Future Research Directions: Reverse Logistics Network Design
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Abstract
Economic, environmental, and corporate social responsibility issues have significant impacts on the rapid development of reverse logistics research in both academia and business. Particularly, a variety of quantitative business models have been proposed to address reverse logistics network design, a key area of research in logistics. The objectives of this documentary research paper were to synthesize research papers on reverse logistics network design during the period 2009-2017 and identify future research gaps and opportunities. The methodology employed in this research was documentary research, and content analysis was employed for data analysis. Accessing three standard electronic databases including Science Direct, Emerald Insight, and Academic Search Complete, it was found that there were 41 relevant international journal papers published during period 2009-2017, and these papers had been categorized into four major research streams: 1) mixed-integer linear programming models for reverse logistics network design, 2) fuzzy programming models for reverse logistics network design, 3) stochastic models for reverse logistics network design and 4) an analysis of multi-agent character of reverse logistics network design.
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