Imprecise DEA framework for evaluating health-care performance of districts

Karsak, E. Ertuğrul; Karadayı, Melis Almula

doi:10.1108/k-05-2015-0139

Cited by 18 publications

(12 citation statements)

References 59 publications

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“…This led to the specific DEA method suggestion by Charnes, Cooper and Rhodes in 1978 [68]. Advantages of the increasing use in management research are the facts that no a priori existing knowledge of a production function is required, only real-life data is used (no hypothetical production function or efficiency values); and a multitude of inputs can be combined with a multitude of outputs, which is very typical for LSP as complex and high-level service providers as well as other service industries like health care or higher education [69][70][71][72][73].…”

Section: Efficiency Measurementmentioning

confidence: 99%

How to Achieve Supply Chain Sustainability Efficiently? Taming the Triple Bottom Line Split Business Cycle

Klumpp

2018

Sustainability

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For sustainable supply chains, specific concepts regarding how to efficiently improve sustainability are needed in a global comprehensive triple bottom line (TBL) approach, especially for forwarders as central actors in supply chain design. Such specific advice is provided by reporting empirical DEA Malmquist index findings from seven large European forwarders regarding a TBL sustainability analysis from 2006 to 2016. A major obstacle in improving sustainability consists in the newly discovered fact that with the business cycle, the three TBL areas of economic, ecologic and social objectives for logistics are undergoing different up-and down-ward trends, making it very hard to improve all three simultaneously. Additional factors are identified in the characteristics of size and government influence regarding the sustainability efficiency of forwarders. This has important impacts on supply chain design like e.g., with selection criteria.

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Section: Efficiency Measurementmentioning

confidence: 99%

How to Achieve Supply Chain Sustainability Efficiently? Taming the Triple Bottom Line Split Business Cycle

Klumpp

2018

Sustainability

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“…The study in [136] applied similar data reduction methods and evaluated deregulated airline networks to measure the quality of Western European airports. Reference [137] proposed a new DEA framework to evaluate the healthcare performance of different districts in Istanbul, Turkey. They suggested an imprecise data envelopment analysis approach, which sets forth a more realistic decision methodology for evaluating the relative health-care performance and enables the determination of the best district in terms of health-care performance in Istanbul.…”

Section: Literature Reviewmentioning

confidence: 99%

An integrated Multi-Criteria Decision Making Model for Sustainability Performance Assessment for Insurance Companies

et al. 2020

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To stay competitive in a business environment, continuous performance evaluation based on the triple bottom line standard of sustainability is necessary. There is a gap in addressing the computational expense caused by increased decision units due to increasing the performance evaluation indices to more accuracy in the evaluation. We successfully addressed these two gaps through (1) using principal component analysis (PCA) to cut the number of evaluation indices, and (2) since PCA itself has the problem of merely using the data distribution without considering the domain-related knowledge, we utilized Analytic Hierarchy Process (AHP) to rank the indices through the expert’s domain-related knowledge. We propose an integrated approach for sustainability performance assessment in qualitative and quantitative perspectives. Fourteen insurance companies were evaluated using eight economic, three environmental, and four social indices. The indices were ranked by expert judgment though an analytical hierarchy process as subjective weighting, and then principal component analysis as objective weighting was used to reduce the number of indices. The obtained principal components were then used as variables in the data envelopment analysis model. So, subjective and objective evaluations were integrated. Finally, for validating the results, Spearman and Kendall’s Tau correlation tests were used. The results show that Dana, Razi, and Dey had the best sustainability performance.

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“…However, in addition to the study by Alinezhad et al (2013), there are few literatures that integrated the interval data or imprecise information into the Six Sigma project selection process. Since Cooper et al (1999) proposed the imprecise data envelopment analysis (IDEA), substantial researchers, such as Karsak and Karadayi (2017), Yu and Hou (2016) and Zhu (2003, studied the methods to deal with the uncertain data in DEA). In this paper, the DEA method is also used to deal with the optimal Six Sigma project selection problem in the absence of the interval data.…”

Section: Five Phases Of Dmaic Phase Descriptionmentioning

confidence: 99%

“…Yu and Hou (2016) proposed a super-efficiency IDEA model with interval data based on cross-evaluation. Karsak and Karadayi (2017) presented an IDEA framework that considered qualitative and quantitative data for evaluating the healthcare performance of 26 districts in Istanbul. They used weight restricts IDEA model to evade the unrealistic weight flexibility and improve the discriminating power.…”

Section: Selection Of Six Sigma Projectmentioning

confidence: 99%

Selection of Six Sigma project with interval data: common weight DEA model

Wen

et al. 2018

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Purpose This paper aims to prioritize the most efficient Six Sigma project that can generate the greatest benefit to the organization, according to the relative performance among a set of homogenous projects (in here, DMUs). The selection of a Six Sigma project is a multiple-criteria decision-making problem, which is difficult in practice because the projects are not yet complete and the values of evaluation indicators are often interval or imprecise data. Managers stress the need for developing an effective performance evaluation methodology for selecting a Six Sigma project. Design/methodology/approach This study proposes a modified model considering interval or imprecise data based on common weight data envelopment analysis (DEA) approach to solve problems on project selection. Findings By comparing its findings with an example from a previous study, the new model obtained realistic and fair evaluation results and significantly reduced the difficulties and the time spent during calculation. Moreover, not only the best project is identified, but also the exact indicator information is obtained. Originality/value This study solves the problem of selecting the most efficient Six Sigma project in the preference of interval or imprecise data. Many studies have shown how a Six Sigma project is chosen, but only a few have integrated interval data into the selection process.

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Imprecise DEA framework for evaluating health-care performance of districts

Cited by 18 publications

References 59 publications

How to Achieve Supply Chain Sustainability Efficiently? Taming the Triple Bottom Line Split Business Cycle

How to Achieve Supply Chain Sustainability Efficiently? Taming the Triple Bottom Line Split Business Cycle

An integrated Multi-Criteria Decision Making Model for Sustainability Performance Assessment for Insurance Companies

Selection of Six Sigma project with interval data: common weight DEA model

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