Incentivizing Knowledge Transfers

TL;DR

This paper analyzes how to design optimal contracts that incentivize experts to share knowledge with novices, balancing the expert's concerns and the principal's incentives, with insights from real-world technology transfers.

Contribution

It introduces a novel model of relational contracts for knowledge transfer, highlighting the optimal strategies and limitations in incentivizing expert sharing.

Findings

Experts are incentivized to share maximum knowledge initially for free.

Knowledge transfer proceeds gradually and perpetually under optimal contracts.

Complete knowledge transfer may not be achievable in practice.

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, while the principal offers lump-sum compensations to the expert right after verifying each transfer; even in the long run, a complete knowledge transfer might not be attainable. Our analysis sheds light on the success of several prominent cross-border technology transfers that took place in China's auto industry and Korea's high-speed rail development.