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Knowledge Sharing and Incentive Design in Production Environments: Theory and Evidence
Yuhchang Hwang,
Arizona State University
David H Erkens, Arizona State University
John H Evans, University of Pittsburgh
ABSTRACT. We develop and empirically test a parsimonious model of how specific knowledge and the value of knowledge sharing influence manufacturing plants’ incentive design choices. Our results confirm the prediction that increases in the extent of agents’ specific knowledge and the value of knowledge sharing are associated with greater (less) reliance on output (input) performance measures. Moreover, we find that relative to the incentive weight placed on individual-based output performance measures, the incentive weight placed on group-based output performance measures is increasing in the value of knowledge sharing and decreasing in the extent of specific knowledge. Further, we find that the influence of knowledge sharing on the use of group-based output performance measures is decreasing in the extent of specific knowledge. Finally, consistent with previous research, we find that as output performance measures become noisier, firms rely less on these measures in incentive contracts.
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