Government Regulations and Top Management Influence on Manufacturing Firms Environmental Performance: Nexus of Green Supply Chain , Culture and Technology Adoption

Government Regulations and Top Management Influence on Manufacturing Firms Environmental Performance: Nexus of Green Supply Chain , Culture and Technology Adoption | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Government Regulations and Top Management Influence on Manufacturing Firms Environmental Performance: Nexus of Green Supply Chain , Culture and Technology Adoption Saqib Mehmood, Samera Nazir, Jianqiang Fan, Zarish Nazir, Amad Shoukat This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-3666203/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Purpose: This study investigates the relationships between sustainable technology adoption, green supply chain integration, sustainability culture, and environmental performance in organizations. It also explores the moderating effects of government environmental regulations and top management commitment on these relationships. Design: The study employs a comprehensive research design, incorporating literature analysis and empirical data collection via survey. Data was gathered through purposive sampling, involving 244 samples from manufacturing companies in Pakistan. PLS-SEM analysis was used to assess the connections between sustainable technology adoption, green supply chain integration, sustainability culture, environmental performance, and the moderating influence of government regulations and top management commitment. Findings: The results highlight significant positive relationships between sustainable technology adoption, green supply chain integration, sustainability culture, and improved environmental performance. Additionally, government environmental regulations and top management commitment were identified as moderators that strengthened these relationships, emphasizing their pivotal role in fostering sustainability within organizations. Originality or Value: The study contributes to our understanding of how sustainable technology adoption, green supply chain integration, sustainability culture, and environmental performance are interconnected, while also considering the influence of government regulations and top management commitment. These findings enrich our knowledge of factors that promote sustainability in organizations. Sustainable Technology Adoption Green Supply Chain Integration Sustainability Culture Environmental Performance Government Environmental Regulations Top Management Commitment Figures Figure 1 Figure 2 1. Introduction In today's dynamic business landscape, the pursuit of environmental sustainability has become a paramount concern for manufacturing firms worldwide. This study delves into the intricate influences shaping these organizations' environmental performance (EP). Green supply chain integration (GSCI) highlights how green manufacturing improves performance and identifies collaboration needs (Wong et al., 2020 ). Internal collaboration enhances overall sustainable performance. GSCI boosts market shares and profits (Eltayeb et al., 2011 ), but lack of support leads to economic failure (Zhu et al., 2012 ). Sustainable design practices improve income, employee welfare, and profits (Cosenz et al., 2020). Internal coordination enhances socially sustainable performance (Shahzad et al., 2020 ). Sustainable technology adoption (STA) involves integrating eco-friendly technologies to reduce environmental impact. Key elements include renewable energy, energy efficiency, waste reduction, and green manufacturing (Koval et al., 2021 ). A green supply chain incorporates eco-friendly materials, efficient logistics, and responsible product disposal (Zhu et al., 2012 ). Sustainable culture (SC) promotes environmental responsibility, social equity, and economic viability (Lu et al., 2021 ). Government environmental regulations (GER) and top management commitment (TMC) shape sustainability initiatives (Wijethilake and Lama, 2019 ). Supplier integration correlates with sustainable performance (Lăzăroiu et al., 2020 ). Environmental performance (EP) assesses energy use, emission reduction, and resource management. It's about reducing emissions, waste, and accidents (Tiwari et al., 2020). EP aids in risk mitigation and policy formulation (Alaeddin et al., 2019). While substantial empirical evidence supports a positive connection between green supply chain management (GSCM) pattern and firm execution, limited attention has been given to the factors that could modulate the nature and strength of this relationship (Dubey et al., 2015 ). (Dubey et al., 2015 ), examine the part of institutional pressure resulting from operational practices (e.g., TQM and customer relationship management) on EP. As scholars and practitioners in the tract of supply chain management increasingly recognize the value of the GSCM pattern, it's crucial to consider the growing environmental challenges (Chen et al., 2022 ). Consequently, adopting GSCM within organizations should be viewed as a source of value rather than a threat (Abdel-Baset et al., 2019). GER, including carbon emissions caps, eco-friendly mitigation methods, and a green culture to protect the planet's ecological well-being, are driving wider adoption across various firms, expanding its relevance in the corporate landscape (Zheng et al., 2019 ). GSCM involves the administration of data, resources, and investments, as fit as collaboration between supply chain businesses, to dynamically integrate objectives related to the three dimensions of property improvement; economical, cultural, and environmental. These objectives naturally align with the demands of stakeholders and consumers (Nureen et al., 2023 ). It's important to note that effective GSCM implementation necessitates a multifaceted approach (Sahu et al., 2023 ) (Novitasari et al., 2023 ). As organizations strive for a more environmentally responsible future, a green supply chain, which offers economic benefits and ecological responsibility, should take precedence (Guo et al., 2022 ). GSCM enhances the conventional concept of supply chain by adopting an ecologically responsible perspective, thereby improving the overall life cycle EP of products and services (Esfahbodi et al., 2023 ). While the existing literature acknowledges the significance of STA, GSCI, SC, and EP, a research gap remains in comprehensively examining the interconnections between these elements. Additionally, few studies adequately address the moderating influence of GER and TMC in this circumstance (Makhloufi et al., 2022 ). Therefore, there is a need for empirical research that systematically investigates how these components energetically affect sustainability outcomes within organizations, considering the regulatory and leadership frameworks that shape their implementation and effectiveness. This research purpose to furnish vision into the following inquiries. RQ1. How STA is associated with GSCI and SC. RQ2. How GSCI and SC are associated with EP. RQ3. How GER and TMC moderate the relationship between GSCI and SC with EP. This study aims to thoroughly investigate the relationships between Sustainability (STA), Global Supply Chain Integration (GSCI), Supply Chain (SC), and Environmental Performance (EP) within organizations. It also seeks to analyze the influences of Government Environmental Regulations (GER) and Top Management Commitment (TMC) on these relationships, providing insights into how external regulations and leadership affect sustainable practices in the fast-changing business environment. This study aids organizations in enhancing sustainability strategies by analyzing the effects of sustainable technology, green supply chains, and supply chain operations on environmental performance. It emphasizes the importance of government regulations and top management alignment and support. Ultimately, this research improves our understanding of the factors driving sustainability for better strategies and positive environmental results. This study is rooted in sustainability theory, emphasizing meeting present needs while safeguarding future generations. Concepts like STA, GSCI, and fostering SC align with this principle, striving for economic, social, and environmental sustainability. Resource dependence theory explains how organizations respond to external influences, including government regulations, shaping sustainability practices and performance. Institutional theory helps understand how organizations adhere to sustainability norms and regulations. The study explores responses to external pressures, like environmental regulations, in shaping sustainability initiatives. Stakeholder theory recognizes various stakeholders, such as government regulators and top management, as crucial in shaping sustainability initiatives. It provides a framework to analyze how stakeholder interests impact sustainable practices and environmental performance. Top management commitment theory emphasizes the critical role of top management in driving organizational change and sustainability initiatives. In the context of sustainability, the study examines how top management commitment influences approaches to sustainable technology adoption, green supply chains, and sustainability culture. These theories form the core framework for understanding how government environmental regulations, top management commitment, and their influence on manufacturing firms' environmental performance (EP) are interconnected, considering factors like GSCI, SC, and sustainable technology adoption. A research framework is essential, offering a structured path for clarity, hypothesis development, theory testing, and rigor, enabling researchers to advance knowledge in their fields. In Fig. 1 , the study framework is displayed. 2. Hypothesis Development The research hypotheses presented below have been formulated following the earlier discussions. 2.1 STA and GSCI Sustainable Technology Adoption (STA) involves integrating and utilizing technologies that promote environmental sustainability resource efficiency and reduce negative environmental impacts within a company's operations. This can encompass various applications such as inexhaustible strength methods, energy-economical machinery, material change applications, and sustainable transportation systems (Melville, 2010 ) (Caiado et al., 2019 ); (Maksimovic, 2018 , Javaid et al., 2022 ). Green Supply Chain Integration (GSCI) involves incorporating environmentally sustainable practices throughout the supply chain, encompassing environmentally friendly sourcing, manufacturing, transportation, and distribution processes (Li et al., 2023 ) (Han and Huo, 2020 ). Companies embracing GSCI focus on reducing their carbon footprint, minimizing waste, optimizing resource utilization, and ensuring responsible sourcing and disposal (Kumar et al., 2019 ). STA leads to reduced environmental impacts within supply chains, aligning with research by (Carter and Rogers, 2008 ), which emphasizes sustainable practices. Advanced technologies like RFID and GPS improve real-time monitoring and tracking, vital for achieving green supply chain goals (Zhu et al., 2013 ). STA fosters collaboration and data mutuality between supply chain relations, which is crucial for GSCI (Tseng, 2014 ). It enhances resource efficiency, waste reduction, and compliance with environmental regulations and standards (Wijethilake and Lama, 2019 ). Additionally, it positively impacts corporate reputation and customer perception while contributing to cost savings and resilience in supply chains (Bocken et al., 2016 ) (Pettit et al., 2013 ). Based on these findings, we formulate the following hypothesis: H1: STA is positively connected with GSCI. 2.2 STA and SC STA involves assimilating and utilizing technologies designed to minimize environmental impact, optimize resource utilization, and contribute to sustainability objectives (Shahzad et al., 2021 ). A sustainability culture (SC) encompasses the values, norms, attitudes, and behaviors of individuals or organizations concerning sustainability and environmental responsibility (Wei et al., 2017 ). When sustainability principles are deeply ingrained in an organization's or an individual's core values, they guide decision-making processes, leading to a robust SC (Jasiński et al., 2021). Research indicates that a strong SC within an organization encourages stakeholders' integration of sustainable technologies, aligning with the organization's environmental objectives (Sahoo et al., 2023 ). (Wei et al., 2017 ), empirical studies demonstrate that organizations with a well-established SC are more likely to invest in STA, given the emphasis on reducing environmental impact and promoting sustainability (Liu et al., 2023 ). The prioritization of sustainability within the culture catalyzes the proactive adoption of technologies aligned with environmental goals (Raub and Martin-Rios, 2019 ). While organizations ingrained with an SC tend to be more open to adopting sustainable technologies (Pretty et al., 2018 ), In environments where a sustainability culture is deeply rooted, there is a noticeable increase in incorporating sustainable technologies, fostering innovation and facilitating seamless adoption (El-Haddadeh et al., 2021 ). Additionally, within communities or networks embracing an SC, individuals can parcel data and mutually encourage the adoption of sustainable technologies, supporting the idea of a positive association between SC and technology adoption (Beltrán-Rodríguez et al., 2021 ). This collective effort further propels the integration of sustainable technologies toward a more sustainable future. Basis on these findings we formulate following hypothesis: H2: STA is positively connected with SC. 2.3 GSCI and EP. GSCI involves incorporating environmentally affable practices and principles end-to-end in the supply chain. This includes sustainably sourcing raw materials, optimizing transportation to reduce emissions, adopting eco-friendly packaging, and implementing efficient waste management (Younis et al., 2016 ). EP measures a company's ability to minimize its environmental impact, considering factors like carbon discharge decrease, strength efficiency, waste reduction, water preservation, and compliance with environmental regulations (Mumtaz and Smith, 2019 ). EP is enhanced through strategies such as sourcing sustainable materials and collaborating with eco-friendly suppliers (Pagell and Wu, 2009 ) By integrating sustainable practices into their supply chains, companies reduce resource consumption, waste generation, and emissions, resulting in improved EP (Bassetti et al., 2021 ). This integration is vital for reducing environmental accidents, pollution, hazardous components, and solid waste, ultimately benefiting the company and society (Esfahbodi et al., 2016 ), Effective integration of environmentally sustainable practices leads to notable improvements in EP metrics, including reduced carbon emissions, minimized waste, and enhanced resource efficiency, underlining the positive impact of GSCI on overall sustainability (Maksimovic, 2018 ). Aligning supply chain processes with sustainability objectives by adopting eco-friendly sourcing, production, and distribution practices further associates with favorable outcomes in EP (Abuzawida et al., 2023 ). Basis on these findings we formulate following hypothesis: H3: GSCI is positively related to EP. 2.4 SC and EP SC in an organization center on values, beliefs, norms, and practices emphasizing environmental sustainability. This entails integrating sustainability into the organizational culture with leadership endorsement, employee involvement, and a focus on sustainable practices (Roscoe et al., 2019 ). EP pertains to an organization's effectiveness in managing its environmental impact, encompassing reducing greenhouse gas emissions, conserving resources, waste reduction, and compliance with environmental standards (Yaro et al., 2023 ). A strong SC promotes collective commitment to environmental responsibility and encourages environmentally conscious behaviors among employees, like waste reduction and energy conservation (Yaro et al., 2023 ). This heightened dedication correlates with improved EP, ultimately leading to reduced ecological impact and a sustainable organizational and environmental future (Sahoo and Thakur, 2023 ) (Gilal et al., 2019 ), establish a supportive nexus among firm cultural execution, including SC and EP, supporting the belief that a robust SC enhances environmental outcomes. Additionally, studies by (He and Kim, 2021 ), demonstrated that participation in voluntary environmental programs driven by a proactive SC is linked to improved EP. Furthermore, (Russo and Harrison, 2005 ), concluded that companies with a strong SC exhibit better EP, reaffirming the connection between sustainability culture and environmental outcomes. These studies support Hypothesis H4 by confirming a supportive state among SC and EP within organizations. Founded on this collection, we develop the pursuing hypothesis: H4: SC is positively connected with EP. 2.5 GER moderate between GSCI and EP Government environmental regulations (GER) encompass laws, policies, and directives instituted by governmental bodies, spanning local, regional, and national levels, to oversee and manage environmental concerns. These regulations guide organizations, promoting sustainable practices and mitigating environmental impacts (Coenen et al., 2021 ). GSCI involves infusing environmentally sustainable practices end-to-end into the supply chain, from material root to direction, necessitating collaboration among supply chain partners for minimal environmental harm and heightened sustainability (Wong et al., 2020 ). EP evaluation involves assessing an organization's activities and operations to manage and diminish its environmental footprint while complying with pertinent standards and objectives (Benzidia et al., 2021 ). Several studies highlight the state of GER and GSCM patterns. (Zhu and Sarkis, 2007 ), affirm that stringent government regulations reinforce the positive connection between GSCI and EP. (Darnall et al., 2008), assert that government regulations drive companies to integrate GSCM patterns, enhancing EP. (Han and Huo, 2020 ), strict environmental regulations augment the supportive relationship between the GSCM pattern and EP. (Kolk and Pinkse, 2010 ) underline GER's role in influencing corporate environmental strategies, driving environmentally friendly practices adoption. Additionally, (Rasool et al., 2020 ) (Zhu et al., 2012 ), reiterates the positive influence of stringent environmental regulations in enhancing the association between GSCI and EP, emphasizing the helpful role of government regulations in promoting environmentally responsible business behavior. Based on these findings, we formulate following hypothesis: H5: GER moderates the state between GSCI and EP. 2.6 GER moderates between SC and EP As defined by [61], SC encompasses an organization's shared commitment to integrating environmental, social, and economic sustainability into decision-making and operations. As outlined by [55], GER serves as laws and policies enacted to regulate and manage environmental issues, guiding organizations toward sustainable practices. EP, as examined by (Gilal et al., 2019 ), involves measuring an organization's environmental impact and compliance with environmental standards and goals. Research by (Gadenne et al., 2009 ), explores how environmental awareness and compliance with government regulations influence the environmental practices of SMEs, shedding light on the role of regulations in shaping SC. (Kolk and Pinkse, 2010 ), investigate the role of GER in shaping societal and environmental obligations within supply chains, emphasizing how regulations moderate the relationship between SC and EP. (Shafique et al., 2021 ), stringent GER motivates firms with an SC to adopt eco-friendly practices, positively impacting their EP. (Zheng et al., 2019 ), discovered that organizations with a strong SC thrive under stricter regulatory environments, indicating the value of SC in achieving superior EP. (Iraldo et al., 2011 ), emphasize the importance of regulatory frameworks as complements to internal SC, as government regulations provide standardized rules and incentives guiding organizations towards sustainable practices and enhancing their EP. Founded on these collection we formulate the pursuing hypothesis: H6: GER moderates the relationship between SC and EP. 2.7 TMC moderates among GSCI and EP To reduce the supply chain's environmental impact, GSCI integrates environmental considerations into supply chain processes, including commodity plans, substantial points, manufacture, transportation, and waste management (Younis et al., 2016 ). This integration is assessed through indicators such as carbon emissions, water and energy consumption, waste generation, recycling rates, and compliance with environmental regulations, measuring how a company's operations affect the environment. TMC signifies the dedication and support of senior leadership toward implementing and maintaining environmentally sustainable practices within the company. It entails resource allocation, goal setting, and communicating the importance of environmental sustainability throughout the organization (Jasiński et al., 2021). TMC moderates the state among GSCI and EP, indicating that the impact of integrating green practices is contingent on top management's commitment level (Ilyas et al., 2020). Studies emphasize that a strong TMC fosters a society of environmental responsibility within the structure, influencing decisions and practices throughout the supply chain (Jazairy and von Haartman, 2020 ) (Aragón-Correa and Sharma, 2003 ). This commitment enhances the prioritization, monitoring, and effective execution of the GSCM pattern, ultimately improving EP (Srivastava, 2007 ). In summary, strong TMC will likely moderate the relationship between integration efforts and subsequent improvements in EP, shaping the organization's approach toward environmental sustainability. Supported by this collection, we develop the pursuing hypothesis: H7: TMC moderates the relationship between GSCI and EP. 2.8 TMC moderates among SC and EP SC in an organization represents mutual belief, ideas, measures, and behaviors, prioritizing environmental sustainability and social responsibility (Tseng, 2014 ). It involves all employees embracing sustainability in their work (Lo et al., 2014 ). EP measures how well an organization manages its environmental impact, including reducing emissions, conserving resources, and minimizing waste (Jasiński et al., 2021, Lo et al., 2014 ). TMC is the dedication and active involvement of senior executives in promoting sustainability initiatives, setting goals, and allocating resources (Labella-Fernández et al., 2021 ). A strong SC positively impacts EP, leading to environmentally friendly practices and strategies. Companies with such a culture are more likely to follow active environmental governance patterns, improving their performance (Tsai et al., 2020 ), suggesting that TMC and regulations jointly moderate the relationship between SC and EP. Strong TMC and supportive regulations enhance this positive impact, while weak commitment and lax compliance may weaken it (El-Kassar and Singh, 2019 ). Research consistently shows that TMC positively influences EP (Dubey et al., 2015 ) (Lo et al., 2014 ). Similarly, a strong SC within an organization is linked to enhanced EP (Heras-Saizarbitoria et al., 2020 ). Compliance with environmental regulations is associated with improved EP (Arimura et al., 2011 ). These findings emphasize the importance of integrating SC, top management commitment, and regulatory compliance for enhanced EP. Based on these findings, we formulate the pursuing hypothesis: H8: TMC regulations moderate the relationship between SC and EP. 3. Study Methodology 3.1 Instrument Evolution The measuring components utilized in this research were drawn from existing literature and subsequently adapted to align with the current research context. The scales employed have been customized to suit the specific requirements of this research, with due consideration to their appropriateness for the survey respondents. To assess the robustness of the conceptual model, a pilot study was conducted involving 244 top managers, supply chain professionals, policymakers and employees who are professional members of the manufacturing industry of Pakistan. The manufacturing and related sectors are inherently dynamic, presenting unique challenges and risks. The questionnaire has been designed to capture pertinent data for this study, with all items being measured exploitation a five-point Likert scale. Detailed information regarding the sources of the measurement portion can be found in Table 3 . 3.2 Sample distribution strategy and data grouping The data for this research were gathered utilizing purposive sampling via an online survey distributed through a Google Docs link. Data was collected from June to August 2023. Initially, this survey was dispatched to 300 professionals who are members of the manufacturing industry in Pakistan. In the end, 260 questionnaires were returned, resulting in an outcome range of 83.66 percent. Out of 260 total, 244 questionnaires are fully completed, others are incomplete and outlier. Researchers used purposive sampling to align the sample selection with the study's goals and research questions. This method provides the advantage of purposefully targeting participants most likely to contribute relevant and valuable information, enhancing the study's quality and relevance to the specific research objectives. Table 1 presents the data about the manufacturing industry types and size in the shape of numbers of employees and respondents' areas of employment, years of professional experience, education and age and Table 2 shows the descriptive Statistics of variables. Table 1 shows the demographic collection of the survey associate and company. Table 1 Work Domains of Respondents and their Professional Experience Demographic Factors Respondents Frequency Percentage Gender Male 183 75 Female 61 25 Age 20–30 78 32 31–40 61 25 41–50 68 28 51 & above 37 15 Education Bachelors 81 33 Masters 112 46 Above Masters 51 21 Experience 10 years 37 15 11–15 years 76 31 16–20 years 63 26 21 & above years 68 28 Industry Electronics 73 30 Textile 110 45 Food manufacturing 61 25 Company's number of Employees Less than 30 32 13 30–60 112 46 61–90 49 20 91–120 32 13 More than 120 19 08 Company's Years of Working Less than 5 years 37 15 6–10 years 76 31 11–15 years 63 26 16 & above 68 28 Table 2 Variable Descriptive Statistics Variables Sample mean Standard Deviation Sample Size EP 4.03 0.68 244 GER 3.21 0.87 244 GSCI 4.76 0.98 244 SC 3.38 0.74 244 STA 4.02 0.53 244 EP 4.27 0.48 244 3.3 Common method bias, nonresponse bias, Social Desirability and Multicollinearity CMB may pose a potential issue when dealing with self-reported data, as the [74], study highlighted. Several preventive measures were taken to mitigate this concern at the pre-data collection stage. The questionnaire commenced with a special note to ensure that respondents clearly understood the survey's purpose, emphasizing that it was strictly for academic research and not for any commercial use. The confidentiality of respondents' information throughout all stages of the research was also assured. In the post-data collection phase, Harman's individual-section trial was employed to measure whether extraneous factors influenced the data due to the measurement instrument. EFA was conducted using the data obtained from an online survey. The results of this analysis indicated the existence of five defined sections, with the initial element explaining the highest proportion of covariance at 33.28%. According to the criteria established by (Podsakoff and Organ, 1986 ), if an individual factor accounts for less than 50% of the maximum covariance, it does not significantly impact the data. The nonresponse bias was assessed following the guidelines outlined by (Armstrong and Overton, 1977 ). Additionally, a relation was conducted among the advanced wave and late wave (after the first reminder) during the data collection phase by employing the Homogeneity of Variance test. To respond to the influence of social desirability response bias, anonymous surveys were employed to foster honest and open feedback. The survey questions were designed to be impartial and free from leading language, and participants were confident of the privacy of their outcomes. The researcher was careful not to frame questions in a way that would encourage socially desirable answers and took the extra step of conducting pilot testing to address any potential biases. Additionally, efforts were made to assess multicollinearity following the criteria outlined by (Yoo et al., 2014 ). The results of these assessments revealed that the model did not exhibit multicollinearity, as all VIF values remained beneath the established threshold of 3.3. These VIF values can be found in Table 4 . 3.4 Assessment of Measurement Model Considering the constructs nature and interrelationships, a reflective measurement model established by (Hair Jr et al., 2021 ), was evaluated for reliability and validity, as shown in Table 4 . The survey has been meticulously structured to gather relevant information for this research, and each element is assessed using a five-point Likert scale. Comprehensive details about the origins of these measurement items are available in Table 3 . Table 3 Measurement Instruments' Source Constructs Item Description Source Environmental Performance (EP) EP1 Environmental initiatives have a positive impact on our company's profitability. (Coenen et al., 2021 , Gilal et al., 2019 ) EP2 Our environmental performance is a competitive advantage in our industry. EP3 Our organization has made significant improvements in reducing our environmental footprint. EP4 Our environmental performance contributes to a positive public image and brand reputation. EP5 Environmental performance is a key performance indicator in our manufacturing firm. Government Environmental Regulations (GER) GER1 Compliance with government environmental regulations is a top priority in our organization. (Coenen et al., 2021 , Darnall et al., 2008) GER2 Our organization invests in technologies and processes to meet or exceed government environmental regulations. GER3 Compliance with government environmental regulations is a priority in our manufacturing operations. GER4 Our firm seeks to exceed regulatory requirements in its environmental efforts. GER5 To what extent do you believe that government environmental regulations positively impact your manufacturing firm's environmental performance Sustainable Technology Adoption (STA) STA1 Our organization is adopting sustainable and environmentally friendly technologies in manufacturing processes. (Esfahbodi et al., 2016 , Jasiński et al., 2021) STA2 Our manufacturing firm invests in and adopts sustainable technologies to reduce environmental impacts. STA3 Employees obtain the essential education and help to effectively use sustainable technologies. STA4 Our organization encourages to adoption of sustainable technology. STA5 Sustainable technology adoption is positively correlated with our environmental performance. STA6 Sustainable technology adoption is important to improve the environmental performance of the company. Sustainable Culture (SC) SC1 Our manufacturing firm promotes a culture of environmental responsibility and sustainability. (Esfahbodi et al., 2016 , Wijethilake and Lama, 2019 ) SC2 Sustainable practices and values are integrated into our organization's core mission. SC3 Our firm promotes a culture of sustainability and environmental responsibility. SC4 A sustainable culture positively influences our firm's environmental performance. SC5 Does your firm promote a culture that values sustainability and environmental responsibility? SC6 How do you believe this culture affects your firm's environmental performance? Top Management Commitment (TMC) TMC1 Our top management's commitment to the environment positively affects our company's overall performance. (Bassetti et al., 2021 , Srivastava, 2007 ) TMC2 Senior management is actively involved in environmental decision-making and strategies. TMC3 Top management's commitment positively influences our firm's environmental performance. TMC4 Our organization's top management is highly committed to environmental sustainability in your firm. TMC5 Environmental sustainability is integrated into our firm's strategic decision-making processes. Green Supply Chain Integration (GSCI) GSCI1 GSCI is essential to our manufacturing firm's environmental strategy (Younis et al., 2016 , Kumar et al., 2019 ) GSCI2 How would you rate the level of commitment of your organization to reducing the environmental impact of its supply chain activities? GSCI3 Our company collaborates with suppliers and partners to implement environmentally friendly practices. GSCI4 To what extent has your manufacturing firm integrated green practices into its supply chain GSCI5 To what extent has your manufacturing firm integrated green practices into its supply chain? GSCI6 Integrating environmentally friendly practices in our supply chain is a top priority for our organization. To assess reliability, we utilized Cronbach's Alpha and composite reliability, as proposed by (Bacon et al., 1995 ), and examined outer loadings to evaluate the reliability of the indicators. Likewise, for validity assessment, we employed the Average Variance Extracted (AVE) and outer loadings, drawing on the work of (Chin, 2009 ). It's worth noting that all the criteria, including alpha coefficients, composite reliability estimates, and AVE shown in Table 4 , met or exceeded their predefined thresholds, as suggested by (Hair et al., 2013 ) (Hair et al., 2017 ), thereby confirming the reliability and validity of the measurement model. Table 4 Outer Loadings, Cross loading, VIF, Cronbach's Alpha, CR, and AVE Constructs Indicator Outer Loading Cross Loading VIF Alpha Composite Reliability AVE EP EP1 0.788 0.788 3.757 0.905 0.93 0.727 EP2 0.892 0.892 4.534 EP3 0.788 0.788 2.757 EP4 0.895 0.895 3.203 EP5 0.893 0.893 4.235 GER GER1 0.755 0.655 2.496 0.873 0.902 0.652 GER2 0.863 0.863 2.422 GER3 0.764 0.664 1.325 GER4 0.916 0.916 2.185 GER5 0.899 0.899 1.596 GSCI GSCI1 0.796 0.796 2.324 0.931 0.946 0.745 GSCI2 0.89 0.89 3.505 GSCI3 0.897 0.897 4.673 GSCI4 0.905 0.905 4.914 GSCI5 0.863 0.863 2.791 GSCI6 0.821 0.821 2.583 SC SC1 0.917 0.536 1.645 0.937 0.95 0.76 SC2 0.89 0.535 3.663 SC3 0.871 0.477 3.304 SC4 0.851 0.514 2.831 SC5 0.803 0.402 2.226 SC6 0.893 0.528 4.734 STA STA1 0.72 0.125 1.825 0.895 0.917 0.649 STA2 0.785 0.11 2.214 STA3 0.807 0.176 2.213 STA4 0.822 0.278 2.036 STA5 0.869 0.3 2.389 STA6 0.824 0.268 2.038 TMC TMC1 0.759 0.1 1.692 0.746 0.832 0.504 TMC2 0.822 0.109 2.092 TMC3 0.691 0.114 1.708 TMC4 0.727 0.106 1.547 TMC5 0.509 0.07 1.084 Convergent validity is employed to evaluate the extent to which an indicator exhibits a positive correlation with other indicators specified within the theoretical framework (Chin, 2009 ). Discriminant validity was scrutinized through cross-loadings, the (Ab Hamid et al., 2017 ), and the HTMT method outlined by (Hair et al., 2013 ). Cross-loadings confirmed construct differentiation from other constructs in the model (Ab Hamid et al., 2017 ), (see Table 4 ). Notably, the square root of AVE for each latent variable surpasses the association between these latent variables, as (Hair et al., 2012 ), asserted, shown in Table 5 . Table 5 Fornel and Larker Criteria (1981) Constructs EP GER GSCI SC STA TMC EP 0.853 GER 0.435 0.808 GSCI 0.155 0.29 0.863 SC 0.177 0.241 0.575 0.872 STA 0.006 0.112 0.287 0.201 0.806 TMC 0.36 0.302 0.141 0.212 0.133 0.71 Additionally, the HTMT values fell beneath the critical threshold of 0.85 with coefficient of determination values R 2, thus affirming the discriminant validity of the framework, in line with the research by (Henseler et al., 2015). Q 2 measures the predictive performance of a model. It also assesses how well the framework generalizes to new data (see Table 6 ). Table 6 HTMT and Coefficient of Determination Constructs EP GER GSCI SC STA R 2 Q 2 EP 0.47 0.43 GER 0.455 GSCI 0.166 0.31 0.82 0.75 SC 0.189 0.263 0.608 0.41 0.40 STA 0.058 0.138 0.278 0.201 TMC 0.422 0.315 0.164 0.257 0.159 In Table 7 , EP exhibits positive correlations with other constructs: 0.435 with GER, 0.155 with GSCI, 0.177 with SC, 0.006 with STA, and 0.36 with TMC. GER shows similar patterns of correlation with the constructs. Notably, GSCI has a relatively strong positive correlation (0.575) with SC and a moderate positive correlation (0.287) with STA. The correlations provide insights into the relationships between these constructs, with varying degrees of strength and direction. Table 7 Correlations of Constructs Correlation EP GER GSCI SC STA TMC EP 1 0.435 0.155 0.177 0.006 0.36 GER 0.435 1 0.29 0.241 0.112 0.302 GSCI 0.155 0.29 1 0.575 0.287 0.141 SC 0.177 0.241 0.575 1 0.201 0.212 STA 0.006 0.112 0.287 0.201 1 0.133 TMC 0.36 0.302 0.141 0.212 0.133 1 3.5 Classification of Structural Model The relevance of the routes, linearity, coefficient of determination (R2), effect size (f2), and other parameters are considered when evaluating the structural model in this study (Hair et al., 2013 ). To ensure the most accurate parameter estimation, we evaluated multicollinearity as well (Mela and Kopalle, 2002 ) and all values were below the threshold of ± 5.0, as established by (Hair et al., 2013 ), (See Table 4 ). The cumulative effect of exogenous latent variables on the endogenous latent variable is represented by the coefficient of determination (R2). The coefficient of R2 and Q2 was used to evaluate predictive accuracy (see Table 6 ). The effect size for the relationship under test is shown by the F2 value in Table 8 . A regression study measure how strongly the variables are related to one another. The F2 statistic shows the magnitude of the association between the independent and dependent variables. The results indicate a strong and positive correlation between STA and GSCI, supporting our H1 (β = 0.374, t = 16.777, p = 0.000). Additionally, STA has a notable and supportive impact on SC, validating our H2 (β = 0.298, t = 13.292, p = 0.000). Furthermore, the findings confirm H3 (β = 0.184, t = 9.071, p = 0.000), demonstrating that GSCI is important and positively associated with EP. Similarly, H4 is upheld (β = 0.168, t = 8.187, p = 0), indicating a meaningful and supportive relationship between SC and EP. The results demonstrate support for H5 (β = 0.654, t = 3.519, p = 0.000), H6 (β = 0.492, t = 5.601, p = 0.000), H7 (β = 0.564, t = 3.46, p = 0.000) and H8 (β = 0.763, t = 2.955, p = 0.000) confirming the presence of moderating effects of H5 GER x GSCI -> EP and H6 shows the moderating effect of GER x SC -> EP also H7 shows the moderating effect of TMC x GSCI -> EP lastly H8 shows the moderating effect of TMC x SC -> EP. Table 8 provides comprehensive information on the direct and indirect pathways (moderating effects). Table 8 Hypothesis Testing Hypothesis β Standard deviation (STDEV) T statistics P- values F 2 Results Direct Effect STA -> GSCI H1 0.374 0.22 16.777 0.000 2.456 Accepted STA -> SC H2 0.298 0.21 13.292 0.000 2.211 Accepted GSCI -> EP H3 0.184 0.23 9.071 0.000 1.456 Accepted SC -> EP H4 0.168 0.19 8.187 0.000 1.896 Accepted Moderation Effect GER x GSCI -> EP H5 0.654 0.19 3.519 0.000 0.763 Accepted GER x SC -> EP H6 0.492 0.18 5.601 0.000 0.859 Accepted TMC x GSCI -> EP H7 0.564 0.28 3.46 0.001 0.435 Accepted TMC x SC -> EP H8 0.763 0.25 2.955 0.003 0.102 Accepted The study explores the relationships among GER, GSCI, SC, STA, TMC and EP, analyzing their statistical significance at a substance equal below 0.05 (shown in Fig. 2 ). 4. Discussion The positive correlation between adopting sustainable technologies and integrating green practices within the supply chain conforms with the core tenets of sustainability theory. Sustainable technologies are pivotal in implementing environmentally friendly practices across the supply chain (Dubey et al., 2015 ). This association can be appreciated as the direct channel of the sustainability concept, which underscores the significance of environmental stewardship, resource efficiency, long-term sustainability, meeting stakeholder expectations, and considering the triple bottom line (Hussain et al., 2018). Organizations embracing sustainable technologies are more inclined to infuse eco-friendly practices throughout their supply chain. As a result, this fosters a more sustainable and environmentally responsible approach to their operational processes (Yu et al., 2022 ). The study's confirmation of the hypothesis linking STA to the cultivation of a SC aligns with the principles of Resource dependence theory. STA can be viewed as a strategic move aimed at reducing the reliance on external environmental resources, thereby encouraging the development of a culture that places a high premium on environmental accountability and sustainability (Glasmeier and Farrigan, 2003 ). Resource dependence theory is a robust theoretical underpinning for comprehending the connection between adopting sustainable technologies and promoting a SC within organizational contexts. This theory underscores the pivotal role of external resources, exchange relationships, resource dependency, institutional pressures, and the process of organizational learning in shaping the prevailing organizational culture (Paulraj, 2011 ). In this context, STA emerges as a response to these influential factors, ultimately creating a culture prioritizing sustainability and environmental responsibility (Kouhizadeh et al., 2021 ). The positive connection between GSCI and enhanced EP is following the core tenets of Institutional theory. Organizations are subject to the pervasive influence of institutional norms and external pressures, compelling them to adopt and implement sustainable practices, yielding favorable EP outcomes (El-Kassar and Singh, 2019 ). Institutional concept underscores the profound effect of various organizational factors, including outer force, societal norms, regulatory adherence, organizational legitimacy, and cultural-cognitive elements, on shaping the behavioral patterns of organizations (Linnenluecke and Griffiths, 2010 ). Considering these influences, organizations embrace and introduce green patterns within their supply chain dealings, ultimately culminating in the augmentation of their EP. The hypothesis connecting SC with enhanced EP finds alignment with stakeholder theory. A robust SC indicates an administration's unwavering dedication to gathering its diverse stakeholders' multifaceted expectations, encompassing a commitment to environmentally responsible practices that, in turn, result in heightened EP (Awan et al., 2017). Stakeholder theory provides a robust and coherent theoretical underpinning for comprehending the affirmative correlation between SC and EP (Awan et al., 2017). It accentuates the pivotal role of stakeholders, elucidating their inherent values, expectations, normative influence, and the exertion of pressure in molding an organization's steadfastness to environmental responsibility. Stakeholder Theory underscores the insistency of recognizing and appropriately addressing the spectrum of stakeholder interests, which extend to sustainability and environmental concerns (Alpaslan et al., 2009 ). Such alignment serves as the catalyst for the augmentation of EP, harmoniously aligned with the values and expectations of the stakeholders. The discovery that GER act as moderators in shaping the connections among GSCI, SC, and EP aligns with the foundational tenets of institutional theory. These regulations serve as extraneous institutions that mold organizational conduct, with regulatory compliance augmenting the affirmative impact of green practices and SC on EP (Alpaslan et al., 2009 ). Institutional theory serves as the theoretical bedrock for elucidating the influence of GER on the intricate interplay among GSCI, SC, and EP within organizational contexts. This theoretical framework posits that organizations adhere to regulatory standards and embrace ecologically responsible practices to attain legitimacy, procure vital resources, and effectively respond to coercive pressures exerted by regulatory bodies (Darnall et al., 2008). This conformity with institutional paradigms, prioritizing sustainability, and environmental conscientiousness, ultimately ameliorates EP corroboration of the findings presented in the study. The revelation that TMC moderates the interactions between GSCI, SC, and EP is in harmony with the principles of TMC theory. TMC theory underscores the pivotal role that top leadership, including executives and senior managers, plays in spearheading strategic endeavors and enacting organizational transformations (Amir et al., 2020). In the context of sustainability and EP, this theory posits that the unwavering dedication of TMC to environmental responsibility and sustainability objectives holds substantial sway (Kitsis and Chen, 2021 ). It influences the organization's capacity to seamlessly integrate green practices into its supply chain and foster a sustainability culture, yielding a beneficial environmental performance effect. This alignment with TMC theory underscores the indispensable function of leadership in propelling sustainability initiatives and realizing environmental objectives within an organization (Esfahbodi et al., 2016 ). 5. Conclusion The study's findings shed light on several significant relationships between sustainable activity and EP. Firstly , the research confirms a positive link between STA and GSCI (H1). This indicates that organizations embracing sustainable technologies tend to incorporate environmentally affable exercises into their supply chain dealings. Secondly , STA is positively associated with developing a SC within organizations (H2), underscoring how embracing sustainable technologies can shape a corporate culture that values environmental responsibility and sustainability. Thirdly , the study verifies that GSCI is positively connected with improved EP (H3), highlighting the benefits of integrating eco-friendly activity into supply chain dealings. In line with this, an organization's strong SC is also positively connected to enhanced EP (H4), emphasizing the importance of fostering a corporate culture that prioritizes sustainability. GER act as moderators in the state among GSCI, SC, and EP (H5 and H6), implying that the regulatory environment can influence the effect of green patterns and an SC on EP. Compliance with environmental regulations can enhance the positive effects of these factors on EP. Lastly , TMC is a key moderator in the relation among GSCI, SC, and EP (H7 and H8). The commitment and support of TMC play a pivotal role in determining how GSCI practices and cultivating an SC translates into improved EP. 5.1 Theoretical and Practical Implications Practical implications from this research content a comprehensive model for organizations seeking to better their environmental responsibility and sustainability efforts. STA is a crucial starting point, as it enhances EP and facilitates combining eco-friendly practices across the supply chain. Fostering a SC within the organization can be achieved through STA, training, and promoting environmentally conscious behaviors among employees. GSCI practices, like sustainable sourcing and waste reduction, are key to enhancing overall EP. Compliance with GER is essential for legal adherence and amplifying the positive impacts of GSCI and SC on EP. The TMC is pivotal, influencing the thriving execution of green preparation and SC. Transparent reporting and communication about sustainability efforts can improve an organization's reputation and stakeholder relationships. Collaboration with supply chain partners and active employee engagement strengthen the SC and drive environmental improvements. Recognizing environmental responsibility as an ongoing commitment, organizations should continually assess and adapt their sustainable practices to align with evolving regulations and emerging technologies. Lastly, establishing performance metrics and key indicators for tracking EP enables data-driven decision-making and setting specific sustainability goals, ensuring continuous progress toward sustainability objectives. This study has substantial theoretical implications. It introduces the sustainability integration framework, highlighting the interconnected effects of STA, GSCI, and SC on EP. It underscores the theoretical roles of GER and TMC in shaping these relationships. The study emphasizes using key performance indicators (KPIs) to theoretically measure EP. It advances theory by demonstrating the causes of organizational culture on sustainability and highlights the complex interplay of multiple factors. The research calls for longitudinal studies and incorporates various theoretical perspectives, contributing to a better understanding of sustainability as a multidisciplinary concept. Additionally, it highlights the complexity of sustainability research, prompting the development of more significance theoretical models. 5.2 Future Research and Limitations This research offers both potential and limitations for future studies. Limitations include context-specific constraints, potential bias in self-reported data, and a limited ability to capture dynamic changes due to the cross-sectional design. The study's focus on moderating factors may not encompass all contextual variables, and there is room for improving the measurement of sustainability-related constructs. Future research directions include cross-industry and regional comparisons, longitudinal studies for long-term sustainability effects, exploration of emerging technologies (e.g., IoT and renewable energy), and understanding the impact of consumer preferences and regulatory changes on sustainability efforts. Further research can investigate supply chain complexity, transparent sustainability reporting effects, and the alignment of corporate social responsibility (CSR) with environmental objectives. Exploring the interaction between sustainability and innovation and the role of employee engagement in fostering sustainability culture are also promising areas of study. Declarations -Ethical Approval This document officially confirms ethical approval for the research project. Key ethical considerations include: Informed Consent: Participants are fully informed and voluntarily consent to participation, understanding the research's purpose, procedures, and potential impacts. Voluntariness: Participants are free to withdraw at any stage without repercussions, and no coercion is employed to secure participation. Confidentiality: Stringent measures safeguard participant confidentiality, preventing inadvertent disclosure of personal information. Protection of Sensitive Information: Sensitive data shared by participants is handled discreetly and is not disclosed in publications or reports. Right to Withdraw: Participants have an unequivocal right to withdraw without adverse consequences, and the withdrawal process is straightforward. Institutional Review Board (IRB) Approval: The research has received formal approval from the IRB, ensuring adherence to ethical standards and regulations. Publication Safeguards: Participants are aware of the intention to publish, with precautions taken to maintain confidentiality and privacy in publications. Acknowledgment of Contributions: Authors and contributors will be duly acknowledged in resulting publications, ensuring transparency and ethical practice. The research adheres to ethical principles, international guidelines, and regulatory requirements, emphasizing the team's commitment to participants' rights, well-being, and confidentiality. Inquiries or concerns can be directed to the principal investigator or the designated contact person listed in the informed consent materials. -Consent to Participate In seeking your participation in this research study, we want to provide you with a clear understanding of the purpose, procedures, and potential impact of our investigation into the interplay between government regulations, top management influence, and their effects on the environmental performance of manufacturing firms. The study specifically explores the connections among these factors with a focus on the green supply chain, organizational culture, and technology adoption within manufacturing firms. Your participation in this study is vital for advancing our understanding of the complex relationships between government regulations, top management influence, and environmental performance in manufacturing firms. By agreeing to participate, you contribute to the broader knowledge in this field, potentially influencing future practices and policies. If you have any questions or concerns about your participation, please do not hesitate to reach out to the research team. Your cooperation is highly valued and we appreciate your thoughtful consideration of this consent request. -Consent to Publish In addition to seeking your consent to participate in our research study on the relationships among government regulations, top management influence, and environmental performance in manufacturing firms, we also seek your permission to publish the outcomes of this study. Your consent to publish is an essential aspect of our research process. It enables us to share valuable insights with the academic community, industry practitioners, and policymakers. We appreciate your willingness to contribute to the dissemination of knowledge in this field. If you have any concerns or questions regarding the publication aspect of this study, please feel free to reach out to the research team for further clarification. Your cooperation and participation are highly valued, and we look forward to responsibly sharing the outcomes of this research. -Authors Contributions Saqib Mehmood: Data Gathering, Result Interpretation Samera Nazir: Data Analysis, Interpretation Jianqiang Fan: Proof Reading, Result Analysis Zarish Nazir: Software Run, Amad Shoukat: Software Run. Result Interpretation. -Funding There is no Funding from anyone. -Competing Interests I have no conflict of interest with anyone. References AB HAMID, M., SAMI, W. & SIDEK, M. M. Discriminant validity assessment: Use of Fornell & Larcker criterion versus HTMT criterion. Journal of Physics: Conference Series, 2017. IOP Publishing, 012163. ABDEL-BASET, M., CHANG, V. & GAMAL, A. 2019. Evaluation of the green supply chain management practices: A novel neutrosophic approach. Computers in Industry, 108 , 210-220. ABUZAWIDA, S. S., ALZUBI, A. B. & IYIOLA, K. 2023. Sustainable Supply Chain Practices: An Empirical Investigation from the Manufacturing Industry. Sustainability, 15 , ALAEDDIN, O., SHAWTARI, F. A. M., SALEM, M. A. & ALTOUNJY, R. 2019. The effect of management accounting systems in influencing environmental uncertainty, energy efficiency and environmental performance. International Journal of Energy Economics and Policy, 9 , 346-352. ALPASLAN, C. M., GREEN, S. E. & MITROFF, I. I. 2009. Corporate governance in the context of crises: Towards a stakeholder theory of crisis management. Journal of contingencies and crisis management, 17 , 38-49. AMIR, M., REHMAN, S. A. & KHAN, M. I. 2020. Mediating role of environmental management accounting and control system between top management commitment and environmental performance: A legitimacy theory. Journal of Management and Research, 7 , 132-160. ARAGÓN-CORREA, J. A. & SHARMA, S. 2003. A contingent resource-based view of proactive corporate environmental strategy. Academy of management review, 28 , 71-88. ARIMURA, T. H., DARNALL, N. & KATAYAMA, H. 2011. Is ISO 14001 a gateway to more advanced voluntary action? The case of green supply chain management. Journal of environmental economics and management, 61 , 170-182. ARMSTRONG, J. S. & OVERTON, T. S. 1977. Estimating nonresponse bias in mail surveys. Journal of marketing research, 14 , 396-402. AWAN, U., KRASLAWSKI, A. & HUISKONEN, J. 2017. Understanding the relationship between stakeholder pressure and sustainability performance in manufacturing firms in Pakistan. Procedia Manufacturing, 11 , 768-777. BACON, D. R., SAUER, P. L. & YOUNG, M. 1995. Composite reliability in structural equations modeling. Educational and psychological measurement, 55 , 394-406. BASSETTI, T., BLASI, S. & SEDITA, S. R. 2021. The management of sustainable development: A longitudinal analysis of the effects of environmental performance on economic performance. Business Strategy and the Environment, 30 , 21-37. BELTRÁN-RODRÍGUEZ, L., VALDEZ-HERNÁNDEZ, J. I., SAYNES-VÁSQUEZ, A., BLANCAS, J., SIERRA-HUELSZ, J. A., CRISTIANS, S., MARTÍNEZ-BALLESTÉ, A., ROMERO-MANZANARES, A., LUNA-CAVAZOS, M. & BORJA DE LA ROSA, M. A. 2021. Sustaining medicinal barks: survival and bark regeneration of Amphipterygium adstringens (Anacardiaceae), a tropical tree under experimental debarking. Sustainability, 13 , BENZIDIA, S., MAKAOUI, N. & BENTAHAR, O. 2021. The impact of big data analytics and artificial intelligence on green supply chain process integration and hospital environmental performance. Technological forecasting and social change, 165 , BOCKEN, N., MILLER, K. & EVANS, S. 2016. Assessing the environmental impact of new Circular business models. Proceedings of the “New Business Models”—Exploring a Changing View on Organizing Value Creation, Toulouse, France, 1 , 16-17. CAIADO, R. G. G., QUELHAS, O. L. G., NASCIMENTO, D. L. D. M., ANHOLON, R. & LEAL FILHO, W. 2019. Towards sustainability by aligning operational programmes and sustainable performance measures. Production Planning & Control, 30 , 413-425. CARTER, C. R. & ROGERS, D. S. 2008. A framework of sustainable supply chain management: moving toward new theory. International journal of physical distribution & logistics management, 38 , 360-387. CHEN, A. P. S., HUANG, Y.-F. & DO, M.-H. 2022. Exploring the Challenges to Adopt Green Initiatives to Supply Chain Management for Manufacturing Industries. Sustainability, 14 , CHIN, W. W. 2009. Bootstrap cross-validation indices for PLS path model assessment. Handbook of partial least squares: Concepts, methods and applications. COENEN, J., BAGER, S., MEYFROIDT, P., NEWIG, J. & CHALLIES, E. 2021. Environmental governance of China's belt and road initiative. Environmental Policy and Governance, 31 , 3-17. COSENZ, F., RODRIGUES, V. P. & ROSATI, F. 2020. Dynamic business modeling for sustainability: Exploring a system dynamics perspective to develop sustainable business models. Business Strategy and the Environment, 29 , 651-664. DARNALL, N., JOLLEY, G. J. & HANDFIELD, R. 2008. Environmental management systems and green supply chain management: complements for sustainability? Business strategy and the environment, 17 , 30-45. DUBEY, R., GUNASEKARAN, A. & ALI, S. S. 2015. Exploring the relationship between leadership, operational practices, institutional pressures and environmental performance: A framework for green supply chain. International Journal of Production Economics, 160 , 120-132. EL-HADDADEH, R., OSMANI, M., HINDI, N. & FADLALLA, A. 2021. Value creation for realising the sustainable development goals: Fostering organisational adoption of big data analytics. Journal of Business Research, 131 , 402-410. EL-KASSAR, A.-N. & SINGH, S. K. 2019. Green innovation and organizational performance: The influence of big data and the moderating role of management commitment and HR practices. Technological forecasting and social change, 144 , 483-498. ELTAYEB, T. K., ZAILANI, S. & RAMAYAH, T. 2011. Green supply chain initiatives among certified companies in Malaysia and environmental sustainability: Investigating the outcomes. Resources, conservation and recycling, 55 , 495-506. ESFAHBODI, A., ZHANG, Y., LIU, Y. & GENG, D. 2023. The fallacy of profitable green supply chains: The role of green information systems (GIS) in attenuating the sustainability trade-offs. International Journal of Production Economics, 255 , ESFAHBODI, A., ZHANG, Y. & WATSON, G. 2016. Sustainable supply chain management in emerging economies: Trade-offs between environmental and cost performance. International Journal of Production Economics, 181 , 350-366. GADENNE, D. L., KENNEDY, J. & MCKEIVER, C. 2009. An empirical study of environmental awareness and practices in SMEs. Journal of Business Ethics, 84 , 45-63. GILAL, F. G., ASHRAF, Z., GILAL, N. G., GILAL, R. G. & CHANNA, N. A. 2019. Promoting environmental performance through green human resource management practices in higher education institutions: A moderated mediation model. Corporate Social Responsibility and Environmental Management, 26 , 1579-1590. GLASMEIER, A. K. & FARRIGAN, T. L. 2003. Poverty, sustainability, and the culture of despair: can sustainable development strategies support poverty alleviation in America's most environmentally challenged communities? The Annals of the American Academy of Political and Social Science, 590 , 131-149. GUO, X., XIA, W., FENG, T. & SHENG, H. 2022. Sustainable supply chain finance adoption and firm performance: Is green supply chain integration a missing link? Sustainable Development, 30 , 1135-1154. HAIR, J. F., HULT, G. T. M., RINGLE, C. M., SARSTEDT, M. & THIELE, K. O. 2017. Mirror, mirror on the wall: a comparative evaluation of composite-based structural equation modeling methods. Journal of the academy of marketing science, 45 , 616-632. HAIR, J. F., RINGLE, C. M. & SARSTEDT, M. 2013. Partial least squares structural equation modeling: Rigorous applications, better results and higher acceptance. Long range planning, 46 , 1-12. HAIR, J. F., SARSTEDT, M., RINGLE, C. M. & MENA, J. A. 2012. An assessment of the use of partial least squares structural equation modeling in marketing research. Journal of the academy of marketing science, 40 , 414-433. HAIR JR, J. F., HULT, G. T. M., RINGLE, C. M., SARSTEDT, M., DANKS, N. P., RAY, S., HAIR, J. F., HULT, G. T. M., RINGLE, C. M. & SARSTEDT, M. 2021. An introduction to structural equation modeling. Partial least squares structural equation modeling (PLS-SEM) using R: a workbook , 1-29. HAN, Z. & HUO, B. 2020. The impact of green supply chain integration on sustainable performance. Industrial Management & Data Systems, 120 , 657-674. HE, J. & KIM, H. 2021. The effect of socially responsible HRM on organizational citizenship behavior for the environment: A proactive motivation model. Sustainability, 13 , HENSELER, J., RINGLE, C. M. & SARSTEDT, M. 2015. A new criterion for assessing discriminant validity in variance-based structural equation modeling. Journal of the academy of marketing science, 43 , 115-135. HERAS‐SAIZARBITORIA, I., BOIRAL, O. & DÍAZ DE JUNGUITU, A. 2020. Environmental management certification and environmental performance: Greening or greenwashing? Business Strategy and the Environment, 29 , 2829-2841. HUSSAIN, N., RIGONI, U. & ORIJ, R. P. 2018. Corporate governance and sustainability performance: Analysis of triple bottom line performance. Journal of business ethics, 149 , 411-432. ILYAS, S., HU, Z. & WIWATTANAKORNWONG, K. 2020. Unleashing the role of top management and government support in green supply chain management and sustainable development goals. Environmental Science and Pollution Research, 27 , 8210-8223. IRALDO, F., TESTA, F., MELIS, M. & FREY, M. 2011. A literature review on the links between environmental regulation and competitiveness. Environmental Policy and Governance, 21 , 210-222. JASIŃSKI, D., MEREDITH, J. & KIRWAN, K. 2021. Sustainable development model for measuring and managing sustainability in the automotive sector. Sustainable Development, 29 , 1123-1137. JAVAID, M., HALEEM, A., SINGH, R. P., SUMAN, R. & GONZALEZ, E. S. 2022. Understanding the adoption of Industry 4.0 technologies in improving environmental sustainability. Sustainable Operations and Computers, 3 , 203-217. JAZAIRY, A. & VON HAARTMAN, R. 2020. Analysing the institutional pressures on shippers and logistics service providers to implement green supply chain management practices. International Journal of Logistics Research and Applications, 23 , 44-84. KITSIS, A. M. & CHEN, I. J. 2021. Do stakeholder pressures influence green supply chain Practices? Exploring the mediating role of top management commitment. Journal of Cleaner Production, 316 , KOLK, A. & PINKSE, J. 2010. The integration of corporate governance in corporate social responsibility disclosures. Corporate social responsibility and environmental management, 17 , 15-26. KOUHIZADEH, M., SABERI, S. & SARKIS, J. 2021. Blockchain technology and the sustainable supply chain: Theoretically exploring adoption barriers. International journal of production economics, 231 , KOVAL, V., OLCZAK, P., VDOVENKO, N., BOIKO, O., MATUSZEWSKA, D. & MIKHNO, I. 2021. Ecosystem of environmentally sustainable municipal infrastructure in the Ukraine. Sustainability 2021, 13, 10223. s Note: MDPI stays neutral with regard to jurisdictional claims in published …. KUMAR, N., BRINT, A., SHI, E., UPADHYAY, A. & RUAN, X. 2019. Integrating sustainable supply chain practices with operational performance: an exploratory study of Chinese SMEs. Production Planning & Control, 30 , 464-478. LABELLA-FERNÁNDEZ, A., SERRANO-ARCOS, M. M. & PAYÁN-SÁNCHEZ, B. 2021. Firm growth as a driver of sustainable product innovation: Mediation and moderation analysis. Evidence from manufacturing firms. International journal of environmental research and public health, 18 , LĂZĂROIU, G., IONESCU, L., ANDRONIE, M. & DIJMĂRESCU, I. 2020. Sustainability management and performance in the urban corporate economy: a systematic literature review. Sustainability, 12 , LI, C. S., WONG, C. W., WONG, C. Y., BOON-ITT, S. & MIAO, X. 2023. Empirical research on performance effects of supply chain resilience: Systematic literature review, citation network analysis and future research directions. International Journal of Shipping and Transport Logistics, 17 , 80-106. LINNENLUECKE, M. K. & GRIFFITHS, A. 2010. Corporate sustainability and organizational culture. Journal of world business, 45 , 357-366. LIU, H., ZAFAR, M. W., SINHA, A. & KHAN, I. 2023. The path to sustainable environment: Do environmental taxes and governance matter? Sustainable Development . LO, M.-C., RAMAYAH, T. & HUI, H. L. H. 2014. Rural communities perceptions and attitudes towards environment tourism development. Journal of Sustainable Development, 7 , LU, J., LIANG, M., ZHANG, C., RONG, D., GUAN, H., MAZEIKAITE, K. & STREIMIKIS, J. 2021. Assessment of corporate social responsibility by addressing sustainable development goals. Corporate Social Responsibility and Environmental Management, 28 , 686-703. MAKHLOUFI, L., LAGHOUAG, A. A., MEIRUN, T. & BELAID, F. 2022. Impact of green entrepreneurship orientation on environmental performance: The natural resource‐based view and environmental policy perspective. Business Strategy and the Environment, 31 , 425-444. MAKSIMOVIC, M. 2018. Greening the future: Green Internet of Things (G-IoT) as a key technological enabler of sustainable development. Internet of things and big data analytics toward next-generation intelligence , 283-313. MELA, C. F. & KOPALLE, P. K. 2002. The impact of collinearity on regression analysis: the asymmetric effect of negative and positive correlations. Applied Economics, 34 , 667-677. MELVILLE, N. P. 2010. Information systems innovation for environmental sustainability. MIS quarterly , 1-21. MUMTAZ, M. Z. & SMITH, Z. A. 2019. Green finance for sustainable development in Pakistan. IPRI Journal, 19 , 1-34. NOVITASARI, M., WIJAYA, A. L., AGUSTIN, N. M., GUNARDI, A. & DANA, L. P. 2023. Corporate social responsibility and firm performance: Green supply chain management as a mediating variable. Corporate Social Responsibility and Environmental Management, 30 , 267-276. NUREEN, N., XIN, Y., IRFAN, M. & FAHAD, S. 2023. Going green: how do green supply chain management and green training influence firm performance? Evidence from a developing country. Environmental Science and Pollution Research, 30 , 57448-57459. PAGELL, M. & WU, Z. 2009. Building a more complete theory of sustainable supply chain management using case studies of 10 exemplars. Journal of supply chain management, 45 , 37-56. PAULRAJ, A. 2011. Understanding the relationships between internal resources and capabilities, sustainable supply management and organizational sustainability. Journal of Supply Chain Management, 47 , 19-37. PETTIT, T. J., CROXTON, K. L. & FIKSEL, J. 2013. Ensuring supply chain resilience: development and implementation of an assessment tool. Journal of business logistics, 34 , 46-76. PODSAKOFF, P. M. & ORGAN, D. W. 1986. Self-reports in organizational research: Problems and prospects. Journal of management, 12 , 531-544. PRETTY, J., BENTON, T. G., BHARUCHA, Z. P., DICKS, L. V., FLORA, C. B., GODFRAY, H. C. J., GOULSON, D., HARTLEY, S., LAMPKIN, N. & MORRIS, C. 2018. Global assessment of agricultural system redesign for sustainable intensification. Nature Sustainability, 1 , 441-446. RASOOL, S. F., WANG, M., ZHANG, Y. & SAMMA, M. 2020. Sustainable work performance: the roles of workplace violence and occupational stress. International journal of environmental research and public health, 17 , RAUB, S. P. & MARTIN-RIOS, C. 2019. “Think sustainable, act local”–a stakeholder-filter-model for translating SDGs into sustainability initiatives with local impact. International Journal of Contemporary Hospitality Management, 31 , 2428-2447. ROSCOE, S., SUBRAMANIAN, N., JABBOUR, C. J. & CHONG, T. 2019. Green human resource management and the enablers of green organisational culture: Enhancing a firm's environmental performance for sustainable development. Business Strategy and the Environment, 28 , 737-749. RUSSO, M. V. & HARRISON, N. S. 2005. Organizational design and environmental performance: Clues from the electronics industry. Academy of Management Journal, 48 , 582-593. SAHOO, P. B. B. & THAKUR, V. 2023. Enhancing the performance of Indian micro, small and medium enterprises by implementing supply chain finance: challenges emerging from COVID-19 pandemic. Benchmarking: An International Journal, 30 , 2110-2138. SAHOO, S., KUMAR, A. & UPADHYAY, A. 2023. How do green knowledge management and green technology innovation impact corporate environmental performance? Understanding the role of green knowledge acquisition. Business Strategy and the Environment, 32 , 551-569. SAHU, A. K., RAUT, R. D., GEDAM, V. V., CHEIKHROUHOU, N. & SAHU, A. K. 2023. Lean–agile–resilience–green practices adoption challenges in sustainable agri‐food supply chains. Business Strategy and the Environment, 32 , 3272-3291. SHAFIQUE, I., KALYAR, M. N. & MEHWISH, N. 2021. Organizational ambidexterity, green entrepreneurial orientation, and environmental performance in SMEs context: Examining the moderating role of perceived CSR. Corporate Social Responsibility and Environmental Management, 28 , 446-456. SHAHZAD, M., QU, Y., ZAFAR, A. U. & APPOLLONI, A. 2021. Does the interaction between the knowledge management process and sustainable development practices boost corporate green innovation? Business Strategy and the Environment, 30 , 4206-4222. SHAHZAD, M., QU, Y., ZAFAR, A. U., REHMAN, S. U. & ISLAM, T. 2020. Exploring the influence of knowledge management process on corporate sustainable performance through green innovation. Journal of Knowledge Management, 24 , 2079-2106. SRIVASTAVA, S. K. 2007. Green supply‐chain management: a state‐of‐the‐art literature review. International journal of management reviews, 9 , 53-80. TIWARI, P., SADEGHI, J. K. & ESEONU, C. 2020. A sustainable lean production framework with a case implementation: Practice-based view theory. Journal of Cleaner Production, 277 , TSAI, K. H., HUANG, C. T. & CHEN, Z. H. 2020. Understanding variation in the relationship between environmental management practices and firm performance across studies: A meta‐analytic review. Business Strategy and the Environment, 29 , 547-565. TSENG, S.-M. 2014. The impact of knowledge management capabilities and supplier relationship management on corporate performance. International Journal of Production Economics, 154 , 39-47. WEI, Z., SHEN, H., ZHOU, K. Z. & LI, J. J. 2017. How does environmental corporate social responsibility matter in a dysfunctional institutional environment? Evidence from China. Journal of business ethics, 140 , 209-223. WIJETHILAKE, C. & LAMA, T. 2019. Sustainability core values and sustainability risk management: Moderating effects of top management commitment and stakeholder pressure. Business Strategy and the Environment, 28 , 143-154. WONG, C. Y., WONG, C. W. & BOON-ITT, S. 2020. Effects of green supply chain integration and green innovation on environmental and cost performance. International Journal of Production Research, 58 , 4589-4609. YARO, N. S. A., SUTANTO, M. H., BALOO, L., HABIB, N. Z., USMAN, A., YOUSAFZAI, A. K., AHMAD, A., BIRNIWA, A. H., JAGABA, A. H. & NOOR, A. 2023. A comprehensive overview of the utilization of recycled waste materials and technologies in asphalt pavements: towards environmental and sustainable low-carbon roads. Processes, 11 , YOO, W., MAYBERRY, R., BAE, S., SINGH, K., HE, Q. P. & LILLARD JR, J. W. 2014. A study of effects of multicollinearity in the multivariable analysis. International journal of applied science and technology, 4 , YOUNIS, H., SUNDARAKANI, B. & VEL, P. 2016. The impact of implementing green supply chain management practices on corporate performance. Competitiveness Review, 26 , 216-245. YU, Z., WAQAS, M., TABISH, M., TANVEER, M., HAQ, I. U. & KHAN, S. A. R. 2022. Sustainable supply chain management and green technologies: a bibliometric review of literature. Environmental Science and Pollution Research, 29 , 58454-58470. ZHENG, H., WANG, L., PENG, W., ZHANG, C., LI, C., ROBINSON, B. E., WU, X., KONG, L., LI, R. & XIAO, Y. 2019. Realizing the values of natural capital for inclusive, sustainable development: Informing China’s new ecological development strategy. Proceedings of the National Academy of Sciences, 116 , 8623-8628. ZHU, Q. & SARKIS, J. 2007. The moderating effects of institutional pressures on emergent green supply chain practices and performance. International journal of production research, 45 , 4333-4355. ZHU, Q., SARKIS, J. & LAI, K.-H. 2012. Examining the effects of green supply chain management practices and their mediations on performance improvements. International journal of production research, 50 , 1377-1394. ZHU, Q., SARKIS, J. & LAI, K.-H. 2013. Institutional-based antecedents and performance outcomes of internal and external green supply chain management practices. Journal of Purchasing and Supply Management, 19 , 106-117. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-3666203","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":267688891,"identity":"690ebf80-f7d4-4346-902a-d779a574973f","order_by":0,"name":"Saqib Mehmood","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA4klEQVRIiWNgGAWjYBACCQkIzcPG33zwAYjBR7QWPoljyQZgvcRqYZBjyFEDswlqkZzd/OzhjxprGTaGM2yVX3PsgAzmh49u4NEiLXPM3JjnWDoPG3Pvsduy25KBDmMzNs7Bo0VOIsFMmoHtMFDlubTbktuYgQweNmn8WtK/Sf74B9KSY1Ysua2esBZpiRwzCd42iBbGj9sOE9YiOSOnTJq3D+gXYCBLM247DvQUAb9I3EjfJvnjm7W9fH/zwY8/t1Xb87M3P3yMTwsUMENIHgSbSC2MP4hTPQpGwSgYBSMMAADrbT30AgcBJwAAAABJRU5ErkJggg==","orcid":"","institution":"Chang'an University","correspondingAuthor":true,"prefix":"","firstName":"Saqib","middleName":"","lastName":"Mehmood","suffix":""},{"id":267688892,"identity":"d68ef359-b8fc-4a1c-9db8-b1ef3909063b","order_by":1,"name":"Samera Nazir","email":"","orcid":"https://orcid.org/0009-0007-4220-4879","institution":"Chang'an University","correspondingAuthor":false,"prefix":"","firstName":"Samera","middleName":"","lastName":"Nazir","suffix":""},{"id":267688893,"identity":"d5fe1267-fd32-4f62-a3e5-786fce127e53","order_by":2,"name":"Jianqiang Fan","email":"","orcid":"","institution":"Changan University: Chang'an University","correspondingAuthor":false,"prefix":"","firstName":"Jianqiang","middleName":"","lastName":"Fan","suffix":""},{"id":267688894,"identity":"7a5ff8a1-51e5-4d1c-bd16-b68f05ab224d","order_by":3,"name":"Zarish Nazir","email":"","orcid":"","institution":"Chang'an University","correspondingAuthor":false,"prefix":"","firstName":"Zarish","middleName":"","lastName":"Nazir","suffix":""},{"id":267688895,"identity":"17898305-67e4-4c96-b1e4-4ce4717da11d","order_by":4,"name":"Amad Shoukat","email":"","orcid":"","institution":"Chang'an University","correspondingAuthor":false,"prefix":"","firstName":"Amad","middleName":"","lastName":"Shoukat","suffix":""}],"badges":[],"createdAt":"2023-11-26 06:37:18","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-3666203/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-3666203/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":49879184,"identity":"a31c8adb-3f00-49d0-9ba4-937754b7ad1c","added_by":"auto","created_at":"2024-01-19 15:01:06","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":171544,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cem\u003e\u003cstrong\u003eFramework for Research\u003c/strong\u003e\u003c/em\u003e\u003c/p\u003e","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-3666203/v1/2aa6941c8b2899ea2383aff9.png"},{"id":49878863,"identity":"e85080bc-5d6d-400c-aa56-a563aea55e13","added_by":"auto","created_at":"2024-01-19 14:53:06","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":299707,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cem\u003e\u003cstrong\u003eDisplays the model achieved following statistical testing\u003c/strong\u003e\u003c/em\u003e\u003c/p\u003e","description":"","filename":"floatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-3666203/v1/29fc11c855e0812854f8d674.png"},{"id":56921541,"identity":"927f8fc1-a09d-45fb-9b1e-c495d9d0af92","added_by":"auto","created_at":"2024-05-22 07:42:18","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1945539,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-3666203/v1/0488664b-2520-4b1b-92a0-90f1b1239330.pdf"}],"financialInterests":"","formattedTitle":"Government Regulations and Top Management Influence on Manufacturing Firms Environmental Performance: Nexus of Green Supply Chain , Culture and Technology Adoption","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eIn today's dynamic business landscape, the pursuit of environmental sustainability has become a paramount concern for manufacturing firms worldwide. This study delves into the intricate influences shaping these organizations' environmental performance (EP). Green supply chain integration (GSCI) highlights how green manufacturing improves performance and identifies collaboration needs (Wong et al., \u003cspan citationid=\"CR87\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Internal collaboration enhances overall sustainable performance. GSCI boosts market shares and profits (Eltayeb et al., \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2011\u003c/span\u003e), but lack of support leads to economic failure (Zhu et al., \u003cspan citationid=\"CR94\" class=\"CitationRef\"\u003e2012\u003c/span\u003e). Sustainable design practices improve income, employee welfare, and profits (Cosenz et al., 2020). Internal coordination enhances socially sustainable performance (Shahzad et al., \u003cspan citationid=\"CR80\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Sustainable technology adoption (STA) involves integrating eco-friendly technologies to reduce environmental impact. Key elements include renewable energy, energy efficiency, waste reduction, and green manufacturing (Koval et al., \u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). A green supply chain incorporates eco-friendly materials, efficient logistics, and responsible product disposal (Zhu et al., \u003cspan citationid=\"CR94\" class=\"CitationRef\"\u003e2012\u003c/span\u003e). Sustainable culture (SC) promotes environmental responsibility, social equity, and economic viability (Lu et al., \u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Government environmental regulations (GER) and top management commitment (TMC) shape sustainability initiatives (Wijethilake and Lama, \u003cspan citationid=\"CR86\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Supplier integration correlates with sustainable performance (Lăzăroiu et al., \u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Environmental performance (EP) assesses energy use, emission reduction, and resource management. It's about reducing emissions, waste, and accidents (Tiwari et al., 2020). EP aids in risk mitigation and policy formulation (Alaeddin et al., 2019).\u003c/p\u003e \u003cp\u003eWhile substantial empirical evidence supports a positive connection between green supply chain management (GSCM) pattern and firm execution, limited attention has been given to the factors that could modulate the nature and strength of this relationship (Dubey et al., \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). (Dubey et al., \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2015\u003c/span\u003e), examine the part of institutional pressure resulting from operational practices (e.g., TQM and customer relationship management) on EP. As scholars and practitioners in the tract of supply chain management increasingly recognize the value of the GSCM pattern, it's crucial to consider the growing environmental challenges (Chen et al., \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Consequently, adopting GSCM within organizations should be viewed as a source of value rather than a threat (Abdel-Baset et al., 2019). GER, including carbon emissions caps, eco-friendly mitigation methods, and a green culture to protect the planet's ecological well-being, are driving wider adoption across various firms, expanding its relevance in the corporate landscape (Zheng et al., \u003cspan citationid=\"CR92\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). GSCM involves the administration of data, resources, and investments, as fit as collaboration between supply chain businesses, to dynamically integrate objectives related to the three dimensions of property improvement; economical, cultural, and environmental. These objectives naturally align with the demands of stakeholders and consumers (Nureen et al., \u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). It's important to note that effective GSCM implementation necessitates a multifaceted approach (Sahu et al., \u003cspan citationid=\"CR77\" class=\"CitationRef\"\u003e2023\u003c/span\u003e) (Novitasari et al., \u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). As organizations strive for a more environmentally responsible future, a green supply chain, which offers economic benefits and ecological responsibility, should take precedence (Guo et al., \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). GSCM enhances the conventional concept of supply chain by adopting an ecologically responsible perspective, thereby improving the overall life cycle EP of products and services (Esfahbodi et al., \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). While the existing literature acknowledges the significance of STA, GSCI, SC, and EP, a research gap remains in comprehensively examining the interconnections between these elements. Additionally, few studies adequately address the moderating influence of GER and TMC in this circumstance (Makhloufi et al., \u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Therefore, there is a need for empirical research that systematically investigates how these components energetically affect sustainability outcomes within organizations, considering the regulatory and leadership frameworks that shape their implementation and effectiveness. This research purpose to furnish vision into the following inquiries.\u003c/p\u003e \u003cp\u003e \u003cb\u003eRQ1.\u003c/b\u003e How STA is associated with GSCI and SC.\u003c/p\u003e \u003cp\u003e \u003cb\u003eRQ2.\u003c/b\u003e How GSCI and SC are associated with EP.\u003c/p\u003e \u003cp\u003e \u003cb\u003eRQ3.\u003c/b\u003e How GER and TMC moderate the relationship between GSCI and SC with EP.\u003c/p\u003e \u003cp\u003eThis study aims to thoroughly investigate the relationships between Sustainability (STA), Global Supply Chain Integration (GSCI), Supply Chain (SC), and Environmental Performance (EP) within organizations. It also seeks to analyze the influences of Government Environmental Regulations (GER) and Top Management Commitment (TMC) on these relationships, providing insights into how external regulations and leadership affect sustainable practices in the fast-changing business environment.\u003c/p\u003e \u003cp\u003eThis study aids organizations in enhancing sustainability strategies by analyzing the effects of sustainable technology, green supply chains, and supply chain operations on environmental performance. It emphasizes the importance of government regulations and top management alignment and support. Ultimately, this research improves our understanding of the factors driving sustainability for better strategies and positive environmental results.\u003c/p\u003e \u003cp\u003eThis study is rooted in sustainability theory, emphasizing meeting present needs while safeguarding future generations. Concepts like STA, GSCI, and fostering SC align with this principle, striving for economic, social, and environmental sustainability. Resource dependence theory explains how organizations respond to external influences, including government regulations, shaping sustainability practices and performance. Institutional theory helps understand how organizations adhere to sustainability norms and regulations. The study explores responses to external pressures, like environmental regulations, in shaping sustainability initiatives. Stakeholder theory recognizes various stakeholders, such as government regulators and top management, as crucial in shaping sustainability initiatives. It provides a framework to analyze how stakeholder interests impact sustainable practices and environmental performance. Top management commitment theory emphasizes the critical role of top management in driving organizational change and sustainability initiatives. In the context of sustainability, the study examines how top management commitment influences approaches to sustainable technology adoption, green supply chains, and sustainability culture.\u003c/p\u003e \u003cp\u003eThese theories form the core framework for understanding how government environmental regulations, top management commitment, and their influence on manufacturing firms' environmental performance (EP) are interconnected, considering factors like GSCI, SC, and sustainable technology adoption.\u003c/p\u003e \u003cp\u003eA research framework is essential, offering a structured path for clarity, hypothesis development, theory testing, and rigor, enabling researchers to advance knowledge in their fields.\u003c/p\u003e \u003cp\u003eIn Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e, the study framework is displayed.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e"},{"header":"2. Hypothesis Development","content":"\u003cp\u003eThe research hypotheses presented below have been formulated following the earlier discussions.\u003c/p\u003e \u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e2.1 STA and GSCI\u003c/h2\u003e \u003cp\u003eSustainable Technology Adoption (STA) involves integrating and utilizing technologies that promote environmental sustainability resource efficiency and reduce negative environmental impacts within a company's operations. This can encompass various applications such as inexhaustible strength methods, energy-economical machinery, material change applications, and sustainable transportation systems (Melville, \u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e2010\u003c/span\u003e) (Caiado et al., \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2019\u003c/span\u003e); (Maksimovic, \u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e2018\u003c/span\u003e, Javaid et al., \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Green Supply Chain Integration (GSCI) involves incorporating environmentally sustainable practices throughout the supply chain, encompassing environmentally friendly sourcing, manufacturing, transportation, and distribution processes (Li et al., \u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e2023\u003c/span\u003e) (Han and Huo, \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Companies embracing GSCI focus on reducing their carbon footprint, minimizing waste, optimizing resource utilization, and ensuring responsible sourcing and disposal (Kumar et al., \u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). STA leads to reduced environmental impacts within supply chains, aligning with research by (Carter and Rogers, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2008\u003c/span\u003e), which emphasizes sustainable practices. Advanced technologies like RFID and GPS improve real-time monitoring and tracking, vital for achieving green supply chain goals (Zhu et al., \u003cspan citationid=\"CR95\" class=\"CitationRef\"\u003e2013\u003c/span\u003e). STA fosters collaboration and data mutuality between supply chain relations, which is crucial for GSCI (Tseng, \u003cspan citationid=\"CR84\" class=\"CitationRef\"\u003e2014\u003c/span\u003e). It enhances resource efficiency, waste reduction, and compliance with environmental regulations and standards (Wijethilake and Lama, \u003cspan citationid=\"CR86\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Additionally, it positively impacts corporate reputation and customer perception while contributing to cost savings and resilience in supply chains (Bocken et al., \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2016\u003c/span\u003e) (Pettit et al., \u003cspan citationid=\"CR68\" class=\"CitationRef\"\u003e2013\u003c/span\u003e). Based on these findings, we formulate the following hypothesis:\u003c/p\u003e \u003cp\u003e \u003cb\u003eH1: STA is positively connected with GSCI.\u003c/b\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e2.2 STA and SC\u003c/h2\u003e \u003cp\u003eSTA involves assimilating and utilizing technologies designed to minimize environmental impact, optimize resource utilization, and contribute to sustainability objectives (Shahzad et al., \u003cspan citationid=\"CR79\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). A sustainability culture (SC) encompasses the values, norms, attitudes, and behaviors of individuals or organizations concerning sustainability and environmental responsibility (Wei et al., \u003cspan citationid=\"CR85\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). When sustainability principles are deeply ingrained in an organization's or an individual's core values, they guide decision-making processes, leading to a robust SC (Jasiński et al., 2021). Research indicates that a strong SC within an organization encourages stakeholders' integration of sustainable technologies, aligning with the organization's environmental objectives (Sahoo et al., \u003cspan citationid=\"CR76\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). (Wei et al., \u003cspan citationid=\"CR85\" class=\"CitationRef\"\u003e2017\u003c/span\u003e), empirical studies demonstrate that organizations with a well-established SC are more likely to invest in STA, given the emphasis on reducing environmental impact and promoting sustainability (Liu et al., \u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). The prioritization of sustainability within the culture catalyzes the proactive adoption of technologies aligned with environmental goals (Raub and Martin-Rios, \u003cspan citationid=\"CR72\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). While organizations ingrained with an SC tend to be more open to adopting sustainable technologies (Pretty et al., \u003cspan citationid=\"CR70\" class=\"CitationRef\"\u003e2018\u003c/span\u003e), In environments where a sustainability culture is deeply rooted, there is a noticeable increase in incorporating sustainable technologies, fostering innovation and facilitating seamless adoption (El-Haddadeh et al., \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Additionally, within communities or networks embracing an SC, individuals can parcel data and mutually encourage the adoption of sustainable technologies, supporting the idea of a positive association between SC and technology adoption (Beltr\u0026aacute;n-Rodr\u0026iacute;guez et al., \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). This collective effort further propels the integration of sustainable technologies toward a more sustainable future. Basis on these findings we formulate following hypothesis:\u003c/p\u003e \u003cp\u003e \u003cb\u003eH2: STA is positively connected with SC.\u003c/b\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003e2.3 GSCI and EP.\u003c/h2\u003e \u003cp\u003eGSCI involves incorporating environmentally affable practices and principles end-to-end in the supply chain. This includes sustainably sourcing raw materials, optimizing transportation to reduce emissions, adopting eco-friendly packaging, and implementing efficient waste management (Younis et al., \u003cspan citationid=\"CR90\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). EP measures a company's ability to minimize its environmental impact, considering factors like carbon discharge decrease, strength efficiency, waste reduction, water preservation, and compliance with environmental regulations (Mumtaz and Smith, \u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). EP is enhanced through strategies such as sourcing sustainable materials and collaborating with eco-friendly suppliers (Pagell and Wu, \u003cspan citationid=\"CR66\" class=\"CitationRef\"\u003e2009\u003c/span\u003e) By integrating sustainable practices into their supply chains, companies reduce resource consumption, waste generation, and emissions, resulting in improved EP (Bassetti et al., \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). This integration is vital for reducing environmental accidents, pollution, hazardous components, and solid waste, ultimately benefiting the company and society (Esfahbodi et al., \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2016\u003c/span\u003e), Effective integration of environmentally sustainable practices leads to notable improvements in EP metrics, including reduced carbon emissions, minimized waste, and enhanced resource efficiency, underlining the positive impact of GSCI on overall sustainability (Maksimovic, \u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). Aligning supply chain processes with sustainability objectives by adopting eco-friendly sourcing, production, and distribution practices further associates with favorable outcomes in EP (Abuzawida et al., \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Basis on these findings we formulate following hypothesis:\u003c/p\u003e \u003cp\u003e \u003cb\u003eH3: GSCI is positively related to EP.\u003c/b\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003e2.4 SC and EP\u003c/h2\u003e \u003cp\u003eSC in an organization center on values, beliefs, norms, and practices emphasizing environmental sustainability. This entails integrating sustainability into the organizational culture with leadership endorsement, employee involvement, and a focus on sustainable practices (Roscoe et al., \u003cspan citationid=\"CR73\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). EP pertains to an organization's effectiveness in managing its environmental impact, encompassing reducing greenhouse gas emissions, conserving resources, waste reduction, and compliance with environmental standards (Yaro et al., \u003cspan citationid=\"CR88\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). A strong SC promotes collective commitment to environmental responsibility and encourages environmentally conscious behaviors among employees, like waste reduction and energy conservation (Yaro et al., \u003cspan citationid=\"CR88\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). This heightened dedication correlates with improved EP, ultimately leading to reduced ecological impact and a sustainable organizational and environmental future (Sahoo and Thakur, \u003cspan citationid=\"CR75\" class=\"CitationRef\"\u003e2023\u003c/span\u003e) (Gilal et al., \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2019\u003c/span\u003e), establish a supportive nexus among firm cultural execution, including SC and EP, supporting the belief that a robust SC enhances environmental outcomes.\u003c/p\u003e \u003cp\u003eAdditionally, studies by (He and Kim, \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2021\u003c/span\u003e), demonstrated that participation in voluntary environmental programs driven by a proactive SC is linked to improved EP. Furthermore, (Russo and Harrison, \u003cspan citationid=\"CR74\" class=\"CitationRef\"\u003e2005\u003c/span\u003e), concluded that companies with a strong SC exhibit better EP, reaffirming the connection between sustainability culture and environmental outcomes. These studies support Hypothesis H4 by confirming a supportive state among SC and EP within organizations. Founded on this collection, we develop the pursuing hypothesis:\u003c/p\u003e \u003cp\u003e \u003cb\u003eH4: SC is positively connected with EP.\u003c/b\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003e2.5 GER moderate between GSCI and EP\u003c/h2\u003e \u003cp\u003eGovernment environmental regulations (GER) encompass laws, policies, and directives instituted by governmental bodies, spanning local, regional, and national levels, to oversee and manage environmental concerns. These regulations guide organizations, promoting sustainable practices and mitigating environmental impacts (Coenen et al., \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). GSCI involves infusing environmentally sustainable practices end-to-end into the supply chain, from material root to direction, necessitating collaboration among supply chain partners for minimal environmental harm and heightened sustainability (Wong et al., \u003cspan citationid=\"CR87\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). EP evaluation involves assessing an organization's activities and operations to manage and diminish its environmental footprint while complying with pertinent standards and objectives (Benzidia et al., \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Several studies highlight the state of GER and GSCM patterns. (Zhu and Sarkis, \u003cspan citationid=\"CR93\" class=\"CitationRef\"\u003e2007\u003c/span\u003e), affirm that stringent government regulations reinforce the positive connection between GSCI and EP. (Darnall et al., 2008), assert that government regulations drive companies to integrate GSCM patterns, enhancing EP. (Han and Huo, \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2020\u003c/span\u003e), strict environmental regulations augment the supportive relationship between the GSCM pattern and EP. (Kolk and Pinkse, \u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e2010\u003c/span\u003e) underline GER's role in influencing corporate environmental strategies, driving environmentally friendly practices adoption. Additionally, (Rasool et al., \u003cspan citationid=\"CR71\" class=\"CitationRef\"\u003e2020\u003c/span\u003e) (Zhu et al., \u003cspan citationid=\"CR94\" class=\"CitationRef\"\u003e2012\u003c/span\u003e), reiterates the positive influence of stringent environmental regulations in enhancing the association between GSCI and EP, emphasizing the helpful role of government regulations in promoting environmentally responsible business behavior. Based on these findings, we formulate following hypothesis:\u003c/p\u003e \u003cp\u003e \u003cb\u003eH5: GER moderates the state between GSCI and EP.\u003c/b\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003e2.6 GER moderates between SC and EP\u003c/h2\u003e \u003cp\u003eAs defined by [61], SC encompasses an organization's shared commitment to integrating environmental, social, and economic sustainability into decision-making and operations. As outlined by [55], GER serves as laws and policies enacted to regulate and manage environmental issues, guiding organizations toward sustainable practices. EP, as examined by (Gilal et al., \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2019\u003c/span\u003e), involves measuring an organization's environmental impact and compliance with environmental standards and goals. Research by (Gadenne et al., \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2009\u003c/span\u003e), explores how environmental awareness and compliance with government regulations influence the environmental practices of SMEs, shedding light on the role of regulations in shaping SC. (Kolk and Pinkse, \u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e2010\u003c/span\u003e), investigate the role of GER in shaping societal and environmental obligations within supply chains, emphasizing how regulations moderate the relationship between SC and EP. (Shafique et al., \u003cspan citationid=\"CR78\" class=\"CitationRef\"\u003e2021\u003c/span\u003e), stringent GER motivates firms with an SC to adopt eco-friendly practices, positively impacting their EP. (Zheng et al., \u003cspan citationid=\"CR92\" class=\"CitationRef\"\u003e2019\u003c/span\u003e), discovered that organizations with a strong SC thrive under stricter regulatory environments, indicating the value of SC in achieving superior EP. (Iraldo et al., \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e2011\u003c/span\u003e), emphasize the importance of regulatory frameworks as complements to internal SC, as government regulations provide standardized rules and incentives guiding organizations towards sustainable practices and enhancing their EP. Founded on these collection we formulate the pursuing hypothesis:\u003c/p\u003e \u003cp\u003e \u003cb\u003eH6: GER moderates the relationship between SC and EP.\u003c/b\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003e2.7 TMC moderates among GSCI and EP\u003c/h2\u003e \u003cp\u003eTo reduce the supply chain's environmental impact, GSCI integrates environmental considerations into supply chain processes, including commodity plans, substantial points, manufacture, transportation, and waste management (Younis et al., \u003cspan citationid=\"CR90\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). This integration is assessed through indicators such as carbon emissions, water and energy consumption, waste generation, recycling rates, and compliance with environmental regulations, measuring how a company's operations affect the environment. TMC signifies the dedication and support of senior leadership toward implementing and maintaining environmentally sustainable practices within the company. It entails resource allocation, goal setting, and communicating the importance of environmental sustainability throughout the organization (Jasiński et al., 2021). TMC moderates the state among GSCI and EP, indicating that the impact of integrating green practices is contingent on top management's commitment level (Ilyas et al., 2020). Studies emphasize that a strong TMC fosters a society of environmental responsibility within the structure, influencing decisions and practices throughout the supply chain (Jazairy and von Haartman, \u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e2020\u003c/span\u003e) (Arag\u0026oacute;n-Correa and Sharma, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2003\u003c/span\u003e). This commitment enhances the prioritization, monitoring, and effective execution of the GSCM pattern, ultimately improving EP (Srivastava, \u003cspan citationid=\"CR81\" class=\"CitationRef\"\u003e2007\u003c/span\u003e). In summary, strong TMC will likely moderate the relationship between integration efforts and subsequent improvements in EP, shaping the organization's approach toward environmental sustainability. Supported by this collection, we develop the pursuing hypothesis:\u003c/p\u003e \u003cp\u003e \u003cb\u003eH7: TMC moderates the relationship between GSCI and EP.\u003c/b\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003e2.8 TMC moderates among SC and EP\u003c/h2\u003e \u003cp\u003eSC in an organization represents mutual belief, ideas, measures, and behaviors, prioritizing environmental sustainability and social responsibility (Tseng, \u003cspan citationid=\"CR84\" class=\"CitationRef\"\u003e2014\u003c/span\u003e). It involves all employees embracing sustainability in their work (Lo et al., \u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e2014\u003c/span\u003e). EP measures how well an organization manages its environmental impact, including reducing emissions, conserving resources, and minimizing waste (Jasiński et al., 2021, Lo et al., \u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e2014\u003c/span\u003e). TMC is the dedication and active involvement of senior executives in promoting sustainability initiatives, setting goals, and allocating resources (Labella-Fern\u0026aacute;ndez et al., \u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). A strong SC positively impacts EP, leading to environmentally friendly practices and strategies. Companies with such a culture are more likely to follow active environmental governance patterns, improving their performance (Tsai et al., \u003cspan citationid=\"CR83\" class=\"CitationRef\"\u003e2020\u003c/span\u003e), suggesting that TMC and regulations jointly moderate the relationship between SC and EP. Strong TMC and supportive regulations enhance this positive impact, while weak commitment and lax compliance may weaken it (El-Kassar and Singh, \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Research consistently shows that TMC positively influences EP (Dubey et al., \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2015\u003c/span\u003e) (Lo et al., \u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e2014\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eSimilarly, a strong SC within an organization is linked to enhanced EP (Heras-Saizarbitoria et al., \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Compliance with environmental regulations is associated with improved EP (Arimura et al., \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2011\u003c/span\u003e). These findings emphasize the importance of integrating SC, top management commitment, and regulatory compliance for enhanced EP. Based on these findings, we formulate the pursuing hypothesis:\u003c/p\u003e \u003cp\u003e \u003cb\u003eH8: TMC regulations moderate the relationship between SC and EP.\u003c/b\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"3. Study Methodology","content":"\u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003e3.1 Instrument Evolution\u003c/h2\u003e \u003cp\u003eThe measuring components utilized in this research were drawn from existing literature and subsequently adapted to align with the current research context. The scales employed have been customized to suit the specific requirements of this research, with due consideration to their appropriateness for the survey respondents. To assess the robustness of the conceptual model, a pilot study was conducted involving 244 top managers, supply chain professionals, policymakers and employees who are professional members of the manufacturing industry of Pakistan. The manufacturing and related sectors are inherently dynamic, presenting unique challenges and risks. The questionnaire has been designed to capture pertinent data for this study, with all items being measured exploitation a five-point Likert scale. Detailed information regarding the sources of the measurement portion can be found in Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003e3.2 Sample distribution strategy and data grouping\u003c/h2\u003e \u003cp\u003eThe data for this research were gathered utilizing purposive sampling via an online survey distributed through a Google Docs link. Data was collected from June to August 2023. Initially, this survey was dispatched to 300 professionals who are members of the manufacturing industry in Pakistan. In the end, 260 questionnaires were returned, resulting in an outcome range of 83.66 percent.\u003c/p\u003e \u003cp\u003eOut of 260 total, 244 questionnaires are fully completed, others are incomplete and outlier. Researchers used purposive sampling to align the sample selection with the study's goals and research questions. This method provides the advantage of purposefully targeting participants most likely to contribute relevant and valuable information, enhancing the study's quality and relevance to the specific research objectives. Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e presents the data about the manufacturing industry types and size in the shape of numbers of employees and respondents' areas of employment, years of professional experience, education and age and Table \u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e shows the descriptive Statistics of variables.\u003c/p\u003e \u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e shows the demographic collection of the survey associate and company.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eWork Domains of Respondents and their Professional Experience\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDemographic Factors\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRespondents\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eFrequency\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003ePercentage\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eGender\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e183\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e75\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e61\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e25\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003eAge\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e20\u0026ndash;30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e78\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e32\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e31\u0026ndash;40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e61\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e25\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e41\u0026ndash;50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e68\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e28\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e51 \u0026amp; above\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eEducation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBachelors\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e81\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e33\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMasters\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e112\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e46\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAbove Masters\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e51\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e21\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003eExperience\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e10 years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e11\u0026ndash;15 years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e76\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e31\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e16\u0026ndash;20 years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e63\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e26\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e21 \u0026amp; above years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e68\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e28\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eIndustry\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eElectronics\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e73\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e30\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTextile\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e110\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e45\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFood manufacturing\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e61\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e25\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"4\" rowspan=\"5\"\u003e \u003cp\u003eCompany's number of Employees\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLess than 30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e13\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e30\u0026ndash;60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e112\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e46\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e61\u0026ndash;90\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e49\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e20\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e91\u0026ndash;120\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e13\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMore than 120\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e08\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003eCompany's Years of Working\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLess than 5 years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6\u0026ndash;10 years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e76\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e31\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e11\u0026ndash;15 years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e63\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e26\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e16 \u0026amp; above\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e68\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e28\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eVariable Descriptive Statistics\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariables\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSample mean\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eStandard Deviation\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eSample Size\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eEP\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e4.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.68\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e244\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eGER\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3.21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.87\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e244\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eGSCI\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e4.76\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.98\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e244\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSC\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3.38\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.74\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e244\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSTA\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e4.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.53\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e244\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eEP\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e4.27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.48\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e244\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003e3.3 Common method bias, nonresponse bias, Social Desirability and Multicollinearity\u003c/h2\u003e \u003cp\u003eCMB may pose a potential issue when dealing with self-reported data, as the [74], study highlighted. Several preventive measures were taken to mitigate this concern at the pre-data collection stage. The questionnaire commenced with a special note to ensure that respondents clearly understood the survey's purpose, emphasizing that it was strictly for academic research and not for any commercial use. The confidentiality of respondents' information throughout all stages of the research was also assured. In the post-data collection phase, Harman's individual-section trial was employed to measure whether extraneous factors influenced the data due to the measurement instrument. EFA was conducted using the data obtained from an online survey. The results of this analysis indicated the existence of five defined sections, with the initial element explaining the highest proportion of covariance at 33.28%. According to the criteria established by (Podsakoff and Organ, \u003cspan citationid=\"CR69\" class=\"CitationRef\"\u003e1986\u003c/span\u003e), if an individual factor accounts for less than 50% of the maximum covariance, it does not significantly impact the data. The nonresponse bias was assessed following the guidelines outlined by (Armstrong and Overton, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e1977\u003c/span\u003e). Additionally, a relation was conducted among the advanced wave and late wave (after the first reminder) during the data collection phase by employing the Homogeneity of Variance test.\u003c/p\u003e \u003cp\u003eTo respond to the influence of social desirability response bias, anonymous surveys were employed to foster honest and open feedback. The survey questions were designed to be impartial and free from leading language, and participants were confident of the privacy of their outcomes. The researcher was careful not to frame questions in a way that would encourage socially desirable answers and took the extra step of conducting pilot testing to address any potential biases. Additionally, efforts were made to assess multicollinearity following the criteria outlined by (Yoo et al., \u003cspan citationid=\"CR89\" class=\"CitationRef\"\u003e2014\u003c/span\u003e). The results of these assessments revealed that the model did not exhibit multicollinearity, as all VIF values remained beneath the established threshold of 3.3. These VIF values can be found in Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003e3.4 Assessment of Measurement Model\u003c/h2\u003e \u003cp\u003eConsidering the constructs nature and interrelationships, a reflective measurement model established by (Hair Jr et al., \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2021\u003c/span\u003e), was evaluated for reliability and validity, as shown in Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e. The survey has been meticulously structured to gather relevant information for this research, and each element is assessed using a five-point Likert scale. Comprehensive details about the origins of these measurement items are available in Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eMeasurement Instruments' Source\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eConstructs\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eItem\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eDescription\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eSource\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"4\" rowspan=\"5\"\u003e \u003cp\u003e\u003cb\u003eEnvironmental Performance (EP)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eEP1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eEnvironmental initiatives have a positive impact on our company's profitability.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\" morerows=\"4\" rowspan=\"5\"\u003e \u003cp\u003e(Coenen et al., \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2021\u003c/span\u003e, Gilal et al., \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2019\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eEP2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eOur environmental performance is a competitive advantage in our industry.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eEP3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eOur organization has made significant improvements in reducing our environmental footprint.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eEP4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eOur environmental performance contributes to a positive public image and brand reputation.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eEP5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eEnvironmental performance is a key performance indicator in our manufacturing firm.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"4\" rowspan=\"5\"\u003e \u003cp\u003e\u003cb\u003eGovernment Environmental Regulations (GER)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGER1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCompliance with government environmental regulations is a top priority in our organization.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\" morerows=\"4\" rowspan=\"5\"\u003e \u003cp\u003e(Coenen et al., \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2021\u003c/span\u003e, Darnall et al., 2008)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGER2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eOur organization invests in technologies and processes to meet or exceed government environmental regulations.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGER3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCompliance with government environmental regulations is a priority in our manufacturing operations.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGER4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eOur firm seeks to exceed regulatory requirements in its environmental efforts.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGER5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eTo what extent do you believe that government environmental regulations positively impact your manufacturing firm's environmental performance\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"5\" rowspan=\"6\"\u003e \u003cp\u003e\u003cb\u003eSustainable Technology Adoption (STA)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSTA1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eOur organization is adopting sustainable and environmentally friendly technologies in manufacturing processes.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\" morerows=\"4\" rowspan=\"5\"\u003e \u003cp\u003e(Esfahbodi et al., \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2016\u003c/span\u003e, Jasiński et al., 2021)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSTA2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eOur manufacturing firm invests in and adopts sustainable technologies to reduce environmental impacts.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSTA3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eEmployees obtain the essential education and help to effectively use sustainable technologies.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSTA4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eOur organization encourages to adoption of sustainable technology.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSTA5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSustainable technology adoption is positively correlated with our environmental performance.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSTA6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSustainable technology adoption is important to improve the environmental performance of the company.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"5\" rowspan=\"6\"\u003e \u003cp\u003e\u003cb\u003eSustainable Culture (SC)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSC1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eOur manufacturing firm promotes a culture of environmental responsibility and sustainability.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\" morerows=\"4\" rowspan=\"5\"\u003e \u003cp\u003e(Esfahbodi et al., \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2016\u003c/span\u003e, Wijethilake and Lama, \u003cspan citationid=\"CR86\" class=\"CitationRef\"\u003e2019\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSC2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSustainable practices and values are integrated into our organization's core mission.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSC3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eOur firm promotes a culture of sustainability and environmental responsibility.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSC4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eA sustainable culture positively influences our firm's environmental performance.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSC5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eDoes your firm promote a culture that values sustainability and environmental responsibility?\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSC6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eHow do you believe this culture affects your firm's environmental performance?\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"4\" rowspan=\"5\"\u003e \u003cp\u003e\u003cb\u003eTop Management Commitment (TMC)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTMC1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eOur top management's commitment to the environment positively affects our company's overall performance.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\" morerows=\"4\" rowspan=\"5\"\u003e \u003cp\u003e(Bassetti et al., \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2021\u003c/span\u003e, Srivastava, \u003cspan citationid=\"CR81\" class=\"CitationRef\"\u003e2007\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTMC2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSenior management is actively involved in environmental decision-making and strategies.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTMC3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eTop management's commitment positively influences our firm's environmental performance.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTMC4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eOur organization's top management is highly committed to environmental sustainability in your firm.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTMC5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eEnvironmental sustainability is integrated into our firm's strategic decision-making processes.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"5\" rowspan=\"6\"\u003e \u003cp\u003e\u003cb\u003eGreen Supply Chain Integration (GSCI)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGSCI1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eGSCI is essential to our manufacturing firm's environmental strategy\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\" morerows=\"5\" rowspan=\"6\"\u003e \u003cp\u003e(Younis et al., \u003cspan citationid=\"CR90\" class=\"CitationRef\"\u003e2016\u003c/span\u003e, Kumar et al., \u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e2019\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGSCI2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eHow would you rate the level of commitment of your organization to reducing the environmental impact of its supply chain activities?\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGSCI3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eOur company collaborates with suppliers and partners to implement environmentally friendly practices.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGSCI4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eTo what extent has your manufacturing firm integrated green practices into its supply chain\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGSCI5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eTo what extent has your manufacturing firm integrated green practices into its supply chain?\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGSCI6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eIntegrating environmentally friendly practices in our supply chain is a top priority for our organization.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eTo assess reliability, we utilized Cronbach's Alpha and composite reliability, as proposed by (Bacon et al., \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e1995\u003c/span\u003e), and examined outer loadings to evaluate the reliability of the indicators. Likewise, for validity assessment, we employed the Average Variance Extracted (AVE) and outer loadings, drawing on the work of (Chin, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2009\u003c/span\u003e). It's worth noting that all the criteria, including alpha coefficients, composite reliability estimates, and AVE shown in Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e, met or exceeded their predefined thresholds, as suggested by (Hair et al., \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2013\u003c/span\u003e) (Hair et al., \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2017\u003c/span\u003e), thereby confirming the reliability and validity of the measurement model.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eOuter Loadings, Cross loading, VIF, Cronbach's Alpha, CR, and AVE\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"8\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eConstructs\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eIndicator\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eOuter Loading\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eCross\u003c/p\u003e \u003cp\u003eLoading\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eVIF\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eAlpha\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eComposite Reliability\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003eAVE\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"4\" rowspan=\"5\"\u003e \u003cp\u003e\u003cb\u003eEP\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eEP1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.788\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.788\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e3.757\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\" morerows=\"4\" rowspan=\"5\"\u003e \u003cp\u003e0.905\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\" morerows=\"4\" rowspan=\"5\"\u003e \u003cp\u003e0.93\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\" morerows=\"4\" rowspan=\"5\"\u003e \u003cp\u003e0.727\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eEP2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.892\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.892\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e4.534\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eEP3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.788\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.788\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e2.757\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eEP4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.895\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.895\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e3.203\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eEP5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.893\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.893\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e4.235\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"4\" rowspan=\"5\"\u003e \u003cp\u003e\u003cb\u003eGER\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGER1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.755\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.655\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e2.496\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\" morerows=\"4\" rowspan=\"5\"\u003e \u003cp\u003e0.873\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\" morerows=\"4\" rowspan=\"5\"\u003e \u003cp\u003e0.902\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\" morerows=\"4\" rowspan=\"5\"\u003e \u003cp\u003e0.652\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGER2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.863\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.863\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e2.422\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGER3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.764\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.664\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.325\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGER4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.916\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.916\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e2.185\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGER5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.899\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.899\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.596\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"5\" rowspan=\"6\"\u003e \u003cp\u003e\u003cb\u003eGSCI\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGSCI1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.796\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.796\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e2.324\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\" morerows=\"5\" rowspan=\"6\"\u003e \u003cp\u003e0.931\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\" morerows=\"5\" rowspan=\"6\"\u003e \u003cp\u003e0.946\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\" morerows=\"5\" rowspan=\"6\"\u003e \u003cp\u003e0.745\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGSCI2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.89\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.89\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e3.505\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGSCI3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.897\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.897\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e4.673\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGSCI4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.905\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.905\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e4.914\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGSCI5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.863\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.863\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e2.791\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGSCI6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.821\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.821\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e2.583\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"5\" rowspan=\"6\"\u003e \u003cp\u003e\u003cb\u003eSC\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSC1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.917\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.536\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.645\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\" morerows=\"5\" rowspan=\"6\"\u003e \u003cp\u003e0.937\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\" morerows=\"5\" rowspan=\"6\"\u003e \u003cp\u003e0.95\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\" morerows=\"5\" rowspan=\"6\"\u003e \u003cp\u003e0.76\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSC2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.89\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.535\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e3.663\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSC3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.871\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.477\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e3.304\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSC4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.851\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.514\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e2.831\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSC5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.803\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.402\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e2.226\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSC6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.893\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.528\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e4.734\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"5\" rowspan=\"6\"\u003e \u003cp\u003e\u003cb\u003eSTA\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSTA1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.72\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.125\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.825\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\" morerows=\"5\" rowspan=\"6\"\u003e \u003cp\u003e0.895\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\" morerows=\"5\" rowspan=\"6\"\u003e \u003cp\u003e0.917\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\" morerows=\"5\" rowspan=\"6\"\u003e \u003cp\u003e0.649\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSTA2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.785\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e2.214\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSTA3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.807\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.176\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e2.213\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSTA4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.822\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.278\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e2.036\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSTA5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.869\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e2.389\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSTA6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.824\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.268\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e2.038\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"4\" rowspan=\"5\"\u003e \u003cp\u003e\u003cb\u003eTMC\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTMC1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.759\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.692\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\" morerows=\"4\" rowspan=\"5\"\u003e \u003cp\u003e0.746\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\" morerows=\"4\" rowspan=\"5\"\u003e \u003cp\u003e0.832\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\" morerows=\"4\" rowspan=\"5\"\u003e \u003cp\u003e0.504\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTMC2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.822\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.109\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e2.092\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTMC3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.691\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.114\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.708\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTMC4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.727\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.106\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.547\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTMC5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.509\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.084\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eConvergent validity is employed to evaluate the extent to which an indicator exhibits a positive correlation with other indicators specified within the theoretical framework (Chin, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2009\u003c/span\u003e). Discriminant validity was scrutinized through cross-loadings, the (Ab Hamid et al., \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2017\u003c/span\u003e), and the HTMT method outlined by (Hair et al., \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2013\u003c/span\u003e). Cross-loadings confirmed construct differentiation from other constructs in the model (Ab Hamid et al., \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2017\u003c/span\u003e), (see Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). Notably, the square root of AVE for each latent variable surpasses the association between these latent variables, as (Hair et al., \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2012\u003c/span\u003e), asserted, shown in Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab5\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eFornel and Larker Criteria (1981)\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eConstructs\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eEP\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eGER\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eGSCI\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eSC\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eSTA\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eTMC\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEP\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.853\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eGER\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.435\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e0.808\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eGSCI\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.155\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e0.863\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSC\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.177\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.241\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.575\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.872\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSTA\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.006\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.112\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.287\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.201\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e0.806\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eTMC\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.36\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.302\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.141\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.212\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.133\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e0.71\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eAdditionally, the HTMT values fell beneath the critical threshold of 0.85 with coefficient of determination values R\u003csup\u003e2,\u003c/sup\u003e thus affirming the discriminant validity of the framework, in line with the research by (Henseler et al., 2015). Q\u003csup\u003e2\u003c/sup\u003e measures the predictive performance of a model. It also assesses how well the framework generalizes to new data (see Table\u0026nbsp;\u003cspan refid=\"Tab6\" class=\"InternalRef\"\u003e6\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab6\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 6\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eHTMT and Coefficient of Determination\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"8\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eConstructs\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eEP\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eGER\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eGSCI\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eSC\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eSTA\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eR\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003eQ\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eEP\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.47\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.43\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eGER\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.455\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eGSCI\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.166\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.82\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.75\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSC\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.189\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.263\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.608\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.41\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.40\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSTA\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.058\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.138\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.278\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.201\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eTMC\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.422\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.315\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.164\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.257\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.159\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eIn Table\u0026nbsp;\u003cspan refid=\"Tab7\" class=\"InternalRef\"\u003e7\u003c/span\u003e, EP exhibits positive correlations with other constructs: 0.435 with GER, 0.155 with GSCI, 0.177 with SC, 0.006 with STA, and 0.36 with TMC. GER shows similar patterns of correlation with the constructs. Notably, GSCI has a relatively strong positive correlation (0.575) with SC and a moderate positive correlation (0.287) with STA. The correlations provide insights into the relationships between these constructs, with varying degrees of strength and direction.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab7\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 7\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eCorrelations of Constructs\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCorrelation\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eEP\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eGER\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eGSCI\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eSC\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eSTA\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eTMC\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eEP\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.435\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.155\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.177\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.006\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.36\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eGER\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.435\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.241\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.112\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.302\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eGSCI\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.155\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.575\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.287\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.141\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSC\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.177\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.241\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.575\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.201\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.212\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSTA\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.006\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.112\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.287\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.201\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.133\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eTMC\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.36\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.302\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.141\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.212\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.133\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec16\" class=\"Section2\"\u003e \u003ch2\u003e3.5 Classification of Structural Model\u003c/h2\u003e \u003cp\u003eThe relevance of the routes, linearity, coefficient of determination (R2), effect size (f2), and other parameters are considered when evaluating the structural model in this study (Hair et al., \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2013\u003c/span\u003e). To ensure the most accurate parameter estimation, we evaluated multicollinearity as well (Mela and Kopalle, \u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e2002\u003c/span\u003e) and all values were below the threshold of \u0026plusmn;\u0026thinsp;5.0, as established by (Hair et al., \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2013\u003c/span\u003e), (See Table \u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). The cumulative effect of exogenous latent variables on the endogenous latent variable is represented by the coefficient of determination (R2). The coefficient of R2 and Q2 was used to evaluate predictive accuracy (see Table\u0026nbsp;\u003cspan refid=\"Tab6\" class=\"InternalRef\"\u003e6\u003c/span\u003e). The effect size for the relationship under test is shown by the F2 value in Table\u0026nbsp;\u003cspan refid=\"Tab8\" class=\"InternalRef\"\u003e8\u003c/span\u003e. A regression study measure how strongly the variables are related to one another. The F2 statistic shows the magnitude of the association between the independent and dependent variables.\u003c/p\u003e \u003cp\u003eThe results indicate a strong and positive correlation between STA and GSCI, supporting our H1 (β\u0026thinsp;=\u0026thinsp;0.374, t\u0026thinsp;=\u0026thinsp;16.777, p\u0026thinsp;=\u0026thinsp;0.000). Additionally, STA has a notable and supportive impact on SC, validating our H2 (β\u0026thinsp;=\u0026thinsp;0.298, t\u0026thinsp;=\u0026thinsp;13.292, p\u0026thinsp;=\u0026thinsp;0.000). Furthermore, the findings confirm H3 (β\u0026thinsp;=\u0026thinsp;0.184, t\u0026thinsp;=\u0026thinsp;9.071, p\u0026thinsp;=\u0026thinsp;0.000), demonstrating that GSCI is important and positively associated with EP. Similarly, H4 is upheld (β\u0026thinsp;=\u0026thinsp;0.168, t\u0026thinsp;=\u0026thinsp;8.187, p\u0026thinsp;=\u0026thinsp;0), indicating a meaningful and supportive relationship between SC and EP. The results demonstrate support for H5 (β\u0026thinsp;=\u0026thinsp;0.654, t\u0026thinsp;=\u0026thinsp;3.519, p\u0026thinsp;=\u0026thinsp;0.000), H6 (β\u0026thinsp;=\u0026thinsp;0.492, t\u0026thinsp;=\u0026thinsp;5.601, p\u0026thinsp;=\u0026thinsp;0.000), H7 (β\u0026thinsp;=\u0026thinsp;0.564, t\u0026thinsp;=\u0026thinsp;3.46, p\u0026thinsp;=\u0026thinsp;0.000) and H8 (β\u0026thinsp;=\u0026thinsp;0.763, t\u0026thinsp;=\u0026thinsp;2.955, p\u0026thinsp;=\u0026thinsp;0.000) confirming the presence of moderating effects of H5 GER x GSCI -\u0026gt; EP and H6 shows the moderating effect of GER x SC -\u0026gt; EP also H7 shows the moderating effect of TMC x GSCI -\u0026gt; EP lastly H8 shows the moderating effect of TMC x SC -\u0026gt; EP. Table\u0026nbsp;\u003cspan refid=\"Tab8\" class=\"InternalRef\"\u003e8\u003c/span\u003e provides comprehensive information on the direct and indirect pathways (moderating effects).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab8\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 8\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eHypothesis Testing\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"8\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHypothesis\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eβ\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eStandard deviation (STDEV)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eT statistics\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eP- values\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eF\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003eResults\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"6\" nameend=\"c6\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eDirect Effect\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSTA -\u0026gt; GSCI\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eH1\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.374\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e16.777\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e2.456\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eAccepted\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSTA -\u0026gt; SC\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eH2\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.298\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e13.292\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e2.211\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eAccepted\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eGSCI -\u0026gt; EP\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eH3\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.184\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e9.071\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.456\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eAccepted\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSC -\u0026gt; EP\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eH4\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.168\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e8.187\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.896\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eAccepted\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"6\" nameend=\"c6\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eModeration Effect\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eGER x GSCI -\u0026gt; EP\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eH5\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.654\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3.519\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.763\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eAccepted\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eGER x SC -\u0026gt; EP\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eH6\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.492\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e5.601\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.859\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eAccepted\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eTMC x GSCI -\u0026gt; EP\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eH7\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.564\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3.46\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.435\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eAccepted\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eTMC x SC -\u0026gt; EP\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eH8\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.763\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.955\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.003\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.102\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eAccepted\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eThe study explores the relationships among GER, GSCI, SC, STA, TMC and EP, analyzing their statistical significance at a substance equal below 0.05 (shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"4. Discussion","content":"\u003cp\u003eThe positive correlation between adopting sustainable technologies and integrating green practices within the supply chain conforms with the core tenets of sustainability theory. Sustainable technologies are pivotal in implementing environmentally friendly practices across the supply chain (Dubey et al., \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). This association can be appreciated as the direct channel of the sustainability concept, which underscores the significance of environmental stewardship, resource efficiency, long-term sustainability, meeting stakeholder expectations, and considering the triple bottom line (Hussain et al., 2018). Organizations embracing sustainable technologies are more inclined to infuse eco-friendly practices throughout their supply chain. As a result, this fosters a more sustainable and environmentally responsible approach to their operational processes (Yu et al., \u003cspan citationid=\"CR91\" class=\"CitationRef\"\u003e2022\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe study's confirmation of the hypothesis linking STA to the cultivation of a SC aligns with the principles of Resource dependence theory. STA can be viewed as a strategic move aimed at reducing the reliance on external environmental resources, thereby encouraging the development of a culture that places a high premium on environmental accountability and sustainability (Glasmeier and Farrigan, \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2003\u003c/span\u003e). Resource dependence theory is a robust theoretical underpinning for comprehending the connection between adopting sustainable technologies and promoting a SC within organizational contexts. This theory underscores the pivotal role of external resources, exchange relationships, resource dependency, institutional pressures, and the process of organizational learning in shaping the prevailing organizational culture (Paulraj, \u003cspan citationid=\"CR67\" class=\"CitationRef\"\u003e2011\u003c/span\u003e). In this context, STA emerges as a response to these influential factors, ultimately creating a culture prioritizing sustainability and environmental responsibility (Kouhizadeh et al., \u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e2021\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe positive connection between GSCI and enhanced EP is following the core tenets of Institutional theory. Organizations are subject to the pervasive influence of institutional norms and external pressures, compelling them to adopt and implement sustainable practices, yielding favorable EP outcomes (El-Kassar and Singh, \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Institutional concept underscores the profound effect of various organizational factors, including outer force, societal norms, regulatory adherence, organizational legitimacy, and cultural-cognitive elements, on shaping the behavioral patterns of organizations (Linnenluecke and Griffiths, \u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e2010\u003c/span\u003e). Considering these influences, organizations embrace and introduce green patterns within their supply chain dealings, ultimately culminating in the augmentation of their EP.\u003c/p\u003e \u003cp\u003eThe hypothesis connecting SC with enhanced EP finds alignment with stakeholder theory. A robust SC indicates an administration's unwavering dedication to gathering its diverse stakeholders' multifaceted expectations, encompassing a commitment to environmentally responsible practices that, in turn, result in heightened EP (Awan et al., 2017). Stakeholder theory provides a robust and coherent theoretical underpinning for comprehending the affirmative correlation between SC and EP (Awan et al., 2017). It accentuates the pivotal role of stakeholders, elucidating their inherent values, expectations, normative influence, and the exertion of pressure in molding an organization's steadfastness to environmental responsibility. Stakeholder Theory underscores the insistency of recognizing and appropriately addressing the spectrum of stakeholder interests, which extend to sustainability and environmental concerns (Alpaslan et al., \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2009\u003c/span\u003e). Such alignment serves as the catalyst for the augmentation of EP, harmoniously aligned with the values and expectations of the stakeholders.\u003c/p\u003e \u003cp\u003eThe discovery that GER act as moderators in shaping the connections among GSCI, SC, and EP aligns with the foundational tenets of institutional theory. These regulations serve as extraneous institutions that mold organizational conduct, with regulatory compliance augmenting the affirmative impact of green practices and SC on EP (Alpaslan et al., \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2009\u003c/span\u003e). Institutional theory serves as the theoretical bedrock for elucidating the influence of GER on the intricate interplay among GSCI, SC, and EP within organizational contexts. This theoretical framework posits that organizations adhere to regulatory standards and embrace ecologically responsible practices to attain legitimacy, procure vital resources, and effectively respond to coercive pressures exerted by regulatory bodies (Darnall et al., 2008). This conformity with institutional paradigms, prioritizing sustainability, and environmental conscientiousness, ultimately ameliorates EP corroboration of the findings presented in the study.\u003c/p\u003e \u003cp\u003eThe revelation that TMC moderates the interactions between GSCI, SC, and EP is in harmony with the principles of TMC theory. TMC theory underscores the pivotal role that top leadership, including executives and senior managers, plays in spearheading strategic endeavors and enacting organizational transformations (Amir et al., 2020). In the context of sustainability and EP, this theory posits that the unwavering dedication of TMC to environmental responsibility and sustainability objectives holds substantial sway (Kitsis and Chen, \u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). It influences the organization's capacity to seamlessly integrate green practices into its supply chain and foster a sustainability culture, yielding a beneficial environmental performance effect. This alignment with TMC theory underscores the indispensable function of leadership in propelling sustainability initiatives and realizing environmental objectives within an organization (Esfahbodi et al., \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2016\u003c/span\u003e).\u003c/p\u003e"},{"header":"5. Conclusion","content":"\u003cp\u003eThe study's findings shed light on several significant relationships between sustainable activity and EP. \u003cb\u003eFirstly\u003c/b\u003e, the research confirms a positive link between STA and GSCI (H1). This indicates that organizations embracing sustainable technologies tend to incorporate environmentally affable exercises into their supply chain dealings. \u003cb\u003eSecondly\u003c/b\u003e, STA is positively associated with developing a SC within organizations (H2), underscoring how embracing sustainable technologies can shape a corporate culture that values environmental responsibility and sustainability. \u003cb\u003eThirdly\u003c/b\u003e, the study verifies that GSCI is positively connected with improved EP (H3), highlighting the benefits of integrating eco-friendly activity into supply chain dealings. In line with this, an organization's strong SC is also positively connected to enhanced EP (H4), emphasizing the importance of fostering a corporate culture that prioritizes sustainability. GER act as moderators in the state among GSCI, SC, and EP (H5 and H6), implying that the regulatory environment can influence the effect of green patterns and an SC on EP. Compliance with environmental regulations can enhance the positive effects of these factors on EP. \u003cb\u003eLastly\u003c/b\u003e, TMC is a key moderator in the relation among GSCI, SC, and EP (H7 and H8). The commitment and support of TMC play a pivotal role in determining how GSCI practices and cultivating an SC translates into improved EP.\u003c/p\u003e \u003cdiv id=\"Sec19\" class=\"Section2\"\u003e \u003ch2\u003e5.1 Theoretical and Practical Implications\u003c/h2\u003e \u003cp\u003ePractical implications from this research content a comprehensive model for organizations seeking to better their environmental responsibility and sustainability efforts. STA is a crucial starting point, as it enhances EP and facilitates combining eco-friendly practices across the supply chain. Fostering a SC within the organization can be achieved through STA, training, and promoting environmentally conscious behaviors among employees. GSCI practices, like sustainable sourcing and waste reduction, are key to enhancing overall EP. Compliance with GER is essential for legal adherence and amplifying the positive impacts of GSCI and SC on EP. The TMC is pivotal, influencing the thriving execution of green preparation and SC. Transparent reporting and communication about sustainability efforts can improve an organization's reputation and stakeholder relationships. Collaboration with supply chain partners and active employee engagement strengthen the SC and drive environmental improvements. Recognizing environmental responsibility as an ongoing commitment, organizations should continually assess and adapt their sustainable practices to align with evolving regulations and emerging technologies. Lastly, establishing performance metrics and key indicators for tracking EP enables data-driven decision-making and setting specific sustainability goals, ensuring continuous progress toward sustainability objectives.\u003c/p\u003e \u003cp\u003eThis study has substantial theoretical implications. It introduces the sustainability integration framework, highlighting the interconnected effects of STA, GSCI, and SC on EP. It underscores the theoretical roles of GER and TMC in shaping these relationships. The study emphasizes using key performance indicators (KPIs) to theoretically measure EP. It advances theory by demonstrating the causes of organizational culture on sustainability and highlights the complex interplay of multiple factors. The research calls for longitudinal studies and incorporates various theoretical perspectives, contributing to a better understanding of sustainability as a multidisciplinary concept. Additionally, it highlights the complexity of sustainability research, prompting the development of more significance theoretical models.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec20\" class=\"Section2\"\u003e \u003ch2\u003e5.2 Future Research and Limitations\u003c/h2\u003e \u003cp\u003eThis research offers both potential and limitations for future studies. Limitations include context-specific constraints, potential bias in self-reported data, and a limited ability to capture dynamic changes due to the cross-sectional design. The study's focus on moderating factors may not encompass all contextual variables, and there is room for improving the measurement of sustainability-related constructs.\u003c/p\u003e \u003cp\u003eFuture research directions include cross-industry and regional comparisons, longitudinal studies for long-term sustainability effects, exploration of emerging technologies (e.g., IoT and renewable energy), and understanding the impact of consumer preferences and regulatory changes on sustainability efforts. Further research can investigate supply chain complexity, transparent sustainability reporting effects, and the alignment of corporate social responsibility (CSR) with environmental objectives. Exploring the interaction between sustainability and innovation and the role of employee engagement in fostering sustainability culture are also promising areas of study.\u003c/p\u003e \u003c/div\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003e-Ethical Approval\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis document officially confirms ethical approval for the research project. Key ethical considerations include:\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eInformed Consent:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eParticipants are fully informed and voluntarily consent to participation, understanding the research\u0026apos;s purpose, procedures, and potential impacts.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eVoluntariness:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eParticipants are free to withdraw at any stage without repercussions, and no coercion is employed to secure participation.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConfidentiality:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eStringent measures safeguard participant confidentiality, preventing inadvertent disclosure of personal information.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eProtection of Sensitive Information:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eSensitive data shared by participants is handled discreetly and is not disclosed in publications or reports.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eRight to Withdraw:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eParticipants have an unequivocal right to withdraw without adverse consequences, and the withdrawal process is straightforward.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eInstitutional Review Board (IRB) Approval:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe research has received formal approval from the IRB, ensuring adherence to ethical standards and regulations.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ePublication Safeguards:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eParticipants are aware of the intention to publish, with precautions taken to maintain confidentiality and privacy in publications.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgment of Contributions:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAuthors and contributors will be duly acknowledged in resulting publications, ensuring transparency and ethical practice.\u003c/p\u003e\n\u003cp\u003eThe research adheres to ethical principles, international guidelines, and regulatory \u0026nbsp; \u0026nbsp; \u0026nbsp;requirements, emphasizing the team\u0026apos;s commitment to participants\u0026apos; rights, \u0026nbsp;well-being, and confidentiality. Inquiries or concerns can be directed to the principal investigator or the designated contact person listed in the informed consent materials.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u0026nbsp;-Consent to Participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eIn seeking your participation in this research study, we want to provide you with a clear understanding of the purpose, procedures, and potential impact of our investigation into the interplay between government regulations, top management influence, and their effects on the environmental performance of manufacturing firms. The study specifically explores the connections among these factors with a focus on the green supply chain, organizational culture, and technology adoption within manufacturing firms.\u003c/p\u003e\n\u003cp\u003eYour participation in this study is vital for advancing our understanding of the complex relationships between government regulations, top management influence, and environmental performance in manufacturing firms. By agreeing to participate, you contribute to the broader knowledge in this field, potentially influencing future practices and policies. If you have any questions or concerns about your participation, please do not hesitate to reach out to the research team. Your cooperation is highly valued and we appreciate your thoughtful consideration of this consent request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u0026nbsp;-Consent to Publish\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eIn addition to seeking your consent to participate in our research study on the relationships among government regulations, top management influence, and environmental performance in manufacturing firms, we also seek your permission to publish the outcomes of this study.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eYour consent to publish is an essential aspect of our research process. It enables us to share valuable insights with the academic community, industry practitioners, and policymakers. We appreciate your willingness to contribute to the dissemination of knowledge in this field. If you have any concerns or questions regarding the publication aspect of this study, please feel free to reach out to the research team for further clarification. Your cooperation and participation are highly valued, and we look forward to responsibly sharing the outcomes of this research.\u003cstrong\u003e\u003cbr\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e-Authors Contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eSaqib Mehmood: Data Gathering, Result Interpretation\u003c/p\u003e\n\u003cp\u003eSamera Nazir: Data Analysis, Interpretation\u003c/p\u003e\n\u003cp\u003eJianqiang Fan: Proof Reading, Result Analysis\u003c/p\u003e\n\u003cp\u003eZarish Nazir: Software Run,\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eAmad Shoukat: Software Run. Result Interpretation.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u0026nbsp;-Funding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThere is no Funding from anyone.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u0026nbsp;-Competing Interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eI have no conflict of interest with anyone.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eAB HAMID, M., SAMI, W. \u0026amp; SIDEK, M. M. Discriminant validity assessment: Use of Fornell \u0026amp; Larcker criterion versus HTMT criterion. Journal of Physics: Conference Series, 2017. IOP Publishing, 012163.\u003c/li\u003e\n\u003cli\u003eABDEL-BASET, M., CHANG, V. \u0026amp; GAMAL, A. 2019. Evaluation of the green supply chain management practices: A novel neutrosophic approach. \u003cem\u003eComputers in Industry,\u003c/em\u003e 108\u003cstrong\u003e,\u003c/strong\u003e 210-220.\u003c/li\u003e\n\u003cli\u003eABUZAWIDA, S. S., ALZUBI, A. B. \u0026amp; IYIOLA, K. 2023. Sustainable Supply Chain Practices: An Empirical Investigation from the Manufacturing Industry. \u003cem\u003eSustainability,\u003c/em\u003e 15\u003cstrong\u003e,\u003c/strong\u003e\u003c/li\u003e\n\u003cli\u003eALAEDDIN, O., SHAWTARI, F. A. M., SALEM, M. A. \u0026amp; ALTOUNJY, R. 2019. The effect of management accounting systems in influencing environmental uncertainty, energy efficiency and environmental performance. \u003cem\u003eInternational Journal of Energy Economics and Policy,\u003c/em\u003e 9\u003cstrong\u003e,\u003c/strong\u003e 346-352.\u003c/li\u003e\n\u003cli\u003eALPASLAN, C. M., GREEN, S. E. \u0026amp; MITROFF, I. I. 2009. Corporate governance in the context of crises: Towards a stakeholder theory of crisis management. \u003cem\u003eJournal of contingencies and crisis management,\u003c/em\u003e 17\u003cstrong\u003e,\u003c/strong\u003e 38-49.\u003c/li\u003e\n\u003cli\u003eAMIR, M., REHMAN, S. A. \u0026amp; KHAN, M. I. 2020. Mediating role of environmental management accounting and control system between top management commitment and environmental performance: A legitimacy theory. \u003cem\u003eJournal of Management and Research,\u003c/em\u003e 7\u003cstrong\u003e,\u003c/strong\u003e 132-160.\u003c/li\u003e\n\u003cli\u003eARAG\u0026Oacute;N-CORREA, J. A. \u0026amp; SHARMA, S. 2003. A contingent resource-based view of proactive corporate environmental strategy. \u003cem\u003eAcademy of management review,\u003c/em\u003e 28\u003cstrong\u003e,\u003c/strong\u003e 71-88.\u003c/li\u003e\n\u003cli\u003eARIMURA, T. H., DARNALL, N. \u0026amp; KATAYAMA, H. 2011. Is ISO 14001 a gateway to more advanced voluntary action? The case of green supply chain management. \u003cem\u003eJournal of environmental economics and management,\u003c/em\u003e 61\u003cstrong\u003e,\u003c/strong\u003e 170-182.\u003c/li\u003e\n\u003cli\u003eARMSTRONG, J. S. \u0026amp; OVERTON, T. S. 1977. Estimating nonresponse bias in mail surveys. \u003cem\u003eJournal of marketing research,\u003c/em\u003e 14\u003cstrong\u003e,\u003c/strong\u003e 396-402.\u003c/li\u003e\n\u003cli\u003eAWAN, U., KRASLAWSKI, A. \u0026amp; HUISKONEN, J. 2017. Understanding the relationship between stakeholder pressure and sustainability performance in manufacturing firms in Pakistan. \u003cem\u003eProcedia Manufacturing,\u003c/em\u003e 11\u003cstrong\u003e,\u003c/strong\u003e 768-777.\u003c/li\u003e\n\u003cli\u003eBACON, D. R., SAUER, P. L. \u0026amp; YOUNG, M. 1995. Composite reliability in structural equations modeling. \u003cem\u003eEducational and psychological measurement,\u003c/em\u003e 55\u003cstrong\u003e,\u003c/strong\u003e 394-406.\u003c/li\u003e\n\u003cli\u003eBASSETTI, T., BLASI, S. \u0026amp; SEDITA, S. R. 2021. The management of sustainable development: A longitudinal analysis of the effects of environmental performance on economic performance. \u003cem\u003eBusiness Strategy and the Environment,\u003c/em\u003e 30\u003cstrong\u003e,\u003c/strong\u003e 21-37.\u003c/li\u003e\n\u003cli\u003eBELTR\u0026Aacute;N-RODR\u0026Iacute;GUEZ, L., VALDEZ-HERN\u0026Aacute;NDEZ, J. I., SAYNES-V\u0026Aacute;SQUEZ, A., BLANCAS, J., SIERRA-HUELSZ, J. A., CRISTIANS, S., MART\u0026Iacute;NEZ-BALLEST\u0026Eacute;, A., ROMERO-MANZANARES, A., LUNA-CAVAZOS, M. \u0026amp; BORJA DE LA ROSA, M. A. 2021. Sustaining medicinal barks: survival and bark regeneration of Amphipterygium adstringens (Anacardiaceae), a tropical tree under experimental debarking. \u003cem\u003eSustainability,\u003c/em\u003e 13\u003cstrong\u003e,\u003c/strong\u003e\u003c/li\u003e\n\u003cli\u003eBENZIDIA, S., MAKAOUI, N. \u0026amp; BENTAHAR, O. 2021. The impact of big data analytics and artificial intelligence on green supply chain process integration and hospital environmental performance. \u003cem\u003eTechnological forecasting and social change,\u003c/em\u003e 165\u003cstrong\u003e,\u003c/strong\u003e\u003c/li\u003e\n\u003cli\u003eBOCKEN, N., MILLER, K. \u0026amp; EVANS, S. 2016. Assessing the environmental impact of new Circular business models. \u003cem\u003eProceedings of the \u0026ldquo;New Business Models\u0026rdquo;\u0026mdash;Exploring a Changing View on Organizing Value Creation, Toulouse, France,\u003c/em\u003e 1\u003cstrong\u003e,\u003c/strong\u003e 16-17.\u003c/li\u003e\n\u003cli\u003eCAIADO, R. G. G., QUELHAS, O. L. G., NASCIMENTO, D. L. D. M., ANHOLON, R. \u0026amp; LEAL FILHO, W. 2019. Towards sustainability by aligning operational programmes and sustainable performance measures. \u003cem\u003eProduction Planning \u0026amp; Control,\u003c/em\u003e 30\u003cstrong\u003e,\u003c/strong\u003e 413-425.\u003c/li\u003e\n\u003cli\u003eCARTER, C. R. \u0026amp; ROGERS, D. S. 2008. A framework of sustainable supply chain management: moving toward new theory. \u003cem\u003eInternational journal of physical distribution \u0026amp; logistics management,\u003c/em\u003e 38\u003cstrong\u003e,\u003c/strong\u003e 360-387.\u003c/li\u003e\n\u003cli\u003eCHEN, A. P. S., HUANG, Y.-F. \u0026amp; DO, M.-H. 2022. Exploring the Challenges to Adopt Green Initiatives to Supply Chain Management for Manufacturing Industries. \u003cem\u003eSustainability,\u003c/em\u003e 14\u003cstrong\u003e,\u003c/strong\u003e\u003c/li\u003e\n\u003cli\u003eCHIN, W. W. 2009. Bootstrap cross-validation indices for PLS path model assessment. \u003cem\u003eHandbook of partial least squares: Concepts, methods and applications.\u003c/em\u003e\u003c/li\u003e\n\u003cli\u003eCOENEN, J., BAGER, S., MEYFROIDT, P., NEWIG, J. \u0026amp; CHALLIES, E. 2021. Environmental governance of China's belt and road initiative. \u003cem\u003eEnvironmental Policy and Governance,\u003c/em\u003e 31\u003cstrong\u003e,\u003c/strong\u003e 3-17.\u003c/li\u003e\n\u003cli\u003eCOSENZ, F., RODRIGUES, V. P. \u0026amp; ROSATI, F. 2020. Dynamic business modeling for sustainability: Exploring a system dynamics perspective to develop sustainable business models. \u003cem\u003eBusiness Strategy and the Environment,\u003c/em\u003e 29\u003cstrong\u003e,\u003c/strong\u003e 651-664.\u003c/li\u003e\n\u003cli\u003eDARNALL, N., JOLLEY, G. J. \u0026amp; HANDFIELD, R. 2008. Environmental management systems and green supply chain management: complements for sustainability? \u003cem\u003eBusiness strategy and the environment,\u003c/em\u003e 17\u003cstrong\u003e,\u003c/strong\u003e 30-45.\u003c/li\u003e\n\u003cli\u003eDUBEY, R., GUNASEKARAN, A. \u0026amp; ALI, S. S. 2015. Exploring the relationship between leadership, operational practices, institutional pressures and environmental performance: A framework for green supply chain. \u003cem\u003eInternational Journal of Production Economics,\u003c/em\u003e 160\u003cstrong\u003e,\u003c/strong\u003e 120-132.\u003c/li\u003e\n\u003cli\u003eEL-HADDADEH, R., OSMANI, M., HINDI, N. \u0026amp; FADLALLA, A. 2021. Value creation for realising the sustainable development goals: Fostering organisational adoption of big data analytics. \u003cem\u003eJournal of Business Research,\u003c/em\u003e 131\u003cstrong\u003e,\u003c/strong\u003e 402-410.\u003c/li\u003e\n\u003cli\u003eEL-KASSAR, A.-N. \u0026amp; SINGH, S. K. 2019. Green innovation and organizational performance: The influence of big data and the moderating role of management commitment and HR practices. \u003cem\u003eTechnological forecasting and social change,\u003c/em\u003e 144\u003cstrong\u003e,\u003c/strong\u003e 483-498.\u003c/li\u003e\n\u003cli\u003eELTAYEB, T. K., ZAILANI, S. \u0026amp; RAMAYAH, T. 2011. Green supply chain initiatives among certified companies in Malaysia and environmental sustainability: Investigating the outcomes. \u003cem\u003eResources, conservation and recycling,\u003c/em\u003e 55\u003cstrong\u003e,\u003c/strong\u003e 495-506.\u003c/li\u003e\n\u003cli\u003eESFAHBODI, A., ZHANG, Y., LIU, Y. \u0026amp; GENG, D. 2023. The fallacy of profitable green supply chains: The role of green information systems (GIS) in attenuating the sustainability trade-offs. \u003cem\u003eInternational Journal of Production Economics,\u003c/em\u003e 255\u003cstrong\u003e,\u003c/strong\u003e\u003c/li\u003e\n\u003cli\u003eESFAHBODI, A., ZHANG, Y. \u0026amp; WATSON, G. 2016. Sustainable supply chain management in emerging economies: Trade-offs between environmental and cost performance. \u003cem\u003eInternational Journal of Production Economics,\u003c/em\u003e 181\u003cstrong\u003e,\u003c/strong\u003e 350-366.\u003c/li\u003e\n\u003cli\u003eGADENNE, D. L., KENNEDY, J. \u0026amp; MCKEIVER, C. 2009. An empirical study of environmental awareness and practices in SMEs. \u003cem\u003eJournal of Business Ethics,\u003c/em\u003e 84\u003cstrong\u003e,\u003c/strong\u003e 45-63.\u003c/li\u003e\n\u003cli\u003eGILAL, F. G., ASHRAF, Z., GILAL, N. G., GILAL, R. G. \u0026amp; CHANNA, N. A. 2019. Promoting environmental performance through green human resource management practices in higher education institutions: A moderated mediation model. \u003cem\u003eCorporate Social Responsibility and Environmental Management,\u003c/em\u003e 26\u003cstrong\u003e,\u003c/strong\u003e 1579-1590.\u003c/li\u003e\n\u003cli\u003eGLASMEIER, A. K. \u0026amp; FARRIGAN, T. L. 2003. Poverty, sustainability, and the culture of despair: can sustainable development strategies support poverty alleviation in America's most environmentally challenged communities? \u003cem\u003eThe Annals of the American Academy of Political and Social Science,\u003c/em\u003e 590\u003cstrong\u003e,\u003c/strong\u003e 131-149.\u003c/li\u003e\n\u003cli\u003eGUO, X., XIA, W., FENG, T. \u0026amp; SHENG, H. 2022. Sustainable supply chain finance adoption and firm performance: Is green supply chain integration a missing link? \u003cem\u003eSustainable Development,\u003c/em\u003e 30\u003cstrong\u003e,\u003c/strong\u003e 1135-1154.\u003c/li\u003e\n\u003cli\u003eHAIR, J. F., HULT, G. T. M., RINGLE, C. M., SARSTEDT, M. \u0026amp; THIELE, K. O. 2017. Mirror, mirror on the wall: a comparative evaluation of composite-based structural equation modeling methods. \u003cem\u003eJournal of the academy of marketing science,\u003c/em\u003e 45\u003cstrong\u003e,\u003c/strong\u003e 616-632.\u003c/li\u003e\n\u003cli\u003eHAIR, J. F., RINGLE, C. M. \u0026amp; SARSTEDT, M. 2013. Partial least squares structural equation modeling: Rigorous applications, better results and higher acceptance. \u003cem\u003eLong range planning,\u003c/em\u003e 46\u003cstrong\u003e,\u003c/strong\u003e 1-12.\u003c/li\u003e\n\u003cli\u003eHAIR, J. F., SARSTEDT, M., RINGLE, C. M. \u0026amp; MENA, J. A. 2012. An assessment of the use of partial least squares structural equation modeling in marketing research. \u003cem\u003eJournal of the academy of marketing science,\u003c/em\u003e 40\u003cstrong\u003e,\u003c/strong\u003e 414-433.\u003c/li\u003e\n\u003cli\u003eHAIR JR, J. F., HULT, G. T. M., RINGLE, C. M., SARSTEDT, M., DANKS, N. P., RAY, S., HAIR, J. F., HULT, G. T. M., RINGLE, C. M. \u0026amp; SARSTEDT, M. 2021. An introduction to structural equation modeling. \u003cem\u003ePartial least squares structural equation modeling (PLS-SEM) using R: a workbook\u003c/em\u003e\u003cstrong\u003e,\u003c/strong\u003e 1-29.\u003c/li\u003e\n\u003cli\u003eHAN, Z. \u0026amp; HUO, B. 2020. The impact of green supply chain integration on sustainable performance. \u003cem\u003eIndustrial Management \u0026amp; Data Systems,\u003c/em\u003e 120\u003cstrong\u003e,\u003c/strong\u003e 657-674.\u003c/li\u003e\n\u003cli\u003eHE, J. \u0026amp; KIM, H. 2021. The effect of socially responsible HRM on organizational citizenship behavior for the environment: A proactive motivation model. \u003cem\u003eSustainability,\u003c/em\u003e 13\u003cstrong\u003e,\u003c/strong\u003e\u003c/li\u003e\n\u003cli\u003eHENSELER, J., RINGLE, C. M. \u0026amp; SARSTEDT, M. 2015. A new criterion for assessing discriminant validity in variance-based structural equation modeling. \u003cem\u003eJournal of the academy of marketing science,\u003c/em\u003e 43\u003cstrong\u003e,\u003c/strong\u003e 115-135.\u003c/li\u003e\n\u003cli\u003eHERAS‐SAIZARBITORIA, I., BOIRAL, O. \u0026amp; D\u0026Iacute;AZ DE JUNGUITU, A. 2020. Environmental management certification and environmental performance: Greening or greenwashing? \u003cem\u003eBusiness Strategy and the Environment,\u003c/em\u003e 29\u003cstrong\u003e,\u003c/strong\u003e 2829-2841.\u003c/li\u003e\n\u003cli\u003eHUSSAIN, N., RIGONI, U. \u0026amp; ORIJ, R. P. 2018. Corporate governance and sustainability performance: Analysis of triple bottom line performance. \u003cem\u003eJournal of business ethics,\u003c/em\u003e 149\u003cstrong\u003e,\u003c/strong\u003e 411-432.\u003c/li\u003e\n\u003cli\u003eILYAS, S., HU, Z. \u0026amp; WIWATTANAKORNWONG, K. 2020. Unleashing the role of top management and government support in green supply chain management and sustainable development goals. \u003cem\u003eEnvironmental Science and Pollution Research,\u003c/em\u003e 27\u003cstrong\u003e,\u003c/strong\u003e 8210-8223.\u003c/li\u003e\n\u003cli\u003eIRALDO, F., TESTA, F., MELIS, M. \u0026amp; FREY, M. 2011. A literature review on the links between environmental regulation and competitiveness. \u003cem\u003eEnvironmental Policy and Governance,\u003c/em\u003e 21\u003cstrong\u003e,\u003c/strong\u003e 210-222.\u003c/li\u003e\n\u003cli\u003eJASIŃSKI, D., MEREDITH, J. \u0026amp; KIRWAN, K. 2021. Sustainable development model for measuring and managing sustainability in the automotive sector. \u003cem\u003eSustainable Development,\u003c/em\u003e 29\u003cstrong\u003e,\u003c/strong\u003e 1123-1137.\u003c/li\u003e\n\u003cli\u003eJAVAID, M., HALEEM, A., SINGH, R. P., SUMAN, R. \u0026amp; GONZALEZ, E. S. 2022. Understanding the adoption of Industry 4.0 technologies in improving environmental sustainability. \u003cem\u003eSustainable Operations and Computers,\u003c/em\u003e 3\u003cstrong\u003e,\u003c/strong\u003e 203-217.\u003c/li\u003e\n\u003cli\u003eJAZAIRY, A. \u0026amp; VON HAARTMAN, R. 2020. Analysing the institutional pressures on shippers and logistics service providers to implement green supply chain management practices. \u003cem\u003eInternational Journal of Logistics Research and Applications,\u003c/em\u003e 23\u003cstrong\u003e,\u003c/strong\u003e 44-84.\u003c/li\u003e\n\u003cli\u003eKITSIS, A. M. \u0026amp; CHEN, I. J. 2021. Do stakeholder pressures influence green supply chain Practices? Exploring the mediating role of top management commitment. \u003cem\u003eJournal of Cleaner Production,\u003c/em\u003e 316\u003cstrong\u003e,\u003c/strong\u003e\u003c/li\u003e\n\u003cli\u003eKOLK, A. \u0026amp; PINKSE, J. 2010. The integration of corporate governance in corporate social responsibility disclosures. \u003cem\u003eCorporate social responsibility and environmental management,\u003c/em\u003e 17\u003cstrong\u003e,\u003c/strong\u003e 15-26.\u003c/li\u003e\n\u003cli\u003eKOUHIZADEH, M., SABERI, S. \u0026amp; SARKIS, J. 2021. Blockchain technology and the sustainable supply chain: Theoretically exploring adoption barriers. \u003cem\u003eInternational journal of production economics,\u003c/em\u003e 231\u003cstrong\u003e,\u003c/strong\u003e\u003c/li\u003e\n\u003cli\u003eKOVAL, V., OLCZAK, P., VDOVENKO, N., BOIKO, O., MATUSZEWSKA, D. \u0026amp; MIKHNO, I. 2021. Ecosystem of environmentally sustainable municipal infrastructure in the Ukraine. Sustainability 2021, 13, 10223. s Note: MDPI stays neutral with regard to jurisdictional claims in published\u0026nbsp;\u0026hellip;.\u003c/li\u003e\n\u003cli\u003eKUMAR, N., BRINT, A., SHI, E., UPADHYAY, A. \u0026amp; RUAN, X. 2019. Integrating sustainable supply chain practices with operational performance: an exploratory study of Chinese SMEs. \u003cem\u003eProduction Planning \u0026amp; Control,\u003c/em\u003e 30\u003cstrong\u003e,\u003c/strong\u003e 464-478.\u003c/li\u003e\n\u003cli\u003eLABELLA-FERN\u0026Aacute;NDEZ, A., SERRANO-ARCOS, M. M. \u0026amp; PAY\u0026Aacute;N-S\u0026Aacute;NCHEZ, B. 2021. Firm growth as a driver of sustainable product innovation: Mediation and moderation analysis. Evidence from manufacturing firms. \u003cem\u003eInternational journal of environmental research and public health,\u003c/em\u003e 18\u003cstrong\u003e,\u003c/strong\u003e\u003c/li\u003e\n\u003cli\u003eLĂZĂROIU, G., IONESCU, L., ANDRONIE, M. \u0026amp; DIJMĂRESCU, I. 2020. Sustainability management and performance in the urban corporate economy: a systematic literature review. \u003cem\u003eSustainability,\u003c/em\u003e 12\u003cstrong\u003e,\u003c/strong\u003e\u003c/li\u003e\n\u003cli\u003eLI, C. S., WONG, C. W., WONG, C. Y., BOON-ITT, S. \u0026amp; MIAO, X. 2023. Empirical research on performance effects of supply chain resilience: Systematic literature review, citation network analysis and future research directions. \u003cem\u003eInternational Journal of Shipping and Transport Logistics,\u003c/em\u003e 17\u003cstrong\u003e,\u003c/strong\u003e 80-106.\u003c/li\u003e\n\u003cli\u003eLINNENLUECKE, M. K. \u0026amp; GRIFFITHS, A. 2010. Corporate sustainability and organizational culture. \u003cem\u003eJournal of world business,\u003c/em\u003e 45\u003cstrong\u003e,\u003c/strong\u003e 357-366.\u003c/li\u003e\n\u003cli\u003eLIU, H., ZAFAR, M. W., SINHA, A. \u0026amp; KHAN, I. 2023. The path to sustainable environment: Do environmental taxes and governance matter? \u003cem\u003eSustainable Development\u003c/em\u003e.\u003c/li\u003e\n\u003cli\u003eLO, M.-C., RAMAYAH, T. \u0026amp; HUI, H. L. H. 2014. Rural communities perceptions and attitudes towards environment tourism development. \u003cem\u003eJournal of Sustainable Development,\u003c/em\u003e 7\u003cstrong\u003e,\u003c/strong\u003e\u003c/li\u003e\n\u003cli\u003eLU, J., LIANG, M., ZHANG, C., RONG, D., GUAN, H., MAZEIKAITE, K. \u0026amp; STREIMIKIS, J. 2021. Assessment of corporate social responsibility by addressing sustainable development goals. \u003cem\u003eCorporate Social Responsibility and Environmental Management,\u003c/em\u003e 28\u003cstrong\u003e,\u003c/strong\u003e 686-703.\u003c/li\u003e\n\u003cli\u003eMAKHLOUFI, L., LAGHOUAG, A. A., MEIRUN, T. \u0026amp; BELAID, F. 2022. Impact of green entrepreneurship orientation on environmental performance: The natural resource‐based view and environmental policy perspective. \u003cem\u003eBusiness Strategy and the Environment,\u003c/em\u003e 31\u003cstrong\u003e,\u003c/strong\u003e 425-444.\u003c/li\u003e\n\u003cli\u003eMAKSIMOVIC, M. 2018. Greening the future: Green Internet of Things (G-IoT) as a key technological enabler of sustainable development. \u003cem\u003eInternet of things and big data analytics toward next-generation intelligence\u003c/em\u003e\u003cstrong\u003e,\u003c/strong\u003e 283-313.\u003c/li\u003e\n\u003cli\u003eMELA, C. F. \u0026amp; KOPALLE, P. K. 2002. The impact of collinearity on regression analysis: the asymmetric effect of negative and positive correlations. \u003cem\u003eApplied Economics,\u003c/em\u003e 34\u003cstrong\u003e,\u003c/strong\u003e 667-677.\u003c/li\u003e\n\u003cli\u003eMELVILLE, N. P. 2010. Information systems innovation for environmental sustainability. \u003cem\u003eMIS quarterly\u003c/em\u003e\u003cstrong\u003e,\u003c/strong\u003e 1-21.\u003c/li\u003e\n\u003cli\u003eMUMTAZ, M. Z. \u0026amp; SMITH, Z. A. 2019. Green finance for sustainable development in Pakistan. \u003cem\u003eIPRI Journal,\u003c/em\u003e 19\u003cstrong\u003e,\u003c/strong\u003e 1-34.\u003c/li\u003e\n\u003cli\u003eNOVITASARI, M., WIJAYA, A. L., AGUSTIN, N. M., GUNARDI, A. \u0026amp; DANA, L. P. 2023. Corporate social responsibility and firm performance: Green supply chain management as a mediating variable. \u003cem\u003eCorporate Social Responsibility and Environmental Management,\u003c/em\u003e 30\u003cstrong\u003e,\u003c/strong\u003e 267-276.\u003c/li\u003e\n\u003cli\u003eNUREEN, N., XIN, Y., IRFAN, M. \u0026amp; FAHAD, S. 2023. Going green: how do green supply chain management and green training influence firm performance? Evidence from a developing country. \u003cem\u003eEnvironmental Science and Pollution Research,\u003c/em\u003e 30\u003cstrong\u003e,\u003c/strong\u003e 57448-57459.\u003c/li\u003e\n\u003cli\u003ePAGELL, M. \u0026amp; WU, Z. 2009. Building a more complete theory of sustainable supply chain management using case studies of 10 exemplars. \u003cem\u003eJournal of supply chain management,\u003c/em\u003e 45\u003cstrong\u003e,\u003c/strong\u003e 37-56.\u003c/li\u003e\n\u003cli\u003ePAULRAJ, A. 2011. Understanding the relationships between internal resources and capabilities, sustainable supply management and organizational sustainability. \u003cem\u003eJournal of Supply Chain Management,\u003c/em\u003e 47\u003cstrong\u003e,\u003c/strong\u003e 19-37.\u003c/li\u003e\n\u003cli\u003ePETTIT, T. J., CROXTON, K. L. \u0026amp; FIKSEL, J. 2013. Ensuring supply chain resilience: development and implementation of an assessment tool. \u003cem\u003eJournal of business logistics,\u003c/em\u003e 34\u003cstrong\u003e,\u003c/strong\u003e 46-76.\u003c/li\u003e\n\u003cli\u003ePODSAKOFF, P. M. \u0026amp; ORGAN, D. W. 1986. Self-reports in organizational research: Problems and prospects. \u003cem\u003eJournal of management,\u003c/em\u003e 12\u003cstrong\u003e,\u003c/strong\u003e 531-544.\u003c/li\u003e\n\u003cli\u003ePRETTY, J., BENTON, T. G., BHARUCHA, Z. P., DICKS, L. V., FLORA, C. B., GODFRAY, H. C. J., GOULSON, D., HARTLEY, S., LAMPKIN, N. \u0026amp; MORRIS, C. 2018. Global assessment of agricultural system redesign for sustainable intensification. \u003cem\u003eNature Sustainability,\u003c/em\u003e 1\u003cstrong\u003e,\u003c/strong\u003e 441-446.\u003c/li\u003e\n\u003cli\u003eRASOOL, S. F., WANG, M., ZHANG, Y. \u0026amp; SAMMA, M. 2020. Sustainable work performance: the roles of workplace violence and occupational stress. \u003cem\u003eInternational journal of environmental research and public health,\u003c/em\u003e 17\u003cstrong\u003e,\u003c/strong\u003e\u003c/li\u003e\n\u003cli\u003eRAUB, S. P. \u0026amp; MARTIN-RIOS, C. 2019. \u0026ldquo;Think sustainable, act local\u0026rdquo;\u0026ndash;a stakeholder-filter-model for translating SDGs into sustainability initiatives with local impact. \u003cem\u003eInternational Journal of Contemporary Hospitality Management,\u003c/em\u003e 31\u003cstrong\u003e,\u003c/strong\u003e 2428-2447.\u003c/li\u003e\n\u003cli\u003eROSCOE, S., SUBRAMANIAN, N., JABBOUR, C. J. \u0026amp; CHONG, T. 2019. Green human resource management and the enablers of green organisational culture: Enhancing a firm's environmental performance for sustainable development. \u003cem\u003eBusiness Strategy and the Environment,\u003c/em\u003e 28\u003cstrong\u003e,\u003c/strong\u003e 737-749.\u003c/li\u003e\n\u003cli\u003eRUSSO, M. V. \u0026amp; HARRISON, N. S. 2005. Organizational design and environmental performance: Clues from the electronics industry. \u003cem\u003eAcademy of Management Journal,\u003c/em\u003e 48\u003cstrong\u003e,\u003c/strong\u003e 582-593.\u003c/li\u003e\n\u003cli\u003eSAHOO, P. B. B. \u0026amp; THAKUR, V. 2023. Enhancing the performance of Indian micro, small and medium enterprises by implementing supply chain finance: challenges emerging from COVID-19 pandemic. \u003cem\u003eBenchmarking: An International Journal,\u003c/em\u003e 30\u003cstrong\u003e,\u003c/strong\u003e 2110-2138.\u003c/li\u003e\n\u003cli\u003eSAHOO, S., KUMAR, A. \u0026amp; UPADHYAY, A. 2023. How do green knowledge management and green technology innovation impact corporate environmental performance? Understanding the role of green knowledge acquisition. \u003cem\u003eBusiness Strategy and the Environment,\u003c/em\u003e 32\u003cstrong\u003e,\u003c/strong\u003e 551-569.\u003c/li\u003e\n\u003cli\u003eSAHU, A. K., RAUT, R. D., GEDAM, V. V., CHEIKHROUHOU, N. \u0026amp; SAHU, A. K. 2023. Lean\u0026ndash;agile\u0026ndash;resilience\u0026ndash;green practices adoption challenges in sustainable agri‐food supply chains. \u003cem\u003eBusiness Strategy and the Environment,\u003c/em\u003e 32\u003cstrong\u003e,\u003c/strong\u003e 3272-3291.\u003c/li\u003e\n\u003cli\u003eSHAFIQUE, I., KALYAR, M. N. \u0026amp; MEHWISH, N. 2021. Organizational ambidexterity, green entrepreneurial orientation, and environmental performance in SMEs context: Examining the moderating role of perceived CSR. \u003cem\u003eCorporate Social Responsibility and Environmental Management,\u003c/em\u003e 28\u003cstrong\u003e,\u003c/strong\u003e 446-456.\u003c/li\u003e\n\u003cli\u003eSHAHZAD, M., QU, Y., ZAFAR, A. U. \u0026amp; APPOLLONI, A. 2021. Does the interaction between the knowledge management process and sustainable development practices boost corporate green innovation? \u003cem\u003eBusiness Strategy and the Environment,\u003c/em\u003e 30\u003cstrong\u003e,\u003c/strong\u003e 4206-4222.\u003c/li\u003e\n\u003cli\u003eSHAHZAD, M., QU, Y., ZAFAR, A. U., REHMAN, S. U. \u0026amp; ISLAM, T. 2020. Exploring the influence of knowledge management process on corporate sustainable performance through green innovation. \u003cem\u003eJournal of Knowledge Management,\u003c/em\u003e 24\u003cstrong\u003e,\u003c/strong\u003e 2079-2106.\u003c/li\u003e\n\u003cli\u003eSRIVASTAVA, S. K. 2007. Green supply‐chain management: a state‐of‐the‐art literature review. \u003cem\u003eInternational journal of management reviews,\u003c/em\u003e 9\u003cstrong\u003e,\u003c/strong\u003e 53-80.\u003c/li\u003e\n\u003cli\u003eTIWARI, P., SADEGHI, J. K. \u0026amp; ESEONU, C. 2020. A sustainable lean production framework with a case implementation: Practice-based view theory. \u003cem\u003eJournal of Cleaner Production,\u003c/em\u003e 277\u003cstrong\u003e,\u003c/strong\u003e\u003c/li\u003e\n\u003cli\u003eTSAI, K. H., HUANG, C. T. \u0026amp; CHEN, Z. H. 2020. Understanding variation in the relationship between environmental management practices and firm performance across studies: A meta‐analytic review. \u003cem\u003eBusiness Strategy and the Environment,\u003c/em\u003e 29\u003cstrong\u003e,\u003c/strong\u003e 547-565.\u003c/li\u003e\n\u003cli\u003eTSENG, S.-M. 2014. The impact of knowledge management capabilities and supplier relationship management on corporate performance. \u003cem\u003eInternational Journal of Production Economics,\u003c/em\u003e 154\u003cstrong\u003e,\u003c/strong\u003e 39-47.\u003c/li\u003e\n\u003cli\u003eWEI, Z., SHEN, H., ZHOU, K. Z. \u0026amp; LI, J. J. 2017. How does environmental corporate social responsibility matter in a dysfunctional institutional environment? Evidence from China. \u003cem\u003eJournal of business ethics,\u003c/em\u003e 140\u003cstrong\u003e,\u003c/strong\u003e 209-223.\u003c/li\u003e\n\u003cli\u003eWIJETHILAKE, C. \u0026amp; LAMA, T. 2019. Sustainability core values and sustainability risk management: Moderating effects of top management commitment and stakeholder pressure. \u003cem\u003eBusiness Strategy and the Environment,\u003c/em\u003e 28\u003cstrong\u003e,\u003c/strong\u003e 143-154.\u003c/li\u003e\n\u003cli\u003eWONG, C. Y., WONG, C. W. \u0026amp; BOON-ITT, S. 2020. Effects of green supply chain integration and green innovation on environmental and cost performance. \u003cem\u003eInternational Journal of Production Research,\u003c/em\u003e 58\u003cstrong\u003e,\u003c/strong\u003e 4589-4609.\u003c/li\u003e\n\u003cli\u003eYARO, N. S. A., SUTANTO, M. H., BALOO, L., HABIB, N. Z., USMAN, A., YOUSAFZAI, A. K., AHMAD, A., BIRNIWA, A. H., JAGABA, A. H. \u0026amp; NOOR, A. 2023. A comprehensive overview of the utilization of recycled waste materials and technologies in asphalt pavements: towards environmental and sustainable low-carbon roads. \u003cem\u003eProcesses,\u003c/em\u003e 11\u003cstrong\u003e,\u003c/strong\u003e\u003c/li\u003e\n\u003cli\u003eYOO, W., MAYBERRY, R., BAE, S., SINGH, K., HE, Q. P. \u0026amp; LILLARD JR, J. W. 2014. A study of effects of multicollinearity in the multivariable analysis. \u003cem\u003eInternational journal of applied science and technology,\u003c/em\u003e 4\u003cstrong\u003e,\u003c/strong\u003e\u003c/li\u003e\n\u003cli\u003eYOUNIS, H., SUNDARAKANI, B. \u0026amp; VEL, P. 2016. The impact of implementing green supply chain management practices on corporate performance. \u003cem\u003eCompetitiveness Review,\u003c/em\u003e 26\u003cstrong\u003e,\u003c/strong\u003e 216-245.\u003c/li\u003e\n\u003cli\u003eYU, Z., WAQAS, M., TABISH, M., TANVEER, M., HAQ, I. U. \u0026amp; KHAN, S. A. R. 2022. Sustainable supply chain management and green technologies: a bibliometric review of literature. \u003cem\u003eEnvironmental Science and Pollution Research,\u003c/em\u003e 29\u003cstrong\u003e,\u003c/strong\u003e 58454-58470.\u003c/li\u003e\n\u003cli\u003eZHENG, H., WANG, L., PENG, W., ZHANG, C., LI, C., ROBINSON, B. E., WU, X., KONG, L., LI, R. \u0026amp; XIAO, Y. 2019. Realizing the values of natural capital for inclusive, sustainable development: Informing China\u0026rsquo;s new ecological development strategy. \u003cem\u003eProceedings of the National Academy of Sciences,\u003c/em\u003e 116\u003cstrong\u003e,\u003c/strong\u003e 8623-8628.\u003c/li\u003e\n\u003cli\u003eZHU, Q. \u0026amp; SARKIS, J. 2007. The moderating effects of institutional pressures on emergent green supply chain practices and performance. \u003cem\u003eInternational journal of production research,\u003c/em\u003e 45\u003cstrong\u003e,\u003c/strong\u003e 4333-4355.\u003c/li\u003e\n\u003cli\u003eZHU, Q., SARKIS, J. \u0026amp; LAI, K.-H. 2012. Examining the effects of green supply chain management practices and their mediations on performance improvements. \u003cem\u003eInternational journal of production research,\u003c/em\u003e 50\u003cstrong\u003e,\u003c/strong\u003e 1377-1394.\u003c/li\u003e\n\u003cli\u003eZHU, Q., SARKIS, J. \u0026amp; LAI, K.-H. 2013. Institutional-based antecedents and performance outcomes of internal and external green supply chain management practices. \u003cem\u003eJournal of Purchasing and Supply Management,\u003c/em\u003e 19\u003cstrong\u003e,\u003c/strong\u003e 106-117.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Sustainable Technology Adoption, Green Supply Chain Integration, Sustainability Culture, Environmental Performance, Government Environmental Regulations, Top Management Commitment","lastPublishedDoi":"10.21203/rs.3.rs-3666203/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-3666203/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cem\u003e\u003cstrong\u003ePurpose: \u003c/strong\u003e\u003c/em\u003e\u003cem\u003eThis study investigates the relationships between sustainable technology adoption, green supply chain integration, sustainability culture, and environmental performance in organizations. It also explores the moderating effects of government environmental regulations and top management commitment on these relationships.\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e\u003cstrong\u003eDesign:\u003c/strong\u003e\u003c/em\u003e\u003cem\u003e The study employs a comprehensive research design, incorporating literature analysis and empirical data collection via survey. Data was gathered through purposive sampling, involving 244 samples from manufacturing companies in Pakistan. PLS-SEM analysis was used to assess the connections between sustainable technology adoption, green supply chain integration, sustainability culture, environmental performance, and the moderating influence of government regulations and top management commitment.\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e\u003cstrong\u003eFindings:\u003c/strong\u003e\u003c/em\u003e\u003cem\u003e The results highlight significant positive relationships between sustainable technology adoption, green supply chain integration, sustainability culture, and improved environmental performance. Additionally, government environmental regulations and top management commitment were identified as moderators that strengthened these relationships, emphasizing their pivotal role in fostering sustainability within organizations.\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e\u003cstrong\u003eOriginality or Value:\u003c/strong\u003e\u003c/em\u003e\u003cem\u003e The study contributes to our understanding of how sustainable technology adoption, green supply chain integration, sustainability culture, and environmental performance are interconnected, while also considering the influence of government regulations and top management commitment. These findings enrich our knowledge of factors that promote sustainability in organizations.\u003c/em\u003e\u003c/p\u003e","manuscriptTitle":"Government Regulations and Top Management Influence on Manufacturing Firms Environmental Performance: Nexus of Green Supply Chain , Culture and Technology Adoption","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-01-19 14:53:01","doi":"10.21203/rs.3.rs-3666203/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"251ea937-91ed-4a9e-b3f7-3b87232afc2d","owner":[],"postedDate":"January 19th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2024-05-22T07:42:09+00:00","versionOfRecord":[],"versionCreatedAt":"2024-01-19 14:53:01","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-3666203","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-3666203","identity":"rs-3666203","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}