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Organizational Research Methods
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An Examination of Firm, Industry, and Time Effects on Performance Using Random Coefficients Modeling

Jeremy C. Short

Texas Tech University

David J. Ketchen, Jr.

Auburn University

Nathan Bennett

Georgia Institute of Technology

Mathilda du Toit

Scientific Software International

The strategic management literature is unclear about how firm and industry effects influence performance, and the analysis of longitudinal data therein continues to be problematic. The authors analyze longitudinal data using hierarchical linear modeling to illustrate a random coefficients modeling alternative for examining firm performance. This approach allows researchers to explicitly model different conceptual approaches to testing change in performance over time and model predictor variables and cross-level interactions at multiple levels of analysis, and it also allows for investigation of time series errors. The results have implications for the strategic management field's goal of understanding multilevel determinants of firm performance over time.

Key Words: organizational performance • longitudinal research • multilevel studies

Organizational Research Methods, Vol. 9, No. 3, 259-284 (2006)
DOI: 10.1177/1094428106287572
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T. Greckhamer, V. F. Misangyi, H. Elms, and R. Lacey
Using Qualitative Comparative Analysis in Strategic Management Research: An Examination of Combinations of Industry, Corporate, and Business-Unit Effects
Organizational Research Methods, October 1, 2008; 11(4): 695 - 726.
[Abstract] [PDF]