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1 – 3 of 3This paper examines the effect of intergroup competition on intragroup cooperation. Three experiments are reviewed. The first experiment establishes that intergroup competition…
Abstract
This paper examines the effect of intergroup competition on intragroup cooperation. Three experiments are reviewed. The first experiment establishes that intergroup competition can effectively increase intragroup cooperation in a laboratory setting where symmetric players make binary decisions in one‐shot dilemma games. The second experiment shows that this constructive effect of intergroup competition is generalizable to a real‐life setting in which asymmetric players make continuous decisions in an ongoing interaction. The third experiment demonstrates that the increase in intragroup cooperation can be accounted for at least in part by motivational, rather than structural, effects of the intergroup competition. Theoretical and practical issues concerning the applications of these findings are discussed.
Eldad Yechiam, Ernan Haruvy and Ido Erev
Companies incur immense losses due to employee neglect to save and back up data and failure to frequently update anti‐virus protections. This problem appears perplexing as such…
Abstract
Companies incur immense losses due to employee neglect to save and back up data and failure to frequently update anti‐virus protections. This problem appears perplexing as such oversights are clearly neither in the organization’s nor in the employees’ best interest. We review the possible reasons for this phenomenon arising from studies of social dilemmas, unrealistic optimism, and reinforcement learning. We follow with three examples of “under‐saving” behavior. The results reveal that in all three cases computer users, novices and experts, feel that they do not save enough. This feeling is consistent with the reinforcement learning account. People think that they are less careful than they wish to be. The implications of this observation are discussed.
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Resource reconfiguration enables firms to adapt in dynamic environments by supplementing, removing, recombining, or redeploying resources. Whereas prior research has underscored…
Abstract
Resource reconfiguration enables firms to adapt in dynamic environments by supplementing, removing, recombining, or redeploying resources. Whereas prior research has underscored the merits of resource reconfiguration and the modes for implementing it, little is known about the antecedents of this practice. According to prior research, under given industry conditions, resource reconfiguration is prompted by a firm’s corporate strategy and by characteristics of its knowledge assets. We complement this research by identifying learning from performance feedback as a fundamental driver of resource reconfiguration. We claim that performance decline relative to aspiration motivates the firm’s investment in knowledge reconfiguration, and that this investment is reinforced by the munificence of complementary resources in its industry, although uncertainty about the availability of such resources limits that investment. Testing our conjectures with a sample of 248 electronics firms during the period 1993–2001, we reveal a clear distinction between exploitative reconfiguration, which combines existing knowledge elements, and exploratory reconfiguration, which incorporates new knowledge elements. We demonstrate that performance decline relative to aspiration motivates a shift from exploitative reconfiguration to exploratory reconfiguration. Moreover, munificence of complementary resources mitigates the tradeoff between exploratory and exploitative reconfigurations, whereas uncertainty weakens the motivation to engage in both types of reconfiguration, despite the performance gap. Nevertheless, codeployment, which extends the deployment of knowledge assets to additional domains, is more susceptible to uncertainty than redeployment, which withdraws those assets from their original domain and reallocates them to new domains. Our study contributes to emerging research on resource reconfiguration, extends the literature on learning from performance feedback, and advances research on balancing exploration and exploitation.
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