China’s textile and fashion industry, commanding a substantial 31.7% of global clothing exports in 2022 (DFU, 2023; Li et al., 2021), is a cornerstone of its economic framework, driving significant growth and providing extensive employment opportunities both domestically and internationally (Rafiq et al., 2023; Yang et al., 2023). However, China’s textile and fashion industry is a significant contributor to negative externalities, particularly environmental degradation. The industry faces severe environmental challenges. It is a major source of greenhouse gas (GHG) emissions due to its energy-intensive production processes, and it significantly contributes to air pollution through high levels of particulate matter (PM2.5 and PM10), which are detrimental to the air quality and ecological footprint (Minlah and Zhang, 2021; Peng et al., 2022; Zhao and Lin, 2019). The industry’s ecological footprint is also exacerbated by excessive water use, pollution from dyeing and finishing processes, and substantial waste generation (Herbst, 2021; Lu, 2021). To address these challenges, the Chinese government has enacted a suite of policies aimed at reducing the sector’s environmental impact. These include regulations to improve energy efficiency, lower emissions, and adopt cleaner production techniques. The 14th Five-Year Plan (FYP) (2021–2025) outlines a greener textile and fashion industry strategy by promoting a circular economy, advancing technological innovations, and implementing stringent pollution controls (Gao et al., 2022; Xu et al., 2024). Environmental taxes have also been introduced to incentivize emissions and reduce resource use, supporting China’s goal of achieving carbon neutrality by 2060 (Ruggerio, 2021).

Environmental regulation has become a crucial instrument in addressing these issues during periods of rapid economic development (Zhang H. et al., 2022). By 2013, China had established 30 national laws, over 1,400 industrial standards, and 314 local regulations related to environmental governance (Zheng and Shi, 2017). Implementing a stringent environmental protection law in 2015 further advanced the country’s regulatory framework. Despite these measures, the efficacy of China’s environmental regulations remains insufficient (Zhang H. et al., 2022). The 2020 Global Environmental Performance Index (EPI) ranked China 120th out of 180 countries in air quality, indicating ongoing pollution challenges. These persistent issues are primarily due to the incomplete implementation of central government policies at the local level, which is a phenomenon known as the “implementation gap” (Zhao et al., 2022).

Despite recent policy initiatives, significant gaps persist in understanding the environmental impact of China’s textile and fashion industry. Theoretically, the environmental Kuznets curve (EKC) model, which suggests that environmental degradation initially increases with economic growth but decreases as economies mature, inadequately addresses the complexities of this sector. The interplay among policy measures, technological advancements, and regulatory frameworks presents a more intricate scenario than the EKC model encompasses (He et al., 2021; Zhang et al., 2022b). This underscores the need for a comprehensive framework to better grasp the sector’s environmental performance. Key questions include how current environmental policies influence efficiency and whether these policies effectively drive improvements in the industry’s environmental impact. A significant conceptual gap exists in understanding how technological advancements and renewable energy adoption interact within policy frameworks, as current literature often isolates these factors and neglects their combined impact on environmental efficiency (Fernández et al., 2018). Moreover, the role of environmental policies, taxes, research and development (R&D), and renewable energy across different textile and fashion sectors remains underexplored. This integration is crucial for assessing how these elements collectively influence regulatory effectiveness. Additionally, the specific effects of environmental taxes on the textile and fashion industry are insufficiently examined. Understanding how these taxes impact industry practices is essential for evaluating their effectiveness and refining policy design (Ruggerio, 2021).

Empirical research on environmental regulations often overlooks the specific response of China’s textile and fashion industry, particularly concerning the effects of environmental taxes and the role of R&D in driving technological innovation. Additionally, the impact of renewable energy adoption on the industry’s ecological footprint remains insufficiently examined (Chen et al., 2021; Leal Filho et al., 2022). This underscores the need for targeted studies to better understand how regulatory measures, technological advancements, and renewable energy integration collectively influence environmental performance. Furthermore, the interaction between technological innovation and policy frameworks, particularly in relation to the impact of renewable energy adoption on environmental efficiency, warrants comprehensive exploration. A deeper understanding of these critical areas is vital for crafting more effective and informed policy strategies.

The findings reveal that stringent environmental regulations and taxes are potent drivers of sustainable practices, significantly reducing greenhouse gas emissions and particulate matter. Although technological advancements, particularly in environmental technologies and R&D, are vital, they initially increase the industry’s ecological footprint due to high costs and adjustments. However, the transition to renewable energy is pivotal for substantial long-term reductions in carbon emissions. The LFP and FP sectors exhibit notably higher coefficients related to GHG emissions and environmental pollutants than other textile and fashion sectors, underscoring the substantial impact of policy implementation in these areas. This finding highlights the effectiveness and prioritization of environmental regulations within these sectors, signaling a critical focus on mitigating environmental impact through targeted policy measures. The necessity of an integrated regulatory framework that harmonizes policy, technology, and renewable energy to achieve sustained environmental improvements is emphasized the study. Furthermore, a dynamic, reciprocal relationship between technological progress and regulatory advancements is highlighted, where each fosters the other’s evolution, creating a reinforcing cycle essential for long-term environmental sustainability.

This study significantly advances our understanding of environmental sustainability within China’s textile and fashion industry by offering a sector-specific analysis of the total textile production, leather and feather production, fashion production, and combined textile and fashion production. By examining the textile and fashion sectors, the study addresses crucial questions about the varying impacts of policies, technologies, and renewable energy adoption on environmental efficiency. It reveals that whereas environmental policies and taxes broadly enhance the efficiency, the effectiveness of technological innovations and renewable energy adoption differs significantly across industry segments, depending on their unique characteristics and practices. It fills a critical gap by revealing how different segments respond to environmental regulations and innovations, providing a comprehensive view of the industry’s environmental performance. The study extends the EKC model and the regulatory push innovation hypothesis, demonstrating how regulatory measures and technological advancements uniquely interact within the textile sector to influence environmental outcomes. By integrating the effects of technological innovation, R&D, and renewable energy adoption, this research presents a holistic framework that illustrates the combined impact of these factors on environmental efficiency. Empirically, it clarifies the role of environmental policies and taxes in driving technological innovation and promoting cleaner production practices. It also highlights the significant benefits of renewable energy adoption in reducing the industry’s ecological footprint. The study’s theoretical implications challenge simplified assumptions, advocating for an integrated approach to environmental management. Practically, it provides actionable insights for policymakers and industry leaders, emphasizing the need for cohesive strategies that combine stringent regulations, supportive policies, and technological investments to drive sustainability and enhance competitiveness.

The theoretical foundation of environmental regulation is grounded in frameworks that explore how regulatory policies shape industrial behavior, innovation, and economic performance. A key theory in this domain is the EKC hypothesis, which posits an inverted U-shaped relationship between environmental degradation and economic development. According to this model, in the initial stages of economic growth, industrialization and increased consumption lead to an increase in environmental pollutants and resource depletion. The trend reverses as an economy continues to expand and reaches a certain threshold of income per capita (Minlah and Zhang, 2021). Higher levels of income facilitate greater investment in cleaner technologies, enhance public demand for environmental quality, and enable the implementation of more stringent regulatory measures. Consequently, further economic growth contributes to reducing pollutants and improving environmental conditions. The EKC suggests that increased economic pressures and regulatory measures can improve environmental outcomes over time (Zhang et al., 2022b). This framework implies that sufficient economic advancement and appropriate policy frameworks can achieve both continued economic growth and enhanced environmental quality. Thus, the EKC underscores the potential for harmonizing economic development with environmental sustainability through targeted regulatory and technological strategies.

Complementing this view are theories of sustainable development and industrial ecology. Sustainable development theory advocates for a balance between economic growth, environmental protection, and social equity, integrating environmental considerations into industrial policy to promote practices that reduce resource consumption and environmental impact (Ruggerio, 2021). Industrial ecology extends this by viewing industrial systems as part of a broader ecological system, emphasizing closed-loop systems and resource optimization to minimize waste and environmental footprints. Together, these frameworks provide a comprehensive lens for examining how stringent environmental regulations in China’s textile and fashion industry can drive innovation, improve environmental performance, and support sustainable economic development.

Building on the foundational theories outlined above, this study introduces several key theoretical assumptions that further deepen our understanding of how environmental regulations shape industrial behavior and performance, particularly in the context of China’s textile and fashion industry. One critical assumption is the regulatory push innovation hypothesis, which posits that stringent environmental regulations act as a catalyst for innovation in industrial sectors (Bitat, 2018). In response to increasing regulatory pressures, firms are incentivized to adopt cleaner technologies, enhance operational efficiency, and develop sustainable processes. Drawing on Porter’s hypothesis, which suggests that environmental regulations can drive firms to innovate and unlock new market opportunities, we argue that China’s textile industry is no exception (Bibi et al., 2024). Faced with both domestic and international regulatory demands, firms are compelled to innovate in ways that improve their environmental performance while maintaining competitive advantage (Khan et al., 2023).

Another important assumption is that of policy synergy and interaction (Li et al., 2024). This assumption asserts that environmental regulations, technological innovation, taxes, and renewable energy policies interact synergistically to amplify their collective impact on sustainability. Rather than operating in isolation, these policy instruments reinforce each other, creating a comprehensive policy environment that accelerates the adoption of green technologies and practices. For instance, the effectiveness of renewable energy adoption in the textile industry can be significantly enhanced when paired with carbon taxes or green subsidies, facilitating the transition to more sustainable production methods. This assumption highlights the necessity for coherent and integrated policy frameworks to drive significant environmental improvements. Furthermore, we propose the dynamic interaction assumption, which draws on the EKC hypothesis to explain how economic growth and environmental regulations interact over time. As China’s textile and fashion industry continues to grow, the initial phase of rapid industrialization often leads to environmental degradation. However, as the economy matures, a shift occurs, where firms, driven by consumer demand for sustainability and regulatory incentives, begin to adopt cleaner technologies and more sustainable practices. This dynamic shift underscores the potential for harmonizing economic growth with environmental sustainability through effective regulation and innovation.

Finally, the globalization assumption suggests that international pressures, particularly from global consumers and stakeholders (Baah et al., 2021; Christmann, 2004), significantly influence the environmental performance of the textile industry in China. With increasing demand for sustainable products in global markets, Chinese firms are compelled to align with international sustainability standards. This not only drives innovation and compliance with both domestic and foreign regulations but also reflects the broader phenomenon of environmental globalization. The increasing importance of international consumer preferences and regulatory frameworks compels industries worldwide to adopt sustainable practices, influencing the trajectory of environmental policy and performance in the Chinese textile sector. Together, these theoretical assumptions provide a comprehensive lens to examine the complex relationships among environmental regulations, innovation, and industry performance. By integrating these assumptions into our framework, we offer a more nuanced understanding of how regulatory pressures, economic growth, and globalization intersect to drive sustainable practices in China’s textile and fashion industry.

Four multivariate equations were estimated each for GHG emissions, PM2.5, PM10, and ecological footprint. The ARDL bounds test approach was applied to examine cointegration between variables. As the ARDL bounds test is sensitive to lag length, the VAR lag length criteria were used to determine the appropriate lag length for each equation. Table 4 shows the bounds test results, indicating that all the estimated bounds test equations for GHG emissions, PM2.5, PM10, and EFP were cointegrated as the F-calculated values are greater than F-tabulated values (Khan et al., 2023).

Table 5 shows the textile and fashion industry’s sector-wise long and short-run results. The long-run dynamics show that the equation estimated for TMP impacts on GHG emissions indicates that environmental policy controls (EPCs) with δ = −0.081*, ER with δ = −0.102*, REG with δ = −0.567*, PGDP with δ = −0.377*, and TMP with δ = −0.059* negatively influence GHG emissions in the TMP sector. The long-run assessment of the LFP sector indicates that environmental regulations (ER) with δ = −0.073*, REG with δ = −0.564*, PGDP with δ = −0.399*, and LFP with δ = −0.101* negatively impact GHG emissions. Likewise, the long-run results of the FP sector show EPC with δ = −0.0312***, ER with δ = −0.068*, REG with δ = −0.588*, PGDP with δ = −0.390*, and FP with δ = −0.091* also negatively influence GHG emissions. The fourth equation estimated for GHG emissions demonstrates that ER with δ = −0.078*, REG with δ = −0.487*, PGDP with δ = −0.385*, and TTP with δ = −0.115* indicate the environmental efficiency of these indicators. Interestingly, R&D and environmental technologies indicate positive impacts in all four equations estimated for GHG emissions (see Table 5).

Four additional equations were calculated to assess the impacts of environmental instruments on PM2.5 in the textile and fashion industry. Table 5 shows that EPC with δ = −0.125*, ER with δ = −0.058*, REG with δ = −0.487*, PGDP with δ = −0.189*, and TMP with δ = −0.063* negatively influence PM2.5. The long-run estimates indicate that EPC with δ = −0.061*, ER with δ = −0.112*, REG with δ = −0.403*, PGDP with δ = −0.236*, and LFP with δ = −0.123* negatively affect PM2.5 in the leather and feather production sector. The long-run dynamics for the fashion production sector indicate that EPC with δ = −0.075***, ER with δ = −0.105*, REG with δ = −0.408*, PGDP with δ = −0.234*, and FP with δ = −0.107* significantly influence PM2.5. Similarly, the long-run indicator for TTP shows that EPC with δ = −0.055*, ER with δ = −0.105*, REG with δ = −0.289*, PGDP with δ = −0.254*, and TPP with δ = −0.154* significantly influence PM2.5. Similar to GHG emissions, R&D and environmental technologies (ET) show a positive effect on PM2.5 in all four sectors.

The estimated equation for PM10 indicates that EPC with δ = −0.117*, REG with δ = −0.252*, PGDP with δ = −0.139*, and TMP with δ = −0.056* significantly influence PM10 in the textile production sector. The long-run estimates show that EPC with δ = −0.033**, ER with δ = −0.086*, REG with δ = −0.319*, PGDP with δ = −0.14*, and LFP with δ = −0.126* negatively influence PM10 in the LFP sector. The long-run impacts in the fashion sector indicate that EPC with δ = −0.066*, ER with δ = −0.058*, REG with δ = −0.320*, PGDP with δ = −0.203*, and FP with δ = −0.102* significantly influence PM10 emissions in the fashion production sector. The estimates for the TTP sector shows that EPC with δ = −0.044*, ER with δ = −0.086*, REG with δ = −0.205*, PGDP with δ = −0.227*, and TTP with δ = −0.152* significantly affect PM10 emissions.

The long-run dynamics for ecological footprint indicate that only REG with δ = −0.352*, R&D with δ = −0.119**, and TMP with δ = −0.021*** significantly influence EFP in the textile production sector. Likewise, REG with δ = −0.346*, R&D with δ = −0.129**, and LFP with δ = −0.022*** significantly influence EFP in the leather and feather production sector. The long-run indicators show that REG with δ = −0.353*, R&D with δ = −0.110**, and FP with δ = −0.028* significantly affect EFP in the fashion production sector. The long-run dynamics show that EPC with δ = −0.018***, REG with δ = −0.335*, R&D with δ = −0.127*, and TTP with δ = −0.028*** significantly influence EFP in the TTP sector. However, environmental technologies positively and significantly impact EFP in all four sectors.

The lower part of Table 5 shows the short-run results, equation diagnostics, and model fits. The short-run results are considered in the Findings and Discussion sections to support the arguments for policy recommendations based on long-run dynamics. The diagnostics test indicators suggest that all estimated models are free of serial correlation and heteroskedasticity problems. The adjusted-R² is a measure of accuracy for regression models. Table 5 shows that adjusted-R² for all the models was significant, indicating the model’s goodness of fit. All error correction models were negative and statistically significant at the 5% level, consistent with the assumptions of the ARDL framework. The ECM represents the speed at which the system returns to equilibrium after a deviation in the long-run relationship, with its value expected to be greater than −2 and within the unit circle (Adeleye et al., 2018). Additionally, the results of the cumulative sum (CUSUM) and cumulative sum of squares (CUSUMSQ) tests for most models fell within the 5% significance boundaries, confirming the stability of the models (Xiong et al., 2023).

The estimated Granger causality results given in Table 6 indicate that GHG emissions demonstrate bidirectional causalities with EFP, ER, ET, PGDP, REG, and TTP. However, EPC, R&D, TMP, LFP, and FP establish unidirectional causalities with GHG emissions. PM2.5 bidirectional Granger causes EPC, ER, and REG. In addition, TMP, LFP, FP, and TTP unidirectionally cause PM2.5. Similarly, PM10 is bidirectional, causing EPC and REG; however, TMP, LFP, FP, and TTP unidirectionally cause PM10. The ecological footprint bidirectionally causes GHG, ER, PGDP, REG, and TTP. Likewise, EPC, ET, R&D, TMP, LFP, and FP unidirectionally cause EFP. Further details on EPC, ER, ET, and REG causalities are given in Table 6.

In this study, we examine the interaction among environmental policies, technological innovations, and renewable energy adoption to enhance environmental efficiency in the textile and fashion industry. Our findings demonstrate that stringent environmental regulations and taxes effectively drive the sector toward sustainable practices by significantly improving environmental performance. Although technological advancements are vital for long-term sustainability, our research shows that ET and research and development (R&D) impact different pollutants and may initially increase the ecological footprint due to high upfront costs and adjustments. Conversely, transitioning to renewable energy sources is crucial for significantly reducing the industry’s carbon footprint. The LFP and FP sectors demonstrate greater responsiveness to environmental policies and regulations than other sectors, underscoring the significant influence of policy implementation in these areas. This observation highlights the effectiveness and prioritization of environmental regulations within these sectors, reflecting a strategic emphasis on the reducing environmental impact through well-targeted policy measures. These findings provide a clear and actionable strategy, illustrating how an integrated regulatory framework, innovative technologies, and renewable energy can lead to a more sustainable and environmentally responsible textile industry. The contextual insights provided by this study are highly relevant to China’s current environmental and industrial landscape. The findings reflect the dynamic interplay among policy, technology, and industry practices, offering practical recommendations for improving environmental efficiency. The research also contributes to the broader discourse on sustainable development by providing evidence-based insights into how different factors influence environmental performance in the textile and fashion industry (Li et al., 2021; Wang and Yu, 2021).

The use of taxes as a regulatory mechanism to mitigate the textile industry’s environmental impact has gained increasing importance, particularly in China, where the sector is a significant contributor to pollution (DFU, 2023; Yu and Cheng, 2021). This study demonstrates that environmental policies and taxes effectively reduce GHG emissions and particulate matter (PM2.5 and PM10) across textile and fashion sectors (TMP, LFP, FP, and TTP). While EPCs significantly influence TTP, their broader impact is limited, suggesting that EPCs are more effective at the aggregate production level. In contrast, environmental taxes exhibit greater efficacy across all sectors, highlighting their superiority in curbing GHG emissions and air pollutants. The Granger causality analysis (Table 6) further confirms that both ERs and EPCs are causally linked to reductions in GHG, PM2.5, PM10, and ecological footprints, emphasizing the effectiveness of an integrated regulatory framework. These findings are in line with those obtained by He et al. (2021), suggesting that environmental taxes and policies are instrumental in reducing GHG emissions and air pollutants. Taxes are strict regulatory instruments; therefore, this study is in line with that by Shen et al. (2020), who suggested that command-and-control-type environmental policy tools positively affect green production.

China’s regulatory framework for environmental protection has evolved significantly since the 1979 Environmental Protection Law. For instance, the Circular Economy Promotion Law (2009) mandates efficient resource use and waste reduction across industries, including textiles (Chen et al., 2021). The Cleaner Production Promotion Law (2003, revised 2012) builds on this foundation by mandating cleaner production audits, reducing toxic substance usage, and improving resource efficiency (Xu et al., 2024). The cornerstone of China’s environmental governance is the Environmental Protection Law (revised 2014), which imposes stringent penalties for non-compliance and strengthens the authority of environmental protection agencies. This law has led to stricter pollution controls and increased accountability within the textile industry; however, enforcement challenges persist, particularly in economically dependent regions (Zhang et al., 2017).

The introduction of the Environmental Protection Tax Law (2018) marked a significant shift from pollution fees to a structured tax system, targeting air and water pollutants, solid waste, and noise emissions (Gao et al., 2022). China’s FYPs further reinforce these regulatory efforts. The 13th FYP (2016–2020) made strides in reducing the energy intensity of the textile industry and promoting cleaner technologies. The 14th FYP (2021–2025) continues this trajectory with a heightened focus on green transformation and technological innovation. The 15th Five-Year Plan (2025–2030) emphasizes China’s commitment to achieving its carbon neutrality goals. This plan focuses on advancing the nation’s efforts toward zero-carbon emissions by 2060, promoting carbon neutrality, and further integrating green transformation and technological innovation across industries. The 15th FYP also prioritizes developing and implementing sustainable practices and technologies to accelerate the transition to a low-carbon economy. Despite these advances, challenges remain in achieving consistent implementation and target goals. Bidirectional causality among GHG emissions, PM2.5, PM10, EFP, environmental policies, technological advancements, and renewable energy transitions is revealed in this study, highlighting a complex, reciprocal relationship. In this study, we reveal that TMP, LFP, FP, and TTP exhibit unidirectional causality with GHG emissions, PM2.5, PM10, and EFP, indicating that these sectors respond to environmental policies, taxes, and technological changes.

The higher coefficient of REG indicates that it is the more efficient path for mitigating the GHG emissions, air pollutants, and ecological footprint in the textile and fashion industry. This study’s findings also underscore the pivotal role of renewable energy adoption in reducing the industry’s carbon footprint. The shift to renewable energy sources is vital for achieving significant long-term reductions in GHG emissions, supporting the theories of sustainable development and industrial ecology (Berg et al., 2019). By minimizing reliance on fossil fuels and optimizing resource use, renewable energy integration aligns with the principles of closed-loop systems and resource optimization advocated by industrial ecology (Chen et al., 2021). The findings support the notion that technological advancements and renewable energy adoption are critical for achieving higher levels of environmental efficiency, consistent with the conclusions obtained by Liu et al. (2019) and Yang et al. (2023). The Cleaner Production Promotion Law has driven significant improvements in waste management and energy efficiency within the textile sector; however, its effectiveness is contingent on consistent local enforcement (Xu et al., 2024). In addition, the Environmental Protection Tax Law (2018) incentivizes the adoption of pollution control technologies and more sustainable practices within the textile industry and mitigates GHG emissions by 41% and PM by 39% (Gao et al., 2022).

Environmental technologies and R&D have significant positive impacts on GHG emissions and environmental pollutants. However, ET and R&D only establish a causal relationship between GHG emissions and EFP (see Table 6). Interestingly, ET and R&D unidirectionally cause EPC and bidirectionally cause ER and REG. This study’s findings contradict those obtained by Ghazouani et al. (2021) and Fernández et al. (2018), who suggested that ET and R&D significantly reduce GHG emissions in European countries. These findings indicate that investments in these areas are effective tools for environmental improvement. The unidirectional causality among ET, R&D, and EPC suggests that advancements in technology and R&D drive the development and implementation of stricter environmental policies. This implies that as new technologies emerge and R&D efforts advance, they create the groundwork for more stringent regulatory frameworks, likely because policymakers see the potential of these technologies to mitigate environmental impact effectively. The bidirectional causality among ET, R&D, ER, and REG indicates a dynamic interplay, where regulatory frameworks influence technological advancements. This mutual relationship suggests that as environmental regulations become more stringent, they push for further innovation in ET and R&D and the adoption of REG. Simultaneously, as new technologies and R&D outcomes become available, they encourage the evolution of more refined and targeted regulations. These findings underscore the critical role of ET, R&D, and renewable energy in shaping and being shaped by environmental policies and regulations. They reveal a feedback loop where technological progress and renewable energy adoption foster regulatory advancements, which, in turn, stimulate further innovation and adoption, creating a reinforcing cycle of environmental improvement. This dynamic interplay is essential for achieving sustained reductions in GHG emissions and broader environmental pollutants.

In conclusion, in this study, we offer significant insights into the intricate relationship among environmental regulations, technological innovation, and renewable energy adoption within China’s textile and fashion industry. Whereas the EKC hypothesis posits a straightforward, linear relationship between economic development and environmental improvement, our findings reveal a more complex dynamic. The analysis demonstrates that the relationship between environmental regulations and sustainability is not one-directional. Instead, there exists a bidirectional influence where regulatory frameworks and technological advancements mutually reinforce each other. As companies in the textile sector face increasingly stringent regulations, they are prompted to innovate, adopting cleaner technologies and enhancing environmental practices. This innovation, in turn, drives further regulatory refinement as governments respond to industry advancements by enacting more targeted and supportive policies. Therefore, the relationship between regulation and innovation is dynamic and interdependent, rather than merely reactive. In this study, we also emphasize the necessity of an integrated approach to sustainability. It is not sufficient for policies and innovations to exist in isolation; they must be harmonized to achieve significant and long-lasting improvements. The synergistic interaction of environmental regulations, technological innovation, and renewable energy adoption creates a cohesive framework that can drive substantial environmental benefits. This finding suggests that policymakers should craft regulations that not only enforce compliance but also encourage innovation, particularly in the areas of renewable energy and sustainable production technologies. By designing policy frameworks that incentivize firms to adopt green technologies and renewable energy solutions, governments can facilitate a smooth transition to more sustainable practices across the industry.

The practical implications of this research are profound. Industry leaders must begin to view environmental regulations not as obstacles but as catalysts for innovation and business growth. In an increasingly competitive global market, the ability to innovate in response to regulatory pressures can provide firms with a distinct competitive edge. Furthermore, aligning innovation efforts with global sustainability goals will not only enhance the environmental performance of the industry but also position it as a leader in the global shift toward sustainable production practices. In this study, we also underscore the importance of collaboration among industry stakeholders, regulatory bodies, and international organizations to create a cohesive approach to sustainability that can serve as a model for other sectors. Ultimately, this research highlights that the path to sustainability in the textile and fashion industry is multifaceted and requires a concerted effort from all involved parties. By integrating regulatory pressures, technological innovation, and renewable energy adoption, the industry can navigate the complexities of environmental sustainability and become a benchmark for other sectors striving to balance economic growth with environmental responsibility. This study contributes to the growing body of knowledge on sustainability, providing both theoretical and practical frameworks for achieving long-term environmental improvements in resource-intensive industries.

This study is not without its limitations. One significant limitation is that the analysis primarily relies on existing data, which, although comprehensive, may not fully capture the latest technological and regulatory innovations within the textile and fashion industry. As the industry continues to evolve rapidly, the data available for analysis may not reflect recent shifts in technological advancements or regulatory frameworks. Additionally, the study’s focus on specific regional contexts—namely, China’s textile and fashion industry—may limit the broader applicability of the findings to other geographic areas with differing regulatory environments and market conditions. The diversity of regulatory policies across countries and regions, as well as varying levels of technological adoption in various textile and fashion sectors, presents a challenge to generalizing the results to a global scale. Future research should address these limitations by incorporating longitudinal studies that track the evolution of technological and regulatory landscapes over time. Such studies would provide a richer understanding of how industry dynamics and environmental regulations evolve, especially as new technologies and policy frameworks emerge.

Furthermore, the study does not delve into the direct impact of specific policy changes, which represents another important gap in the analysis. The absence of specific policy intervention data limits the ability to assess the nuanced effects of particular regulatory measures on sustainability outcomes. Future research could significantly benefit from adopting advanced methodologies such as difference-in-differences (DID) to analyze the causal impact of policy changes. By isolating the effects of specific regulatory interventions, such research would provide valuable insights into how particular policies drive technological innovation and environmental performance. This approach could be instrumental in formulating more targeted and effective policies for enhancing sustainability in the textile and fashion industry, offering clearer guidance for policymakers seeking to optimize regulatory strategies. In addition, comparative analyses across different regions and industries would further expand the generalizability of the findings and offer a more comprehensive understanding of how various factors—such as market conditions, regulatory intensity, and technological capabilities—interact to influence sustainability outcomes. By comparing industries in different countries or regions, research workers could identify patterns of innovation and regulatory success, providing a broader perspective on what drives industry-wide sustainability.