Intelligent Management of Human Capital

Intelligent Management of Human Capital

Examining the dynamics of the role of artificial intelligence in marketing strategies with a focus on ethical and cultural issues and their impact on consumer behavior

Document Type : Original Article

Authors
1 Associate Prof, Department of Management, Faculty of Social Sciences and Economics, Alzahra University, Tehran, Iran.
2 Master of Business Management. Department of Management, Faculty of Social Sciences and Economics, Alzahra University, Tehran, Iran.
Abstract
Background and Objective: This study aimed to Examining the dynamics of the role of artificial intelligence in marketing strategies with a focus on ethical and cultural issues such as privacy of data, algorithmic fanaticism, etc. and its effect on consumer behavior.
Methodology: This applied research was conducted using a qualitative approach. In this research, the concepts of artificial intelligence, marketing strategy and consumer behavior, and the relationship between artificial intelligence and ethics, culture and consumer behavior were investigated through the dynamic system method, and the connections.
Findings: Artificial intelligence, marketing strategies, consumer behavior, cultural challenges and issues, and ethical issues are the five main concepts of this research, which were identified by extracting and examining the variables that influence each relationship and their implications. AI-powered personalization involves the collection and analysis of customer data, so the lack of legal and compliance frameworks in this area raises privacy concerns, which negatively impacts consumer behavior. Cultural aspects include customs, traditions and social norms, which in turn affect the use of AI in this society and among consumers.
Conclusion:The use of artificial intelligence introduces inconsistencies into the culture of society and creates ethical concerns such as data protection, skills shortages and implementation difficulties, problems arising from the lack of legal frameworks and the digital divide. To reduce the negative effects of AI, solutions such as creating ethical frameworks for AI development, applied laws, the creation of regulatory and development institutions with respect for cultures have been proposed.
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Akter, S., McCarthy, G., Sajib, S., Michael, K., Dwivedi, Y. K., D’Ambra, J., & Shen, K. N. (2021). Algorithmic bias in data-driven innovation in the age of AI. International Journal of Information Management, 60, 102387.‏ https://doi.org/10.1016/j.ijinfomgt.2021.102387
Biswas, K., & Patrab, G. (2023). Role of Artificial Intelligence (AI) in Changing Consumer Buying Behaviour. Int. J. Res. Publ. Rev., 4(02), 943-951.  https://doi.org/10.55248/gengpi.2023.4227
Bouhouita-Guermech, S., Gogognon, P., & Bélisle-Pipon, J.-C. (2023). Specific challenges posed by artificial intelligence in research ethics. Frontiers in artificial intelligence, 6, 1149082            https://doi.org/10.3389/frai.2023.1149082  .  
Canbul Yaroğlu, A. (2024). The effects of artificial intelligence on organizational culture in the perspective of the hermeneutic cycle: The intersection of mental processes. Systems Research and Behavioral Science.  https://doi.org/10.1002/sres.3037
Devi, M. H., & Uniyal, A. K. (2024). Artificial intelligence in marketing: enhancing customer engagement and business performance. Journal of Research Administration, 6(1).
Di Vaio, A., Hassan, R., & Alavoine, C. (2022). Data intelligence and analytics: A bibliometric analysis of human–Artificial intelligence in public sector decision-making effectiveness. Technological Forecasting and Social Change, 174, 121201 . https://doi.org/10.1016/j.techfore.2021.121201
Gkikas, D. C., & Theodoridis, P. K. (2022). AI in consumer behavior. Advances in Artificial Intelligence-based Technologies: Selected Papers in Honour of Professor Nikolaos G. Bourbakis—Vol. 1, 147-176.  http:// doi.org/10.1007/978-3-030-80571-5_10.
Golshahi, Behnam, and Mortezadeh, Alireza. (1403). Scenario-building of risks of the development of artificial intelligence in human capital management processes. Intelligent human capital management.1(1):29-60. https://doi.org/10.22034/imhr.2024.480339.1011. [in persion]
Hadi Peykani, Mehraban, and Ostadi, Majid. (1403). Knowledge-based human resource development strategies for sustainable management. Intelligent Human Capital Management. 1(1):143-172. https://doi.org/10.22034/imhr.2025.494947.1018 [in persion]
 
Hajigholam Sarizadi, Ali, and Moteghi, Manouchehr. (2018). Testing and Validation of Group Modeling Method with Reference Model. Quarterly Journal of Strategic Management in Industrial Systems (formerly Industrial Management). 13(44): 29-46. [in persion]
Haji Gholam Sarizadi, Ali; Rajabzadeh Qatari, Ali; Mashayekhi, Ali Naghi; and Hassanzadeh, Alireza. (2019). Designing a Dynamic Model of Crowdfunding System in Iran. Modern Research in Decision Making. 5(2): 49-80. https://dor.isc.ac/dor/20.1001.1.24766291.1399.5.2.3.6 [in persion]
Hermansyah, M., Najib, A., Farida, A., Sacipto, R., & Rintyarna, B. S. (2023). Artificial intelligence and ethics: Building an artificial intelligence system that ensures privacy and social justice. International Journal of Science and Society, 5(1), 154-168.  http:// doi.org/10.54783/ijsoc.v5i1.644
Jahanfar, Hamed. (1400). Artificial Intelligence in Marketing: A Systematic Review and Future Research Directions. Intelligent Marketing Management.2(4): 1-14. https://doi.org/JABM.3.2.15564.358878.367908 [in persion]
Jain, V., Wadhwani, K., & Eastman, J. K. (2024). Artificial intelligence consumer behavior: A hybrid review and research agenda. Journal of Consumer Behaviour, 23(2), 676-697.  https://doi.org/10.1002/cb.2233
Jarek, K., & Mazurek, G. (2019). Marketing and artificial intelligence. Central European Business Review, 8(2).‏ http:// doi.org/10.18267/j.cebr.213
Labib, E. (2024). Artificial intelligence in marketing: exploring current and future trends. Cogent Business & Management, 11(1), 2348728. https://doi.org/10.1080/23311975.2024.2348728
Maghsudi, S., Lan, A., Xu, J., & van Der Schaar, M. (2021). Personalized education in the artificial intelligence era: what to expect next. IEEE Signal ProcessingMagazine, 38(3), 37-50.  https://doi.org/10.1109/MSP.2021.3055032
Mohajer, Seyyed Mohammad. (1402). The role of artificial intelligence in marketing and business. Brand Afarin scientific-specialized monthly magazine. 4(41). [in persion]
Morgan, N. A., Whitler, K. A., Feng, H., & Chari, S. (2019). Research in marketing strategy. Journal of the Academy of Marketing Science, 47, 4-29.‏ http:// doi.org/10.1007/s11747-018-0598-1
Najafi, Alireza; Noormohammad Nasrabadi, Gholamreza; and Mohammadzadeh, Soheila. (2014). The role of artificial intelligence in marketing policies and market management. Quarterly Journal of Standard and Quality Management. 14(1): 1-19. http:// doi.org/10.22034/jsqm.2024.451996.1575 [in persion]
Nikabadi, M. S., Hakaki, A., & Gholamshahi, S. (2020). Dynamic Model for Evaluating Information Systems Security by System Dynamics Modeling. Roshd -e- Fanavari, 64(16), 52-61.  https://doi.org/10.52547/jstpi.20820.16.64.52
Parsa, Ali. (1403). The role of artificial intelligence in marketing activities, Brand Afarin Scientific-Specialized Monthly Magazine. 4 (38).[in persion]
Perez-Vega, R., Kaartemo, V., Lages, C. R., Razavi, N. B., & Männistö, J. (2021). Reshaping the contexts of online customer engagement behavior via artificial intelligence: A conceptual framework. Journal of Business Research, 129, 902-910.  https://doi.org/10.1016/j.jbusres.2020.11.002
Potwora, M., Vdovichena, O., Semchuk, D., Lipych, L., & Saienko, V. (2024). The use of artificial intelligence in marketing strategies: Automation, personalization and forecasting. Journal of Management World, 2, 41-49.‏ https://doi.org/10.53935/jomw.v2024i2.275
Prabhakaran, V., Qadri, R., & Hutchinson, B. (2022). Cultural incongruencies in artificial intelligence. arXiv preprint arXiv:2211.13069.  https://doi.org/10.48550/arXiv.2211.13069
Putri, A., & Tran, M. Q. (2023). Global Perspectives on AI Deployment: Cultural, Ethical, and Operational Dimensions. Journal of Computational SocialDynamics, 8(11), 26-33.  https://vectoral.org/index.php/JCSD/article/view/87
Raji, M. A., Olodo, H. B., Oke, T. T., Addy, W. A., Ofodile, O. C., & Oyewole, A. T. (2024). E-commerce and consumer behavior: A review of AI-powered personalization and market trends. GSC Advanced Research and Reviews, 18(3), 066-077.  https://doi.org/10.30574/gscarr.2024.18.3.0090
Roche, C., Wall, P., & Lewis, D. (2023). Ethics and diversity in artificial intelligence policies, strategies and initiatives. AI and Ethics, 3(4), 1095-1115.  https://doi.org/10.1007/s43681-022-00218-9
Rosário, A., & Raimundo, R. (2021). Consumer marketing strategy and E-commerce in the last decade: a literature review. Journal of theoretical and applied electronic commerce research, 16(7), 3003-3024.  https://doi.org/10.3390/jtaer16070164
Sozuer, S., Carpenter, G. S., Kopalle, P. K., McAlister, L. M., & Lehmann, D. R. (2020). The past, present, and future of marketing strategy. Marketing Letters, 31, 163-174.‏ https://link.springer.com/article/10.1007/s11002-020-09529-5
Umamaheswari, D. D. (2024). Role of Artificial Intelligence in Marketing Strategies and Performance. Migration Letters, 21(S4), 1589-1599.  https://migrationletters.com/index.php/ml/article/view/7579
Venkatachalam, P., & Ray, S. (2022). How do context-aware artificial intelligence algorithms used in fitness recommender systems? A literature review and research agenda. International Journal of Information Management Data Insights, 2(2), 100139.  https://doi.org/10.1016/j.jjimei.2022.100139
Vidhya, V., Donthu, S., Veeran, L., Lakshmi, Y. S., & Yadav, B. (2023). The intersection of AI and consumer behavior: Predictive models in modern marketing. Remittances Review, 8(4).  http:// doi.org/10.33182/rr.v8i4.166
Wei, L., & Xia, Z. (2022). Big Data-Driven Personalization in E-Commerce: Algorithms, Privacy Concerns, and Consumer Behavior Implications. International Journal of Applied Machine Learning and Computational Intelligence, 12(4) .https://neuralslate.com/index.php/Machine-Learning-Computational-I/article/view/47
Wu, C., Xu, H., Bai, D., Chen, X., Gao, J., & Jiang, X. (2023). Public perceptions on the application of artificial intelligence in healthcare: a qualitative meta-synthesis. BMJ open, 13(1), e066322. http:// doi.org/10.1136/bmjopen-2022-066322
Zulaikha, S., Mohamed, H., Kurniawati, M., Rusgianto, S., & Rusmita, S. A. (2020). Customer predictive analytics using artificial intelligence. The Singapore Economic Review, 1-12. http:// doi.org/10.1142/S0217590820480021.