Analyzing the impact of environmental collaboration among supply chain stakeholders on a firm’s sustainable performance

Influence of financial accounting information transparency on supply chain financial decision-making

The study examines the ecological and economic effects of the Chinese environment supply chain financial decision-making recommendation systems from 2009 to 2021. Environment analytics has become essential for organizations because of the rapid growth of digital technology and data. This technology offers exceptional corporate performance and environmental sustainability opportunities. This research uses Spatial Durbin Models and mediation effect analysis to examine how environment adoption affects key company performance measures. It also discusses the differences between industry and business models. Environment technologies improve operating efficiency, customer happiness, and company value. According to findings, environmental technology may streamline operational operations, boost customer happiness, and generate value, improving financial performance. Big data has ecological benefits, according to the findings. Environment technology may reduce a firm's environmental effect by improving operational efficiency and allowing sustainable practices. Research shows significant industry and organizational differences. This highlights the need for ecological plans for each sector's needs. Big data also mediates, showing that the environment may affect other operational aspects and increase their impact. Data ethics and responsibility are crucial. The findings demonstrate that the climate may support sustainable behaviors and meet environmental sustainability goals. To better understand big data's revolutionary power. Enterprises must carefully manage and responsibly use this powerful tool to maximize its benefits and minimize its disadvantages. This research will shape environmental strategies and practices as digital possibilities present themselves to enterprises and society.

Energy transition and environmental stability prospects for OECD economies: The prominence role of environmental governance, and economic complexity: Does the geopolitical risk matter?

The global increase in temperature and climate change signals the need for humanity to reduce greenhouse gas emissions and to adopt eco-friendly lifestyles. The 2023 United Nations Climate Change Conference (COP28) in the UAE emphasized this, urging nations to commit to the Paris Agreement and pursue a greener, carbon-free future. In recent decades, climate change has become a critical issue, primarily because of the extensive use of fossil fuels and conventional energy resources. Economic growth has led to an increase in energy consumption and widespread environmental damage. The present study empirically explores whether any changes in environmental governance, economic complexity, geopolitical risk, and the interaction term influence energy transition and environmental stability in OECD economies over the period 1990-2021. Novel econometric methods, including Westerlund co-integration and the Method of Moments Quantile Regression (MMQR), are employed to address complexities such as cross-sectional dependency and panel causality. The key findings from the MMQR technique showed a positive link between environmental governance and economic complexity in driving sustainable energy transitions, thus bolstering environmental resilience in OECD countries. However, economic complexity counterbalances environmental stability. Significantly, geopolitical risk acts as a moderating variable, enhancing the effects of governance and complexity on sustainable energy practices and environmental stability. Based on these insights, this study recommends strategic initiatives, including investment in eco-friendly technologies, to fast-track the shift to clean energy and strengthen environmental resilience in OECD countries. These strategies align with the broader objectives of global sustainable development, offering a path towards a greener and more sustainable future.

Disentangling circular economy practices and firm's sustainability performance: A systematic literature review of past achievements and future promises

This paper systematically and critically reviews the literature on the intersection of circular economy practices (CEPs) and sustainability performance (SP). We synthesize and analyze the extant literature to uncover the knowledge gaps, highlight the contradictory views, and provide a comprehensive overview of the field. Following a detailed database search, we selected 104 empirical studies published in peer-reviewed journals for analysis. Our review reports the publication trends, top publishing journal outlets, research methodologies, and empirical contexts. We outline the theoretical underpinnings, identify the diverse circular economy practices and the key factors that impact circular economy practices and sustainable performance. The review shows a propensity for most authors to reuse established theories or not use theory at all, revealing the need for theory development. Furthermore, our analysis revealed that R&D and innovation, digital technologies, organizational capabilities/resources, and stakeholder and institutional pressure substantially influence the CEPs - SP relationship. Through our detailed assessment of the existing literature, we identified and proposed several themes and avenues for future research.

The nexus between green intellectual capital, blockchain technology, green manufacturing, and sustainable performance

Enterprises across the globe are facing increasing pressure to effectively utilize resources and reduce costs through green supply chain practices. Emerging technology, such as blockchain technology which enables green practices, has become a contemporary industrial paradigm. However, enterprises need to build green intellectual capital to implement blockchain technology, which can be key to realizing green supply chain practices. This research examines the impact of green intellectual capital (GIC) on blockchain technology and its role in implementing green manufacturing to achieve sustainability. Partial least squares structural equation modeling was utilized for assessing the proposed hypotheses, and cross-sectional data was accumulated from manufacturing firms. As per the results, GIC, which includes green human capital, green structural capital, and green relational capital has a crucial role in the implementation of blockchain technology. The outcomes also indicated that the adoption of blockchain technology significantly influences green manufacturing. Moreover, green manufacturing (GM) has a substantial role in improving business sustainability. This empirical research provides a deeper understanding of how GIC and blockchain technology contribute to the implementation of GM. This research also provides guidelines that managers, policymakers, and producers can use to facilitate the incorporation of GM practice into business activities.

Emissions reduction strategy in a three-stage agrifood value chain: A dynamic differential game approach

Agrifood systems account for 31% of global greenhouse gas emissions. Substantial emissions reduction in agrifood systems is critical to achieving the temperature goal set by the Paris Agreement. A key challenge in reducing GHG emissions in the agrifood value chain is the imbalanced allocation of benefits and costs associated with emissions reduction among agrifood value chain participants. However, only a few studies have examined agrifood emissions reduction from a value chain perspective, especially using dynamic methods to investigate participants' long-term emissions reduction strategies. This paper helps fill this gap in the existing literature by examining the impact of collaborations among agrifood value chain participants on correcting those misallocations and reducing emissions in agrifood systems. We develop a dynamic differential game model to examine participants' long-term emissions reduction strategies in a three-stage agrifood value chain. We use the Hamilton-Jacobi-Bellman equation to derive the Nash equilibrium emissions reduction strategies under non-cooperative, cost-sharing, and cooperative mechanisms. We then conduct numerical analysis and sensitivity analysis to validate our model. Our results show that collaboration among value chain participants leads to higher emissions reduction efforts and profits for the entire value chain. Specifically, based on our numerical results, the cooperative mechanism results in the greatest emissions reduction effort by the three participants, which leads to a total that is nearly three times higher than that of the non-cooperative mechanism and close to two times higher than the cost-sharing mechanism. The cooperative mechanism also recorded the highest profits for the entire value chain, surpassing the non-cooperative and cost-sharing mechanisms by around 37% and 16%, respectively. Our results provide valuable insights for policymakers and agrifood industry stakeholders to develop strategies and policies encouraging emissions reduction collaborations in the agrifood value chain and reduce emissions in the agrifood systems.

Sustainability in Pakistan's textile industry: analyzing barriers and strategies for green supply chain management implementation

The industries view green supply chain management (GSCM) as a viable means of achieving sustainable operations by reducing environmental impact and enhancing operational performance. Although conventional supply chains still dominate many industries, integrating eco-friendly practices through green supply chain management (GSCM) is crucial. Nonetheless, there are several barriers that hinder the successful adoption of GSCM practices. Therefore, this study proposes fuzzy-based multi-criteria decision-making approaches comprised of the Analytical Hierarchy Process (FAHP) and the Technique for Order of Preference by Similarity to Ideal Solution (FTOPSIS). The study evaluates and overcomes barriers to the adoption of GSCM practices in the textile manufacturing sector of Pakistan. After the comprehensive literature review, this study identifies 6 barriers, 24 sub-barriers, and 10 strategies. The FAHP method employs to analyze the barriers and sub-barriers. Then, the FTOPSIS method ranks the strategies to overcome various identified barriers. Based on the FAHP results, the most significant barriers to the adoption of GSCM practices are technological (MB4), financial (MB1), and information and knowledge (MB5). Further, the FTOPSIS indicates that increasing the research and development capacity (GS4) is the most vital strategy for implementing GSCM. The study's findings have important implications for policymakers, organizations, and other stakeholders interested in promoting sustainable development and implementing GSCM practices in Pakistan.

Influence of supply chain risk management and its mediating role on supply chain performance: perspectives from an agri-fresh produce

As agropreneurs of fresh fruits and vegetables are important contributors to the economy, supply chain risk management is vital for their survival and growth. Therefore, this study examined the mediating effect of supply chain risk management in reducing the impact of supply chain risks and increasing supply chain performance among small scale agropreneurs in Malaysia. It also evaluated the moderating role that knowledge management plays between supply chain risks and supply chain risk management. SmartPLS 3.0 (PLS-SEM), which uses partial least squares structural equation modelling, was utilised to test the framework. Data from 430 fresh fruit and vegetable agropreneurs in the five most productive Malaysian states were collected using a questionnaire. The results confirmed (1) a negative correlation between supply chain risks and supply chain performance (2) that supply chain risk management mediates the relationship between supply chain risks and supply chain performance, and (3) that knowledge management moderates the relationship between supply chain risks and supply chain performance. Therefore, these findings could help government institutes and agropreneurs associations better appreciate the value of supply chain risk management due to its positive effect on the overall performance of agropreneurships.

Technological Revolution and Circular Economy Practices: A Mechanism of Green Economy

Rising environmental concerns, Industry 4.0 technologies, and circular economy (CE) practices are the prevailing business considerations of the current time, and they are transforming business models. Keeping in view the importance of these considerations, this work looks into the role of Industry 4.0 technologies in adoption of CE practices and the impact of CE practices on firms’ performance. The current study collected data from 213 automotive firms located in Eastern European countries including Poland, Romania, and Ukraine. Using Covariance-Based Structural Equation Modelling (CB-SEM), the current study provides some important findings. Firstly, Industry 4.0 technologies significantly enhance circular economy practices. Secondly, circular economy practices are found to be positively related with environmental and operational performance. Lastly, higher economic and operational performance boost organizational performance. Hence, the current study provides deeper understanding regarding performance implications of Industry 4.0 technologies and offers insights about ways of promoting sustainable performance in the current age of digitization.

Green Supply Chain Management With Sustainable Economic Growth by CS-ARDL Technique: Perspective to Blockchain Technology

Logistics plays a major part in any country's or region's economic success. Logistics performance depends upon the trade between other countries and urbanization. Urbanization has major role in logistics performance. However, being a significant energy user, logistics has negative consequences. As the logistics performance increases, carbon emissions increase as well because of more transportation and urbanization. Logistics performance has positive effects related to trade openness which reduces carbon emissions. As a result, it is necessary to understand function of logistics from both economic and environmental standpoint. Logistics performance is affected by urbanization of any region. The dataset for this research is made up of 10 Asian nations with 550 observations from 2010 to 2018 and is based on the theoretical underpinnings of impact of population affluence and technology (IPAT) and stochastic impacts by regression on population affluence and technology (STIRPAT). After applying various tests like cointegration analysis, unit root test, cross-sectional dependence now long & short-term relation of variables is studied by Cross-sectionally augmented autoregressive distributed lag (CS-ARDL). As indicated by the discoveries, the logistic performance index (LPI) is basically effective on economic growth and carbon emissions, particularly when related to IPAT and STIRPAT. The findings are reviewed, and policy implications are offered, which say that current logistical infrastructure should be transformed to more environmentally friendly operations. Finally, the limits are acknowledged, as well as future research possibilities that should be pursued.

Influence Mechanism on Supplier Emission Reduction Based on a Two-Level Supply Chain

The purpose of this paper is to investigate environmental performance of a supply chain which consists of an upstream supplier and a downstream firm. A mathematical model considering both downstream firm's monitoring and governmental intervention is developed. Afterwards, a numerical example is presented to show the equilibriums of these models and the optimal choices of firms and government. The results show that when customers' environmental awareness increases, both total environmental impact and social welfare decrease. The downstream firm's monitoring will certainly reduce the total environmental impact. In most cases, it does not matter whether the downstream firm chooses to monitor the supplier or not, the total environmental impact and social welfare would not be affected when the government chooses subsidy. If a subsidy is present, firms and environment will be better than those without subsidy. Hence, the government is more likely to choose to provide subsidy and the downstream firm will not monitor the supplier's greenhouse gas (GHG) emissions reduction effort. In a few cases when environmental impact is too large, taxation may be the optimal choice for the government and the downstream firm will choose to monitor the supplier's GHG emissions reduction investment.

Mapping Interactions among Green Innovations Barriers in Manufacturing Industry Using Hybrid Methodology: Insights from a Developing Country

Recent years have witnessed continuous rise in adopting green innovations which is considered as an important organizational instrument to achieve profits by reducing environmental deterioration. However, green innovation in developing countries, especially in Pakistan, is surprisingly scant as compared to developed countries. This paper empirically investigated obstacles to green innovations in Pakistani manufacturing firms. Specifically, a novel three phase methodological framework was applied to investigate significant barriers and filtration by integrating Delphi method (DM), interpretive structural modeling (ISM), and cross-impact matrix multiplication applied to classification (MICMAC). Our results highlighted that lack of enforceable laws regarding returned goods and recycled products, lack of rules and regulations for green practices, and lack of collaboration with government and environmental institutions are most critical barriers. However, fear of failure about green innovation is least important barriers to green innovations adoption. This study offers interesting clues to promote green innovation in manufacturing industry.

Research on Supplier Selection of Prefabricated Building Elements from the Perspective of Sustainable Development

Prefabricated building is an efficient building mode. Compared with the traditional building mode, the prefabricated building has advantages of less pollution, high construction efficiency, being more labor-saving, and economy, which is in line with China’s sustainable development strategy. This paper proposes a supplier selection evaluation model based on the mechanism equation model (SEM) and intuitionistic fuzzy analytic hierarchy process (IFAHP). Based on a detailed literature review, 300 structured questionnaires were distributed to the relevant enterprises, and an evaluation index system of prefabricated building element suppliers was built. With the fitting and modification process using a structural equation model, and assist of a path factor, an evaluation index system for evaluating the prefabricated building element suppliers was finally obtained. Finally, the intuitionistic fuzzy analytic hierarchy process was used to establish a selection model of prefabricated element suppliers, and the prefabricated element suppliers of Shuangyashan prefabricated construction projects were analyzed as a case study. The results show that the following factors have the most significant impact on supplier selection (from high to low): quality, economy, long-term cooperation, after-sales, and transportation. This study had a comprehensive consideration of the influencing factors existing in the whole selection process and should provide a valuable reference for the sustainable development of prefabricated construction engineering.

Gresilient supplier selection through Fuzzy Ordinal Priority Approach: decision-making in post-COVID era

Because of the COVID-19 outbreak, the supply of both essential and non-essential goods and services has been unprecedentedly disrupted. In the absence of any playbook, the need for innovative technologies to aid recovery from the Supply Chain (SC) disruptions quickly and effectively becomes persistent. The study aims to develop an innovative decision-making technology to handle the supplier selection problems arising from the frequent impreciseness and incompleteness in the nowadays' SC reports within the framework of the gresilient supply chain management. Through the integration of green and resilience aspects of the SCs, the supply chain 'gresilience' has been conceptualized. In light of this construct and based on the data collected from a manufacturing firm, the study deploys a two-fold decomposition of the core algorithm of the Ordinal Priority Approach (OPA), one for attributes and other for alternatives. It extends the OPA to the Fuzzy OPA (OPA-F) for solving the supplier selection problems. The study illustrates how green and resilience aspects of the SC can be integrated to better understand the gresilient suppliers in the wake of the SC disruptions. A novel construct of SC Gresilience is also furnished along with a novel definition of SC Gresilience. It also provides an innovative SC decision-making technology to help procurement managers to evaluate their suppliers. The resultant framework can help them better prepare for the COVID-19 like disruptions in the future.