A tale of two effects: Using longitudinal data to compare within‐ and between‐firm effects |
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Authors: | S. Trevis Certo Michael C. Withers Matthew Semadeni |
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Affiliation: | 1. W.P. Carey School of Business, Arizona State University, Tempe, Arizona, U.S.A.;2. Mays Business School, Texas A&M University, College Station, Texas, U.S.A. |
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Abstract: | Research summary : We investigate the theoretical and empirical implications of longitudinal data in strategy research. Theoretically, longitudinal data allow strategy researchers to distinguish between relationships among constructs within versus between firms. Empirically, longitudinal data contain information about two types of relationships: within‐ and between‐firm. We describe how the hybrid approach, a technique used in other disciplines, disentangles within‐ and between‐firm relationships. We reexamine a study of research and development expenditures to illustrate the advantages of the hybrid approach. Based on our theory and reexamination, we offer a series of recommendations for researchers using longitudinal data to test theoretical perspectives . Managerial summary: Strategy research examines two sources of variation over time: what is occurring within the firm (e.g., Do firms perform better over time when investing more in R&D?) and what is occurring between firms (e.g., Do firms investing more in R&D outperform firms investing less in R&D?). These two sources may be similar or different in both direction and magnitude, and when significant differences exist in either direction or magnitude, researchers must carefully consider the implication of these differences to their theoretical rationale and statistical testing. Our article highlights the benefits of theorizing and testing these two sources of variance, providing scholars the ability to broaden both the theoretical and empirical contribution of their research. This distinction is important to how research informs managerial decision making . Copyright © 2016 John Wiley & Sons, Ltd. |
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Keywords: | research methods theory testing longitudinal data theory development hybrid approach |
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