过度自信行为影响下的应急决策偏差和惩罚援助机制研究 本期目录 >>
Title: The Effect of Overconfidence on the Decision Bias,Subsidy and Penalty in Disruption Management
作者 包兴
Author(s): BAO Xing
摘要: 本文基于某电力公司的实地调研,在运作能力因灾受损情境下研究了应急修复过程中管理者两种过度自信行为对决策偏差的影响,分析了惩罚援助机制在决策纠偏方面的作用。研究结果表明:提高惩罚和积极援助的“胡萝卜+大棒”调控机制有助于纠正管理者过度自信造成的决策偏差;过度精确行为对偏差存在双向影响,但可通过调节惩罚援助参数比例促使管理者向“积极应急”的方向决策;过高估计行为必将造成应急投入不足,同时将抑制过度精确行为的偏差,惩罚援助的调控机制必然失效;外界随机扰动分布左偏时,管理者需适当增加决策量以缓解应急投入不足。
Abstract: Overconfidence behavior stems from the confidence of manager when treating his own prior knowledge, which could be strengthened by learning, training or successful experience. Some theoretical and experimental studies suggest that overconfidence could help manager improve decision performance in the incomplete-information or uncertain scenario. However, this is not always the case, especially in the scenario of unexpected events with extremely low probability, such as fire, earthquake and terrorist attacks, decision bias caused by overconfidence behavior could weaken or even invalid management’s performance, because the kind of human behavior might make manager lose his capability of knowledge calibration when he observes the inconsistencies with his prior knowledge. Some cases, such as the Blackout in USA and Canada(2003), and Fukushima nuclear leak in Japan(2011), verify that manager’s overconfidence plays a seriously negative role during the disruption management, which is also revealed by our survey of a power company’s senior and middle managers. The impact of manager’s overconfidence towards the disruption management’ performance is seldom concerned in the field of disruption management, and the research of mathematical model that includes different kinds of overconfidence is even less in the voluminous operational researches. In this paper, we are going to focus our research in the situation of large-scale operation systems, such as power station, chemical plant and communication system’s critical capacities are crippled by unexpected events, present the decision bias caused manager’s overconfidence, and further analyze the impact of this kind of behavior towards on the regulatory penalty and subsidy mechanism. In section 2, we firstly construct a mathematical model when manager is assumed to be completely rational, this model which is called Model I in this paper includes all kinds of cost that could be met in the period of disruption management, and it is proved to be a newsvendor model. Model I serves as a basic model for subsequent comparison. In section 3, we extend the Model I to Model II by including two kinds of overconfidence behavior which are over-estimation and over-precision. We proof that the manager’s decision is inevitable biased in Model II when compared to Model I, and decision bias caused by these two kinds of overconfidence behavior is rather different, which also affect the calibration capacity of regulatory penalty and subsidy. In section 4, we present the numerical analysis in order to show the manager’s decision bias when random disturbance is symmetrically and asymmetrically distributed, and we find that it is consistently conclusion of over-estimation and over-precision behavior to recover less injured capacities when manager shows over-estimation. However, bilateral impaction on decision bias, that would enlarge or narrow the bias gap when manager shows over-precision. In section 5, we present 5 managerial insights in order to show the ways for both regulators and managers to improve the doing performance separately. For regulators, 4 managerial insights could be help to narrow the gap of the decision bias when manager presents overconfident. As for an overconfident manager, 1 important managerial insight should be highly paid attention to when making decision which is proved to be helpful to lower the negative impaction during disruption management.
关键词: 过度自信;应急运作;决策偏差;惩罚和援助;有偏随机扰动
Keywords: Overconfidence; disruption management;; decision bias; penalty and subsidy; skewed random disturbance
基金项目: 国家自然科学基金;国家自然科学基金;教育部博士点基金;浙江省自然科学基金;浙江省社科规划“之江青年课题研究成果”
发表期数: 2017年 第3期
中图分类号: 文献标识码: 文章编号:
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