Author:
K.E.K. Vimal,Raja Sonu,Yendeti Venkata Siva Prasanth,Kancharla Amarendra,Kandasamy Jayakrishna
Abstract
Purpose
The purpose of this paper is to investigate the effect of current carbon tax (CT) policy on organizations involved in a sharing network relation.
Design/methodology/approach
For finding the CT and economic value of the industries connected in a sharing network model a multi-objective multi-integer linear model has been formulated. The data set of the case organization is used for computation. The formulated mathematical model is computed with the aid of GAMS optimization program.
Findings
This research paper demonstrates the effectiveness of the sharing network strategy in increasing the economic value and decreasing the CT for industries involved in sharing network. The CT value INR 3,012.694 for the industries in Scenario II which incorporates the sharing network is less than the CT INR 3,580.167 for industries in Scenario I without sharing network.
Research limitations/implications
The data used for the computation is based on a particular sharing network under investigation. The formulated mathematical model can be checked with similar sharing networks by varying the parameters.
Practical implications
This work can aid in gaining complete knowledge on the sharing network strategy which can uplift the resources and the monetary value of the non-efficient industries moving them towards sustainable and greener supply chain practices.
Social implications
The presented work can impact various industries in developing countries providing them with a strategy to enhance their resources and economic value by maintaining an amicable relation.
Originality/value
This work uniquely was able to validate economic feasibility and CT in accordance with the carbon footprint involved in sharing network. This sharing network also incorporates the concepts of circular economy and reverse logistics for showcasing a better strategy.
Subject
Management Science and Operations Research,Strategy and Management,General Decision Sciences
Cited by
1 articles.
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