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Organizations' technological management capabilities (TMC) have emerged as a powerful tool to enable manufacturing firms to deal with environmental issues. This empirical investigation aims to introduce and validate a novel conceptual framework that seeks to uncover the latent relationships among the selected constructs of this study. Organizational TMC could enhance green production (GP) and reinforce the green competitive advantage (GCA) among manufacturing firms. Therefore, this research investigates the role of TMC of firms such as artificial intelligence capability (AIC), big data analytics capability (BDAC) and Internet of things capability (IOTC) in reshaping green innovation (RGI), employee development (ED), GP and GCA.

The Partial Least Squares-Structural Equation Modeling was proposed to test and validate this research’s conceptual model using 463 valid responses from manufacturing under the China–Pakistan Economic Corridor (CPEC) umbrella.

Our statistical findings confirmed that TMCs such as AIC, BDAC and IOTC supported the GP and CGA. ED and RGI positively correlated to GP. The hypotheses testing results also confirmed the mediating role of ED, RGI and GP and the moderating role of green firm innovativeness capability (GFIC) in the underdeveloped context of the manufacturing industry under the CPEC.

Moreover, the statistical findings of this study extend the existing literature by validating the possible direct, indirect/mediation and indirect/moderation relationship between TMC and GCA.

The circular economy (CE) is an evolving subject transitioning from conceptualization to empirical testing. Over the past decade, researchers have done an exhaustive study to understand the concept of CE and its realized values both financially and environmentally on organizations that have traditional business models based on linear consumption. For understanding the transitional phenomena completely, the paper aims to review the current and emerging research trends in CE to ascertain future direction.

The research was conducted on 91 articles published in the study area during the past decade (2016–2021) in renowned peer-reviewed journals. The criteria set to review literature are based on the following assortment: CE drivers, CE barriers, definitions by different authors, yearly distribution of the publication, research publisher and journals, google citation and methodology used in the selected research articles.

The study suggests that researchers from the selected years are keen to understand the transition and its critical factors by bringing forward frameworks and incorporating CE with digital technologies. The digital technology implied are Industrial Technology (IR) 4.0, Big Data, Internet of Things (IoT), Artificial Intelligence, Blockchain and Data Analytics to increase organizational and environmental performance. CE researchers need to use empirical testing in different sectors to understand and bring forward more improvised business models and practices according to the dynamics of the industry.

The literature review suggests gaps exist to integrate the micro, meso and macro levels to get CE implementation's system-wide benefits. The study has also identified that many CE frameworks available in the literature for implementation must be empirically tested to yield performance results.

The purpose of this study is to examine the impact of Industry 4.0 on economic and environmental performance through the mediation of green supply chain management (GSCM) practices in the emerging economic context, like Pakistan.

This cross-sectional study investigates Industry 4.0 effects on economic and environmental performance through GSCM practices in an emerging economy. For the testing of hypotheses, Smart-PLS is employed. In total, 284 valid responses were analyzed in this study.

The outcomes indicate that GSCM practices mediate the effect of Industry 4.0 on both economic and environmental performance. Also, the results indicate that GSCM practices are positively affected by Industry 4.0.

The scope of this study is limited to manufacturing firms in Pakistan. Future studies may explore other variables that could expedite the adoption of GSCM as the concept of GSCM is still in its infancy. Future studies can conceptualize GSCM through resource based theory as mainstream SCM research has largely ignored the synergistic view of resource based approach in conceptualizing green supply chain models. Implications include policy making that emphasis on enhancing environmental knowledge training.

According to the best knowledge of the researcher, no study has been conducted regarding the effect of Industry 4.0 on economic and environmental performance through the mediation of GSCM practices in the emerging economy, like Pakistan.

Growing emphasis on long-term viability prompts researchers and industry professionals to collaborate on innovative approaches for sustainability and survival. Industry 4.0 (I4.0) technology's importance drives active adoption by firms amidst evolving business dynamics. This research examines the influence of I4.0 technologies on lean, agile resilient and green practices and their impact on supply chain performance.

Survey data from Pakistani manufacturing enterprises were analyzed using SMART PLS to explore the relationship between I4.0 technology, supply chain practices and supply chain performance.

I4.0 technologies significantly impact all practices, while agile and resilient supply chain approaches partially mediate the relationship with supply chain performance.

Insights from this research guide policymakers and business experts in implementing and managing lean, agile, resilient and green practices. Integrating these principles with digital technology solutions enhances supply chain performance.

This study advances understanding of the interplay between I4.0 technologies, practices and supply chain performance, providing a basis for further research and practical implications.

The study explores the linkage between environmental awareness, green practices, firm reputation and performance. Undeniably, very few studies have been conducted on corporate social responsibility (CSR) and its effect on firms' performance.

In the current study, the data are collected from 404 firms located in Pakistan, and structural equation modeling (SEM) is employed to validate hypotheses.

The results show that green practices are statistically significant to build a positive image of firms; also, these practices enhance firm performance. Furthermore, the results also confirmed that CSR practice “indirect support to the community” has an insignificant relationship with firm reputation due to mismanagement and corruption involvement on governmental levels.

This study suggests that the firms' management should spend money on CSR activities and concentrate on proper monitoring of CSR activities to utilize funds efficiently. The research is conducted in Pakistan's context, while future studies need to be conducted in other emerging economies to investigate the linkage between CSR, firm reputation and performance.

According to the researcher's best knowledge, very few studies have been conducted regarding the relationship between environmental awareness, green practices, firm reputation and performance in emerging economies like Pakistan.

The current study investigates the effect of industry 4.0 on green practices, including green manufacturing and green logistics, in the context of emerging economies.

A cross-sectional data were collected from 234 manufacturing firms in Pakistan, and PLS-SEM was employed to test hypotheses.

With the advent of industry 4.0 in the current era, more emphasis is being given to the adoption of digital technologies in every field. The adoption of the green approach in supply chain management provides firms with socioeconomic and environmental benefits. The study results indicate that industry 4.0 positively affects green practices, including green manufacturing and green logistics. Moreover, the results also illustrate that these green practices have a substantial effect on the sustainability performance of the firms.

This study provides an amplified understanding of the industry 4.0 technologies in the adoption of green practices. The outcomes also offer a policy framework for managers, legislators and manufacturers to promote green practices (i.e. green manufacturing and green logistics) in businesses.

Although several recent studies have tried to investigate the effect of green practices on sustainability performance. However, as per the author's best knowledge, very few studies have analyzed the influence of industry 4.0 on green practices (i.e. green manufacturing and green logistics) in the context of emerging economies.

Amid rising environmental concerns, Industry 4.0 and blockchain technology (BCT) are transforming circular economy practices and prevailing business models. Recognizing the same, the current study examines the role of advanced technology in circular practices and their impact on eco-environmental performance, which influences organizational performance. The study collects data from 185 food processing enterprises that are located in Malaysian territories. By employing CB-SEM modeling, the study provides three key findings. First, Industry 4.0 significantly improves the circular economy practices. Second, circular economy practices help to improve firms' environmental performance but did not stimulate operational performance. Third, higher eco-environmental performance significantly boosts organizational performance. This study set out the foundations for participating countries/firms that help to achieve sustainable goals through the integration of blockchain technology in circular economy practices.

The abrupt outbreak of coronavirus disease (COVID-19) hit every nation in 2020–2021, causing a worldwide pandemic. The worldwide COVID-19 epidemic, described as a “black swan”, has severely disrupted manufacturing firms' supply chain. The purpose of this study is to investigate how supply chain data analytics enable the effective deployment of agility, adaptability and alignment (3As) strategies, resulting in improving post-COVID disruption performance. It also analyses the indirect effect of supply chain data analytics on disruption performance through the 3As supply chain strategies.

The hypothesis and theoretical framework were tested using a questionnaire survey. The authors employed structural equation modelling through the SMART PLS version 3.2.7 to analyse data from 163 textile firms located in Pakistan.

The results revealed that the supply chain data analytics contributed positively and significantly to the agility and adaptability, while all 3As supply chain strategies impacted the PPERF substantially. Further, the connection between supply chain data analytics (SCDA) and disruption performance has substantially been influenced through 3As supply chain strategies.

The results imply that in the event of low likelihood, high effect disruptions, managers and decision-makers should focus their efforts on integrating data analytics capabilities with 3As supply chain policies to ensure long-term company success.

This research sheds fresh light on the importance of data analytics in effectively implementing 3As strategies for sustaining company performance amid COVID-19 disruptions.

The primary aim of this study is to examine the decision-making process of a reverse supply chain within a cooperative-competitive environment, with a particular emphasis on the incorporation of Internet of Things (IoT) technology in the recycling process.

The impact of IoT on recycling effectiveness, RF (refurbished) product demand and remanufacturing expenses is analyzed. The game-theoretic models are constructed to incorporate the co-competitive relationship between a IR (Internet Recycler) and a remanufacturer, with specific attention paid to the IR's application of IoT technology.

The results indicate that the use of IoT reduces the costs associated with remanufacturing, leading to an increase in the transfer price of pre-owned items procured from IRs. The efficacy of the reverse supply chain depends not only on its cost-saving capabilities but also on consumer preferences toward RF and remanufactured (RM) items.

IoT technology can benefit Internet recycling and remanufacturing by enhancing transparency, quality monitoring and automation of processes. It can also help reduce operating costs, improve customer engagement and incentivize cooperation between organizations.

This study examined the strategic decision-making processes in the context of cooperation and competition between IR and remanufacturers. In addition, this research makes a valuable contribution to the literature by elucidating the optimal conditions for the effective implementation of Internet of Things (IoT) technology in recycling operations.