Sustainable supply chain modeling and analysis: Past debate, present problems and future challenges

For the last two decades, the topic of sustainable supply chains has evoked considerable interest from academics and practitioners. Within this context, Resources, Conservation and Recycling (RCR) and its two predecessors (Resources and Conservation, and Conservation and Recycling) have provided a platform for the exchange of technological, economic, institutional and policy aspects to help societies transition toward sustainability. The current article analyses the published research works in the RCR literature within the context of sustainable supply chain modeling by employing a content analysis literature review technique. Using the body of available literature in RCR, the articles on sustainable supply chain are analyzed in terms of the following: (1) publication per year, (2) top-cited papers across time, (3) most productive and influential authors, institutions and countries (4) supply chain related topical themes, (5) research methodologies applied, (6) illustration types and (7) industries addressed. The analysis revealed that the call for incorporating sustainability (i.e., economic, social, and environmental pillars) into supply chain operations has increased in recent years in RCR publications. Finally, the comprehensive findings and interpretations are presented, as well as the primary current trends, future challenges, directions and opportunities

An Integrated Approach of Fuzzy Quality Function Deployment and Fuzzy Multi-Objective Programming Tosustainable Supplier Selection and Order Allocation

The emergence of sustainability paradigm has influenced many research disciplines including supply chain management. It has drawn the attention of manufacturing companies’ CEOs to incorporate sustainability in their supply chain and manufacturing activities. Supplier selection problem, as one of the main problems in supply chain activities, is also combined with sustainable development where traditional procedures are now transformed to sustainable initiatives. Moreover, allocating optimal order quantities to sustainable suppliers has also attracted attention of many scholars and industrial practitioners, which has not been comprehensively addressed. Therefore, a practical model of supplier selection and order allocation based on the sustainability Triple Bottom Line (TBL) approach is presented in this research article. The proposed approach utilizes Fuzzy Analytical Hierarchy Process combined with Quality Function Deployment (FAHP-QFD) for reflecting buyer’s sustainability requirements into the preference weights that are then exerted by an efficient Fuzzy Assessment Method (FAM) to assess the suppliers to obtain their sustainability scores. Thereupon, these scores are utilized in a fuzzy multi-objective mix-integer non-linear programming model (MINLP) for allocating orders to suppliers based on the manufacturer’s sustainability preference. A real-world application of food industry is presented to show the practicality of the proposed approach

The impact of regional financial development on economic growth in Beijing-Tianjin-Hebei region:a spatial econometric analysis

The Beijing–Tianjin–Hebei (BTH) integration project in China is ambitious which offers great potential with its promotion of sustainable and inclusive development. This study investigates the impact of regional financial development on economic growth in the BTH region, with panel data collected from 2007 to 2016. Two indicators namely, CREDIT (denoted as regional financial development depth) and BRANCH (denoted as regional financial intermediaries accessibility) are used to construct an integrated regional financial development indicator through the spatial econometrics approach. The spatio-temporal distribution characteristics of regional financial development and economic growth are analyzed. Afterward, the global Moran’s I and local Getis–Ord Gi* statistics are applied to detect the presence of spatial autocorrelation. Finally, a spatial Durbin model (SDM) is utilized to examine spatial distribution and spatial association. The research findings of this study suggest that the CREDIT has a positive effect on regional economic growth, while the BRANCH has no impact on regional economic growth. Moreover, it is found that the spatial autocorrelation of CREDIT and BRANCH are statistically significant. The CREDIT of the neighboring areas has a negative spatial spillover effect on economic growth of one area, while the BRANCH in the neighboring areas has a positive effect on the one area. The results and research findings reported in this article highlight the role of regional financial development in improving the economic growth not only for Chinese policy makers but also for other countries’ researchers and practitioners in this field

An Integrated Approach of Fuzzy Quality Function Deployment and Fuzzy Multi-Objective Programming Tosustainable Supplier Selection and Order Allocation

The emergence of sustainability paradigm has influenced many research disciplines including supply chain management. It has drawn the attention of manufacturing companies’ CEOs to incorporate sustainability in their supply chain and manufacturing activities. Supplier selection problem, as one of the main problems in supply chain activities, is also combined with sustainable development where traditional procedures are now transformed to sustainable initiatives. Moreover, allocating optimal order quantities to sustainable suppliers has also attracted attention of many scholars and industrial practitioners, which has not been comprehensively addressed. Therefore, a practical model of supplier selection and order allocation based on the sustainability Triple Bottom Line (TBL) approach is presented in this research article. The proposed approach utilizes Fuzzy Analytical Hierarchy Process combined with Quality Function Deployment (FAHP-QFD) for reflecting buyer’s sustainability requirements into the preference weights that are then exerted by an efficient Fuzzy Assessment Method (FAM) to assess the suppliers to obtain their sustainability scores. Thereupon, these scores are utilized in a fuzzy multi-objective mix-integer non-linear programming model (MINLP) for allocating orders to suppliers based on the manufacturer’s sustainability preference. A real-world application of food industry is presented to show the practicality of the proposed approach

A literature review of sustainable consumption and production:A comparative analysis in developed and developing economies

Sustainable consumption and production is identified as one of the essential requirements for sustainable development. Due to different economic conditions and socio-cultural factors, sustainable consumption and production requires a diverse focus in developing and developed economies. To date, few efforts have been made to systematically compare the status of sustainable consumption and production and its direction from the perspective of developing and developed economies. This paper provides a literature review of published articles in international scientific journals related to sustainable consumption and production between 1998 and 2018 inclusive. Three carefully designed questions are proposed and answered in this article, forming the basis for conducting a comprehensive comparative analysis of the differences and challenges in sustainable consumption and production practices within developed and developing economies. The findings strongly suggest that countries in Europe hold international leadership in sustainable consumption and production practices. This finding, alongside others, is analyzed and discussed in greater detail in this paper, resulting in the articulation of gaps and future research opportunities in the current body of the literature

Life Cycle-based Environmental Performance Indicator for the Coal-to-energy Supply Chain: A Chinese Case Application

Coal consumption and energy production (CCEP) has received increasing attention since coal-fired power plants play a dominant role in the power sector worldwide. In China, coal is expected to retain its primary energy position over the next few decades. However, a large share of CO2 emissions and other environmental hazards, such as SO2 and NOx, are attributed to coal consumption. Therefore, understanding the environmental implications of the life cycle of coal from its production in coal mines to its consumption at coal-fired power plants is an essential task. Evaluation of such environmental burdens can be conducted using the life cycle assessment (LCA) tool. The main issues with the traditional LCA results are the lack of a numerical magnitude associated with the performance level of the obtained environmental burden values and the inherent uncertainty associated with the output results. This issue was addressed in this research by integrating the traditional LCA methodology with a weighted fuzzy inference system model, which is applied to a Chinese coal-to-energy supply chain system to demonstrate its applicability and effectiveness. Regarding the coal-to-energy supply chain under investigation, the CCEP environmental performance has been determined as “medium performance”, with an indicator score of 39.15%. Accordingly, the decision makers suggested additional scenarios (redesign, equipment replacement, etc.) to improve the performance. A scenario-based analysis was designed to identify alternative paths to mitigate the environmental impact of the coal-to-energy supply chain. Finally, limitations and possible future work are discussed, and the conclusions are presented

Supplier Selection: A Hybrid Approach Using ELECTRE and Fuzzy Clustering

Vendor selection is a strategic issue in supply-chain management for any organization to identify the right supplier. Such selection in most cases is based on the analysis of some specific criteria. Most of the researches so far concentrate on multi-criteria decision making (MCDM) analysis. However, it incurs a huge computational complexity when a large number of suppliers are considered. So, data mining approaches would be required to convert raw data into useful information and knowledge. Hence, a new hybrid model of MCDM and data mining approaches was proposed in this research to address the supplier selection problem. In this paper, Fuzzy C-Means (FCM) clustering as a data mining model has been used to cluster suppliers into groups. Then, Elimination and Choice Expressing Reality (ELECTRE) method has been employed to rank the suppliers. The efficiency of this method was revealed by conducting a case study in an automotive industry

Structural evolution of global plastic life cycle trade: a multilayer network perspective

International trade in plastics accounts for 5 % of total merchandise trade and involves all nations in modern society. To explore global plastic life cycle trade, a life cycle-based plastic trade multilayer network (LC-PTMN), including a raw materials layer, a semifinished products layer, a plastic products layer, and a plastic waste layer, is constructed. The structure of the global plastic trade is studied by analyzing each layer in the LC-PTMN from 1990 to 2019. The results reveal that the LC-PTMN has a prominent hierarchical structure and a small-world property, namely, a few countries occupy most trade channels and trade volume. The trade channels and trade volume in the plastic waste layer are the most concentrated. Countries with massive channels have a strong cooperative ability to prompt their trading partners to form close groups. Developing countries in Asia, such as Vietnam and Turkey, have outstanding performance in the LC-PTMN. The major trade flows have distinct geographical patterns, mainly occurring in intra-North American, intra-Asian and North American-Asian networks. Additionally, the community structures of the LC-PTMN have tended to stabilize. Dramatic changes are mainly caused by the merging of European countries with Asian and African countries and the split of North American countries from other countries. These findings will help policy makers encourage plastic sector transformation

Sustainable Supplier Selection based on Self-organizing Map Neural Network and Multi Criteria Decision Making Approaches

Due to increasing public awareness, government regulation and market pressure on sustainability issues, companies have found out that in order to have a competitive edge, sustainable operational activities should be adopted with their supply chain. Sustainable supplier selection as a crucial decision can affect the overall degree of sustainability in a supply chain. In this paper, an integrated approach of clustering and multi criteria decision making methods have been proposed in order to solve sustainable supplier selection problem. Firstly, self- organizing map as one of the well-known neural network methods has been utilized in order to cluster and prequalify the suppliers based on customer demand attribute and sustainability elements. Then, multi criteria decision making methods will be utilized in order to rank the cluster of suppliers to make coordination between them and customers. A case study has been carried out in order to show the efficiency of proposed approach

Order Processing in Supply Chain Management with Developing an Information System Model An Automotive Manufacturing Case Study

Nowadays, high competitive market needs fast, effective, high responsiveness, online interactive, 24 hours 7 days availability and easy to follow up order processing. Consequently, there is a need for a model in which interdisciplinary approaches for understanding the range of Supply Chain Management (SCM) Information System (IS) capabilities are provided. In this study, an integrated model of SCM IS was developed that is supported by empirical evidence specific to SCM IS implementations. The developed model integrates and enriches theories of competitive strategy, supply chain management and inter-organizational information systems. Then, a case study of an automotive manufacturing industry was conducted to demonstrate the proficiency of the proposed model. As a result, better understanding of capabilities of implemented supply chain management information systems and expected future capabilities could be identified by practitioners and decision makers. Finally, findings of this study are listed together with some future works