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Article

Exploring the Challenges to Adopt Green Initiatives to Supply Chain Management for Manufacturing Industries

by
Abbott Po Shun Chen
1,
Yung-Fu Huang
1 and
Manh-Hoang Do
1,2,*
1
Department of Marketing and Logistics Management, Chaoyang University of Technology, Taichung 413310, Taiwan
2
Faculty of Economics, Tay Nguyen University, Buon Ma Thuot 63000, Vietnam
*
Author to whom correspondence should be addressed.
Sustainability 2022, 14(20), 13516; https://doi.org/10.3390/su142013516
Submission received: 26 September 2022 / Revised: 14 October 2022 / Accepted: 17 October 2022 / Published: 19 October 2022
(This article belongs to the Special Issue Green Information Technology and Sustainability)
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Abstract

:
Green initiatives have been widely introduced and have contributed to attaining sustainability and improving performance for supply chain management. However, only a few studies focus on green supply chain management (GSCM) practices in Vietnam. Hence, this work is the first study modeling the challenges in implementing green initiatives in the Vietnamese manufacturing supply chain. The authors aim to identify the fundamental challenges and evaluate the cross-interactions among them. The Interpretive Structural Model (ISM) method has been employed, based on experts’ perspectives, to clarify which factor is the most potent challenge. Consequently, seven major challenge clusters have been identified, and they were divided into nineteen sub-challenges. Meanwhile, the authors evaluated their interrelationships based on the hierarchical structure diagram and the Matrice d’Impacts Croisés Multiplication Appliquée á un Classement (MICMAC) analysis. It is observed that the “Financial Costs” elements group is the most difficult, followed by the lack of the Vietnamese government’s green regulation and the lack of senior managers’ support. The “Information” challenges cluster is considered as the middle bridge between the strong and weak elements. At the end of the diagram, two challenges are a lack of training courses about implementing GSCM and a lack of customer awareness and pressure about GSCM. Hence, these findings will become valuable suggestions for the top managers of Vietnamese manufacturers to make blueprint decisions.

1. Introduction

Eco-friendly production activities tend to be widely conducted and aim to minimize harm to the planet. Moreover, some studies documented that sustainability could be reached by reusing and recycling the used products [1,2]. Undoubtedly, sustainable development drives most governments to concentrate more on environmental protection and green economy building through established environmental policies [3,4]. In terms of the supply chain, green initiatives have been widely discussed and adopted to reduce the harms to the environment and achieve sustainability [5]. Unsurprisingly, the green supply chain management (GSCM) practices have been firmly integrated into firms’ business strategies as a result of the advantages of these initiatives to enhance brands, improve competing capability, and improve business performance [6,7]. However, several authors still have inconsistent arguments regarding GSCM practices. For example, by considering different aspects, Taddei et al. [8] have synthesized conflicting studies regarding relevant GSCM concepts such as circular supply chains. In particular, some studies focused on the identification of diversity challenges, the drivers, or the factors which impact the GSCM practices in various sectors [1,9]. In fact, supply chain management is a series of complex tasks that must involve all stakeholders, from upstream to downstream, acting together to avoid adverse impacts on the ecological and local community. Therefore, the vulnerability and discontinuity of the GSCM practices significantly influence organizational performance [7,10]. Aiming to implement green ideas in the supply chain, several challenges for the GSCM practices have been defined and must be solved. Notably, there is no consistency and limited research on identifying challenges for adopting green initiatives in supply chain management [11,12]. Depending on the specific research context, scholars have defined several key variables that impact the GSCM practices [4,11]. For instance, Rahman et al. [13] indicated the role of knowledge and hi-technology in green practices in the Bangladesh plastic sector; costs and long return periods [14,15]; or the market competition and uncertainty [15,16]. Hence, the results of these empirical cases may be biased [4], leading to promising suggestions for other scholars to consider in the various research contexts to enrich the GSCM literature [11].
Research on environmental problems is receiving more attention in developing countries, where there have been many reports related to harmful impacts and solutions related to the ecology [5], particularly in the manufacturing industries [17]. The pressure and awareness from the local inhabitants are the key factors that force enterprises to change their development strategies. Unfortunately, the citizens of developed economies take more drastic actions, whereas an apathetic attitude is typical in emerging economies [5,13,18]. Vietnam is a transitional and dynamic economy, where green innovation is encouraged to be implemented and integrated into the development strategy [1,19]. The social responsibility of Vietnamese enterprises in recent years has experienced many significant changes related to the community [18,20]. As a result, they have made more contributions to the local inhabitants through social activities, reducing the harmful impact on the ecosystem [21,22]. In fact, the manufacturing industry is among Vietnam’s most significant sectors and firmly influences the Vietnamese socio-economy [1]. However, the existing literature has a lack of studies concentrating on the GSCM practices in this country; moreover, Vietnam has been suggested as a promising context for research related to environmental and sustainability issues [1,21]. Thus, considering the GSCM practices in the case of the Vietnamese manufacturing sector is an exciting topic that could contribute to the GSCM literature. In this case, the authors have chosen the Vietnamese manufacturing industry as the research context to explore which challenges can impact GSCM practices. Thereby, to fill these gaps, this manuscript has the following research objectives:
RO1. Exploring the challenges of adopting green initiatives to supply chain management for the Vietnamese manufacturing sector.
RO2. Evaluating the interrelationships among challenges to identify the most power parameter.
RO3. Discussing the research results and research implications for both theory and practice.
Hence, these findings will solve the existing research gaps, such as identifying the challenges regarding adopting green initiatives in SCM and modeling them through exploring complex interrelationships. Notably, this is the first research in Vietnam that could address the obstacles to Vietnamese manufacturers’ GSCM practices. Thus, the theories related to these identified challenges have great potential for evaluation in other contexts in the future. In detail, the main content of this article will be arranged and represented in the following sequence. After the introduction, Section 2 will cover the GSCM literature and the vital challenges for GSCM practices. Then, Section 3 clarifies the research methodology. Next, the findings and research implications will be discussed and presented thoroughly in Section 4 and Section 5, respectively. Finally, the conclusions and the future scope are detailed in the last section.

2. Identification of Challenges

The swift prevalence of green initiatives in supply chain management has attracted the attention to consider by scholars and practitioners. As a result, the existing literature has experienced numerous GSCM concepts and approaches in different contexts [12,23]. Choudhary and Sangwan [11] have employed more than 500 recent articles related to GSCM topics, and they found that emerging markets are a promising research context for scholars. In line with that, Zhang and Zhao [12] also used the bibliometric analysis technique and focused on the platform to highlight the GSCM practice problems. Meanwhile, according to the evidence from small and medium South African manufacturers, Bag et al. [6] evaluated the relationships among green ideas, GSCM, and firm performance. They confirmed that eco-friendly innovation could be encouraged due to the efficiency in enhancing GSCM practices and improving performance (Table 1).
Furthermore, Shetty and Bhat [5] emphasized that eco-friendly issues have been widely conducted in various industries, and they suggested that firms must proactively respond to challenges. Indeed, various challenges or barriers have been highlighted to clarify and diversify knowledge about GSCM practices [11,42]. Regarding the manufacturing industries, several studies have claimed that the manufacturers are attempting to conduct environment management systems to offer cleaner products, particularly in developing countries, such as the Indian automotive industry [30,34] and Brazil [43]. Notably, India is the context that has recorded the most studies in this regard. For example, Govindan et al. [27] have suggested 26 critical barriers for Indian enterprises from a total of 47 identified GCSM implementation barriers. In line with that, Soda et al. [28] have considered 16 GSCM obstacles to the power industry, and Kalpande and Toke [44] assessed 15 barriers for Indian manufacturing to reach sustainable development. Additionally, a diversity of approaches has been shown, such as the AHP-ELECTRE technique [31], and the DEMATEL approach also has been conducted due to complex issues of identification of essential GSCM barriers. The Indian food packaging industries [24] and manufacturing industries in Canada [33] are notable samples. Therefore, based on the existing literature about GSCM practices, thanks to the consultation of relevant experts who have extensive knowledge about green initiatives and GSCM practices, this research tries to identify and concentrate on the most critical elements in this regard. Hence, the list of challenges that may interfere with adopting green initiatives in the SCM of the manufacturing industries has been discussed and identified. Consequently, this study will evaluate nineteen vital challenges (Table 1).

2.1. High Investments and Less Return-on-Investments

Financial resources are a key challenge in GSCM implementation, which requires firms to invest in technology, systems, and operational competitive capabilities [25]. Furthermore, Return on Investment is a common profitability metric for determining how well an investment has done [26,45]. If the firm invests in GSCM but the payback period is long and the efficiency is low, it becomes a key challenge when implementing GSCM, as has been verified by several studies in the past [14,25,26].

2.2. Non-Availability of Financial Assistants

Majumdar and Sinha [14] indicate non-availability of financial assistants is one of the economic factors that make it difficult to apply green initiatives to achieve organizational goals. Lack of initial capital, difficulty in accessing organizations and lending funds, lack of loan capital for environmental development projects, and high recycling costs are the reasons for limiting the application of GSCM [27,28,38].

2.3. Financial Constraints

Green idea applications may be hampered by a lack of funding or cost of green application [13,16,27]. In particular, there may be difficulty in accessing loan capital, high cost of conversion, management of operating costs, and cost implication [13,30]. Therefore, financial inadequacies are one of the elements that make it difficult to conduct green ideas in the SCM [38].

2.4. High Cost of Hazardous Waste Disposal

Some authors pointed out that, in local industries, some of the most mentioned green practices are environmental practices including hazardous waste treatment, environmental protection, and use of recycled products [14,15]. How firms can manage hazardous waste disposal is one of the big questions in each industry to reduce high cost of treatment [34,37]. Several scholars have claimed that high cost of hazardous waste disposal is one of the barriers for firms to carry out their GSCM [24,27,38].

2.5. Lack of Government Regulation and Legislation

Some studies found that government regulation and legislation is one of the primary influences on GSCM adoption in the country [13,31]. Firms are compelled to implement applicable strategies and practices in order to improve their performance as a result of legislation [13,14,29].

2.6. Lack of Customer Awareness and Pressure about GSCM

Customer awareness of the problems for environmental issues, such as biodiversity loss, pollution, global warming, and so on, is growing [13]. Thus, environmental awareness is a critical component of our daily life [15,34,46]. In order to protect the sustainability of development, there is pressure on everyone to commit to becoming more environmentally conscious through the implementation of green ideas [4,18]. If customers have a good awareness of green products, the implementation of GSCM will become favorable [47].

2.7. Lack of Involvement of Top Management in Adopting GSCM

The participation of top management plays an important role in GSCM implementation [48,49], for the following reasons: to be implemented, a GSCM needs top management support through approval of necessary resources and persuading stakeholders [32]. Top management has the authority to allocate supply chain resources and the power to structure or restructure resources [50]. Top management approves policies related to GSCM implementation in order to achieve the organizational objective [48].

2.8. Lack of Technical Expertise

Technical expertise barriers to the implementation of environmental initiatives have been classified as internal barriers [33,51]. However, many studies suggest that the lack of technical expertise is the basic condition of companies in the process of applying [15,31,34]. Firms will be able to prioritize and manage their resources more efficiently and effectively such as new technologies, raw material, and technical expertise of employees [15,33].

2.9. Lack of Training Courses about Implementing GSCM

Training courses are a necessity for changing the perspective of managers and employees in applying green inititatives and SCM practices [24,27,33]. To cooperate with customers, training employees is required for green suppliers to build up a green system [47]. Environmental problems, such as product design, material sourcing, manufacturing processes, and distribution channels, are all incorporated into green supply chain management [47,52,53].

2.10. Lack of Awareness about Reverse Logistics Adoption

The term “reverse logistics” refers to any operations that occur after a product has been sold. The most significant phase of reverse logistics has been recognized as product return choices, such as used product, refurbished/remanufactured, and recycled items [35]. Furthermore, the increased awareness of environmental concerns and the benefits of recycling puts further pressure on firms to develop a better reverse logistics approach [34].

2.11. Lack of Environmental Knowledge

Knowledge about environmental issues appears to be low in developing countries, indicated by the use of input materials that are not safe for the environment, which may affect the transformation and implementation of GSCM [31]. Environmental attitudes are found to be correlated with environmental knowledge in a consistent and favorable way [4]. Because knowledge and attitudes are linked, a lack of environmental knowledge has troubling implications for GSCM and it will become an obstacle [24,31,34].

2.12. Market Competition and Uncertainty

Market competition and uncertainty have an influence on the adoption of target costing [27,36,54]. To achieve the goal of sustainable development in line with the general trend of the market, they must focus on minimizing costs and maximizing profits to enhance their advantages compete in an uncertain environment [1,55].

2.13. Lack of Corporate Social Responsibility

Commitment-related responsibility is one kind of corporate social responsibility of each firm and lack of corporate social responsibility (CSR) has been identified as a significant variable in the SCM [30,33]. The classification of barriers needs to be done to understand the difficulties in green initiatives’ implementation, as well as solutions to both reduce costs and optimize green implementation. Thus, CSR ideas can help businesses adopt and implement GSCM by providing valuable insights [20,23,56].

2.14. Restrictive Company Policies towards Product/Process Stewardship

Examining the company’s recycling and operations policies and procedures can demonstrate how the company’s managers can reduce the negative influence on the environment [57,58]. The company’s top managers can strike a good balance between cost and environmental performance. Therefore, restrictive company policies for product/ process management directly affect the GSCM transition and become a challenge to green initiatives’ implementation [15,27,33].

2.15. Lack of New Technology, Materials, and Processes

The allocation of resources to a new direction of the organization can reduce environmental pollution impacts through the application of new technologies, materials, and processes [36]. Furthermore, new technology, material, and processes, in particular, may help businesses compete on a global scale by lowering costs [59]. Hence, GSCM enhances the competitive advantage of any company by using the processes, technology, and capabilities of upstream supply chain partners that need to be taken care of, otherwise it becomes a challenge to GSCM implementation [13,38].

2.16. Lack of Effective Environmental Measures

A firm will be more competitive if they have effective environmental programs and encourage their supplier partners to enhance environmental performance, minimize waste, and increase cost-saving [25,39]. Recent studies have shown that the firm’s competitiveness and profitability will improve as a result of implementing appropriate environmental measures [36]. The SCM consists of integrating the environmental issues and measures through the practices oriented towards the environment [47,53,59].

2.17. Complexity of Green Process and System Design

The complexity of the green processes and system design is a key point that firms must overcome in order to make efficient use of the resources available in the current industry [27,60]. As a result, businesses must design green procedures that maximize the use of all available resources [14,36]. Inadequacies in the design of processes and systems are a challenge for the adoption of green ideas in the SCM [14,29].

2.18. Poor Supplier Commitment; Unwillingness to Exchange Information

Poor supplier commitment or unwillingness to exchange information is further explained by a lack of trust and the fear of leaking information [49]. However, the supplier’s failure to switch to GSCM means they are afraid of exposing their weakness and losing their competitive edge [16]. This factor is considered as a challenge due to suppliers having different perspectives on environment problems [27,33,61].

2.19. Lack of an Environmental Partnership with Suppliers

The number of companies that understand the benefits of green initiatives is increasing dramatically, and collaborating with their suppliers to reduce their ecological effects is necessary. It is necessary to create a relationship with suppliers by developing reward systems, profit sharing, or establishing trust [36,59] so that the supply chain partners’ role will be synchronized to reduce the environmental harms [14]. Hence, environmental consciousness to maintain partnerships with suppliers will become a key challenge [15,27].

3. Research Methodology

3.1. The ISM Technique

Aiming to evaluate the interrelationships among challenges to identify the most potent variables in the Vietnamese manufacturing sectors, the authors used the Interpretive Structural Model (ISM) to solve this research objective. The ISM technique was developed by Warfield [62] to construct an interconnection matrix, which helped the authors to illustrate different factors into a unified and intelligible model based on the experts’ perspective. Indeed, the application scope of this ISM approach has been swiftly rising due to its advantages, particularly in qualitative studies [1]. The significant benefit is that it does not require too many respondents and it is possible to quickly interview and collect their opinions [63,64,65], even needing only two professionals in Agrawal’s research [66]. More importantly, this technique requires the participants to have extensive knowledge and wisdom in the research topic, such as senior lecturers and top managers [1]. Thus, several authors have claimed that the ISM method is the most effective and more accessible than other qualitative and quantitative techniques in analyzing the results, showing a logical and transitive relationship among variables [1,65,67]. Noticeably, this technique also provides suggestions to identify the most powerful variables based on the driving power values of each element [17,68]. Hence, this study agrees with the suggestions of previous studies in employing the ISM approach to explore the interrelationships among green initiatives challenges [63,64,65,66]. Based on their recommendations, the ISM technique has been employed through several basic steps as follows (Figure 1).

3.1.1. Step 1: Developing Structural Self-Interaction Matrix

Several essential variables were identified, which are the GSCM challenges in the contextual research, which are the results relying on the insights of the relevant literature combined with the consultation of the experts’ perspective. Consequently, a contextual relationship has been established among them as “Vi leads to Vj” in the Structural Self-Interaction Matrix (SSIM) (i and j indicates variables in row and column of the matrix) [1,67]. In detail, the SSIM matrix has four linguistic symbols: V, A, X, O indicate the different relationships as follows:
V :   means = > V j
A :   means = > V i
X :   means   < = >   V j
O :   means   V i   < ≠ >   V j

3.1.2. Step 2: Establishing Reachability Matrix

In this stage, the SSIM matrix will transform into the reachability matrix, and the binary matrix represents four symbols (V, A, X, O) with two distinct values, including “1” and “0”. This means if the (i,j) entry is “1”, then the opposite cell (j,i) is “0” [1,17]. Thereby, firstly, the initial reachability matrix (IRM) witnesses the substitution of all symbols by the binary values, where “V” and “X” replaced by “1”, and “0” will be replaced for “A” and “O”. Secondly, the final reachability matrix (FRM) could be obtained by considering the integrating transitivity phase, and then by employing the entries “1*”, which indicates transitivity links among elements. Additionally, the authors can evaluate two essential values as “driving power” and “dependence power” in this step, calculating these two values by the total of factors’ entries per row and column, respectively (including itself).

3.1.3. Step 3: Partitioning of All Variables into Levels

After identifying the final reachability matrix, the authors perform level partitioning to highlight that the intersection consists of the “reachability set” and “antecedent set”, which were derived for all variables [1,17,67].

3.1.4. Step 4: Drawing the Directed Graph

Consequently, the ISM model could be drawn from the level of the partitioning to demonstrate each group from the bottom to the top of the digraph. The ISM graph indicates that the most essential or powerful variables are located at the bottom. Besides that, the authors must check for any inconsistency in concept and consider necessary modifications, if required [1,17,67].

3.1.5. Step 5: The MICMAC Analysis

This stage will employ the MICMAC analysis based on two essential values of the final reachability matrix (Step 4) to point out and discuss the research results, consisting of “driving power” and “dependence power”, which indicates the significance of each factor (Table 2) [17,67]. Remarkably, four distinguished quadrants can reveal the role of each variable if it belongs to that cluster [1]. The key challenges are the variables with a driving power higher than the mean value and dependence power as small as possible.

3.2. Research Context

In Vietnam, enterprises are under tremendous pressure from stakeholders to comply with their commitments to ecological protection and contributions to the community [18]; more particularly, the Vietnamese government actively encourages various industries to adopt green ideas to achieve sustainability [1,19,22]. Consequently, the integration of green ideas into the manufacturing supply chain under research is one of the main concerns in Vietnam due to its vast influence on the socio-economy [1,19]. However, the complexity of the supply chain will significantly affect the implementation of green strategies [4,29,65], particularly in the transitional market condition [19,65]. Hence, this work could help better understand the roadmap for adopting green initiatives in the Vietnamese manufacturing supply chain context and which challenges must be overcome.
The semi-structured interviews were conducted with the respondents, who are Vietnamese experts in supply chain management in both academic (n = 3) and manufacturing industries (n = 4) (Table 3). Based on their experience (at least 11 years) and extensive knowledge regarding the topics, they provide their judgments to the authors, defining challenges to adopting green initiatives and the decision-makers that could help the authors establish the ISM model and the MICMAC analysis [17,67].

4. Research Findings

The manufacturing industry is an essential sector in a transitional country such as Vietnam and also firmly influences the socio-economy [1]. However, under pressure from stakeholders to reach sustainability, Vietnamese firms must overcome several challenges in attempting to employ green initiatives to SCM for this industry. Consequently, there are nineteen variables, which have been considered as the most vital challenges for the SCM of Vietnamese manufacturing industry (Table 1). They were divided into seven categories including Financial Costs (n = 4), External Stakeholders (n = 2), Human Resource (n = 3), Information (n = 3), Strategic Management (n = 2), Technology (n = 3), and Suppliers (n = 2). Meanwhile, to solve the second research objective, the ISM method was conducted to evaluate the interrelationships among challenges. From that, the findings provide some suggestions to identify the most powerful variables [17]. Thus, following the ISM approach rules [67,68], the authors have processed the data based on the perspectives of senior experts.
Firstly, the Structural Self-Interaction Matrix has been developed, relying on the cross-interactions among identified nineteen variables (Table A1-Appendix A). The experts have been interviewed to share their experience and extensive knowledge about relevant topics, particularly defining interrelationships among challenges in this work. As a result, the SSIM demonstrated the different correlations by four linguistic symbols are “V, A, X, O”. For example, “V” means CO1 can help to achieve CO2; if ES2 has been obtained by HR2, then the symbol is “A”; if CO1 and CO3 are able to achieve each other, then the symbol is “X”; if there is no relationship between CO1 and CO4, then the symbol is “O”.
Secondly, a Reachability Matrix has been established by transforming the SSIM (Table A2-Appendix A). The binary matrix with two distinct values (“1” and “0”) will replaced by four symbols (V, A, X, O). Noticeably, the authors evaluated two essential values as “driving power” and “dependence power” in this step. Calculation was carried out of these two values by the total of the factor’s entries per row and column, respectively (including itself). However, the integrating transitivity phase was considered and represented by “1*” in the final reachability matrix (Table A3-Appendix A). As a result, the high investments and less return-on-investments (CO1) and financial constraints (CO3) have the biggest driving power values (value = 19), followed by non-availability of financial assistance (CO2 value = 17); meanwhile, lack of customer awareness and pressure about GSCM (ES2) and lack of training courses about implementing GSC (HR3) have the smallest values (value = 1).
Thirdly, aiming to draw the diagram, which can illustrate directed relationships among the nineteen GSCM challenges, level partitioning was performed for all variables. Consequently, ten levels represent all GSCM challenges of Vietnamese manufacturing industries (Table A4-Appendix A). Finally, to connect these with the measured value in the final level partitioning table, the digraph was developed into the ISM model for the Vietnamese manufacturing firms to apply green initiatives to supply chain management (Figure 2).
It has been observed that ten levels in the diagram indicate the critical role of each GSCM challenge. At level 1 of the ISM model, the two challenges are lack of training courses about implementing GSCM (HR3) and lack of customer awareness and pressure about GSCM (ES2). Meanwhile, at level 10 of the ISM model, the financial challenges with two sub-obstacles are high investments and less return-on-investments (CO1) and non-availability of financial assistants (CO3); then, the financial constraints (CO2) are shown at level 9. Likewise, the classification levels in Figure 2 are linked by arrows that describe relationships between the factors from bottom to top.

5. Discussions and Research Implications

In terms of the adoption of green ideas for the SCM of the Vietnamese manufacturing sector, the authors have successfully identified seven categories with nineteen vital challenges. At the last stage of the ISM approach, the authors employed the MICMAC analysis based on two essential values of the FRM consisting of “driving power” and “dependence power” to clarify the role of each challenge [67]. All nineteen challenges were allocated to four distinguished quadrants, which served as a basis for comparisons with other studies and suggested several research implications in both theoretical and practical areas (see Figure 3) [1].
Surprisingly, there are no GSCM challenges in cluster I (Autonomous) in the case of Vietnamese manufacturing industries. This range indicates a weak effect on the system that is easily overcome. Thus, nineteen sub-challenges focus on the remaining three quadrants, so applying green ideas to supply chain management will be more difficult, consistent with the findings of Mathiyazhagan et al. [34] in India context.
Secondly, the identified challenges, V18-Poor supplier commitment unwilling to exchange information (SU1), V16-Lack of effective environmental measures (TE2) [27], V13-Lack of corporate social responsibility (SM1) [34], V17-Complexity of green process and system design (TE3) [14], V8- Lack of technical expertise (HR2) [15], V9-Lack of training courses about implementing GSC (HR3) [28], V6-Lack of customer awareness and pressure about GSCM (ES2) [16,34] are in the group of “dependent” challenges (cluster II). These variables have a weak driving power but strong dependence power. Moreover, this case study gathered the majority of the GSCM challenges in this cluster compared to the rest. Combined with the level partitioning digraph (Figure 2), these key challenges range from level 1 to level 5, and it is found that ES2 and HR3 challenges (level 1) could have less attention than other obstacles in the Vietnamese manufacturing industries context, and particularly the role of customer’s pressure (ES2 challenge), which is the most essential element in the Indian manufacturers [34]; however, it inconsistent with the finding of this research. Meanwhile, in the context of developed countries such as Canada, Kaur et al. [15] suggested that Canadian manufacturing companies need more training courses as well as help from research institutes related to green knowledge and how to adapt green ideas to SCM.
Moving to the cluster III (Linkage), it is seen that six sub-challenges consist of V10— Lack of awareness about reverse logistics adoption (IN1) [30], V11—Lack of environmental knowledge (IN2) [13], V12—Market competition and uncertainty (IN3) [37], V14— Restrictive company policies towards product/process stewardship (SM2) [44], V15—Lack of new technology, materials and processes (TE1) [13], and V19—Lack of an environmental partnership with suppliers (SU2) [14]. Interestingly, these six elements form level 6 of the ISM model. Thus, implementing green initiatives into supply chain management will be successful if the Vietnamese manufacturers focus on this group. In addition, the substantial driving power value will impact the senior manager’s decision and development strategy. The linkage factors are the middle bridge between the strong and weak elements in this study. Hence, the “Information” factors challenge has been recommended for Vietnamese firms to deal with.
Finally, V1—High investments and less return-on-investments (CO1) [31,69], V3—Financial constraints (CO3) [29], V2—Non-availability of financial assistants (CO2) [15], V4—High cost of hazardous waste disposal (CO4) [69], V5—Lack of government regulation and legislation (ES1) [70], and V7—Lack of involvement of top management in adopting GSCM (HR1) [44] belong to the “independent” cluster. In the hierarchical structure diagram, it is observed that these challenges serve as the basis for the whole structure (from level 7 to level 10). Therefore, they are the most critical obstacles to remove if applying green initiatives to SCM in Vietnamese manufacturing industries. Notably, through the survey from the SCM experts, the authors found that the “Financial Costs” factors are the biggest concerns of Vietnamese manufacturers if they implement green programs. Indeed, some previous studies also mentioned this problem if conducting any new ideas in emerging economies [1,29]. However, some issues related to the financial risk that they may face have become their critical concern [31,69]. The unexpected dangers of investing heavily in implementing green ideas have forced Vietnamese enterprises to consider them. However, this study finding is inconsistent with other prior studies. According to their results, the manufacturing sector has also been evaluated in the context of a transitional economy. Kalpande and Toke [44] claimed that Indian firms should increase the role of top managers due to their lack of commitment to green programs. Meanwhile, Rahman et al. [13] stressed that manufacturers in Bangladesh need training courses regarding to green practices. Hence, in this study, six elements in the “independent” quadrant are the key suggestions for the Vietnamese manufacturing sector to consider before making strategy decisions.
Through evidence from the Vietnamese manufacturing sectors, modelling the challenges of adopting green initiatives to SCM could provide several research implications in both theoretical and managerial areas. Firstly, this study conducted semi-structured interviews with the experts; thereby, the research findings contribute to the existing SCM literature on the knowledge related to green initiatives and the green supply chain management, especially in the manufacturing industry context of the emerging market. Promoting and implementing green ideas in SCM is an obligatory trend if corporations want to improve their competitive advantage [3,26]. Secondly, this research stressed the suggestions regarding the various challenges the Vietnamese manufacturers possibly overcome. As a result, seven major obstacles have been identified and divided into nineteen sub-challenges that should be solved simultaneously. Thanks to the ISM approach, the authors could evaluate the interrelationships among nineteen parameters to identify which is the most powerful challenge based on the hierarchical structure diagram and the MICMAC analysis. However, senior managers lack management experience, and other limitations such as financial ability and partnerships affect the decision of the top managers [35]. Hence, they clearly understand that they could not solve all these challenges simultaneously. The suggestions indicate that they only prioritized identifying and dealing with fundamental challenges [6,26]. Consequently, the research findings offer valuable knowledge contributions to Vietnamese manufacturers on how to adopt green initiatives. As discussed above, the top managers should prioritize several challenges in the “independent” and "linkage" clusters.

6. Conclusions and Future Scope

Green initiatives have been introduced and confirmed in the context of supply chain management to help the enterprises’ competing capabilities and sustainability. Aiming to offer practical evidence contributes to the GSCM literature; with Vietnamese manufacturing industries as the particular sample, this study tried to achieve three research objectives. Consequently, it is observed that there are seven most significant challenge clusters, which are grouped by nineteen different variables. Combining the ISM model and the MICMAC analysis, the authors successfully modeled the interrelationships among these challenges to identify the most potent parameter. Based on two power values consisting of “driving” and “dependence”, this study indicated that the “Financial Costs” challenges group, along with the green regulation of the Vietnamese government and the senior manager’s attention, are the top priorities, followed by the “information” challenges cluster.
This study revealed that this is the first empirical research in Vietnam and makes several contributions related to the manufacturing supply chain and eco-friendly problem. Unfortunately, this research still has some limitations, which may become promising ideas in the future scope for other scholars to explore. Firstly, employing the ISM approach, the authors have interviewed several SCM experts’ perspectives from academia and manufacturing corporates to develop a theoretical model; however, the identified challenges might not be fully comprehensive due to the research context in this case. Secondly, due to the ISM method only requiring a small number of respondents for the survey, this framework model should be statistically validated with a large sample, which can be generalizable for the Vietnamese manufacturer supply chain; thus, structural equation modeling (SEM) will be suggested in the future. Finally, the eco-friendly problem was considered in the Vietnamese manufacturing supply chain. Hence, applying and assessing this model in diverse contexts and comparing the research findings will enrich the GSCM literature.

Author Contributions

Conceptualization, Y.-F.H. and M.-H.D.; methodology, Y.-F.H. and M.-H.D.; validation, A.P.S.C. and Y.-F.H.; formal analysis, A.P.S.C.; investigation, M.-H.D.; resources, Y.-F.H. and M.-H.D.; data curation, A.P.S.C. and M.-H.D.; writing—original draft preparation, M.-H.D. and A.P.S.C.; writing—review and editing, M.-H.D.; visualization, A.P.S.C.; supervision, Y.-F.H.; project administration, Y.-F.H. and A.P.S.C. All authors have read and agreed to the published version of the manuscript.

Funding

The APC was funded by grants from the National Science and Technology Council, Taiwan (Grant numbers: MOST-111-2637-H-324-001-) and the Ministry of Education, Taiwan (Grant numbers: 1110035928).

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

Not applicable.

Conflicts of Interest

All authors declare no conflicts of interest in this paper.

Appendix A

Table
Table A1. Structural Self-Interaction Matrix (SSIM).
Table A1. Structural Self-Interaction Matrix (SSIM).
jV1V2V3V4V5V6V7V8V9V10V11V12V13V14V15V16V17V18V19
iChallengesCO1CO2CO3CO4ES1ES2HR1HR2HR3IN1IN2IN3SM1SM2TE1TE2TE3SU1SU2
V1CO11VXOVOOVVOOVVOOOOOO
V2CO2 1OVOOVOOVOVOOVOOOO
V3CO3 1VOOVVVOOVOOVOOOO
V4CO4 1XOOOOOVVOVOOOVO
V5ES1 1OVOVVOOOVOOOOV
V6ES2 1OAOOOAOOAOAOO
V7HR1 1VOOVVOVOOVOO
V8HR2 1OOOOAAAAOOA
V9HR3 1OOOAOAAOOO
V10IN1 1VVVVVVOOA
V11IN2 1VVAAOOOA
V12IN3 1OOOOOVV
V13SM1 1AOAOAO
V14SM2 1VOOVV
V15TE1 1OVOO
V16TE2 1OAA
V17TE3 1OA
V18SU1 1O
V19SU2 1
Table
Table A2. Initial Reachability Matrix (IRM).
Table A2. Initial Reachability Matrix (IRM).
jV1V2V3V4V5V6V7V8V9V10V11V12V13V14V15V16V17V18V19Driving Power
iChallengesCO1CO2CO3CO4ES1ES2HR1HR2HR3IN1IN2IN3SM1SM2TE1TE2TE3SU1SU2
V1CO111000111100101100018
V2CO201011100010100101116
V3CO300111110010100011118
V4CO401011110111100101116
V5ES100001010010100000107
V6ES200000101011010000011
V7HR100001010011000000106
V8HR200000001010100000002
V9HR300000000100000000001
V10IN100000000111100000007
V11IN200000000011100000003
V12IN300000000011100000004
V13SM100000000111010000003
V14SM211000111100101100017
V15TE101011100010100101116
V16TE200111110010100011114
V17TE301011110111100101112
V18SU100001010010100000103
V19SU200000101011010000016
Dependence Power2224354974787554444
Table
Table A3. Final Reachability Matrix (FRM).
Table A3. Final Reachability Matrix (FRM).
jV1V2V3V4V5V6V7V8V9V10V11V12V13V14V15V16V17V18V19Driving Power
iChallengesCO1CO2CO3CO4ES1ES2HR1HR2HR3IN1IN2IN3SM1SM2TE1TE2TE3SU1SU2
V1CO11111*11*1*111*1*111*1*1*1*1*1*19
V2CO201011*1*11*1*11*11*1*11*1*1*1*17
V3CO311*111*1*1111*1*11*1*11*1*1*1*19
V4CO4000111*1*1*1*1*111*11*1*1*11*16
V5ES1000111*11*111*1*1*11*1*1*1*116
V6ES200000100000000000001
V7HR1000001*111*1*111*11*1*11*1*14
V8HR200000101000000000002
V9HR300000000100000000001
V10IN1000001*01*1*11111111*1*1*13
V11IN2000001*01*1*1*1111*1*1*1*1*1*13
V12IN300000101*1*1*1*11*1*1*1*1*1113
V13SM1000001*01100010000004
V14SM2000001*011*1*11*1111*1*1113
V15TE10000010111*11*1*1*11*11*1*13
V16TE2000001*01100010010005
V17TE300000100000000001002
V18SU1000001*01*1*00010010106
V19SU2000001*011*111*1*1*1*111*113
Dependence Power23255186161612121215121214131312
Table
Table A4. Final Level Partitioning (FLP).
Table A4. Final Level Partitioning (FLP).
VariablesReachability SetAntecedent SetIntersection SetLevel
11, 3,1, 3,1, 3,10
22,1, 2, 3,2,9
31, 3,1, 3,1, 3,10
44, 5,1, 2, 3, 4, 5,4, 5,8
54, 5,1, 2, 3, 4, 5,4, 5,8
66,1, 2, 3, 4, 5, 6, 7, 8, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19,6,1
77,1, 2, 3, 4, 5, 7,7,7
88,1, 2, 3, 4, 5, 7, 8, 10, 11, 12, 13, 14, 15, 16, 18, 19,8,2
99,1, 2, 3, 4, 5, 7, 9, 10, 11, 12, 13, 14, 15, 16, 18, 19,9,1
1010, 11, 12, 14, 15, 19,1, 2, 3, 4, 5, 7, 10, 11, 12, 14, 15, 19,10, 11, 12, 14, 15, 19,6
1110, 11, 12, 14, 15, 19,1, 2, 3, 4, 5, 7, 10, 11, 12, 14, 15, 19,10, 11, 12, 14, 15, 19,6
1210, 11, 12, 14, 15, 19,1, 2, 3, 4, 5, 7, 10, 11, 12, 14, 15, 19,10, 11, 12, 14, 15, 19,6
1313,1, 2, 3, 4, 5, 7, 10, 11, 12, 13, 14, 15, 16, 18, 19,13,3
1410, 11, 12, 14, 15, 19,1, 2, 3, 4, 5, 7, 10, 11, 12, 14, 15, 19,10, 11, 12, 14, 15, 19,6
1510, 11, 12, 14, 15, 19,1, 2, 3, 4, 5, 7, 10, 11, 12, 14, 15, 19,10, 11, 12, 14, 15, 19,6
1616,1, 2, 3, 4, 5, 7, 10, 11, 12, 14, 15, 16, 18, 19,16,4
1717,1, 2, 3, 4, 5, 7, 10, 11, 12, 14, 15, 17, 19,17,2
1818,1, 2, 3, 4, 5, 7, 10, 11, 12, 14, 15, 18, 19,18,5
1910, 11, 12, 14, 15, 19,1, 2, 3, 4, 5, 7, 10, 11, 12, 14, 15, 19,10, 11, 12, 14, 15, 19,6

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Figure 1. Flowchart of the ISM approach.
Figure 1. Flowchart of the ISM approach.
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Figure 2. The ISM model of GSCM for the Vietnamese manufacturing sector.
Figure 2. The ISM model of GSCM for the Vietnamese manufacturing sector.
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Figure 3. The MICMAC analysis.
Figure 3. The MICMAC analysis.
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Table
Table 1. Identification of the critical challenges of GSCM.
Table 1. Identification of the critical challenges of GSCM.
CategoryChallengesSourcesCoding
Financial Costs
(CO)		High investments and less return-on-investments[14,15,24,25,26]CO1
Non-availability of financial assistants[14,15,24,27,28]CO2
Financial constraints[13,16,29,30,31]CO3
High cost of hazardous waste disposal[14,15,24,27,31]CO4
External
Stakeholders (ES)		Lack of government regulation and legislation[13,14,15,29,31]ES1
Lack of customer awareness and pressure about GSCM[13,14,15,24]ES2
Human
Resource (HR)		Lack of involvement of top management in adopting GSCM[13,14,16,29,32]HR1
Lack of technical expertise[13,14,28,33]HR2
Lack of training courses about implementing GSC[14,15,24,34]HR3
Information
(IN)		Lack of awareness about reverse logistics adoption[14,15,24,35]IN1
Lack of environmental knowledge[13,14,15,34]IN2
Market competition and uncertainty[14,15,16,36,37]IN3
Strategic
Management (SM)		Lack of corporate social responsibility[14,15,27,30,38]SM1
Restrictive company policies towards product/process stewardship[15,27,33,38]SM2
Technology
(TE)		Lack of new technology, materials and processes[14,15,24,33,34]TE1
Lack of effective environmental measures[14,15,25,39]TE2
Complexity of green process and system design[14,15,24,40]TE3
Suppliers
(SU)		Poor supplier commitment unwilling to exchange information[15,16,34,41]SU1
Lack of an environmental partnership with suppliers[14,15,33]SU2
Table
Table 2. Identification of the MICMAC analysis.
Table 2. Identification of the MICMAC analysis.
QuadrantDriving PowerDependence Power
WeakStrongWeakStrong
(1) Autonomous✓ ✓
(2) Dependent✓ ✓
(3) Linkage ✓ ✓
(4) Independent ✓✓
Table
Table 3. Profile of Respondents.
Table 3. Profile of Respondents.
No.FieldJob TitleGenderEducationYears of
Experience
Expert 1AcademicAssociate ProfessorFemalePh.D.12
Expert 2AcademicAssociate ProfessorMalePh.D.13
Expert 3AcademicFull ProfessorMalePh.D.22
Expert 4IndustrySenior ManagerFemaleMaster16
Expert 5IndustryDirectorMaleBachelor15
Expert 6IndustrySenior ManagerFemaleMaster17
Expert 7IndustryVice DirectorFemaleBachelor11
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Chen, A.P.S.; Huang, Y.-F.; Do, M.-H. Exploring the Challenges to Adopt Green Initiatives to Supply Chain Management for Manufacturing Industries. Sustainability 2022, 14, 13516. https://doi.org/10.3390/su142013516

AMA Style

Chen APS, Huang Y-F, Do M-H. Exploring the Challenges to Adopt Green Initiatives to Supply Chain Management for Manufacturing Industries. Sustainability. 2022; 14(20):13516. https://doi.org/10.3390/su142013516

Chicago/Turabian Style

Chen, Abbott Po Shun, Yung-Fu Huang, and Manh-Hoang Do. 2022. "Exploring the Challenges to Adopt Green Initiatives to Supply Chain Management for Manufacturing Industries" Sustainability 14, no. 20: 13516. https://doi.org/10.3390/su142013516

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