The association between cognitive biases and the quality of strategic decision making: Evidence from Jordanian banks

  • Received August 15, 2020;
    Accepted March 10, 2021;
    Published April 20, 2021
  • Author(s)
  • DOI
    http://dx.doi.org/10.21511/bbs.16(2).2021.01
  • Article Info
    Volume 16 2021 , Issue #2, pp. 1-11
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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.

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    • 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
    • Data curation
      Ayman Jarrar
    • Formal Analysis
      Ayman Jarrar
    • Investigation
      Ayman Jarrar
    • Methodology
      Ayman Jarrar
    • Project administration
      Ayman Jarrar
    • Software
      Ayman Jarrar
    • Writing – original draft
      Ayman Jarrar
    • Writing – review & editing
      Ayman Jarrar