Please use this identifier to cite or link to this item: https://scholarbank.nus.edu.sg/handle/10635/44962
DC FieldValue
dc.titleStrategic leaders or strategic groups: A longitudinal data envelopment analysis of the U.S. brewing industry
dc.contributor.authorDay, D.L.
dc.contributor.authorLewin, A.Y.
dc.contributor.authorLi, H.
dc.date.accessioned2013-10-10T04:38:48Z
dc.date.available2013-10-10T04:38:48Z
dc.date.issued1995
dc.identifier.citationDay, D.L.,Lewin, A.Y.,Li, H. (1995). Strategic leaders or strategic groups: A longitudinal data envelopment analysis of the U.S. brewing industry. European Journal of Operational Research 80 (3) : 619-638. ScholarBank@NUS Repository.
dc.identifier.issn03772217
dc.identifier.urihttp://scholarbank.nus.edu.sg/handle/10635/44962
dc.description.abstractThis paper builds on strategic group theory which was originally introduced to help explain the observed variation in firm profitability across an industry. This paper applies Data Envelopment Analysis (DEA) to identify both strategic leaders, the 'best practice' players in the industry, and strategic groups to examine which are the source of the most sustained heterogeneity in the performance of U.S. brewers. Contrary to the prevalent research approach in Strategy and Organization research which places a premium on empirical analyses that maximize explanation of average behavior (Daft and Lewin, 1990), this paper examines extremal observations as a means of studying or inducing theories about best practice, such as best strategies or most effective organization design (Lewin and Minton, 1986). The paper argues that significant insights, new knowledge, and unexpected theories can arise from studying the best or worst of a population. The paper applies DEA to a longitudinal reanalysis of U.S. brewing data to demonstrate its usefulness for obtaining new insights from identifying and studying industry outliers. The paper raises important questions about the construct of strategic groups and illustrates how competing theories can be deduced and analyzed for explaining performance heterogeneity in the U.S. brewing industry. © 1995.
dc.sourceScopus
dc.typeArticle
dc.contributor.departmentDECISION SCIENCES
dc.description.sourcetitleEuropean Journal of Operational Research
dc.description.volume80
dc.description.issue3
dc.description.page619-638
dc.description.codenEJORD
dc.identifier.isiutNOT_IN_WOS
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