Designing the cognitive bias pattern for insurance industry marketing managers through digitization.
Subject Areas : marketing
Seyed Fakhredin Alavi
1
,
Farid Asgari
2
*
,
Behzad Shahrabi
3
,
Babak Haj Karimi
4
1 - Department of Management, Abhar Branch, Islamic Azad University, Abhar, Iran
2 - Department of Management, Abhar Branch, Islamic Azad University, Abhar, Iran
3 - Assistant Prof., Department of Management, Aliabad Katoul Branch, Islamic Azad University, AliAbad Katoul, Iran
4 - Assistant Professor, Department of Industrial Management, Azad University, Qazvin, Iran
Keywords: cognitive bias pattern, marketing managers, insurance industry, digitalization,
Abstract :
The purpose of this study was to design a cognitive bias pattern of insurance industry marketing managers through digitalization.This study is qualitative and is based on the grounded theory. The participants include members of the business management faculty, as well as assistant managers and marketing experts of the insurance industry in Golestan province (20 people were selected by snowball method).Data was collected through in-depth interviews, and theoretical saturation was achieved in the 17th interview. The text of the interviews was analyzed through three stages of open, axial and selective coding.To check the validity of the findings, long-term engagement measures, continuous observation,review by the participants and triangulation technique were carried out.Transferability, reliability criteria and verifiability were used to check the reliability of the study.Findings indicated that causing factors are improving risk assessment tools, investor psychology, customer behavior and motivations, human risk management, improving the quality of machine learning models, artificial intelligence and human behavior and consumer behavior. Optimization factors of organizational processes, data mining management and organizational dependencies were identified as underlying factors and behavioral challenges of managers and incompatible behaviors in the insurance industry were recognized as intervening factors.Intelligent management approaches, customer relationship management in insurance sector, artificial intelligence-based decision-making strategies can be considered to prevent the cognitive bias of insurance industry marketing managers.Strategic management of the insurance company performance, working intelligence on control and strategic actions in the insurance industry as consequences of the cognitive bias pattern of insurance industry marketing managers was identified through digitization.
احمدیان، محمد و جهانی، حوریه، (1399)، سوگیری‌های شناختی و ویژگی‌های شخصیتی، نخستین همایش ملی رویکردهای نوین مدیریت در مطالعات میان رشته‌ای، گنبد کاووس باباجانی محمدی، سعیده، مرتضوی، سعید، مهارتی، یعقوب، تهرانی، رضا. (1396). شناسایی عمده‌ترین سوگیری‌های سرمایه گذاران در بازار سرمایه ایران با استفاده از روش فراتحلیل، فصلنامه علوم مدیریت ایران، سال دوازدهم، شماره (45)، ص 113-81.
بشیری منش، نازنین، حاجی زاده، زهرا، قبادی، سعید. (1401). تأثیر سوگیری رفتاری مدیران بر تصمیم گیری و کیفیت اطلاعات مالی. پژوهش‌های تجربی حسابداری، 12(1)، 141-160. بیرامی، منصور، پورمحمدی، مرتضی، خرازی نوتاش، هانیه، احمدی، لیلا (1393). سوگیری شناختی پردازش اطلاعات هیجانی در افراد مضطرب، افسرده، بهنجار، فصلنامه روانشناسی شناختی، شماره (4)، ص 60-51.
درویشی، میلاد؛ ساعی، محمدجواد؛ کاردان، بهزاد (1398). بررسی عوامل مؤثر بر سوگیری بودجه‌ای مدیران، مجله پیشرفت‌های حسابداری، 11(2)، 117-150. نوری، پوریا و احمدی کافشانی، عبداله، (1397)، واکاوی مهمترین سوگیری‌های شناختی در تصمیم‌های کارآفرینان، دومین کنفرانس ملی کارآفرینی دانشگاه صنعتی شریف، تهران.
Acciarini, C., Brunetta, F. and Boccardelli, P. (2021), "Cognitive biases and decision-making strategies in times of change: a systematic literature review",
Management Decision, Vol. 59 No. 3, pp. 638-652. Athota, V. S. (2021). Mind over Matter and Artificial Intelligence: Building employee mental fitness for organisational success. Palgrave Macmillan. Athota, V. S., Pereira, V., Hasan, Z., Vaz, D., Laker, B., & Reppas, D. (2023). Overcoming financial planners’ cognitive biases through digitalization: A
qualitative study. Journal of Business Research, 154, 113291. doi:https://doi.org/10.1016/j.jbusres.2022.08.055 Baker, H. K., & Puttonen, V. (2017). Investment Traps Exposed: Navigating Investor Mistakes and Behavioral Biases. Bingley, UK: Emerald Publishing
limited. Berthet V (2022) The Impact of Cognitive Biases on Professionals’ Decision-Making: A Review of Four Occupational Areas. Front. Psychol. 12:802439. doi:
10.3389/fpsyg.2021.802439 Callaway, F., Jain, Y. R., van Opheusden, B., Das, P., Iwama, G., Gul, S., & Lieder, F. (2022). Leveraging artificial intelligence to improve people’s planning
strategies. Proceedings of the National Academy of Sciences, 119(12), 1–11. Caputo, F., Cillo, V., Candelo, E., & Liu, Y. (2019). Innovating through digital revolution: The role of soft skills and Big Data in increasing firm performance.
Management Decision., 57(8), 2032–2051. Carpena, F., Cole, S., Shapiro, J., & Zia, B. (2019). The ABCs of financial education: Experimental evidence on attitudes, behavior, and cognitive biases.
Management Science, 65(1), 346–369. Di Vaio, A., Palladino, R., Hassan, R., & Escobar, O. (2020). Artificial intelligence and business models in the sustainable development goals perspective:
A systematic literature review. Journal of Business Research, 121, 283–314.
Ehrlinger, J., Readinger, W. O., & Kim, B. (2016). Decision-making and cognitive biases. Encyclopedia of mental health, 12, 1–20. Harris, C. G. (2020). Mitigating Cognitive Biases in Machine Learning Algorithms for Decision Making. In In Companion Proceedings of the Web
Conference, pp. 775–781.
Jones, E. B., & Sharpe, L. (2017). Cognitive bias modification: A review of meta-analyses. Journal of affective disorders, 223, 175-183. Kaplan, A., & Haenlein, M. (2019). Siri, Siri, in my hand: Who’s the fairest in the land? On the interpretations, illustrations, and implications of artificial
intelligence. Business Horizons, 62(1), 15–25. Lee J, Hamilton JT (2022) Anchoring in the past, tweeting from the present: Cognitive bias in journalists’ word choices. PLoS ONE 17(3): e0263730.
https://doi.org/10.1371/journal.pone.0263730 Mercier, H. (2017). Confirmation bias—Myside bias. In R. F. Pohl (Ed.), Cognitive illusions: Intriguing phenomena in thinking, judgment and memory (pp. 99–114). Routledge/Taylor & Francis Group
. Murata, A. (2019). Cross-cultural difference and cognitive biases as causes of gap of mindset toward safety between approach based on hazard detection and that based on firm safety confirmation. In J. I. Kantola, S. Nazir, & T. Barath (Eds.), Advances in Human Factors, Business Management and Society - Proceedings of the AHFE 2018 International Conference on Human Factors, Business Management and Society, (pp. 582-596). (Advances in
Intelligent Systems and Computing; Vol. 783). Oschinsky, F. M., Stelter, A., & Niehaves, B. (2021). Cognitive biases in the digital age – How resolving the status quo bias enables public-sector
employees to overcome restraint. Government Information Quarterly, 38(4), 101611. doi:https://doi.org/10.1016/j.giq.2021.101611 Platt, B., Waters, A. M., Schulte-Koerne, G., Engelmann, L., & Salemink, E. (2017). A review of cognitive biases in youth depression: attention,
interpretation and memory. Cognition and Emotion, 31(3), 462-483. Rastogi, C., Zhang, Y., Wei, D., Varshney, K. R., Dhurandhar, A., & Tomsett, R. (2020). Deciding Fast and Slow: The Role of Cognitive Biases in AI-assisted
Decision-making. 1-22. arXiv preprint arXiv:2010.07938. Tabrizi, B., Lam, E., Girard, K., & Irvin, V. (2019). Digital transformation is not about technology. Harvard business review, 13(March), 1–6. Thomas, O. (2018) Two decades of cognitive bias research in entrepreneurship: What do we know and where do we go from here?. Manag Rev Q 68,
107–143 (2018). https://doi.org/10.1007/s11301-018-0135-9 Xiong, W., Fan, H., Ma, L., & Wang, C. (2022). Challenges of human—machine collaboration in risky decision-making. Frontiers of Engineering
Management, 9(1), 89–103.