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Harnessing Corporate Sustainability Decision-Making Complexity: A Field Study of Complementary Approaches

Authors: Kafa, N.; Jaegler, A.; Sarkis, J.;

Harnessing Corporate Sustainability Decision-Making Complexity: A Field Study of Complementary Approaches

Abstract

Supply chain management environmental and social criteria are practical and research concerns due to regulatory, stakeholder, and economic pressures. Effective holistic sustainable supply management schemes require the evaluation and selection of suppliers. Supplier evaluation requires the balancing of multiple criteria. Multiple criteria tools, each with advantages and limitations, are necessary for the supplier evaluation and selection problem. This paper introduces a new methodological approach including complementary, analytic hierarchy process (AHP), decision-making trial and evaluation laboratory (DEMATEL) techniques and Bayesian networks (BN). The combination of DEMATEL, AHP and Bayesian approaches, although they are supportive and complementary methods, has seen limited investigation. The Bayesian network approach can complement DEMATEL and AHP to help improve the accuracy of AHP input data. Alternatively, DEMATEL and AHP can provide expert and more objective inputs for intangible factors, used in the Bayesian network approach. The validity and efficacy of this approach is demonstrated through a real industrial case using decision-makers’ inputs and outputs. The study shows the advantages and disadvantages of each method. Finally, we present results with managerial and research implications and future research directions.

Keywords

supply chain management, Environmental effects of industries and plants, sustainable supplier evaluation, AHP, TJ807-830, DEMATEL, TD194-195, Renewable energy sources, Environmental sciences, Bayesian network, GE1-350, supplier selection, [SHS] Humanities and Social Sciences

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    citations
    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    9
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Top 10%
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Average
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Top 10%
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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
9
Top 10%
Average
Top 10%
gold