A RESOURCE-GRADIENT THEORY OF INDUSTRY COMPETITION GROUPS AND THE STOCK RETURN METHOD

McGee and Thomas (1986) and Barney and Hoskisson (1990) conclude that there are a number of significant limitations to the theory and empirical research underlying strategic group theory, an approach primarily developed by Porter (1976, 1979, 1980) and Caves and Porter (1977) in the context of industrial organization (IO) economics. Recently the narrow performance orientation of the IO view of industry structure has been broadened to include a number of alternative theoretical bases for subgrouping by Thomas and colleagues (Porac and Thomas, 1990; Tang and Thomas, 1992; Bogner and Thomas, 1993; Bogner, Mahoney, and Thomas, 1993)—tending toward a nichebased theory sensitive to competitors and environmental opportunities. A cognitive taxonomic variant has been added by Reger (1990), Reger and Huff (1993), and Peteraf and Shanley (1993). Two problems are apparent: (1) A coherent theory of industry groupings has evaporated; and (2) Empirical methods for testing the efficacy of either the original IO view or the more recent alternatives remain unresolved. As Barney and Hoskisson (1990: 190) observe, “Given the limitations of cluster analysis as a way to test the existence of strategic groups, one is forced to wonder whether strategic groups really exist, or are an artifact of clustering analysis. ” Despite this pessimism about the reality of strategic groups and the soundness of the empirical findings, the fundamental importance of better understanding questions about the structure of industry phenomena cannot be diminished. Barney and Hoskisson observe that “few concepts have caught the interest of strategic management theorists as much as the concept of strategic groups” (1990: 187). Nonetheless, they conclude that industrylevel strategic group theory may be replaced by the firmlevel resource-based (RB) view (Wernerfelt, 1984; Teece, 1984; Barney, 1986, 1989, 1991; Rumelt, 1987; Prahalad and Hamel, 1990; Reevis-Conner, 1991; Teece, Pisano, and Schuen, 1994). In contrast, Bogner, Mahoney, and Thomas reaffirm an industry-level “integrative economic, behavioral, and cognitive perspective” (1993: 23). At the heart of this theoretical debate is the theory of how firms actually compete, survive, and gain rents, given the common resource pool commensurate with a market segment. We propose a revised theory of industry substructure, sensitive to both industryand firm-level concerns, having its roots in evolutionary ecology (Pianka, 1994). Specifically, we focus on two elements of biological and organizational competition theory: (1) The “principle of competitive exclusion” (Gause, 1934; Henderson, 1989), suggesting that a population of firms may compete by becoming more homogeneous, subsequently raising barriers, and colluding (IO theory), thus creating a basis of excluding other firms; and (2) The “principle of resource partitioning” (Lack, 1971; Carroll, 1985), suggesting that a population of firms may compete by becoming more heterogeneous from developing resource and competence differences and advantages (RB theory), that is, by shifting positions along a niche-based resource gradient. In light of the failure to find natural groupings (Barney and Hoskisson, 1990) and the artifactuality of the F-test as a significance test for clusters (Johnson, 1995), the empirical resolution of the theory issues still remains out of reach. Therefore, we introduce the stock return method of identifying groups, showing evidence that it can produce groups reflecting statistically significant structure within the data. Our method incorporates several improvements over the approach as initially developed by Ryans and Wittink (1985)—specifically statistical significance and objective stopping rules. It avoids many of the empirical pitfalls identified by McGee and Thomas (1986) and Barney and Hoskisson (1990). In Section 2 we review grouping theories and develop an integrative theory of industry substructure. We review empirical problems in Section 3 and develop the stock return method. In Section 4 we describe the data and analytical methods. Results are discussed in Section 5. Conclusions follow in Section 6.