Empirical social network studies on small groups usually aim to identify structural properties that correlate with performance on specific tasks. In recent decades, behavioral economics have shown that, in certain circumstances, individuals can be, in a specific sense, irrational, behaving in predictable ways that don’t maximize their self-interest. One of these circumstances is high stakes - the presence of high level incentives. In fact, it has been demonstrated that in tasks requiring cognitive abilities, large rewards tend to reduce individuals’ performance. Our attention is particularly focused on groups’ cognitive tasks requiring efficient and effective knowledge sharing (KS). Specifically, our study explores how the network structure of groups affects the relationship between incentives and performance. To answer this question, we ran a laboratory experiment on 4-person groups constructed by the researcher on the basis of existing trust relations (both cognitive and affective trust) among 169 individuals who have known each other for some time. One type of group defined by the researcher was centralized (a sociometric star): all trust relations involved one central person. A second type of group was a sociometric clique: everyone trusted everyone. A third type of group was an empty graph: no trust ties within the group at all. The laboratory setting allowed us to randomly assign different incentive levels to the groups, and also allowed us to readily measure performance, both at the individual and at the group level. The results show that for a relatively simple cognitive task requiring KS, cliques were markedly less efficient, except in the presence of external incentives. Whereas other groups were unaffected by incentives, the clique structures benefitted considerably, bringing their efficiency levels in line with the other groups. This outcome constitutes not only a theoretical advancement in knowledge management discipline, but also a practical instrument that companies could use when dealing with human resources allocation for different tasks.

The Impact of Social Relationships and Incentives on Small Groups' Knowledge Sharing Dynamics

Giulia Palombi
2018-01-01

Abstract

Empirical social network studies on small groups usually aim to identify structural properties that correlate with performance on specific tasks. In recent decades, behavioral economics have shown that, in certain circumstances, individuals can be, in a specific sense, irrational, behaving in predictable ways that don’t maximize their self-interest. One of these circumstances is high stakes - the presence of high level incentives. In fact, it has been demonstrated that in tasks requiring cognitive abilities, large rewards tend to reduce individuals’ performance. Our attention is particularly focused on groups’ cognitive tasks requiring efficient and effective knowledge sharing (KS). Specifically, our study explores how the network structure of groups affects the relationship between incentives and performance. To answer this question, we ran a laboratory experiment on 4-person groups constructed by the researcher on the basis of existing trust relations (both cognitive and affective trust) among 169 individuals who have known each other for some time. One type of group defined by the researcher was centralized (a sociometric star): all trust relations involved one central person. A second type of group was a sociometric clique: everyone trusted everyone. A third type of group was an empty graph: no trust ties within the group at all. The laboratory setting allowed us to randomly assign different incentive levels to the groups, and also allowed us to readily measure performance, both at the individual and at the group level. The results show that for a relatively simple cognitive task requiring KS, cliques were markedly less efficient, except in the presence of external incentives. Whereas other groups were unaffected by incentives, the clique structures benefitted considerably, bringing their efficiency levels in line with the other groups. This outcome constitutes not only a theoretical advancement in knowledge management discipline, but also a practical instrument that companies could use when dealing with human resources allocation for different tasks.
2018
978-88-96687-11-6
Knowledge Sharing
Groups
Trust
Social Network Analysis
Information Flow
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.12606/10485
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