2017
DOI: 10.1108/jm2-08-2014-0066
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An ISM-based approach analyzing interactions among variables of reverse logistics in automobile industries

Abstract: Purpose This paper aims to analyze the interaction among the major variables of reverse logistics seen in automobile industries. Design/methodology/approach In this research, interpretive structural modeling (ISM) has been used to understand mutual influences among identified variables of reverse logistics. The advantage of the ISM methodology is that variables can be categorized depending upon their driving power and dependence. Findings Regulations make it mandatory for automobile companies to own respon… Show more

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Cited by 41 publications
(32 citation statements)
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“…The initial reachability matrix created in step 4 is then scanned for transitivity. Transitivity implies if Factor X influences Factor Y and Factor Y influences Factor Z, then Factor X can influence Factor Z (Ravi and Shankar, 2017). Once the transitivity check is done, a final reachability matrix is formed.…”
Section: Methodsmentioning
confidence: 99%
“…The initial reachability matrix created in step 4 is then scanned for transitivity. Transitivity implies if Factor X influences Factor Y and Factor Y influences Factor Z, then Factor X can influence Factor Z (Ravi and Shankar, 2017). Once the transitivity check is done, a final reachability matrix is formed.…”
Section: Methodsmentioning
confidence: 99%
“…Moreover, Mangla et al (2016) used DEMATEL and AHP approaches to examine the RL critical success elements in Indian industries. Ravi and Shankar (2017) investigated RL principles in the automobile industry using interpretive structural modeling.…”
Section: Green Supplier Assessment and Assortmentmentioning
confidence: 99%
“…The measures appeared with different terminology in the literature, typically termed as drivers, barriers, enablers, and success factors. The studies did not confine their investigation merely to the identification of the measures, but some rather investigated the interactions among measures as well (e.g., [149][150][151]). The second group of studies (e.g., [62,65,[152][153][154][155]) were dedicated to measuring the ultimate outcomes of SSCM in terms of social, environmental, and economic performance.…”
Section: Outputs (Performance)mentioning
confidence: 99%