Comment on Industry, corporate and business-segment effects and business performance : a non-parametric approach by Ruefli and Wiggins
By: MCGAHAN, Anita M
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Contributor(s): Porter, Michael E.
Material type: 
ArticlePublisher: UK : Wiley, September 2005Subject(s): Corporate performance | Sustainability | Profitability | Industry structure | Business strategyTotal Quality Management & Business Excellence 26, 9, p. 873 - 880Abstract: The Strategic Management Journal has published a series of articles on variation in business-segment performance. This comment addresses the insights and potential sources of confusion in the decomposition literature, with a particular focus on Ruefli and Wiggins (2003). We review the basic purpose of descriptive decomposition techniques and argue that they offer no information about the drivers of business performance or the mechanisms by which performance is generated. The techniques in the literature do not rely on ceteris paribus assumptions or a mapping between managerial influence and corporate effects. The estimated effects of industry, business segments, and corporate parents need not be independent to be modeled using variance decomposition. The comment also focuses on the distortions in estimates that can arise when the underlying sample of data does not represent the population accurately.
The Strategic Management Journal has published a series of articles on variation in business-segment performance. This comment addresses the insights and potential sources of confusion in the decomposition literature, with a particular focus on Ruefli and Wiggins (2003). We review the basic purpose of descriptive decomposition techniques and argue that they offer no information about the drivers of business performance or the mechanisms by which performance is generated. The techniques in the literature do not rely on ceteris paribus assumptions or a mapping between managerial influence and corporate effects. The estimated effects of industry, business segments, and corporate parents need not be independent to be modeled using variance decomposition. The comment also focuses on the distortions in estimates that can arise when the underlying sample of data does not represent the population accurately.
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