Data Envelopment Analysis with Common Weights in a Fuzzy Environment

Hu, Cheng-Kai; Liu, Fung-Bao; Hu, Cheng-Feng

doi:10.1142/s0218488517500386

Cited by 1 publication

(1 citation statement)

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“…Kordrostami and Noveiri Jahani Sayyad (2017) developed a fuzzy DEA approach that results in efficiency scores at different periods of time, and efficiency changes were dealt by Malmquist productivity index with common set of weights. Hu et al (2017a) constructed a common base for calculating the relative efficiency of a group of homogenous DMUs in a fuzzy environment.…”

Section: Methodsmentioning

confidence: 99%

A 2-tuple integrated DEA-based approach for neuromarketing technology evaluation

Dursun

Göker

2019

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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.

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Section: Methodsmentioning

confidence: 99%

A 2-tuple integrated DEA-based approach for neuromarketing technology evaluation

Dursun

Göker

2019

View full text Add to dashboard Cite

show abstract

Data Envelopment Analysis with Common Weights in a Fuzzy Environment

Cited by 1 publication

References 34 publications

A 2-tuple integrated DEA-based approach for neuromarketing technology evaluation

A 2-tuple integrated DEA-based approach for neuromarketing technology evaluation

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