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thesis_Daniela Noethen_print final - Jacobs University

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Preventing Knowledge Loss When Employees Expect to Leave<br />

4. Preventing Knowledge Loss When Employees Expect to Leave:<br />

Effects of Expected Turnover on Knowledge Transfer and Interactions with<br />

Perceived Supervisor Support 5<br />

This is the last of the three empirical chapters of the present dissertation. With this paper, I<br />

shift the focus from predictors of knowledge transfer to knowledge transfer in situations that<br />

bear a threat of knowledge loss for the organization. More specifically, I am looking at<br />

situations in which employees expect or intend to leave the organization. Ideally, this would<br />

be situations in which the employees’ knowledge is safeguarded against loss by increased<br />

knowledge transfer to other employees, but there is good reason to belief that employees in<br />

such situations are less inclined to share their knowledge with colleagues. Thus, with this<br />

paper, I examine if knowledge transfer in such situations is actually a preferable prevention<br />

strategy.<br />

4.1. Abstract<br />

The prevention of knowledge loss is a pressing issue in the era of the knowledge-based view<br />

of the firm (Grant, 1996, 1997), not only because of the large cohort of baby boomers now<br />

starting to retire, but also because turnover rates among the younger generations are on the<br />

rise. Increased knowledge sharing can be one strategy to counteract organizational or group<br />

knowledge loss prior to employees’ turnover. However, knowledge sharing is a discretionary<br />

behavior which can be encouraged, but hardly demanded of employees intending or expecting<br />

to leave the organization. The objective of the present work was to investigate the effects of<br />

voluntary turnover intention and expected involuntary turnover on employees’ knowledge<br />

sharing within teams, as well as to examine a buffering effect of perceived supervisor support<br />

5 I thank Torsten Biemann and Sven Voelpel, who will be co-authoring this paper upon publication,<br />

for their input and collaboration.<br />

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