Technology Adoption: Optimal Timing, Pricing, and Employee Incentives

Abstract

This paper models the incentive misalignment between firm owners and their employees as a barrier to technology diffusion, which is a critical yet understudied feature, in technology adoption settings. To do so, we consider a general continuous-time optimal stopping framework with the Stackelberg game to characterize the equilibrium outcome of a firm's technology adoption decision, its employees' usage decisions, and the technology supplier's pricing decision under incentive misalignment. Despite a complex setting with multiple players in a continuous-time framework, we are able to fully characterize the optimal adoption policy in closed-form. Specifically, the condition for adoption is characterized by a closed-form threshold that explicitly depends on the percentage of employees who choose to use the technology. Based on the structure of the optimal adoption policy, we further characterize three adoption regions (i.e., no-adoption, immediate-adoption, and delayed-adoption) to understand how the incentive misalignment affects the adoption decisions. Next, we study two actionable strategies to motivate employee technology usage: adjusting the base salary and increasing the bonus rate. Interestingly, we demonstrate that increasing the bonus rate always performs better than adjusting the base salary. Moreover, the firm's optimal revenue can be achieved by solely relying on increasing the bonus rate. Finally, we characterize the technology supplier's equilibrium price and discuss its structural properties. To supplement our theoretical results, we study a real-world case of artificial intelligence (AI) technology adoption in collaboration with a large regional bank in Asia. We first collect 992 surveys illuminating the incentive misalignment and then conduct numerical experiments to illustrate how practitioners can achieve better performance by adjusting the technology adoption timing and wage contracts per incentive misalignment.