Motivating Innovation

Motivating Innovation

November 26, 2010 | Gustavo Manso
The paper "Motivating Innovation" by Gustavo Manso explores the optimal incentive schemes for encouraging innovation in large corporations. The author argues that standard pay-for-performance schemes, which often punish early failures and only reward long-term success, can hinder innovation. Instead, the optimal incentive scheme should exhibit substantial tolerance for early failure and reward long-term success. This scheme can be implemented through a combination of stock options with long vesting periods, option repricing, golden parachutes, and managerial entrenchment. The paper also highlights the importance of commitment to long-term compensation plans, job security, and timely feedback on performance. The analysis is grounded in a Bayesian decision model known as a bandit problem, which models the exploration-exploitation trade-off in innovation. The results show that the optimal contract for exploration depends on the path of performance, not just total performance, and that termination can be used to incentivize effort, especially in the context of exploration. The paper concludes by discussing the implications for corporate governance, executive compensation, bankruptcy laws, and entrepreneurship.The paper "Motivating Innovation" by Gustavo Manso explores the optimal incentive schemes for encouraging innovation in large corporations. The author argues that standard pay-for-performance schemes, which often punish early failures and only reward long-term success, can hinder innovation. Instead, the optimal incentive scheme should exhibit substantial tolerance for early failure and reward long-term success. This scheme can be implemented through a combination of stock options with long vesting periods, option repricing, golden parachutes, and managerial entrenchment. The paper also highlights the importance of commitment to long-term compensation plans, job security, and timely feedback on performance. The analysis is grounded in a Bayesian decision model known as a bandit problem, which models the exploration-exploitation trade-off in innovation. The results show that the optimal contract for exploration depends on the path of performance, not just total performance, and that termination can be used to incentivize effort, especially in the context of exploration. The paper concludes by discussing the implications for corporate governance, executive compensation, bankruptcy laws, and entrepreneurship.
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