Editorial
Sustainable supply chain modeling and optimization

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Introduction

Managing and optimizing sustainable supply chains presents multiple challenges involving social, economic, and environmental issues. With regard to social issues the purpose of sustainability includes meeting the needs of increasing numbers of people, creating jobs in society, and contributing to communities by providing scholarship, support for cultural events, sporting events and charity programs. Maximizing profit and minimizing generated waste and pollution are goals of economic and environmental sustainability respectively.

However, in many real world applications these objectives can be in conflict. For example, social sustainability can conflict with the aims of marketing, which classify customers into different categories with different priorities for business. For example, classifying customers in a customer pyramid as Platinum, Gold, Iron and Lead is a popular concept in marketing literature. The main purpose of this classification is not satisfying the needs of more customers but it is done to provide better services to the top tiers of the pyramid specifically.

This special issue is aimed at publishing manuscripts by researchers who develop analytical models relating to the environmental impacts of transportation including implications for the design, planning, and management of transportation systems as part of the sustainable supply chain. In the design, management, and performance measurement of the sustainable supply chain models should seek to minimize factors like energy consumption, material consumption, hazardous waste, pollution, discrimination, abuse of human rights, child labor, long working hours, unfair competition, etc. Also, factors like profit, utilization of facilities, recovered materials, recovered energy and meeting population needs should be maximized.

In the first paper Davarzani, Fahimnia, Bell and Sarkis discuss past and present research on green ports and maritime logistics. They review the key studies, collaboration patterns, research clusters and interrelationships of the areas that have provided the field with foundational knowledge, concepts, theories, tools, and techniques. The research identifies the need for closer collaboration between naval architects and those involved in broader maritime issues in order to achieve environmental outcomes.

In the second paper Amirteimoori, Despotis, Azizi and Kordrostami evaluate the relative efficiency of a set of specialized and interdependent decision-making subunits that make up a larger decision making unit (DMU) in supply networks. The study uses a two-stage DEA approach where the first stage uses its own inputs to generate outputs which then become the inputs to the second stage. The study then provides a set of additive models which measure the performance of the two-stage network DEA processes. The applicability of the approach to supply networks is discussed.

In the third paper Mohajeri and Fallah present a carbon footprint-based problem that arises in a closed-loop supply chain where returned products are collected from customers. Their reverse logistics approach is illustrated using data from a business in Iran. The authors propose a closed-loop network where capacity limits, single-item management, and uncertainty on product demands and returns are considered. First, fuzzy mathematical programming is introduced for uncertain modeling, then a statistical approach to synthesize fuzzy information is utilized. The research finds that customer demand and recovery rates are the main factors in an uncertain green supply chain environment. Therefore, an accurate forecast of the demand and recovery rate should be conducted in Green Supply Chain logistics planning.

Next Ji, Wu and Zhu discuss the adoption and extension of Data Envelopment Analysis (DEA) in constructing a model to address the issue of eco-design for transportation in order to achieve sustainable supply chain management (SSCM). The model, together with the algorithm developed in the research, can help stakeholders realize transportation goals that lead to a transportation strategy with less resource consumption and pollution emissions. An empirical study of a sustainable transportation mechanism for an air-condition manufacturer in China is presented.

In the fifth paper Chen, Chen, Miao, Song and Fan discuss the unbalanced development of China’s inter-provincial highway using decomposition of the Gini coefficient for each province. On the basis of the Gini coefficient decomposition method used in the research the authors are able apply additional dimensions to discover causes of unbalanced development of inter-provincial high-grade highways. From empirical data the authors find that lower development of inter-provincial high-grade highway occurred in inland areas of China. The research finds that government should pay more attention to providing a suitable highway network to promote long-term, environmentally sustainable development. Policy recommendations are made along with suggestions for more effective and efficient future inter-provincial highway construction.

In the sixth paper Song, Zeng, Zhang, Liu and Fang present a study that investigates whether the railway transportation system in China has reduced the environmental impact of transportation. The authors first use a non-radial DEA approach to measure the environmental efficiency of 30 regions in China, before proposing a panel beta regression with fixed effects to model the impact of railway transportation on environmental efficiency. The results indicate that environmental efficiency slowly increased during 2006–2011. The authors also identify and discuss regional disparities. Overall, the research conclusions find that railway transportation has a positive impact on environmental efficiency.

In the final paper Wu, Zhu, Chu, Liu and Liang present a paper where transportation in China is treated as a parallel system consisting of subsystems for passenger transportation and freight transportation. Their research extends a parallel DEA approach to evaluate the efficiency of each subsystem, especially in terms of energy and environmental efficiency. The model is then applied in an empirical study of 30 of mainland China’s provincial-level regions, showing that most have low efficiency in their transportation systems and parallel subsystems. In particular large efficiency differences are noted between the passenger and freight transportation subsystems while unbalanced development has also occurred in the eastern, central and western areas of China. The paper concludes that government should act to address regional disparities in efficiency in China based on the findings of the study.

We wish to thank all the authors for their contribution to this special issue and for their patience in the review process. We express our gratitude to the reviewers who played an important role in the finished product and were instrumental in improving the original submissions. We also wish to acknowledge the assistance we received from Oliver Gao and Vasudha Pandey in putting together this special issue.

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