Strategic Leaders in the U.S. Brewing Industry: A Longitudinal Analysis of Outliers

Day, D.B.; Lewin, Arie Y.; Li, Hongyu; Salazar, Ronald J.

doi:10.1007/978-94-011-0637-5_11

Cited by 15 publications

(16 citation statements)

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“…The applications continue to become more sophisticated and recent studies have focused on revenue transfers (local aid) (Ali et al 1993), total quality management (TQM) (Bailey 1993), benchmarking and identification of best practice (Collier and Storbeck 1993;Chilingerian 1995; Golany and Thore forthcoming), forcasting bank failures (Barr et al 1993(Barr et al , 1994Siems 1991), strategy (Day et al 1994(Day et al , 1995 Ali and Lerme forthcoming), pollution , improved performance indexes in sports (Anderson and Sharp forthcoming), and X-efficiency (Bohnet and Beck 1990;Frantz 1992;Leibenstein and Maital 1992). At the same time DEA has moved from being an esoteric research methodology to a more mainstream analytical tool as evidence by (1) its inclusion in an introductory MBA OR textbook (Anderson, Sweeney, and Williams 1991), and (2) its being featured in Fortune magazine (Norton 1994).…”

Section: State Of the Art Circa 1995mentioning

confidence: 99%

Data envelopment analysis: The evolution of the state of the art (1978?1995)

1996

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The purpose of this paper is to briefly trace the evolution of DEA from the initial publication by Charnes et al. (1978b) to the current state of the art (SOA). The state of development of DEA is characterized at four points in time to provide a perspective in both directions-past and f&ue. An evolution map is provided which illustrates DEA growth during the 17year period, the timing of the major events, and the interconnections and influences between topics. An extensive DEA bibliogmphy is provided.

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Section: State Of the Art Circa 1995mentioning

confidence: 99%

Data envelopment analysis: The evolution of the state of the art (1978?1995)

1996

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“…However, as far as we know, previous literature using the DEA method ology to determine strategic groups is truly scarce. Day et al (1994Day et al ( , 1995 reveal the indubitable advantages of this technique. In particular, they highlight the capacity to consider multiple outputs or the establishment of a nexus between inputs and output when firms pursue multiple objectives.…”

Section: Introductionmentioning

confidence: 99%

“…The second problem identified is that the methodology for treating the data is inadequate (Ketchen and Shook, 1996); and the habitual use of Cluster Analysis is criticised (Thomas and Ven katraman, 1988;Barney and Hoskisson, 1990). Day et al (1994Day et al ( , 1995 illustrate the crucial weak ness of this technique by showing that when firms are designing strategies; in fact, managers cognise a causal model (i.e. a transformation function) relating, in a more or less conscious manner, oper ational decisions with the attainment of an objec tive function.…”

Section: Introductionmentioning

confidence: 99%

“…a transformation function) relating, in a more or less conscious manner, oper ational decisions with the attainment of an objec tive function. Furthermore, Day et al (1994Day et al ( , 1995 report that firms are typically driven by mul tiple goals: not just profit maximization. There fore, Cluster Analysis is an inadequate technique because (i) it does not capture the multidimensio nality of strategy; (ii) it does not take into account the relative importance of the key decision varia bles (Hatten and Hatten, 1987); and (iii) because it does not allow the incorporation the inherent causality of the definition of strategy (Thomas and Venkatraman, 1988).…”

Section: Introductionmentioning

confidence: 99%

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Strategic groups based on marginal rates: An application to the Spanish banking industry

Prior

Surroca

2006

European Journal of Operational Research

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This paper uses Data Envelopment Analysis (DEA) to identify strategic groups (SGs) in the Spanish banking industry. The concept of SG relies on the fact that firms grouped together value inputs and outputs in the same way. As such, they take identical direction when, due to external influences, changes are required. Weights obtained from DEA are extremely useful in the valuation of inputs and outputs. Specifically, by comparing DEA weights pair-wise, i.e. quantifying the variablesÕ marginal rates (MR), we can obtain a very good representation of the existent trade-off and the relative importance of the two variables.The paper uses MRs obtained through DEA models and, simultaneously, proposes feasible ways to overcome two usual problems with DEA virtual weights, namely: (1) the multiplicity of weights for efficient DMUs; and (2) the inexistence of dual variables for inefficient DMUs.From the empirical point of view, once the MRs are determined, the second stage is to perform Cluster Analysis. We apply Cluster Analysis in two ways: (1) on the basis of the MRs; and (2) following the traditional application by running Cluster Analysis with the original variables. The results obtained show the advantages of using MRs instead of the standard application of Cluster Analysis.Summing up, the concept of SG is reinforced if we use refined methods to determine the existence of SGs. The results of the application of DEA models to observe the presence of SG in the Spanish banking industry offer interesting views on it.

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“…DEA has been used as a technique for identifying strategic groups previously in works such as Day et al [6] [5], in an application to the brewing industry in the United States, or that of Prior and Surroca [12] [13], for the Spanish banking sector.…”

Section: Methodsmentioning

confidence: 99%

Strategic Efficiency. An Example using Data Envelopment Analysis in the Spanish Ceramic Tiles Industry.

Marco-Serrano¹

2017

Preprint

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The strategic groups analysis, developed by Michael Porter [10] [11], is defined between the sectoral analysis and the individual competitors assessment. It allows to set groups of companies with similar strategies. Generally, a deep knowledge of the strategic characteristics of the companies is needed. Our proposal is focused on the public financial information extracted from the registered accounts. From this information, mixing the Data Envelopment Analysis based methodologies from Zhu [16] and Barr et al. [2], strategic groups are identified. For these aims, the 'strategic efficiency' concept is defined as the conjoint use of productive efficiency and (shareholder) value creation.

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Strategic Leaders in the U.S. Brewing Industry: A Longitudinal Analysis of Outliers

Cited by 15 publications

References 0 publications

Data envelopment analysis: The evolution of the state of the art (1978?1995)

Data envelopment analysis: The evolution of the state of the art (1978?1995)

Strategic groups based on marginal rates: An application to the Spanish banking industry

Strategic Efficiency. An Example using Data Envelopment Analysis in the Spanish Ceramic Tiles Industry.

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