Modeling Levels and Time in Entrepreneurship Research : An Illustration with Growth Strategies and Post-IPO Performance

New ventures lack resources, are buffeted by environmental factors, and often experience rapid growth and organizational transformations that can have profound effects on performance and survival. Methodologically, however, efforts to explain variation in entrepreneurial outcomes among and between levels over time often address levels or time, but rarely both. Because scholars potentially can make rich theoretical contributions by simultaneously investigating temporal relationships that cross levels, we illustrate multi-year, multilevel model building with random coefficient modeling (RCM) using language that is accessible to entrepreneurship scholars. Specifically, we model the effects of strategic growth actions on new venture performance using a longitudinal dataset of young, IPO-stage firms. Our illustration demonstrates the statistical advantages of modeling levels and time simultaneously, and offers a roadmap for entrepreneurship scholars interested in examining these effects. We also describe some specific research questions to help advance theory development using RCM