Performance evaluation of purchasing and supply management using value chain DEA approach

Saranga, Haritha; Moser, Roger

doi:10.1016/j.ejor.2010.04.023

Cited by 81 publications

(68 citation statements)

References 22 publications

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“…These organizations represent various sectors including banking, IT investment, purchasing and supply management (PSM), and sports [32,[35][36][37]. Recently, Cao and Yang [38] applied the two-stage DEA model when measuring the productivity of internet-based companies.…”

Section: Two-stage Dea Model For Analyzing Innovation and Commercialimentioning

confidence: 99%

Labor Union Effects on Innovation and Commercialization Productivity: An Integrated Propensity Score Matching and Two-Stage Data Envelopment Analysis

et al. 2015

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Abstract:Research and development (R&D) is a critical factor in sustaining a firm's competitive advantage. Accurate measurement of R&D productivity and investigation of its influencing factors are of value for R&D productivity improvements. This study is divided into two sections. The first section outlines the innovation and commercialization stages of firm-level R&D activities. This section analyzes the productivity of each stage using a propensity score matching (PSM) and two-stage data envelopment analysis (DEA) integrated model to solve the selection bias problem. Second, this study conducts a comparative analysis among subgroups categorized as labor unionized or non-labor unionized on productivity at each stage. We used Korea Innovation Survey (KIS) data for analysis using a sample of 400 Korean manufacturers. The key findings of this study include: (1) firm innovation and commercialization productivity are balanced and show relatively low innovation productivity; and (2) labor unions have a positive effect on commercialization productivity. Moreover, labor unions are an influential factor in determining manufacturing firms' commercialization productivity. OPEN ACCESSSustainability 2015, 7 5121

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Section: Two-stage Dea Model For Analyzing Innovation and Commercialimentioning

confidence: 99%

Labor Union Effects on Innovation and Commercialization Productivity: An Integrated Propensity Score Matching and Two-Stage Data Envelopment Analysis

et al. 2015

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“…Liu and Liu (2010) illustrate the use of DEA in evaluating and ranking the research and redevelopment performance of Taiwan's government-supported research institutes. Saranga and Moser (2010) develop a comprehensive performance measurement framework using the classical and two-stage value chain DEA model.…”

Section: Previous Studies On Application Of Dea To Assess the Financimentioning

confidence: 99%

Evaluating loans using variable benchmark data envelopment analysis

Malhotra

Tsetsekos

2016

IJBISE

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Loan officers use many business intelligence methods to screen consumer loan applications besides intuitive judgement and experience. They also use mathematical techniques such as credit-scoring models, traditional statistical models, and artificial intelligence methods such as expert systems, artificial neural systems, and fuzzy logic. This study illustrates the development of a decision support system using variable benchmark data envelopment analysis model to predicting bad loans. Further, the study also compares the performance of the DEA model with linear discriminant analysis model. The study illustrates the viability of the variable benchmark DEA model that outperforms the linear discriminant analysis model.

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“…Second, it can contextualise and make allowances for factors that are outside the control of management but affect the performance of supply chain members. Third, it can help management to establish informed improvement targets (Charnes et al 1994;Liu et al 2000;Saranga and Moser 2010). This paper demonstrates a novel application of how DEA can be used to facilitate the development of a diagnostic reference tool to analyse the supply chain performance of product value streams (business units) operating within a supply chain network.…”

Section: Introductionmentioning

confidence: 99%

“…The motivation for this research stems firstly from the increasing recognition within the SCM literature of the critical influence of uncertainty on the efficiency, effectiveness and flexibility of supply chains (Koutsoukis et al 2000; Van der Vorst and Beulens 2002;Lockamy et al 2008), secondly from the paucity of empirical research examining the influence of uncertainty on supply chain performance, and thirdly from the perceived advantages offered by the DEA technique for developing a diagnostic reference tool for comparative performance assessment (Talluri and Baker 2002;Saranga and Moser 2010).…”

Section: Introductionmentioning

confidence: 99%

An environmental uncertainty-based diagnostic reference tool for evaluating the performance of supply chain value streams

Gallear

Ghobadian

et al. 2013

Production Planning & Control

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This research has responded to the need for diagnostic reference tools explicitly linking the influence of environmental uncertainty and performance within the supply chain. Uncertainty is a key factor influencing performance and an important measure of the operating environment. We develop and demonstrate a novel reference methodology based on the data envelopment analysis (DEA) for examining the performance of value streams within the supply chain with specific reference to the level of environmental uncertainty they face. In this paper, using real industrial data, 20 product supply value streams within the European automotive industry sector are evaluated. Two are found to be efficient. The peer reference groups for the underperforming value streams are identified and numerical improvement targets are derived. The paper demonstrates how DEA can be used to guide supply chain improvement efforts through role-model identification and target setting, in a way that recognises the multiple dimensions/outcomes of the supply chain process and the influence of its environmental conditions. We have facilitated the contextualisation of environmental uncertainty and its incorporation into a specific diagnostic reference tool.

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Performance evaluation of purchasing and supply management using value chain DEA approach

Cited by 81 publications

References 22 publications

Labor Union Effects on Innovation and Commercialization Productivity: An Integrated Propensity Score Matching and Two-Stage Data Envelopment Analysis

Labor Union Effects on Innovation and Commercialization Productivity: An Integrated Propensity Score Matching and Two-Stage Data Envelopment Analysis

Evaluating loans using variable benchmark data envelopment analysis

An environmental uncertainty-based diagnostic reference tool for evaluating the performance of supply chain value streams

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