Balancing cooperation and competition in human groups: the role of emotional algorithms and evolution
Author: Loch, Christoph H. ; Galunic, D. Charles ; Schneider, Susan C.INSEAD Area: Organisational Behaviour ; Technology and Operations Management ; Technology and Operations ManagementIn: Managerial and Decision Economics, vol. 27, no. 2-3, March 2006 Language: EnglishDescription: p. 217-233.Type of document: INSEAD ArticleNote: Please ask us for this itemAbstract: We examine emotional algorithms and their role in a fundamental dilemma that confronts human groups - whether actors should take care of me (compete) or take care of we (cooperate). We argue that human emotions, triggered in algorithmic fashion through four common, although culturally specified, mechanisms, powerfully direct humans to compete or cooperate. Drawing on evolutionary psychology, we first define and characterize these hard-wired emotional algorithms, presenting evidence for their independent influence. Their regulatory influence on human groups, however, can only be appreciated once we examine them as a system. We show how, as a system, these algorithms help explain the dynamic balance that members of human groups can (and often must) achieve between competition and cooperation. We derive three propositions regarding how these algorithms play out in groups. We suggest that understanding these dynamics can help leaders better manage cooperation and competition in organizational groups.| Item type | Current location | Call number | Status | Date due | Barcode | Item holds |
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We examine emotional algorithms and their role in a fundamental dilemma that confronts human groups - whether actors should take care of me (compete) or take care of we (cooperate). We argue that human emotions, triggered in algorithmic fashion through four common, although culturally specified, mechanisms, powerfully direct humans to compete or cooperate. Drawing on evolutionary psychology, we first define and characterize these hard-wired emotional algorithms, presenting evidence for their independent influence. Their regulatory influence on human groups, however, can only be appreciated once we examine them as a system. We show how, as a system, these algorithms help explain the dynamic balance that members of human groups can (and often must) achieve between competition and cooperation. We derive three propositions regarding how these algorithms play out in groups. We suggest that understanding these dynamics can help leaders better manage cooperation and competition in organizational groups.
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