Decision Making Under Uncertainty Market During Covid-19
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This article discussed decision-making models in the context of crisis and uncertainty during the COVID-19 pandemic. Time and information constraints, the effectiveness of government policies, and public expectations were used to build the research model. Data were collected by distributing a semi-open and closed survey questionnaire (Google Forms). The statistical result showed that the decisions taken during a crisis/pandemic were more determined by the time constraints and the information (significantly positive) than the government policies and the public expectations (negative is not significant). Related to the effectiveness of the health and economic policies taken by the government, it concluded the effective response; however the virus recurs, the public health response succeeds, but measures are insufficient to prevent recurrence so that physical distancing continues (regionally) for several months. Analysis of the survey respondents towards the government economic policy assessed that government policy was still partially effective intervention, policy responses partially offset economic damage, the banking crisis was avoided, and muted recovery levels. The economic impact of co-19 predicted a slow economic recovery, supported by respondents' expectation of pessimism towards future economic conditions.
Bakker, Marije H., José H. Kerstholt, Marco van Bommel, and Ellen Giebels. (2019). Decision-Making during a Crisis: The Interplay of Narratives and Statistical Information before and after Crisis Communication. Journal of Risk Research 22 (11): 1409–24. https://doi.org/10.1080/13669877.2018.1473464.
Barros, G. (2010). Herbert A. Simon and the concept of rationality: boundaries and procedures. Brazilian Journal of Political Economy, 30, 455-472.
Bloom David, E., Daniel, C., & Sevilla, J. P. (2018). Epidemics and economics: New and resurgent infectious diseases can have far-reaching economic repercussions. Finance and Development, 55(2), 46-49.
Creswell, J. W. (2014). Research Design: Qualitative, Quantitative and Mixed Methods Approaches. 4th ed. SAGE Publications, Inc. https://doi.org/10.16309/j.cnki.issn.1007-1776.2003.03.004.
Dionne, S. D., Gooty, J., Yammarino, F. J., & Sayama, H. (2018). Decision making in crisis: A multilevel model of the interplay between cognitions and emotions. Organizational Psychology Review, 8(2-3), 95-124.
Fan, Victoria Y., Dean T. Jamison, and Lawrence H. Summers. (2018). Pandemic Risk: How Large Are the Expected Losses? Bulletin of the World Health Organization 96 (2): 129–34. https://doi.org/10.2471/BLT.17.199588.
Gigerenzer, Gerd, and Henry Brighton. (2009). Homo Heuristicus: Why Biased Minds Make Better Inferences. Topics in Cognitive Science 1 (1): 107–43. https://doi.org/10.1111/j.1756-8765.2008.01006.x.
Hausfeld, Jan, and Sven Resnjanskij. (2018). Risky Decisions and the Opportunity Cost of Time, no. October. www.cesifo-group.de.
Hernandez, Jose G Vargas, and Ricardo Perez Ortega. (2019). Bounded Rationality in Decision–Making.” MOJ Current Research & Reviews 2 (1): 1–8. https://doi.org/10.15406/10.15406/mojcrr.2019.02.00047.
Hoyer, Wayne; & Deborah J MacInnis. (2009). Consumer Behavior. 5th ed. Mason Ohio ;London: South Western ;Cengage Learning [distributor].
Kocher, Martin G., David Schindler, Stefan T. Trautmann, and Yilong Xu. (2019). Risk, Time Pressure, and Selection Effects. Experimental Economics 22 (1): 216–46. https://doi.org/10.1007/s10683-018-9576-1.
Korepanov, O., Mekhovich, S., Karpenko, N., Kryvytska, O., Kovalskyi, A., & Karpenko, R. (2019). Modelling Decision Making under Uncertainty for Strategic Forecasting. International Journal of Recent Technology and Engineering 8 (3): 7251–55. https://doi.org/10.35940/ijrte.C6312.098319.
McFall, Joseph P. (2015). Rational, Normative, Descriptive, Prescriptive, or Choice Behavior? The Search for Integrative Metatheory of Decision Making. Behavioral Development Bulletin 20 (1): 45–59. https://doi.org/10.1037/h0101039.
McKinsey and Company. (2020). Crushing Coronavirus Uncertainty: The Big ‘ Unlock ' for Our Economies. Strategy & Corporate Finance Practice, no. May.
Makridakis, S., and Bakas, N. (2016). Forecasting and uncertainty: A survey. Risk and Decision Analysis, 6(1), 37-64.
Parker, A.M, Nelson, C., Shelton, S.R., Dausey, D.J., Lewis, M.L., Pomeroy, A., Leuschner, K.J. (2009). Measuring Crisis Decision Making for Public Health Emergencies: Santa Monica, California. RAND Corporation.
Savage, D. A. (2013). Decision making under pressure: a behavioural economics perspective (Doctoral dissertation, Queensland University of Technology).
Strahle, William M, Rider College, E H Bonfield, and Rider College. (1951). A Model Of Consumer Decision Making Under Severe Time Constraints: William M. Strahle, Rider College E. H. Bonfield, Rider College, 428–36.
Tashakkori, Abbas, and Charles Teddlie. (2015). SAGE Handbook of Mixed Methods in Social & Behavioral Research. SAGE Handbook of Mixed Methods in Social & Behavioral Research. SAGE Publications, Inc. https://doi.org/10.4135/9781506335193.
Tversky, A., and Kahneman, D. (1974). Judgment under Uncertainty: Heuristics and Biases: Biases in judgments reveal some heuristics of thinking under uncertainty. Science, 185(4157), 1124-1131.
Young, Diana L., Adam S. Goodie, Daniel B. Hall, and Eric Wu. (2012). Decision Making under Time Pressure, Modeled in a Prospect Theory Framework. Organizational Behavior and Human Decision Processes 118 (2): 179–88. https://doi.org/10.1016/j.obhdp.2012.03.005.
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