Jorge Tamayo

Professor Tamayo’s research focuses on theoretical modeling and structural estimation of firm decision-making and productivity.

Professor Tamayo studies dynamic competition for customer membership. Generally, firms that implement a membership model charge a ‘membership’ fee that allows consumers to buy products/services at a unit price, in multiple periods. He looks into the price discrimination that these firms such as Amazon and DirecTV employ between new and old customers. In his research, Professor Tamayo explores how the length of the membership, the ability to price discriminate between ‘old’ and ‘new’ customers with the membership fee and unit price, and the incentives to price discriminate, all affect competition.

Professor Tamayo also researches the functioning of firms, in particular, causes of low or high labor productivity, and how firms and managers can overcome these issues. He examines how the quality of managers contributes to the productivity dynamics of the teams they manage. Using two years of daily, line-level production data from six garment factories in India, he measured contributions of seven distinct dimensions of managerial quality: tenure, cognitive skills, autonomy, personality psychometrics, control, attention, and ‘relatability’ to workers. He finds that several key dimensions of managerial quality, such as attention, autonomy, and control, are important for productivity but are not appropriately priced into market wages. Counterfactual simulations provide clear guidance on hiring and training policies. That is, firms could substantially improve productivity via psychometric measurement and screening of potential hires, and by training supervisors in attention and control.

Winner of the 2023 HBR Award for the best article of the year in Harvard Business Review for “Reskilling in the Age of AI” (September–October 2023) with Leila Doumi, Sagar Goel, Orsolya Kovács-Ondrejkovic, and Raffaella Sadun.