Strategic Management Journal Strat. Mgmt. J., 26: 881–886 (2005) Published online in Wiley InterScience (www.interscience.wiley.com). DOI: 10.1002/smj.479 RESEARCH NOTES AND COMMENTARIES RESPONSE TO McGAHAN AND PORTER’S COMMENTARY ON ‘INDUSTRY, CORPORATE AND BUSINESS-SEGMENT EFFECTS AND BUSINESS PERFORMANCE: A NON-PARAMETRIC APPROACH’ TIMOTHY W. RUEFLI 1 * and ROBERT R. WIGGINS 2 1 McCombs School of Business and The IC 2 Institute, University of Texas at Austin, Austin, Texas, U.S.A. 2 Fogelman College of Business and Economics, University of Memphis, Memphis, Tennessee, U.S.A. In the comment on Ruefli and Wiggins (2003), a number of points are made supporting the variance component analysis approach to determining the importance of industry, corporate, and business segment factors on business segment performance. This response addresses in more detail the nature of the methodological and statistical assumptions made by variance components analysis or ANOVA and their implications for the ‘puzzling’ results obtained when these techniques are employed. The response then contrasts the variance-based methodologies with a non-parametric approach used in Ruefli and Wiggins (2003) that makes fewer and weaker assumptions and yields more robust and more internally consistent results. The response also examines the limitations of employing an autoregressive approach to measuring persistence of abnormal profits and contrasts it with a non-parametric methodology presented in the article. Copyright  2005 John Wiley & Sons, Ltd. INTRODUCTION The comment (McGahan and Porter, 2005) on Ruefli and Wiggins (2003) raises a number of issues relevant to not only our article, but to the broader area of research on the importance of industry, corporate, and business segment fac- tors to business segment performance. Rather than sequentially address each of the points noted in the comment, this response begins with an overview Keywords: non-parametric analysis; variance components analysis; ceteris paribus assumption *Correspondence to: Timothy W. Ruefli, McCombs School of Business, University of Texas at Austin, CBA 5.202, Austin, TX 78712, U.S.A. E-mail: tim.ruefli@mccombs.utexas.edu of the methodology employed in Ruefli and Wig- gins (2003) as a way of providing a context in which to speak to the issues that were raised. In our research, time series performance data on entities at the levels of business segments, cor- porations, and industries were stratified on each level and in each period by the iterative application of the non-parametric Kolmogorov–Smirnov (IKS hereafter) test (Ruefli and Wiggins, 2000). This technique clusters entities into strata that are statis- tically significantly different in their performance from all other strata in that period. In using IKS the researcher does not specify a priori or ex post (as in most methods of clustering) the number or nature of the strata — the IKS technique determines those parameters from the data. Our application Copyright  2005 John Wiley & Sons, Ltd. Received 12 October 2004 Final revision received 3 December 2004