This article proposes and demonstrates how conjoint methods can be adapted to allow the modeling of managerial reactions to various changes in economic and competitive environments and their effects on observed sales levels. Because in general micro-level data on strategic decision making over time are difficult and expensive to obtain, this approach can be of much value to the further study of managerial strategic behavior and market dynamics. In our application we model retailer reactions to changes in their sales, focusing in particular on the actions that affect the demand for retail space and possibilities to improve retail sites. Choice responses to hypothetical sales and environmental trend scenarios are collected from 183 retailers and used to estimate to logit regression model that predicts retailers' probabilities of choosing actions. The model results confirm that retailers are more likely to take action when sales go down than when they go up, and also that they react more quickly if sales go down. It is also found that retailers are more reluctant to change the positioning of their store when confronted with a sales increase than when confronted with a sales decrease. The model is compared with a non-experimental model that is based on retailers' reactions to the trends they report to have observed for their own stores. The article concludes with a discussion of the implications of this research for the further development of conjoint-like approaches to studying entrepreneurial behavior.