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Article
Publication date: 1 January 2006

John Seydel

To provide decision makers (DMs) an option for addressing problems involving finite alternative sets and multiple criteria, where criterion weighting is difficult or impossible.

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Abstract

Purpose

To provide decision makers (DMs) an option for addressing problems involving finite alternative sets and multiple criteria, where criterion weighting is difficult or impossible.

Design/methodology/approach

The multicriteria decision problem is described, and a typically descriptive (rather than prescriptive) tool, data envelopment analysis (DEA), is summarized, along with a hypothetical but typical example of a multicriteria decision (vendor selection). The DEA approach is modified to incorporate weight constraints and is used to rank the available vendors. Results are compared with those from the use of a popular multicriteria decision tool (SMART) and a naïve averaging approach.

Findings

The modified DEA approach yields results very similar to those produced using SMART; these results are quite satisfactory in spite of the fact that DEA requires less involvement on the part of the DM. In addition, non‐dominant optima (a possible anomaly with DEA) are avoided, and often a single alternative, rather than a non‐dominated set, will result, thus providing a unique optimum.

Research limitations/implications

Results are based on the analysis of a single data set. Future investigation should examine the performance of the DEA approach when other data sets involving more like as well as more unlike alternatives are involved.

Practical implications

With DEA the burden on the DM is reduced, as the need for eliciting criterion weights is obviated. DEA should thus provide an acceptable alternative to prescriptive modeling tools when multiple DMs are involved and/or criterion weight determination is unfeasible.

Originality/value

This paper demonstrates how DEA, a tool used more typically in post hoc evaluations, can be used also, with some modifications, as a prescriptive decision support tool.

Details

Industrial Management & Data Systems, vol. 106 no. 1
Type: Research Article
ISSN: 0263-5577

Keywords

Book part
Publication date: 11 September 2020

Ronald Klimberg and Samuel Ratick

When comparing and evaluating performance, decision-makers are concerned with providing a range of effective, efficient, and fair measures that can yield representative relative…

Abstract

When comparing and evaluating performance, decision-makers are concerned with providing a range of effective, efficient, and fair measures that can yield representative relative rankings for the units being evaluated. In this chapter, we apply three multicriteria benchmarking modeling techniques – weighted linear combination, data envelopment analysis (DEA), and ordered weighted average (OWA) – to an example dataset to provide a quantitative assessment of performance. Evaluation of the results demonstrates that each of these techniques has relative strengths and shortcomings. To take advantage of the relative strengths, and avoid some of the shortcomings that we observed, we develop and assess a promising new methodological approach, the order rated effectiveness (ORE) model. ORE uses the OWA unit ratings within a DEA optimization framework to provide an overall relative performance assessment.

Article
Publication date: 12 February 2018

Hongwei Liu, Henry Tsai and Jie Wu

This study models cost-efficiency against revenue for hotels in the Pearl River Delta (PRD) – in Guangzhou, Hong Kong and Macau – by considering regional differences and weight…

Abstract

Purpose

This study models cost-efficiency against revenue for hotels in the Pearl River Delta (PRD) – in Guangzhou, Hong Kong and Macau – by considering regional differences and weight restrictions on revenue output.

Design/methodology/approach

The authors modified and applied a context-dependent assurance region data envelopment analysis (CAR-DEA) model in assessing the performance of 41 hotels in the PRD. The model considers the relationships among output variables and sets the revenue composition of the hotels as weight restrictions in accounting for the relative importance of different revenue sources.

Findings

When assessing the 41 hotels all together, those in Guangzhou outperformed the hotels in other two cities by showing better pure technical efficiency (PTE), while those in Macau had the best scale efficiency (SE). When the assurance region (AR) restriction was imposed, the hotels in Macau outperformed those in the other two cities by showing better SE. When considering regional differences, the Macau hotels ranked first in terms of both the average efficiency score and the overall ranking. All the sample hotels in Guangzhou and half of the sample hotels in Hong Kong and Macau exhibited increasing, constant and decreasing returns to scale.

Research limitations/implications

The research results are limited by data quality and the variables included in the models.

Practical implications

The study helps hotel practitioners in the PRD better assess their cost-efficiency performance by considering regional differences and operational parameters so as to strategically improve their performance.

Originality/value

This study improves upon previous hotel efficiency studies by considering the influence of different operational parameters across different localities. It can be extended to examine the performance of different calibers of hotels, restaurants or tourism entities located in various localities and possessing different operational characteristics.

Details

International Journal of Contemporary Hospitality Management, vol. 30 no. 2
Type: Research Article
ISSN: 0959-6119

Keywords

Article
Publication date: 17 June 2019

Kiran Mehta, Renuka Sharma and Vishal Vyas

This study aims to assign efficiency score and then ranking the Indian companies known for best practices to control carbon-emission in the environment. It is destined to…

Abstract

Purpose

This study aims to assign efficiency score and then ranking the Indian companies known for best practices to control carbon-emission in the environment. It is destined to benchmark one company for best performance on the basis of selected alternatives among its peer group companies.

Design/methodology/approach

The present study has used a hybrid model by applying data envelopment analysis (DEA)-technique for order performance by similarity to ideal solution (TOPSIS) to measure the efficiency and ranking of various decision units on the basis of specified variables.

Findings

The findings of DEA have given the best alternative or best decision-making unit (DMU) among the set of 25 DMUs considered for empirical testing. The DEA technique is used with TOPSIS, which is another popular multi-criteria decision model. The integrated DEA-TOPSIS model has helped to compute the efficiency score of all 25 DMUs of study and also provide a unique rank to each of the efficient unit identified with the help of DEA technique.

Practical implications

The findings of the study have provided Benchmark Company amongst the companies following best practices for saving energy and having best operating profits too. This benchmark business unit can be studied extensively by peer group companies to compare various parameters affecting their efficiency and profits both.

Social implications

The findings of the study will promote the socially responsible practices by corporate citizens and adopt the practices to reduce their carbon footprints. It will also suggest to socially responsible investors to select the benchmark and most efficient companies for investment purpose.

Originality/value

The study is original in terms of measuring efficiency and ranking of companies known for best practices for controlling their carbon footprints and suggesting a benchmark company to its peer group. Also, the integrated approach of using DEA-TOPSIS for such type of studies also makes it distinctive from earlier work done in the related field.

Details

Journal of Indian Business Research, vol. 11 no. 2
Type: Research Article
ISSN: 1755-4195

Keywords

Book part
Publication date: 12 April 2012

Yong Zha, Xixiang Ding, Liang Liang and Zhimin Huang

With rapid social development and deepening division of labor, more and more complex projects are required to be carried out in a team form. When evaluating team performance…

Abstract

With rapid social development and deepening division of labor, more and more complex projects are required to be carried out in a team form. When evaluating team performance, previous research has usually treated team as a united entity. However, the operating environment of the team has a significant impact on its members and the interaction between them greatly influences the team's efficiency. To better evaluate team performance, we propose a circle loop to illustrate the relationship between the operating environment of the team and its members. A two-stage DEA model with feedback is developed to evaluate the team performance, together with the efficiencies of the operating environment and team members as well as their impacts on overall efficiency. Various conditions of the team are discussed to illustrate that team performance depends on the assumption of the conditions.

Details

Applications of Management Science
Type: Book
ISBN: 978-1-78052-100-8

Article
Publication date: 16 January 2019

Anup Kumar and Rajiv R. Thakur

There has been a persistent debate on measures of efficiency and ranking procedures of higher education institutions (HEIs). Deriving absolute efficiency measures and their…

Abstract

Purpose

There has been a persistent debate on measures of efficiency and ranking procedures of higher education institutions (HEIs). Deriving absolute efficiency measures and their ranking provide a critical input for the society to choose the appropriate educational institute. The purpose of this paper is to evaluate the relative performance of institutions in management education in different locations in India and propose a holistic efficiency measurement which can be applied to HEIs in general.

Design/methodology/approach

This study uses dynamic data envelopment analysis (DDEA) as the primary methodology of analysis. Multiple measures of inputs and output have been defined to assess efficiency in institutions of management education. Some of the output variables used for measuring relative effectiveness are: the number of students placed, number of entrepreneurs, median CTC of placed students, total number of students passed, number of research publications, number of students and faculty who have participated in international exchange, input variables used, student intake, faculty profile, resource allocation on the development of student, faculty and staff, industry linkages, alumni network. The institutions under study are in three different locations in India, having distinct characteristics. The multiple measures of inputs and outputs defined have been used to measure efficiency, following which DDEA was used to rank the efficiency measures.

Findings

Various agencies use their framework to evaluate and rank HEIs; however, they are either subjective or less researched methodologies. The proposed method acts as a new researched and objective methodology for ranking of HEIs operating across regions with different societal, economic and political contexts. Efficiency in education is of high relevance today for various stakeholders such as students, parents, industry, policy-makers and government. An objective, such as the one proposed in this paper, would be helpful in satisfying the needs of various stakeholders. Furthermore, the government has policies of allocating funds, in case of public-funded institutions, based on efficiency levels in HEIs. The measure using DDEA suggested in this study provides a better measurement of efficiency.

Research limitations/implications

This research is based on the extension of DDEA with slight modification to the denominator portion of efficiency calculation. The modification is accentuated by taking an industry benchmark or government benchmark. This may lead to slight difficulty in the appropriation of input parameters. Hence, selection of appropriate input and output parameters is the key limitation. To demonstrate capabilities of the proposed approach, this framework is implemented for performance evaluation of institutions of higher education in India. Some helpful policy-making and managerial insights are derived from the numerical results.

Originality/value

The uniqueness of this research is that it adds a well-researched methodology based on DDEA to measure efficiency and rank HEIs for effective assessment and benchmarking. The frameworks used so far have been either subjective or less researched methodologies.

Details

International Journal of Productivity and Performance Management, vol. 68 no. 4
Type: Research Article
ISSN: 1741-0401

Keywords

Article
Publication date: 15 March 2011

F. Jalalvand, E. Teimoury, A. Makui, M.B. Aryanezhad and F. Jolai

The purpose of this paper is to develop a method to compare supply chains (SCs) of an industry in the scope of supplier's supplier to customer's customer.

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Abstract

Purpose

The purpose of this paper is to develop a method to compare supply chains (SCs) of an industry in the scope of supplier's supplier to customer's customer.

Design/methodology/approach

The proposed method is based on five processes provided in SCOR model version 9.0 (plan, source, make, deliver and return) and main business stages of the industry. It uses Data Envelopment Analysis (DEA) and PROMETHEE II, a multiple criteria decision‐making technique, as tools to compare SCs in the process level, business stage level and SC level. Therefore, the method is basically a new combination of existing models and methods including SCOR model, DEA and PROMETHEE II. To show the applicability and strength of the method in comparing SCs, it has been implemented in the seven SCs of the Iran broiler industry as a case study.

Findings

Comparing SCs of an industry via the proposed method results in process benchmarking, business stage benchmarking and SCs ranking in the scope of supplier's supplier to customer's customer.

Originality/value

The suggested method provides realistic and attainable information for SCs' owner/managers to find out the strengths and weaknesses of their SCs and improve their performance by process benchmarking and business stage benchmarking. Also they could identify their competitive position in the industry by SCs ranking.

Details

Supply Chain Management: An International Journal, vol. 16 no. 2
Type: Research Article
ISSN: 1359-8546

Keywords

Article
Publication date: 5 May 2015

Yong Zha, Jun Wang, Zhao Linlin and Liang Liang

The purpose of this paper is to consider the following problem: the authors consider a new constructed unit system to indicate the characteristics of the inputs and outputs of…

Abstract

Purpose

The purpose of this paper is to consider the following problem: the authors consider a new constructed unit system to indicate the characteristics of the inputs and outputs of different decision-making units (DMUs) and propose several modified models to calculate their efficiencies based on overall value judgment and weight restriction in the production process.

Design/methodology/approach

This paper applies principal component analysis (PCA) to analyze the original value judgment information, and the key indices in the production process are extracted. The modified data envelopment analysis (DEA) models are proposed and DEA efficiencies and their projections are calculated.

Findings

By incorporate PCA and DEA, the authors propose new virtual DMUs composed of unique optimal multipliers of each DMU. Crucial indexes are extracted and the weights of inputs and output are ranked through using PCA by taking the preference and value judgments of all DMUs into consideration. Weight constraints from the ranking are utilized to improve the traditional CCR-DEA model. The empirical results validate the feasibility of the approach.

Practical implications

The method can be used in many organizations which have excessive amounts of inputs and outputs variables, such as banks, chain stores, car factory, etc.

Originality/value

This paper presents an integrated methodology of using PCA and DEA for considering the preferences of the inputs and outputs and value judgment of all DMUs and ranks the importance of the indicators from the overall perspectives.

Details

Kybernetes, vol. 44 no. 5
Type: Research Article
ISSN: 0368-492X

Keywords

Article
Publication date: 31 July 2019

Fang Li, Lei Deng, Longxiao Li, Zizhen Cheng and Han Yu

The purpose of this paper is to monitor the environmental efficiency of suppliers in the presence of undesirable output and dual-role factors with static and dynamic aspects…

Abstract

Purpose

The purpose of this paper is to monitor the environmental efficiency of suppliers in the presence of undesirable output and dual-role factors with static and dynamic aspects. Meanwhile, it also aims to explain the main reason for the low efficiency of suppliers.

Design/methodology/approach

The authors propose a modified data model considering undesirable output and dual-role factors. The study integrates the modified data envelopment analysis model into the distance function of the Malmquist–Luenberger index. Moreover, this study uses the global benchmark technology to formulate a two-stage model. To verify the validity of this model, a model application is conducted on an automotive spare components company in China.

Findings

The results identify the unique status of dual-role factors based on the global optimality of the model and then categorize inefficient suppliers in an individual evaluation cycle. In addition, each supplier is projected on a frontier curve after obtaining the improved data. Furthermore, through the status plot of M-L and its components, this paper concludes that efficiency scale change is the main reason for the gap in ecological performance between different suppliers.

Research limitations/implications

The proposed model considers both undesirable output and dual-role factors; however, variables with different features, such as imprecise, fuzzy and qualitative characteristics, can be embedded into the presented two-stage model.

Originality/value

Evaluating green suppliers through multiple consecutive evaluation cycles will aid a company in effectively managing its key suppliers. Furthermore, the evaluation provides policy guidance for further improvement of suppliers.

Details

Asia Pacific Journal of Marketing and Logistics, vol. 32 no. 1
Type: Research Article
ISSN: 1355-5855

Keywords

Article
Publication date: 10 January 2018

Yao Wen, Qingxian An, Xuanhua Xu and Ya Chen

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…

Abstract

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.

Details

Kybernetes, vol. 47 no. 7
Type: Research Article
ISSN: 0368-492X

Keywords

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