Effects of behavioral bias regarding demand forecasting in a competitive market

Abstract Considerable human judgment is involved in demand forecasting. When managers judge demands under uncertainty, they inevitably use signals to update their demand information. These signals are seldom perfect; hence, managers hold behavioral bias about the signal fidelity, that is, over‐ or under‐estimating the signal fidelity. This article models managers' behavioral bias about signal fidelity in Bayesian demand forecasting and explores its impact on competitive firms. We find that no matter whether the competitor's manager is unbiased or biased, a firm can benefit from its manager's slight overestimation, but the competitor can benefit from the firm's manager's underestimation. However, when one firm's manager is biased, improving the signal fidelity may not constantly improve firms' profits, revealing the potential risk of behavioral bias on the efficiency of the forecasting systems. We further consider the diversity of biased managers and the information asymmetry regarding the bias. Except that the benefits of behavioral bias exist, we additionally find that managers' heterogeneous behavioral bias can form a hedge effect and bring a win‐win situation. Under asymmetric information, managers' inference bias on the competitor's type may benefit firms by easing the negative impact of managers' behavioral bias about signal fidelity. We finally analyze the social welfare and consumer surplus, check the robustness of the main results and deliver additional findings by considering competing firms, different signal fidelity measures, and the signal‐dependent behavioral bias.