Assessment of performance using MPSS based DEA

Sarkar, Subhadip

doi:10.1108/bij-02-2014-0012

Cited by 6 publications

(13 citation statements)

References 11 publications

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“…Quoting from the earlier research of Sarkar (2014a, 2014b, 2017, 2019) Figure 1 is revisited to enumerate the importance of such eigenvectors. Let there be a number of firms which utilise land (L) and capital (K) as inputs to generate unit amount of an output.…”

Section: Normalised Multi-dimensional Herfindahl–hirschman Indexmentioning

confidence: 99%

“…Let there be column vector ∅ such that ∅= λ+β Y T Y Y T −1 g y is possible. The matrix Y Y T is a positive definite symmetric & as per Sarkar, S. (2014a), the first Principal Eigen vector of Y Y T certainly has the nonnegative property. Moreover, similar Eigenvector appears as one analyses the matrix Y Y T −1.…”

Section: Measurement Of Competitiveness Using Output Oriented Ddf Modelmentioning

confidence: 99%

“…Hence, it is aborted. On the contrary, if in case the crisis is better be handled through the input lists (for example, performance assessment of private primary schools mentioned by Sarkar (2014a) then the output oriented model should be replaced by an input oriented model.…”

Section: Measurement Of Competitiveness Using Output Oriented Ddf Modelmentioning

confidence: 99%

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Assessment of Competitive Position of a Firm Using a Multi-dimensional Herfindahl–Hirschman Index and Linear Additive Directional Distance Function

Sarkar

2019

The Indian Economic Journal

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Herfindahl–Hirschman has been one of the renowned techniques for the measurement of market concentration. This article proposes an assessment of concentration with the aid of a matrix termed as a multi-dimensional Herfindahl–Hirschman index for a set of outputs which are possibly categorised under line items. The extant research is aimed to achieve the sole objective of investigating and obtaining a direction vector for augmenting the market share of a firm in a specified manner to strengthen the competitive position. The first eigenvector computed from the normalised non-centred covariance matrix of output set is found to be carrying high degree of explanation of the market concentration. Directional distance additive model (DDAM) is applied to detect the peer firm while replacing the input–output vector of a firm with its vector of market share due to these inputs and outputs. The first eigenvector of the above stated covariance matrix is proved to be a legitimate direction vector which is inherited by the DDAM itself. Benefits of this model is illustrated finally with the aid of an example.

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Section: Normalised Multi-dimensional Herfindahl–hirschman Indexmentioning

confidence: 99%

Section: Measurement Of Competitiveness Using Output Oriented Ddf Modelmentioning

confidence: 99%

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Assessment of Competitive Position of a Firm Using a Multi-dimensional Herfindahl–Hirschman Index and Linear Additive Directional Distance Function

Sarkar

2019

The Indian Economic Journal

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“…The reason for calling it "cost" or "combined spending" is that the firm would like to concentrate on the curtailing down such expenditure in comparison to others rivals and will consume less ingredients. A DMU which has a minimal projection on this vector must be an efficient DMU (Sarkar, 2014(Sarkar, , 2015. Remaining (p−1) dimensions (which reflect unique capacity of a firm) are indeed essential to gain various competitive advantages.…”

Section: Detection Of Costmentioning

confidence: 99%

“…In absence of the input price information, the present model applies a non-central PCA to understand the direction of the existing major variations in specific resource consumption ( for any one output) due to all existing rivals in the market. The first principal vector of a specific covariance matrix of an output is found essential for framing the cost function, whereas the remaining principal vectors signify several other attributes essential for gaining competitive advantage (Sarkar, 2014(Sarkar, , 2015.…”

Section: Introductionmentioning

confidence: 99%

Detection of cost leaders using non-central principal component analysis and data envelopment analysis

Sarkar

2019

BIJ

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Purpose The purpose of this paper is to express the strategic positioning of a firm among its rivals based on an overall analysis. The proposed model uses data envelopment analysis (DEA) to determine the indexes due to cost leadership and differentiation. The model can be useful to identify the true cost leaders and those who are stuck in the middle. This work suggests the way how the strategic position can be explored from the consumption of resources (unlike the prevalent models like Banker et al., 2014). Design/methodology/approach Depending on the previous surveys, two inputs (spending per student and percentage of non-poor income group) and two outputs (average scores attained by students in science group and in language group in six private schools, located within the outskirt of Durgapur) were analyzed. Findings The classification made on the basis of the result of the proposed model reveals that out of the six schools (A, B, C, D, E and F), A, E and F occupy a strong position in this context, whereas B can be an example of stuck in the middle scenario. It not only has to reduce cost by 30 percent but also improve the differentiation index by 140 percent. C and D are lagging behind as they do not have enough differentiating qualities. Research limitations/implications Only six schools were taken for the analysis. Second, the input and output vectors had to be non-negative. In case of a negative input (output) set, separate treatment must be applied to them before the application of non-central PCA. Any decision-making unit producing an output of 0 will prohibit the use of the non-central PCA. Practical implications The extant study provides the indices to measure cost leadership and differentiation strategies for the classification as per the generic strategies. A firm which is lagging behind can adjust its consumption to remain successful. Social implications According to Hillman and Jenkner (2002), the developing countries lack the willingness of a primary school to impart education to children. The current study is used to explore whether any private primary school has the same goal or not. They also pointed out the possible future consequences while stating that the cost of educating children from the poorer section might be outweighed by the cost of not educating them and adults lacking basic skills had greater difficulty in finding well-paying jobs to escape poverty. So it is important to understand the role of a private primary school to offer seats to underprivileged students for educating them. The intention of six private primary schools toward educating the population of the small area within Durgapur is analyzed in this study, The study revealed that few schools spend more to serve the students belonging to upper classes to remain successful, whereas few schools as a differentiator make conscious attempts for providing services to poorer sections in an economical manner like a cost leader. Originality/value The extant research aims to formulate the determining methods of identifying strategic groups (proposed by Hunt, 1983) to make a parity between business definition view and strategic type concepts. The model can assess the rivals within an industry to explore the true cost leaders and those who are stuck in the middle using DEA. There are not enough kinds of literature which could effectively measure them.

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A Robust Optimization Approach for Estimating the Most Productive Scale Size in Uncertain Data Envelopment Analysis

Peykani,

Hamidzadeh,

Pishvaee

et al. 2024

Infosys Science Foundation Series

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Assessment of performance using MPSS based DEA

Cited by 6 publications

References 11 publications

Assessment of Competitive Position of a Firm Using a Multi-dimensional Herfindahl–Hirschman Index and Linear Additive Directional Distance Function

Assessment of Competitive Position of a Firm Using a Multi-dimensional Herfindahl–Hirschman Index and Linear Additive Directional Distance Function

Detection of cost leaders using non-central principal component analysis and data envelopment analysis

A Robust Optimization Approach for Estimating the Most Productive Scale Size in Uncertain Data Envelopment Analysis

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