Applications and Implications of Status Quo Bias
DOI:
https://doi.org/10.54097/hbem.v21i.13735Keywords:
Status quo bias; inertia; cognitive bias.Abstract
Status quo bias (SQB) refers to the inclination of individuals to prefer and maintain the current state in decision-making. This study explores the profound impact of SQB on decision-making in the fields of medicine, technology, and business. Through an extensive review of existing literature, we examine how SQB significantly influences the decision-making process and its subsequent outcomes, hampering the progress of innovation and hindering the adoption of optimal choices. Rooted in factors such as familiarity, comfort, and resistance to change, SQB acts as a formidable barrier to embracing novel alternatives. Additionally, limited understanding and low market penetration further reinforce this cognitive bias. By gaining a comprehensive understanding of the nature and implications of SQB, policymakers and decision-makers can access valuable insights to guide future planning and strategies effectively, mitigating the adverse effects of this cognitive bias. The study aims to encourage progress in medicine, technology, and business domains by promoting the exploration and adoption of new products and practices. By acknowledging and addressing SQB, stakeholders can foster a culture of adaptability and open-mindedness, ultimately driving positive advancements in their respective fields.
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References
Camilleri, A. R., & Sah, S. (2021). Amplification of the status quo bias among physicians making medical decisions. Applied Cognitive Psychology, 35(6), 1374–1386.
Suri, G., Sheppes, G., Schwartz, C., & Gross, J. J. (2013). Patient Inertia and the Status Quo Bias: When an Inferior Option Is Preferred. Psychological Science, 24(9), 1763–1769.
Hsieh, P.J. (2015). Healthcare professionals’ use of health clouds: Integrating technology acceptance and status quo bias perspectives. International Journal of Medical Informatics (Shannon, Ireland), 84(7), 512–523.
Chi, W.C., Lin, P.J., Chang, I.C., & Chen, S.L. (2020). The inhibiting effects of resistance to change of disability determination system: A status quo bias perspective. BMC Medical Informatics and Decision Making, 20(1), 82–82.
Fan, Y.W., Chen, C.D., Wu, C.C., & Fang, Y.H. (2015). The Effect of Status Quo Bias on Cloud System Adoption. The Journal of Computer Information Systems, 55(3), 55–64.
Klein, H. C., Stelter, A., Oschinsky, F. M., & Niehaves, B. (2022). A status quo bias perspective on user resistance in building information modeling adoption – Towards a taxonomy. Computers in Industry, 143, 103760–.
Loh, X.M., Lee, V.H., & Leong, L.Y. (2022). A Multi-Dimensional Nomological Network of Mobile Payment Continuance. The Journal of Computer Information Systems, ahead-of-print(ahead-of-print), 1–23.
Shi, X., Lin, Z., Liu, J., & Hui, Y. K. (2018). Consumer loyalty toward smartphone brands: The determining roles of deliberate inertia and cognitive lock-in. Information & Management, 55(7), 866–876.
Grabicki, F., & Menges, R. (2019). Consumer Responsibility and the Transformation Process of the Electricity Market: Insights from Behavioral Decision Research. Management Revue, 30(2/3), 312–330.
Li, J., Liu, M., & Liu, X. (2016). Why do employees resist knowledge management systems? An empirical study from the status quo bias and inertia perspectives. Computers in Human Behavior, 65, 189–200.
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