Green decision-making model in reverse logistics using FUZZY-VIKOR method (Reprinted from Resources, Conservation and Recycling, vol 103, pg 125-138, 2015)

Due to the increasing global environmental consciousness and sustainability concerns, different industries that deal with Reverse Logistics (RL) are seeking methods to measure and analyze the impacts of their RL activities on the environment. However, making the greenest decision in the vague and complex area of RL makes this process somewhat difficult. Hence, to address these issues and provide a more meticulous and closer approach to the real world situations, a FUZZY-VIKOR method using interval-valued trapezoidal fuzzy numbers is proposed in the current research. As the further discussions explain, first, the significant factors in environmental sound practices together with the main processes and recovery options in RL are identified. Second, the influences of each green environmental factor on each RL recovery option are analyzed and ranked. To obtain concise results, the elicitation of experts is sought from among academicians and industry. The final results illustrate that, intriguingly, disposing of the returns has the lowest negative impact on the environment; thereby the best recovery option, while reselling of the returns was perceived as the worst recovery option. This research also suggests new directions for future research. From the managerial point of view, it would be interesting to study a sustainable reverse logistics through the proposed model. We only considered the impacts of environmental factors on RL, while the final decision will be more exact if the economic and societal aspects of RL are also analyzed. In addition, to reflect the technical views of all the stakeholders in RL towards the best recovery option and also take into account their concerns, we suggest designing a group decision making model across the RL using the Fuzzy-MADM methods. (C) 2015 Elsevier B.V. All rights reserved.