Next Article in Journal
Allotment Garden Products as Contribution to Sustainable and Resilient Cities: An Analysis in Leipzig, Germany
Previous Article in Journal
Micro-Videos as a Learning Tool for Professional Practice during the Post-COVID Era: An Educational Experience
Previous Article in Special Issue
Supply Chain Finance and Blockchain in Operations Management: A Literature Review
Order Article Reprints
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:

Nexuses among Green Supply Chain Management, Green Human Capital, Managerial Environmental Knowledge, and Firm Performance: Evidence from a Developing Country

School of Economics and Management, North China Electric Power University, Beijing 102206, China
School of Management and Economics, Beijing Institute of Technology, Beijing 100081, China
Center for Energy and Environmental Policy Research, Beijing Institute of Technology, Beijing 100081, China
Faculty of Management Sciences, Department of Business Administration, ILMA University, Karachi 75190, Pakistan
The NUST Business School, National University of Sciences and Technology, Islamabad 44000, Pakistan
Center for Research on Digitalization & Sustainability, Inland Norway Business School, Inland Norway University of Applied Sciences, 2212 Kongsvinger, Norway
Authors to whom correspondence should be addressed.
Sustainability 2023, 15(6), 5597;
Received: 12 February 2023 / Revised: 8 March 2023 / Accepted: 14 March 2023 / Published: 22 March 2023


The growing pressures from the government, buyers, consumers, suppliers, and the general public have recently compelled manufacturing firms to enhance their production methods by becoming more environmentally friendly and pursuing new innovative methods for producing green goods in developing countries. However, the relationship between green supply chain management (GSCM), green human capital (GHC), green innovation (GIN), managerial environmental knowledge (MEK), and firm performance (FPR) has received only a minimal amount of research focus. This study addresses this research gap by providing empirical evidence to motivate firms to implement GSCM, GHC, GIN, and MEK to enhance their FPR in developing countries substantially. A conceptual framework was developed to connect the concepts mentioned above. A questionnaire-based survey was used to collect the data. A total of 736 respondents from manufacturing firms in China were selected. Utilizing structural equation modeling (SEM), the data were analyzed. The findings indicate that neither GHC nor GSCM directly affects FPR; rather, GIN mediates the connection between GHC, GSCM, and FPR. In addition, the findings showed that MEK directly affects FPR and moderates the link between GIN and FPR. This study examined several theoretical and managerial implications and expanded research in the related fields. The results may help practitioners and managers comprehend how GSCM practices impact GIN and FPR. The outcomes of this research will benefit experts, policy makers, and stakeholders who seek to encourage FPR enhancements.

1. Introduction

Numerous environmental challenges have come to light due to rapid economic expansion [1,2]. Manufacturing companies’ activities may cause the exhaustion of natural resources, environmental degradation [3], and the emission of several ecological toxins that pollute biodiversity, water, light, oxygen, and the sound environment [4,5]. Several businesses and countries have recognized the importance of environmental sustainability to economic and social development. This issue requires a public emphasis on green and environmental concerns, such as green transformation, green supply chain management, recycling, and renewable energy sources [6]. Firms have sought to embrace sustainable green practices in response to requirements from various stakeholder groups, corporate entities, and environmental legislation [7,8]. GHC, GIN, and GSCM practices, as well as MEK are becoming necessary for better FPR, which affects customer fulfillment, legitimacy, desire, and belief in the manufacturing firms to attain competitiveness [9,10].
The concept of GHC was developed by [11] as a full stream of intangible capacities, knowledge, and relationships related to environmental stewardship at a firm’s corporate and individual levels. Furthermore, GHC is anticipated to relate strongly with GIN and FPR at the firm level. The GHC is “the sum of employees’ pollution prevention or green innovation-related information, competence, expertise, intelligence, inventiveness, and dedication, etc., and is entrenched in people, not firms” [12]. GHC has been highlighted as a critical component in the implementation of green human resource management (GHRM) strategies, and it is considered among the most vital corporate science concepts. It has been argued that workers’ proactive environmental skills and competencies contribute significantly to the transition of GHRM [13]. Conversely, it has been seen that employees’ knowledge and abilities increase when they recognize the corporate commitment to sustainability, which directly leads to employee engagement in the company [14]. It is believed that firms that recognize the value of GHC invest in their personnel to achieve greater FPR [15]. GHC interacts with other corporate resources and competencies. We define GHC in this paper as the whole portfolio of all intangible firm resources, connections, information, and skills managed with the ultimate vision of protecting the natural environment for better FPR. This research illustrates that GHC may be focused on FPR without compromising its ability to lead GIN. In ideal circumstances, GHC should incorporate the most recent information and add to it, creating new cycles of knowledge development [16].
GIN is a concept that can reduce adverse environmental impacts and improve FPR in order to increase public trust, cost-effectiveness, productivity, and opportunities for market share [17]. GSCM, eco-friendly nature conservation, and green and sustainable product research and development are some additions needed to implement GIN. This is difficult to comprehend from the organizational and employee points of view because it discards the current work system [18]. GIN may be achieved if environmental indicators, such as an unstable climate and restricted natural resources, are considered. Consequently, firms must adjust their activities with due consideration to their ecological consequences. By incorporating GIN, FPR can be significantly changed [19], as an advancement in FPR can provide a competitive edge. The government has introduced stringent administrative procedures to encourage manufacturing firms in heavily polluting sectors to engage in environmental projects [20]. Meanwhile, the environmental consciousness of users, environmental protection groups, communities, entrepreneurs, and other stakeholders has steadily increased, putting heavy polluters under significant environmental pressure. These highly polluting manufacturing firms must focus on environmental management to limit environmental damage and lessen environmental strain. Therefore, GIN has received considerable attention [12]. GIN is the application or enhancement of green goods or processes, such as innovations in energy-saving, pollution-prevention, waste-recycling, and green-product-design technologies [21]. As the government, environmental groups, users, communities, and the media grow increasingly concerned about the environment’s protection, legislators and scholars are paying greater attention to GIN due to its potential to accomplish a “win-win” scenario in the reduction of pollution and maximizing revenue [22], and firms can boost resource efficiency via GIN to offset environmental consequences [23].
The green concept has been extensively used in various sectors. Incorporating the term “green” into SCM necessitates considering the consequences and linkages between SCM and the environmental context. GSCM, with environmental stewardship, has become an essential organizational philosophy for achieving profitability and market share objectives by reducing environmental risks and consequences and enhancing the firms’ and stakeholders’ environmental efficiency [24,25]. GSCM reduces the ecological impact of industrial operations, improves energy usage efficiency and cooperation between business associates, and increases the firm’s strength. Furthermore, FPR and the company’s green image are improved while wastage is reduced [26,27]. According to [28], GSCM consists of several environmental management methods that might be advantageous for logistics. Its structure seeks to integrate environmental concerns into forward and reverse logistics [29]. Examples of GSCM initiatives include minimizing packing and trash, evaluating suppliers based on FPR, creating more ecologically friendly manufacturing, and decreasing CO2 emissions associated with product transportation. GSCM is a concept that can handle significant concerns, including (i) the deployment of green initiatives, (ii) the motivation of stakeholders to embrace GSCM, (iii) the impediments stakeholders face during GSCM implementation, and (iv) the effects on overall FPR [30]. GSCM is a link between a firm and its partners, consumers, and vendors in which environmental preservation is a priority. By producing green products, GSCM may increase FPR profitability [31]. Hence, the number of companies utilizing GSCM to improve FPR will increase.
To date, extensive research has focused on exploring the links among the following aspects: Studies [32,33] have reported that academic interest in GSCM has expanded considerably with GHC. As per [34], manufacturers should use GSCM features to address customer demand for sustainable and environmental products and services designed and manufactured utilizing responsible environmental procedures. This method of sustainable development addresses the ethical imperative of enterprises to enhance eco-efficiency while guaranteeing compliance with applicable regulations, hence lowering the risk of penalties and closure. The study conducted by [35] found that GHC is positively connected with all aspects of performance, including economic, social, and environmental performance. However, not every aspect of business success is linked to GHC in the same way. Social performance, defined as “enhancing stakeholder satisfaction, public safety and health, employee welfare, and reduced risk to the general populace” [36], seems to be more strongly connected with GHC than with FPR. Understanding the decreased influence of GHC on FPR, as evaluated by decreases in environmental destruction and protection from the exploitation of resources, in contrast to its impact on economic and social sustainability variables, is intriguing and essential for researchers and scholars [37]. Similarly, GSCM affects the entire environment of any business participating in supply chain activities, leading to improved FPR. GSCM is a crucial issue for the majority of companies, especially in Asia and South Asia [38]. Numerous firms in this field have demonstrated their commitment to environmentally friendly growth using this method, but there remains an opportunity for enhancement and expansion. Ref. [39] suggest that GSCM features may not be connected with economic resilience. These inconsistent results concerning the relationship between GHC, GIN, GSCM, and FPR indicate that the relationships between these essential elements should be reevaluated.
Moreover, most related studies contend that MEK reduces firms’ economic performance. However, more recent research has identified quantifiable benefits of eco-friendly practices. According to the research, MEK and FPR may have a complex relationship [40]. However, few studies have explored how firms convert their MEK into a competitive advantage and determine the essential resources required to expand their FPR. Intangible resources are frequently referred to as GHC and are considered essential than tangible resources [41]. Therefore, this study sought to demonstrate how GHC helps businesses to increase their FPR using GIN. Only [32,42] have researched GHC in relation to environmental issues. According to their research, the effects of GHC on FPR may be contradictory, and this remains an unresolved issue [43]. In comparison, while GHC at the company level has been the focus of substantial research, the related investigations have not clarified how GHC impacts FPR because they have not incorporated MEK and GIN into the interaction between GHC, GSCM, and the FPR [44]. This leaves other questions unexplained: the importance of moderating and mediating effects. The study conducted by [32] stressed the need to investigate how GHC supports FPR based on this logic. Thus, our study analyzes whether GIN mediates the relationship between GSCM, GHC, and FPR to further explore this particular research issue and fill a significant knowledge gap. An earlier study demonstrated that GIN is essential for guaranteeing performance results [45]. Hence, our study investigated the novel elements that may enhance FPR, which have been largely overlooked despite the enduring interest of previous researchers. These study gaps prompted us to contribute to the existing body of knowledge by examining GHC, GSCM, GIN, and MEK for the FPR.
The following are the study’s contributions: First, unlike previous research, the current study addresses a gap in the literature by addressing the elements that may influence FPR. According to the authors’ understanding, this is a pioneer study undertaken in a setting of a developing country, as no other research has been conducted in this context under such a novel framework. Second, this research examines the relationship between GHC, GSCM, GIN, MEK, and FPR. The natural resource-based view (RBV) theory underlines the importance of GIN as a mediating and MEK as a moderating component in understanding the FPR’s continuous advancement [46]. Nonetheless, when analyzing FPR, researchers have paid little consideration to these elements. This study thus aimed to account for this oversight, the findings of which may add to and extend earlier research [38,47,48] by suggesting that neither GHC nor GSCM directly impacts FPR. We propose that GHC and GSCM indirectly impact FPR through GIN since GIN acts as a mediator. Moreover, we examined whether MEK moderates the effect of GIN on FPR. This study highlights the complex relationships between GHC, GIN, GSCM, MEK, and FPR.
The remaining sections of this study are as follows: The literature review and the formulation of hypotheses are covered in the Section 2. In Section 3, the technique and research design are described. The findings and analyses are presented in the Section 4. In Section 5, the implications of the study results for policy, the limitations, and recommendations for further research are examined.

2. Review of Literature and Development of Hypotheses

2.1. Natural Resource-Based View Theory

Ref. [46] adopted a different stance from [49] and suggested that an “internally focused” approach to the competition may be insufficient due to the problem of external interactions. In comparison, Ref. [49] acknowledges the obstacles provided by social and natural settings and suggests that a firm’s competitive advantage and strategy are likely anchored in its capacity to facilitate ecologically responsible activities. The previous efforts to connect the quality of the environment with FPR were conceptually proposed by [46], in which natural RBV theory comprises three complementary approaches: (1) pollution prevention that is viewed as a naturalistically ambiguous schedule which can generate a company’s key cost minimizations as its competitiveness; (2) product stewardship, which allows a company to lessen the social and economic costs associated with the product; and (3) a vision statement for environmental sustainability centered on minimizing the firm’s carbon footprint and showing more significant interaction with external stakeholders in manner that can create potential prospects and continue to gain from a stabilized competency development for a sustainable competitive edge.
Based on the natural RBV theory, the resources and competencies of a firm play a crucial role in determining its competitive edge. Moreover, the natural RBV theory is an advanced form of the RBV theory that argues firms may achieve sustainable competitiveness by addressing environmental concerns. According to [46], RBV theory has many drawbacks. It eliminates, for instance, the connection between a firm’s natural surroundings and the organization itself. Previously, this negligence was reasonable, but it is evident that the natural environment is necessary to obtain a competitive advantage. Natural resources and competencies boost firms’ sustainable performance by lowering pollution. In addition, it is argued that pollution control strategies, environmental resources, and the firm’s competencies lead to effective FPR [50]. According to the natural RBV theory, environmental awareness, including of product stewardship, pollution reduction, and environmentalism, may offer enterprises a competitive advantage [46]. In accordance with this perspective, we suggest that GHC can be regarded as an underlying organizational resource and an ever-expanding capacity. According to this perspective, businesses that increase the effect of GHC on GIN and ultimately, their FPR, may gain a competitive advantage that competitors cannot replicate by other means. Additionally, companies may continually raise their FPR by raising their MEK through GIN, GHC, and GSCM.

2.2. Green Human Capital

GHC is “the sum of employees’ pollution prevention or green innovation-related information, competence, expertise, intelligence, inventiveness, and dedication, etc., and is entrenched in people, not firms” [32]. The GHC has been highlighted as a critical component in the implementation of GHRM strategies, and it is considered among the most vital corporate sciences concepts [13]. It has been argued that workers’ proactive environmental skills and competencies contribute significantly to the transition of GHRM [51]. On the other hand, it has been observed that employees’ knowledge and abilities increase when they recognize the corporate commitment to sustainability, which directly leads to employee engagement in the company [52]. Ref. [32] indicated that environmentalism has gained popularity in the contemporary business sector because it attempts to mitigate environmental effects and manage climate change to encourage organizations to generate green products. Moreover, heightened consumer knowledge of environmental concerns has compelled businesses to develop more effective compliance methods by incorporating environmental management to enhance their green marketing and competitiveness. Ref. [53] further stated that GHC assists organizations in adhering to stringent international environmental rules, adds value to the organization, and satisfies customers’ stringent environmental needs. In addition, ref. [32] argued that for organizations to implement an environmental strategy effectively, they must have environmental information that enables them to determine the relevant opportunities for process and product modification. In this approach, GHC reduces the environmental effect and gives organizations a competitive edge by reducing expenses.
GHC is distinctive to each company and offers crucial resources and competencies for manufacturing sector competitiveness, which is difficult to replicate in other businesses. When confronted with environmental constraints, companies may identify opportunities to profit from a better environment by employing proactive measures and strategies regarding environmental concerns [54]. Thus, several researchers have analyzed the elements that impact GHC, including corporate environmental ideals and social considerations. It can speculated that having inadequate GHC is more detrimental than is having limited resources. Education, information, abilities, and training may decrease the disparity between developed and developing nations. Considering the nature of the link between GHC and economic development, it is suggested that GHC plays a crucial role in transforming the financial resilience of a country by fostering investment growth. Diversity in GHC may create diversity in regional development, which can influence the expansion. In addition, it has been emphasized that GHC helps economic progress by fostering the capacity for innovation via increased research and development (R&D) [55]. In addition, several studies have shown that GHC facilitates green growth, enhanced FPR, and the potential for economic growth [44]. Ref. [51] argued that GHC plays a crucial role in a company’s value creation although research on GHC remains scarce. Ref. [37] reported that GHC improves a company’s social, economic, and environmental performance, while Ref. [42] also found there to be a correlation between GHC and FPR.

2.3. Green Innovation

Several academics have voiced diverse opinions on GIN from numerous angles. GIN is defined by [56] as a transformative approach that includes innovative techniques (e.g., manufacturing, construction, procedures, and networks) that provide positive and immediate environmental benefits. Ref. [20] noted that GIN is a breakthrough technique that encompasses the energy saving, pollutant prevention, recycling and reuse, greener product development, and ecological management of a firm. The relevance of the terminologies centers on how stakeholders may adopt GIN in order to promote and achieve business goals without compromising the sustainability of the environment. GIN contributes significantly to the development of sustainable firms and has now been recognized as an essential component for effective FPR [57]. Firms that intend to stay afloat in today’s highly competitive economy must adopt successful GIN approaches. With the proper regulations, businesses may advance while becoming well-known brands [58].

2.4. Green Supply Chain Management

Researchers have advocated GSCM as a feasible method for improving FPR. Whereas the original concept of GSCM may be dated back to as early as the 1990s, the surge in scholarly publications indicates that it gained prominence in 2000 [59]. According to [60], GSCM may be attributed to the environmental stewardship movement of the 1960s. Ref. [61] indicated that from the 1990s, the GSCM concept took conventional shape as a new intellectual pursuit. Over time, the concept of sustainable supply chain management has further developed. Ref. [62] examined the application of ecological ideas to the whole spectrum of the order processing cycle processes. Ref. [63] defined GSCM as combining ecological aspects into interorganizational sustainable SCM techniques, including logistical operations. The notion of GSCM is expansive, and no comprehensive explanation is available. Due to conflicting definitions in the literature, it is difficult to provide a standard explanation of GSCM [64]. Despite discrepancies in descriptions, several common terminologies have been used, such as “green logistics and environmental logistics”, “green buying and procurement”, “supply chain environmental management”, and “sustainable supply network management” [65].

2.5. Managerial Environmental Knowledge

The ever-increasing anxieties concerning the environmental repercussions of commercial activities have rendered environmental sustainability a significant problem. Firm managers and executives may assist in preventing potential environmental issues by adhering to green business practices and standards. The opportunity for MEK may be viewed as a decision between environmental devastation and conservation based on the possible financial rewards. The intellectual framework provides executives and managers a clearer understanding of why they should embrace challenging issues [66]. Intellectual frameworks aid CEOs in sorting through all available evidence and choosing the ideal answer. Environmental management and initiatives are used to encourage GIN to enhance the FPR. Generally, businesses may utilize two core approaches (i.e., monitoring and preventive) to manage sustainability challenges [67]. For example, an organization’s management may lessen or eradicate sustainability hazards by employing the entire firm’s capabilities and skills to generate alternatives to ecological difficulties. In particular, the continued development of current manufacturing units, the introduction of novel manufacturing processes, and the implementation of overall quality management are contributing factors [68]. In this view, the MEK may be either moderate or high. A company with MEK is assumed to be more engaged in ecological issues (e.g., environmental rules and principles) and more creative in developing GIN operations [69]. In contrast, those with a low MEK are considered passive or reactive toward environmental problems.

2.6. Hypotheses Development

2.6.1. Green Human Capital, Firm Performance, and Green Innovation

GHC positively relates to competitiveness [11]. However, researchers believe that GHC may have varying effects on economic sustainability (ranging from strong to weak). Moreover, GHC may have minimal or no influence on the economy’s perseverance. In contrast, additional studies examining the effect of GHC have revealed that GHC is positively connected with the social, environmental, and financial performance of business companies [70]. Numerous studies have examined the relationship between GIN and FPR; however, the research does not link the factors [35]. In this respect, most researchers have demonstrated a connection between GIN and FPR. These comprise empirical studies [71] indicating that an improvement in a firm’s outlook on GIN corresponds to an increase in an FPR. However, a few researchers have reported there to be a negative relationship between GIN and FPR. For example, [28] hypothesized that GIN decreases business financial performance. Similarly, [72] found that the implementation of GIN raises organizational expenditures. In examining the link between GIN and FPR, [73] found that non-GIN firms have stronger FPR than do GIN firms, which did not see an increase in FPR. Given the lack of consensus in the literature regarding the exact contribution of GIN to FPR, this study sought to test the following hypotheses:
GHC is significantly associated with FPR.
GHC is significantly related to GIN.

2.6.2. Green Supply Chain Management, Green Innovation, and Firm Performance

The connection between GSCM and GIN includes supply chain players who may create GIN in reaction to external issues posed by authorities and regulators. The processes of GSCM and GIN are vitally linked, with GSCM exerting a significant and positive effect on GIN [38]. This concept illustrates that GSCM is a significant driver of a company’s GIN. The interaction between GSCM and GIN can help companies considerably by enhancing product development, manufacturing processes, and compliance with environmental regulations [74]. To effectively implement GIN, organizations must rigorously regulate and supervise their suppliers’ attempts to produce eco-friendly resources and fulfill customer demand for eco-friendly products [28].
Integrating GSCM to safeguard the environment may assist businesses in reducing raw material costs and increasing the use of recycled materials, resulting in an enhanced competitive edge and improved FPR. GSCM might promote FPR by facilitating the adoption of enhanced environmental management practices that improve FPR [75]. The study conducted by [76] suggested that GSCM has a positive and considerable impact on FPR, indicating that it can aid organizations in developing competitiveness and enhance financial performance over time. There are difference in company perspectives concerning the use of GSCM methods to improve FPR. This is because firms must comprehend GSCM’s facets in order to implement the process [56] properly. Thus, we hypothesized the following:
GSCM is significantly associated with the FPR.
GSCM has a significant relationship with GIN.

2.6.3. Green Innovation, Managerial Environmental Knowledge, and Firm Performance

GIN is positively associated with organizational success generally. It may enhance output and compensate for rising raw material costs. First, GIN can help to improve current goods and processes for further eco-friendly manufacturing without fundamentally altering them. GIN’s second benefit is to create new and innovative goods and processes [77]. Through GIN, product innovations and procedures can radically transform old systems of production, thus substantially reducing their environmental impact. It can also lead to the development of innovative products and methods that aid in the cleaning, restoration, and establishment of ecologically sustainable societies [78].
GIN and FPR are related since GIN is the technology for creating eco-friendly products that may boost marketing and sales, leading to solid FPR. Gaining market share reflects the efficacy of the FPR and GIN [79]. As per [80], firms that adopt GIN may enhance their FPR by (1) employing reusable products, which saves expenses and boosts profits, and (2) by altering the designs of environmentally friendly goods, which increases profits and revenues. FPR may be measured in financial and nonfinancial terms, with green innovators enjoying a “first-mover benefit” in price competition policy, better brand image, and increased market share perspective [81]. Thus, we developed the following hypothesis:
GIN is significantly related to the FPR.

2.6.4. Managerial Environmental Knowledge as a Moderator

Innovative technologies must have managerial support to be successful. This justification is also acceptable for GIN in sustainable products [16]. Furthermore, [82] reported that the greater the managerial support for GIN is, the greater the ambition of prominent firms to use green technology. Ref. [83] identified MEK as one of the most significant variables in green practices. It may stimulate GIN, hence increasing the competitiveness and productivity of organizations. According to the results of the study by [40], MEK has a significant effect on the inclination to engage in environmentally friendly actions. According to [67], attitudes, beliefs, and norms influence eco-innovation acceptance. However, according to [84], a firm’s MEK and specific proactive steps are intended to develop environmentally friendly and sustainable technologies that may also assist enterprises in improving their FPR. Alternately, an ineffective MEK may lead to a reactive rather than proactive MEK, raising the risk of disasters and leading to a damaged reputation [85]. According to the natural-resources-based paradigm, mitigation, enhanced producer responsibility, and environmental balance are crucial environmental measures that provide firms with a competitive advantage [46]. Considering that MEK may either increase or decrease a firm’s GIN, we proposed that MEK may influence the relationship between GIN and FPR and developed the following hypotheses:
MEK significantly moderates the link between GIN and the FPR.
MEK is significantly related to the FPR.

2.6.5. Green Innovation as a Mediator

Based on their connection to GIN, GHC and GSCM may or may not have a positive relationship with FPR. Although some studies have shown there to be an association between GHC and a company’s social, environmental, and economic performance [86], others have not [87]. These relationships may be weakened due to businesses not using GHC effectively, undermining the connection between GHC and the FPR. Only when GHC enhances GIN (and GIN creates knowledge insights that GHC can absorb) is it possible for GHC to improve FPR. Thus, GIN may serve as a mediator between GHC and FPR. Similarly to GSCM, there may or may not be a significant connection between FPR and GSCM. Numerous researchers have analyzed the impact of GSCM on FPR [88]. Furthermore, additional elements must be incorporated as a mediator to comprehend the relationship between GSCM and the FPR. In this study, GIN is treated as a mediating variable. GIN may indicate a company’s capacity to seek market share, strengthen the economy, establish product links, and enhance the sociocultural environment. By using GIN, enterprises may significantly reduce the environmental impact disputed by third parties while preserving and enhancing their performance [89]. Consequently, the following hypotheses were developed:
GIN significantly mediates the relationship between GHC and the FPR.
GIN significantly mediates the association between GSCM and the FPR.

3. Methodology

3.1. Population and Sampling

We applied the Chinese Big Five Inventory developed by [90] to evaluate the personality traits of the targeted respondents. The questionnaire is supplied as a digital annex. On a five-point Likert scale, one indicates “strongly disagree,” and five indicates “strongly agree” for all questions. Chinese cities can be divided into four groups based on their degrees of economic progress: first tier, second tier, third tier, and fourth tier. First-tier regions are the most economically, socially, and culturally advanced. Second-tier regions are provincial capitals with moderate industrialization. The 3rd tier consists mainly of somewhat developed regions in every province, while the 4th tier consists of national regions. Between January and February 2023, we conducted a comprehensive questionnaire survey in 10 Chinese regions, including Shanghai, Shenzhen, and Beijing (1st tier); Chengdu, Jinan, and Hefei (2nd tier); Xiangfan and Zhongshan (3rd tier); and Xinmin and Changshu (4th tier). These regions were chosen as they represent almost 700 cities in China [91]. A second rationale was that being the world’s leading technical innovation center [92], encouraging innovative techniques in these locations would have significant policy implications for the globe.
Before conducting the research, a pilot study with a smaller sample size was undertaken to ensure that the questionnaire was valid and would collect relevant data [93]. Subsequently, we addressed responders personally [94]. The procedure consisted of two main steps. The first step included the distribution of questionnaires to 1200 participants, who were required to return their responses within one month. Participants were provided with a comprehensive explanation of each aspect of the questionnaire. Participants then completed their surveys within the allotted time frame. A total of 736 valid answers were obtained, representing 61% of the sample size. According to Westland’s formula, our model necessitates a sample size of 536 [95]. Nevertheless, our final sample size (736 respondents) was much greater, indicating that the sample size was sufficient for an empirical investigation. The detailed demography of respondents is shown in Table 1.

3.2. Development of the Questionnaire

We evaluated GHC using seven questions from various past studies [32]. The seven factors for GSCM practices were derived from prior empirical research [30]. Five elements were utilized to evaluate GIN [96]. MEK was assessed using five questions from [97]. Finally, the FPR was examined with four elements drawn from [98].

3.3. Data Analysis

For statistical analysis, the AMOS (version 26) and SPSS (version 26) software packages were applied. The presented hypotheses were investigated using structural equation modeling (SEM). SEM is a comprehensive strategy that provides reliable and valuable data for determining the relationship between multiple variables [99] and has three critical advantages over earlier methods: (i) an accurate estimation of measurement error, (ii) an estimation of latent constructs from observable data, and (iii) a validation of the framework used to evaluate and execute a pattern utilizing data conformity [100]. In particular, the bulk of multivariate approaches implicitly disregards computational error. However, the SEM analyzes independent and dependent variables by considering calculation errors. Owing to its dependability and sturdiness, the approach delivers accurate and distinct results [101].
SEM permits the generation of unique indicator structures for each element and delivers valid conclusions. Also assessed are the inaccuracy areas of the variables tested. Consequently, the link between variables generates trustworthy findings. Moreover, it can analyze complex relationships and several hypotheses by combining mean configurations and group assessments, something other frameworks and prototypes cannot accomplish [102]. Considering the advantages of SEM, it represents the most effective method for assessing the link between all constructs taken into consideration; hence, we employed it in our research.

4. Results

4.1. Statistical Analysis

4.1.1. Descriptive Statistics, Discriminant Validity, and Correlation Analysis

The descriptive information is displayed in Table 2 and includes the mean, standard deviation, and coefficient of variation. Using correlation analysis, the interconnections between variables were examined. The research indicated significant relationships between the factors. We examined the discriminant validity using the square root of the average variance extracted (AVE). Results validated the discriminant validity since the square root of AVE’s correlation with other variables was greater than its relationship with other variables [103]. Comparing the AVE values to the MSV values for each variable is another way to establish discriminant validity. When the AVE values for a construct are larger than its MSV, discriminant validity is established [104]. The fact that the AVE values for all constructions surpassed the MSV values supported these conclusions. In addition, using AVE and item loadings, convergent validity was conducted to investigate the potential relationship between the constructs [105]. AVE values for each component were larger than 0.50, suggesting that the latent constructs maintained greater than 50% variance (see Table 3).

4.1.2. Reliability Analysis

To assess the components’ reliability analysis, Cronbach’s alpha was determined. Cronbach’s alpha values for all variables were more than [106] the recommended threshold value of 0.70, indicating reliability. To establish the consistency of all components, a composite reliability (CR) test was carried out. According to the study results, the CR levels were above the minimum cutoff value of 0.70 [107]. The study’s results are reported in Table 4.

4.1.3. Multicollinearity

To develop the variance inflation factor (VIF) and tolerance values, multicollinearity was investigated using regression. [108] stated that the values of VIF and levels of tolerance must not surpass 10 and 0.1, respectively. The values of tolerance and VIF were under the allowable limits across all components, suggesting that there was no multicollinearity problem with the study’s model. Table 5 summarizes the findings.

4.1.4. Factor Analysis

An EFA was performed to identify the framework of contributing design. EFA studies factor structure, as well as intervariable relationships and variable classifications based on their factor structure [8]. The results were gathered using the maximum likelihood method, which was modified using Promax Kaiser normalization to obtain more pertinent findings. Eigenvalues were critical for defining the constructs’ ordering. Throughout this stage, multiple assessments of the usefulness of EFA data were conducted [109]. For example, the Kaiser–Meyer–Olkin (KMO) test and Bartlett’s test of sphericity (BTS) were used to evaluate the data’s suitability. KMO was determined with a value of 0.907%, suggesting that factor analysis could continue (an index of factorial simplicity). In addition, BTS was a substantial amount, at 6759.03, satisfying the EFA’s standards (see Table 6). Likewise, the Table 7 communalities findings reveal that all elements with values over the minimum given standard of 0.4 were communal [110]. Promax rotation with Kaiser normalization found seven essential aspects with Eigenvalues greater than 1 and a total variance of 659.93% for the framework of this investigation (see Table 8). These findings confirm data reliability, permitting further examination [111].
The model was then determined via a CFA. CFA validates the structure of the retrieved elements under the EFA. The initial step in constructing a paradigm is to evaluate its unidimensionality. Components with significant loadings (greater than 0.7) on the leading indicators should be preserved [112]. Based on the findings, every loading was more than 0.70. Since all elements were assembled into their appropriate structures, the measuring model’s accuracy was also validated (see Figure 1). These results suggest that this investigation’s data correspond well with the measurement model.

4.1.5. Results of the Hypotheses and Structural Model

We analyzed the model’s relationships by employing SEM and covariance-based curve assessment techniques. A high f-value in the research indicated that all connections were linear. Furthermore, numerous fitness tests were undertaken to ensure that the findings were consistent with the structural model. All values of fit index (i.e., CFI = 0.998, NFI = 0.953, IFI = 0.972, TLI = 0.977, GFI = 0.967, RMSEA = 0.033, X2/df = 1.257, and SRMR = 0.033) were in the allowable threshold, suggesting that the conceptual framework sufficiently prepared for the data [113]. The schematic representation of SEM along with the structural paths is shown in Figure 2. The path coefficient of the variables GHC and GSCM did not significantly influence FPR (β = 0.458, β = 0.182). Consequently, we rejected H1 and H3. On the contrary, GHC and GSCM significantly influenced GIN (β = 0.143, p-value = 0.05, β = 0.046, p-value = 0.1). Thus, we accepted H2 and H4. Similarly, GIN significantly influenced FPR (β = 0.073, p-value = 0.1); therefore, H5 was accepted. MEK significantly moderated the association between GIN and ENP. Thus, H6 was accepted. MEK also significantly influenced FPR, confirming H7. The mediation effect of GIN between the relationships of GHC → FPR and GSCM → FPR was also estimated. Estimations revealed full mediation (β = 0.157, p-value = 0.01) and (β = 0.036, p-value = 0.01), respectively. As a result, H8 and H9 were also accepted. Table 9 represents hypothesized paths and the hypotheses’ validity.

5. Discussion and Conclusions

Based on the natural RBV theory, corporations must seek competitiveness through pollution reduction programs, increased manufacturer awareness, and sustainable growth [46]. To reinforce this position, we assessed the significance of MEK in supporting a company in enhancing its FPR. In addition, researchers have shown that MEK increases FPR and that the relationship between GHC, GSCM, and FPR may be modified and mediated by several variables [114]. According to prior research, MEK’s impact could consist of reduced CO2 emission and contributing to healthy ecosystems, improving FPR [115]. This study indicates that MEK can increase an FPR while attenuating the link between GIN and FPR.
In addition, we demonstrate that GHC and GSCM are not directly tied to FPR. This finding was evaluated from the perspective of the proposed reassessment of the relationship between GHC, GSCM, and GIN. We argue that GHC and GSCM do not always directly lead to the FPR of a sustainable firm. Nonetheless, these factors impact the FPR via the GIN as a mediator. GSCM may not have a direct relationship with FPR, notwithstanding its importance. [89] stated that firms should be strongly motivated to use GSCM and GIN to enhance their reputation, efficacy, productivity, differentiation, and competitiveness, Table 10 represents the comparison studies.
In addition, this research established a link between GSCM and the FPR mediated by GIN. This finding was then supported by the results of other experts, including [28]. This research analyzed the hypothesis that increasing GSCM may increase GIN and FPR. MEK has compelled companies to place a greater emphasis on GSCM, GHC, and GIN, forcing them to be environmentally responsible. Simultaneously, conscientiously buying eco-friendly components and raw materials and implementing GIN can increase FPR. Nevertheless, companies actively involved in GIN have a substantial influence on the environment. As proven throughout this study, GIN may thus serve as a mediator when examining the effect of GHC and GSCM on FPR.

5.1. Theoretical Implications

This research expands upon the concept of MEK by using GHC, GSCM, and GIN. In general, it is essential to note that GHC and GIN engage in a dynamic interplay. The only way for GHC to grow is for a company to actively commit to GIN. This dedication helps businesses to continually improve GHC. Upon GIN’s incorporation into GHC, a business may become more efficient and focused. Constantly improved GHC may encourage new and inventive cycles, hence enhancing GIN’s benefits. Ultimately, this continual interaction may have a substantial effect on FPR. Similarly, GSCM is abstractly related to GIN. Through the use of GIN, GSCM practices may increase their impact on FPR.
In addition, this study represents a significant theoretical development in the academic and research domains related to the natural RBV theory. This idea emphasizes the concentration and volatility of resources and skills inside organizations. They are thought to have a direct relationship with the firm’s efficiency and competitive advantage [46]. The finding implies that manufacturing companies in developing countries with increased GSCM and GHC may enhance their FPR by using GIN. Successful implementation ofGSCM practices in a production line may extend the understanding of how manufacturing organizations may use GHC, GSCM, GIN, and MEK to enhance their FPR.

5.2. Practical Implications

This research has numerous practical implications, especially for legislators and firm leaders. Our study’s suggested framework consists of leveraging the influence of GHC and GSCM on FPR by mediating the influence of GIN and moderating the impact of MEK. Hence, it provides a roadmap for manufacturing firms to enhance their FPR. Because of the increased attention being paid to GSCM recently, using this paradigm in developing countries’ manufacturing firms may assist a firm in raising its quality and clean productivity and preserving its manufacturing competitiveness. Persistent efforts must be made by businesses to refresh and improve their GHC. When a firm’s GHC yields GIN, it might gain an advantage over competitors. In this manner, GHC is a secret source and has the dynamic potential to continually evolve in response. Managers and executives of manufacturing firms must not limit themselves to GIN initiatives that improve existing sustainable and environmental products and processes. In an era of environmental concern, manufacturers should have an eco-friendly business and market structure. However, it should be kept in mind that implementing eco-friendly practices alone may not automatically increase FPR. They must encourage GIN to reduce the negative environmental impact of their activities and meet the needs of greener consumers and stakeholders.
Consequently, our research recommends that manufacturing firms should adopt GHC and GSCM and participate in GIN to enhance FPR. Environmental consequences have become a worldwide concern requiring considerable attention. In addition, this study offers a clear roadmap for manufacturing regulators and leaders to improve their FPR and environmental sustainability with several positive externalities. The manufacturing industry is a substantial contributor to environmental contamination in developing countries. The concepts and conclusions in this paper may help convince legislators and upper management of the importance of enhanced FPR via GHC, GSCM, MEK, and GIN. Therefore, when manufacturing firms embrace this strategy, the community will gain from eco-friendly products, higher resource efficiency, and enhanced life satisfaction. To retain their GHC, managers need to make a determined commitment to engage in and develop effective information systems. Managers should concurrently create proactive environmental strategies incorporating ecological security features including GSCM, GHC, MEK, and GIN. People are committed to accomplishing environmental goals when firms have excellent environmental programs.

5.3. Conclusions

This study employed the natural RBV theory to understand how GHC, GSCM, MEK, and GIN might improve FPR in the manufacturing companies of developing countries. It was shown that GIN mediates the links between GHC, GSCM, and the FPR. In particular, MEK has a moderating effect on a firm’s GIN and FPR. The findings demonstrate that managers in developing economies should assign the highest weight to GHC, GSCM, MEK, and GIN. They should enhance their GHC and GSCM investments. This study further identified a mediating link between GIN, GHC, and GSCM and highlights the importance of these factors for FPR. The mediating influence of GIN and the moderating effect of MEK were validated using SEM. In particular, developing countries’ manufacturing firms are less advanced and capable at applying GHC and GSCM than are their rivals in industrialized countries. Many manufacturing firms are subject to harsh environmental regulations that the government and domestic and foreign customers enforce. As a result, GHC and GSCM have been used exclusively to meet consumers’ wishes, demands, and expectations because they are regarded as quick solutions to these problems.

5.4. Limitations and Future Directions

There were several limitations to this research. These findings offer valuable general information; however, the surveyed regions may restrict the generalization of the research’s conclusions since the data were taken only one developing country i.e., China and many other developing countries were omitted from the survey owing to the low economic and population growth. In order to allow for greater generalization, it is necessary to incorporate other developing countries in future research. Moreover, in this study, we made no distinction between exploitative and exploratory GIN. The relationship between exploitative and exploratory GIN and FPR may be unique. Therefore, future research should differentiate between the two types of GIN. Furthermore, the study was cross-sectional as opposed to longitudinal. Cross-sectional examinations of a sequence of dynamical notions (e.g., GHC, GSCM, GIN, and MEK) include an assessment at a single point in time instead of the overall behavior throughout a period. Thus, the cause–effect relationships could not be identified. In future research, the significance of green culture, green organizational commitment, and green organizational strategy may be examined as moderators of the relationship between GSCM, GHC, and FPR.

Author Contributions

Conceptualization, N.N.; data curation, D.L., M.I. and U.A.; formal analysis, M.M. and M.I.; funding acquisition, M.I.; supervision, M.I. and D.L.; validation, M.I.; software, M.I.; visualization, U.A. and N.N.; writing—original draft, N.N.; writing—review and editing, M.I. and M.M. All authors have read and agreed to the published version of the manuscript.


This research received no external funding.

Institutional Review Board Statement

This study followed the Helsinki Declaration guidelines and was approved by the North China Electric Power University’s Institutional Review Board (protocol code 019924 dated 18 April 2022).

Informed Consent Statement

Informed consent was obtained from all participants involved in the study.

Data Availability Statement

The data will be made available on reasonable request from the corresponding author.

Conflicts of Interest

The authors have no conflict of interest.


  1. Awan, U. Effects of Buyer-Supplier Relationship on Social Performance Improvement and Innovation Performance Improvement. Int. J. Appl. Manag. Sci. 2019, 11, 21. [Google Scholar] [CrossRef]
  2. He, P.; Shang, Y.; Ajaz, T.; Nureen, N.; Sukstan, W. Assessment of Critical Factors Influencing Consumers’ Acceptance of Wearable Sports Devices During COVID-19 Pandemic Conditions. Front. Energy Res. 2022, 10, 877260. [Google Scholar] [CrossRef]
  3. Sharif, A.; Raza, S.A.; Ozturk, I.; Afshan, S. The Dynamic Relationship of Renewable and Nonrenewable Energy Consumption with Carbon Emission: A Global Study with the Application of Heterogeneous Panel Estimations. Renew. Energy 2019, 133, 685–691. [Google Scholar] [CrossRef]
  4. Hao, Y.; Ba, N.; Ren, S.; Wu, H. How Does International Technology Spillover Affect China’s Carbon Emissions? A New Perspective Through Intellectual Property Protection. Sustain. Prod. Consum. 2021, 25, 577–590. [Google Scholar] [CrossRef]
  5. Nureen, N.; Liu, D.; Ahmad, B.; Irfan, M. Relating Green Information Acquisition, Absorptive Capacity, Institutional Pressure, and Firm Performance: An Environmentally Sustainable Perspective. Environ. Sci. Pollut. Res. 2023, 1–16. [Google Scholar] [CrossRef] [PubMed]
  6. Huang, W.; Chau, K.Y.; Kit, I.Y.; Nureen, N.; Irfan, M.; Dilanchiev, A. Relating Sustainable Business Development Practices and Information Management in Promoting Digital Green Innovation: Evidence from China. Front. Psychol. 2022, 13, 930138. [Google Scholar] [CrossRef]
  7. Ren, S.; Hao, Y.; Xu, L.; Wu, H.; Ba, N. Digitalization and Energy: How Does Internet Development Affect China’s Energy Consumption? Energy Econ. 2021, 98, 105220. [Google Scholar] [CrossRef]
  8. Rauf, A.; Nureen, N.; Irfan, M.; Ali, M. The Current Developments and Future Prospects of Solar Photovoltaic Industry in an Emerging Economy of India. Environ. Sci. Pollut. Res. 2023, 1–12. [Google Scholar] [CrossRef]
  9. Wu, H.; Xu, L.; Ren, S.; Hao, Y.; Yan, G. How Do Energy Consumption and Environmental Regulation Affect Carbon Emissions in China? New Evidence from a Dynamic Threshold Panel Model. Resour. Policy 2020, 67, 101678. [Google Scholar] [CrossRef]
  10. Wu, R.; Huo, B.; Yu, Y.; Zhang, Z. Quality and Green Management for Operational and Environmental Performance: Relational Capital in Supply Chain Management. Int. J. Logist. Res. Appl. 2022, 25, 471–492. [Google Scholar] [CrossRef]
  11. Chen, Y.S. The Driver of Green Innovation and Green Image—Green Core Competence. J. Bus. Ethics 2008, 81, 531–543. [Google Scholar] [CrossRef]
  12. Saudi, M.H.M.; Sinaga, O.; Gusni; Zainudin, Z. The Effect of Green Innovation in Influencing Sustainable Performance: Moderating Role of Managerial Environmental Concern. Int. J. Supply Chain Manag. 2019, 8, 303–310. [Google Scholar]
  13. Chen, Y.S.; Chang, C.H. Utilize Structural Equation Modeling (SEM) to Explore the Influence of Corporate Environmental Ethics: The Mediation Effect of Green Human Capital. Qual. Quant. 2013, 47, 79–95. [Google Scholar] [CrossRef]
  14. Yong, J.Y.; Yusliza, M.Y.; Ramayah, T.; Farooq, K.; Tanveer, M.I. Accentuating the Interconnection between Green Intellectual Capital, Green Human Resource Management and Sustainability. Benchmarking 2022. ahead-of-print. [Google Scholar] [CrossRef]
  15. Wang, C.H.; Juo, W.J. An Environmental Policy of Green Intellectual Capital: Green Innovation Strategy for Performance Sustainability. Bus. Strateg. Environ. 2021, 30, 3241–3254. [Google Scholar] [CrossRef]
  16. Song, W.; Yu, H.; Xu, H. Effects of Green Human Resource Management and Managerial Environmental Concern on Green Innovation. Eur. J. Innov. Manag. 2020, 24, 951–967. [Google Scholar] [CrossRef]
  17. Song, W.; Yu, H. Green Innovation Strategy and Green Innovation: The Roles of Green Creativity and Green Organizational Identity. Corp. Soc. Responsib. Environ. Manag. 2018, 25, 135–150. [Google Scholar] [CrossRef]
  18. Owen, R.; Brennan, G.; Lyon, F. Enabling Investment for the Transition to a Low Carbon Economy: Government Policy to Finance Early Stage Green Innovation. Curr. Opin. Environ. Sustain. 2018, 31, 137–145. [Google Scholar] [CrossRef]
  19. Huang, J.W.; Li, Y.H. Green Innovation and Performance: The View of Organizational Capability and Social Reciprocity. J. Bus. Ethics 2017, 145, 309–324. [Google Scholar] [CrossRef]
  20. Shahzad, M.; Qu, Y.; Zafar, A.U.; Ding, X.; Rehman, S.U. Translating Stakeholders’ Pressure into Environmental Practices—The Mediating Role of Knowledge Management. J. Clean. Prod. 2020, 275, 124163. [Google Scholar] [CrossRef]
  21. Chen, Y.S.; Lai, S.B.; Wen, C.T. The Influence of Green Innovation Performance on Corporate Advantage in Taiwan. J. Bus. Ethics 2006, 67, 331–339. [Google Scholar] [CrossRef]
  22. Awan, U.; Khattak, A.; Kraslawski, A. Corporate Social Responsibility (CSR) Priorities in the Small and Medium Enterprises (SMEs) of the Industrial Sector of Sialkot, Pakistan. In Corporate Social Responsibility in the Manufacturing and Services Sectors; Springer: Berlin/Heidelberg, Germany, 2019; pp. 267–278. [Google Scholar] [CrossRef]
  23. Guo, J.; Zhou, Y.; Ali, S.; Shahzad, U.; Cui, L. Exploring the Role of Green Innovation and Investment in Energy for Environmental Quality: An Empirical Appraisal from Provincial Data of China. J. Environ. Manag. 2021, 292, 112779. [Google Scholar] [CrossRef] [PubMed]
  24. Awan, U.; Kraslawski, A.; Huiskonen, J. The Impact of Relational Governance on Performance Improvement in Export Manufacturing Firms. J. Ind. Eng. Manag. 2018, 11, 349–370. [Google Scholar] [CrossRef][Green Version]
  25. Khan, S.A.R.; Sharif, A.; Golpîra, H.; Kumar, A. A Green Ideology in Asian Emerging Economies: From Environmental Policy and Sustainable Development. Sustain. Dev. 2019, 27, 1063–1075. [Google Scholar] [CrossRef]
  26. Khan, S.A.R.; Yu, Z.; Golpira, H.; Sharif, A.; Mardani, A. A State-of-the-Art Review and Meta-Analysis on Sustainable Supply Chain Management: Future Research Directions. J. Clean. Prod. 2021, 278, 123357. [Google Scholar] [CrossRef]
  27. Awan, U.; Kraslawski, A.; Huiskonen, J. Understanding the Relationship between Stakeholder Pressure and Sustainability Performance in Manufacturing Firms in Pakistan. Procedia Manuf. 2017, 11, 768–777. [Google Scholar] [CrossRef]
  28. Abu Seman, N.A.; Govindan, K.; Mardani, A.; Zakuan, N.; Mat Saman, M.Z.; Hooker, R.E.; Ozkul, S. The Mediating Effect of Green Innovation on the Relationship between Green Supply Chain Management and Environmental Performance. J. Clean. Prod. 2019, 229, 115–127. [Google Scholar] [CrossRef]
  29. Suki, N.M.; Sharif, A.; Afshan, S.; Suki, N.M. Revisiting the Environmental Kuznets Curve in Malaysia: The Role of Globalization in Sustainable Environment. J. Clean. Prod. 2020, 264, 121669. [Google Scholar] [CrossRef]
  30. Nureen, N.; Liu, D.; Ahmad, B.; Irfan, M. Exploring the Technical and Behavioral Dimensions of Green Supply Chain Management: A Roadmap toward Environmental Sustainability. Environ. Sci. Pollut. Res. 2022, 29, 63444–63457. [Google Scholar] [CrossRef]
  31. Akhtar, R.; AdeelAkhtar, G.G.R.; Ilyas, S. Analysis of Green Supply Chain Management Practices, Institutional Pressures and Environmental Performance: Evidence from Pakistani Pesticide Firms. Compet. Soc. Sci. 2022, 3, 657–674. [Google Scholar]
  32. Chen, Y.S. The Positive Effect of Green Intellectual Capital on Competitive Advantages of Firms. J. Bus. Ethics 2008, 77, 271–286. [Google Scholar] [CrossRef]
  33. Munawar, S.; Yousaf, D.H.Q.; Ahmed, M.; Rehman, D.S. Effects of Green Human Resource Management on Green Innovation through Green Human Capital, Environmental Knowledge, and Managerial Environmental Concern. J. Hosp. Tour. Manag. 2022, 52, 141–150. [Google Scholar] [CrossRef]
  34. Liu, J.; Liu, Y.; Yang, L. Uncovering the Influence Mechanism between Top Management Support and Green Procurement: The Effect of Green Training. J. Clean. Prod. 2020, 251, 119674. [Google Scholar] [CrossRef]
  35. Yong, J.Y.; Yusliza, M.Y.; Fawehinmi, O.O. Green Human Resource Management: A Systematic Literature Review from 2007 to 2019. Benchmarking 2020, 27, 2005–2027. [Google Scholar] [CrossRef]
  36. Andersén, J. A Relational Natural-Resource-Based View on Product Innovation: The Influence of Green Product Innovation and Green Suppliers on Differentiation Advantage in Small Manufacturing Firms. Technovation 2021, 104, 102254. [Google Scholar] [CrossRef]
  37. Yusoff, Y.M.; Omar, M.K.; Kamarul Zaman, M.D.; Samad, S. Do All Elements of Green Intellectual Capital Contribute toward Business Sustainability? Evidence from the Malaysian Context Using the Partial Least Squares Method. J. Clean. Prod. 2019, 234, 626–637. [Google Scholar] [CrossRef]
  38. Novitasari, M.; Agustia, D. Green Supply Chain Management and Firm Performance: The Mediating Effect of Green Innovation. J. Ind. Eng. Manag. 2021, 14, 391–403. [Google Scholar] [CrossRef]
  39. Chu, S.H.; Yang, H.; Lee, M.; Park, S. The Impact of Institutional Pressures on Green Supply Chain Management and Firm Performance: Top Management Roles and Social Capital. Sustainability 2017, 9, 764. [Google Scholar] [CrossRef][Green Version]
  40. Liu, P.; Teng, M.; Han, C. How Does Environmental Knowledge Translate into Pro-Environmental Behaviors?: The Mediating Role of Environmental Attitudes and Behavioral Intentions. Sci. Total Environ. 2020, 728, 138126. [Google Scholar] [CrossRef] [PubMed]
  41. Shoaib, M.; Abbas, Z.; Yousaf, M.; Zámečník, R.; Ahmed, J.; Saqib, S. The Role of GHRM Practices towards Organizational Commitment: A Mediation Analysis of Green Human Capital. Cogent Bus. Manag. 2021, 8, 1870798. [Google Scholar] [CrossRef]
  42. Yusliza, M.Y.; Yong, J.Y.; Tanveer, M.I.; Ramayah, T.; Noor Faezah, J.; Muhammad, Z. A Structural Model of the Impact of Green Intellectual Capital on Sustainable Performance. J. Clean. Prod. 2020, 249, 119334. [Google Scholar] [CrossRef]
  43. Syahidun, S.; Nawangsari, L.C. Role of Green Human Capital on Company Sustainability Based on Study at Pertamina Rewulu Fuel Terminal. Linguist. Cult. Rev. 2022, 6, 711–719. [Google Scholar] [CrossRef]
  44. Agyabeng-Mensah, Y.; Tang, L. The Relationship among Green Human Capital, Green Logistics Practices, Green Competitiveness, Social Performance and Financial Performance. J. Manuf. Technol. Manag. 2021, 32, 1377–1398. [Google Scholar] [CrossRef]
  45. Tang, M.; Walsh, G.; Lerner, D.; Fitza, M.A.; Li, Q. Green Innovation, Managerial Concern and Firm Performance: An Empirical Study. Bus. Strateg. Environ. 2018, 27, 39–51. [Google Scholar] [CrossRef]
  46. Hart, S.L. A Natural-Resource-Based View of the Firm. Corp. Environ. Responsib. 1995, 20, 986–1014. [Google Scholar] [CrossRef][Green Version]
  47. Yusoff, Y.M.; Nejati, M.; Kee, D.M.H.; Amran, A. Linking Green Human Resource Management Practices to Environmental Performance in Hotel Industry. Glob. Bus. Rev. 2020, 21, 663–680. [Google Scholar] [CrossRef]
  48. Rehman, S.U.; Kraus, S.; Shah, S.A.; Khanin, D.; Mahto, R.V. Analyzing the Relationship between Green Innovation and Environmental Performance in Large Manufacturing Firms. Technol. Forecast. Soc. Chang. 2021, 163, 120481. [Google Scholar] [CrossRef]
  49. Barney, J. Firm Resources and Competitive Advantage. J. Manag. 1991, 17, 99–120. [Google Scholar]
  50. Barney, J.B. Firm Resources and Sustained Competitive Advantage. Adv. Strateg. Manag. 2000, 17, 203–227. [Google Scholar] [CrossRef]
  51. Yong, J.Y.; Yusliza, M.Y.; Ramayah, T.; Fawehinmi, O. Nexus between Green Intellectual Capital and Green Human Resource Management. J. Clean. Prod. 2019, 215, 364–374. [Google Scholar] [CrossRef]
  52. Tjahjadi, B.; Agastya, I.B.G.A.; Soewarno, N.; Adyantari, A. Green Human Capital Readiness and Business Performance: Do Green Market Orientation and Green Supply Chain Management Matter? Benchmarking, 2022; ahead-of-print. [Google Scholar] [CrossRef]
  53. Zhao, W.; Huang, L. The Impact of Green Transformational Leadership, Green HRM, Green Innovation and Organizational Support on the Sustainable Business Performance: Evidence from China. Econ. Res. Istraz. 2022, 35, 6121–6141. [Google Scholar] [CrossRef]
  54. Chen, Y.S.; Chang, C.H. The Determinants of Green Product Development Performance: Green Dynamic Capabilities, Green Transformational Leadership, and Green Creativity. J. Bus. Ethics 2013, 116, 107–119. [Google Scholar] [CrossRef]
  55. Khan, Z.; Hossain, M.R.; Badeeb, R.A.; Zhang, C. Aggregate and Disaggregate Impact of Natural Resources on Economic Performance: Role of Green Growth and Human Capital. Resour. Policy 2022, 80, 103103. [Google Scholar] [CrossRef]
  56. Singh, S.K.; Giudice, M.D.; Chierici, R.; Graziano, D. Green Innovation and Environmental Performance: The Role of Green Transformational Leadership and Green Human Resource Management. Technol. Forecast. Soc. Chang. 2020, 150, 119762. [Google Scholar] [CrossRef]
  57. Abbas, J.; Sağsan, M. Impact of Knowledge Management Practices on Green Innovation and Corporate Sustainable Development: A Structural Analysis. J. Clean. Prod. 2019, 229, 611–620. [Google Scholar] [CrossRef]
  58. Zhang, D.; Rong, Z.; Ji, Q. Green Innovation and Firm Performance: Evidence from Listed Companies in China. Resour. Conserv. Recycl. 2019, 144, 48–55. [Google Scholar] [CrossRef]
  59. Samad, S.; Nilashi, M.; Almulihi, A.; Alrizq, M.; Alghamdi, A.; Mohd, S.; Ahmadi, H.; Syed Azhar, S.N.F. Green Supply Chain Management Practices and Impact on Firm Performance: The Moderating Effect of Collaborative Capability. Technol. Soc. 2021, 67, 101766. [Google Scholar] [CrossRef]
  60. Bag, S.; Gupta, S.; Kumar, S.; Sivarajah, U. Role of Technological Dimensions of Green Supply Chain Management Practices on Firm Performance. J. Enterp. Inf. Manag. 2020, 34, 1–27. [Google Scholar] [CrossRef]
  61. Dubey, R.; Gunasekaran, A.; Papadopoulos, T. Green Supply Chain Management: Theoretical Framework and Further Research Directions. Benchmarking 2017, 24, 184–218. [Google Scholar] [CrossRef]
  62. Habib, M.A.; Bao, Y.; Nabi, N.; Dulal, M.; Asha, A.A.; Islam, M. Impact of Strategic Orientations on the Implementation of Green Supply Chain Management Practices and Sustainable Firm Performance. Sustainability 2021, 13, 340. [Google Scholar] [CrossRef]
  63. Bu, X.; Dang, W.V.T.; Wang, J.; Liu, Q. Environmental Orientation, Green Supply Chain Management, and Firm Performance: Empirical Evidence from Chinese Small and Medium-Sized Enterprises. Int. J. Environ. Res. Public Health 2020, 17, 1199. [Google Scholar] [CrossRef][Green Version]
  64. Schmidt, C.G.; Foerstl, K.; Schaltenbrand, B. The Supply Chain Position Paradox: Green Practices and Firm Performance. J. Supply Chain Manag. 2017, 53, 3–25. [Google Scholar] [CrossRef]
  65. Tarigan, Z.J.H.; Siagian, H.; Jie, F. Impact of Enhanced Enterprise Resource Planning (ERP) on Firm Performance through Green Supply Chain Management. Sustainability 2021, 13, 4358. [Google Scholar] [CrossRef]
  66. Naz, S.; Jamshed, S.; Nisar, Q.A.; Nasir, N. Green HRM, Psychological Green Climate and pro-Environmental Behaviors: An Efficacious Drive towards Environmental Performance in China. In Key Topics in Health, Nature, and Behavior; Springer Nature: Cham, Switzerland, 2022; pp. 95–110. [Google Scholar] [CrossRef]
  67. Fawehinmi, O.; Yusliza, M.Y.; Mohamad, Z.; Noor Faezah, J.; Muhammad, Z. Assessing the Green Behaviour of Academics: The Role of Green Human Resource Management and Environmental Knowledge. Int. J. Manpow. 2020, 41, 879–900. [Google Scholar] [CrossRef]
  68. Amoako, G.K.; Dzogbenuku, R.K.; Abubakari, A. Do Green Knowledge and Attitude Influence the Youth’s Green Purchasing? Theory of Planned Behavior. Int. J. Product. Perform. Manag. 2020, 69, 1609–1626. [Google Scholar] [CrossRef]
  69. Issock Issock, P.B.; Mpinganjira, M.; Roberts-Lombard, M. Modelling Green Customer Loyalty and Positive Word of Mouth: Can Environmental Knowledge Make the Difference in an Emerging Market? Int. J. Emerg. Mark. 2020, 15, 405–426. [Google Scholar] [CrossRef]
  70. Ahmed, L.; Nasir, A.; Nasir, A.; Bakhtawar, A. The Influence of Green Human Capital and Green Abilities on Employee Green Behavior with Moderating Role of Green Knowledge Sharing: A Conceptual Study. S. Asian J. Soc. Sci. Humanit. 2021, 2, 1–12. [Google Scholar] [CrossRef]
  71. Li, D.; Zheng, M.; Cao, C.; Chen, X.; Ren, S.; Huang, M. The Impact of Legitimacy Pressure and Corporate Profitability on Green Innovation: Evidence from China Top 100. J. Clean. Prod. 2017, 141, 41–49. [Google Scholar] [CrossRef][Green Version]
  72. Kraus, S.; Rehman, S.U.; García, F.J.S. Corporate Social Responsibility and Environmental Performance: The Mediating Role of Environmental Strategy and Green Innovation. Technol. Forecast. Soc. Chang. 2020, 160, 120262. [Google Scholar] [CrossRef]
  73. El-Kassar, A.N.; Singh, S.K. Green Innovation and Organizational Performance: The Influence of Big Data and the Moderating Role of Management Commitment and HR Practices. Technol. Forecast. Soc. Chang. 2019, 144, 483–498. [Google Scholar] [CrossRef]
  74. Le, T.T.; Vo, X.V.; Venkatesh, V.G. Role of Green Innovation and Supply Chain Management in Driving Sustainable Corporate Performance. J. Clean. Prod. 2022, 374, 133875. [Google Scholar] [CrossRef]
  75. Chu, Z.; Xu, J.; Lai, F.; Collins, B.J. Institutional Theory and Environmental Pressures: The Moderating Effect of Market Uncertainty on Innovation and Firm Performance. IEEE Trans. Eng. Manag. 2018, 65, 392–403. [Google Scholar] [CrossRef]
  76. Shafique, M.; Asghar, M.; Rahman, H. The Impact of Green Supply Chain Management Practices on Performance: Moderating Role of Institutional Pressure with Mediating Effect of Green Innovation. Bus. Manag. Educ. 2017, 15, 91–108. [Google Scholar] [CrossRef][Green Version]
  77. Bag, S.; Dhamija, P.; Bryde, D.J.; Singh, R.K. Effect of Eco-Innovation on Green Supply Chain Management, Circular Economy Capability, and Performance of Small and Medium Enterprises. J. Bus. Res. 2022, 141, 60–72. [Google Scholar] [CrossRef]
  78. Khan, K.I.; Babar, Z.; Sharif, S.; Iqbal, S.; Khan, M.I. Going Green? Investigating the Role of GSCM Practices on Firm Financial and Environmental Performance through Green Innovation. Int. J. Procure. Manag. 2021, 14, 681–701. [Google Scholar] [CrossRef]
  79. Purwanto, A.; Fahmi, K.; Irwansyah, I.; Hadinegoro, R.; Rochmad, I.; Syahril, S.; Sulastri, E. The Role of Green Innovation and Green Supply Chain Management on the Sustainability of the Performance of SMEs. J. Futur. Sustain. 2022, 2, 49–52. [Google Scholar] [CrossRef]
  80. Burki, U. Green Supply Chain Management, Green Innovations, and Green Practices. In Innovative Solutions for Sustainable Supply Chains. Understanding Complex Systems; Qudrat-Ullah, H., Ed.; Springer: Cham, Switzerland, 2018; pp. 81–109. [Google Scholar] [CrossRef]
  81. Yusr, M.M.; Salimon, M.G.; Mokhtar, S.S.M.; Abaid, W.M.A.W.; Shaari, H.; Perumal, S.; Saoula, O. Green Innovation Performance! How to Be Achieved? A Study Applied on Malaysian Manufacturing Sector. Sustain. Futur. 2020, 2, 100040. [Google Scholar] [CrossRef]
  82. Xue, M.; Boadu, F.; Xie, Y. The Penetration of Green Innovation on Firm Performance: Effects of Absorptive Capacity and Managerial Environmental Concern. Sustainability 2019, 11, 2455. [Google Scholar] [CrossRef][Green Version]
  83. Paço, A.; Lavrador, T. Environmental Knowledge and Attitudes and Behaviours towards Energy Consumption. J. Environ. Manag. 2017, 197, 384–392. [Google Scholar] [CrossRef]
  84. Grafman, J. Plans, Actions, and Mental Sets: Managerial Knowledge Units in the Frontal Lobes. Psychol. Libr. Ed. Neuropsychol. 2021, 10–12, 93–138. [Google Scholar]
  85. Debora Indriani, I.A.; Rahayu, M.; Hadiwidjojo, D. The Influence of Environmental Knowledge on Green Purchase Intention the Role of Attitude as Mediating Variable. Int. J. Multicult. Multireligious Underst. 2019, 6, 627. [Google Scholar] [CrossRef]
  86. Aboelmaged, M.; Hashem, G. Absorptive Capacity and Green Innovation Adoption in SMEs: The Mediating Effects of Sustainable Organisational Capabilities. J. Clean. Prod. 2019, 220, 853–863. [Google Scholar] [CrossRef]
  87. Ma, X.; Ock, Y.S.; Wu, F.; Zhang, Z. The Effect of Internal Control on Green Innovation: Corporate Environmental Investment as a Mediator. Sustainability 2022, 14, 1755. [Google Scholar] [CrossRef]
  88. Imran, M.; Arshad, I.; Ismail, F. Green Organizational Culture and Organizational Performance: The Mediating Role of Green Innovation and Environmental Performance. J. Pendidik. IPA Indones. 2021, 10, 515–530. [Google Scholar] [CrossRef]
  89. Roh, T.; Noh, J.; Oh, Y.; Park, K.S. Structural Relationships of a Firm’s Green Strategies for Environmental Performance: The Roles of Green Supply Chain Management and Green Marketing Innovation. J. Clean. Prod. 2022, 356, 131877. [Google Scholar] [CrossRef]
  90. Wang, M.; Dai, X.; Yao, S. Development of the Chinese Big Five Personality Inventory (CBF-PI) III: Psychometric Properties of CBF-PI Brief Version. Chin. J. Clin. Psychol. 2011, 19, 454–457. [Google Scholar]
  91. Hao, Y.; Dong, X.Y.; Deng, Y.X.; Li, L.X.; Ma, Y. What Influences Personal Purchases of New Energy Vehicles in China? An Empirical Study Based on a Survey of Chinese Citizens. J. Renew. Sustain. Energy 2016, 8, 065904. [Google Scholar] [CrossRef]
  92. KMPG. Technology Innovation Hubs. 2020. Available online: (accessed on 13 March 2023).
  93. Ahmad, B.; Akbar, M.I.u.D.; Asif, M.H.; Nureen, N. An Investigation of Sales Managers’ Aggressiveness in B2B Sales Leadership: The Sequential Mediation Model of Emotional Exhaustion and Adaptive Selling. Manag. Sci. Lett. 2021, 11, 2243–2254. [Google Scholar] [CrossRef]
  94. Reuter, K.E.; Schaefer, M.S. Illegal Captive Lemurs in Madagascar: Comparing the Use of Online and in-Person Data Collection Methods. Am. J. Primatol. 2017, 79, 22541. [Google Scholar] [CrossRef]
  95. Westland, J.C. Lower Bounds on Sample Size in Structural Equation Modeling. Electron. Commer. Res. Appl. 2010, 9, 476–487. [Google Scholar] [CrossRef]
  96. Zhang, Y.; Sun, J.; Yang, Z.; Wang, Y. Critical Success Factors of Green Innovation: Technology, Organization and Environment Readiness. J. Clean. Prod. 2020, 264, 121701. [Google Scholar] [CrossRef]
  97. Sreen, N.; Dhir, A.; Talwar, S.; Tan, T.M.; Alharbi, F. Behavioral Reasoning Perspectives to Brand Love toward Natural Products: Moderating Role of Environmental Concern and Household Size. J. Retail. Consum. Serv. 2021, 61, 102549. [Google Scholar] [CrossRef]
  98. Su, X.; Xu, A.; Lin, W.; Chen, Y.; Liu, S.; Xu, W. Environmental Leadership, Green Innovation Practices, Environmental Knowledge Learning, and Firm Performance. Sage Open 2020, 10, 2158244020922909. [Google Scholar] [CrossRef]
  99. Steenkamp, J.E.M.; Baumgartner, H. On the Use of Structural Equation Models for Marketing Modeling. Int. J. Res. Mark. 2000, 17, 195–202. [Google Scholar] [CrossRef]
  100. Novikova, S.I.; Richman, D.M.; Supekar, K.; Barnard-Brak, L.; Hall, D. NDAR: A Model Federal System for Secondary Analysis in Developmental Disabilities Research, 1st ed.; Elsevier Inc.: Amsterdam, The Netherlands, 2013; Volume 45, ISBN 9780124077607. [Google Scholar]
  101. Belaïd, F. Untangling the Complexity of the Direct and Indirect Determinants of the Residential Energy Consumption in France: Quantitative Analysis Using a Structural Equation Modeling Approach. Energy Policy 2017, 110, 246–256. [Google Scholar] [CrossRef]
  102. Al-Gahtani, S.S. Empirical Investigation of E-Learning Acceptance and Assimilation: A Structural Equation Model. Appl. Comput. Inform. 2016, 12, 27–50. [Google Scholar] [CrossRef][Green Version]
  103. Ahmad, B.; Da, L.; Asif, M.H.; Irfan, M.; Ali, S.; Akbar, M.I.U.D. Understanding the Antecedents and Consequences of Service-Sales Ambidexterity: A Motivation-Opportunity-Ability (MOA) Framework. Sustainability 2021, 13, 9675. [Google Scholar] [CrossRef]
  104. Fornell, C.; Larcker, D.F. Evaluating Structural Equation Models with Unobservable Variables and Measurement Error. J. Mark. Res. 1981, 18, 39. [Google Scholar] [CrossRef]
  105. Wong, K.K.K. Partial Least Squares Structural Equation Modeling (PLS-SEM) Techniques Using SmartPLS. Mark. Bull. 2013, 24, 1–32. [Google Scholar]
  106. Nunnally, J.C. Psychometric Theory 3E; Tata McGraw-Hill Education: New York, NY, USA, 1994. [Google Scholar]
  107. Hair, J.F., Jr.; Matthews, L.M.; Matthews, R.L.; Sarstedt, M. PLS-SEM or CB-SEM: Updated Guidelines on Which Method to Use. Int. J. Multivar. Data Anal. 2017, 1, 107. [Google Scholar] [CrossRef]
  108. Field, A. Discovering Statistics Using IBM SPSS Statistics; Sage: Thousand Oaks, CA, USA, 2013; ISBN 1446274586. [Google Scholar]
  109. Deng, P.; Lu, S.; Xiao, H. Evaluation of the Relevance Measure between Ports and Regional Economy Using Structural Equation Modeling. Transp. Policy 2013, 27, 123–133. [Google Scholar] [CrossRef]
  110. Stevens, J.P. Applied Multivariate Statistics for the Social Sciences, 5th ed.; Routledge, Tylor & Francis Group: London, UK, 2012; ISBN 978-0-8058-5901-0. [Google Scholar]
  111. Blunch, N.J. Introduction to Structural Equation Modeling Using IBM SPSS Statistics and Amos, 2nd ed.; Sage: Thousand Oaks, CA, USA, 2012; ISBN 978-1-4462-4899-7. [Google Scholar]
  112. Truong, D.; Pan, J.Y.; Buaphiban, T. Low Cost Carriers in Southeast Asia: How Does Ticket Price Change the Way Passengers Make Their Airline Selection? J. Air Transp. Manag. 2020, 86, 101836. [Google Scholar] [CrossRef]
  113. Lucianetti, L.; Chiappetta Jabbour, C.J.; Gunasekaran, A.; Latan, H. Contingency Factors and Complementary Effects of Adopting Advanced Manufacturing Tools and Managerial Practices: Effects on Organizational Measurement Systems and Firms’ Performance. Int. J. Prod. Econ. 2018, 200, 318–328. [Google Scholar] [CrossRef]
  114. Almajali, D.A. Diagnosing the Effect of Green Supply Chain Management on Firm Performance: An Experiment Study among Jordan Industrial Estates Companies. Uncertain Supply Chain Manag. 2021, 9, 897–904. [Google Scholar] [CrossRef]
  115. Makhloufi, L.; Laghouag, A.A.; Meirun, T.; Belaid, F. Impact of Green Entrepreneurship Orientation on Environmental Performance: The Natural Resource-Based View and Environmental Policy Perspective. Bus. Strateg. Environ. 2022, 31, 425–444. [Google Scholar] [CrossRef]
  116. Seman, N.A.B.A.; Govindan, K.; Mardani, A. The Mediating Effect of Green Innovation on the Relationship Between Green Supply Chain Management and Environmental Performance in Malaysia Manufacturing Industries. Elsevier 2016, 7, 1080–1089. [Google Scholar]
Figure 1. Confirmatory factor analysis representing the measurement model. Source: Authors’ calculations.
Figure 1. Confirmatory factor analysis representing the measurement model. Source: Authors’ calculations.
Sustainability 15 05597 g001
Figure 2. Path diagram of structural equation modeling. * p < 0.1, ** p < 0.05, *** p < 0.01. Source: Authors’ calculation.
Figure 2. Path diagram of structural equation modeling. * p < 0.1, ** p < 0.05, *** p < 0.01. Source: Authors’ calculation.
Sustainability 15 05597 g002
Table 1. Respondents’ demographics.
Table 1. Respondents’ demographics.
Age (Years)18–3529039.4
Above 558611.68
Income (CNY)2000–500016522.41
EducationHigh school10013.58
College degree23431.79
Experience2–5 years19526.49
5–10 years35047.55
More than 10 years19129.95
Table 2. Descriptive statistics of the data.
Table 2. Descriptive statistics of the data.
VariablesObservationsItemsMeanStd. DevCoefficient of Variation (CV)
Notes: GHC–green human capital; GSCM—green supply chain management; GIN—green innovation; MEK—managerial environmental knowledge; FPR—firm performance.
Table 3. Correlation and discriminant validity analysis.
Table 3. Correlation and discriminant validity analysis.
GHC(0.795) 0.6320.278
GSCM0.527(0.829) 0.6870.278
GIN0.2690.362(0.762) 0.5800.131
MEK0.2230.2370.324(0.839) 0.7030.121
Notes: Values in parentheses represent the root square of AVEs.
Table 4. Results of reliability analysis and factor loadings.
Table 4. Results of reliability analysis and factor loadings.
Green human capital 0.8840.914
GHC 10.603
GHC 20.830
GHC 30.749
GHC 40.737
GHC 50.842
GHC 60.864
GHC 70.671
Green supply chain management 0.9160.875
GSCM 10.806
GSCM 20.880
GSCM 30.906
GSCM 40.923
GSCM 50.835
GSCM 60.746
GSCM 70.679
Green innovation 0.8540.908
GIN 10.781
GIN 20.823
GIN 30.875
GIN 40.858
GIN 50.853
Managerial environmental knowledge 0.8480.891
MEK 10.837
MEK 20.891
MEK 30.758
MEK 40.792
MEK 50.681
Firm performance 0.8940.917
FPR 10.715
FPR 20.752
FPR 30.686
FPR 40.702
Notes: Extraction method: maximum likelihood; Rotation method: Promax with Kaiser normalization.
Table 5. Collinearity diagnostics.
Table 5. Collinearity diagnostics.
VariablesCollinearity Statistics
Notes: Dependent variable: FPR.
Table 6. Kaiser–Meyer–Olkin (KMO) and Bartlett’s tests.
Table 6. Kaiser–Meyer–Olkin (KMO) and Bartlett’s tests.
KMO and Bartlett’s Tests
Kaiser–Meyer–Olkin Measure of Sampling Adequacy0.907
Bartlett’s Test of SphericityApprox. Chi-Square6759.03
Notes: Df—degree of freedom; Sig—significance.
Table 7. Communalities findings.
Table 7. Communalities findings.
Notes: Extraction method: maximum likelihood.
Table 8. Eigenvalues and cumulative variance.
Table 8. Eigenvalues and cumulative variance.
VariablesInitial EigenvaluesExtraction Sums of Squared
Total% of VarianceCumulative %Total% of VarianceCumulative %
Notes: Rotation method: Promax with Kaiser normalization; Cumulative variance: 63.390%.
Table 9. Results for the hypotheses.
Table 9. Results for the hypotheses.
HypothesesStructural Pathsβ-Valuef-ValueResults
Direct effects
H1GHC → FPR0.458143.1 ***Rejected
H2GHC → GIN0.143 **292.6 ***Accepted
H3GSCM → FPR0.182175.2 ***Rejected
H4GSCM → GIN0.046 *292.8 ***Accepted
H5GIN → FPR0.073 *297.3 ***Accepted
H6MEK * GIN → FPR0.203 ***140.5 ***Accepted
H7MEK → FPR0.138 *197.2 ***Accepted
Indirect effects
H8GIN → GHC → FPR0.157 ***155.8 ***Full mediation
H9GIN → GSCM → FPR0.036 ***142.5 ***Full mediation
Notes: * p < 0.1, ** p < 0.05, *** p < 0.01.
Table 10. Comparison table.
Table 10. Comparison table.
Analyzing the relationship between green innovation and environmental performance in large manufacturing firmsThis paper argues that neither green intellectual capital nor green human resource management is directly related to environmental performance. It argues instead that green innovation mediates the relationships between green intellectual capital, green human resource management, and environmental performance. It is further concluded that environmental strategies are directly related to environmental performance and moderate the relationship between green innovation and environmental performance.[48]
Green supply chain management and firm performance: the mediating effect of green innovationThe findings showed that green supply chain management positively affected green innovation, green innovation positively affected firm performance, and green supply chain management did not affect firm performance directly. Green innovation mediated the relationship between green supply chain management and firm performance.[38]
Effects of green human resource management on green innovation through green human capital, environmental knowledge, and managerial environmental concernThe findings of this study revealed that green human resource management positively contributed to the green innovation of organizations. The mediating roles of green human capital and environmental knowledge were also statistically significant. Furthermore, the results revealed that the link between green human resource management and green human capital is stronger with managerial environmental concern as a moderator.[33]
The mediating effect of green innovation on the relationship between green supply chain management and environmental performance in Malaysia manufacturing industriesThe findings of this study showed that green supply chain management practices positively affect green innovation and environmental performance. Green innovation was found to affect environmental performance positively, and its role as a mediator between GSCM practices and environmental performance was confirmed. The results confirmed the complementary effect of GSCM practices on green innovation and environmental performance.[116]
An environmental policy of green intellectual capital: green innovation strategy for performance sustainabilityThis study showed ways in which three dimensions of GIC influence a firm’s performance; that is, green human capital (GHC), green relational capital (GRC), and green structural capital (GSC). The mediating role of green innovation was used to explain the relationships. The findings indicated that the three GIC constructs positively affect economic performance, green performance, and green innovation. Further analysis found that green innovation fully mediates the linkage of GHC–economic performance and GSC–green performance and partially mediates the linkage of GRC–economic performance and GRC–green performance. Moreover, green innovation does not mediate the linkage of GSC–economic performance or of GHC–green performance.[15]
A structural model of the impact of green intellectual capital on sustainable performanceThis study investigated the connection between green intellectual capital and sustainable performance. According to their findings, green intellectual capital positively affects environmental, social, and economic performance. The significance of green intellectual capital was revealed to be an intangible resource for enterprises to achieve sustainable performance and a competitive edge for future researchers.[42]
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

Nureen, N.; Liu, D.; Irfan, M.; Malik, M.; Awan, U. Nexuses among Green Supply Chain Management, Green Human Capital, Managerial Environmental Knowledge, and Firm Performance: Evidence from a Developing Country. Sustainability 2023, 15, 5597.

AMA Style

Nureen N, Liu D, Irfan M, Malik M, Awan U. Nexuses among Green Supply Chain Management, Green Human Capital, Managerial Environmental Knowledge, and Firm Performance: Evidence from a Developing Country. Sustainability. 2023; 15(6):5597.

Chicago/Turabian Style

Nureen, Naila, Da Liu, Muhammad Irfan, Maida Malik, and Usama Awan. 2023. "Nexuses among Green Supply Chain Management, Green Human Capital, Managerial Environmental Knowledge, and Firm Performance: Evidence from a Developing Country" Sustainability 15, no. 6: 5597.

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