Diversity and Social Network Structure in Collective Decision Making: Evolutionary Perspectives with Agent-Based Simulations
Diversity and Social Network Structure in Collective Decision Making: Evolutionary Perspectives with Agent-Based Simulations
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DOI：
10.1155/2019/7591072
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发表时间：
2013-11
期刊：
影响因子：
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通讯作者：
Shelley D. Dionne;Hiroki Sayama;F. Yammarino
中科院分区：
文献类型：
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作者：
Shelley D. Dionne;Hiroki Sayama;F. Yammarino
集体决策，尤其是基于群体的决策，在组织中至关重要。采用进化理论的方法进行集体决策，基于代理的模拟研究如何影响人类集体决策的代理人的多样性，在问题的理解和/或行为的讨论，以及他们的社会网络结构。模拟结果表明，具有一致问题理解的群体倾向于产生更高的效用值的想法，并显示出更好的决策收敛，但前提是集体问题理解没有群体水平的偏见。模拟结果还表明了面向选择（即，剥削的）和面向变化的（即，探索性的）行为，以实现质量的最终决定。扩大群体规模和引入非平凡的社交网络结构通常会提高想法的质量，但代价是决策收敛。不同的社会网络拓扑结构的模拟显示，集体决策的小世界网络与高本地集群往往比随机或无标度网络更容易实现最高的决策质量。这种进化理论和模拟方法的集体，群体和多级决策的未来管理研究的影响进行了讨论。
Collective, especially group-based, managerial decision making is crucial in organizations. Using an evolutionary theoretic approach to collective decision making, agent-based simulations were conducted to investigate how human collective decision making would be affected by the agents’ diversity in problem understanding and/or behavior in discussion, as well as by their social network structure. Simulation results indicated that groups with consistent problem understanding tended to produce higher utility values of ideas and displayed better decision convergence, but only if there was no group-level bias in collective problem understanding. Simulation results also indicated the importance of balance between selection-oriented (i.e., exploitative) and variation-oriented (i.e., explorative) behaviors in discussion to achieve quality final decisions. Expanding the group size and introducing nontrivial social network structure generally improved the quality of ideas at the cost of decision convergence. Simulations with different social network topologies revealed collective decision making on small-world networks with high local clustering tended to achieve highest decision quality more often than on random or scale-free networks. Implications of this evolutionary theory and simulation approach for future managerial research on collective, group, and multilevel decision making are discussed.