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Article
Publication date: 13 July 2020

Jolly Puri and Meenu Verma

This paper is focused on developing an integrated algorithmic approach named as data envelopment analysis and multicriteria decision-making (DEA-MCDM) for ranking decision-making…

Abstract

Purpose

This paper is focused on developing an integrated algorithmic approach named as data envelopment analysis and multicriteria decision-making (DEA-MCDM) for ranking decision-making units (DMUs) based on cross-efficiency technique and subjective preference(s) of the decision maker.

Design/methodology/approach

Self-evaluation in data envelopment analysis (DEA) lacks in discrimination power among DMUs. To fix this, a cross-efficiency technique has been introduced that ranks DMUs based on peer-evaluation. Different cross-efficiency formulations such as aggressive and benevolent and neutral are available in the literature. The existing ranking approaches fail to incorporate subjective preference of “one” or “some” or “all” or “most” of the cross-efficiency evaluation formulations. Therefore, the integrated framework in this paper, based on DEA and multicriteria decision-making (MCDM), aims to present a ranking approach to incorporate different cross-efficiency formulations as well as subjective preference(s) of decision maker.

Findings

The proposed approach has an advantage that each of the aggressive, benevolent and neutral cross-efficiency formulations contribute to select the best alternative among the DMUs in a MCDM problem. Ordered weighted averaging (OWA) aggregation is applied to aggregate final cross-efficiencies and to achieve complete ranking of the DMUs. This new approach is further illustrated and compared with existing MCDM approaches like simple additive weighting (SAW) and Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) to prove its validity in real situations.

Research limitations/implications

The choice of cross-efficiency formulation(s) as per subjective preference of the decision maker and different orness levels lead to different aggregated scores and thus ranking of the DMUs accordingly. The proposed ranking approach is highly useful in real applications like R and D projects, flexible manufacturing systems, electricity distribution sector, banking industry, labor assignment and the economic environmental performances for ranking and benchmarking.

Practical implications

To prove the practical applicability and robustness of the proposed integrated DEA-MCDM approach, it is applied to top twelve Indian banks in terms of three inputs and two outputs for the period 2018–2019. The findings of the study (1) ensure the impact of non-performing assets (NPAs) on the ranking of the selected banks and (2) are enormously valuable for the bank experts and policy makers to consider the impact of peer-evaluation and subjective preference(s) in formulating appropriate policies to improve performance and ranks of underperformed banks in competitive scenario.

Originality/value

To the best of the authors’ knowledge, this is the first study that has integrated both DEA and MCDM via OWA aggregation to present a ranking approach that can incorporate different cross-efficiency formulations and subjective preference(s) of the decision maker for ranking DMUs.

Details

Data Technologies and Applications, vol. 54 no. 4
Type: Research Article
ISSN: 2514-9288

Keywords

Article
Publication date: 2 November 2015

Qiuping Wang, Subing Liu and Guoqiang Xiong

The aggregation of information from a group of decision experts for developing collective opinion is the important question in practice. The purpose of this paper is to provide a…

Abstract

Purpose

The aggregation of information from a group of decision experts for developing collective opinion is the important question in practice. The purpose of this paper is to provide a group decision-making method via ordered weighted aggregation (OWA) operator and grey incidence analysis.

Design/methodology/approach

In this study, OWA operator provides aggregation of attribute values to form an overall decision for each decision expert, and grey incidence model provides aggregation of decision experts’ evaluations to form overall score for each alternative. The example illustrates the procedure and practicability of the proposed model.

Findings

A new thought for multiple attribute group decision-making problems is given. The proposed method produces an overall desirability score for each alternative.

Practical implications

This is to obtain a more comprehensive and realistic solution to the given group decision-making problem. The proposed analysis method of group decision-making problems reveals vitality of grey systems theory.

Originality/value

This paper combines OWA operator and grey incidence analysis to obtain a novel and effective method for group decision making. It is suitable for group decision-making problems in which the attribute weights are completely unknown, expert weights are completely unknown.

Details

Grey Systems: Theory and Application, vol. 5 no. 3
Type: Research Article
ISSN: 2043-9377

Keywords

Book part
Publication date: 11 September 2020

Ronald Klimberg and Samuel Ratick

A major consequence of global environmental change is projected to be the alteration in flood periodicity, magnitude, and geographic patterns. There are a number of extant methods…

Abstract

A major consequence of global environmental change is projected to be the alteration in flood periodicity, magnitude, and geographic patterns. There are a number of extant methods designed to help identify areas vulnerable to these consequences, the construction of composite vulnerability indices prominent among them. In this paper we have implemented the Order Rated Effectiveness (ORE) model (Klimberg & Ratick, 2020) to produce composite flood vulnerability indicators through the aggregation of six constituent vulnerability indicators future projected for 204 hydrologic subbasins that cover the contiguous US. The ORE aggregation results, when compared with those obtained using the Weighted Linear Combination and Data Envelopment Analysis, provided a more robust and actionable distribution of composite vulnerability results for decision-makers when prioritizing Hydrologic Unit Codes for further analysis and for effectively and efficiently implementing adaptation and mitigation strategies to address the flooding consequences due to global climate change.

Article
Publication date: 9 January 2017

Valeria Scherger, Antonio Terceño and Hernán Vigier

The purpose of this paper is to develop a goodness index based on Hamming distance and ordered weighted averaging distance (OWAD), which is useful to make decisions. These…

Abstract

Purpose

The purpose of this paper is to develop a goodness index based on Hamming distance and ordered weighted averaging distance (OWAD), which is useful to make decisions. These alternative measures enrich the results of diagnostic fuzzy models and facilitate the experts’ task in decision-making. An application to a set of firms to verify the results is also presented.

Design/methodology/approach

The paper follows the basis of OWA operators to design a methodology to reduce the map of causes of business failure into monitoring key areas.

Findings

The present paper introduces two alternative measures to test the proposal of grouping. In the empirical application, the superiority of the minimum T-norm over other decision rules is verified. The ordered weighted averaging distance (OWAD) goodness index predicts a better adjustment over the index built using OWA and Hamming distance measures.

Practical implications

A useful mechanism to reduce the map of causes or diseases detected in key areas is added through this analysis. At the same time, these key areas can be disaggregated once some alert indicator is identified; this allows knowing the causes that require special attention. This application of OWA can encourage the development of suitable computer systems for monitoring the firm’s problems, alerting regarding failures and easing decision-making.

Originality/value

A comparison of grouping causes into key areas through a goodness index based on Hamming distance and OWAD is proposed. These contributions enrich the Vigier and Terceño (2008) model and could be applied to any model of fuzzy diagnosis to test the results.

Details

Kybernetes, vol. 46 no. 1
Type: Research Article
ISSN: 0368-492X

Keywords

Article
Publication date: 24 May 2013

Shouzhen Zeng

The purpose of this paper is to present a new decision making technique called the uncertain induced Minkowski OWA distance (UIMOWAD) operator.

Abstract

Purpose

The purpose of this paper is to present a new decision making technique called the uncertain induced Minkowski OWA distance (UIMOWAD) operator.

Design/methodology/approach

The developed UIMOWAD operator is a new aggregation operator that uses the IOWA operator, the Minkowski distance and interval numbers. It is an extension of the IMOWAD operator that uses uncertain information in the aggregation represented in the form of interval numbers.

Findings

The UIMOWAD operator is very suitable to deal with complex reordering processes that represent a wide range of factors in an uncertain environment that can be assessed with interval numbers.

Research limitations/implications

Clearly, this paper is devoted to the OWA operator and uncertain theory.

Practical implications

The UIMOWAD operator is applicable in a wide range of situations such as decision‐making, statistics, engineering and economics.

Originality/value

This paper fulfils an identified need to study how to make a decision according to expert's interest in uncertain environment.

Details

Kybernetes, vol. 42 no. 5
Type: Research Article
ISSN: 0368-492X

Keywords

Article
Publication date: 1 June 1996

Ronald R. Yager

Focuses on the applications of fuzzy set theory as a tool for the construction of multi‐criteria decision functions from specifications expressed in natural language. Starting…

218

Abstract

Focuses on the applications of fuzzy set theory as a tool for the construction of multi‐criteria decision functions from specifications expressed in natural language. Starting with the ability to represent individual criteria satisfactions in terms of membership of fuzzy subsets, shows how different types of linguistic specifications are implemented. Consideration is given to the representation of trade‐offs between criteria, quantifier‐guided aggregations, conditioned criteria and possibilistically qualified criteria.

Details

Kybernetes, vol. 25 no. 4
Type: Research Article
ISSN: 0368-492X

Keywords

Article
Publication date: 13 July 2018

Mehtap Dursun and Nazli Goker

Neuromarketing, which is an interdisciplinary area, concentrates on evaluating consumers’ cognitive and emotional reactions to different marketing stimuli. In spite of advantages…

Abstract

Purpose

Neuromarketing, which is an interdisciplinary area, concentrates on evaluating consumers’ cognitive and emotional reactions to different marketing stimuli. In spite of advantages, neuromarketing still requires development and lacks a strong theoretical framework. Techniques that are used in neuromarketing studies have different superiorities and limitations, and thus, there is a need for the evaluation of the relevance of these techniques. The purpose of this study is to introduce a novel integrated approach for the neuromarketing research area.

Design/methodology/approach

The proposed approach combines 2-tuple linguistic representation model and data envelopment analysis to obtain the most efficient neuromarketing technique. It is apt to handle information provided by using both linguistic and numerical scales with multiple information sources. Furthermore, it allows managers to deal with heterogeneous information, without loss of information.

Findings

The proposed approach indicates that functional magnetic resonance imaging (fMRI) is the best performing neuromarketing technology. Recently, fMRI has been widely used in neuromarketing research. In spite of its high cost, its main superiorities are improved spatial and temporal resolutions. On the other hand, transcranial magnetic stimulation (TMS) and positron emission tomography (PET) are ranked at the bottom because of their poor resolutions and lower willingness of participants.

Originality/value

This paper proposes a common weight data envelopment analysis (DEA)-based decision model to cope with heterogeneous information collected by the experts to determine the best performing neuromarketing technology. The decision procedure enables the decision-makers to handle the problems of loss of information and multi-granularity by using the fusion of 2-tuple linguistic representation model and fuzzy information. Moreover, a DEA-based common weight model does not require subjective experts’ opinions to weight the evaluation criteria.

Article
Publication date: 5 January 2010

Abhay Kumar Singh, Rajendra Sahu and Shalini Bharadwaj

The purpose of this paper is to evaluate two different asset selection methodologies and further examine these by forming optimal portfolios.

1130

Abstract

Purpose

The purpose of this paper is to evaluate two different asset selection methodologies and further examine these by forming optimal portfolios.

Design/methodology/approach

This paper deals with the problem of portfolio formation, broadly in two steps: asset selection and asset allocation by using the two different approaches for the first step and then well‐known mean variance portfolio optimization. In addition, the resulting portfolios are compared using Sharpe ratio.

Findings

The empirical observations prove the applicability of the methodology adopted in the research design, ordered weighted averaging (OWA)‐heuristic algorithm gives us a better portfolio from the sample observations. Also the asset selection procedures adopted in the research proves to be of help when an investor has to narrow down the number of assets to invest in.

Practical implications

The analysis provides two different methodologies for portfolio formation – though the asset allocation is based on the mean variance portfolio optimization, the asset selection methods adopted provide a systematic approach to select the efficient securities.

Originality/value

This paper shows that OWA can be used to decide the order of inputs for the heuristic algorithm. Also an attempt is made to use data envelopment analysis to find a solution to the problem of portfolio formation.

Details

The Journal of Risk Finance, vol. 11 no. 1
Type: Research Article
ISSN: 1526-5943

Keywords

Article
Publication date: 21 September 2012

Hamid Sadeghi

This paper seeks to disclose the important role of missing documents, broken links and duplicate items in the results merging process of a metasearch engine in detail. It aims to…

Abstract

Purpose

This paper seeks to disclose the important role of missing documents, broken links and duplicate items in the results merging process of a metasearch engine in detail. It aims to investigate some related practical challenges and proposes some solutions. The study also aims to employ these solutions to improve an existing model for results aggregation.

Design/methodology/approach

This research measures the amount of an increase in retrieval effectiveness of an existing results merging model that is obtained as a result of the proposed improvements. The 50 queries of the 2002 TREC web track were employed as a standard test collection based on a snapshot of the worldwide web to explore and evaluate the retrieval effectiveness of the suggested method. Three popular web search engines (Ask, Bing and Google) as the underlying resources of metasearch engines were selected. Each of the 50 queries was passed to all three search engines. For each query the top ten non‐sponsored results of each search engine were retrieved. The returned result lists of the search engines were aggregated using a proposed algorithm that takes the practical issues of the process into consideration. The effectiveness of the result lists generated was measured using a well‐known performance indicator called “TSAP” (TREC‐style average precision).

Findings

Experimental results demonstrate that the proposed model increases the performance of an existing results merging system by 14.39 percent on average.

Practical implications

The findings of this research would be helpful for metasearch engine designers as well as providing motivation to the vendors of web search engines to improve their technology.

Originality/value

This study provides some valuable concepts, practical challenges, solutions and experimental results in the field of web metasearching that have not been previously investigated.

Article
Publication date: 25 October 2018

Ying Huang, Nu-nu Wang, Hongyu Zhang and Jianqiang Wang

The purpose of this paper is to propose a model for product recommendation to improve the accuracy of recommendation based on the current search engines used in e-commerce…

Abstract

Purpose

The purpose of this paper is to propose a model for product recommendation to improve the accuracy of recommendation based on the current search engines used in e-commerce platforms like Tmall.com.

Design/methodology/approach

First, the proposed model comprehensively considers price, trust and online reviews, which all represent critical factors in consumers’ purchasing decisions. Second, the model introduces the quantization methods for these criteria incorporating fuzzy theory. Third, the model uses a distance measure between two single valued neutrosophic sets based on the prioritized average operator to consolidate the influences of positive, neutral and negative comments. Finally, the model uses multi-criteria decision-making methods to integrate the influences of price, trust and online reviews on purchasing decisions to generate recommendations.

Findings

To demonstrate the feasibility and efficiency of the proposed model, a case study is conducted based on Tmall.com. The results of case study indicate that the recommendations of our model perform better than those of current search engines of Tmall.com. The proposed model can significantly improve the accuracy of product recommendations based on search engines.

Originality/value

The product recommendation method can meet the critical challenge from the search engines on e-commerce platforms. In addition, the proposed method could be used in practice to develop a new application for e-commerce platforms.

Details

Kybernetes, vol. 48 no. 6
Type: Research Article
ISSN: 0368-492X

Keywords

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