Toward an Understanding of Dynamic Moral Decision Making: Model-Free and Model-Based Learning

George I. Christopoulos (georchris5@yahoo.com), Xiao-Xiao Liu (liuxx624@xmu.edu.cn) and Ying-yi Hong (yingyi.hong@gmail.com)
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George I. Christopoulos: Nanyang Technological University
Xiao-Xiao Liu: Xiamen University
Ying-yi Hong: The Chinese University of Hong Kong

Journal of Business Ethics, 2017, vol. 144, issue 4, No 3, 699-715

Abstract: Abstract In business settings, decision makers facing moral issues often experience the challenges of continuous changes. This dynamic process has been less examined in previous literature on moral decision making. We borrow theories on learning strategies and computational models from decision neuroscience to explain the updating and learning mechanisms underlying moral decision processes. Specifically, we present two main learning strategies: model-free learning, wherein the values of choices are updated in a trial-and-error fashion sustaining the formation of habits and model-based learning, wherein the brain updates more general cognitive maps and associations, thus sustaining flexible and state-dependent behaviors. We then summarize studies explaining the neuro-computational processes of both learning strategies—the calculation of prediction errors and valuation. We conclude by emphasizing how the incorporation of dynamic aspects in moral decision making could open new avenues for understanding moral behaviors in a changing world.

Keywords: Corruption; Bribery; Decision making; Decision neuroscience; Learning; Model-based (search for similar items in EconPapers)
Date: 2017
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Citations: View citations in EconPapers (4)

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DOI: 10.1007/s10551-016-3058-1

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