A decision model for supplier selection in the presence of dual-role factors

Ding, Jingjing; Dong, Wei; Bi, Gongbing; Liang, Liang

doi:10.1057/jors.2014.53

Cited by 23 publications

(12 citation statements)

References 50 publications

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“…DEA has been extensively employed to analyse the performance of suppliers for selection and control purposes (Narasimhan et al, 2001;Kumar et al, 2014;Ding et al, 2015). A review of 78 papers by Ho et al (2010) shows DEA to be the most popular criterion in the literature on supplier evaluation and selection.…”

Section: Tco-based Deamentioning

confidence: 99%

Supplier’s total cost of ownership evaluation: a data envelopment analysis approach

Visani

Barbieri

Lascio

et al. 2016

Omega

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Section: Tco-based Deamentioning

confidence: 99%

Supplier’s total cost of ownership evaluation: a data envelopment analysis approach

Visani

Barbieri

Lascio

et al. 2016

Omega

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“…To date, several studies have investigated how to cope with dual-role factors focusing on real-world problems (Saen, 2010a, b). As Ding et al (2015) mentioned, dual factors include exogenous and endogenous types. The exogenous type tries to explore standards to recognize the categorization of a dual-role factor that is an input or output.…”

Section: Literature Reviewmentioning

confidence: 99%

A two-stage model for monitoring the green supplier performance considering dual-role and undesirable factors

Deng

et al. 2019

APJML

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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.

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“…Generally, the existing approaches for evaluating the performance of firms in the presence of dual-role factors are classified into exogenous and endogenous categories. The exogenous category at first exploits some criteria to identify the classification of a dual-role factor as either an input or an output (Ding et al 2015). The endogenous category considers a flexibility in determining the classification of a dual-role factor in the DEA model (e.g., Beasley 1990Beasley , 1990Cook et al 2006;Saen 2010a;Toloo and Barat 2015).…”

Section: A C C E P T E D Mmentioning

confidence: 99%

“…Kumar et al (2014) slightly modified Saen (2010a)'s model to propose a Green DEA framework for the purpose of formulating supplier selection problems with carbon footprints of suppliers as a dual role factor. Ding et al (2015) developed a two-step approach to pinpoint the appropriate suppliers in the presence of dual-role factors.…”

Section: A C C E P T E D Mmentioning

confidence: 99%