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Incentivizing Knowledge Transfers

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  • Zhonghong Kuang
  • Yi Liu
  • Dong Wei

Abstract

We study the optimal design of relational contracts that incentivize an expert to share specialized knowledge with a novice. While the expert fears that a more knowledgeable novice may later erode his future rents, a third-party principal is willing to allocate her resources to facilitate knowledge transfer. In the unique profit-maximizing contract between the principal and the expert, the expert is asked to train the novice as much as possible, for free, in the initial period; knowledge transfers then proceed gradually and perpetually, with the principal always compensating the expert for his future losses immediately upon verifying the training he provided; even in the long run, a complete knowledge transfer might not be attainable. We further extend our analysis to an overlapping-generation model, accounting for the retirement of experts and the career progression of novices.

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  • Zhonghong Kuang & Yi Liu & Dong Wei, 2025. "Incentivizing Knowledge Transfers," Papers 2507.11018, arXiv.org.
    • Handle: RePEc:arx:papers:2507.11018
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    References listed on IDEAS

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    3. Hua, Xiameng & Watson, Joel, 2022. "Starting small in project choice: A discrete-time setting with a continuum of types," Journal of Economic Theory, Elsevier, vol. 204(C).
    4. Hua, Xiameng & Watson, Joel, 2022. "Starting small in project choice: A discrete-time setting with a continuum of types," University of California at San Diego, Economics Working Paper Series qt1fb0j67c, Department of Economics, UC San Diego.
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