ANALYSIS AND MANAGEMENT OF RISKS IN GREEN SUPPLY CHAIN

Abstract

Due to increase in customer environmental awareness, competitiveness and strict governmental policies, the approach of incorporating Green Supply Chain Management (GSCM), to conserve resources and sustainable production, is gradually becoming more imperative for organizations. In the line of getting of the maximum economic-environmental advantages, many organizations have either initiated or about to initiate the green trends in their business activities. However, still, organizations are reluctant in adoption of green initiatives in their supply chain planning. One of its reasons is inadequacy in their knowledge of green and economic benefits obtained from adoption and implementation of GSCM. Another reason is an incomplete understanding of what is responsible for green adoption to fail in the supply chain. It is due to because the initiatives of green at various aspects of business involve several complexities. Due to which, it arises different risks and risk factors in implementing different Green Supply Chain (GSC) initiatives in business, which would certainly affect the overall performance. Therefore, to effectively managing initiation and implementation of GSC initiatives, the background of the risks related to GSC essentially needs to be known, analyzed, and managed. All India Plastics Manufacturers Association (AIPMA) report estimates that plastics is one of the major contributors to India‘s GDP and the consumption of plastic will increase to almost 2-3 times a year in 2020 from the existing 8 million tons a year in India. It has been noticed that the global trend and competitions in the plastic industrial sector proposes a great pressure to consider green or ecological influence in the supply chain planning process. However, the managers/business professionals may face several risks in GSCM network design. Under these considerations, to help organizations in this sector to adopt effective green initiatives, it is important to manage and reduce the convolution of risks in GSC. Hence, GSCM example of poly-plastic manufacturing business organizations operational in India has been identified and discussed in this research work. Twenty five specific risks, associated with the GSC, were identified. The basis of identification of the risks was literature and inputs received from the experts. Further, these identified risks were grouped into six categories of risks, namely, Operational risks (O), Supply risks (S), Product recovery risks (PR), Financial risks (F), Demand risks (D), and Government v and Organizational related risks (GO). These categories of risks were finalized through an interactive discussion with the experts of decision-making team. After the identification of risks of GSC in the context of Indian plastic business organizations, a qualitative model has been developed to prioritize the selected risks using fuzzy Analytic Hierarchy Process (AHP) approach. It will provide a measure for determining the relative concerns of recognized six categories of risks and twenty five specific risks in GSC. The fuzzy AHP analysis results point out that operational risk is the most prioritized risk with an overall priority value of 0.2507. The used fuzzy AHP approach is also useful in dealing with the human subjectivity and ambiguity involved in the risk analysis. To confirm the fuzzy AHP based ranking, the methodology of Interactive Ranking Process (IRP) was used. This method present interpretive logic for dominance of one risk over the other for each paired comparison developed, and thus, overcome the shortcomings of the AHP - fuzzy AHP method. Six categories of risks (O, S, PR, F, D, and GO) relevant to GSC and four expected performance (Environmental performances (P1), Economic performances (P2), Operational performances (P3), and Competitiveness performance (P4)) measures by implementing efficient GSCM concept were identified. Interpretive ranking model of the derived final ranks of the risks helps to interpret how each risk is influencing various performances. The results obtained from the fuzzy AHP and IRP analysis shows a reasonable consistency in the findings of the present research work. Human judgment input is utilized to calculate the weights for the listed categories of risks and specific risks. Thereby, sensitivity analysis is conducted to test the final ranking by varying the weights of all the categories of risks. The present work also analyzes the performance of GSC from risks management viewpoint. The risks identified in this work were evaluated to access their effects in terms of Time, Brand image, Economic, Health and Safety, and Quality. The maximum impacts were seen in time based effects and that was measured in terms of time delays and disruptions. In time based dimension, time delay/disturbance is the significant impact of GSC risks. The human based assessment unable to give extreme scenario. Thus, simulation approach was used. Monte Carlo Simulation approach was used to analyze the drivers of risk and their impact on GSC performance. In addition, it also helps to capture the uncertainties in the inputs. A sensitivity analysis test was performed to capture the effects of risks on the delay profile mean. The proposed model will provide analytic means to analyze the risks more efficiently towards effective implementation of GSCM. vi After listing the potential risks and their impacts, it is needed to understand how to manage the risks and its consequences. For managing the GSC risks, various mitigation strategies and response measures need to be proposed. Therefore, a model is proposed by using an integrated approach based on the fuzzy AHP and the fuzzy Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) methods to prioritize the responses in GSC to manage its risks under the fuzzy environment. In order to manage the risks, seventeen responses were identified. These responses were selected through literature and inputs received from the experts of the decision-making team. The fuzzy AHP is useful in deciding the importance weights of the GSC risks. While, the priority of the responses in a successful accomplishment of GSC business initiatives is determined using the fuzzy TOPSIS. According to the values of closeness coefficient, the priority of concern of the responses of the risks in GSC is given as, R12 - R15 - R10 - R7 - R17 - R16 - R8 - R6 – R14 - R11 - R13 - R5 - R4 - R9 - R3 - R1 - R2. To develop and upgrade on technology being used in the specific sectors for implementation of green (R12) obtains the highest rank. Thus, it needs to focus this response at priority in managing the risks in GSC. The model proposed would offer a scientific decision means to the managers/business professionals/practitioners for systematic implementation of the responses of risks relevant to adoption and effective implementation of GSC initiatives in business. A sensitivity analysis test was also performed to monitor the robustness of the proposed model. A framework is developed to evaluate the strategies to mitigate risk in GSC, which would be helpful for business organizations in improving the GSC robustness. This framework is developed on the basis of SAP-LAP (Situation Actor Process - Learning Action Performance) and IRP approaches. According to the SAP-LAP approach, the standpoint of the actors including ultimate users, supply chain managers, suppliers, and top management should be considered in building a GSC risk mitigation strategy framework. Managers must make good understanding on both the values and shortcomings of the strategies, as well as their appropriateness for an organization. To capture the interactions among the variables of SAPLAP based model, i.e., Actors v/s Processes and Actions v/s Performances, an interactive process of decision making is used. The methodology of IRP enables the managers to limit the limitations of the SAP-LAP. According to the findings of IRP approach, the role of top management as an Actor and the commitment of top management as an Action come out be most important in building and implementation of GSC risk mitigation strategies. The developed framework can help in reviewing current risk mitigation strategies in GSC by supply chain experts and managers to plan for further improvements to make them more vii comprehensive and robust. Furthermore, the developed SAP-LAP and IRP based framework would help organizations to address risk mitigation strategies for GSC with concerns over situation, actors, process, learning, actions and performance aspects, together with to interpret the of role and influence of actors and actions in accordance with process and performance, that will increase the GSC effectiveness. The findings of this research would be useful for managers in managing the risks and risk factors relevant to a successful implementation of GSC business initiatives, and hence enhancement in ecological-economic gains of the related organizations. The main purpose of this study is to provide a better understanding of developing and managing of GSC in a most effective way. Besides, this work touched on various problematic issues of Indian plastic business organizations that may be helpful in developing strategies and will be useful in improving GSC effectiveness. The present work is useful to both theoretical and practical domains in the field of GSCM. Finally, this research work may help managers and practitioners to manage the GSC efficiently, while achieving sustainability in business.