Abstract
The existence of ambiguity presents a challenge to decision-makers as it eliminates the ability to apply standard optimization approaches, such as those based on calculating the objective expected values of alternative actions. In reality, ambiguity arises in most strategically important decisions in some form because of the genuine limits on the decision-maker’s rationality and on the information available about the alternatives and the future. To address that reality, we define such problems as strategic decision-making under ambiguity where choices over resource investments must be made in competitive environments where possible outcomes and their payoffs are known ex ante, but the probabilities of such outcomes are unknowable ex ante. We outline a multi-step, logical approach for addressing such problems in theory with the goal of providing an improved basis for practical decisions that should increase organizational performance.
Highlights
Most research in management focuses on decision-making in risky contexts, given the ease of modeling and experimenting on expected utility maximization (e.g., Malecka 2020; Starmer 2000)
Ambiguity arises in most strategically important decisions in some form because of the genuine limits on the decision-maker’s rationality and on the information available about the alternatives and the future. We define such problems as strategic decision-making under ambiguity where choices over resource investments must be made in competitive environments where possible outcomes and their payoffs are known ex ante, but the probabilities of such outcomes are unknowable ex ante
We propose a new approach for dealing with strategic decision-making under ambiguity (SDMUA)
Summary
Most research in management focuses on decision-making in risky contexts, given the ease of modeling and experimenting on expected utility maximization (e.g., Malecka 2020; Starmer 2000). We propose a new approach for dealing with strategic decision-making under ambiguity (SDMUA). Most daily decisions involve incomplete knowledge, and the kind that generates uncertainty over outcome probabilities, better known as ambiguity (e.g., Peysakovich and Karmarkar 2016) Such decisions include everything from choosing a dish from a menu to choosing a medical or retirement plan to contemplating the value of a stock (e.g., Jia et al 2020; Peysakovich and Naecker 2017). To our knowledge, based on keyword searches across business journals, no papers have combined all of the tools we have in one approach, let alone to address a SDMUA problem This is new and speaks to the leverage that current economic concepts can generate when packaged together in an appropriate context. We propose several performance-related relationships, and discuss the implications our approach has for academics, practitioners and policy-makers
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