Sustainable Supply Chain Network Design: A Review on Quantitative Models Using Content Analysis

• Main Authors: Ezzatollah Asgharizadeh, S. Ali Torabi, Ali Mohaghar, Mohammad Ali Zare-Shourijeh
• Format: Article
• Language: English
• Published: Iranian Association for Energy Economics 2019-05-01
• Series: Environmental Energy and Economic Research
• Subjects: Supply chain network design; Quantitative Models; Sustainability; Systematic literature review; content analysis
• Online Access: http://www.eeer.ir/article_88256_c0ca44537991421332ad8324f21c024e.pdf

The purpose of this paper is to develop a systematic literature review on the subject of sustainable supply chain network design during 1990-2016, through a review of 261 papers.<br /> In this study, qualitative technique for conducting a systematic literature review was used. To systematize and make the literature review more accurate, content analysis method was used that include data collection, coding, analysis and interpretation of data. Several tables and figures were developed to provide a better interpretation of the literature. The results show that: 1. Researches has been growing dramatically in this field, especially since 2008; 2. Most research has been conducted in five countries; 3. The most of quantitative models of SCND have published respectively in five top journals; 4. Generally, the researchers were more interested in: single-objective, linear programming, single-period, multi-product, capacity-limited facilities, multi-mode, reverse and environmental models, than other types of models and considerations; 5. In phase of modeling and solving, the authors have used more of mathematical programming (specifically MILP) and commercial solvers. The general contribution of this paper is in its addressing the topic of Sustainable Supply chain Network Design. Supply chain network design (SCND) is one of the strategic problems at the intersection of disciplines such as management, strategy, logistics, and operational research. Moreover, this work specifically contributes to understanding sustainability and identifies research gaps and characteristics of the scientific papers on this topic.