Forecasting the industry context underpins much of the canonical perspectives within the field of Strategy. Additionally, many of the core tradeoffs illuminated in the field are premised upon different forward-looking expectations between short-term and long-term outcomes. While extant literature has begun to offer important clarity regarding antecedents toward superior foresight, the focus has largely been on understanding foresight around short-term outcomes, which is but half of the story. In this study, we complement existing literature by offering a perspective of how individuals navigate the complexities of forecasting across different temporal horizons: a duality between short- and long-term issues. Integrating the behavioral decision theory and industry evolution literatures, we argue that individuals tend to overreact in the short-term of industry evolution and underreact in the long term due to a fundamental difference between common linear cognitive processes and nonlinear (S-curve) industry outcomes. Utilizing a novel dataset of 7,569 forecasts by 505 participants who participated in parallel short-term and long-term industry forecasting tournaments related to the evolution of the automotive industry, we find support for our hypotheses. Further, in post hoc analyses, we explore individual-level differences in belief updating patterns and background, identifying the role of overreaction, underreaction, and domain experience in shaping industry foresight across different temporal horizons.
