Measurement of Firm Diversification: Is It Robust?

Chatterjee, Sayan; Blocher, James D.

doi:10.5465/256320

Cited by 42 publications

(48 citation statements)

References 9 publications

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“…see Chatterjee and Blocher, 1992;Hoskisson, Hitt, Johnson & Moesel, 1993;Lubatkin, Merchant & Srinivasan, 1993;Hall & St. John, 1994;Montgomery, 1982;Pitts and Hopkins, 1982;Robins & Wiersema, 2003 for extensive reviews and comparison), which overall suggest thatalthough the different measures are characterized by a good level of consistency-they tend to capture slightly different aspects of the phenomenon and should be used accordingly.…”

Section: Insert Table 2 Here ----------------------------------The Mementioning

confidence: 99%

“…The high efficiency of SIC-based count measures is noted Pitts and Hopkins, 1982 Comparison between business-count versus category-based measures. Business count measures appear to be more suitable for research comparing diversified and non-diversified firms but not for explaining the difference among diversified firms Chatterjee and Blocher, 1992 Comparison of convergent and predictive validity of Rumelt's categorical classification and continuous measures of diversification (Herfindhal, weighted and entropy indexes). Not strong convergent validity of Rumelt's measures.…”

Section: Contingent Variable Illustrative Studies Core Findingsmentioning

confidence: 99%

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Redirecting Research Efforts on the Diversification–Performance Linkage: The Search for Synergy

Ahuja

Novelli

2017

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This is the accepted version of the paper.This version of the publication may differ from the final published version. Permanent repository link AcknowledgmentsThe authors would like to thank the editors and reviewers for their very constructive and insightful comments through the review process. Elena Novelli also gratefully acknowledges the financial support of the ESRC Future Research Leaders Scheme (Grant ES/K001388/1) and Cass Business School. Gautam Ahuja would like to thank the University of Michigan for support. 2 AbstractWe review the literature on the diversification-performance (D-P) relationship to a) propose that the time is ripe for a renewed attack on understanding the relationship between diversification and firm performance, and b) outline a new approach to attacking the question.Our paper makes four main contributions. First, through a review of the literature we establish the inherent complexities in the D-P relationship and the methodological challenges confronted by the literature in reaching its current conclusion of a non-linear relationship between diversification and performance. Second, we argue that to better guide managers the literature needs to develop along a complementary path -whereas past research has often focused on answering the big question of does diversification affect firm performance, this second path would focus more on identifying the precise micro-mechanisms through which diversification adds or subtracts value. Third, we outline a new approach to the investigation of this topic, based on (a) identifying the precise underlying mechanisms through which diversification affects performance; (b) identifying performance outcomes that are "proximate" to the mechanism that the researcher is studying, and (c) identifying an appropriate research design that can enable a causal claim. Finally, we outline a set of directions for future research.3

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Section: Insert Table 2 Here ----------------------------------The Mementioning

confidence: 99%

Section: Contingent Variable Illustrative Studies Core Findingsmentioning

confidence: 99%

Redirecting Research Efforts on the Diversification–Performance Linkage: The Search for Synergy

Ahuja

Novelli

2017

ANNALS

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“…It is also open to possible bias due to the subjective nature of the relatedness judgments, which may lead different researchers to place the same firms in different diversification categories (Chatterjee and Blocher, 1992).…”

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confidence: 99%

A General Interindustry Relatedness Index

2009

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For empirical work in the resource-based view of the firm, characterizing the resources that are responsible for firm growth is difficult because valuable resources are often tacit, ambiguous, or difficult to identify. This is a particular problem for empirical assessments that rely upon the concept of relatedness between resources to characterize the direction of growth of the firm. We tackle the problem for the general case by developing a general interindustry relatedness index. The index harnesses the relatedness information embedded in the multiproduct organization decisions of every diversified firm in the U.S. manufacturing economy. The index is general in that it can be used across industry contexts without requiring explicit identification of resources and it provides a percentile relatedness rank for every possible pair of four-digit Standard Industrial Classification manufacturing industries. The general index is tested for predictive validity and found to perform as expected. Applications of the index in strategy research are suggested. The research program of the Center for Economic Studies (CES) produces a wide range of theoretical and empirical economic analyses that serve to improve the statistical programs of the U.S. Bureau of the Census. Many of these analyses take the form of CES research papers. The papers are intended to make the results of CES research available to economists and other interested parties in order to encourage discussion and obtain suggestions for revision before publication. The papers are unofficial and have not undergone the review accorded official Census Bureau publications.The opinions and conclusions expressed in the papers are those of the authors and do not necessarily represent those of the U.S. Bureau of the Census. Republication in whole or part must be cleared with the authors. All papers are screened to ensure that they do not disclose confidential information. A GENERAL INTER-INDUSTRY RELATEDNESSPersons who wish to obtain a copy of the paper, submit comments about the paper, or obtain general information about the series should contact Sang V. Nguyen, Editor AbstractFirm growth and expansion is widely believed to be guided by the desire to leverage existing resources. But which resources? The answer depends largely on context-the peculiarities of industries, firms, technologies, production, customers, and a host of other dimensions. This fact makes pointing to any particular set of resources as the source of expansion decisions potentially problematic and makes more difficult tests of theories such as the resource-based view of the firm. This paper tackles the problem by developing a general inter-industry relatedness index that can be usefully applied across industry and firm contexts. The index harnesses the relatedness information embedded in the multi-product organization and diversification decisions of every firm in the US manufacturing economy. The index is general in that it implicitly varies the underlying resources upon which expansion proc...

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“…Montgomery (1982) found that categorical measurement was relevant to continuous measurement. Chartterjee and Blocher (1992) and Hoskisson et al (1993) also found that Rumelt's categorical measurement has high content validity in certain areas. However, shortcomings of the measurement were also revealed.…”

Section: Categorical Measuresmentioning

confidence: 99%

“…The measurement was widely adopted by researchers (Bettis, 1981;Christensen and Montgomery, 1981;Montgomery, 1982Montgomery, , 1985Chartterjee and Blocher, 1992;Hoskisson et al, 1993). Montgomery (1982) found that categorical measurement was relevant to continuous measurement.…”

Section: Categorical Measuresmentioning

confidence: 99%