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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.

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.

This study aims to identify individuals' biases while making investment decisions and explore how these biases can be incorporated into a robo-advisory platform to help mitigate these biases. This paper identifies eight investment-related behavioral biases: mental accounting, gambler’s fallacy, hindsight, regret aversion, disposition, trend-chasing, loss aversion and herding.

This study uses primary data from 263 respondents across various age groups, of which approximately 50 were wealth management professionals in the UAE. A random sampling method from probability sampling is employed to gather the primary data. The identified biases serve as dependent variables; the age and income of individuals serve as the independent variables.

Age and income are significantly related to mental accounting, herding, gambler fallacy and loss aversion. Existing studies on behavioral finance demonstrate that individuals who make investment decisions are susceptible to cognitive fallacies, leading to nonrational investment decisions.

By studying these biases affecting individuals of varying ages and income levels, wealth management professionals can tailor their financial robo-advisory services to address these biases and help clients build wealth with consistent investment.

This study uses survey-based sampling in the context of the UAE; hence, the data and analysis represent originality.

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.