scholarly journals Entrepreneurial judgment as empathic accuracy: a sequential decision-making approach to entrepreneurial action

2013 ◽  
Vol 11 (3) ◽  
pp. 651-681 ◽  
Author(s):  
JEFFERY S. MCMULLEN

Abstract:Entrepreurship theory within economics has long touted the importance of judgment in entrepreneurial action. More recently, proponents have begun to advocate extension of this work to organization studies. However, critics of entrepreneurial judgment have responded by claiming that the construct is only meaningfulpost hocand vapid when examinedex ante. Instead, they claim that, if entrepreneurship theory is to progress, then judgment must be replaced by a process logic known as effectuation. This article examines their claims and redefines the judgment dilemma as one of scope rather than existence. Empathic accuracy is then introduced to offer a means of addressing their criticism without having to deny the existence of entrepreneurial judgment. Empathic accuracy is also shown to be capable of explaining some of the cognitive mechanisms necessary for effectuation and dynamic socio-economic order.

2021 ◽  
Author(s):  
Laura Fontanesi ◽  
Amitai Shenhav ◽  
Sebastian Gluth

Recent years have witnessed a surge of interest in understanding the neural and cognitive dynamics that drive sequential decision making in general and foraging behavior in particular. Due to the intrinsic properties of most sequential decision-making paradigms, however, previous research in this area has suffered from the difficulty to disentangle properties of the decision related to (a) the value of switching to a new patch versus (b) the conflict experienced between choosing to stay or leave. Here, we show how the same problems arise in studies of sequential decision-making under risk, and how they can be overcome, taking as a specific example recent research on the `pig' dice game. In each round of the `pig' dice game, people roll a die and accumulate rewards until they either decide to proceed to the next round or lose all rewards. By combining simulation-based dissections of the task structure with two experiments, we show how an extension of the standard paradigm, together with cognitive modeling of decision-making processes, disentangles value- from conflict-related choice properties. Our study elucidates the cognitive mechanisms of sequential decision making and underscores the importance of avoiding potential pitfalls of paradigms that are commonly used in this research area.


Author(s):  
Ming-Sheng Ying ◽  
Yuan Feng ◽  
Sheng-Gang Ying

AbstractMarkov decision process (MDP) offers a general framework for modelling sequential decision making where outcomes are random. In particular, it serves as a mathematical framework for reinforcement learning. This paper introduces an extension of MDP, namely quantum MDP (qMDP), that can serve as a mathematical model of decision making about quantum systems. We develop dynamic programming algorithms for policy evaluation and finding optimal policies for qMDPs in the case of finite-horizon. The results obtained in this paper provide some useful mathematical tools for reinforcement learning techniques applied to the quantum world.


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