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Review

Sustainable Supply Chain Management in the Automotive Industry: A Process-Oriented Review

by
S. Maryam Masoumi
1,*,
Nima Kazemi
2 and
Salwa Hanim Abdul-Rashid
3
1
Department of Operations and Supply Chain Management, Australian Institute of Business (AIB), 27 Currie Street, 5000 Adelaide, SA, Australia
2
Center for Transportation & Logistics, Massachusetts Institute of Technology, Cambridge, MA 02142, USA
3
Faculty of Engineering, Department of Mechanical Engineering, Center for Product Design and Manufacturing, University of Malaya, Kuala Lumpur 50603, Malaysia
*
Author to whom correspondence should be addressed.
Sustainability 2019, 11(14), 3945; https://doi.org/10.3390/su11143945
Submission received: 25 May 2019 / Revised: 1 July 2019 / Accepted: 4 July 2019 / Published: 19 July 2019

Abstract

:
The holistic shift from traditional supply chain to sustainable supply chain has been practiced in different industries for many years. The automotive industry, as one of the largest and most influential industries in the world, could have a substantial effect on the movement toward a sustainable society. Despite the growing body of literature in the field of sustainable supply chain management, there is no review article that comprehensively synthesizes the state-of-the-art research in the automotive industry. To cover this gap, this paper reviews the sustainable supply chain management literature in the automotive industry published between 1995 and 2017. A systematic review and content analysis were conducted to collect the studies and analyze their content. The content analysis was structured based upon a set of key business processes following the Integration Definition Function (IDEF0) method, which is a structured approach of analyzing business processes. The study provides a practical guideline for designing a sustainable automotive supply chain and culminates with the outlined research gaps and recommendations for future research.

1. Introduction

The automotive industry is indubitably one of the largest and most influential industries in the world [1,2]. It involves a wide variety of companies taking part in design, development, manufacturing, selling, and marketing of automobiles and their spare parts [3]. The industry is a major contributor to the world’s economy and is one of the most important economic sectors by revenue, such that its turnover is equivalent to the sixth largest economy in the world [4]. Besides the economic impact, the industry is a huge contributor to the well-being of people and society, through affecting the quality of a human’s life remarkably [5]. With the growth of the industry and the production rate, more vehicles are seen on the roads, bringing their own problem to society. Automobiles affect the environment in various ways during their life cycle. Any automobile, before being ready to roll, consumes a considerable amount of materials like plastics, rubber, glass, steel, and many more, many of which are difficult and expensive to recycle or dispose of. On the other hand, fuel consumption leads to air pollution, which affects air quality and worsens global warming. Considering the substantial effect of the automotive industry on economic, environmental, and social activities all over the globe, effective management of this sector has become vital to assure the well-being of society [6]. Owing to these concerns, automotive companies have started to implement particular practices that enable them to integrate sustainability measures into their operations [7,8,9].
The necessity of changing industrial activities to attain a more sustainable world started with the report by the World Commission on Environment and Development (WCED) in 1987 [10], with the emphasis that different industries have to incorporate sustainability-conscious initiatives into their business practices. Since then, controversies have risen as to how a better sustainable performance might be achieved for industries, and indeed what practices can be incorporated into conventional supply chain management (SCM) that make supply chain (SC) activities more sustainable. Given the fact that SCs manage the flow of products from their early stage until they are delivered to end users, the focus on SCM is a step toward the wider execution and development of sustainability [11,12]. Consequently, integrating the concept of sustainability into SCM, leading to the definition of the so-called term sustainable supply chain management (SSCM), has provided the opportunity for the broader development of this field. Green supply chain management (GSCM) [13,14], reverse logistics (RL) [15], and closed-loop supply chain management (CLSCM) [16] are terms that have emerged in the literature focusing on the environmental aspect of sustainability.
Recently, the automotive industry, as an industry with huge potential for tackling environmental issues, has felt increasing pressure from authorities and the public. For instance, regulations framed by governments, such as the EU Directive of End-of-Life (EOL) Vehicles, has encouraged car manufacturers in the European region to accelerate greening their SCs. As a result of these pressures and regulations, the concept of SSCM in the automotive industry (from now onward, auto-SSCM) has received growing attention in recent decades and unfolded plenty of opportunities for research in this area. Several studies have been conducted to discuss different aspects of environmentally-conscious practices and the challenges that the automotive sector encounters for the effective implementation of the practices. This had led to the incorporation of sustainable practices and aspects into different stages of automotive SCM, including, but not limited to design, purchasing, supplier collaboration, logistics, warehousing, and packaging [17].
As the field of auto-SSCM grows rapidly, there is a necessity to conduct review studies that structure the literature in a systematic way. Doing so can facilitate identifying primary research streams, analyzing research findings, and highlighting future research directions. Analyzing the studies in the area of SSCM indicates that several review articles have been published so far. However, the published review papers have discussed the SSCM field in general, without drawing specific attention to the automotive industry (see the background of the study in Section 2). As Carter and Easton [18] noted, the existing research on multi-industry samples provides an opportunity for deeper studies on individual industries that aid in discerning specific sustainability issues within those industries. To address this research gap, this paper aims to present a systematic state-of-the-art literature review discussing sustainability-conscious issues in automotive SCs. The paper categorizes and synthesizes the existing studies from a process-oriented perspective, and tries to distinguish prominent research areas that establish an agenda on future research opportunities. In this perspective, the paper will answer the following research questions:
What is the current state-of-the-art research on auto-SSCM from a process’s perspective?
On the basis of the literature review, what steps can be taken for designing a sustainable SC in the automotive industry?
What future research directions can be identified for this field of research?
The rest of the paper is organized as follows. In Section 2, a background to this research is provided. In Section 3, the research process applied in this study is presented. Section 4 provides a classified review of auto-SSCM issues. A conceptual model for designing a sustainable SSCM is presented in Section 5. Finally, the future research directions and the conclusions of this paper are given in Section 6 and Section 7.

2. The Background of the Study

Review studies are primary sources in any field of science, as they can critically summarise the body of knowledge of the field [19]. Review studies categorize and synthesize the past and current progress in the area under investigation and can identify the strengths and weaknesses of prior studies, which can be beneficial in laying foundations for future studies [20,21]. As the area of SSCM took shape at the beginning of the 2000s, it has gained increasing attention over the years and has been a dominant research domain since 2010 [22]. The growing number of studies has consequently led to the growth in the number of review studies. A recent study by Rajeev et al. [22] comprehensively reviewed studies in the field of SSCM published over a period of 16 years, from 2000 to 2015, where the authors found 59 review papers covering different issues and sub-issues of SSCM. According to Rajeev et al.’s [22] analysis, the first review paper emerged in 2002, and the number of review papers followed a fairly stable trend until 2010, with less than four reviews published per year. From 2011 onward, the trend has changed and the number of review papers showed substantial growth, highlighting the importance that this topic has been gaining in the literature. The content analysis of the papers published during this time frame reveals that only the study of Beske et al. [23] focused on SSCM in a specific industry [22]. Beske et al. [23] investigated SSCM practices in the food industry and analyzed their connection to dynamic capabilities, which refers to the capabilities of companies to gain competitive advantages in a highly dynamic business environment. As a complement to the study of Rajeev et al. [22], Table A1 in the Appendix provides the review studies that appeared in the literature from 2016 onward. Totally, 23 review papers were found with a focus on SSCM or GSCM. The number of studies within the two recent years also confirms the finding of Rajeev et al. [22], who stated that the number of review studies in SSCM has been growing since 2011. Looking at the fourth column of Table A1, it can be realized that only six papers analyzed a particular industry within the frame of SSCM research. They include mineral [24], textile [25], biorefinery [26], oil and gas [27], food [28], and fashion [29]. This analysis discloses that despite the high number of literature review studies conducted in SSCM, no study can be found that solely focused on the automotive industry. This is surprising given the importance of the automotive industry and its role in building a more sustainable world. This study, therefore, tries to cover this research gap and presents a review of research works published so far with the considerations of auto-SSCM.

3. Research Methodology

In this review study, we used a systematic review and content analysis to search and classify the body of the literature. A systematic literature review is a type of literature review that analyses the literature in a structured way [30,31] and presents the results in a transparent, objective, and reproducible way [32]. In addition, systematic literature reviews are usually performed using defined keywords and through iterative search phases that allow finding sample papers and organizing them for evaluation [33]. Similar to the most recent reviews [30,31,34,35,36], this paper follows a seven-step methodology for data collection, sample formation, and content analysis in order to investigate and classify research issues in auto-SSCM. The detailed guideline of executing a multi-step methodology for conducting a literature review is discussed by Tranfield et al. [37] and Cooper [38]. In what follows, we explain the methodology that was used to identify and analyze the studies.

3.1. Defining the Relevant Keywords for Searching Databases

Defining the appropriate search terms is an initial step in any systematic literature review. For deriving the necessary keywords, the recent review papers were thoroughly checked. The keywords were in line with the studies of Rajeev et al. [22], Sauer and Seuring [24], Seuring and Müller [39]. Four sets of keywords were defined, aiming at covering different dimensions of the study. Set A sought to retrieve the studies related to sustainability issue, which were chosen in line with three pillars of sustainability (i.e., economic, environmental, and social): “Sustainable”, “Sustainability”, “Sustainable Development”, “Green”, “Environment”, “Ethics/Ethical”, “Social”, “Economic”. The terms “Green” and “Environment” were added to the keywords because of the fact that the term “Sustainable” involves environmentally sustainable development. Set B indented to limit the search to the papers that only discussed SC and its sub-categories: “Supply Chain”, “Logistics/Logistical”, “Supply”, “Reverse”, “Closed-loop”. Set C was defined to ensure that different aspects of sustainable operations were covered: “Waste Management”, “Return”, “Reuse”, “Recycle”, “Remanufacture”, “Life cycle assessment”, “EOL”, “Product recovery”. Finally, set D of keywords was defined to limit the search to the papers in the area of the automotive industry: “Automotive”, “Auto”, “Automobile”, “Automaker”, “Car”, “Vehicle”. The final set of keywords was generated by combining the keywords from the four sets defined above. Thus, the search string used in the database search was the combination of keywords from all four sets using Boolean operators: [“Sustainable” “Sustainability” “Sustainable Development” “Green” “Environment” “Ethics/Ethical” “Social” “Economic”] [“Supply Chain” “Logistics/Logistical” “Supply” “Reverse” “Closed-loop”] [“Waste Management” “Return” “Reuse” “Recycle” “Remanufacture” “Life cycle assessment” “EOL” “Product recovery”] [“Automotive” “Auto” “Automobile” “Automaker” “Car” “Vehicle”].

3.2. Database Selection and the First Search Phase

To form the initial search sample, Scopus was chosen as the main database to search the relevant papers in the first step. We preferred Scopus over Web of Science (WOS) because Scopus is a more comprehensive database than WOS (Scopus covers over 22,000 peer-reviewed journals, while WOS only comprises 12,000 titles) [30,40]. Furthermore, Scopus was identified as a good source for SC peer-reviewed papers [30,41]. Thus, Scopus was widely searched using the final list of the keywords defined in Section 3.1 to identify the papers that carried the keywords. The title, abstract, and keywords in the two databases were used to search for the defined keywords. Using the aforementioned settings, papers were searched for all years. In this step of our literature search, 957 papers were identified.

3.3. Filtration

In the second phase in Scopus, a number of exclusion criteria were implemented. First, the types of the papers were selected as article, review, and article in press, whereas other sources, the so-called gray literature, such as conference papers, books and book chapters, editorial, notes, short survey, letter, and erratum, were excluded from the search. During the search phase, the language of the papers was set as English. In this step of the search, 389 papers were found. To ensure that no paper was missing from the review, we added Google Scholar as the second scholarly database to our search. Using the same keywords as presented in Section 3.1, the papers were searched through Google Scholar and compared to the list of papers found from Scopus. This step resulted in finding 31 additional papers. Both papers from the databases were integrated and formed a single sample.

3.4. Snowball Approach

To ensure that the sample includes all the papers published in the literature, forward and backward snowball approaches were executed via searching through the references of the sample papers. The references were checked to find whether or not they contain the aforementioned keywords. In addition, the papers citing the sample papers were checked in order to find relevant papers. A total of 14 papers were added to the sample papers in this stage.

3.5. Final Filtration

To finalize the sample, the title, abstract, and contents of the papers were analyzed. The papers were examined in terms of their focus on business and operations management aspects of auto-SSCM and, in case they were found irrelevant (i.e., the focus was on other areas such as material design and engineering), they were eliminated from the sample. Moreover, some papers were removed from the sample as they were duplicated. The same size at this state was reduced to 229 papers.

3.6. Descriptive Analysis of the Sample

The results of this search were filtered by keeping the articles that focused on the automotive industry. Finally, a total of 229 articles published between 1995 and 2017 were taken into account for the purpose of content analysis. Table A2 in the Appendix shows the distribution of articles in the various journal from 1995 to 2017.

3.7. The Content Classification Scheme

In this step, a content analysis framework was developed to classify the sample papers. The framework considers SSCM as a set of key business processes and applies the IDEF0 (Integration Definition Function) method, which is a structured approach for enterprise analysis [42]. IDEF0 is a rigorous and flexible approach that can be successfully applied to model systems with varying objectives, scopes, and complexities [43]. It is an approach that transforms inputs into outputs by using resources and applying the mechanisms under a set of rules and controls [44]. As an SSCM can be viewed as a set of processes, operations, and regulations, IDEF0 is suitable for representing it as a system. Following IDEF0, a content analysis framework was applied in this research, categorizing the SSCM literature in five content categories, which is illustrated in Figure 1. The components displayed in Figure 1 are structured based on the language’s syntax defined for IDEF0 [45]. The boxes represent functions that, in the context of this study, show what must be accomplished to green a supply chain. The input arrows located on the left side of the diagram are the data or objects that are alerted by the functions to produce the outputs, which are displayed as exiting arrows on the right side of the box. In the context of this study, the inputs include the information flows regarding the stakeholders’ requirements that flow into the SSCM processes, and the outputs are the results of greening the supply chain in the form reflecting on the performance measures. The control arrows flowing into the top of the function box are the standards and regulations; the SSCM processes are performed under the constraints imposed by them. According to IDEF0′s syntax, if an input arrow serves as both input and control, it is shown as control only. The mechanism arrows flowing into the bottom of the function box are defined as the enablers in accomplishing the SSCM processes.

4. Classification and Review of Studies in Auto-SSCM

In this section, the results of the content analysis of the auto-SSCM literature are presented. First, a descriptive analysis of the reviewed articles is presented, which is followed by a discussion highlighting some key research issues from the literature within each category and its sub-categories.

4.1. Descriptive Analysis of the Literature Based on Their Content

To descriptively analyze the literature, the frequency of appearance of each five content category and their sub-categories (for categories and their sub-categories, see Figure 2) was counted in the sample articles. Table 1 illustrates the result of the analysis. It is necessary to note that some articles only investigated one category, while the others discussed more than one category. Hence, the frequency of the categories is more than the number of papers.
As can be seen from Table 1, “process” is the most highly studied area in auto-SSCM (almost 42%). The “output”-related studies, with about 32% of the total frequencies, constitutes the second considerable portion of the reviewed literature. “Resource”-related research placed third with about 12% of total publications. The less published areas are “inputs” and “legislations and standards”, accounting for approximately 4% and 6% of the total studies, respectively. Among “process” sub-categories, the heavily investigated area is “post-use” process, with a percentage of roughly 61%. This is far more than “supply”, with almost 20% of the publications of this category. In this sub-process, “delivery” and “use” are less explored areas, which just account for almost 2% and 6% of studies, respectively. Concerning the sub-category of “resources and mechanisms”, while the “technology”-centered studies have been favored more by researchers, “management capabilities” is a research area that is faced with a significant shortfall. Some examined articles discussed the concept of sustainability in the automotive industry, investigating how the sustainability-conscious issues can be integrated into the business strategy. They provided a comprehensive insight into the challenges that the companies encounter while developing a sustainable SC. The category of overall review represents this kind of study. As illustrated in Table 1, the articles falling into this category account for a small proportion of the total reviewed articles. Table A3 in Appendix provides more detailed information and categorizes all the reviewed articles under the five main categories.

4.2. Key Findings from the Previous Research on Auto-SSCM

In this section, the results of the content analysis of the auto-SSCM literature are presented. Figure 2 depicts a comprehensive framework of the processes and sub-processes of an auto-SSCM.

4.2.1. Legislation and Standards

Environmental management standards and legal directives on environmental issues have played a key role in extending environmentally-conscious initiatives in the automotive industry. The European Union (EU) directive on ELV Commission [46] is one of the most influential legislative policies. It forces auto manufacturers to reuse, recycle, and adopt other forms of recovery for end-of-life vehicles (ELVs) and their components, aiming at preventing waste generation from vehicles and a reduction in disposal of waste. Considering the requirements of this directive, Zorpas and Inglezakis [47] tried to investigate the challenges that the automotive industry is experiencing to meet the quantified targets for reuse and recovery per vehicle and year specified by the EU directive. Other studies such as Ferrão and Amaral [48], Johnson and Wang [48,49], and Coates and Rahimifard [50], discussed the circumstances in which EOL activities could be economical, while meeting the requirements of the EU directive on ELVs. Apart from the EU rules, some studies investigated standards in China as the largest automobile manufacturer and the biggest market in the world. For instance, Zhang and Chen [51] discussed the rules and regulations of ELVs’ plastic recovery in China and criticized that the regulations of plastic recovery in China are not as perfect as in other developed countries. Zhang and Chen [52] investigated the effect of vehicles’ emission standards set up in China (China 2, China 3, and China 4) on diesel engine remanufacturing.
ISO 14001 is the environmental management system (EMS) standard that is widely established among original equipment manufacturers (OEMs) and their suppliers [53]. Some researchers like Nawrocka et al. [53] and Gonzalez et al. [54] investigated the role of this standard on extending SSCM practices within the automotive industry. “Recycling regulation” [51], “economic instrument including free take back” [54], “landfill tax” [54], “recycling credit-fee” [54], “tax on virgin materials subsidies on recycled material” [54], “imposing tax on used car export” [55], and “extended producer responsibility” [56] are the other policy-related issues investigated in the literature.

4.2.2. Inputs (Stakeholder Requirements)

Stakeholders are a group or single entity who may influence a firm or are influenced by the firm’s goals and behaviors [57,58]. According to the literature, stakeholders are classified into internal and external types, and typically include customers, suppliers, competitors, government, community, consumers, consumer defenders, environmentalists, and collaborators [57,58]. Increasing pressure from various stakeholders has driven the automotive industry to adopt SSCM practices. However, the types of pressures and stakeholders that enforce them are variable. In this respect, Sarkis et al. [59] and Zhu et al. [60] tried to explore different stakeholders’ requirements and evaluate the impact of their pressure on the adoption of SSCM practices in the automotive industry. They also investigated the link between stakeholders’ pressure and the ultimate outcomes of implementing SSCM initiatives. Stakeholders’ pressure was examined in different automotive sectors as well as geographical areas. Lin and Lan [61] studied external pressure on Taiwanese auto component firms and investigated its possible link to the performance of the firms. Roh et al. [57] analyzed how stakeholders’ pressures affect the decision of developing hybrid cars in seven reputable automotive companies. Vanalle et al. [62] investigated stakeholders’ pressures on a Brazilian automotive SC and further explored its effect on the performance of GSCM. They found out that internal environmental management, green purchasing, and customer cooperation are the main practices adopted by suppliers in Brazil’s automotive industry, which are thanks to the high pressure from assemblers and regulations such as ISO 14000. Finally, Seles et al. [58] tried to find a relation between stakeholders’ pressures and the green bullwhip effect in a Brazilian automotive company.

4.2.3. SSCM Processes

To classify processes-related studies in auto-SSCM (as given in Figure 2), this paper adopted the classification developed by Sutherland et al. [63], which is one of the most comprehensive studies concerning the practical issues of environmental challenges in the automotive industry. Their classification is appreciated and applied by other studies, which discussed SSCM processes, such as the works published by Dyckhoff et al. [64] and Olugu et al. [65].
The first category in SSCM processes is the sustainable supply management process. There are two major directions in this research field: (1) sustainable supplier selection (SSS), and (2) sustainable supplier development (SSD). Supplier selection and evaluation (SSE) refers to the process in which a company tries to select an individual or a group of suppliers as a source of procurement. However, supplier development (SD) is a post-supplier selection process and can be defined as any effort taken on to enhance the performance of the existing supplier [66]. The majority of papers in SSS came up with grouping models or evaluation techniques that aid in selecting relevant suppliers or/and allocating orders among the suppliers (e.g., [67,68,69,70,71,72,73,74,75,76]). A few other studies developed decision support models for SSE in different sectors of the automotive industry, for instance, in logistics service providers ([77,78,79]) and spare part suppliers [80]. A different study of this area was that of Govindan et al. [81], who combined supply chain network design (SCND) with the order allocation problem in order to minimize procurement costs and environmental impacts of an automobile manufacturer in Iran. Even though SSE has been found to be a very well-discussed topic, the supplier–buyer relationship for improving the performance of suppliers has been infrequently addressed in the automotive industry. Koplin et al. [82], however, were the only authors who made an attempt to develop a sustainability concept for supply management in a focal company of the automobile industry. Their solutions for greening the supply process focused on managing the relationships with suppliers in terms of determining the relevant requirements of social and environmental aspects, evaluating and monitoring suppliers’ sustainability-related performance, and providing support for the suppliers in order to solve their social and environmental problems. Similar to the supplier–buyer relationship, SD in the automotive industry has not been a well-liked topic among researchers. The only work was conducted by Akman [83], who developed a decision support model that enables managers to evaluate suppliers and decide which supplier should be undertaken in green development program.
A portion of the studies addressed sustainability in the production process and studied the problem from different angles. Some studies pursue a sustainable production process in terms of product design for ELVs. Meeting the targets for recycling determined in the EU directive is a great challenge for the automotive industry. In this respect, studies concerning product design issues tried to provide design solutions for improving vehicle recyclability while considering economic issues. The studies conducted by [84,85,86,87] are examples of the works revolving around this topic. As a different study in this area, Pechancová [88] investigated utilizing renewable energy in the production processes of a supplier chosen from a region in the Czech Republic.
Fuel efficiency in the utilization stage of the vehicle is another issue that has been given attention in the literature. For instance, Granovskii et al. [89] compared four types of vehicles—conventional, hybrid, electric, and hydrogen fuel cell—in terms of economic and environmental aspects. Other contributions to this topic are the works of Jones [90] and Sivak and Tsimhoni [91].
Green delivery is another research topic in auto-SSCM. The primary role of delivery in SCM is highlighted in the literature [92]. Particularly, delivery is a part of SC that generates environmental waste and releases pollutant gases into the air, thus affecting the performance of an SSCM ([92]). In this line of thought, White et al. [93] addressed the issue of complexity in green packaging design in a case company, and tried to understand how the company made a tradeoff between the operational requirements and sustainability objectives. Staš et al. [94] focused on green transportation and developed a model to assess the green transportation performance. However, despite the emphasis on the importance of environmentally-friendly packaging for materials and components [95], little effort has been made to discuss this issue comprehensively.
A significant body of literature brought up the issues of the post-use stage and investigated different processes that ELVs would undergo. Figure 2 illustrates different treatments that ELVs receive in the post-use stage, and it further shows the flow of ELVs after they are entered into this phase. In the following, the papers are discussed according to the steps of ELVs depicted in Figure 2. The post-use phase starts with the collection of the used products from customers, where the reverse flow starts. In relation to this step, Krikke et al. [96] conducted a study to optimize the collection process of used products or dismantled components from EOL vehicles. Sundin and Dunbäck [97] studied the obstacles of the reverse fellow for collecting automotive mechatronic devices among a number of European automotive companies. In a similar study, [98] explored the challenges that Chinese manufacturers are facing in executing RL. In an exploratory study, Abdulrahman et al. [99] investigated the inputs and outputs of product returns management in five case studies from various industries in Malaysia, one of which was automotive. Concerning the disassembly process, Colledani and Battaïa [100] conducted the only study that addressed this problem by developing a decision support model that integrates disassembly and line balancing problems. When a vehicle undergoes the recycling process, the recyclable components are first segregated, and the remainder that are not recyclable are sent for shredding. These components are known as Automotive shredder residue (ASR); a few papers concentrated on this topic. Hwang et al. [101] and Vermeulen et al. [102] are among these studies that discussed the techniques and solutions to either increase ASR’s recyclability or improve its quality for fuel utilization. Through analyzing a shredder plant in the United Kingdom, Khodier et al. [103] pointed out that shredder plants in the United Kingdom should have better technologies and recovery techniques in shredding processes that would enable them to enhance recovery of material and energy from ASR. Among the post-use options, remanufacturing and recycling were among the favorite topics of research. Saavedra et al. [104] analyzed the attributes of the automotive’s remanufacturing industry in Brazil through an exploratory study, where the researchers highlighted the roles of the government and associations in motivating the remanufacturing companies to expand their business. Similarly, Yusop et al. [105] conducted research within the Malaysian automotive industry to realize the know-how level of remanufacturers. Chaowanapong et al. [106] derived primary factors that affect the remanufacturing decision in the Thailand automotive industry. Ramoni and Zhang [107] debated the issues of recycling as the common method for ELV treatment of electric vehicle batteries, and suggested remanufacturing as a viable option that would be more environmentally friendly. In line with this type of study, some research works were performed to aid in ELV recovery systems and management. In this context, Đorđević and Kokić [108], Ahmed et al. [109], Keivanpour et al. [110], and Kuik et al. [111] developed decision-making models for selecting recovery options including reuse, remanufacturing, recycling, and energy recovery. Subramoniam et al. [112] and Ahmed et al. [109] addressed strategic issues concerning the remanufacturing of auto parts. Yang et al. [86] and Anthony and Cheung [113] discussed the issue of design for remanufacturing, which involves integrating remanufacturing factors into different perspectives of product design. Recycling is another reprocessing option studied in the literature. Li et al. [114] evaluated the environmental impact of ELVs’ recycling in China by examining Corolla taxis as a subject of analysis. Chavez and Sharma [115] studied the chemical recycling of polyethylene terephthalate seats in the Mexican automotive sector from economic and environmental perspectives. There are also some different studies [116] that focused on recycling specific materials (i.e., car plastic, aluminum) with the intention of coming up with the processes and techniques to increase the recyclability rate, while taking economic issues into consideration.

4.2.4. Resources/Mechanisms

A variety of resources and mechanisms are required to carry out SSCM processes effectively. From the literature review, it can be seen that three main categories of resources have attracted the attention of researchers, which are shown in Figure 2. Therefore, in the following paragraphs, the papers of this group will be discussed according to the subcategories presented in Figure 2.
In most cases, the literature concerning SSCM processes is intertwined with the literature of SCND. In other words, SCND is considered as a key element for implementing SSCM processes. With respect to this matter, the topic of “CLSC/RL network design” has been deeply studied by several researchers [117,118,119,120,121,122,123,124,125]. The main objectives of these studies are determining optimal locations and material flows, while satisfying the capacities and demand as constraints. According to the description provided by Sutherland et al. [63], a typical structure for auto-SSCM is drawn in Figure 3.
Technology is another major resource that lays the foundation for the accomplishment of SSCM practices. As noted by Sutherland et al. [64], the automotive recovery system is heavily dependent on the capabilities provided by the recycling technologies. To emphasize the key role of technology in driving recycling and remanufacturing initiatives in Auto-SSCM, some articles addressed this topic in detail. The works by Boks and Tempelman [126] and Pickering [127] represent the direction of these types of studies. In this line of research, some scholars reviewed specific technologies and brought up their specifications, applications, implementation challenges, and future research needs. For instance, Zhang and Chen [51] studied recycling technology and equipment that are utilized for treating the plastic components of ELVs in China’s automotive industry. The authors expressed the reasons why ELVs’ plastic recycling system in China is not as perfect as those of other developed countries. Günther et al. [128] underlined the impact of electric vehicles on deriving an SSCM, and further anticipated future development of the automotive industry in applying this type of vehicle. The examples of other technologies presented in the literature are as follows: ASR treatment technology [102,129], ELV recovery technology [130], fuel-propulsion system technologies [131], integrated management system (IMS) for EOL tires [132], recycling technology [51,133], reverse engineering technologies for remanufacturing [134], battery electric vehicles (BEV) [135], and automotive components remanufacturing [136]. The study of Förster [137] is relatively different from those reviewed above. The authors studied the future technologies that would facilitate sustainable production within the scope of German automotive manufacturers. They further tried to designate the time when the technology will be commonly used in the German industry.
It goes without saying that management skills are an imperative part of the successful implementation of SSCM practices. Management skills include all the management capabilities, systems, and strategies that are utilized, intending to improve the sustainability of SC. Reviewing the content of the works in this area reveals that the topic of management skills has diversely been discussed in the relevant literature. For example, the work done by Ferguson and Browne [138] and Rahimifard et al. [139] argued for designing information systems to support ELV recovery activities.
The studies conducted by Vachon and Klassen [140] and Samson Simpson, et al. [141] were about relationship and collaboration management, covering issues related to collaboration with suppliers and customers in environmentally-related initiatives. Another topic seen in the literature is SC capabilities (SCCs), which refers to the combination of people skills and knowledge, physical assets, and organizational routines. In this respect, Liu et al. [142] and Liu et al. [143] analyzed the role of SCCs in the implementation of sustainable strategies and practices. Finally, Xie [144] investigated the impact of cooperative strategies on sustainability in the automotive industry and concluded that the industry can benefit from a cooperative strategy, as it can positively affect the sustainability of SC.

4.2.5. Outputs (Performance)

An SC may not achieve its sustainable objectives without having an appropriate system that measures the performance of the SC’s practices. When it comes to the automotive industry, measuring performance is very demanding as the industry is very unusual and complex [65]. Given the importance of the output phase in the automotive industry, many existing studies discussed this important issue by taking up two major directions: 1—defining performance measures and/or 2—designing measurement systems. The first type of research (e.g., [60,93,106,145,146,147,148]) tried to develop key performance indicators (measures) and measurement procedure for evaluating particular practices for SSCM and/or investigating the impact of the green practices on economic and environmental performance. The measures appeared with different terminology in the literature, typically termed as drivers, barriers, enablers, and success factors. The studies did not confine their investigation merely to the identification of the measures, but some rather investigated the interactions among measures as well (e.g., [149,150,151]). The second group of studies (e.g., [62,65,152,153,154,155]) were dedicated to measuring the ultimate outcomes of SSCM in terms of social, environmental, and economic performance. In this group, apart from some studies that investigated only sustainable performance of automotive SC, some others were developed in combination with other SCs’ characteristics to assess the performance more comprehensively; for example, with resilient [156]; lean and resilient [157]; lean, agile, and resilient [155]; customer-centric and customer pressure [158]; and green human resource management [159]. Talking about the output phase generally, the problem was investigated across the industry of emerging markets (e.g., [106,145,160,161,162,163,164,165,166,167,168,169,170,171]). However, few studies investigated the problem within European industries [159,172]. Furthermore, developing models to measure the performance for automotive components was observed to be under-researched in this category (e.g., [169,172,173]).

5. Implications for Designing an Auto-SSCM

The comprehensive review of all issues in the research area of auto-SSCM provides useful insights into the aspects required to be considered while designing an automotive SSC. On the basis of the findings of the review, this section presents a practical guideline for designing a sustainable SC (SSC) in the automotive industry, which could be a useful resource for practitioners, managers, and policymakers who aim to plan for designing their sustainable SSC.
Figure 4 illustrates five stages in which an automotive SSC can be designed and implemented. The main goal of this procedure is to help designing an automotive SSC that would generate values for stakeholders and that, at the same time, is aligned with the policy requirements enforced by legislation and standards. According to the key findings of the literature review presented in this paper, stakeholders’ requirements are the main inputs for designing an automotive SSC. In addition, an automotive SSC is designed under the controls of legislation and environmental management standards. In this respect, as shown in Figure 4, the automotive SSC designers should initially analyze the stakeholders’ requirements related to the environmental, social, and economic performance that are expected to be achieved. Meanwhile, they would examine the requirements of environmental regulations and standards.
Stakeholders may include a wide variety of sources in the automotive industry. Customers are one of the main external stakeholders of any firm, who impose normative isomorphic pressure on them to adopt environmental strategies [174]. Firms have been increasingly influenced by consumers’ ethical values and ecological thinking, pushing them to address environmental management practices [175]. Firms’ successful competitors are the second important stakeholders who motivate them to improve their environmental management systems [176]. Previous studies showed that the pressure from competitors in the form of mimicking isomorphic is one of the major drivers of implementing environmental management practices [177,178]. Non-governmental organizations (NGOs), media, local communities, and environmental interest groups are external stakeholders who do not participate in a firm’s transactions, but are affected by the organization [179,180]. These stakeholders are a source of coercive pressure that can influence companies’ decisions to adopt environmental strategies [176]. Thus, the requirements of all these stakeholders should be taken in designing an automotive SSC.
Concerning the legislation, governmental bodies with environmental management legislation, such as waste reduction, cleaner production, resource savings, and conservation regulations, are forcing companies to implement environmental practices across their value chain [7]. In this respect, an automotive SSC should follow the requirements of legislation and environmental management standards while designing the SSC. At the end of the first stage of design, a formal document can be provided by decision makers, representing the results of the requirement analysis.
To satisfy stakeholders’ and regulatory requirements, at the second stage, the processes of the whole SC are required to be designed with eco-design provisions. As has been previously stated in Section 5.2.3, this involves designing SSCM processes, such as supply, production, delivery, use, and post-use. Including eco-design aspects into SSC design can ensure that SSCM processes are planned to maximize environmental performances or mitigate the environmental impact of SCM operations (i.e., reducing waste and emissions; increasing rate of reuse, recycling, and recovery).
The processes coupled with sustainable supply remarkably affect the environmental impacts of products through resource reduction and waste elimination [181]. The sustainable supply process can be classified into two major sub-processes: (1) sustainable purchasing that entails using environmentally friendly materials to reduce resource usage in production, and (2) SSS/SSD that includes integrating environmental initiatives into selection and management of suppliers in sourcing. The production phase might involve a wide range of manufacturing processes, accounting for a large amount of potential pollution and waste generation. In this respect, taking environmental-related actions to design and optimize the production process would critically contribute to the efficient resource usage, pollution prevention, and waste management [182,183]. On the downstream side of the SC, there are processes associated with delivery and consumption that might affect the environment [182,183]. In the green delivery process, the entire process of delivery to customers will be set up to reduce the environmental impact. The green consumption process, on the other hand, entails integrating the customer’s voice into the firm’s environmental activities and collaboration with customers to reduce the environmental impact of products in the usage stage.
To transfer from the traditional SC towards the SSC, an extension of the SC including product and material recovery operations has been suggested in the literature. Recovery management is an important process in the transition to SSCM, which takes place in the post-use stage. Recovery management involves product recovery options, such as repair, refurbishing, remanufacturing, cannibalization, and material recycling from packages or EOL products [184]. Investment recovery in terms of product and material reuse or selling the scrap or used materials and components is another process in the post-use stage that has been introduced in previous studies. Investment recovery seeks to find alternative uses for products, components, or materials that no longer create direct value for the firm [185].
In order to implement the designed SSCM processes, the proper infrastructures are supposed to be acquired at stage 3. This includes the appropriate forward and reverse logistics networks, clean technologies, and management capabilities.
After finalizing the design stages and acquiring the related resources, the designed automotive SSC can be implemented in stage 4. The ultimate outcome of such an implemented auto-SSCM is expected to be the realization of sustainable values by all the SC’s stakeholders. In this respect, within stage 5, the expected sustainable values generated as a result of implementing the designed SSC would be measured, and the corrective actions will be done according to the results of the performance measurement system.

6. Research Gaps and Recommendations for Future Research

Despite the growing body of the extant literature on SSCM in the automotive industry, there are yet a couple of areas that are not studied to an adequate degree. According to the comprehensive literature review conducted in this research, the main research implications are provided in the following as the basis for future research. These suggestions might be suitable for researchers who wish to work further on advancing this research field.
The automotive industry is an industry that is highly influenced and shaped by its stakeholders’ (e.g., investors, governments, employees, consumers, competitors) demands. As our study shows, investigating the stakeholders’ requirements is one of the less studied areas in the literature. Specially, we discovered that a few studies available in this literature have mainly focused on the effect of stakeholders’ pressure on performance or adoption of environmental policies of a single firm. The automotive industry has a complex supply chain network with many tiers, where environmental degradation happens mostly within the supply chain network. Future studies should be directed toward how stakeholders’ requirements may affect the collaboration of supply chain tiers in the automotive industry in responding to the pressure.
Discussing the stakeholders’ pressure further, future research needs to catch up with the fast growth of the industry and changing stakeholders’ expectations. Given the globalization of the industry and the universal growth of car manufacturing, the stakeholders’ demands are constantly changing, putting more pressure on the industry to ensure that the sustainable requirements of the stakeholders are met. For instance, the industry is moving toward zero emissions and clean cities through renewable energies for electricity and alternative fuels by 2050 [186]. In this regard, it is crucial for the automotive industry to respond effectively to the complex and evolving needs of its stakeholders. To help the industry in tackling this issue, more academic research is required. For example, identifying the most influential stakeholders and investigating the change in their needs and expectations with growth of technology can be a promising research area. Furthermore, the growth in technology also increases the challenges of making the balance between environmental expectations of stakeholders and the economic benefit of the industry. These are some of the main challenges that leave a substantial room for future studies.
Concerning the aforementioned matter, it is further observed that the effect of stakeholders’ requirements on the relationship between different tiers in SC is largely unexplored. For instance, it is still not clear how different tiers in the automotive supply chain work collaboratively to address the environmental concern or regulations in the industry. Furthermore, the relationship between the tiers can additionally be joined to performance indicators of an SSC to explore how stakeholders’ requirements and the relationship between different tiers may affect the performance of an SSC.
Legislation and standards is another area that is not deeply studied. The studies have thus far investigated the problem across only one emerging economy (i.e., China) and in a few automobile sectors (i.e., plastic industry). There is not much knowledge about the effect of legislation and standards on the automobile sectors of several countries, particularly on the world’s major automobile manufacturers (i.e., India, Brazil). In addition, further research is required to study the impact of legislation and standards on reprocessing activities of various components in the automotive industry.
As to the sub-categories of SSCM processes, far more studies have been done on the post-use process compared with other sub-categories. Thus, more researches are needed to be conducted in the sub-categories of delivery, supply, production, and use to make a balance between the number of research in all sub-groups. Future studies in these sub-classes of SSCM processes would also lead to the development of the field.
In spite of the strategic importance of management capabilities for developing an SSCM, this topic is observed to be an under-researched area. Although the importance role of management capabilities including information management, relatiohnship and collaboration management, risk and knowledge management, and human resource management in the supply chain has been already very well researched in the literature of traditional SCM, it is certainly less investigated in the auto SSCM literature.
Despite the growing body of literature in the field of performance analysis, little effort has been made to discuss the intangible values that could be created by sustainability-conscious practices in the automotive industry. Studying the latent cost or intangible values of SSCM practices would provide a better understanding of the link between SSCM implementation and organizational performance, which could encourage proactive adoption of SSCM practices beyond the legislation.
The sustainability reports of the top-ranking car manufacturers are valuable secondary resources presenting the best sustainability-conscious practices in addition to the performance outcomes of the practices. These valuable sources have rarely been investigated in the reviewed literature. Future studies can develop further practical studies in this area relying on the useful information provided in these reports. Designing expert systems for measuring the environmental performance of automotive SCs and benchmarking with the best practices in this industry is an example.
Reviewing the available studies discloses that they have only discussed the selected stages of auto-SSCM. However, more studies should be conducted to develop an integrated perspective that resembles several processes of SSCM (or ideally even the whole processes). Doing so not only can boost the potential of designing a more sustainable SCM, but also would allow researchers to analyze the interaction between the processes and stages to make a transition toward a more sustainable SC.
Other than the aforementioned recommendation for future research adopted from the processes analysis, we observed a couple of other research gaps that are worth further investigation in the future:
The focus of studies in the automotive industry has only been on single countries so far. The practices and lessons learned from every country are different and comparing countries may shed more light on the establishment of a more sustainable automotive industry.
There is a growing concern on the social aspects of supply chains in the literature. We found only nine papers in our sample addressed a social issue. The social aspects of an automotive supply chain such as safety, health, training, education of the employees and their satisfaction, community development, and public policy of companies are understudied to a great extent.
The concentration of the studies in the literature has mostly been on large to medium size companies. The supply chain of automotive companies may include many small-sized companies’ employees and the level of adaptation of sustainability may be different for these companies compared with the large to medium sized ones. So, future studies should investigate the adaptation of sustainability by small companies.

7. Conclusions

The study at hand presented a process-oriented review of the studies in the area of auto-SSCM. A broad range of publications was collected, applying a structured and systematic approach, where the core themes addressed in the literature of auto-SSCM were classified and discussed. To categorize the papers, a content analysis framework was developed based on IDEF0, which divided the studies into a number of major processes in the industry, namely (1) inputs/stakeholder requirements; (2) legislation and standards; (3) SSCM process, (4) resources/mechanisms; and (5) outputs/performance. Relying on the results of the investigation into the different aspects of auto-SSCM literature, a five-stage procedure was presented that can be used as a guideline to design an automotive SSC. The content analysis resulted in the identification of several promising research opportunities that will require further investigation.
Even though this review paper applied a rigorous and systematic research methodology, it carries some limitations like any other review study. The first limitation is affiliated with the search phase, where we limited our search to the papers published in journals, and skipped other scientific resources (i.e., theses, conference papers, and book chapters). Adding these overlooked resources to the sample papers could have led to additional studies that may derive further insights. As another limitation, this review is structured on the basis of the processes in the automotive industry, and not based on other characteristics of the studies (e.g., model’s characteristics). Obviously, conducting a different content analysis approach on the same sample will lead to a different study that may provide beneficial insights. This limitation will be left for future studies.

Author Contributions

S.M.M. prepared the original draft and reviewed and edited the final draft. N.K. updated the origanial draft by including the recent literature, and reviewed and edited the final draft. S.H.A.-R. supervised the research, and reviewed the final draft.

Funding

This research received no external funding.

Acknowledgments

This study is supported by the Exploratory Research Grant Scheme (ERGS Grant No. ER033-2011A) from Malaysian Ministry of Higher Education.

Conflicts of Interest

The authors declare no conflict of interest.

Appendix A

Table A1. Review studies in the area of sustainable supply chain management (SSCM) published from 2016 onward. GSCM—green SCM.
Table A1. Review studies in the area of sustainable supply chain management (SSCM) published from 2016 onward. GSCM—green SCM.
No.SourceArea of StudyObjectiveIndustry-Oriented
1[187]SSCMReviewing the studies applied system dynamic approach in renewable energy in SSCM×
2[188]SSCMReviewing and classifying the whole area in order to find research gaps, and building a theoretical framework to define world-class SSCM×
3[189]SSCMReviewing the themes and challenges of social sustainability in the context of SCs×
4[190]SSCMTracking the integration of sustainable dimensions of automated guided vehicles into SCs×
5[24]SSCMAnalyzing the advancement of sustainability issue for mineral SC
6[25]SSCMPresenting an overview of the studies addressed social issues in SSCM in the textile industry
7[26]SSCMReview of the studies related to sustainable management and optimization of biorefinery SC
8[191]SSCMA systematic literature review of the role of information systems in supporting SSCM×
9[192]GSCMBuilding a conceptual framework on GSCM and proposing future research opportunities×
10[22]SSCMTracking the emergence of SSCM topic in the literature×
11[27]SSCMDeriving the key elements of SSCM implementation in the oil and gas industry and their relationship
12[17]GSCMReview of the practices and aspect of GSCM×
13[193]GSCMDrivers and barriers of adopting GSCM practices in Asian emerging economies×
14[194]GSCMIdentifying the factors affecting GSCM in small and medium enterprises (SMEs)×
15[28]GSCMInvestigating the effect of GSCM practices on U.K. food SMEs
16[195]GSCMAnalyzing and classifying past studies in the area of GSCM×
17[196]GSCMReview of the models in SC dealing with optimizing CO2 emission×
18[197]GSCMInvestigating the interaction between GSCM and green SC performance×
19[198]GSCMGiving an overview of the drivers and barriers of SSCM×
20[199]SSCMDeriving energy-related measurements in SSCM×
21[200]SSCMReview of the studies pertained to sustainable
SC innovation
×
22[29]SSCMReviewing the development of SSCM in the fashion industry
23[201]GSCMReviewing and classification of GSCM models and concepts×
Table A2. Distribution of studies over different journals and years.
Table A2. Distribution of studies over different journals and years.
Journal1995–20002001–20052006–20102011–20152016–2017Total
Journal of Cleaner Production 14122037
Journal of Material Cycles and Waste Management 56112
International Journal of Production Economics 3249
Resources, Conservation and Recycling212139
Waste Management 31329
The International Journal of Advanced Manufacturing Technology 628
Journal of Remanufacturing 448
Benchmarking: An International Journal 1427
Production Planning & Control 246
Sustainability 1146
The International Journal of Life Cycle Assessment123 6
Jom 12115
International Journal of Production Research 224
Business Strategy and the Environment 11114
Journal of Manufacturing Technology Management 1113
Computers & Industrial Engineering 123
Transportation Research Part E: Logistics and Transportation Review 1113
International Journal of Operations & Production Management1 2 3
Global Business Review 123
Supply Chain Management: An International Journal 2 13
Chemosphere 2 2
Flexible Services and Manufacturing Journal 112
Ecological Economics 11 2
European Journal of Operational Research 2 2
Journal of Hazardous Materials 2 2
Technovation2 2
Annals of Operations Research 22
International Journal of Sustainable Engineering 22
Expert Systems with Applications 112
Others *564173163
Total1118367094229
* This category includes articles from several journals only published one paper.
Table A3. Classification of auto-sustainable supply chain management (SSCM) papers.

References

  1. Orsato, R.; Wells, P. The automobile industry & sustainability. J. Clean. Prod. 2007, 15, 989–993. [Google Scholar]
  2. Mathivathanan, D.; Haq, A.N. Comparisons of sustainable supply chain management practices in the automotive sector. Int. J. Bus. Perform. Supply Chain Model. 2017, 9, 18–27. [Google Scholar] [CrossRef]
  3. Adams, W.J. The automobile industry. In The Structure of European Industry; Springer: Dordrecht, Netherlands, 1981; pp. 187–207. [Google Scholar]
  4. Binder, A.; Rae, J. Encyclopedia Britannica. Last Update 4th August. Available online: http://global.britannica.com/EBchecked/topic/45050/automotive-industry 2013 (accessed on 4 June 2017).
  5. Xia, X.; Govindan, K.; Zhu, Q. Analyzing internal barriers for automotive parts remanufacturers in China using grey-DEMATEL approach. J. Clean. Prod. 2015, 87, 811–825. [Google Scholar] [CrossRef]
  6. Larsson, A. The development and regional significance of the automotive industry: Supplier parks in Western Europe. Int. J. Urban Reg. Res. 2002, 26, 767–784. [Google Scholar] [CrossRef]
  7. Zhu, Q.; Sarkis, J.; Lai, K.-H. Institutional-based antecedents and performance outcomes of internal and external green supply chain management practices. J. Purch. Supply Manag. 2013, 19, 106–117. [Google Scholar] [CrossRef]
  8. Govindan, K.; Azevedo, S.; Carvalho, H.; Cruz-Machado, V. Lean, green and resilient practices influence on supply chain performance: Interpretive structural modeling approach. Int. J. Environ. Sci. Technol. 2015, 12, 15–34. [Google Scholar] [CrossRef]
  9. Mathivathanan, D.; Kannan, D.; Haq, A.N. Sustainable supply chain management practices in Indian automotive industry: A multi-stakeholder view. Resour. Conserv. Recycl. 2018, 128, 284–305. [Google Scholar] [CrossRef]
  10. Brundtland, G. World Commission on Environment and Development; Oxford University Press: Oxford, UK, 1987. [Google Scholar]
  11. Ashby, A.; Leat, M.; Hudson-Smith, M. Making connections: A review of supply chain management and sustainability literature. Supply Chain Manag. Int. J. 2012, 17, 497–516. [Google Scholar] [CrossRef]
  12. Ahi, P.; Searcy, C. A comparative literature analysis of definitions for green and sustainable supply chain management. J. Clean. Prod. 2013, 52, 329–341. [Google Scholar] [CrossRef]
  13. Beamon, B.M. Designing the green supply chain. Logist. Inf. Manag. 1999, 12, 332–342. [Google Scholar] [CrossRef] [Green Version]
  14. Srivastava, S.K. Green supply-chain management: A state-of-the-art literature review. Int. J. Manag. Rev. 2007, 9, 53–80. [Google Scholar] [CrossRef]
  15. Fleischmann, M.; Bloemhof-Ruwaard, J.M.; Dekker, R.; Van der Laan, E.; Van Nunen, J.A.; Van Wassenhove, L.N. Quantitative models for reverse logistics: A review. Eur. J. Oper. Res. 1997, 103, 1–17. [Google Scholar] [CrossRef] [Green Version]
  16. Guide, V.D.R., Jr.; Van Wassenhove, L.N. Closed-loop supply chains: An introduction to the feature issue (part 1). Prod. Oper. Manag. 2006, 15, 345–350. [Google Scholar] [CrossRef]
  17. Islam, S.; Karia, N.; Fauzi, F.B.A.; Soliman, M. A review on green supply chain aspects and practices. Manag. Mark. 2017, 12, 12–36. [Google Scholar] [CrossRef] [Green Version]
  18. Carter, C.R.; Liane Easton, P. Sustainable supply chain management: evolution and future directions. Int. J. Phys. Distrib. Logist. Manag. 2011, 41, 46–62. [Google Scholar] [CrossRef]
  19. Machi, L.A.; McEvoy, B.T. The literature review: Six steps to success; Corwin Press: Sauzen Oaks, CA, USA, 2016. [Google Scholar]
  20. Creswell, J.W.; Creswell, J.D. Research Design: Qualitative, Quantitative, and Mixed Methods Approaches; Sage publications: Thousand oaks, CA, USA, 2017. [Google Scholar]
  21. Govindan, K.; Soleimani, H. A review of reverse logistics and closed-loop supply chains: A Journal of Cleaner Production focus. J. Clean. Prod. 2017, 142, 371–384. [Google Scholar] [CrossRef]
  22. Rajeev, A.; Pati, R.K.; Padhi, S.S.; Govindan, K. Evolution of sustainability in supply chain management: A literature review. J. Clean. Prod. 2017, 162, 299–314. [Google Scholar] [CrossRef]
  23. Beske, P.; Land, A.; Seuring, S. Sustainable supply chain management practices and dynamic capabilities in the food industry: A critical analysis of the literature. Int. J. Prod. Econ. 2014, 152, 131–143. [Google Scholar] [CrossRef]
  24. Sauer, P.C.; Seuring, S. Sustainable supply chain management for minerals. J. Clean. Prod. 2017, 151, 235–249. [Google Scholar] [CrossRef]
  25. Köksal, D.; Strähle, J.; Müller, M.; Freise, M. Social Sustainable Supply Chain Management in the Textile and Apparel Industry—A Literature Review. Sustainability 2017, 9, 100. [Google Scholar] [CrossRef]
  26. Pérez, A.T.E.; Camargo, M.; Rincón, P.C.N.; Marchant, M.A. Key challenges and requirements for sustainable and industrialized biorefinery supply chain design and management: A bibliographic analysis. Renew. Sustain. Energy Rev. 2017, 69, 350–359. [Google Scholar] [CrossRef]
  27. Ahmad, N.K.W.; de Brito, M.P.; Rezaei, J.; Tavasszy, L.A. An integrative framework for sustainable supply chain management practices in the oil and gas industry. J. Environ. Plan. Manag. 2017, 60, 577–601. [Google Scholar] [CrossRef]
  28. Ali, A.; Bentley, Y.; Cao, G.; Habib, F. Green supply chain management–food for thought? Int. J. Logist. Res. Appl. 2017, 20, 22–38. [Google Scholar] [CrossRef]
  29. Khurana, K.; Ricchetti, M. Two decades of sustainable supply chain management in the fashion business, an appraisal. J. Fash. Mark. Manag. 2016, 20, 89–104. [Google Scholar] [CrossRef]
  30. Fahimnia, B.; Sarkis, J.; Davarzani, H. Green supply chain management: A review and bibliometric analysis. Int. J. Prod. Econ. 2015, 162, 101–114. [Google Scholar] [CrossRef]
  31. Abedinnia, H.; Glock, C.H.; Schneider, M.; Grosse, E.H. Machine scheduling problems in production: A tertiary study. Comput. Ind. Eng. 2017, 111, 403–416. [Google Scholar] [CrossRef]
  32. Hochrein, S.; Glock, C.H. Systematic literature reviews in purchasing and supply management research: A tertiary study. Int. J. Integr. Supply Manag. 2013, 7, 215–245. [Google Scholar] [CrossRef]
  33. Saunders, M.N. Research Methods for Business Students, 5/e; Pearson Education Edinburgh: London, UK, 2011. [Google Scholar]
  34. Marasco, A. Third-party logistics: A literature review. Int. J. Prod. Econ. 2008, 113, 127–147. [Google Scholar] [CrossRef]
  35. Abedinnia, H.; Glock, C.H.; Schneider, M.D. Machine scheduling in production: A content analysis. Appl. Math. Model. 2017, 50, 279–299. [Google Scholar] [CrossRef]
  36. Shekarian, E.; Rashid, S.H.A.; Bottan, E.; De, S.K. Fuzzy inventory models: A comprehensive review. Appl. Soft Comput. 2017. [Google Scholar] [CrossRef]
  37. Tranfield, D.; Denyer, D.; Smart, P. Towards a methodology for developing evidence-informed management knowledge by means of systematic review. Br. J. Manag. 2003, 14, 207–222. [Google Scholar] [CrossRef]
  38. Cooper, H. Research Synthesis and Meta-Analysis: A Step-by-Step Approach; Sage publications: Thousand Oaks, CA, USA, 2015. [Google Scholar]
  39. Seuring, S.; Müller, M. From a literature review to a conceptual framework for sustainable supply chain management. J. Clean. Prod. 2008, 16, 1699–1710. [Google Scholar] [CrossRef]
  40. Yong-Hak, J. Web of Science; Thomson Reuters: Eagan, MN, USA, 2013. [Google Scholar]
  41. Chicksand, D.; Watson, G.; Walker, H.; Radnor, Z.; Johnston, R. Theoretical perspectives in purchasing and supply chain management: An analysis of the literature. Supply Chain Manag. Int. J. 2012, 17, 454–472. [Google Scholar] [CrossRef]
  42. Cheng-Leong, A.; Li Pheng, K.; Keng Leng, G.R. IDEF*: A comprehensive modelling methodology for the development of manufacturing enterprise systems. Int. J. Prod. Res. 1999, 37, 3839–3858. [Google Scholar] [CrossRef]
  43. Woolridge, A.; Morrissey, A.; Phillips, P.S. The development of strategic and tactical tools, using systems analysis, for waste management in large complex organisations: A case study in UK healthcare waste. Resour. Conserv. Recycl. 2005, 44, 115–137. [Google Scholar] [CrossRef]
  44. Fenech, C.; Nolan, K.; Rock, L.; Morrissey, A. Development of a decision-support tool for identifying the most suitable approach to achieve nitrate source determination. Environ. Sci. Process. Impacts 2014, 16, 2564–2570. [Google Scholar] [CrossRef] [Green Version]
  45. Kim, S.-H.; Jang, K.-J. Designing performance analysis and IDEF0 for enterprise modelling in BPR. Int. J. Prod. Econ. 2002, 76, 121–133. [Google Scholar] [CrossRef]
  46. Commission, E. Directive 2000/53/EC of the European Parliament and of the Council of 18 September 2000 on end-of-life vehicles. Off. J. Eur. Communities 2000, 269, 34–269. [Google Scholar]
  47. Zorpas, A.A.; Inglezakis, V.J. Automotive industry challenges in meeting EU 2015 environmental standard. Technol. Soc. 2012, 34, 55–83. [Google Scholar] [CrossRef]
  48. Ferrao, P.; Amaral, J. Assessing the economics of auto recycling activities in relation to European Union Directive on end of life vehicles. Technol. Forecast. Soc. Chang. 2006, 73, 277–289. [Google Scholar] [CrossRef]
  49. Johnson, M.; Wang, M. Evaluation policies and automotive recovery options according to the European Union directive on end-of-life vehicles (ELV). Proc. Inst. Mech. Eng. Part D J. Automob. Eng. 2002, 216, 723–739. [Google Scholar] [CrossRef]
  50. Coates, G.; Rahimifard, S. Cost Models for Increased Value Recovery from End-of-Life Vehicles; CIRP Life Cycle Engineering Conference; Loughborough University: Loughborough, UK, 2006. [Google Scholar]
  51. Zhang, H.; Chen, M. Current recycling regulations and technologies for the typical plastic components of end-of-life passenger vehicles: A meaningful lesson for China. J. Mater. Cycles Waste Manag. 2014, 16, 187–200. [Google Scholar] [CrossRef]
  52. Zhang, J.-H.; Chen, M. Assessing the impact of China’s vehicle emission standards on diesel engine remanufacturing. J. Clean. Prod. 2015, 107, 177–184. [Google Scholar] [CrossRef]
  53. Nawrocka, D.; Brorson, T.; Lindhqvist, T. ISO 14001 in environmental supply chain practices. J. Clean. Prod. 2009, 17, 1435–1443. [Google Scholar] [CrossRef]
  54. Mazzanti, M.; Zoboli, R. Economic instruments and induced innovation: The European policies on end-of-life vehicles. Ecol. Econ. 2006, 58, 318–337. [Google Scholar] [CrossRef]
  55. Kumar, S.; Yamaoka, T. System dynamics study of the Japanese automotive industry closed loop supply chain. J. Manuf. Technol. Manag. 2007, 18, 115–138. [Google Scholar] [CrossRef]
  56. Xiang, W.; Ming, C. Implementing extended producer responsibility: vehicle remanufacturing in China. J. Clean. Prod. 2011, 19, 680–686. [Google Scholar] [CrossRef]
  57. Roh, J.J.; Yang, M.G.; Park, K.; Hong, P. Stakeholders’ pressure and managerial responses: lessons from hybrid car development and commercialisation. Int. J. Bus. Inf. Syst. 2015, 18, 506–529. [Google Scholar] [CrossRef]
  58. Seles, B.M.R.P.; de Sousa Jabbour, A.B.L.; Jabbour, C.J.C.; Dangelico, R.M. The green bullwhip effect, the diffusion of green supply chain practices, and institutional pressures: Evidence from the automotive sector. Int. J. Prod. Econ. 2016, 182, 342–355. [Google Scholar] [CrossRef]
  59. Sarkis, J.; Gonzalez-Torre, P.; Adenso-Diaz, B. Stakeholder pressure and the adoption of environmental practices: The mediating effect of training. J. Oper. Manag. 2010, 28, 163–176. [Google Scholar] [CrossRef]
  60. Zhu, Q.; Sarkis, J.; Lai, K.-H. Green supply chain management: Pressures, practices and performance within the Chinese automobile industry. J. Clean. Prod. 2007, 15, 1041–1052. [Google Scholar] [CrossRef]
  61. Lin, L.-H.; Lan, J.-F. Green supply chain management for the SME automotive suppliers. Int. J. Automot. Technol. Manag. 2013, 13, 372–390. [Google Scholar] [CrossRef]
  62. Vanalle, R.M.; Ganga, G.M.D.; Godinho Filho, M.; Lucato, W.C. Green supply chain management: An investigation of pressures, practices, and performance within the Brazilian automotive supply chain. J. Clean. Prod. 2017, 151, 250–259. [Google Scholar] [CrossRef]
  63. Sutherland, J.; Gunter, K.; Allen, D.; Bauer, D.; Bras, B.; Gutowski, T.; Murphy, C.; Piwonka, T.; Sheng, P.; Thurston, D. A global perspective on the environmental challenges facing the automotive industry: State-of-the-art and directions for the future. Int. J. Veh. Des. 2004, 34, 86–110. [Google Scholar] [CrossRef]
  64. Dyckhoff, H.; Souren, R.; Keilen, J. The expansion of supply chains to closed loop systems: A conceptual framework and the automotive industry’s point of view. In Supply Chain Management and Reverse Logistics; Springer: Berlin, Germany, 2004; pp. 13–34. [Google Scholar]
  65. Olugu, E.U.; Wong, K.Y.; Shaharoun, A.M. Development of key performance measures for the automobile green supply chain. Resour. Conserv. Recycl. 2011, 55, 567–579. [Google Scholar] [CrossRef]
  66. Glock, C.H.; Grosse, E.H.; Ries, J.M. Decision support models for supplier development: Systematic literature review and research agenda. Int. J. Prod. Econ. 2017, 193, 798–812. [Google Scholar] [CrossRef]
  67. Kannan, D.; Khodaverdi, R.; Olfat, L.; Jafarian, A.; Diabat, A. Integrated fuzzy multi criteria decision making method and multi-objective programming approach for supplier selection and order allocation in a green supply chain. J. Clean. Prod. 2013, 47, 355–367. [Google Scholar] [CrossRef]
  68. Kumar, A.; Jain, V.; Kumar, S. A comprehensive environment friendly approach for supplier selection. Omega 2014, 42, 109–123. [Google Scholar] [CrossRef]
  69. Kumar Sahu, N.; Datta, S.; Sankar Mahapatra, S. Green supplier appraisement in fuzzy environment. Benchmarking Int. J. 2014, 21, 412–429. [Google Scholar] [CrossRef]
  70. Hashemi, S.H.; Karimi, A.; Tavana, M. An integrated green supplier selection approach with analytic network process and improved Grey relational analysis. Int. J. Prod. Econ. 2015, 159, 178–191. [Google Scholar] [CrossRef]
  71. Yu, Q.; Hou, F. An approach for green supplier selection in the automobile manufacturing industry. Kybernetes 2016, 45, 571–588. [Google Scholar] [CrossRef]
  72. Neumüller, C.; Lasch, R.; Kellner, F. Integrating sustainability into strategic supplier portfolio selection. Manag. Decis. 2016, 54, 194–221. [Google Scholar] [CrossRef]
  73. Luthra, S.; Govindan, K.; Kannan, D.; Mangla, S.K.; Garg, C.P. An integrated framework for sustainable supplier selection and evaluation in supply chains. J. Clean. Prod. 2017, 140, 1686–1698. [Google Scholar] [CrossRef]
  74. Jauhar, S.K.; Pant, M. Integrating DEA with DE and MODE for sustainable supplier selection. J. Comput. Sci. 2017, 21, 299–306. [Google Scholar] [CrossRef]
  75. Ghadimi, P.; Dargi, A.; Heavey, C. Making sustainable sourcing decisions: practical evidence from the automotive industry. Int. J. Logist. Res. Appl. 2017, 20, 297–321. [Google Scholar] [CrossRef]
  76. Kumar, D.; Rahman, Z.; Chan, F.T. A fuzzy AHP and fuzzy multi-objective linear programming model for order allocation in a sustainable supply chain: A case study. Int. J. Comput. Integr. Manuf. 2017, 30, 535–551. [Google Scholar] [CrossRef]
  77. Datta, S.; Samantra, C.; Sankar Mahapatra, S.; Mandal, G.; Majumdar, G. Appraisement and selection of third party logistics service providers in fuzzy environment. Benchmarking Int. J. 2013, 20, 537–548. [Google Scholar] [CrossRef]
  78. Khodaverdi, R.; Hashemi, S.H. A grey–based decision–making approach for selecting a reverse logistics provider in a closed loop supply chain. Int. J. Manag. Decis. Mak. 2015, 14, 32–43. [Google Scholar] [CrossRef]
  79. Basu, R.J.; Subramanian, N.; Gunasekaran, A.; Palaniappan, P. Influence of non-price and environmental sustainability factors on truckload procurement process. Ann. Oper. Res. 2017, 250, 363–388. [Google Scholar] [CrossRef]
  80. Ghadimi, P.; Dargi, A.; Heavey, C. Sustainable supplier performance scoring using audition check-list based fuzzy inference system: A case application in automotive spare part industry. Comput. Ind. Eng. 2017, 105, 12–27. [Google Scholar] [CrossRef] [Green Version]
  81. Govindan, K.; Jafarian, A.; Nourbakhsh, V. Bi-objective integrating sustainable order allocation and sustainable supply chain network strategic design with stochastic demand using a novel robust hybrid multi-objective metaheuristic. Comput. Oper. Res. 2015, 62, 112–130. [Google Scholar] [CrossRef]
  82. Koplin, J.; Seuring, S.; Mesterharm, M. Incorporating sustainability into supply management in the automotive industry – the case of the Volkswagen AG. J. Clean. Prod. 2007, 15, 1053–1062. [Google Scholar] [CrossRef]
  83. Akman, G. Evaluating suppliers to include green supplier development programs via fuzzy c-means and VIKOR methods. Comput. Ind. Eng. 2015, 86, 69–82. [Google Scholar] [CrossRef]
  84. Villalba, G.; Segarra, M.; Chimenos, J.M.; Espiell, F. Using the recyclability index of materials as a tool for design for disassembly. Ecol. Econ. 2004, 50, 195–200. [Google Scholar] [CrossRef]
  85. Mat Saman, M.Z.; Zakuan, N.; Blount, G. Design for End-of-Life Value Framework for Vehicles Design and Development Process. J. Sustain. Dev. 2012, 5. [Google Scholar] [CrossRef]
  86. Yang, S.; Nasr, N.; Ong, S.; Nee, A. Designing automotive products for remanufacturing from material selection perspective. J. Clean. Prod. 2015, 153, 570–579. [Google Scholar] [CrossRef]
  87. Kumar, S.; Luthra, S.; Govindan, K.; Kumar, N.; Haleem, A. Barriers in green lean six sigma product development process: An ISM approach. Prod. Plan. Control 2016, 27, 604–620. [Google Scholar] [CrossRef]
  88. Pechancová, V. Renewable energy potential in the automotive sector: Czech regional case study. J. Secur. Sustain. Issues 2017. [Google Scholar] [CrossRef]
  89. Granovskii, M.; Dincer, I.; Rosen, M.A. Economic and environmental comparison of conventional, hybrid, electric and hydrogen fuel cell vehicles. J. Power Sources 2006, 159, 1186–1193. [Google Scholar] [CrossRef]
  90. Jones, C.T. Another look at US passenger vehicle use and the rebound effect from improved fuel efficiency. Energy J. 2010, 99–110. [Google Scholar]
  91. Sivak, M.; Tsimhoni, O. Fuel efficiency of vehicles on US roads: 1923–2006. Energy Policy 2009, 37, 3168–3170. [Google Scholar] [CrossRef]
  92. Hollos, D.; Blome, C.; Foerstl, K. Does sustainable supplier co-operation affect performance? Examining implications for the triple bottom line. Int. J. Prod. Res. 2012, 50, 2968–2986. [Google Scholar] [CrossRef]
  93. White, G.R.; Wang, X.; Li, D. Inter-organisational green packaging design: A case study of influencing factors and constraints in the automotive supply chain. Int. J. Prod. Res. 2015, 53, 6551–6566. [Google Scholar] [CrossRef]
  94. Staš, D.; Lenort, R.; Wicher, P.; Holman, D. Green Transport balanced scorecard model with analytic network process support. Sustainability 2015, 7, 15243–15261. [Google Scholar] [CrossRef]
  95. Nunes, B.; Bennett, D. Green operations initiatives in the automotive industry: An environmental reports analysis and benchmarking study. Benchmarking Int. J. 2010, 17, 396–420. [Google Scholar] [CrossRef]
  96. Krikke, H.; le Blanc, I.; van Krieken, M.; Fleuren, H. Low-frequency collection of materials disassembled from end-of-life vehicles. Int. J. Prod. Econ. 2008, 111, 209–228. [Google Scholar] [CrossRef]
  97. Sundin, E.; Dunbäck, O. Reverse logistics challenges in remanufacturing of automotive mechatronic devices. J. Remanuf. 2013, 3, 2. [Google Scholar] [CrossRef] [Green Version]
  98. Abdulrahman, M.D.; Gunasekaran, A.; Subramanian, N. Critical barriers in implementing reverse logistics in the Chinese manufacturing sectors. Int. J. Prod. Econ. 2014, 147, 460–471. [Google Scholar] [CrossRef]
  99. Shaharudin, M.R.; Govindan, K.; Zailani, S.; Tan, K.C. Managing product returns to achieve supply chain sustainability: An exploratory study and research propositions. J. Clean. Prod. 2015, 101, 1–15. [Google Scholar] [CrossRef]
  100. Colledani, M.; Battaïa, O. A decision support system to manage the quality of end-of-life products in disassembly systems. CIRP Ann. 2016, 65, 41–44. [Google Scholar] [CrossRef]
  101. Hwang, I.; Yokono, S.; Matsuto, T. Pretreatment of automobile shredder residue (ASR) for fuel utilization. Chemosphere 2008, 71, 879–885. [Google Scholar] [CrossRef] [Green Version]
  102. Vermeulen, I.; Van Caneghem, J.; Block, C.; Baeyens, J.; Vandecasteele, C. Automotive shredder residue (ASR): Reviewing its production from end-of-life vehicles (ELVs) and its recycling, energy or chemicals’ valorisation. J. Hazard. Mater. 2011, 190, 8–27. [Google Scholar] [CrossRef]
  103. Khodier, A.; Williams, K.; Dallison, N. Challenges around automotive shredder residue production and disposal. Waste Manag. 2017, 73, 566–573. [Google Scholar] [CrossRef]
  104. Saavedra, Y.M.; Barquet, A.P.; Rozenfeld, H.; Forcellini, F.A.; Ometto, A.R. Remanufacturing in Brazil: Case studies on the automotive sector. J. Clean. Prod. 2013, 53, 267–276. [Google Scholar] [CrossRef]
  105. Yusop, N.; Wahab, D.A.; Saibani, N. Realising the automotive remanufacturing roadmap in Malaysia: challenges and the way forward. J. Clean. Prod. 2016, 112, 1910–1919. [Google Scholar] [CrossRef]
  106. Chaowanapong, J.; Jongwanich, J.; Ijomah, W. Factors influencing a firm’s decision to conduct remanufacturing: evidence from the Thai automotive parts industry. Prod. Plan. Control 2017, 28, 1139–1151. [Google Scholar] [CrossRef]
  107. Ramoni, M.O.; Zhang, H.-C. End-of-life (EOL) issues and options for electric vehicle batteries. Clean Technol. Environ. Policy 2013, 15, 881–891. [Google Scholar] [CrossRef]
  108. Đorđević, M.; Kokić, M. Concept for management of end of life vehicles recycling system. Int. J. Qual. Res. 2008, 2, 179–184. [Google Scholar]
  109. Ahmed, S.; Ahmed, S.; Shumon, M.R.H.; Quader, M.A.; Cho, H.M.; Mahmud, M.I. Prioritizing strategies for sustainable end-of-life vehicle management using combinatorial multi-criteria decision making method. Int. J. Fuzzy Syst. 2016, 18, 448–462. [Google Scholar] [CrossRef]
  110. Keivanpour, S.; Ait-Kadi, D.; Mascle, C. Automobile manufacturers’ strategic choice in applying green practices: joint application of evolutionary game theory and fuzzy rule-based approach. Int. J. Prod. Res. 2017, 55, 1312–1335. [Google Scholar] [CrossRef]
  111. Kuik, S.S.; Nagalingam, S.; Samaranayake, P.; McLean, M.W. Evaluation of recovery configuration options by product utilisation value. J. Manuf. Technol. Manag. 2017, 28, 686–710. [Google Scholar] [CrossRef]
  112. Subramoniam, R.; Huisingh, D.; Chinnam, R.B. Remanufacturing for the automotive aftermarket-strategic factors: Literature review and future research needs. J. Clean. Prod. 2009, 17, 1163–1174. [Google Scholar] [CrossRef]
  113. Anthony, C.; Cheung, W.M. Cost evaluation in design for end-of-Life of automotive components. J. Remanuf. 2017, 7, 97–111. [Google Scholar] [CrossRef] [Green Version]
  114. Li, W.; Bai, H.; Yin, J.; Xu, H. Life cycle assessment of end-of-life vehicle recycling processes in China—take Corolla taxis for example. J. Clean. Prod. 2016, 117, 176–187. [Google Scholar] [CrossRef]
  115. Chavez, R.; Sharma, M. Profitability and environmental friendliness of a closed-loop supply chain for PET components: A case study of the Mexican automobile market. Resour. Conserv. Recycl. 2017. [Google Scholar] [CrossRef]
  116. Bellmann, K.; Khare, A. European response to issues in recycling car plastics. Technovation 1999, 19, 721–734. [Google Scholar] [CrossRef]
  117. Fleischmann, M.; Krikke, H.R.; Dekker, R.; Flapper, S.D.P. A characterisation of logistics networks for product recovery. Omega 2000, 28, 653–666. [Google Scholar] [CrossRef]
  118. Zarei, M.; Mansour, S.; Husseinzadeh Kashan, A.; Karimi, B. Designing a reverse logistics network for end-of-life vehicles recovery. Math. Probl. Eng. 2010. [Google Scholar] [CrossRef]
  119. Jayant, A. REVERSE LOGISTICS: PERSPECTIVES, EMPIRICAL STUDIES AND RESEARCH DIRECTIONS. Int. J. Ind. Eng. Theoryappl. Pract. 2012, 19. [Google Scholar]
  120. Kannegiesser, M.; Günther, H.-O. Sustainable development of global supply chains—part 1: Sustainability optimization framework. Flex. Serv. Manuf. J. 2014, 26, 24–47. [Google Scholar] [CrossRef]
  121. Kannegiesser, M.; Günther, H.-O.; Gylfason, Ó. Sustainable development of global supply chains—part 2: Investigation of the European automotive industry. Flex. Serv. Manuf. J. 2014, 26, 48–68. [Google Scholar] [CrossRef]
  122. Ene, S.; Öztürk, N. Network modeling for reverse flows of end-of-life vehicles. Waste Manag. 2015, 38, 284–296. [Google Scholar] [CrossRef]
  123. Tognetti, A.; Grosse-Ruyken, P.T.; Wagner, S.M. Green supply chain network optimization and the trade-off between environmental and economic objectives. Int. J. Prod. Econ. 2015, 170, 385–392. [Google Scholar] [CrossRef]
  124. Özceylan, E.; Demirel, N.; Çetinkaya, C.; Demirel, E. A closed-loop supply chain network design for automotive industry in Turkey. Comput. Ind. Eng. 2017, 113, 727–745. [Google Scholar] [CrossRef]
  125. Demirel, E.; Demirel, N.; Gökçen, H. A mixed integer linear programming model to optimize reverse logistics activities of end-of-life vehicles in Turkey. J. Clean. Prod. 2016, 112, 2101–2113. [Google Scholar] [CrossRef]
  126. Boks, C.; Tempelman, E. Future disassembly and recycling technology: results of a Delphi study. Futures 1998, 30, 425–442. [Google Scholar] [CrossRef]
  127. Pickering, S. Recycling technologies for thermoset composite materials—current status. Compos. Part A Appl. Sci. Manuf. 2006, 37, 1206–1215. [Google Scholar] [CrossRef]
  128. Günther, H.-O.; Kannegiesser, M.; Autenrieb, N. The role of electric vehicles for supply chain sustainability in the automotive industry. J. Clean. Prod. 2015, 90, 220–233. [Google Scholar] [CrossRef]
  129. Butler, E.; Devlin, G.; McDonnell, K. Waste polyolefins to liquid fuels via pyrolysis: review of commercial state-of-the-art and recent laboratory research. Waste Biomass Valorization 2011, 2, 227–255. [Google Scholar] [CrossRef]
  130. Schmidt, W.-P.; Dahlqvist, E.; Finkbeiner, M.; Krinke, S.; Lazzari, S.; Oschmann, D.; Pichon, S.; Thiel, C. Life cycle assessment of lightweight and end-of-life scenarios for generic compact class passenger vehicles. Int. J. Life Cycle Assess. 2004, 9, 405–416. [Google Scholar] [CrossRef]
  131. MacLean, H.L.; Lave, L.B. Evaluating automobile fuel/propulsion system technologies. Prog. Energy Combust. Sci. 2003, 29, 1–69. [Google Scholar] [CrossRef]
  132. Uruburu, Á.; Ponce-Cueto, E.; Cobo-Benita, J.R.; Ordieres-Meré, J. The new challenges of end-of-life tyres management systems: A Spanish case study. Waste Manag. 2013, 33, 679–688. [Google Scholar] [CrossRef] [Green Version]
  133. Wang, L.; Chen, M. End-of-life vehicle dismantling and recycling enterprises: developing directions in China. JOM 2013, 65, 1015–1020. [Google Scholar] [CrossRef]
  134. Freiberger, S.; Albrecht, M.; Käufl, J. Reverse engineering technologies for remanufacturing of automotive systems communicating via CAN bus. J. Remanuf. 2011, 1, 6. [Google Scholar] [CrossRef]
  135. Mamalis, A.; Spentzas, K.; Mamali, A. The impact of automotive industry and its supply chain to climate change: Somme techno-economic aspects. Eur. Transp. Res. Rev. 2013, 5, 1–10. [Google Scholar] [CrossRef] [Green Version]
  136. Tian, G.; Chu, J.; Hu, H.; Li, H. Technology innovation system and its integrated structure for automotive components remanufacturing industry development in China. J. Clean. Prod. 2014, 85, 419–432. [Google Scholar] [CrossRef]
  137. Förster, B. Technology foresight for sustainable production in the German automotive supplier industry. Technol. Forecast. Soc. Chang. 2015, 92, 237–248. [Google Scholar] [CrossRef]
  138. Ferguson, N.; Browne, J. Issues in end-of-life product recovery and reverse logistics. Prod. Plan. Control 2001, 12, 534–547. [Google Scholar] [CrossRef]
  139. Rahimifard, A.; Newman, S.T.; Rahimifard, S. A web-based information system to support end-of-life product recovery. Proc. Inst. Mech. Eng. Part B J. Eng. Manuf. 2004, 218, 1047–1057. [Google Scholar] [CrossRef] [Green Version]
  140. Vachon, S.; Klassen, R.D. Extending green practices across the supply chain—The impact of upstream and downstream integration. Int. J. Oper. Prod. Manag. 2006, 26, 795–821. [Google Scholar] [CrossRef]
  141. Simpson, D.; Power, D.; Samson, D. Greening the automotive supply chain: A relationship perspective. Int. J. Oper. Prod. Manag. 2007, 27, 28–48. [Google Scholar] [CrossRef]
  142. Liu, Y.; Srai, J.S.; Evans, S. Environmental management: the role of supply chain capabilities in the auto sector. Supply Chain Manag. Int. J. 2016, 21, 1–19. [Google Scholar] [CrossRef]
  143. Liu, Y.; Zhu, Q.; Seuring, S. Linking capabilities to green operations strategies: The moderating role of corporate environmental proactivity. Int. J. Prod. Econ. 2017, 187, 182–195. [Google Scholar] [CrossRef]
  144. Xie, G. Cooperative strategies for sustainability in a decentralized supply chain with competing suppliers. J. Clean. Prod. 2016, 113, 807–821. [Google Scholar] [CrossRef]
  145. Rehman, M.A.A.; Aneyrao, T.A.; Shrivastava, R. Identification of critical success factors in Indian automobile industry: A GSCM approach. Int. J. Process Manag. Benchmarking 2015, 5, 229–245. [Google Scholar] [CrossRef]
  146. Graham, I.; Goodall, P.; Peng, Y.; Palmer, C.; West, A.; Conway, P.; Mascolo, J.E.; Dettmer, F.U. Performance measurement and KPIs for remanufacturing. J. Remanuf. 2015, 5, 10. [Google Scholar] [CrossRef]
  147. Vasanthakumar, C.; Vinodh, S.; Ramesh, K. Application of interpretive structural modelling for analysis of factors influencing lean remanufacturing practices. Int. J. Prod. Res. 2016, 54, 7439–7452. [Google Scholar] [CrossRef]
  148. Habidin, N.F.; Mohd Zubir, A.F.; Mohd Fuzi, N.; Md Latip, N.A.; Azman, M.N.A. Critical success factors of sustainable manufacturing practices in Malaysian automotive industry. Int. J. Sustain. Eng. 2017, 1–6. [Google Scholar] [CrossRef]
  149. Tyagi, M.; Kumar, P.; Kumar, D. Analysis of interactions among the drivers of green supply chain management. Int. J. Bus. Perform. Supply Chain Model. 2015, 7, 92–108. [Google Scholar] [CrossRef]
  150. Govindan, K.; Khodaverdi, R.; Vafadarnikjoo, A. Intuitionistic fuzzy based DEMATEL method for developing green practices and performances in a green supply chain. Expert Syst. Appl. 2015, 42, 7207–7220. [Google Scholar] [CrossRef]
  151. Ravi, V.; Ravi, V.; Shankar, R.; Shankar, R. An ISM-based approach analyzing interactions among variables of reverse logistics in automobile industries. J. Model. Manag. 2017, 12, 36–52. [Google Scholar] [CrossRef]
  152. Brent, A.C.; Visser, J.K. An environmental performance resource impact indicator for life cycle management in the manufacturing industry. J. Clean. Prod. 2005, 13, 557–565. [Google Scholar] [CrossRef] [Green Version]
  153. Sellitto, M.A.; Bittencourt, S.A.; Reckziegel, B.I. Evaluating the implementation of GSCM in industrial supply chains: Two cases in the automotive industry. Chem. Eng. Trans. 2015, 43, 1315–1320. [Google Scholar]
  154. Schöggl, J.-P.; Fritz, M.M.; Baumgartner, R.J. Toward supply chain-wide sustainability assessment: A conceptual framework and an aggregation method to assess supply chain performance. J. Clean. Prod. 2016, 131, 822–835. [Google Scholar] [CrossRef]
  155. Azevedo, S.G.; Carvalho, H.; Cruz-Machado, V. LARG index: A benchmarking tool for improving the leanness, agility, resilience and greenness of the automotive supply chain. Benchmarking Int. J. 2016, 23, 1472–1499. [Google Scholar] [CrossRef]
  156. Azevedo, S.G.; Govindan, K.; Carvalho, H.; Cruz-Machado, V. Ecosilient Index to assess the greenness and resilience of the upstream automotive supply chain. J. Clean. Prod. 2013, 56, 131–146. [Google Scholar] [CrossRef]
  157. Govindan, K.; Azevedo, S.G.; Carvalho, H.; Cruz-Machado, V. Impact of supply chain management practices on sustainability. J. Clean. Prod. 2014, 85, 212–225. [Google Scholar] [CrossRef]
  158. Chavez, R.; Yu, W.; Feng, M.; Wiengarten, F. The Effect of Customer-Centric Green Supply Chain Management on Operational Performance and Customer Satisfaction. Bus. Strategy Environ. 2016, 25, 205–220. [Google Scholar] [CrossRef]
  159. Chiappetta Jabbour, C.J.; Mauricio, A.L.; Jabbour, A.B.L.D.S. Critical success factors and green supply chain management proactivity: shedding light on the human aspects of this relationship based on cases from the Brazilian industry. Prod. Plan. Control 2017, 28, 671–683. [Google Scholar] [CrossRef] [Green Version]
  160. Maria Vanalle, R.; Blanco Santos, L. Green supply chain management in Brazilian automotive sector. Manag. Environ. Qual. Int. J. 2014, 25, 523–541. [Google Scholar] [CrossRef]
  161. Tian, Y.; Govindan, K.; Zhu, Q. A system dynamics model based on evolutionary game theory for green supply chain management diffusion among Chinese manufacturers. J. Clean. Prod. 2014, 80, 96–105. [Google Scholar] [CrossRef]
  162. Drohomeretski, E.; Gouvea da Costa, S.; Pinheiro de Lima, E. Green supply chain management: drivers, barriers and practices within the Brazilian automotive industry. J. Manuf. Technol. Manag. 2014, 25, 1105–1134. [Google Scholar] [CrossRef]
  163. Luthra, S.; Qadri, M.A.; Garg, D.; Haleem, A. Identification of critical success factors to achieve high green supply chain management performances in Indian automobile industry. Int. J. Logist. Syst. Manag. 2014, 18, 170–199. [Google Scholar] [CrossRef]
  164. Zailani, S.; Govindan, K.; Iranmanesh, M.; Shaharudin, M.R.; Chong, Y.S. Green innovation adoption in automotive supply chain: The Malaysian case. J. Clean. Prod. 2015, 108, 1115–1122. [Google Scholar] [CrossRef]
  165. Luthra, S.; Garg, D.; Haleem, A. Critical success factors of green supply chain management for achieving sustainability in Indian automobile industry. Prod. Plan. Control 2015, 26, 339–362. [Google Scholar]
  166. Govindan, K.; Shankar, K.M.; Kannan, D. Application of fuzzy analytic network process for barrier evaluation in automotive parts remanufacturing towards cleaner production–a study in an Indian scenario. J. Clean. Prod. 2016, 114, 199–213. [Google Scholar] [CrossRef]
  167. Tippayawong, K.Y.; Niyomyat, N.; Sopadang, A.; Ramingwong, S. Factors Affecting Green Supply Chain Operational Performance of the Thai Auto Parts Industry. Sustainability 2016, 8, 1161. [Google Scholar] [CrossRef]
  168. Luthra, S.; Garg, D.; Haleem, A. The impacts of critical success factors for implementing green supply chain management towards sustainability: An empirical investigation of Indian automobile industry. J. Clean. Prod. 2016, 121, 142–158. [Google Scholar] [CrossRef]
  169. Tian, G.; Zhang, H.; Feng, Y.; Jia, H.; Zhang, C.; Jiang, Z.; Li, Z.; Li, P. Operation patterns analysis of automotive components remanufacturing industry development in China. J. Clean. Prod. 2017, 164, 1363–1375. [Google Scholar] [CrossRef]
  170. Kumar, D.; Garg, C.P. Evaluating sustainable supply chain indicators using Fuzzy AHP: Case of Indian automotive industry. Benchmarking Int. J. 2017, 24, 1742–1766. [Google Scholar] [CrossRef]
  171. Ferreira, M.A.; Jabbour, C.J.C.; de Sousa Jabbour, A.B.L. Maturity levels of material cycles and waste management in a context of green supply chain management: An innovative framework and its application to Brazilian cases. J. Mater. Cycles Waste Manag. 2017, 19, 516–525. [Google Scholar] [CrossRef]
  172. Schöggl, J.-P.; Fritz, M.; Baumgartner, R.J. Sustainability Assessment in Automotive and Electronics Supply Chains—A Set of Indicators Defined in a Multi-Stakeholder Approach. Sustainability 2016, 8, 1185. [Google Scholar] [CrossRef]
  173. Mauricio, A.L.; Jabbour, A.B.L.D.S. Critical success factors for GSCM adoption: case studies in the automotive battery industry. Gestão Produção 2017, 24, 78–94. [Google Scholar] [CrossRef]
  174. DiMaggio, P.J.; Powell, W.W. The iron cage revisited institutional isomorphism and collective rationality in organizational fields. Adv. Strateg. Manag. 2000, 17, 143–166. [Google Scholar]
  175. Sarkis, J.; Zhu, Q.H.; Lai, K.H. An organizational theoretic review of green supply chain management literature. Int. J. Prod. Econ. 2011, 130, 1–15. [Google Scholar] [CrossRef]
  176. DiMaggio, P.J.; Powell, W.W. The iron cage revisited: Institutional isomorphism and collective rationality in organizational fields. Am. Sociol. Rev. 1983, 147–160. [Google Scholar] [CrossRef]
  177. Delmas, M.; Toffel, M.W. Stakeholders and environmental management practices: An institutional framework. Bus. Strategy Environ. 2004, 13, 209–222. [Google Scholar] [CrossRef]
  178. Zhu, Q.; Sarkis, J. The moderating effects of institutional pressures on emergent green supply chain practices and performance. Int. J. Prod. Res. 2007, 45, 4333–4355. [Google Scholar] [CrossRef]
  179. González-Benito, J.; González-Benito, Ó. The role of stakeholder pressure and managerial values in the implementation of environmental logistics practices. Int. J. Prod. Res. 2006, 44, 1353–1373. [Google Scholar] [CrossRef]
  180. Walker, H.; Di Sisto, L.; McBain, D. Drivers and barriers to environmental supply chain management practices: Lessons from the public and private sectors. J. Purch. Supply Manag. 2008, 14, 69–85. [Google Scholar] [CrossRef]
  181. Min, H.; Galle, W.P. Green purchasing strategies: Trends and implications. Int. J. Purch. Mater. Manag. 1997, 33, 10–17. [Google Scholar] [CrossRef]
  182. Bloemhof-Ruwaard, J.M.; Van Beek, P.; Hordijk, L.; Van Wassenhove, L.N. Interactions between operational research and environmental management. Eur. J. Oper. Res. 1995, 85, 229–243. [Google Scholar] [CrossRef]
  183. Rao, P.; Holt, D. Do green supply chains lead to competitiveness and economic performance? Int. J. Oper. Prod. Manag. 2005, 25, 898–916. [Google Scholar] [CrossRef]
  184. Thierry, M.C.; Salomon, M.; Nunen, J.; Wassenhove, L.N. Strategic issues in product recovery management. Calif. Manag. Rev. 1995, 37, 114–135. [Google Scholar] [CrossRef]
  185. Zsidisin, G.A.; Hendrick, T.E. Purchasing’s involvement in environmental issues: A multi-country perspective. Ind. Manag. Data Syst. 1998, 98, 313–320. [Google Scholar] [CrossRef]
  186. Cornet, A.; Deubener, H.; Möller, T.; Schaufuss, P.; Tschiesner, A. A Long-term Vision for The European Automotive Industry. Available online: https://www.mckinsey.com/industries/automotive-and-assembly/our-insights/a-long-term-vision-for-the-european-automotive-industry (accessed on 16 June 2019).
  187. Fontes, C.H.D.O.; Freires, F.G.M. Sustainable and renewable energy supply chain: A system dynamics overview. Renew. Sustain. Energy Rev. 2018, 82, 247–259. [Google Scholar]
  188. Dubey, R.; Gunasekaran, A.; Childe, S.J.; Papadopoulos, T.; Fosso Wamba, S. World class sustainable supply chain management: Critical review and further research directions. Int. J. Logist. Manag. 2017, 28, 332–362. [Google Scholar] [CrossRef]
  189. Abbasi, M. Towards socially sustainable supply chains–themes and challenges. Eur. Bus. Rev. 2017, 29. [Google Scholar] [CrossRef]
  190. Bechtsis, D.; Tsolakis, N.; Vlachos, D.; Iakovou, E. Sustainable supply chain management in the digitalisation era: The impact of Automated Guided Vehicles. J. Clean. Prod. 2017, 142, 3970–3984. [Google Scholar] [CrossRef] [Green Version]
  191. de Camargo Fiorini, P.; Jabbour, C.J.C. Information systems and sustainable supply chain management towards a more sustainable society: Where we are and where we are going. Int. J. Inf. Manag. 2017, 37, 241–249. [Google Scholar] [CrossRef] [Green Version]
  192. Dubey, R.; Dubey, R.; Gunasekaran, A.; Gunasekaran, A.; Papadopoulos, T.; Papadopoulos, T. Green supply chain management: Theoretical framework and further research directions. Benchmarking Int. J. 2017, 24, 184–218. [Google Scholar] [CrossRef]
  193. Geng, R.; Mansouri, S.A.; Aktas, E.; Yen, D.A. The role of Guanxi in green supply chain management in Asia’s emerging economies: A conceptual framework. Ind. Mark. Manag. 2017. [Google Scholar] [CrossRef]
  194. Choudhary, A.; Mondal, S.; Mukherjee, K. Analysis of critical factors influencing the management of green supply chain practice in small and medium enterprises. Int. J. Logist. Syst. Manag. 2017, 28, 200–224. [Google Scholar] [CrossRef]
  195. Singh, A.; Singh, A.; Trivedi, A.; Trivedi, A. Sustainable green supply chain management: trends and current practices. Compet. Rev. 2016, 26, 265–288. [Google Scholar] [CrossRef]
  196. Memari, A.; Rahim, A.R.A.; Ahmad, R.; Hassan, A. A literature review on green supply chain modelling for optimising CO2 emission. Int. J. Oper. Res. 2016, 26, 509–525. [Google Scholar] [CrossRef]
  197. Sharma, S.; Sharma, S.; Gandhi, M.A.; Gandhi, M.A. Exploring correlations in components of green supply chain practices and green supply chain performance. Compet. Rev. 2016, 26, 332–368. [Google Scholar] [CrossRef]
  198. Dhull, S.; Narwal, M. Drivers and barriers in green supply chain management adaptation: A state-of-art review. Uncertain Supply Chain Manag. 2016, 4, 61–76. [Google Scholar] [CrossRef]
  199. Ahi, P.; Searcy, C.; Jaber, M.Y. Energy-related performance measures employed in sustainable supply chains: A bibliometric analysis. Sustain. Prod. Consum. 2016, 7, 1–15. [Google Scholar] [CrossRef]
  200. Gao, D.; Xu, Z.; Ruan, Y.Z.; Lu, H. From a systematic literature review to integrated definition for sustainable supply chain innovation (SSCI). J. Clean. Prod. 2016, 142, 1518–1538. [Google Scholar] [CrossRef]
  201. Soda, S.; Sachdeva, A.; Garg, R.K. Literature review of multi-aspect research works carried out on the concept and implementation of GSCM. Int. J. Ind. Syst. Eng. 2016, 23, 223–253. [Google Scholar] [CrossRef]
  202. Darnall, N.; Jolley, G.J.; Handfield, R. Environmental management systems and green supply chain management: Complements for sustainability? Bus. Strategy Environ. 2008, 17, 30–45. [Google Scholar] [CrossRef]
  203. Blount, G.N. End of life vehicles recovery: process description, its impact and direction of research. J. Mek. 2006, 21, 40–52. [Google Scholar]
  204. Mathiyazhagan, K.; Haq, A.N. Analysis of the influential pressures for green supply chain management adoption—an Indian perspective using interpretive structural modeling. Int. J. Adv. Manuf. Technol. 2013, 68, 817–833. [Google Scholar] [CrossRef]
  205. Miemczyk, J. An exploration of institutional constraints on developing end-of-life product recovery capabilities. Int. J. Prod. Econ. 2008, 115, 272–282. [Google Scholar] [CrossRef] [Green Version]
  206. Chandra Shukla, A.; Deshmukh, S.; Kanda, A. Environmentally responsive supply chains: Learnings from the Indian auto sector. J. Adv. Manag. Res. 2009, 6, 154–171. [Google Scholar] [CrossRef]
  207. Shibin, K.; Dubey, R.; Gunasekaran, A.; Hazen, B.; Roubaud, D.; Gupta, S.; Foropon, C. Examining sustainable supply chain management of SMEs using resource based view and institutional theory. Ann. Oper. Res. 2017, 1–26. [Google Scholar] [CrossRef]
  208. Bansal, P.; Bogner, W.C. Deciding on ISO 14001: Economics, institutions, and context. Long Range Plan. 2002, 35, 269–290. [Google Scholar] [CrossRef]
  209. Castro, M.B.; Remmerswaal, J.A.; Reuter, M.A. Life cycle impact assessment of the average passenger vehicle in the Netherlands. Int. J. Life Cycle Assess. 2003, 8, 297–304. [Google Scholar] [CrossRef]
  210. Granovskii, M.; Dincer, I.; Rosen, M.A. Life cycle assessment of hydrogen fuel cell and gasoline vehicles. Int. J. Hydrog. Energy 2006, 31, 337–352. [Google Scholar] [CrossRef]
  211. Kumar, S.; Putnam, V. Cradle to cradle: Reverse logistics strategies and opportunities across three industry sectors. Int. J. Prod. Econ. 2008, 115, 305–315. [Google Scholar] [CrossRef]
  212. Sakai, S.-I.; Noma, Y.; Kida, A. End-of-life vehicle recycling and automobile shredder residue management in Japan. J. Mater. Cycles Waste Manag. 2007, 9, 151–158. [Google Scholar] [CrossRef]
  213. Coates, G.; Rahimifard, S. Assessing the economics of pre-fragmentation material recovery within the UK. Resour. Conserv. Recycl. 2007, 52, 286–302. [Google Scholar] [CrossRef]
  214. Cote, R.P.; Lopez, J.; Marche, S.; Perron, G.M.; Wright, R. Influences, practices and opportunities for environmental supply chain management in Nova Scotia SMEs. J. Clean. Prod. 2008, 16, 1561–1570. [Google Scholar] [CrossRef]
  215. Das, S.; Curlee, T.R.; Rizy, C.G.; Schexnayder, S.M. Automobile recycling in the United States: energy impacts and waste generation. Resour. Conserv. Recycl. 1995, 14, 265–284. [Google Scholar] [CrossRef]
  216. Diabat, A.; Khodaverdi, R.; Olfat, L. An exploration of green supply chain practices and performances in an automotive industry. Int. J. Adv. Manuf. Technol. 2013, 68, 949–961. [Google Scholar] [CrossRef]
  217. Duval, D.; MacLean, H.L. The role of product information in automotive plastics recycling: A financial and life cycle assessment. J. Clean. Prod. 2007, 15, 1158–1168. [Google Scholar] [CrossRef]
  218. Forton, O.; Harder, M.; Moles, N. Value from shredder waste: Ongoing limitations in the UK. Resour. Conserv. Recycl. 2006, 46, 104–113. [Google Scholar] [CrossRef] [Green Version]
  219. Fuse, M.; Kashima, S. Evaluation method of automobile recycling systems for Asia considering international material cycles: Application to Japan and Thailand. J. Mater. Cycles Waste Manag. 2008, 10, 153–164. [Google Scholar] [CrossRef]
  220. Guo, Q.; Zhang, X.; Li, C.; Liu, X.; Li, J. TG–MS study of the thermo-oxidative behavior of plastic automobile shredder residues. J. Hazard. Mater. 2012, 209, 443–448. [Google Scholar] [CrossRef]
  221. Hammond, R.; Amezquita, T.; Bras, B. Issues in the automotive parts remanufacturing industry: A discussion of results from surveys performed among remanufacturers. Eng. Des. Autom. 1998, 4, 27–46. [Google Scholar]
  222. Harder, M.K.; Forton, O.T. A critical review of developments in the pyrolysis of automotive shredder residue. J. Anal. Appl. Pyrolysis 2007, 79, 387–394. [Google Scholar] [CrossRef] [Green Version]
  223. Hu, S.; Kurasaka, H. Projection of end-of-life vehicle (ELV) population at provincial level of China and analysis on the gap between the future requirements and the current situation of ELV treatment in China. J. Mater. Cycles Waste Manag. 2013, 15, 154–170. [Google Scholar] [CrossRef]
  224. Joung, H.-T.; Cho, S.-J.; Seo, Y.-C.; Kim, W.-H. Status of recycling end-of-life vehicles and efforts to reduce automobile shredder residues in Korea. J. Mater. Cycles Waste Manag. 2007, 9, 159–166. [Google Scholar] [CrossRef]
  225. Joung, H.T.; Seo, Y.C.; Kim, K.H.; Hong, J.H.; Yoo, T.W. Distribution and characteristics of pyrolysis products from automobile shredder residue using an experimental semi-batch reactor. Korean J. Chem. Eng. 2007, 24, 996–1002. [Google Scholar] [CrossRef]
  226. Kameda, T.; Fukuda, Y.; Park, K.-S.; Grause, G.; Yoshioka, T. Efficient dehalogenation of automobile shredder residue in NaOH/ethylene glycol using a ball mill. Chemosphere 2009, 74, 287–292. [Google Scholar] [CrossRef] [PubMed]
  227. Kanari, N.; Pineau, J.-L.; Shallari, S. End-of-life vehicle recycling in the European Union. Jom 2003, 55, 15–19. [Google Scholar] [CrossRef]
  228. Kandelaars, P.P.; van Dam, J.D. An analysis of variables influencing the material composition of automobiles. Resour. Conserv. Recycl. 1998, 24, 323–333. [Google Scholar] [CrossRef] [Green Version]
  229. Keoleian, G.A. Is environmental improvement in automotive component design highly constrained? An instrument panel case study. J. Ind. Ecol. 1998, 2, 103–118. [Google Scholar] [CrossRef]
  230. Kim, K.-H.; Joung, H.-T.; Nam, H.; Seo, Y.-C.; Hong, J.H.; Yoo, T.-W.; Lim, B.-S.; Park, J.-H. Management status of end-of-life vehicles and characteristics of automobile shredder residues in Korea. Waste Manag. 2004, 24, 533–540. [Google Scholar] [CrossRef]
  231. Koffler, C.; Rohde-Brandenburger, K. On the calculation of fuel savings through lightweight design in automotive life cycle assessments. Int. J. Life Cycle Assess. 2010, 15, 128. [Google Scholar] [CrossRef]
  232. Martínez, J.D.; Puy, N.; Murillo, R.; García, T.; Navarro, M.V.; Mastral, A.M. Waste tyre pyrolysis–A review. Renew. Sustain. Energy Rev. 2013, 23, 179–213. [Google Scholar] [CrossRef]
  233. Osada, M.; Tanigaki, N.; Takahashi, S.; Sakai, S.-I. Brominated flame retardants and heavy metals in automobile shredder residue (ASR) and their behavior in the melting process. J. Mater. Cycles Waste Manag. 2008, 10, 93–101. [Google Scholar] [CrossRef]
  234. Pineau, J.-L.; Kanari, N.; Menad, N. Representativeness of an automobile shredder residue sample for a verification analysis. Waste Manag. 2005, 25, 737–746. [Google Scholar] [CrossRef] [PubMed]
  235. Roy, C.; Chaala, A. Vacuum pyrolysis of automobile shredder residues. Resour. Conserv. Recycl. 2001, 32, 1–27. [Google Scholar] [CrossRef]
  236. Sakai, S.-I.; Yoshida, H.; Hiratsuka, J.; Vandecasteele, C.; Kohlmeyer, R.; Rotter, V.S.; Passarini, F.; Santini, A.; Peeler, M.; Li, J. An international comparative study of end-of-life vehicle (ELV) recycling systems. J. Mater. Cycles Waste Manag. 2014, 16, 1–20. [Google Scholar] [CrossRef]
  237. Schultmann, F.; Zumkeller, M.; Rentz, O. Modeling reverse logistic tasks within closed-loop supply chains: An example from the automotive industry. Eur. J. Oper. Res. 2006, 171, 1033–1050. [Google Scholar] [CrossRef]
  238. Seitz, M.A.; Wells, P.E. Challenging the implementation of corporate sustainability: The case of automotive engine remanufacturing. Bus. Process Manag. J. 2006, 12, 822–836. [Google Scholar] [CrossRef]
  239. Simpson, D.F.; Power, D.J. Use the supply relationship to develop lean and green suppliers. Supply Chain Manag. Int. J. 2005, 10, 60–68. [Google Scholar] [CrossRef]
  240. Yano, J.; Hirai, Y.; Okamoto, K.; Sakai, S.-I. Dynamic flow analysis of current and future end-of-life vehicles generation and lead content in automobile shredder residue. J. Mater. Cycles Waste Manag. 2014, 16, 52–61. [Google Scholar] [CrossRef]
  241. Zah, R.; Hischier, R.; Leão, A.L.; Braun, I. Curauá fibers in the automobile industry–a sustainability assessment. J. Clean. Prod. 2007, 15, 1032–1040. [Google Scholar] [CrossRef]
  242. Zhu, Q.; Sarkis, J.; Lai, K.-H. Initiatives and outcomes of green supply chain management implementation by Chinese manufacturers. J. Environ. Manag. 2007, 85, 179–189. [Google Scholar] [CrossRef]
  243. Zhu, Q.; Sarkis, J.; Lai, K.-H. Green supply chain management implications for “closing the loop”. Transp. Res. Part E Logist. Transp. Rev. 2008, 44, 1–18. [Google Scholar] [CrossRef]
  244. Zolezzi, M.; Nicolella, C.; Ferrara, S.; Iacobucci, C.; Rovatti, M. Conventional and fast pyrolysis of automobile shredder residues (ASR). Waste Manag. 2004, 24, 691–699. [Google Scholar] [CrossRef]
  245. Errington, M.; Childe, S.J. A business process model of inspection in remanufacturing. J. Remanuf. 2013, 3, 7. [Google Scholar] [CrossRef] [Green Version]
  246. Xu, Y.; Sanchez, J.F.; Njuguna, J. Cost modelling to support optimised selection of End-of-Life options for automotive components. Int. J. Adv. Manuf. Technol. 2014, 73, 399–407. [Google Scholar] [CrossRef] [Green Version]
  247. Lind, S.; Olsson, D.; Sundin, E. Exploring inter-organizational relationships in automotive component remanufacturing. J. Remanuf. 2014, 4, 5. [Google Scholar] [CrossRef]
  248. Elo, M.; Kareila, T. Management of remanufacturing–strategic challenges from intellectual property rights. Int. J. Manuf. Technol. Manag. 2014, 28, 306–335. [Google Scholar] [CrossRef]
  249. Zhu, Q.; Sarkis, J.; Lai, K.-H. Supply chain-based barriers for truck-engine remanufacturing in China. Transp. Res. Part E Logist. Transp. Rev. 2014, 68, 103–117. [Google Scholar] [CrossRef]
  250. Ridley, S.J.; Ijomah, W. A novel pre-processing inspection methodology to enhance productivity in automotive product remanufacture: An industry-based research of 2196 engines. J. Remanuf. 2015, 5, 8. [Google Scholar] [CrossRef]
  251. D’Adamo, I.; Rosa, P. Remanufacturing in industry: Advices from the field. Int. J. Adv. Manuf. Technol. 2016, 86, 2575–2584. [Google Scholar] [CrossRef]
  252. van Loon, P.; Van Wassenhove, L.N. Assessing the economic and environmental impact of remanufacturing: A decision support tool for OEM suppliers. Int. J. Prod. Res. 2017, 1–13. [Google Scholar] [CrossRef]
  253. Zhang, J.-H.; Yang, B.; Chen, M. Challenges of the development for automotive parts remanufacturing in China. J. Clean. Prod. 2017, 140, 1087–1094. [Google Scholar] [CrossRef]
  254. Kumar, A.; Chinnam, R.B.; Murat, A. Hazard rate models for core return modeling in auto parts remanufacturing. Int. J. Prod. Econ. 2017, 183, 354–361. [Google Scholar] [CrossRef]
  255. McKenna, R.; Reith, S.; Cail, S.; Kessler, A.; Fichtner, W. Energy savings through direct secondary reuse: An exemplary analysis of the German automotive sector. J. Clean. Prod. 2013, 52, 103–112. [Google Scholar] [CrossRef]
  256. DeRousseau, M.; Gully, B.; Taylor, C.; Apelian, D.; Wang, Y. Repurposing Used Electric Car Batteries: A Review of Options. JOM 2017, 69, 1575–1582. [Google Scholar] [CrossRef]
  257. Cucchiella, F.; D’Adamo, I.; Rosa, P.; Terzi, S. Scrap automotive electronics: A mini-review of current management practices. Waste Manag. Res. 2016, 34, 3–10. [Google Scholar] [CrossRef]
  258. Parry, G.; Roehrich, J. Automotive enterprise transformation: Build to order as a sustainable and innovative strategy for the automotive industry? J. Enterp. Transform. 2013, 3, 33–52. [Google Scholar] [CrossRef]
  259. Nakamichi, K.; Hanaoka, S.; Kawahara, Y. Estimation of cost and CO2 emissions with a sustainable cross-border supply chain in the automobile industry: A case study of Thailand and neighboring countries. Transp. Res. Part D Transp. Environ. 2016, 43, 158–168. [Google Scholar] [CrossRef]
  260. Zimmer, K.; Fröhling, M.; Breun, P.; Schultmann, F. Assessing social risks of global supply chains: A quantitative analytical approach and its application to supplier selection in the German automotive industry. J. Clean. Prod. 2017, 149, 96–109. [Google Scholar] [CrossRef]
  261. Yazdani, M. An integrated MCDM approach to green supplier selection. Int. J. Ind. Eng. Comput. 2014, 5, 443–458. [Google Scholar] [CrossRef]
  262. Martin, D.M.; Väistö, T. Reducing the Attitude-Behavior Gap in Sustainable Consumption: A Theoretical Proposition and the American Electric Vehicle Market. In Marketing in and for a Sustainable Society; Emerald Group Publishing Limited: London, UK, 2016; pp. 193–213. [Google Scholar]
  263. Patala, S.; Jalkala, A.; Keränen, J.; Väisänen, S.; Tuominen, V.; Soukka, R. Sustainable value propositions: Framework and implications for technology suppliers. Ind. Mark. Manag. 2016, 59, 144–156. [Google Scholar] [CrossRef]
  264. Pallaro, E.; Subramanian, N.; Abdulrahman, M.D.; Liu, C.; Tan, K.H. Review of sustainable service-based business models in the Chinese truck sector. Sustain. Prod. Consum. 2017, 11, 31–45. [Google Scholar] [CrossRef]
  265. Luthra, S.; Govindan, K.; Mangla, S.K. Structural model for sustainable consumption and production adoption—A grey-DEMATEL based approach. Resour. Conserv. Recycl. 2017, 125, 198–207. [Google Scholar] [CrossRef]
  266. Cruz-Rivera, R.; Ertel, J. Reverse logistics network design for the collection of end-of-life vehicles in Mexico. Eur. J. Oper. Res. 2009, 196, 930–939. [Google Scholar] [CrossRef]
  267. Karakayali, I.; Emir-Farinas, H.; Akcali, E. An analysis of decentralized collection and processing of end-of-life products. J. Oper. Manag. 2007, 25, 1161–1183. [Google Scholar] [CrossRef]
  268. Zarandi, M.H.F.; Sisakht, A.H.; Davari, S. Design of a closed-loop supply chain (CLSC) model using an interactive fuzzy goal programming. Int. J. Adv. Manuf. Technol. 2011, 56, 809–821. [Google Scholar] [CrossRef]
  269. Sharma, M. The role of employees’ engagement in the adoption of green supply chain practices as moderated by environment attitude: An empirical study of the Indian automobile industry. Glob. Bus. Rev. 2014, 15, 25S–38S. [Google Scholar] [CrossRef]
  270. Daaboul, J.; Le Duigou, J.; Penciuc, D.; Eynard, B. An integrated closed-loop product lifecycle management approach for reverse logistics design. Prod. Plan. Control 2016, 27, 1062–1077. [Google Scholar] [CrossRef]
  271. Vaz, C.R.; Rauen, T.R.S.; Lezana, Á.G.R. Sustainability and Innovation in the Automotive Sector: A Structured Content Analysis. Sustainability 2017, 9, 880. [Google Scholar] [Green Version]
  272. Azevedo, S.G.; Carvalho, H.; Machado, V.C. The influence of green practices on supply chain performance: A case study approach. Transp. Res. Part E Logist. Transp. Rev. 2011, 47, 850–871. [Google Scholar] [CrossRef]
  273. Azzone, G.; Noci, G. Identifying effective PMSs for the deployment of “green” manufacturing strategies. Int. J. Oper. Prod. Manag. 1998, 18, 308–335. [Google Scholar] [CrossRef]
  274. Chester, M.V.; Horvath, A. Environmental assessment of passenger transportation should include infrastructure and supply chains. Environ. Res. Lett. 2009, 4, 024008. [Google Scholar] [CrossRef]
  275. Finkbeiner, M.; Hoffmann, R. Application of life cycle assessment for the environmental certificate of the Mercedes-Benz S-Class (7 pp). Int. J. Life Cycle Assess. 2006, 11, 240–246. [Google Scholar] [CrossRef]
  276. Gerrard, J.; Kandlikar, M. Is European end-of-life vehicle legislation living up to expectations? Assessing the impact of the ELV Directive on ‘green’innovation and vehicle recovery. J. Clean. Prod. 2007, 15, 17–27. [Google Scholar] [CrossRef]
  277. Giannouli, M.; de Haan, P.; Keller, M.; Samaras, Z. Waste from road transport: development of a model to predict waste from end-of-life and operation phases of road vehicles in Europe. J. Clean. Prod. 2007, 15, 1169–1182. [Google Scholar] [CrossRef]
  278. Hussain, M.; Dincer, I.; Li, X. A preliminary life cycle assessment of PEM fuel cell powered automobiles. Appl. Therm. Eng. 2007, 27, 2294–2299. [Google Scholar] [CrossRef]
  279. Kasai, J. Experiences and thoughts about life cycle assessment in the automotive industry in Japan. Int. J. Life Cycle Assess. 2000, 5, 313–316. [Google Scholar] [CrossRef]
  280. MacLean, H.L.; Lave, L.B. Life cycle assessment of automobile/fuel options. Environ. Sci. Technol. 2003, 37, 5445–5452. [Google Scholar] [CrossRef]
  281. Olugu, E.U.; Wong, K.Y. Evaluation of green supply chain management practices in the Malaysian automotive industry. Int. J. Serv. Oper. Manag. 2011, 9, 245–258. [Google Scholar] [CrossRef]
  282. Olugu, E.U.; Wong, K.Y. An expert fuzzy rule-based system for closed-loop supply chain performance assessment in the automotive industry. Expert Syst. Appl. 2012, 39, 375–384. [Google Scholar] [CrossRef]
  283. Olugu, E.U.; Wong, K.Y.; Shaharoun, A.M. A comprehensive approach in assessing the performance of an automobile closed-loop supply chain. Sustainability 2010, 2, 871–889. [Google Scholar] [CrossRef]
  284. Martínez, C.I.P. Energy efficiency in the automotive industry evidence from Germany and Colombia. Environ. Dev. Sustain. 2011, 13, 367–383. [Google Scholar] [CrossRef]
  285. Puri, P.; Compston, P.; Pantano, V. Life cycle assessment of Australian automotive door skins. Int. J. Life Cycle Assess. 2009, 14, 420–428. [Google Scholar] [CrossRef]
  286. Gopal, P.; Thakkar, J. Development of composite sustainable supply chain performance index for the automobile industry. Int. J. Sustain. Eng. 2015, 8, 366–385. [Google Scholar] [CrossRef]
  287. Luthra, S.; Garg, D.; Haleem, A. Empirical analysis of green supply chain management practices in Indian automobile industry. J. Inst. Eng. (India): Ser. C 2014, 95, 119–126. [Google Scholar] [CrossRef]
  288. Hunke, K.; Prause, G. SUSTAINABLE SUPPLY CHAIN MANAGEMENT IN GERMAN AUTOMOTIVE INDUSTRY: EXPERIENCES AND SUCCESS FACTORS. J. Secur. Sustain. Issues 2014, 3. [Google Scholar] [CrossRef]
  289. Salvado, M.F.; Azevedo, S.G.; Matias, J.C.; Ferreira, L.M. Proposal of a sustainability index for the automotive industry. Sustainability 2015, 7, 2113–2144. [Google Scholar] [CrossRef]
  290. Balon, V.; Sharma, A.K.; Barua, M.K. Assessment of barriers in green supply chain management using ISM: A case study of the automobile industry in India. Glob. Bus. Rev. 2016, 17, 116–135. [Google Scholar] [CrossRef]
  291. Kumar, D.; Rahman, Z. Buyer supplier relationship and supply chain sustainability: empirical study of Indian automobile industry. J. Clean. Prod. 2016, 131, 836–848. [Google Scholar] [CrossRef]
  292. Kushwaha, G.S.; Sharma, N.K. Green initiatives: A step towards sustainable development and firm’s performance in the automobile industry. J. Clean. Prod. 2016, 121, 116–129. [Google Scholar] [CrossRef]
  293. Rehman, M.A.A.; Aneyrao, T.A.; Pachchhao, A.; Shrivastava, R. Identification of performance measures in Indian automobile industry: A green supply chain management approach. Int. J. Bus. Perform. Manag. 2016, 17, 30–43. [Google Scholar] [CrossRef]
  294. Gopal, P.; Thakkar, J. Sustainable supply chain practices: An empirical investigation on Indian automobile industry. Prod. Plan. Control 2016, 27, 49–64. [Google Scholar] [CrossRef]
  295. Khairani, N.S.; Kasim, E.S.; Rajamanoharan, I.D.; Misman, F.N. Green Supply Chain Management in the Malaysian Automotive Industry: A Systems Thinking Perspective. Int. J. Supply Chain Manag. 2017, 6, 38–48. [Google Scholar]
  296. Malviya, R.K.; Kant, R. Modeling the enablers of green supply chain management: An integrated ISM–fuzzy MICMAC approach. Benchmarking Int. J. 2017, 24, 536–568. [Google Scholar] [CrossRef]
  297. Carvalho, H.; Govindan, K.; Azevedo, S.G.; Cruz-Machado, V. Modelling green and lean supply chains: An eco-efficiency perspective. Resour. Conserv. Recycl. 2017, 120, 75–87. [Google Scholar] [CrossRef]
  298. Fritz, M.M.; Schöggl, J.-P.; Baumgartner, R.J. Selected sustainability aspects for supply chain data exchange: Towards a supply chain-wide sustainability assessment. J. Clean. Prod. 2017, 141, 587–607. [Google Scholar] [CrossRef]
  299. Handfield, R.; Sroufe, R.; Walton, S. Integrating environmental management and supply chain strategies. Bus. Strategy Environ. 2005, 14, 1–19. [Google Scholar] [CrossRef]
  300. Van Hoek, R.I. Case studies of greening the automotive supply chain through technology and operations. Int. J. Environ. Technol. Manag. 2001, 1, 140–163. [Google Scholar] [CrossRef]
  301. Wells, P.; Seitz, M. Business models and closed-loop supply chains: A typology. Supply Chain Manag. Int. J. 2005, 10, 249–251. [Google Scholar] [CrossRef]
  302. Wu, H.-J.; Dunn, S.C. Environmentally responsible logistics systems. Int. J. Phys. Distrib. Logist. Manag. 1995, 25, 20–38. [Google Scholar] [CrossRef]
  303. Xia, Y.; Li-Ping Tang, T. Sustainability in supply chain management: Suggestions for the auto industry. Manag. Decis. 2011, 49, 495–512. [Google Scholar] [CrossRef]
Figure 1. The framework for content analysis based on Integration Definition Function (IDEF0). SSCM—sustainable supply chain management.
Figure 1. The framework for content analysis based on Integration Definition Function (IDEF0). SSCM—sustainable supply chain management.
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Figure 2. The framework for the processes and sub-processes of an auto-SSCM. EOL—end-of-life.
Figure 2. The framework for the processes and sub-processes of an auto-SSCM. EOL—end-of-life.
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Figure 3. A typical structure of an auto-SSCM. ELV—end-of-life vehicles.
Figure 3. A typical structure of an auto-SSCM. ELV—end-of-life vehicles.
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Figure 4. A five-stage model for designing an automotive SSC.
Figure 4. A five-stage model for designing an automotive SSC.
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Table 1. Analyzing the literature with respect to their classification.
Table 1. Analyzing the literature with respect to their classification.
Main CategoryProcess Sub-Categories
Content CategoryFre. *Perc. **Content CategoryFre.Perc.Content CategoryFre.Perc.
Input123.87%Delivery32.27%Management Capabilities717.07%
Legislation and Standards185.81%Supply2619.70%Network Structure1639.03%
Processes13041.93%Production1511.36%Technology1843.90%
Resources/Mechanisms3611.62%Use86.06%Total41100%
Output10232.9%Post-use8060.61%
Overall Review123.87%Total132100%
Total310100%
* Frequency of appearance in the literature, ** Percentage.

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Masoumi, S.M.; Kazemi, N.; Abdul-Rashid, S.H. Sustainable Supply Chain Management in the Automotive Industry: A Process-Oriented Review. Sustainability 2019, 11, 3945. https://doi.org/10.3390/su11143945

AMA Style

Masoumi SM, Kazemi N, Abdul-Rashid SH. Sustainable Supply Chain Management in the Automotive Industry: A Process-Oriented Review. Sustainability. 2019; 11(14):3945. https://doi.org/10.3390/su11143945

Chicago/Turabian Style

Masoumi, S. Maryam, Nima Kazemi, and Salwa Hanim Abdul-Rashid. 2019. "Sustainable Supply Chain Management in the Automotive Industry: A Process-Oriented Review" Sustainability 11, no. 14: 3945. https://doi.org/10.3390/su11143945

APA Style

Masoumi, S. M., Kazemi, N., & Abdul-Rashid, S. H. (2019). Sustainable Supply Chain Management in the Automotive Industry: A Process-Oriented Review. Sustainability, 11(14), 3945. https://doi.org/10.3390/su11143945

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