The analytic hierarchy process supporting decision making for sustainable development: An overview of applications

A third party reverse logistic provider (3PRLP) selection and evaluation process is developed.A multiple attribute decision making (MADM) model to evaluate and select 3PRLPs in the presence of risk factors is proposed.A fuzzy step-wise weight assessment ratio analysis (SWARA) approach to weight the evaluation criteria is applied.A fuzzy (COPRAS) is proposed to rank and select the sustainable third-party reverse logistics providers in the presence of risk factors.A real world case study is used from automotive industry to validate the quality of our model. Reverse logistics is the backward process of collecting and redistributing products at the end-of-life from customers to producers and manufacturers for reuse, remanufacturing and disposal purposes. While reverse logistics brings several economic benefits, it seems to become a necessity for businesses to remain competitive in a world that environmental and social aspects of business activities are key to sustainable development. The operations and management of reverse logistics systems is a complex task that requires substantial level of infrastructure, technology, expertise and experience. Therefore, increasingly many business organizations tend to outsource their reverse logistics activities to third-party reverse logistics providers (3PRLPs). In this paper, we propose a multiple attribute decision making (MADM) model to rank and select 3PRLPs, using fuzzy step-wise weight assessment ratio analysis (SWARA) to weight the evaluation criteria. Accordingly, a developed fuzzy complex proportional assessment of alternatives (COPRAS) was proposed to rank and select the sustainable 3PRLPs in the presence risk factors. The suggested model was applied to a case study from automotive industry. Eventually, COPRAS and COPRAS-G methods were considered for the purpose of comparison and validation. As a result, the most sustainable 3PRLP was selected. While incorporating risk factors into our analysis, our study shows that environmental and social drivers are increasingly becoming dominant when selecting 3PRLPs.

Sustainable third-party reverse logistics provider evaluation and selection using fuzzy SWARA and developed fuzzy COPRAS in the presence of risk criteria

Towards the ex-ante sustainability screening of circular economy initiatives in manufacturing companies: Consolidation of leading sustainability-related performance indicators

A novel hybrid multiple attribute decision-making approach for outsourcing sustainable reverse logistics

The effect of big data on the lean, agile, resilient, and green (LARG) supply chain has not been explored much in the literature. This study investigates the role of ‘Big Data Analytics’ (BDA) as a mediator between ‘sustainable supply chain business performance’ and key factors, namely, lean practices, social practices, environmental practices, organisational practices, supply chain practices, financial practices, and total quality management. A sample of 297 responses from thirty-seven Indian manufacturing firms was collected. The paper is beneficial for managers and practitioners to understand supply chain analytics, and it addresses challenges in the management of LARG practices to contribute to a sustainable supply chain.

Big Data Analytics as a mediator in Lean, Agile, Resilient, and Green (LARG) practices effects on sustainable supply chains

Sustainability Performance Measurement for Green Supply Chain Management

Evaluating outsourcing risks in the pharmaceutical supply chain: Case of a multi-criteria combined fuzzy AHP-PROMETHEE approach

An integrated sustainable partner selection approach with closed-loop supply chain network configuration

In emerging markets, the growth of supply chain networks and logistics industry leads to a significant increase in energy consumption and induces high carbon emissions. To design a sustainable low-carbon supply chain network, we consider a carbon emission-compliance green location-inventory problem. It is characterized by uncertain demand and volatile carbon prices under a multi-year emission regulation, inspired from the carbon-trading scheme in China. A two-stage stochastic mathematical model is built and is solved with a three-phase hierarchical metaheuristic on extensive numerical experiments, which mimic the business context of a supply chain network operated in China. The results show to which extent the carbon-trading emission-compliance scheme, with uncertainties in demand and carbon price, impacts the strategic decisions. Besides, carbon emissions and supply chain profits of the design solutions produced under alternative emission regulations are evaluated and discussed. We also underline the sensitivity of the amount of carbon emissions to the demand uncertainty, and to the level and volatility of the carbon price in the carbon-trading system. These results provide managerial insights for supply chain emitters, and indicate that reasonable and stable carbon prices should be maintained by governments in emerging markets.

Carbon emission-compliance green location-inventory problem with demand and carbon price uncertainties

Partner selection is a crucial problem in supply chain management in which it is essential today to integrate sustainability criteria due to regulation, stakeholder pressers and economic interests. Thus, a sustainability-focused evaluation model for partner selection is required in order to improve the overall performance of the supply chain. This paper develops a new hybrid approach to evaluate and select the partners (suppliers and 3PRL providers) in sustainable supply chain network by combining Fuzzy Analytic Hierarchy Process (F-AHP) with Fuzzy Preference Ranking Organization Method for Enrichment Evaluation (F-PROMETHEE), and Fuzzy Technique for Order Performance by Similarity to Ideal Solution (F-TOPSIS). A set of sustainability criteria for both supplier and 3PRL provider selection is proposed based on extensive literature review and experts’ opinions. F-AHP is used to calculate the priority weight of each criterion. Then, F-PROMETHEE and F-TOPSIS are both used to rank the partners comparatively. The validity and efficacy of the proposed approach is demonstrated through an application for selecting partners in the case of light bulbs recycling which has been strengthened by sensitivity analysis.

Nadine Kafa

Papers

Sustainability Performance Measurement for Green Supply Chain Management

Evaluating outsourcing risks in the pharmaceutical supply chain: Case of a multi-criteria combined fuzzy AHP-PROMETHEE approach

An integrated sustainable partner selection approach with closed-loop supply chain network configuration

Carbon emission-compliance green location-inventory problem with demand and carbon price uncertainties

Evaluating and selecting partners in sustainable supply chain network: a comparative analysis of combined fuzzy multi-criteria approaches