The association between cognitive biases and the quality of strategic decision making: Evidence from Jordanian banks
-
DOIhttp://dx.doi.org/10.21511/bbs.16(2).2021.01
-
Article InfoVolume 16 2021 , Issue #2, pp. 1-11
- Cited by
- 950 Views
-
363 Downloads
This work is licensed under a
Creative Commons Attribution 4.0 International License
Excellence in strategic decision making is the driving force behind successful strategy adoption and implementation. However, it is becoming more and more complex as businesses emerge in unpredictable environments and conditions. The main objective of this study is to investigate the impact of cognitive bias and its dimensions (the illusion of control, prior hypothesis bias, escalating commitment bias and representativeness, and availability bias) on strategic decision making. In terms of methodology, the study used a random sampling technique. The study applied a survey as a research tool distributed among 138 bankers (employees at the managerial level) in managerial and administrative positions.
Further, descriptive analysis and regression analysis were used to analyze the data and test hypotheses. The results show a positive and significant effect of the illusion of control and representativeness. The results show that the illusion of control, prior hypothesis bias, escalating commitment bias and representativeness, and availability bias significantly impact the strategic decision-making in Jordanian banks. It is concluded that the null hypothesis will be accepted and, therefore, the alternative hypothesis will be rejected based on the significant levels for the primary and secondary hypotheses.
The factors of the escalating commitment bias, the availability bias, and the reasoning by analogy were not significant. Finally, the study recommends developing more literature on integrating psychology and discrimination and applying the research to different industries and managerial levels.
- Keywords
-
JEL Classification (Paper profile tab)L10, M10, M14
-
References38
-
Tables8
-
Figures1
-
- Figure 1. Study model
-
- Table 1. Descriptive statistics – demographics
- Table 2. Mean and standard deviation values
- Table 3. Regression analysis for H01
- Table 4. Regression analysis for H01-1
- Table 5. Regression analysis for H01-2
- Table 6. Regression analysis for H01-3
- Table 7. Regression analysis for H01-4
- Table 8. Regression analysis for H01-5
-
- AlKhars, M., Evangelopoulos, N., Pavur, R., & Kulkarni, S. (2019). Cognitive biases resulting from the representativeness heuristic in operations management: An experimental investigation. Psychology Research and Behavior Management, 12, 263-276.
- Anderson, J. C., & Gerbing, D. W. (1984). The Effect of Sampling Error on Convergence, Improper Solutions, and Goodness-of-Fit Indices for Maximum Likelihood Confirmatory Factor Analysis. Psychometrika, 49, 155-173.
- Bakar, S., & Yi, A. N. C. (2016). The impact of psychological factors on investors’ decision making in the Malaysian stock market: a case of Klang Valley and Pahang. Procedia Economics and Finance, 35, 319-328.
- Bandura, A. (1977). Self-efficacy: toward a unifying theory of behavioral change. Psychological Review, 84(2), 191215.
- Bandura, A. (1982). Self-efficacy mechanism in human agency. American Psychologist, 37(2), 122-147.
- Barnes Jr, J. H. (1984). Cognitive biases and their impact on strategic planning. Strategic Management Journal, 5(2), 129-137.
- Bartha, P. (2013). Analogy and analogical reasoning. Stanford Encyclopedia of Philosophy.
- Bonn, I., & Fisher, J. (2011). Sustainability: the missing ingredient in strategy. Journal of Business Strategy, 32(1), 5-14.
- Busenitz, L. W., & Barney, J. B. (1997). Differences between entrepreneurs and managers in large organizations: Biases and heuristics in strategic decision-making. Journal of Business Venturing, 12(1), 9-30.
- Chung, E., & McLarney, C. (1999). When giants collide: strategic analysis and application. Management Decision, 37(3), 233-248.
- Corder, G. W., & Foreman, D. I. (2009). Non-parametric Statistics for Non-Statisticians: A Step-by-Step Approach. John Wiley & Sons.
- Das, T. K., & Teng, B. S. (1999). Cognitive biases and strategic decision processes: An integrative perspective. Journal of Management Studies, 36(6), 757-778.
- Dube-Rioux, L., & Russo, J. E. (1988). An availability bias in professional judgment. Journal of Behavioral Decision Making, 1(4), 223-237.
- Gigerenzer, G., & Goldstein, D. G. (1996). Reasoning the fast and frugal way: models of bounded rationality. Psychological Review, 103(4), 650-669.
- Hill, C. W., Jones, G. R., & Schilling, M. A. (2014). Strategic management: Theory & cases: An integrated approach. Cengage Learning.
- Knight, P. A., & Nadel, J. I. (1986). Humility revisited: Self-esteem, information search, and policy consistency. Organizational Behavior and Human Decision Processes, 38(2), 196-206.
- Kyriazos, T. A. (2018). Applied psychometrics: sample size and sample power considerations in factor analysis (EFA, CFA) and SEM in general. Psychology, 9(8), 2207-2230.
- Levine, M. (1971). Hypothesis theory and nonlearning despite ideal S-R-reinforcement contingencies. Psychological Review, 78(2), 130-140.
- Markovitch, D. G., Huang, D., Peters, L., Phani, B. V., Philip, D., & Tracy, W. (2014). Escalation of commitment in entrepreneurship-minded groups. International Journal of Entrepreneurial Behavior & Research, 20(4), 302-323.
- Meissner, P., & Wulf, T. (2017). The effect of cognitive diversity on the illusion of control bias in strategic decisions: An experimental investigation. European Management Journal, 35(4), 430-439.
- Miller, D. (1990). The Icarus Paradox. HarperCollins, New York, NY.
- Mintzberg, H. (1973). Strategy-making in three modes. California Management Review, 16(2), 44-53.
- Montibeller, G., & Von Winterfeldt, D. (2015). Cognitive and motivational biases in decision and risk analysis. Risk Analysis, 35(7), 1230-1251.
- Murata, A., Nakamura, T., & Karwowski, W. (2015). Influence of cognitive biases in distorting decision making and leading to critical unfavorable incidents. Safety, 1(1), 44-58.
- Nooraie, M. (2012). Factors influencing strategic decision-making processes. International Journal of Academic Research in Business and Social Sciences, 2(7), 405-429.
- Nouri, P., Imanipour, N., Talebi, K., & Zali, M. (2018). Most common heuristics and biases in nascent entrepreneurs’ marketing behavior. Journal of Small Business & Entrepreneurship, 30(6), 451-472.
- Quinn, J. B. (1978). Strategic change: logical incrementalism. Sloan Management Review, 20(1), 7-21.
- Schwarz, N., Bless, H., Strack, F., Klumpp, G., Rittenauer-Schatka, H., & Simons, A. (1991). Ease of retrieval as information: another look at the availability heuristic. Journal of Personality and Social Psychology, 61(2), 195-202.
- Schwenk, C. R. (1984). Cognitive simplification processes in strategic decision-making. Strategic Management Journal, 5(2), 111-128.
- Schwenk, C. R. (1988). The cognitive perspective on strategic decision making. Journal of Management Studies, 25(1), 41-55.
- Seppälä, A. (2009). Behavioral biases of investment advisors-The effect of overconfidence and hindsight bias (Master’s Thesis).
- Sharma, R., Mithas, S., & Kankanhalli, A. (2014). Transforming decision-making processes: a research agenda for understanding the impact of business analytics on organizations. European Journal of Information Systems, 23(4), 433-441.
- Staw, B. M. (1981). The escalation of commitment to a course of action. Academy of Management Review, 6(4), 577-587.
- Tversky, A., & Kahneman, D. (1974). Judgment under uncertainty: Heuristics and biases. Science, 185(4157), 1124-1131.
- Wheelen, T. L., Hunger, J. D., Hoffman, A. N., & Bamford, C. E. (2010). Strategic management and business policy. Upper Saddle River, NJ: Prentice Hall.
- Whyte, G., Saks, A. M., & Hook, S. (1997). When success breeds failure: The role of self-efficacy in escalating commitment to a losing course of action. Journal of Organizational Behavior, 18(5), 415-432.
- Xue, Y., Sun, S., Zhang, P., & Meng, T. (2015). Impact of cognitive bias on improvised decision-makers’ risk behavior: an analysis based on the mediating effect of expected revenue and risk perception. Management Science and Engineering, 9(2), 31-42.
- Zuckerman, M., Knee, C. R., Kieffer, S. C., Rawsthome, L., & Bruce, L. M. (1996). Beliefs m Realistic and Unrealistic Control: Assessment and Implications. Journal of Personality, 64(2), 435-464.