelligence in consumer markets: Ethical challenges and opportunities. Journal of Business Research, 129, 961–974. https://doi.org/10.1016/j.jbusres.2020.08.024
Durmaz, Y., & Yusuf Kilic, Y. (2023). A Theoretical Approach to Artificial Intelligence in Consumer Behavior. International Business & Economics Studies, 5(2), p52. https://doi.org/10.22158/ibes.v5n2p52
Gerlich, M. (2023). The Power of Virtual Influencers: Impact on Consumer Behaviour and Attitudes in the Age of AI. Journal of Administrative Sciences, 13(8). https://doi.org/10.3390/admsci13080178
Global Development Lab, U. (n.d.). Reflecting the Past, Shaping the Future: Making AI Work for International Development.
Khan, S. I. (2022). Impact of artificial intelligence on consumer buying behaviors. International Journal of Health Sciences, 8121–8129. https://doi.org/10.53730/ijhs.v6ns2.7025
Krippendorff, K. (2019). Content Analysis: An Introduction to Its Methodology (Fourth Edition). SAGE Publications, Inc.
Lages, C. R., Perez-Vega, R., Kadi?-Maglajli?, S., & Borghei-Razavi, N. (2023). A systematic review and bibliometric analysis of the dark side of customer behavior: An integrative customer incivility framework. Journal of Business Research, 161. https://doi.org/10.1016/j.jbusres.2023.113779
Lévesque, M., Obschonka, M., & Nambisan, S. (2022). Pursuing Impactful Entrepreneurship Research Using Artificial Intelligence (Vol. 46, Issue 4).
Marie-Sophie, Schönitz. (2021). The Dark Side of the Halo – Implications of the Horn Effect for the Management of Business-to-Customer Relationships in the Context of Artificial Intelligence. In Künstliche Intelligenz im Dienstleistungsmanagement (pp. 471-494.). Springer Link.
Mikalef, P., Conboy, K., Lundström, J. E., & Popovi?, A. (2022). Thinking responsibly about responsible AI and ‘the dark side’ of AI. In European Journal of Information Systems (Vol. 31, Issue 3, pp. 257–268). Taylor and Francis Ltd. https://doi.org/10.1080/0960085X.2022.2026621
Oli?ski, M., Krukowski, K., & Sieci?ski, K. (2024). Bibliometric Overview of ChatGPT: New Perspectives in Social Sciences. Publications, 12(1). https://doi.org/10.3390/publications12010009
Rana J, Jain R, & Santosh K. (2023). Automation and AI-Enabled Customer Journey: A Bibliometric Analysis. Vision: The Journal of Business Perspective.
Saxena, A., Bajpai, Y., & Kumar, R. (2022). Dark Side of Artificial Intelligence. International Journal for Research in Applied Science and Engineering Technology, 10(2), 325–327. https://doi.org/10.22214/ijraset.2022.40256
Schultz, C. D., Koch, C., & Olbrich, R. (2024). Dark sides of artificial intelligence: The dangers of automated decision-making in search engine advertising. Journal of the Association for Information Science and Technology, 75(5), 550–566. https://doi.org/10.1002/asi.24798
Sun, Y., Li, S., & Yu, L. (2022). The dark sides of AI personal assistant: effects of service failure on user continuance intention. Electronic Markets, 32(1), 17–39. https://doi.org/10.1007/s12525-021-00483-2
Trivedi Shekar. (2023, June 7). The Dark Side of AI: How Artificial Intelligence can impact Business. Dr. Gaur Hari Singhania Institute of Management & Research (GHS-IMR).
Wach, K., Duong, C. D., Ejdys, J., Kazlauskait?, R., Korzynski, P., Mazurek, G., Paliszkiewicz, J., & Ziemba, E. (2023). The dark side of generative artificial intelligence: A critical analysis of controversies and risks of ChatGPT. Entrepreneurial Business and Economics Review, 11(2), 7-30.
Wang, K., Lu, L., Fang, J., Xing, Y., Tong, Z., & Wang, L. (2023). The downside of artificial intelligence (AI) in green choices: How AI recommender systems decrease green consumption. Managerial & Decision Economics, 44(6), 3346. – 3353.
Xing, Y., Yu, L., Zhang, J. Z., & Zheng, L. J. (2023). Uncovering the Dark Side of Artificial Intelligence in Electronic Markets: A Systematic Literature Review. Journal of Organizational and End User Computing, 35(1). https://doi.org/10.4018/JOEUC.327278
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2025 Sintara Qanita Putri Muslik, Berto Mulia Wibawa, Agus Windharto
This work is licensed under a Creative Commons Attribution 4.0 International License.
Authors who publish their manuscripts in this journal agree to the following conditions:
- The copyright on each article belongs to the author(s).
- The author acknowledges that the Journal of Accounting and Finance Management (JAFM) has the right to be the first to publish with a Creative Commons Attribution 4.0 International license (Attribution 4.0 International (CC BY 4.0).
- Authors can submit articles separately, arrange for the non-exclusive distribution of manuscripts that have been published in this journal into other versions (e.g., sent to the author's institutional repository, publication into books, etc.), by acknowledging that the manuscript has been published for the first time in the Journal of Accounting and Finance Management (JAFM).
