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thesis_Daniela Noethen_print final - Jacobs University

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Intergenerational Knowledge Transfer in Work Teams: A Multilevel Social Network Perspective<br />

in knowledge transfer between age homogenous and age diverse teams should be small as<br />

well.<br />

3.6.2. Knowledge reception<br />

Of all the variables tested, the transfer that the source received from the recipient had the<br />

strongest influence on knowledge transfer. This is in line with previous research: Wasko and<br />

Faraj (2000) have shown that participants in newsgroups help other members of these groups,<br />

because they themselves received help in the past and feel an obligation to “give back”.<br />

Furthermore, Bock and colleagues (2005) as well as Kankanhalli and colleagues (2005)<br />

reported that employees who expected reciprocation from others intended to share more<br />

knowledge and contributed more to electronic knowledge repositories, respectively. In all of<br />

these studies, a generalized rather than person-specific form of reciprocity was considered,<br />

that is, the reciprocal relationship was rather between a participant and a group (whose<br />

members might not even be known personally). In our study, we consider long-standing<br />

relationships between dyads of colleagues who have been working together for years. Thus,<br />

expectations as well as obligations should be a lot stronger, as would be the effect on<br />

knowledge transfer. Moreover, other variables, such as mutual trust or being on good terms<br />

(e.g., Szulanski, 1996), influence both directions of knowledge transfer within a dyad in the<br />

same manner, and could have strengthened the relationship between knowledge transfer and<br />

knowledge reception in addition to reciprocity effects. But even considering all these<br />

arguments, the effect of knowledge reception in the present study is surprisingly strong; over<br />

and above the other control variables, knowledge reception alone explained 63% of the<br />

overall variance. Thus, this transfer in the opposite direction is a truly powerful predictor. The<br />

strength of the relationship was already visible in the high zero-order correlation, reaching an<br />

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