Next Article in Journal
Factors Influencing Water Use Efficiency in Agriculture: A Case Study of Shaanxi, China
Previous Article in Journal
Influence Mechanism of Construction Supply Chain Information Collaboration Based on Structural Equation Model
 
 
Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
Journals
Sustainability
Volume 15
Issue 3
10.3390/su15032156
sustainability-logo
Submit to this Journal Review for this Journal Propose a Special Issue
► Article Menu

Article Menu

share Share announcement Help format_quote Cite question_answer Discuss in SciProfiles thumb_up
...
Endorse textsms
...
Comment
first_page
settings
Order Article Reprints
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

Green Supply Chain Management Practices of Firms with Competitive Strategic Alliances—A Study of the Automobile Industry

by
Hassan Abbas
* and
Shu Tong
*
Business School, Hunan University, Changsha 410082, China
*
Authors to whom correspondence should be addressed.
Sustainability 2023, 15(3), 2156; https://doi.org/10.3390/su15032156
Submission received: 8 September 2022 / Revised: 26 October 2022 / Accepted: 9 November 2022 / Published: 23 January 2023
Browse Figures
Review Reports Versions Notes

Abstract

:
Supply chain management is described as a business strategy that provides operative management of financial, material, and other information flows to ensure harmonization in distributed organizational structures. The predefined aim of this study was to describe the effects of green supply chain management practices on competitive strategic alliances using automobile firms in China. The study aimed to demonstrate different factors that aid strategic alliances, which automobile firms must acknowledge to improve their performance. Fifty automobile firms were used as the study population. The respondents were senior managers of five active areas in each automobile firm. There were a total of 420 respondents, among whom 320 respondents were selected by the convenience sampling method. The study was quantitative, while the data source was primary; the data were obtained using a closed-ended questionnaire as the major instrument for data collection. This closed-ended questionnaire was sent to the intended respondents via email and WeChat simultaneously. Five active areas were included, and Cronbach’s alpha values were measured for each area. The values obtained ranged from 0.8 to 0.9, revealing the data’s consistency and reliability. The primary data obtained were analyzed using descriptive statistics for demographic data and inferential structural equation modeling (SEM) for multivariate data. Considering the outcomes of the research analysis, it was concluded that forming competitive strategic alliances in firms to manage green supply chains could bring several benefits.

1. Introduction

A supply chain management system covers six key aspects of an enterprise’s operation: production, supply, location, inventory, transportation, and information [1]. The primary focus of the supply chain management system is on building trust and advanced collaboration among different supply chain partners [2,3]. The advent of supply chain management has significantly reduced the costs of storing insurance stocks and improved the quality of products supplied, from raw materials to end users [4,5]. At the same time, the requirements for the accuracy of data entered into the system have increased, and the risks for businesses with regard to mistakes by operators and managers have increased significantly [6].
Green supply chain management (GSCM) is not only considered a means of environmental protection but also a valuable and potential way to gain advancements and competitive advantages as well as bring performance improvements to an organization [7]. Companies need to find modern, strategic approaches to achieve sustainable organizational benefits and a competitive advantage in an increasingly competitive world market [8]. The GSCM concept is related to the extensive integration of environmental safety approaches for supply chain management. That is why GSCM is effective for the overall environmental influence of organizations that participate in activities in the supply chain [9]. More importantly, GSCM can contribute to improved sustainability [10].
Intercompany alliances are often viewed as a recent phenomenon, and many relationships between organizations have existed since the companies were founded [11]. Companies competing in a modern business environment can not only create new alliances but also gain access to resources and technologies as well as new markets, procedures, and intellectual resources to create synergistic connections [12] and long-term competitive advantages. Strategic alliances are often used to gather knowledge from outside the company [12,13]. It is believed that close relationships between customers and suppliers and other business relations have numerous technical, financial, and strategic advantages [14]. Presently, strategic alliances are considered a crucial part of a modern business strategy. In the context of an international business environment, which requires concentration and flexibility, strategic alliances act as a driving force behind operational efficiency [15]. To achieve differentiated products with high efficiency, speed, and quality in this more complex environment, companies must focus on their core competencies and external resources in order to gain additional resources, technical capabilities, and training [16]. The GSCM practices considered by researchers demonstrate the characteristics of outsourcing, lean practices, sharing of quality information, customer relationships, and strategic supplier partnerships [17]. GSCM practices are significant for the management of the sustainable performance of firms [18]. Cases where companies were accused of not following sustainable SCM practices have revealed the importance of following GSCM practices to enhance performance and ensure the development of a good brand image [19].
Despite the extensive literature on this subject, the theoretical understanding of how such intercompany and intracompany alliances affect working dynamics and job content is far from complete [20]. Some authors have pointed out that this may be partly due to early research that focused more on the motivations for and results of forming effective alliances than on how alliances influence the management style, working atmosphere, and culture of the organization [21]. The best way to study alliances is not only to consider them from the perspective of front-facing processes but also to consider the continuous activities required to maintain them and the reduced energy during their life cycle [22]. This view means that the nature of the company’s internal work depends directly on what is required to maintain alliance activities and productivity as well as the need to coordinate the use of knowledge and other resources [2].
This study proposes to define a strategic alliance as a voluntary agreement based on trust and dedication between interdependent partners, sharing resources in a way that disrupts the opportunistic behavior of any individual partner and offers added value for all partners [23]. According to this definition, the agreement can differ in the degree of formality, which can be vertical or horizontal [24]. Shared resources can be based on physical elements or knowledge. However, when the frequency of alliance formation increases, the creation of such intercompany connections is often accompanied by instability, poor performance, and unexpected early termination.
Given their growing influence on the changing nature of business environments and the probability of frequent failure, accurately identifying and understanding the events or factors that influence the dynamics and outcomes of strategic alliances has become paramount [25]. Thus, this study fills the gap by examining the influence of green supply chain management practices (as events or factors) on strategic alliances using five key factors (manufacturing, eco-design, reverse logistics, procurement, and transportation) as measures of strategic alliances. This is because the authors believe that these factors are pertinent for the actualization of strategic alliances, especially among automobile firms. Furthermore, these factors constitute a key instrument for understanding firms’ working dynamics and job content [19]. However, no single theory can fully describe and explain the nature of strategic alliance outcomes.

1.1. Study Model

Green Supply Chain Management Practices (Figure 1).

1.2. Aims and Objectives

The predefined aim of this study was to describe the effects of green supply chain management practices on competitive strategic alliances using automobile firms in China. The objectives are as follows:
  • To ascertain the influence of green supply chain performance management on manufacturing in automobile firms.
  • To demonstrate the impact of green supply chain performance management on procurement in automobile firms.
  • To evaluate the influence of green supply chain performance management on reverse logistics in automobile firms.
  • To establish the influence of green supply chain performance management on eco-design in automobile firms.
  • To determine the influence of green supply chain performance management on transportation in automobile firms.

1.3. Research Questions

  • What is the correlation between green supply chain performance management and manufacturing in automobile firms?
  • What is the relationship between green supply chain performance management and procurement in automobile firms?
  • What is the correlation between green supply chain performance management and reverse logistics in automobile firms?
  • What is the correlation between green supply chain performance management and eco-design in automobile firms?
  • What is the correlation between green supply chain performance management and transportation in automobile firms?

1.4. Research Hypotheses

Hypothesis 1 (H1). 
There is no significant correlation between green supply chain performance management and manufacturing in automobile firms.
Hypothesis 2 (H2). 
There is no relationship between green supply chain performance management and procurement in automobile firms.
Hypothesis 3 (H3). 
There is no significant correlation between green supply chain performance management and reverse logistics in automobile firms.
Hypothesis 4 (H4). 
There is no significant correlation between green supply chain performance management and eco-design in automobile firms.
Hypothesis 5 (H5). 
There is no significant correlation between green supply chain performance management and transportation in automobile firms.

2. Literature Review

2.1. Supply Chain Management

The phrase “supply chain management” (SCM) has been widely used in the West for more than 15 years, but there is no consensus among logistics and general management professionals on the definition of this concept [1,26]. Many consider SCM from an operational point of view, referring to material flows, while others see SCM as a management concept or use SCM to introduce the concept in the enterprise [1,2,3,26,27]. The most popular definition of SCM is that it is a collection of different approaches that help in effectively integrating suppliers, distributors, manufacturers, and retailers [4]. Supply chain management describes the process of establishing and managing a distribution network associated with delivering desired products to desired locations over a certain period of time [28]. Considered in another way, supply chain management is presented as an organizational structure in which products are transferred from producers to consumers, which covers the entire process, starting with the purchase of raw materials and delivery of goods and ending with the final product being provided to customers [29]. Supply chain management is a special management strategy that can be used to synchronize the links in a chain to optimize the time and cost of delivering goods [27,30]. It refers to managing and controlling processes primarily related to the production, transportation, distribution, and purchase of products throughout the supply chain [27,31]. Currently, supply chain management is described as one of the most profitable and effective ways to increase profits and market share, and it is actively being introduced into the economies of industrialized countries [4,5,6,32]. Several big companies have adopted SCM principles as a new business ideology.
However, if the supply chain comprises the best network structure, it is usually imperative to change the logistics network structure to add value to the organization [7,9,10,33]. The need to change the structure can be caused by changes in strategic decisions in the supply chain and by various internal and external factors, such as changes in legislation or in the type of demand, or limited opportunities for suppliers. All of these factors can result in the re-engineering of the logistics network. This is a complex organizational task that can be solved by applying strategic supply chain management and advanced technologies [12,14,34,35]. Companies that participate in the same supply chain cannot work in isolation from each other. Instead, they have to work closely together in an integrated manner; in this way, they can solve a broader range of tasks. If each company starts with its own goal, this can lead to unnecessary boundaries between the companies, reducing the efficiency of the flow process and increasing costs [17,18,19,20,21].

Responsibility/Processes of Supply Chain Management

Supply chain management is accomplished through order, delivery, inventory, and production planning [1]. The main responsibility of supply chain management is to combine these structural units into one system to solve problems related to different stages of order processing, goods delivery, export, and import [2]. SCM processes comprise supply chain planning (SCP) and supply chain execution (SCE). Through these processes, the implementation of orders and the synchronization of the entire supply chain can be monitored as a single system [7,8,9]. An information system is used to manage inventory, ensure good workflow, and generate shipping documents for shipment. Using the information system can achieve highly optimized operations in the supply chain, while reducing the time and costs of order processing [15]. Information technology can integrate and synchronize the entire supply chain at a higher level to minimize the consumption of resources. Supply chain management practices focus on internal planning and resource optimization, which is crucial for establishing future-oriented relationships with supply chain participants [17].

2.2. Green Supply Chain Management

In working toward an environmentally sustainable SCM strategy, organizations can implement green supply chain management, which focuses on environmental sustainability in the supply chain. Green supply chain management (GSCM) is a development of SCM, which uses the same traditional concept but adds an environmental component to increase the environmental performance of products and services as firms strive for sustainability. GSCM has several definitions [36]. It can involve green purchases for an integrated supply chain for suppliers, manufacturers, and customers. GSCM enables a supply chain that values economic and environmental issues by designing a strategy that combines environmental standards, such as ISO 14000, and modern theories, such as lean. In this way, organizations can address environmental issues without additional costs. By introducing a GSCM strategy early, organizations can be more competitive in the market [37]. Supply chain operators can also contribute to a better association between parties related to the supply chain on environmental issues. Analyzing the influence of supply chain management practices on performance and operational efficiency can provide information on the effect of such practices on effectiveness and efficiency measures. Such management practices include information sharing, customer integration, and the use of IT to increase the efficiency and effectiveness of the supply chain performance. Integrating management practices for the supply chain, such as information sharing, the use of IT, and internal integration, can have a significant impact on supply chain performance [38]. Examining the practices of supply chain management used by different companies is a good approach, as this can indicate the effectiveness and efficiency of the supply chain. These practices can bring improvements in supply chain efficiency and therefore improve the company’s profitability.
The studied GSCM practices demonstrated the characteristics of outsourcing, lean practices, sharing of quality information, customer relationships, and strategic supplier partnerships.

2.2.1. Green Supply Chain Management for Effective Firm Performance

An organization’s performance is mainly measured by financial and operational variables associated with performance [39]. A study titled “The practical implementation of practices for supply chain management” examined the association between organizational performance and supply chain management practices. The outcomes of the study demonstrated that different GSCM practices had an intensive effect on the effectiveness and efficiency of supply chain management and firm performance [40]. It was further concluded that organizations implement management practices for the supply chain not only to ensure the supply chain’s success but also to improve its performance and profitability [41,42].
Several studies were carried out to determine the impact of green supply chain management on firm performance based on different components of supply chain management [43,44]. They revealed that green supply chain management has a positive and significant relationship with firm performance [45,46]. Furthermore, knowledge management, workflow structure, control and planning, and management methods have a notable influence on green supply chain management, which affects firm profitability. Green supply chain management is also affected by other components and practices, and among them, behavioral and managerial factors are important to consider [47].
Another study on supply chain management showed that sustainable supply chain management can be considered appropriate for attracting the attention of consumers [48,49]. The results revealed that collaborating with suppliers could lead to positive outcomes, as GSCM practice can increase economic performance and create a competitive advantage for firms [50]. Comparing outcomes to those in other developing countries has shown that adopting GSCM practices would improve the sustainability and performance of firms as well as provide a competitive edge [51]. GSCM practices and competitive advantage can positively affect firm performance [52]. The use of GSCM practices along with sustainability management is effective in improving firm performance. Studies carried out to demonstrate the significance of lean management, sustainability, and GSCM practices in improving overall firm performance [47,53,54] revealed that lean management, sustainability, and GSCM practices are effective in the management of the performance and operational efficiency of the supply chain. In this context, the performance and management practices of firms would be effective in increasing profits and goodwill.
As demonstrated by researchers, increased industrial development is associated with increased economic growth. Therefore, it is imperative to implement management practices for green supply chains to bring improvements to supply chain performance. Besides improving ecological performance, the use of management practices for green supply chains has been shown to be effective in improving the overall efficiency of firms [47,55,56]. Within SCM practices, the competitiveness and commitment of top management are two important drivers in managing supply chains and ensuring benefits [57,58].
Operational and financial performance are influenced by the effective implementation of GSCM practices and information systems. Empirical study findings have demonstrated that different dimensions of information systems and GSCM practices affect the performance of firms. It is important to consider these dimensions to ensure the sustainable development of firms. The studies further revealed that emerging countries must focus on GSCM and information management practices in order to improve [50]. Another study on the potential effects of traditional SCM practices and advanced GSCM practices revealed that both are associated with significant improvements in the performance and sustainability management of firms. Practices for a green supply chain, such as total quality management (TQM) and supplier relationship management (SRM), significantly affect the performance of firms [51]. Studies have shown that different supply chain management practices can have a tremendous effect on the performance of the supply chain [59,60].
The impact of certain products can lead to various proactive approaches to managing green supply chains and increased awareness of Chinese industrial regulations for their effective management. China’s traditional manufacturing companies know very little about the policies and regulations of green supply chain management; thus, such techniques are not used. Managing green supply chains is effective, but it is important to follow the rules and policies to ensure the effective implementation of supply chain management practices [52].

2.2.2. Green Supply Chain Management Application, Sustainability, and Collaboration

Service and production departments use different supply chain management techniques. The differences in methods used by these departments vary in terms of logistics management, inventory management, and technology deployment. The level of supply chain management practices varies from department to department. There are few green procurement management practices in the hotel industry, and the banking industry’s supply chain management practices are stringent. Implementing supply chain management techniques in a detailed and strategic manner is important [61]. Empirical studies have shown that the strategic implementation of these methods is effective in the service sector. Using management practices for a cleaner supply to increase the organization’s level of competitiveness is important [37]. Sustainability is a diverse field, and only a few researchers have attempted to evaluate the management practices for a cleaner supply chain to ensure improved supply chain performance [60].
The GSCM framework for performance and practices indicates that different management practices for a cleaner supply chain are effective for the performance and management of different supply chain stages. Therefore, management practices for cleaner supply chain management must be integrated into the organizational procedures for creating a competitive advantage and ensuring effective management [51].
A sustainable plan, sustainable operational process control, and communities for sustainability are some of the supply chain elements that can be implemented for the selection of suppliers and management of the supply chain [60,62].
Organizations can meet the needs and requirements of their customers while spreading awareness of the social, ecological, and economic aspects, three important aspects of sustainability that can inform the production and delivery of services [36]. In other words, GSCM practice is designed to help companies maintain processes and have strong control over the supply chain. Moreover, it helps in gaining a competitive advantage by integrating dynamic skills. Sustainable development practices related to the supply chain are important to improve tracking and traceability while simultaneously meeting the needs and requirements of customers at a broad level [37]. These practices lead to the complexity of the supply chain process and increase the number of risks. Companies coordinate their efforts to manage these complexities as the supply chain becomes increasingly integrated. In this respect, integration is one of the most effective ways to manage the supply chain and achieve optimal performance [38]. The effectiveness of green supply chain management within supply chain management suggests that green supply chain management techniques are effective as indicators of internal and external pressure in different supply chains. Providing training courses on implementing GSCM practices will effectively ensure that such implementation increases an organization’s competitive advantage in terms of effective supply management [39].
In supply chain management, a collaborative relationship is an effective way to promote the supply chain’s presence. The critical review of the research studies revealed that supplier collaboration is a vital approach for the management of different operations of the supply chain [62]. Empirical testing has demonstrated that supplier collaboration can improve elements of the supply chain such as risks, rewards, and knowledge sharing as well as supply chain management. The use of collaboration in the supply chain is imperative for small- and medium-sized organizations [52].
IT can assist companies in exchanging information effectively with their partners and integrating customer relationship management, and ERP applications can ensure supply chain management [63]. Currently, supply chain management has a significant role in managing and meeting customers’ demands and ensuring that global competition is satisfied. With the evolution of technology, technological techniques and practices are the prime factors that can ensure the integration of the supply chain with the company’s value system [64]. Integrating techniques and practices related to IT can result in effective supply chain management, which can improve the effectiveness and profitability of firms. In addition, investing in integrating IT into supply chain management can lead to positive outcomes, including competitive advantages. The development of technology and advancement in the already present technological aspects has led to competition. The competitive landscape has prompted organizations to gain a competitive advantage by operating efficiently and increasing their production in different areas [65]. Faster developments in technology have led to significant global competition. In this regard, the efficiency and competitive benefits of organizations depend on increased productivity and operating efficiency, and for this purpose, integrating technology is imperative [36,66,67].
The use of IT is effective for fostering relationships among different operational activities in the organization and ensuring effective communication to improve the performance of the supply chain [47]. The implementation of supply chain management strategies involving the use of IT can lead to significant positive outcomes [50]. Competition between the supply chains of different organizations has increased the value of supply chain improvements. In this regard, approaches are considered for the effective management of supply chain performance to improve the performance of firms [52]. The sharing of information is a collaborative endeavor, and it occurs with other management practices so that the supply chain can bring improvements in the process.

2.2.3. Green Supply Chain Management for Effective Integration of Strategic Alliances

The motivation for forming strategic alliances positively affects the degree of partners’ integration with them [61]. It has been suggested that companies are more likely to be more flexible and less restrictive, such as by forming strategic alliances, in the face of new challenges in global competition, rapidly changing technologies, and increasingly uncertain business conditions. Companies that do not have a broad range of skills and resources can create alliances with companies that have additional resources and skills to compete effectively in changing markets [62]. Researchers have argued that when it is harder to predict changes in the environment, companies are more likely to attract external knowledge because they are not sure how to develop knowledge themselves or whether their market is necessary. When environmental conditions are more complex, companies are more likely to acquire knowledge from outside to cope with more intense competition [68]. When the environmental conditions are more generous, the motivation to develop internal sources of knowledge is reduced, since it is then easy to obtain key sources from the external environment.
The environment facilitates the relationship between the acquisition of resources and the integration of strategic alliances [69]. A specific aspect of this transaction as an asset is that its value in a given transaction exceeds the value in other transactions. Studies point out that when investments in specific transactions increase, bilateral relationships arise because sellers become less attractive due to how their products are sold. Buyers are blocked because buying from other nonprofessional sources becomes too expensive. Strategic alliances backed by assets with high levels of specificity can be stable and solid relationships because these non-reimbursable investments promote trust and participation among associated companies [70]. A higher level of commitment reflects higher conversion costs because the strategic alliance partners seek more positive results from the cooperation agreement.
The specific characteristics of assets are positively related to the degree of integration among the partners in a strategic alliance. The acceptance of the TCT is that the reason is limited and people can be opportunistic. Partners disliking investments in specific assets indicates that the company is susceptible and that another party may show opportunistic behavior. A rational company will try to solve this problem by signing a contractual agreement with a partner, but such an agreement is imperfect. The specificity of the assets is inversely proportional to the perception of opportunistic behavior by the strategic alliance partners [59,71,72,73,74,75]. The concept of participation is considered an important element in the social interaction literature. Without commitment, business relationships are often fragile. Previous studies focused on the impact of trust and communication in adhering to interorganizational relationships but did not fully explore their interactions [75]. We believe that in strategic alliances, communication, trust, and commitment are not built in a one-sided manner but rather communication, trust, and participation are positively related [60]. If we consider that trust, communication, and dedication are determinants of a company’s missions, goals, and interests in the alliance, it can be concluded that the most reliable, socially responsible, and focused companies will achieve successful outcomes [76].
Researchers have studied three models separately. Business-to-business trust is an important factor in partner satisfaction and is directly related to productivity [77]. Frequent interactions increase reciprocity between partners and the reliability of cooperation [78,79,80]. Likewise, communication in successful alliances is crucial in determining the future intentions of partner companies and the level of supplier expectations. Information exchange and trust between buyers or suppliers have a direct positive impact on the effectiveness of strategic alliances in terms of customers [81]. The level of integration as a single structure affecting the performance of a strategic alliance and the degree of integration between partners has a positive effect on the outcome of the strategic alliance [82].
In this regard, the present research study was carried out to demonstrate the concept of green supply chain management and the benefits of competitive strategic alliances among organizations to implement green supply chain management practices [82]. The outcomes of strategic alliances in green supply chain management can be determined by evaluating and measuring performance [83,84]. The purpose of performance measurement is to evaluate the effectiveness of strategic alliances and assist decision makers in monitoring the progress and performance of alliances, improve communication, and evaluate related challenges [85]. In green supply chain management, an SCM logistic scorecard (LSC) is used, which is based on assessing the impact of any corporate strategy in terms of alignment, logistic performance, capability of planning or execution, and implementation [86,87,88]. It is a simple and effective tool used in several countries. The impact of competitive strategic alliances on firm performance is measured using financial indicators [89], including return on assets and cash-to-cash cycle time.

3. Methodology

The green supply chain performance measurement model (GSPM) model was used to evaluate the effectiveness of competitive strategic alliances in the performance of selected firms. This model was designed to integrate green supply chain management practices, balanced scorecards, and LSC using five factors for measurement: manufacturing, procurement, reverse logistics, eco-design, and transportation. These factors are key instruments in competitive strategies, so a five-level rating was used for evaluation as these five factors represent best practices.
A standard design process was followed to rule out bias and confirm validity. Automobile companies were used as the study population. Automobile companies are a main industrial sector in many nations, and they play a primary role in economic development. Among the automobile companies in China, 50 were selected as they were considered to be involved in inter- or intrafirm alliances to implement green supply chain management practices in order to gain a competitive advantage. The respondents were senior managers of five active areas in each automobile firm who were believed to have vast knowledge of the study problem. The sample size for this study was initially 420 respondents, and 320 respondents were selected by convenience sampling. The convenience sampling method gives researchers the liberty to use their discretion in choosing a sample size that would be manageable to work with.
This study is quantitative, while the data source is primary. Quantitative data obtained from automobile firms involved in intra- or interfirm alliances were considered to evaluate the impact of green supply chain management practices on competitive strategic alliances. Primary data were collected from the responses of senior managers of 50 major automobile firms across the provinces of China with the aid of a closed-ended questionnaire as the major instrument for data collection. The human resource departments of these firms sent an introductory letter stating the study’s title and purpose and requesting the intended respondents’ contact information. The letter also assured them of strict confidentiality with regard to any information provided. It took strenuous author effort to convince the management of these firms to participate due to fear of espionage. After frequent visits, elaboration, and feedback, the contact information of the intended respondents was given. After that, the closed-ended questionnaire and directions were sent simultaneously via email and WeChat to these respondents. Another limitation experienced at this point was the unenthusiastic nature of the respondents and their bias based on their differences (values, understanding, beliefs, and religion). However, suitable responses were obtained after assuring them of confidentiality.
Five active areas were used, and the value of Cronbach’s alpha was measured for each area. The value obtained ranged from 0.8 to 0.9, which revealed the data’s consistency and reliability. The primary data obtained by the use of a questionnaire were analyzed using descriptive statistics for demographic data and inferential structural equation modeling (SEM) for multivariate data.

4. Results

A total of 320 questionnaires were distributed to the respondents. All 320 were duly filled and returned, representing a 100% response rate. All responses were measured on a five-level rating, ranging from “strongly disagree” to “strongly agree”. The demographic profile of respondents is given in Table 1. The analysis of respondents’ ages revealed that 113 respondents (35.3%) were in the 31- to 35-year-old age group (highest number), and 31 of the respondents (9.7%) were in the 40 years and above group (lowest number). Age signifies maturity, and it is common logic that mature individuals possess more cognitive capacity. The analysis of respondents’ provinces indicated that 85 respondents (26.6%) were from Guangdong (highest number), while only 8 respondents (2.5%) were from either Chongqing, Shandong, or Jiangsu (lowest number). It is common logic that more industrious provinces produce competent individuals. The analysis of the respondents’ current employment status revealed that 92 respondents (28.8%) were managers of eco-design and 79 (24.7%) were transportation managers. In comparison, 36 respondents (11.3%) were production managers. It is common logic that specialists or managers in these areas are competent respondents.

4.1. Structural Equation Modeling (SEM)

This section assesses the influence of the proxies of the predictor variable, green supply chain management practices, on the measures of the criterion variable, competitive strategic alliance. Five null hypotheses were tested using structural equation modeling (SEM) to ascertain the influences and goodness of fit. The decision to support or not support the hypotheses was based on the root mean square error of approximation (RMSEA), comparative fit index (CFI), Tucker–Lewis index (TLI), and normed fit index (NFI). The following criteria determined acceptable goodness of fit: RMSEA ≤ 0.06, CFI ≥ 0.95, TLI ≥ 0.95, and NFI ≥ 0.95 [40]. Standardized factor loadings of at least 0.5 defined salient factor loadings [14].

4.1.1. Measurement Model of Green Supply Chain Performance Management (Figure 2)

Table 2 lists the measurement model analysis results for green supply chain performance management to determine a good fit. According to the result, chi-square had a value of 5.86, the normed fit index (NFI) had a value of 0.96, and the Tucker–Lewis index (TLI) had a value of 0.95. Root mean square error of approximation (RMSEA) had a value of 0.043, and the standardized factor loading estimate was 0.67. This confirms that the variable is a good indicator.
Sustainability 15 02156 g002 550
Figure 2. Measurement Model of Green Supply Chain Performance Management.
Figure 2. Measurement Model of Green Supply Chain Performance Management.
Sustainability 15 02156 g002

4.1.2. Measurement Model of Area of Manufacturing (Figure 3)

Table 3 lists the measurement model analysis results for manufacturing to determine goodness of fit. According to the results, chi-square had a value of 225, NFI had a value of 1.05, and TLI had a value of 0.96. RMSEA had a value of 0.060, and the standardized factor loading estimate was 0.76. Model analysis confirms that the variable is reliable enough as a factor for the measurement of competitive strategic alliances.
Sustainability 15 02156 g003 550
Figure 3. Measurement model of Area of manufacturing.
Figure 3. Measurement model of Area of manufacturing.
Sustainability 15 02156 g003

4.1.3. Measurement Model of Area of Transportation (Figure 4)

Table 4 lists the measurement model analysis results to determine goodness of fit in the measurement model in the transportation area. According to the results, chi-square had a value of 60.5, NFI had a value of 0.98, TLI had a value of 1.04, RMSEA had a value of 0.054, and the standardized factor loading estimate was 0.83. The model analysis shows that the variable is a reliable factor for measuring competitive strategic alliances.
Sustainability 15 02156 g004 550
Figure 4. Measurement Model of Area of Transportation.
Figure 4. Measurement Model of Area of Transportation.
Sustainability 15 02156 g004

4.1.4. Measurement Model of Area of Reverse Logistics (Figure 5)

Table 5 lists the measurement model analysis results for reverse logistics to determine a good fit in the measurement model. According to the results, chi-square had a value of 356, NFI had a value of 1.02, TLI had a value of 0.97, RMSEA had a value of 0.038, and the standardized factor loading estimate was 0.84. The analysis confirms that reverse logistics is reliable for measuring competitive strategic alliances.
Sustainability 15 02156 g005 550
Figure 5. Measurement Model of Area of Reverse Logistics.
Figure 5. Measurement Model of Area of Reverse Logistics.
Sustainability 15 02156 g005

4.1.5. Measurement Model of Area of Eco-Design (Figure 6)

Table 6 lists the measurement model analysis results for eco-design to determine the goodness of fit. According to the outcome, chi-square had a value of 541, NFI had a value of 1.04, TLI had a value of 1.06, RMSEA had a value of 0.036, and the standardized factor loading estimate was 0.89. This confirms that eco-design is a reliable factor for the measurement of competitive strategic alliances.
Sustainability 15 02156 g006 550
Figure 6. Measurement Model of Area of Eco-Design.
Figure 6. Measurement Model of Area of Eco-Design.
Sustainability 15 02156 g006

4.1.6. Structural Covariance Model of Green Supply Chain Performance Management and Measures of Competitive Strategic Alliances (Transportation, Manufacturing, Reverse Logistics, Procurement, and Eco-Design) (Figure 7)

Table 7 lists the Structural Covariance Model of Green Supply Chain Performance Management and Measures of Competitive Strategic Alliances (Transportation, Manufacturing, Reverse Logistics, Procurement, and Eco-Design). The test of hypothesis 1, there is a significant correlation between green supply chain performance management and manufacturing. The recorded values of β = 87 and CR = 1.99 (p < 0.05) indicate that green supply chain performance management can explain 87% of the variation in manufacturing. the test of hypothesis 2 indicate that there is a significant correlation between green supply chain performance management and transportation. The recorded values of β = 77 and CR = 3.11 (p < 0.05) indicate that green supply chain performance management can explain 77% of the difference in the area of transportation. The recorded values of β = 78 and CR = 3.08 (p < 0.05) indicate that green supply chain performance management can explain 78% of the difference in the area of reverse logistics. Hypothesis 4 show that eco-design as a measure of competitive strategic alliances is related to green supply chain performance management, with values of β = 96 and CR = 2.18 (p < 0.05). This result indicates that green supply chain management can explain 96% of the variance in the area of eco-design. Test of hypothesis 5 show that procurement as a measure of competitive strategic alliances is related to green supply chain performance management, with values of β = 85 and CR = 2.21 (p < 0.05). This indicates that green supply chain management can explain 85% of the variance in procurement.
Sustainability 15 02156 g007 550
Figure 7. Structural Covariance Model.
Figure 7. Structural Covariance Model.
Sustainability 15 02156 g007

5. Discussion

Business decisions are frequently made in the face of uncertainty and risk [90]. One prominent issue that firms, particularly manufacturing firms, face is managing their processes and products in a way that not only ensures their competitive advantage and superior performance but also mitigates the risks and uncertainties imposed by environmental hazards. Most of the previous studies proposed models that examined the role of different factors or green practices in a firm’s environmental performance or in mitigating environment-related risks and uncertainties [90,91,92]. This study was carried out to examine the influence of green supply chain management practices on competitive strategic alliances. The overall results indicate that green supply chain management practices have a significant and positive effect on the competitive strategic alliances of automobile firms, using the areas of manufacturing, transportation, reverse logistics, eco-design, and procurement as measures.
According to the findings of the test of hypothesis 1, there is a significant correlation between green supply chain performance management and manufacturing. The recorded values of β = 87 and CR = 1.99 (p < 0.05) indicate that green supply chain performance management can explain 87% of the variation in manufacturing. This finding is consistent with the findings of earlier studies that firms can perform significantly better by implementing green initiatives such as green hiring, manufacturing processes, and logistics [93,94]. This finding implies that with green supply chain performance management in place, manufacturing will experience a significant boost in terms of total quality, waste reduction, high productivity, etc., which will in turn enhance firm performance. Thus, these findings answer research question 1, what is the correlation between green supply chain performance management and manufacturing?
The findings of the test of hypothesis 2 indicate that there is a significant correlation between green supply chain performance management and transportation. The recorded values of β = 77 and CR = 3.11 (p < 0.05) indicate that green supply chain performance management can explain 77% of the difference in the area of transportation. This finding supports the argument that implies that with green supply chain performance management in place, there is better movement of goods, binding together of the supply chain, logistic convenience, etc. [94]. This can enhance competitive strategic alliances, which can lead to better firm performance. These findings answer research question 2, what is the correlation between green supply chain performance management and transportation?
The findings of the test of hypothesis 3 revealed that there is a significant relationship between green supply chain performance management and reverse logistics as a measure of competitive strategic alliances. The recorded values of β = 78 and CR = 3.08 (p < 0.05) indicate that green supply chain performance management can explain 78% of the difference in the area of reverse logistics. This finding augments previous studies [95,96] reporting that with green supply chain performance management in place, the upstream movement of products and materials is optimal and there is better recycling, reclamation of raw materials, and facilitation of product reuse. In turn, competitive strategic alliances can be enhanced, which can then lead to better firm performance. These findings answer research question 3, what is the correlation between green supply chain performance management and reverse logistics?
The findings of the test of hypothesis 4 show that eco-design as a measure of competitive strategic alliances is related to green supply chain performance management, with values of β = 96 and CR = 2.18 (p < 0.05). This result indicates that green supply chain management can explain 96% of the variance in the area of eco-design. This finding corroborates the findings of previous studies that green supply chain performance management practices allow firms to achieve their sustainable goals, reduce ecological risks, and improve environmental efficiency throughout the supply chain [19,97,98,99]. These findings imply that with green supply chain performance management in place, the design of products and services is based on special considerations, there are environmental impacts on a product’s life cycle and promotion of waste-free circuits, and ecological sustainability is beneficial for competitive strategies and alliance enhancement. These findings answer research question 4, what is the correlation between green supply chain performance management and eco-design?
The findings of the test of hypothesis 5 show that procurement as a measure of competitive strategic alliances is related to green supply chain performance management, with values of β = 85 and CR = 2.21 (p < 0.05). This indicates that green supply chain management can explain 85% of the variance in procurement. This finding supports the claim that with green supply chain performance management in place, there is a better transactional process, supply chain enhancement, product identification, sourcing, and strategic vetting, which can foster competitive strategic alliances [94,96]. These findings answer research question 5, what is the correlation between green supply chain performance management and procurement?

6. Managerial Implications

This study can enable the managers of automobile firms and other related firms to prioritize the implementation of green supply chain management. This can facilitate the achievement of sustainable goals and the minimization of effluent wastes and hazardous chemicals, thereby improving environmental efficiency all through the supply chain [19]. This can also involve better transactional processes, supply chain enhancement, designing of services and products based on special considerations, waste-free circuit enhancement, better recycling, reclamation of raw materials, and facilitation of reused products.
This study can also enable managers to build strategic alliances in order to promote effective firm performance such that they appreciate the critical role of green supply chain management. This supports the view that collaborating with suppliers can lead to positive outcomes, as GSCM practices can increase economic performance and create a competitive advantage for firms [50].
Additionally, the study makes it clear that practitioners need to incorporate green supply chain management as a critical catalyst of firm performance. This is in agreement with the claim that supply chains are important for improving tracking and traceability while simultaneously meeting the needs and requirements of customers on a broad level [37]. This is also in line with the views of Boon-itt and Wong, who asserted that customer satisfaction should be of the utmost importance to organizations as they engage in identifying, understanding, and utilizing customer requirements with the objectives of producing customer-defined goods/products and increasing benefits to the organization [100].

7. Conclusions

The serious risks that environmental uncertainty presents are making the general public and the business community more aware of environmental issues. Businesses, especially those in the manufacturing industry, have been pressured to adopt environmentally friendly processes and products in order to keep up their strategic competitiveness. In addition to offering protection against environmental uncertainty, GSCM can also enhance firm performance, which is why it is becoming more well liked among academics and practitioners. While previous studies mostly examined the role of GSCM in improving a firm’s environmental performance, this study was conducted to inform policy makers and other relevant stakeholders about the role of green supply chain management practices in competitive strategic alliances as a way to ascertain performance levels in automobile firms. A sample size of 320 was used for this purpose. The outcomes of the analyses revealed that green supply chain management practices influence the competitive strategic alliances of firms, thereby predicting the level of performance they can attain. Green supply chain management, a proxy for green supply chain management practices, correlates with various factors used to measure competitive strategic alliances. Green supply chain performance management ensures the reuse and recycling of raw materials, purchase of raw materials, optimal upstream movement of products and materials, total quality, waste reduction, high productivity, binding together of the supply chain, product identification, better sourcing, and vetting of strategic sources. It also enhances environmental sustainability and management.
Based on the same outcomes, it was further concluded that competitive strategic alliances of firms promote management of the green supply chain, resulting in better performance. Firms are now pursuing sustainability goals and have made strategic alliances to implement management practices for green supply chains. There are a few recommendations related to this research, one of which is to consider different types of strategic alliances to compare their outcomes.

Author Contributions

All authors contributed to study conception and design. The first draft of the manuscript was written by H.A., and all authors commented on previous versions of the manuscript. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Data Availability Statement

The data will be available from the corresponding author upon a reasonable request.

Conflicts of Interest

The authors declared no conflict of interest.

References

  1. Muduli, K.; Govindan, K.; Barve, A.; Kannan, D.; Geng, Y. Role of Behavioural Factors in Green Supply Chain Management Implementation in Indian Mining Industries. Resour. Conserv. Recycl. 2013, 76, 50–60. [Google Scholar] [CrossRef]
  2. Diabat, A.; Govindan, K. An Analysis of the Drivers Affecting the Implementation of Green Supply Chain Management. Resour. Conserv. Recycl. 2011, 55, 659–667. [Google Scholar] [CrossRef]
  3. Cabral, I.; Grilo, A.; Cruz-Machado, V. A Decision-Making Model for Lean, Agile, Resilient and Green Supply Chain Management. Int. J. Prod. Res. 2012, 50, 4830–4845. [Google Scholar] [CrossRef]
  4. Ageron, B.; Gunasekaran, A.; Spalanzani, A. Sustainable Supply Management: An Empirical Study. Int. J. Prod. Econ. 2012, 140, 168–182. [Google Scholar] [CrossRef]
  5. Arimura, T.H.; Darnall, N.; Katayama, H. Is ISO 14001 a Gateway to More Advanced Voluntary Action? The Case of Green Supply Chain Management. J. Environ. Econ. Manag. 2011, 61, 170–182. [Google Scholar] [CrossRef]
  6. Azevedo, S.G.; Carvalho, H.; Duarte, S.; Cruz-Machado, V. Influence of Green and Lean Upstream Supply Chain Management Practices on Business Sustainability. IEEE Trans. Eng. Manag. 2012, 59, 753–765. [Google Scholar] [CrossRef]
  7. Yang, C.S.; Lu, C.S.; Haider, J.J.; Marlow, P.B. The Effect of Green Supply Chain Management on Green Performance and Firm Competitiveness in the Context of Container Shipping in Taiwan. Transp. Res. Part E: Logist. Transp. Rev. 2013, 55, 55–73. [Google Scholar] [CrossRef]
  8. Barve, A.; Muduli, K. Modelling the Challenges of Green Supply Chain Management Practices in Indian Mining Industries. J. Manuf. Technol. Manag. 2013, 24, 1102–1122. [Google Scholar] [CrossRef]
  9. 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]
  10. Brandenburg, M.; Govindan, K.; Sarkis, J.; Seuring, S. Quantitative Models for Sustainable Supply Chain Management: Developments and Directions. Eur. J. Oper. Res. 2014, 233, 299–312. [Google Scholar] [CrossRef]
  11. Nkakleu, R.; Biboum, A.D. Governance and Performance of Strategic Alliances in Africa: The Role of Institutions. J. Afr. Bus. 2019, 20, 242–258. [Google Scholar] [CrossRef]
  12. Büyüközkan, G.; Çifçi, G. Evaluation of the Green Supply Chain Management Practices: A Fuzzy ANP Approach. Prod. Plan. Control 2012, 23, 405–418. [Google Scholar] [CrossRef]
  13. Carvalho, H.; Cruz-Machado, V. Integrating Lean, Agile, Resilience and Green Paradigms in Supply Chain Management (LARG_SCM). In Supply Chain Management; IntechOpen: London, UK, 2011; ISBN 978-953-307-184-8. [Google Scholar]
  14. Chan, H.K.; He, H.; Wang, W.Y.C. Green Marketing and Its Impact on Supply Chain Management in Industrial Markets. Ind. Mark. Manag. 2012, 41, 557–562. [Google Scholar] [CrossRef]
  15. Chan, R.Y.K.; He, H.; Chan, H.K.; Wang, W.Y.C. Environmental Orientation and Corporate Performance: The Mediation Mechanism of Green Supply Chain Management and Moderating Effect of Competitive Intensity. Ind. Mark. Manag. 2012, 41, 621–630. [Google Scholar] [CrossRef]
  16. Chardine-Baumann, E.; Botta-Genoulaz, V. A Framework for Sustainable Performance Assessment of Supply Chain Management Practices. Comput. Ind. Eng. 2014, 76, 138–147. [Google Scholar] [CrossRef]
  17. Azevedo, S.G.; Carvalho, H.; Cruz Machado, V. 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]
  18. Chen, C.C.; Shih, H.S.; Shyur, H.J.; Wu, K.S. A Business Strategy Selection of Green Supply Chain Management via an Analytic Network Process. Comput. Math. Appl. 2012, 64, 2544–2557. [Google Scholar] [CrossRef] [Green Version]
  19. Chin, T.A.; Tat, H.H.; Sulaiman, Z. Green Supply Chain Management, Environmental Collaboration and Sustainability Performance. In Proceedings of the Procedia CIRP; Elsevier: Amsterdam, The Netherlands, 2015; Volume 26, pp. 695–699. [Google Scholar]
  20. De Giovanni, P.; Esposito Vinzi, V. Covariance versus Component-Based Estimations of Performance in Green Supply Chain Management. Int. J. Prod. Econ. 2012, 135, 907–916. [Google Scholar] [CrossRef]
  21. 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]
  22. De Sousa Jabbour, A.B.L.; Jabbour, C.J.C.; Latan, H.; Teixeira, A.A.; de Oliveira, J.H.C. Quality Management, Environmental Management Maturity, Green Supply Chain Practices and Green Performance of Brazilian Companies with ISO 14001 Certification: Direct and Indirect Effects. Transp. Res. Part E Logist. Transp. Rev. 2014, 67, 39–51. [Google Scholar] [CrossRef]
  23. Eltayeb, T.K.; Zailani, S.; Ramayah, T. Green Supply Chain Initiatives among Certified Companies in Malaysia and Environmental Sustainability: Investigating the Outcomes. Resour. Conserv. Recycl. 2011, 55, 495–506. [Google Scholar] [CrossRef]
  24. 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]
  25. Gold, S.; Seuring, S.; Beske, P. Sustainable Supply Chain Management and Inter-Organizational Resources: A Literature Review. Corp. Soc. Responsib. Environ. Manag. 2010, 17, 230–245. [Google Scholar] [CrossRef]
  26. Perotti, S.; Zorzini, M.; Cagno, E.; Micheli, G.J.L. Green Supply Chain Practices and Company Performance: The Case of 3PLs in Italy. Int. J. Phys. Distrib. Logist. Manag. 2012, 42, 640–672. [Google Scholar] [CrossRef]
  27. Rostamzadeh, R.; Govindan, K.; Esmaeili, A.; Sabaghi, M. Application of Fuzzy VIKOR for Evaluation of Green Supply Chain Management Practices. Ecol. Indic. 2015, 49, 188–203. [Google Scholar] [CrossRef]
  28. Govindan, K.; Kaliyan, M.; Kannan, D.; Haq, A.N. Barriers Analysis for Green Supply Chain Management Implementation in Indian Industries Using Analytic Hierarchy Process. Int. J. Prod. Econ. 2014, 147, 555–568. [Google Scholar] [CrossRef]
  29. Govindan, K.; Kannan, D.; Mathiyazhagan, K.; de Sousa Jabbour, A.B.L.; Jabbour, C.J.C. Analysing Green Supply Chain Management Practices in Brazil’s Electrical/Electronics Industry Using Interpretive Structural Modelling. Int. J. Environ. Stud. 2013, 70, 477–493. [Google Scholar] [CrossRef]
  30. Purba, H.H.; Fitra, A.; Nindiani, A. Control and Integration of Milk-Run Operation in Japanese Automotive Company in Indonesia. Manag. Prod. Eng. Rev. 2019, 10, 79–88. [Google Scholar] [CrossRef]
  31. Sharma, R.; Shishodia, A.; Kamble, S.; Gunasekaran, A.; Belhadi, A. Agriculture Supply Chain Risks and COVID-19: Mitigation Strategies and Implications for the Practitioners. Int. J. Logist. Res. Appl. 2020, 1–27. [Google Scholar] [CrossRef]
  32. De Giovanni, P. Leveraging the Circular Economy with a Closed-Loop Supply Chain and a Reverse Omnichannel Using Blockchain Technology and Incentives. Int. J. Oper. Prod. Manag. 2022, 42, 959–994. [Google Scholar] [CrossRef]
  33. Lim, J.; Norman, B.A.; Rajgopal, J. Redesign of Vaccine Distribution Networks. Int. Trans. Oper. Res. 2022, 29, 200–225. [Google Scholar] [CrossRef]
  34. Moshood, T.D.; Nawanir, G.; Sorooshian, S.; Okfalisa, O. Digital Twins Driven Supply Chain Visibility within Logistics: A New Paradigm for Future Logistics. Appl. Syst. Innov. 2021, 4, 29. [Google Scholar] [CrossRef]
  35. Xue, X.; Dou, J.; Shang, Y. Blockchain-Driven Supply Chain Decentralized Operations—Information Sharing Perspective. Bus. Process Manag. J. 2021, 27, 184–203. [Google Scholar] [CrossRef]
  36. Jabbour, C.J.C.; de Sousa Jabbour, A.B.L. Green Human Resource Management and Green Supply Chain Management: Linking Two Emerging Agendas. J. Clean. Prod. 2016, 112, 1824–1833. [Google Scholar] [CrossRef] [Green Version]
  37. Laosirihongthong, T.; Adebanjo, D.; Choon Tan, K. Green Supply Chain Management Practices and Performance. Ind. Manag. Data Syst. 2013, 113, 1088–1109. [Google Scholar] [CrossRef] [Green Version]
  38. Shi, V.G.; Koh, S.C.L.; Baldwin, J.; Cucchiella, F. Natural Resource Based Green Supply Chain Management. Supply Chain Manag. 2012, 17, 54–67. [Google Scholar] [CrossRef]
  39. Lee, S.M.; Kim, S.T.; Choi, D. Green Supply Chain Management and Organizational Performance. Ind. Manag. Data Syst. 2012, 112, 1148–1180. [Google Scholar] [CrossRef]
  40. Lin, R.J. Using Fuzzy DEMATEL to Evaluate the Green Supply Chain Management Practices. J. Clean. Prod. 2013, 40, 32–39. [Google Scholar] [CrossRef]
  41. Zimon, D.; Tyan, J.; Sroufe, R. Implementing Sustainable Supply Chain Management: Reactive, Cooperative, and Dynamic Models. Sustainability 2019, 11, 7227. [Google Scholar] [CrossRef] [Green Version]
  42. Bag, S.; Wood, L.C.; Xu, L.; Dhamija, P.; Kayikci, Y. Big Data Analytics as an Operational Excellence Approach to Enhance Sustainable Supply Chain Performance. Resour. Conserv. Recycl. 2020, 153, 104559. [Google Scholar] [CrossRef]
  43. Murniati, S.; Harjuno, H.A.C.; Mambuhu, N.; Jenni Indriakati, A.; Murniati STIE Wira Bhakti Makassar, S.; Alfabetian Harjuno Condro Haditomo, I. Analyzing Mediation Effect of Competitive Advantage on Firm Performance as Measured by Total Quality Management and Supply Chain Management. J. Apl. Manaj. 2022, 20, 66–74. [Google Scholar] [CrossRef]
  44. Khokhar, M.; Hou, Y.; Rafique, M.A.; Iqbal, W. Evaluating the Social Sustainability Criteria of Supply Chain Management in Manufacturing Industries: A Role of BWM in MCDM. Probl. Ekorozw. 2020, 15, 185–194. [Google Scholar] [CrossRef]
  45. Al-Ghwayeen, W.S.; Abdallah, A.B. Green Supply Chain Management and Export Performance: The Mediating Role of Environmental Performance. J. Manuf. Technol. Manag. 2018, 29, 1233–1252. [Google Scholar] [CrossRef]
  46. Li, G.; Li, L.; Choi, T.M.; Sethi, S.P. Green Supply Chain Management in Chinese Firms: Innovative Measures and the Moderating Role of Quick Response Technology. J. Oper. Manag. 2020, 66, 958–988. [Google Scholar] [CrossRef]
  47. Hazen, B.T.; Cegielski, C.; Hanna, J.B. Diffusion of Green Supply Chain Management: Examining Perceived Quality of Green Reverse Logistics. Int. J. Logist. Manag. 2011, 22, 373–389. [Google Scholar] [CrossRef]
  48. Zhang, Z.; Yu, L. Research on Optimal Pricing Decisions of the Service Supply Chain Oriented to Strategic Consumers. J. Ind. Manag. Optim. 2022, 2022, 1–25. [Google Scholar] [CrossRef]
  49. Guo, J.; Xi, M. Greening, Pricing and Marketing Coordination for a Complex Three-Level Supply Chain Under the Carbon Tax in China. IEEE Access 2022, 10, 76895–76905. [Google Scholar] [CrossRef]
  50. Liu, X.; Yang, J.; Qu, S.; Wang, L.; Shishime, T.; Bao, C. Sustainable Production: Practices and Determinant Factors of Green Supply Chain Management of Chinese Companies. Bus. Strategy Environ. 2012, 21, 1–16. [Google Scholar] [CrossRef]
  51. Luthra, S.; Kumar, V.; Kumar, S.; Haleem, A.; Luthra, S.; Kumar, V.; Kumar, S.; Haleem, A. Barriers to Implement Green Supply Chain Management in Automobile Industry Using Interpretive Structural Modeling Technique: An Indian Perspective. J. Ind. Eng. Manag. 2011, 4, 231–257. [Google Scholar] [CrossRef] [Green Version]
  52. Mathiyazhagan, K.; Govindan, K.; NoorulHaq, A.; Geng, Y. An ISM Approach for the Barrier Analysis in Implementing Green Supply Chain Management. J. Clean. Prod. 2013, 47, 283–297. [Google Scholar] [CrossRef]
  53. Negri, M.; Cagno, E.; Colicchia, C.; Sarkis, J. Integrating Sustainability and Resilience in the Supply Chain: A Systematic Literature Review and a Research Agenda. Bus. Strategy Environ. 2021, 30, 2858–2886. [Google Scholar] [CrossRef]
  54. Sutduean, J.; Singsa, A.; Sriyakul, T.; Jermsittiparsert, K. Supply Chain Integration, Enterprise Resource Planning, and Organizational Performance: The Enterprise Resource Planning Implementation Approach. J. Comput. Theor. Nanosci. 2019, 16, 2975–2981. [Google Scholar] [CrossRef]
  55. Singh, J.; Singh, H.; Kumar, A. Impact of Lean Practices on Organizational Sustainability through Green Supply Chain Management—An Empirical Investigation. Int. J. Lean Six Sigma 2020, 11, 1049–1082. [Google Scholar] [CrossRef]
  56. Sahoo, S.; Vijayvargy, L. Green Supply Chain Management Practices and Its Impact on Organizational Performance: Evidence from Indian Manufacturers. J. Manuf. Technol. Manag. 2020, 32, 862–886. [Google Scholar] [CrossRef]
  57. Jum’a, L.; Ikram, M.; Alkalha, Z.; Alaraj, M. Factors Affecting Managers’ Intention to Adopt Green Supply Chain Management Practices: Evidence from Manufacturing Firms in Jordan. Environ. Sci. Pollut. Res. 2021, 29, 5605–5621. [Google Scholar] [CrossRef]
  58. Sajjad, A.; Eweje, G.; Tappin, D. Managerial Perspectives on Drivers for and Barriers to Sustainable Supply Chain Management Implementation: Evidence from New Zealand. Bus. Strategy Environ. 2020, 29, 592–604. [Google Scholar] [CrossRef]
  59. Tukamuhabwa, B.; Mutebi, H.; Kyomuhendo, R. Competitive Advantage in SMEs: Effect of Supply Chain Management Practices, Logistics Capabilities and Logistics Integration in a Developing Country. J. Bus. Socio-Econ. Dev. 2021. ahead of the print. [Google Scholar] [CrossRef]
  60. Walker, H.; Jones, N. Sustainable Supply Chain Management across the UK Private Sector. Supply Chain Manag. 2012, 17, 15–28. [Google Scholar] [CrossRef]
  61. Mitra, S.; Datta, P.P. Adoption of Green Supply Chain Management Practices and Their Impact on Performance: An Exploratory Study of Indian Manufacturing Firms. Int. J. Prod. Res. 2014, 52, 2085–2107. [Google Scholar] [CrossRef]
  62. Mohanty, R.P.; Prakash, A. Green Supply Chain Management Practices in India: A Confirmatory Empirical Study. Prod. Manuf. Res. 2014, 2, 438–456. [Google Scholar] [CrossRef] [Green Version]
  63. Hsu, C.W.; Kuo, T.C.; Chen, S.H.; Hu, A.H. Using DEMATEL to Develop a Carbon Management Model of Supplier Selection in Green Supply Chain Management. J. Clean. Prod. 2013, 56, 164–172. [Google Scholar] [CrossRef]
  64. Hu, A.H.; Hsu, C.W. Critical Factors for Implementing Green Supply Chain Management Practice: An Empirical Study of Electrical and Electronics Industries in Taiwan. Manag. Res. Rev. 2010, 33, 586–608. [Google Scholar] [CrossRef]
  65. Kumar, A.; Mangla, S.K.; Luthra, S.; Ishizaka, A. Evaluating the Human Resource Related Soft Dimensions in Green Supply Chain Management Implementation. Prod. Plan. Control 2019, 30, 699–715. [Google Scholar] [CrossRef]
  66. Ferraris, A.; Mazzoleni, A.; Devalle, A.; Couturier, J. Big Data Analytics Capabilities and Knowledge Management: Impact on Firm Performance. Manag. Decis. 2019, 57, 1923–1936. [Google Scholar] [CrossRef]
  67. Sima, V.; Gheorghe, I.G.; Subić, J.; Nancu, D. Influences of the Industry 4.0 Revolution on the Human Capital Development and Consumer Behavior: A Systematic Review. Sustainability 2020, 12, 4035. [Google Scholar] [CrossRef]
  68. Tate, W.L.; Ellram, L.M.; Kirchoff, J.F. Corporate Social Responsibility Reports: A Thematic Analysis Related to Supply Chain Management. J. Supply Chain Manag. 2010, 46, 19–44. [Google Scholar] [CrossRef]
  69. Muduli, K.; Govindan, K.; Barve, A.; Geng, Y. Barriers to Green Supply Chain Management in Indian Mining Industries: A Graph Theoretic Approach. J. Clean. Prod. 2013, 47, 335–344. [Google Scholar] [CrossRef]
  70. Sarkis, J.; Zhu, Q.; Lai, K.H. An Organizational Theoretic Review of Green Supply Chain Management Literature. Int. J. Prod. Econ. 2011, 130, 1–15. [Google Scholar] [CrossRef]
  71. Cuypers, I.R.P.; Hennart, J.F.; Silverman, B.S.; Ertug, G. Transaction Cost Theory: Past Progress, Current Challenges, and Suggestions for the Future. Acad. Manag. Ann. 2021, 15, 111–150. [Google Scholar] [CrossRef]
  72. Lee, K.H. Integrating Carbon Footprint into Supply Chain Management: The Case of Hyundai Motor Company (HMC) in the Automobile Industry. J. Clean. Prod. 2011, 19, 1216–1223. [Google Scholar] [CrossRef]
  73. Tseng, M.L. Green Supply Chain Management with Linguistic Preferences and Incomplete Information. Appl. Soft Comput. 2011, 11, 4894–4903. [Google Scholar] [CrossRef]
  74. Tukamuhabwa, B.; Mutebi, H.; Isabirye, D. Supplier Performance in the Public Healthcare: Internal Social Capital, Logistics Capabilities and Supply Chain Risk Management Capabilities as Antecedents in a Developing Economy. J. Bus. Socio-Econ. Dev. 2021. ahead of print. [Google Scholar] [CrossRef]
  75. Tseng, M.L.; Chiu, A.S.F. Evaluating Firm’s Green Supply Chain Management in Linguistic Preferences. J. Clean. Prod. 2013, 40, 22–31. [Google Scholar] [CrossRef]
  76. Sheu, J.B.; Talley, W.K. Green Supply Chain Management: Trends, Challenges, and Solutions. Transp. Res. Part E Logist. Transp. Rev. 2011, 47, 791–792. [Google Scholar] [CrossRef]
  77. Wang, Y.F.; Chen, S.P.; Lee, Y.C.; Tsai, C.T. (Simon) Developing Green Management Standards for Restaurants: An Application of Green Supply Chain Management. Int. J. Hosp. Manag. 2013, 34, 263–273. [Google Scholar] [CrossRef]
  78. Wu, G.-C.; Cheng, Y.; Huang, S.-Y. The Study of Knowledge Transfer and Green Management Performance in Green Supply Chain Management. Afr. J. Bus. Manag. 2010, 4, 44–48. [Google Scholar]
  79. Wu, J.; Dunn, S.; Forman, H. A Study on Green Supply Chain Management Practices among Large Global Corporations. J. Supply Chain Oper. Manag. 2012, 10, 182–194. [Google Scholar]
  80. Wu, K.J.; Tseng, M.L.; Vy, T. Evaluation the Drivers of Green Supply Chain Management Practices in Uncertainty. In Proceedings of the Procedia—Social and Behavioral Sciences; Elsevier: Amsterdam, The Netherlands, 2011; Volume 25, pp. 384–397. [Google Scholar]
  81. Wu, Z.; Pagell, M. Balancing Priorities: Decision-Making in Sustainable Supply Chain Management. J. Oper. Manag. 2011, 29, 577–590. [Google Scholar] [CrossRef]
  82. Zailani, S.; Jeyaraman, K.; Vengadasan, G.; Premkumar, R. Sustainable Supply Chain Management (SSCM) in Malaysia: A Survey. Int. J. Prod. Econ. 2012, 140, 330–340. [Google Scholar] [CrossRef]
  83. Zhu, Q.; Geng, Y.; Sarkis, J.; Lai, K. hung Evaluating Green Supply Chain Management among Chinese Manufacturers from the Ecological Modernization Perspective. Transp. Res. Part E: Logist. Transp. Rev. 2011, 47, 808–821. [Google Scholar] [CrossRef]
  84. Zhu, Q.; Geng, Y.; Fujita, T.; Hashimoto, S. Green Supply Chain Management in Leading Manufacturers: Case Studies in Japanese Large Companies. Manag. Res. Rev. 2010, 33, 380–392. [Google Scholar] [CrossRef]
  85. Zhu, Q.; Sarkis, J.; Lai, K.H. Examining the Effects of Green Supply Chain Management Practices and Their Mediations on Performance Improvements. Int. J. Prod. Res. 2012, 50, 1377–1394. [Google Scholar] [CrossRef]
  86. Zhu, Q.; Sarkis, J.; Lai, K.H. Green Supply Chain Management Innovation Diffusion and Its Relationship to Organizational Improvement: An Ecological Modernization Perspective. J. Eng. Technol. Manag. 2012, 29, 168–185. [Google Scholar] [CrossRef]
  87. Zhu, Q.; Sarkis, J.; Lai, K. hung 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]
  88. Zhu, Q.; Tian, Y.; Sarkis, J. Diffusion of Selected Green Supply Chain Management Practices: An Assessment of Chinese Enterprises. Prod. Plan. Control 2012, 23, 837–850. [Google Scholar] [CrossRef]
  89. Bose, I.; Pal, R. Do Green Supply Chain Management Initiatives Impact Stock Prices of Firms? Decis. Support Syst. 2012, 52, 624–634. [Google Scholar] [CrossRef]
  90. Ji, Y.; Li, H.; Zhang, H. Risk-Averse Two-Stage Stochastic Minimum Cost Consensus Models with Asymmetric Adjustment Cost. Group Decis. Negot. 2022, 31, 261–291. [Google Scholar] [CrossRef]
  91. Qu, S.; Li, Y.; Ji, Y. The Mixed Integer Robust Maximum Expert Consensus Models for Large-Scale GDM under Uncertainty Circumstances. Appl. Soft Comput. 2021, 107, 107369. [Google Scholar] [CrossRef]
  92. Qu, S.; Xu, L.; Mangla, S.K.; Chan, F.T.S.; Zhu, J.; Arisian, S. Matchmaking in Reward-Based Crowdfunding Platforms: A Hybrid Machine Learning Approach. Int. J. Prod. Res. 2022, 1–21. [Google Scholar] [CrossRef]
  93. Green, K.W.; Zelbst, P.J.; Meacham, J.; Bhadauria, V.S. Green Supply Chain Management Practices: Impact on Performance. Supply Chain Manag. 2012, 17, 290–305. [Google Scholar] [CrossRef]
  94. Jawaad, M.; Hasan, T.; Amir, A.; Imam, H. Exploring the Impact of Green Human Resource Management on Firm Sustainable Performance: Roles of Green Supply Chain Management and Firm Size. J. Manag. Organ. 2022, 1–23. [Google Scholar] [CrossRef]
  95. Rao, P. Greening the Supply Chain: A New Initiative in South East Asia. Int. J. Oper. Prod. Manag. 2002, 22, 632–655. [Google Scholar] [CrossRef]
  96. 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]
  97. Aggerholm, H.K.; Andersen, S.E.; Thomsen, C. Conceptualising Employer Branding in Sustainable Organisations. Corp. Commun. 2011, 16, 105–123. [Google Scholar] [CrossRef]
  98. Zhang, B.; Wu, D.; Liang, L.; Olson, D.L. Supply Chain Loss Averse Newsboy Model with Capital Constraint. IEEE Trans. Syst. Man Cybern. Syst. 2016, 46, 646–658. [Google Scholar] [CrossRef]
  99. Luo, Z.; Chen, X.; Chen, J.; Wang, X. Optimal Pricing Policies for Differentiated Brands under Different Supply Chain Power Structures. Eur. J. Oper. Res. 2017, 259, 437–451. [Google Scholar] [CrossRef] [Green Version]
  100. Boon-itt, S.; Wong, C.Y. The Moderating Effects of Technological and Demand Uncertainties on the Relationship between Supply Chain Integration and Customer Delivery Performance. Int. J. Phys. Distrib. Logist. Manag. 2011, 41, 253–276. [Google Scholar] [CrossRef]
Sustainability 15 02156 g001 550
Figure 1. Study Model of Green Supply Chain Management Practices. Source: Researcher, 2022.
Figure 1. Study Model of Green Supply Chain Management Practices. Source: Researcher, 2022.
Sustainability 15 02156 g001
Table
Table 1. Demographic profile of respondents.
Table 1. Demographic profile of respondents.
VariableClassificationFrequencyPercentage (%)
Age 20–253310.3
26–306219.4
31–3511335.3
36–408125.3
40 and above319.7
Province of Guangdong8526.6
Jilin4714.7
Shanghai4313.4
Hubei3310.3
Guangxi123.8
Beijing165.0
Chongqing82.5
Anhui165.0
Shandong82.5
Hebei165.0
Tianjin123.8
Zhejiang165.0
Jiangsu82.5
Experience 1–4319.7
5–811034.4
9–1213341.6
13 and above4614.4
Status Procurement manager4915.3
Reverse logistics manager6420.0
Eco-design manager9228.8
Transport manager7924.7
Production manager3611.3
Source: SPSS output (2022).
Table
Table 2. Measurement model analysis of green supply chain performance management.
Table 2. Measurement model analysis of green supply chain performance management.
ModelChi-Square (df), SignificanceNFITLICFIRMSEAVariableStandardized
Factor Loading Estimate		Error VAR
Green supply chain performance management(5 df)
5.86, p > 0.000		0.960.950.980.043GSCPM10.670.34
GSCPM20.890.44
GSCPM30.740.41
GSCPM40.720.38
Source: Amos 24.0 output on research data, 2022.
Table
Table 3. Measurement model analysis of manufacturing.
Table 3. Measurement model analysis of manufacturing.
ModelChi-Square (df), SignificanceNFITLICFIRMSEAVariableStandardized Factor Loading EstimateError VAR
Manufacturing(67 df)
255, p > 0.000		1.050.960.950.06AoM10.760.54
AoM20.770.25
AoM30.740.46
AoM40.890.38
Source: Amos 24.0 output on research data, 2022.
Table
Table 4. Measurement model analysis of transportation.
Table 4. Measurement model analysis of transportation.
ModelChi-Square (df), SignificanceNFITLICFIRMSEAVariableStandardized Factor Loading EstimateError VAR
Transportation (49 df)
60.5, p > 0.000		0.981.041.000.054ARL 10.830.44
ARL 20.810.56
ARL 30.720.09
ARL 40.690.51
Source: Amos 24.0 output on research data, 2022.
Table
Table 5. Measurement model analysis of reverse logistics.
Table 5. Measurement model analysis of reverse logistics.
ModelChi-Square (df), SignificanceNFITLICFIRMSEAVariableStandardized Factor Loading EstimateError VAR
Reverse logistics(89 df)
356, p > 0.000		1.020.970.990.038ARl10.840.22
ARL 20.720.25
ARL 30.680.47
ARL 40.670.29
Source: Amos 24.0 output on research data, 2022.
Table
Table 6. Measurement model analysis of eco-design.
Table 6. Measurement model analysis of eco-design.
ModelChi-Square (df), SignificanceNFITLICFIRMSEAVariableStandardized Factor Loading EstimateError VAR
Eco-design(78 df)
541, p > 0.000		1.041.061.010.036AED 10.890.55
AED 20.740.56
AED 30.710.29
AED 40.780.33
Source: Amos 24.0 output on research data, 2022.
Table
Table 7. Result of standardized and unstandardized regression estimate of the model.
Table 7. Result of standardized and unstandardized regression estimate of the model.
S/NMediation StageRelationshipStd. BetaActual BetaSECRP
1.X→Y
(Hypothesis 1)		Green supply chain performance management and manufacturing0.870.750.131.990.000
2.X→Y
(Hypothesis 2)		Green supply chain performance management and transportation0.770.790.363.110.000
3.X→Y
(Hypothesis 3)		Green supply chain performance management and reverse logistics0.780.850.343.080.000
4.X→Y
(Hypothesis 4)		Green supply chain performance management and eco-design0.960.680.212.180.000
5.X→Y
(Hypothesis 5)		Green supply chain performance management and procurement0.850.860.192.210.000
Source: Amos 24.0 output on research data, 2022.
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.

Share and Cite

MDPI and ACS Style

Abbas, H.; Tong, S. Green Supply Chain Management Practices of Firms with Competitive Strategic Alliances—A Study of the Automobile Industry. Sustainability 2023, 15, 2156. https://doi.org/10.3390/su15032156

AMA Style

Abbas H, Tong S. Green Supply Chain Management Practices of Firms with Competitive Strategic Alliances—A Study of the Automobile Industry. Sustainability. 2023; 15(3):2156. https://doi.org/10.3390/su15032156

Chicago/Turabian Style

Abbas, Hassan, and Shu Tong. 2023. "Green Supply Chain Management Practices of Firms with Competitive Strategic Alliances—A Study of the Automobile Industry" Sustainability 15, no. 3: 2156. https://doi.org/10.3390/su15032156

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop