A new data envelopment analysis-based model for failure mode and effect analysis with heterogeneous information

2021 ◽  
pp. 107350
Author(s):  
An-Yu Yu ◽  
Hu-Chen Liu ◽  
Ling Zhang ◽  
Yao Chen
Keyword(s):  
Data Envelopment Analysis ◽  
Failure Mode ◽  
Data Envelopment ◽  
Effect Analysis ◽  
Heterogeneous Information

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

Kybernetes ◽  
2019 ◽  
Vol 48 (5) ◽  
pp. 949-966 ◽  
Author(s):  
Mehtap Dursun ◽  
Nazli Goker
Keyword(s):  
Data Envelopment Analysis ◽  
Integrated Approach ◽  
Emotional Reactions ◽  
Data Envelopment ◽  
Content Type ◽  
Heterogeneous Information ◽  
Loss Of Information ◽  
Linguistic Representation ◽  
Representation Model ◽  
Common Weight

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.

Failure mode and effects analysis by data envelopment analysis

2009 ◽  
Vol 48 (1) ◽  
pp. 246-256 ◽  
Author(s):  
Kwai-Sang Chin ◽  
Ying-Ming Wang ◽  
Gary Ka Kwai Poon ◽  
Jian-Bo Yang
Keyword(s):  
Data Envelopment Analysis ◽  
Failure Mode ◽  
Data Envelopment

Determining rates of change in data envelopment analysis

1997 ◽  
Vol 48 (6) ◽  
pp. 591-593
Author(s):  
Z Huang ◽  
S X Li ◽  
J J Rousseau
Keyword(s):  
Data Envelopment Analysis ◽  
Data Envelopment ◽  
Rates Of Change

Data Envelopment Analysis Theory, Methodology and Applications

1997 ◽  
Vol 48 (3) ◽  
pp. 332-333 ◽  
Author(s):  
A Charnes ◽  
W Cooper ◽  
A Y Lewin ◽  
L M Seiford
Keyword(s):  
Data Envelopment Analysis ◽  
Data Envelopment ◽  
Analysis Theory
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