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The paper industry is undergoing a critical phase of digital transformation, driven by the need for increased efficiency and sustainability. This study offers an initial insight into the industry's digitalisation status based on a survey conducted at the ZELLCHEMING Expo 2024 by ZELLCHEMING's technical committee DATA. The survey assessed the digital maturity of various companies and the industry, uncovering data management practices and key challenges. The findings reveal a discrepancy between the companies' self-assessed digital maturity and their views on the industry's overall digitalisation, with the companies generally rating the industry as being on a rather low maturity whilst rating their own maturity more favourably. Challenges, such as legacy systems, data quality issues, and inconsistent digitalisation efforts, persist, although there is a notable awareness of the importance of data. The study highlights the potential of frameworks, like the Industrie 4.0 Maturity Index and the VDI Guideline for Industrie 4.0, in guiding digital transformation. To enhance digital maturity, companies must advance through the stages of digital integration, address key obstacles, and align digital initiatives with strategic goals. This paper offers practical recommendations for advancing digital capabilities and achieving long-term sustainability and competitiveness not only in the paper industry but also generally for manufacturing enterprises. Ultimately, this research emphasises the need for a cohesive approach to digitalisation, which involves all stakeholders—from management to operational staff—in fostering resilience and adaptability in an ever-evolving industrial landscape. [ABSTRACT FROM AUTHOR]

The relevance of this research lies in the increasing global focus on sustainable development, the growth of the green economy, and the pursuit of national and international goals in these areas. This study examines the role of environmental collaboration models and green business integration in implementing environmental and technological projects to achieve sustainable development goals aimed at the enhancement of resource efficiency and environmental performance within companies. Open environmental collaboration business models generate additional value and competitive advantages by leveraging the synergistic integration of resources and knowledge among all participants. The study's methodological foundation includes systems analysis and comparative analysis. The findings identify the key characteristics of open environmental collaboration business models and propose recommendations for establishing a system to assess green integration projects. The proposed approach was validated through application at one of the largest pulp and paper manufacturers. As a result of the implementation of the environmental collaboration business model, the profit of Syktyvkar Forest Industry Complex increased four times, revenue almost doubled, product output increased by 89%, and asset value increased by 62%. The study contributes to a deeper understanding of how industrial integration impacts regional green development. It also provides empirical insights and policy recommendations for businesses and governments to promote environmental collaboration and advance green development through knowledge and technology transfer. [ABSTRACT FROM AUTHOR]

Recent research suggests that built environments can influence user behavior. Concurrently, Design for Sustainable Behaviour (DfSB) has emerged in design and manufacturing disciplines. This paper explores the application of DfSB in built environment design by devising and implementing a toolkit to prompt children to behave more sustainably in schools' washrooms. The resource consumption before and after the toolkit installation in two primary schools was measured and compared. Afterward, interviews and a workshop were carried out to gather the perceptions of children and staff. Results show a preference for stickers that are playful and portray natural motifs. Also, the toolkit design concepts were not perceived by most users, suggesting it can be simplified and serve mainly as a reminder to perform a particular behavior. Yet, the interview participants suggested that the toolkit could indirectly contribute to more sustainable behaviors by creating a pleasant environment and prompting children to not play/waste resources. Additionally, the research reviews and classifies existing DfSB strategies into three categories, providing valuable insights for designers on tailoring interventions based on user control, attitudes, and targeted behaviors. [ABSTRACT FROM AUTHOR]

This paper adopts a scientometric approach to establish a research framework to guide the study of entrepreneurship in the circular economy (ECE) for the coming years. Two hundred papers published on ECE in journals indexed in WOS and Scopus show that this area of research is still in its embryonic stage and that it is geared towards two key axes: environmental and management aspects. In addition to framing the study of ECE based on the concept of conscious entrepreneurship, this paper shows that it is critical to focus efforts on understanding the challenges and obstacles facing the transition from a linear to a circular economy. Furthermore, it is essential to determine the enabling factors from both contextual and organizational perspectives, with a particular focus on examining the negative externalities of ECE. The role of researchers in this field is key to not only better understanding the phenomenon but also to prescribing and disseminating this philosophy on which to base economic growth in the remainder of the century. [ABSTRACT FROM AUTHOR]

In the era of artificial intelligence (AI), economic efficiency has an obvious role to play, but "non-economic benefits" have gradually become the focus of corporate attention; thus, environmental, social, and governance (ESG) has become a mainstream investment strategy. This paper empirically examines the impact of corporate application of AI technology on corporate ESG performance using a sample of 4858 listed companies in China from 2007 to 2022. The study finds that: (1) corporate application of AI technology can significantly enhance corporate ESG performance, and this conclusion still holds after a series of endogeneity treatments and robustness tests; (2) mechanism analysis shows that the degree of corporate digitalization has a positive moderating effect in the process of AI technology affecting corporate ESG performance. The channel analysis shows that the application of AI technology can enhance environmental (E) performance by strengthening corporate green technology innovation, social (S) performance by improving corporate philanthropic responsibility, and overall ESG performance with the above two sub-items as the main aspects. However, AI technology also weakens the effectiveness of corporate internal control, which leads to a decline in corporate governance (G) performance; (3) Heterogeneity analysis shows that AI technology promotes ESG more significantly in more competitive industries and tech-nology-intensive firms, and more significantly in the eastern and central regions than in the western and northeastern regions, and that large- and medium-sized firms are similarly superior to small-sized firms, while medium-sized firms have more room for upward mobility than large-sized firms, which embody a higher promotion effect than large enterprises. This paper provides theoretical evidence that enterprises apply AI technology to improve ESG performance and empirical support around investing in ESG practices and promoting ESG development. [ABSTRACT FROM AUTHOR]

Among transportation researchers, pedestrian issues are highly significant, and various solutions have been proposed to address these challenges. These approaches include Multi-Criteria Decision Analysis (MCDA) and machine learning (ML) techniques, often categorized into two primary types. While previous studies have addressed diverse methods and transportation issues, this research integrates pedestrian modeling with MCDA and ML approaches. This paper examines how MCDA and ML can be combined to enhance decision-making in pedestrian dynamics. Drawing on a review of 1574 papers published from 1999 to 2023, this study identifies prevalent themes and methodologies in MCDA, ML, and pedestrian modeling. The MCDA methods are categorized into weighting and ranking techniques, with an emphasis on their application to complex transportation challenges involving both qualitative and quantitative criteria. The findings suggest that hybrid MCDA algorithms can effectively evaluate ML performance, addressing the limitations of traditional methods. By synthesizing the insights from the existing literature, this review outlines key methodologies and provides a roadmap for future research in integrating MCDA and ML in pedestrian dynamics. This research aims to deepen the understanding of how informed decision-making can enhance urban environments and improve pedestrian safety. [ABSTRACT FROM AUTHOR]

Against the backdrop of funds flowing from the real economy to the virtual economy, the trend of corporate financialization is becoming more and more obvious. Establishing how to guide enterprises to return to their main business is the key to guaranteeing the sustainable development of the economy. Considering the promulgation of new accounting standards in 2007 and the availability and completeness of listed company data, this paper takes A-share listed companies from Shanghai and Shenzhen stock markets in China from 2008 to 2022 as research samples. This paper takes China's smart-city pilot policy as a quasi-natural experiment and constructs a time-varying difference-in-differences (DID) model to empirically analyze the impact of smart city construction on corporate financialization. According to the study, smart city construction can significantly inhibit corporate financialization. Specifically, this paper measures corporate financialization by the proportion of financial assets to total assets, and empirical results show that when the city where the enterprise is located is selected as a smart city pilot, the degree of corporate financialization decreases by 0.7%. After a series of robustness tests, this conclusion still holds. Mechanism analysis indicates that smart city construction can inhibit corporate financialization by alleviating financing constraints and improving profitability. Heterogeneity analysis shows that smart city construction has a stronger inhibitory effect on corporate financialization in the central and western regions, state-owned enterprises, management shareholdings, industries with a high degree of competition, and enterprises in the growth and maturity stages. On the one hand, the research results of this paper can help us to understand the influencing factors of corporate financialization, avoid the excessive financialization of enterprises, and promote the sustainable development of enterprises. On the other hand, it also tests the policy effect of smart cities and provides help for the subsequent policy formulation of smart city construction. [ABSTRACT FROM AUTHOR]

In recent years, the applications of digital technologies in sustainable construction have gained increasing interest. However, no comprehensive literature review has been conducted. Thus, this paper analyzes 990 relevant articles in this regard published from 2014 to 2023 by using CiteSpace (version 6.3.R1) and HistCite (version Pro 2.1) and identifies the most influential journals, institutions, and regions. The knowledge base was detected through a cluster analysis, which concentrates more on seven core themes: barriers, energy efficiency and building energy performance, life cycle assessment, computer vision, renovation, building sustainability assessment, and management. A citation analysis revealed that the applications of digital technologies were based in four dimensions of sustainable construction: environmental, social, and economic performance and green building assessment are the current hotspots. Finally, the potential future research trends in this field were proposed: (1) strengthening research on the application of more digital technologies; (2) expanding the use of digital technologies in the Operation and Maintenance (O & M) and demolition phases; (3) deepening the research on multi-objective optimization; and (4) exploring how to overcome obstacles. The findings provide highly valuable information for researchers with current research ideas and future directions in this field. This paper also has the potential to deepen practitioners' comprehension of optimal digital technologies for bolstering construction sustainability. [ABSTRACT FROM AUTHOR]

This research work aimed to analyse the impact and potential of cardboard as a construction material, as well as cultural aspects and sustainable construction regulations, in the context of Lima, Peru. The study employed a mixed research methodological approach, including three case studies from Japan, the Netherlands, and the UK, online interviews, and surveys with British, Polish, and Peruvian architects. Additionally, a range of dynamic thermal simulations of an existing school building in the UK employing cardboard construction material were conducted to evaluate its impact on energy consumption. The survey revealed that there is a gap in information about the material applied to the architecture and construction environment, which is coupled with a general distrust and little credibility regarding its inclusion. However, cardboard is also seen as a complementary material in hybrid construction systems, with potential recycling enhancing environmental sustainability. The case studies showed cardboard structures can fulfil different functions with flexible designs that are adaptable to different contexts, simple, economical, accessible, recyclable, and capable of resisting natural disasters. However, post-construction consequences affect the structural integrity. Simulations carried out with EnergyPlus confirmed that cardboard has an optimal performance that can be a great complement or variation to traditional materials to reduce the carbon footprint and could meet the U-value requirements established in the construction regulations. Since it has low thermal conductivity and good acoustic insulation, it is recyclable and generates fewer CO2 emissions, and it is economical, accessible, versatile, and light in use. For example, from a technical point of view, when used as thermal insulation, this element outperforms other conventional materials due to its cellular structure, which traps air, a poor conductor of heat. This study provides a set of guidelines for sustainable building practices. Such guidelines can be adopted to produce a prototype of a sustainable building using cardboard as the main construction material to contribute to the current debates on the state of building materials. It offers valuable perspectives on the development of building materials, construction techniques, and building regulations that can guide the way forward for sustainable building practices in the future, informing policymakers and building designers about construction techniques that adhere to building codes and lessen the built environment's environmental impact. [ABSTRACT FROM AUTHOR]

The efficient management of the green power grid supply chain is of great significance in addressing global energy transformation and achieving sustainable development goals. However, traditional methods struggle to effectively cope with the complexity and dynamics of demand forecasting and the multi-objective optimization problems in material allocation. In response to this challenge, this paper proposes a machine-learning-based demand forecasting and allocation optimization method, aiming to improve the management efficiency of the supply chain and reduce environmental impacts. First, based on the whole-process data of power grid materials, a multi-model fusion strategy is adopted for demand forecasting. By combining machine learning models such as long short-term memory (LSTM), extreme gradient boosting (XGBoost), and random forest, the prediction accuracy and the generalization ability of the model are significantly improved. Moreover, a "distributed collaborative optimization algorithm" is proposed. By decomposing the power grid regions, this paper optimizes transportation routes and inventory management, and comprehensively reduces transportation, inventory, and environmental protection costs while taking into account the real-time requirements in a complex supply chain environment. Finally, an empirical analysis is carried out in combination with the optimized allocation plan, verifying the practical effectiveness of the proposed method. The results indicate that the optimized scheme significantly outperforms the traditional method in terms of total cost, transportation efficiency, and carbon emissions. Specifically, the optimized scheme achieves a 13% reduction in transportation costs, a 10% decrease in inventory costs, and a 25% cut in environmental protection expenses. Additionally, it decreases transportation-related carbon emissions by approximately 250 tons. The demand forecasting and allocation optimization method based on machine learning has obvious economic and environmental advantages in the green power grid material supply chain. By effectively integrating various algorithms, this paper enhances the accuracy and stability of material management while substantially reducing operating costs and carbon emissions. This is in line with the sustainable goals of green power grid development. The paper provides an optimized framework with practical value for managing the green supply chain in the power grid industry. [ABSTRACT FROM AUTHOR]

Climate risk, within the context of environmental sustainability, is profoundly affecting global development trends. As critical organizations, enterprises play an irreplaceable role in various stages of economic development, with liquidity being a vital capability for their survival, growth, and sustained value creation. This paper innovatively constructs a framework of climate risk, encompassing three levels: macro background, industry environment, and corporate operation. Focusing on publicly listed companies in China's eight high energy-consuming industries, this paper employs fsQCA and NCA methods to investigate the factors influencing enterprise liquidity in the context of climate risk. Finally, the study finds and concludes with three main patterns: macro-oriented, industry-adaptive, and management-optimized. These findings suggest related policy recommendations and key strategies to enhance economic resilience by adjusting climate policy uncertainty, controlling technical personnel proportion, and improving financial management. [ABSTRACT FROM AUTHOR]

This paper discusses the role of afforestation projects and other climate technologies in the green agenda for Russia and aims to justify the anchoring of jurisdictional carbon pricing in the cost approach to valuation, specifically, with reference to the cost economics for afforestation projects given their centrality to the agenda. Through that, and due to the inchoate state of carbon pricing in the study jurisdiction, this paper aims to advance price discovery for national carbon credits in both compliance and voluntary schemes. The cost approach framework, moderated by international market comparisons, indicates the fair price of carbon in Russian jurisdiction at the level of USD 20–25 per tonne of CO2-eq, which is close to the global median but is more than double the amount of carbon levies set under the Sakhalin GHG quota experiment. It is argued that unless such a fair price for carbon is set in the country, the national carbon credits market will not achieve viable growth, nor will sustainable development be advanced, and funds for it be adequately collected. This represents a relevant contribution to the literature on the development of the national carbon credit markets. [ABSTRACT FROM AUTHOR]

Under the background of global climate change and sustainable development, low-carbon transformation has become an inevitable choice for China and even global economic development. As the cornerstone of social stability and the key to people's well-being, employment is facing profound changes brought about by low-carbon development. Based on the micro perspective of enterprise behavior change, this paper takes the implementation of China's low-carbon city pilot policy as an exogenous policy shock and constructs a time-varying difference-in-differences (DID) model to test the impact of the low-carbon city pilot policy on enterprise employment, based on the data of China's A-share listed enterprises from 2008–2021. The results show that the implementation of low-carbon city pilot policies significantly expands the employment scale of enterprises and increases overall employment by about 6.77%. From the perspective of employment skill structure, it can promote the employment of high-skilled and low-skilled workers. From the perspective of employment position structure, it can promote the employment of production operations personnel, technology research and development personnel, and service and management personnel. These results are still valid after a series of robustness tests. The policy effect is due to the deepening of enterprise capital integration, green investment, technological innovation and vertical specialization. In addition, it is also affected by the differences of enterprise ownership, enterprise scale, industry pollution degree, regional environmental regulation, and market competition degree. Further research shows that low-carbon city pilot policies significantly reduce the share of labor income of employees in heavily polluting enterprises, resulting in the loss of employee welfare. From the perspective of employment, this paper provides more theoretical support and empirical evidence for low-carbon policies to drive changes in micro-enterprise behavior, so as to achieve the sustainable goals of "double carbon" and "stable employment". [ABSTRACT FROM AUTHOR]

It is essential for achieving green and sustainable economic development by using tax incentives to promote green investment. Using the data from the seventh, eighth, ninth, and tenth Chinese Private Enterprise Surveys (CPESs) conducted by the Private Enterprise Research Group and using China's corporate income tax reform in 2008 as a quasi-natural experiment, this paper empirically analyses the effect of tax incentives on corporate green investment based on the difference-in-difference models. The research results show that tax incentives can significantly increase corporate green investment. The mechanism test shows that easing financing constraints is an important channel for tax incentives to promote corporate green investment. In addition, the role of tax incentives in promoting green investment varies depending on the type and location of the enterprise. Relatively speaking, tax incentives have a stronger effect in promoting green investment for corporates with low sales revenue, located in the eastern region, heavy pollution, and high innovation capability. By doing placebo tests and changing measurement methods of indicators for robustness tests, the conclusions of this paper are still valid. Therefore, the government should increase tax incentives to better promote corporate green investment. [ABSTRACT FROM AUTHOR]

Understanding the global trade network in the printing industry is crucial for promoting sustainable development and cultural exchange and knowledge dissemination. However, the extant literature does not reveal the contours of the global cultural printed material trade network. This paper uses a social network analysis and QAP analysis to explore the global printing industry trade network pattern. The aim of this paper is to discern the core and emerging nodes and explore the evolutional characteristics on the network spatial linkage and country role. The results show the following: ① The printing industry's global trade network is growing increasingly intricate, with trade links between nations (regions) becoming closer, the network's connectivity steadily improving, and the hierarchical structure becoming more apparent. ② Germany, France, and Belgium are important intermediary bridges. The "circle of friends" in the trade of cultural products has a growing effect, and China can more easily establish close ties with Southeast Asia, Northern Europe, and Central and Eastern Europe. ③ The industrial chain and geographical proximity are the primary factors in the formation of the trade network. Economic proximity and political proximity significantly and positively contribute to the formation of the trade network, while institutional stability gradually plays a weaker role. As for cultural proximity, a common language and colonial relationship will positively contribute to the formation of a network, while immigrants have no obvious impact. Digital technology is becoming an "emerging force". Additionally, this paper extends sustainable policies and recommendations for the global cultural trade. [ABSTRACT FROM AUTHOR]

In this paper, we provide a review of academic research on inventory pooling published between 2010 and 2024, with a particular emphasis on studies that focus on real-world applications. The review analyzes the research conducted over the past 14 years, evaluates the outcomes of these applied studies, and identifies gaps in the literature. The contribution of this work is twofold: firstly, it provides insights into the extent to which theoretical advancements in inventory pooling have been implemented in the practice; secondly, it provides practitioners with an overview of recent real-world applications across various industrial contexts. The findings highlight the impact of inventory pooling on cost savings, service level improvements, inventory optimization in diverse sectors, and sustainability. Additionally, this paper examines the contributions of inventory pooling to economic, environmental, and social sustainability, offering a comprehensive analysis of its role in fostering sustainable practices across supply chains. Finally, the paper discusses practical challenges encountered in implementation and suggests directions for future research in this domain. [ABSTRACT FROM AUTHOR]

Under the "dual carbon" goals, China's green development faces the challenge of innovating amid a "lightweight and heavy-duty" dilemma, necessitating the simultaneous improvement in both the quantity and quality of green technological innovation. Based on panel data from 285 cities in mainland China between 2006 and 2020, this paper investigates the policy effect of carbon emission trading pilot programs on urban green technological innovation from the dual perspectives of innovation quantity and quality, using a difference-in-differences (DID) model. This study found that implementing carbon trading policies significantly increased both the quantity and quality of green technological innovation in pilot cities, and these results remain robust after a series of tests. The mechanism analysis indicated that the policy's promoting effect primarily operates through three channels: decarbonizing industrial structure, increasing R&D investment, and enhancing government attention to environmental issues, which together reshape the urban innovation ecosystem. Further analysis revealed that the policy effect is more pronounced in western regions, cities with low enterprise density, and areas designated as "two control zones". This paper enriches the theoretical understanding of market-based environmental regulation and technological innovation and provides new micro-level evidence for deepening carbon market policies. [ABSTRACT FROM AUTHOR]

Energy conservation and emission reduction are essential for China's economy to achieve sustainable development. This paper integrates industrial robots and pollution emissions into a heterogeneous firm model to theoretically analyze the impact and mechanism of industrial robots on pollution emissions of listed manufacturing firms. Using data from a sample of listed manufacturing firms over the period 2012–2022, an econometric model is constructed and empirically tested. The results of the study show that industrial robots have had a significant impact on the emission intensity of the manufacturing industry through technological progress and innovation effects, while firms' pollution levels, regional environmental regulatory intensity, ownership type, and factor intensity type have heterogeneous effects on abatement. In view of this, the application of industrial robots should be promoted according to local conditions, the development of differentiated environmental regulatory policies, and targeted measures to give full play to the emission reduction effect of industrial robots, to synergistically promote a high level of ecological environmental protection and sustainable economic and social development by accelerating the greening and intelligent transformation of China's manufacturing enterprises. [ABSTRACT FROM AUTHOR]

As the main driving force of the new technological revolution, intelligent development is the key to promoting high-quality economic development. This paper empirically examines the nonlinear influence of intelligent development on green economy efficiency and its action paths using provincial panel data of China from 2009 to 2021. The result provides significant evidence of a U-shaped relationship between intelligent development and green economy efficiency, indicating that intelligent development initially leads to green economy efficiency decreases before ultimately increasing. Additional analysis confirms that environmental regulation, green finance, and industrial agglomeration positively moderate the impact of intelligent development on green economy efficiency. Furthermore, heterogeneous tests reveal that in the eastern region and after the release of "Made in China 2025" in 2015, the nonlinear effect of intelligent development on green economy efficiency is more pronounced. The findings of this paper provide a beneficial reference for how to leverage intelligent technology to release new kinetic energy for green economic growth under the new development concept. [ABSTRACT FROM AUTHOR]

In order to address the impact of the uncertainty and intermittency of a photovoltaic power generation system on the smooth operation of the power system, a microgrid scheduling model incorporating photovoltaic power generation forecast is proposed in this paper. Firstly, the factors affecting the accuracy of photovoltaic power generation prediction are analyzed by classifying the photovoltaic power generation data using cluster analysis, analyzing its important features using Pearson correlation coefficients, and downscaling the high-dimensional data using PCA. And based on the theories of the sparrow search algorithm, convolutional neural network, and bidirectional long- and short-term memory network, a combined SSA-CNN-BiLSTM prediction model is established, and the attention mechanism is used to improve the prediction accuracy. Secondly, a multi-temporal dispatch optimization model of the microgrid power system, which aims at the economic optimization of the system operation cost and the minimization of the environmental cost, is constructed based on the prediction results. Further, differential evolution is introduced into the QPSO algorithm and the model is solved using this improved quantum particle swarm optimization algorithm. Finally, the feasibility of the photovoltaic power generation forecasting model and the microgrid power system dispatch optimization model, as well as the validity of the solution algorithms, are verified through real case simulation experiments. The results show that the model in this paper has high prediction accuracy. In terms of scheduling strategy, the generation method with the lowest cost is selected to obtain an effective way to interact with the main grid and realize the stable and economically optimized scheduling of the microgrid system. [ABSTRACT FROM AUTHOR]

This paper explores the intersection between transformative resilience and just transitions, two increasingly significant frameworks in the context of environmental and socio-economic adaptation. Applying a systematic literature review, this paper examines how these concepts are defined and identifies both overlapping and non-overlapping dimensions within the existing literature. The analysis then shifts to consider the role of welfare state policies in reinforcing these connections. Specifically, this study assesses how physical social infrastructure, welfare state provisions, and eco-social policies are able to bridge the concepts of transformative resilience and just transitions. The findings indicate a notable gap in the literature connecting transformative resilience and just transition, despite the potential for aligning these concepts. This paper thus contributes to the theoretical foundation for discussing transformative resilience and just transitions together, underscoring the need for inclusive policies in sustainable development frameworks. [ABSTRACT FROM AUTHOR]

This paper examines the influence of green innovation on the sustainable development performance of Chinese companies listed on the Shanghai and Shenzhen A-shares market between 2010 and 2021. Utilizing manually collected green innovation patent data from the National Intellectual Property Administration, this paper finds that green innovation can enhance corporate sustainable development performance by improving the corporation's reputation and increasing resource utilization efficiency within metropolitan areas. Heterogeneity analyses show that the impact of green innovation on sustainable development performance is more pronounced when the urban commercial credit environment is better, following the enactment of the new Environmental Protection Law, and during the implementation of digital transformation processes in cities. This paper enriches the research related to the economic consequences of green innovation and the influencing factors of sustainable development performance, offering theoretical support for policy refinement by regulatory authorities and the optimization of investment decisions by investors. [ABSTRACT FROM AUTHOR]

In recent years, with rapid economic development, the importance of environmental governance has gradually been overlooked. The increasing pollution caused by rural sewage discharge has posed a significant threat to the local ecological environment. In this context, this paper treats the local governments, village enterprises, and farmers as the game subjects, integrating them with prisoner's dilemma theory to construct a tripartite game model. By analyzing the equilibrium points and stability of the model, as well as the effects of the parameters in the dynamic equations, this paper reveals the evolution of strategic choices made by different participants. The results indicate that the optimal strategy for local governments is strict regulation, and village enterprises tend to adopt purification measures, while farmers weigh the costs and benefits and exhibit a negative attitude toward participating in governance. Finally, from a practical perspective, this paper offers suggestions for improving rural ecological environmental protection by engaging local governments, village enterprises, and farmers, aiming to promote the sustainable development of the ecological environment. [ABSTRACT FROM AUTHOR]

Climate change effects have a significant global negative impact, prompting global leaders to promote clean energy use to reduce carbon emissions. Electric vehicles powered by lithium-ion batteries are crucial to achieving this goal. Lithium is an essential material for the efficient operation of electric batteries, so in recent years, its demand has increased, and it is considered a strategic mineral. This paper aims to describe and analyze the scientific development of lithium-based clean energy technologies and reveal future areas of scientific production priority. This research is conducted through a bibliometric analysis in the Scopus database from 1929 to April 2024. Using the software Bibliometrix 4.1 and Biblioshiny the exported literature data are analyzed. The number of papers on lithium topics has significantly increased since 2018, with China leading in publications and collaborating with many countries. The trending topics are geological prospection, lithium ore characterization, chemical engineering, and lithium energy technologies. Lithium research is a growing field, but its development is uneven. Only a few countries lead in scientific production and lithium energy technologies, and sustainability lithium topics related to Life-Cycle Analysis (LCA) require further attention. Lithium research development is influenced by global economic trends. [ABSTRACT FROM AUTHOR]

In the era of VUCA, cultivating and enhancing the resilience of high-end manufacturing enterprises is critical. Based on existing research, this paper defines enterprise resilience at the beginning and constructs an enterprise resilience evaluation index system that includes three segmented capabilities: recognition and resistance, adaptation and adjustment, and recovery and rebound. Finally, the relationship between human capital investment, technological innovation, and high-end enterprise resilience is empirically studied. The research results show that human capital investment positively affects the resilience of high-end manufacturing enterprises, with breakthrough innovation and progressive innovation playing a mediating role. Digital transformation positively moderates the impact of human capital investment on the resilience of high-end manufacturing enterprises. Further, there is a higher threshold between human capital investment and technological innovation in improving the resilience of high-end manufacturing enterprises. Human capital investment has a significantly positive effect on high-end manufacturing enterprises' ability to resist risks and adapt to adjustments but has no significant impact on recovery and rebound ability. Breakthrough and progressive innovation partially mediate the impact of human capital investment on the ability to resist risks and adapt to adjustments, while breakthrough innovation has no significant impact on the recovery of the rebound ability; however, progressive innovation completely mediates the relationship between human capital investment and the recovery of rebound ability. Compared with Chinese non-state-owned enterprises, state-owned enterprises' efforts to increase investment in human capital only positively impact their ability to resist risks. Compared with large-scale enterprises, the increase in human capital investment in small-scale enterprises only has a significant positive impact on the ability to resist risks. Based on the above, this paper suggests that high-end manufacturing enterprises should enhance their strategic focus and constantly strengthen their investment in human capital and technological innovation; at the same time, they should further optimize the structure of human capital investment and introduce and cultivate cutting-edge talents. [ABSTRACT FROM AUTHOR]

We conduct a literature review on integrated land use modelling to guide policy on sustainable food provisioning. Modelling approaches are discussed in the spatial, temporal, and human dimensions, as well as environmental and socio-economic considerations. Many studies have focused on model development over their application to specific policy objectives, often relying on top-down approaches. While ecosystem services are a frequent focus, indicators for their assessment are inconsistently quantified. Socio-economic considerations are coarse in scale compared to biophysical ones, limiting their use in nuanced policy development. Recommendations are made such as standardising data collection and sharing to streamline modelling processes and collaboration. Comprehensive ecosystem services frameworks would benefit from a more uniform classification of values. More bottom-up modelling, connected with top-down models, could account for the heterogeneity between smaller units of analysis such as the landscape, farms, or people. This could reveal further insights into the local contexts and decision-making responses essential for effective land use policy. These advancements would help to design policies that address the complexities of sustainable food provisioning. By connecting local and global perspectives, future models can support more resilient and adaptive food systems, ensuring sustainability in the face of environmental and socio-economic challenges. [ABSTRACT FROM AUTHOR]

Achieving the transformation from "growth at the expense of the environment" to "growth through environmental protection" is an essential path for developing countries to promote sustainable economic and social development. This paper utilizes the staggered difference-in-differences model to empirically test the impact of the "Green Factory" policy under China's green manufacturing system on corporate sustainable development performance in a large sample of Chinese A-share listed companies from 2010 to 2023. The findings show that the level of corporate sustainable development performance significantly improves after being certified as a "Green Factory". After a series of robustness tests such as the parallel trend test, placebo test, and heterogeneous treatment effects test, the promoting effect remains significant. This association is stronger among non-state-owned enterprises, enterprises in high-polluting industries, as well as enterprises with higher environmental information transparency. The mechanism tests reveal that participating in the "Green Factory" project enhance corporate sustainable development performance by attracting more green investors and promoting corporate green innovation. Overall, this paper provides micro-level empirical evidence for the driving factors of corporate sustainable development and offers policy evaluation and practical insights for the implementation of green manufacturing system and voluntary environmental regulation policies. [ABSTRACT FROM AUTHOR]

Research on Urban Carbon Risk (RUCR) is crucial for understanding the impact mechanisms of carbon emissions on urban environments and health, particularly in rapidly urbanizing areas. This paper conducted a bibliometric analysis of 2012 studies on RUCR indexed in the Web of Science (WOS) database from 1991 to June 2023. It reached the following conclusions: (1) The annual publication volume of RUCR has steadily increased since 2005, mainly focusing on environmental science and public health. A co-citation analysis of the literature indicates that RUCR research content is centered on carbon sink assessment, risk factor analysis, and response strategies. (2) RUCR has undergone four developmental stages: singular exploration, evaluation and construction, innovative breakthroughs, and technological synergy. (3) The key research issues of RUCR include carbon reduction and sink enhancement, integrating qualitative and quantitative planning methods, and multidisciplinary collaboration. (4) Current research hotspots in RUCR focus on urban pollution and health risks, ecological environment and land use change, carbon emissions and energy utilization, and pollution monitoring technologies. Future research trends are anticipated to center on source apportionment and monitoring of carbon emissions, the relationship between air pollution and health risks, and the governance and mitigation of carbon emissions. (5) Based on the analysis of critical issues and trends, it is recommended that future research prioritize spatial identification and scenario simulation of urban carbon risk. The conclusions of this paper facilitate researchers' quick understanding of the current status and development trends of RUCR and propose future research directions from urban planning. [ABSTRACT FROM AUTHOR]

The paper will focus on the topic of adapting digital humanities methods from architectural history to technical history, considering mapping and image analysis for increasing disaster resilience in Art Nouveau and Modernist buildings in different geographical areas—including lessons from Europe to the USA. The project proposes the transformation of the collection of photographs of early 20th-century architecture gathered by the applicant over about 30 years of travel into a database by answering the research question on how threats from the hazards of earthquakes, floods, and fires can be answered by taking into account the local culture in the European countries covered, for buildings from a period when the architecture styles were already global at that time. For this purpose, digital humanities methods of image annotation (including architectural volumetric analysis) and mapping are employed. From the knowledge gathered and the resulting database, a prototyping ontology and taxonomy is derived. This outcome can be further developed into a set of evaluation criteria, considering the decisions that can be taken to prioritize the retrofit interventions depending on the geographic positions of the buildings. [ABSTRACT FROM AUTHOR]

Energy is one of the essential human needs that plays a crucial role in achieving sustainable development. Indonesia is among the countries that are highly focused on developing renewable energy to reduce greenhouse gas emissions and achieve net-zero emissions. In addition, the government has launched various policies and programs to promote the use of renewable energy, such as increased investment in biomass, geothermal, and solar power generation. Wind energy stands out as a sufficient, widely available, and an environmentally friendly alternative in renewable energy. In 2021, the Indonesian Energy Outlook highlights that Indonesia has an energy potential of 154.9 gigawatts (GWs). It is associated with minimal emissions of greenhouse gases during its operation and does not demand vast tracts of land. However, the actual installed capacity of wind power plants is at a modest 157.41 megawatts (MWs). Meanwhile, the targeted capacity is 255 MWs for 2025. One significant factor contributing to this lower-than-expected capacity is a lack of in-depth research into the potential of wind energy. Consequently, the primary aim of this paper is to conduct a thorough examination of the wind energy potential in Indonesia. This includes an analysis of the current state of both existing and upcoming power plants, as well as a review of recent studies conducted by Indonesian researchers on wind turbines. Furthermore, this paper explores the government program to encourage the sustainable development of wind power plants. It also explains various aspects including the untapped wind energy potential, the interference in developing wind power plants, and the strategy to harness the full potential of abundant renewable resources in Indonesia. Through an in-depth investigation of the potential of wind energy, this review aims to provide a more comprehensive understanding of the current conditions and prospects of wind power plants in Indonesia as well as contribute to a more accurate mapping of wind energy potential and more targeted development, specifically in remote areas, outer islands, and borders. The results obtained are expected to support Indonesia's energy transition toward more environmentally friendly and sustainable renewable energy sources, thereby reducing dependence on fossil fuels. [ABSTRACT FROM AUTHOR]

Investments are the development core of every economic operator and the driving force for national economic development. While finding the optimal investment point is extremely difficult, every operator may seek to attain a level of fixed assets which allows them to maintain an increase in production and keep their income flowing. The difficulties in finding this optimum may lead to overinvestment. Hence, this paper estimates the parameters of the production function at various investment levels. Its purpose is to identify the relationship between the investment levels, the use of productive inputs, and growth or decline in production (output) levels. This study used microdata for 3273 Polish farms, as retrieved from the FADN (Farm Accountancy Data Network). The differences found at various farm investment levels allow for highlighting some problematic areas, e.g., in the context of excessive capital use relative to yearly increments in production values. The proposed method of analyzing overinvestment based on the production function can be extended to other countries. According to this paper, farms that invested too little or too much in relation to their production potential showed the worst economic performances, including the greatest declines in production. [ABSTRACT FROM AUTHOR]

In many developing countries, economic growth is often prioritized, sidelining critical issues such as social inequality, pollution, climate change, ocean degradation, and pressing needs for health, education, food, and water management. Traditional linear models in organizations, based on product innovation and hierarchical governance, have been successful in certain contexts but are no longer viable in the face of finite natural resources and environmental degradation. This paper proposes a Systems Approach to Circular Economy as a practical framework for achieving "circular business-driven sustainability", a concept proposed by major global organizations such as COP-25. This approach redefines sustainability, aiming to generate "sustainable wealth increasing returns" that benefit all key stakeholders, including the environment, society, and the economy. The primary objective of this paper is to introduce a new paradigm that facilitates the transition to more conscious, long-term growth. The proposed circular iterative thinking framework shifts from linear, reductionist thinking to a more holistic, systemic vision, underpinned by disruptive sustainable innovation. This novel paradigm creates positive impacts across the economy, environment, and global geopolitics. The paper demonstrates the application of this framework in two case studies, providing concrete evidence of its utility in real-world scenarios, including Heineken's sustainable practices at its Meoqui brewery, which recovered methane for energy use, reduced water consumption, and contributed to local irrigation. The results underscore the effectiveness of the Systems Approach to Circular Economy in achieving economic decoupling and enhancing sustainability. [ABSTRACT FROM AUTHOR]

Occupancy is one of the primary contributors to the energy performance gap, defined as the difference between actual and predicted energy usage, in buildings. This paper limits its scope to residential buildings, where occupant-centric consumption often goes unaccounted for in standard energy metrics. This paper starts from the hypothesis that a simple occupant energy efficiency label is needed to capture the essence of occupant behaviour. Such a label would help researchers and practitioners study a wide range of behavioural patterns and may better frame occupant interventions, potentially contributing more than expected to the field. Focusing on the residential sector, this research recognises that the complexity of occupant behaviour and its links to different scientific calculations requires that researchers deal with several intricate factors in their building performance assessments. Moreover, complexity arising from changing attitudes and behaviours—based on building typology, social environment, seasonal effects, and personal comfort levels—further complicates the challenge. Starting with these problems, this paper proposes a framework for an occupant energy labelling (OEL) model to overcome these issues. The contribution of the paper is twofold. Firstly, the literature is reviewed in depth to reveal current research related to occupant behaviour for labelling of humans based on their energy consumption. Secondly, a case study with energy simulations is implemented in the UK, using the CREST tool, to demonstrate the feasibility and potential of OEL. The results show that labelling occupants may help societies reduce building energy consumption by combining insights from energy statistics, surveys, and bills gathered with less effort, and can assist decision-makers in determining the best match between buildings and occupants. While the focus of this study is on residential buildings, future research is recommended to explore the applicability of OEL in office environments, where occupant behaviour and energy dynamics may differ significantly. [ABSTRACT FROM AUTHOR]

With rapid economic development, the amount of the municipal solid waste (MSW) generated has increased dramatically. To improve the socio-economic benefits and environmental impacts of the low-carbon management of MSW, it is crucial to identify the drivers of Greenhouse Gas (GHG) emissions from MSW treatment and assess their systematic and comprehensive benefits. The factor decomposition method is one of the most commonly used methods focused on identifying GHG emission-influencing factors, while the system dynamics (SD) method is commonly used to analyze the causal relationships between linear and nonlinear variables in complex dynamic systems. Unlike existing studies that account for and evaluate MSW from a static perspective, this paper innovatively combines the LMDI-SD model to identify and quantify the GHG emission drivers of MSW and evaluate the benefits of decarbonizing the MSW management in China from a comprehensive and systematic perspective. The results show that the dominant factor driving MSW GHG emissions from 2010 to 2022 is the economic development factor, ∆EED, while the intensity of MSW generation ∆EGI and the structure of MSW treatment ∆ETS play a stronger inhibiting role. Based on this, the SD model is constructed to simulate different scenarios, and the analysis shows that increasing the waste separation rate (S3) is the most effective measure to improve the socio-economic benefits and environmental impacts of the system. Compared with the base scenario, the socio-economic benefits and environmental impacts in 2050, for example, are increased by 82.8% and 43.4%, respectively. Improving the utilization rate of landfill gas (S1), reducing the per capita amount of MSW generated (S4) and increasing the incineration rate of MSW (S2) also have significant advantages for the improvement of benefits. Finally, some policy recommendations for the improvement of the comprehensive benefits of low-carbon MSW management systems are proposed to help policymakers make appropriate decisions. [ABSTRACT FROM AUTHOR]

In the context of slowing economic growth and increasing uncertainty, enhancing the financial flexibility of manufacturing enterprises is a critical foundation for promoting the high-quality development of the real economy. This study selects a sample of Chinese A-share-listed manufacturing firms from Shanghai and Shenzhen, spanning the years 2012 to 2022, and constructs a fixed-effects model to examine the impact of ESG performance on the financial flexibility of these firms and its underlying mechanisms. The study finds that: (1) ESG performance significantly enhances corporate financial flexibility. (2) ESG performance promotes financial flexibility primarily through mechanisms such as alleviating financing constraints, improving competitive advantages, and attracting analysts' attention. (3) Heterogeneity analysis reveals that the positive effect of ESG performance on financial flexibility is more pronounced in high-tech firms and non-heavily-polluted firms. (4) Sub-dimensional analysis shows that corporate governance has a more significant impact on financial flexibility enhancement than social responsibility, while environmental investment exerts an inhibitory effect on financial flexibility. (5) The uncertainty associated with ESG ratings weakens the contribution of ESG practices to the financial flexibility of manufacturing firms. Based on these findings, this paper suggests that enterprises should be encouraged to actively adopt ESG practices, accelerate the improvement of their ESG disclosure systems, and support firms with strong ESG performance to foster high-quality development. [ABSTRACT FROM AUTHOR]

The semi-arid and dry regions of South Africa experience shortages of water resources, which poses major challenges to livelihoods exacerbated by climate change. Despite the importance of indigenous food crops in optimizing water conservation, limited research has been conducted on effective strategies for promoting indigenous crops. This paper explores the potential of indigenous crops in optimizing water conservation in South Africa. This review paper adhered to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses checklist to ensure transparency, rigor, and reproducibility. A comprehensive literature search was conducted across several databases, including Scopus, Web of Science, and Google Scholar. This review found that indigenous crops, such as sorghum and cowpeas, have innate traits that enable them to flourish in environments where water resources are limited. According to the findings of this study, these indigenous crops are resilient to drought and optimize water use efficiency. This review recommends the creation of a national database for indigenous climate-resilient food crops, which can act as an information hub for research and development. In maximizing the water use efficiency of indigenous crops, sustainable water management techniques remain critical. The results of this study have important implications for sustainable agriculture and water conservation in South Africa. [ABSTRACT FROM AUTHOR]

Agricultural cooperatives are the main vehicle for farmers to engage in green agriculture. With the digital transformation in rural areas, it is crucial to explore how cooperative members can effectively access online information and integrate it into green production decision-making processes. Based on the survey data of 530 members of rice planting cooperatives in Heilongjiang Province in China, this paper selected eight green production behaviors commonly used by rice farmers as explained variables, and constructed an ordered probit model. Using the social capital theory, the impact and mechanism of internet use on cooperative members' green production behavior were examined. The results showed the following: (1) Internet use facilitates the cooperative members' green production behavior. This conclusion remains valid even after addressing the endogeneity test and robustness test. (2) The heterogeneity analysis revealed that the internet is particularly effective in enhancing the green production behaviors of farmers who are less educated, middle-aged, and those with strong connections to cooperatives. (3) A further mechanism test indicates that internet use not only significantly influences farmers' trust in cooperatives but also aids them in comprehending the cooperative's production specifications, thereby further advancing the improvement in green production behaviors. (4) Members' satisfaction with cooperative sales can serve as a substitute for the internet in influencing their green production behavior. [ABSTRACT FROM AUTHOR]

E-business, based on information, communication, and digital technologies, is a component of the digital economy. Furthermore, it is characterized by active development, determining the currently spreading changes in the traditional economy. The purpose of this study is to determine the impact of the digital economy on the realization of sustainable development goals and the transformation of the concept of marketing management. The following research methods were used in the study: historical method—to study the evolution of marketing management concepts; statistical analysis—to study aspects of the digital economy; correlation and regression analysis—to identify the relationship between the level of digitalization and key indicators of sustainable development and marketing management; systematic approach to consider digitalization, sustainable development and marketing as interrelated components of a single system. The article presents the relationship of sustainable development goals with the need to improve approaches to marketing management in the context of digitalization. The objectives include UN goal number 8: "Decent Work and Economic Growth", number 9: "Innovation and Infrastructure", and number 12: "Responsible Consumption and Production". The paper examines the evolution in approaches to understanding marketing management in the twentieth and twenty-first centuries. Correlation and regression analysis is used to identify how digitalization affects certain factors and how these factors contribute to it. The paper analyzes the dynamism of the formation and development of the worldwide digital economy, establishes the relationship between its components, and examines their impact on the ecosystem. The dynamics of the number of Internet and social media users in the world is analyzed and the changes in global e-commerce revenue and digital advertising expenditures are estimated. The positive consequences and opportunities that arise in the digital economy are presented. The authors emphasize the transformation of the marketing management concept with regard to the goals of sustainable development. Marketing strategies and directions in state policy for regulating the impact of the digital economy on the environment, taking into account the goals of sustainable development, are proposed for business entities. [ABSTRACT FROM AUTHOR]

Building an ecologically sustainable civilization and promoting green development not only make up the new motive power for China's economic growth but are also an inevitable choice for achieving the "Dual Carbon" goal. This paper draws on the results of China's provincial panels from 2012 to 2021 and constructs a thorough assessment index system for green finance that includes five dimensions: standardized system, disclosure of information, policy incentives, products and market, international cooperation. The influence mechanism of green finance on the realization of the "Dual Carbon" goal is revealed based on both quantity and caliber perspectives of green technological innovation, and the governments' and markets' regulating roles are analyzed. The study's findings imply that (1) green finance facilitates the achievement of the "Dual Carbon" goal; (2) green finance helps to achieve the "Dual Carbon" goal by boosting green technology innovation and, compared with strategic green innovation, the effect of substantive green innovation is more significant; and (3) government support and increased marketization can bolster green finance's contribution to accomplishing the goal. This study not only theoretically breaks through the limitations of the existing green finance evaluation index but also expands the single "quantity" channel of the impact of green finance on carbon emissions to a more comprehensive "quantity" and "caliber" channel, and also provides countermeasures and guidelines for how to better play the "synergy" of the government and the market in the practice of green finance. [ABSTRACT FROM AUTHOR]

In order to advocate for green and environmentally friendly travel modes, enhance the attractiveness of rail transit, and promote the sustainable development of rail transport, we focus on the transportation organization problem under limited-resource conditions. This paper studies the formulation of a train plan under the condition of through operation between intercity and high-speed railway, constructing a multi-objective nonlinear optimization model with train frequency, a stop plan, and turn-back station locations as decision variables. Given the high dimensionality of model variables and complex constraints, an improved multi-population genetic algorithm (IMGA) is designed. Through an actual case study of the through operation between the Chengdu–Mianyang–Leshan Intercity Railway and the Chengdu–Chongqing High-Speed Railway, a staged solution method is adopted for analysis. The results indicate that the through-operation mode can save operational costs for enterprises and travel costs for passengers, while also better adapting to changes in passenger flow. Additionally, the IMGA demonstrates better solution quality and higher efficiency compared to the classical genetic algorithm. The main contribution of this paper is to propose a novel approach to solve the train plan problem. It also contributes to creating a high-quality, high-efficiency, and high-comfort integrated transportation service network, promoting the sustainable development of rail transit. [ABSTRACT FROM AUTHOR]

Sustainability refers to a development approach that meets the needs of the present generation without compromising the ability of future generations to meet their own needs. Solar energy is an inexhaustible and renewable resource. From the perspective of resource utilization, solar power generation has a high degree of sustainability. Therefore, solar power generation is one of the most important ways to transform the energy structure and promote the sustainable development of the economy and society, and it is of great significance for promoting the construction of a resource-conserving and environmentally friendly society. However, solar energy resources also exhibit strong unpredictability; therefore, this paper proposes a novel artificial intelligence (AI) model for short-term solar irradiance prediction in photovoltaic power generation. Leveraging the ProbSparse attention mechanism within an encoder-decoder architecture, the AI model efficiently captures both short- and long-term dependencies in the input sequence. The dingo algorithm is innovatively redesigned to optimize the hyperparameters of the proposed AI model, enhancing model convergence. Data preprocessing involves feature selection based on mutual information, multiple imputations for data cleaning, and median filtering. Evaluation metrics include the mean absolute error (MAE), root mean square error (RMSE), and coefficient of determination (R2). The proposed AI model demonstrates improved efficiency and robust performance in solar irradiance prediction, contributing to advancements in energy management for electrical power and energy systems. [ABSTRACT FROM AUTHOR]

Accurate forecasting of wind power is crucial for addressing energy demands, promoting sustainable energy practices, and mitigating environmental challenges. In order to improve the prediction accuracy of wind power, a VMD-CNN-BiLSTM hybrid model with physical constraints is proposed in this paper. Initially, the isolation forest algorithm identifies samples that deviate from actual power outputs, and the LightGBM algorithm is used to reconstruct the abnormal samples. Then, leveraging the variational mode decomposition (VMD) approach, the reconstructed data are decomposed into 13 sub-signals. Each sub-signal is trained using a CNN-BiLSTM model, yielding individual prediction results. Finally, the XGBoost algorithm is introduced to add the physical penalty term to the loss function. The predicted value of each sub-signal is taken as the input to get the predicted result of wind power. The hybrid model is applied to the 12 h forecast of a wind farm in Zhangjiakou City, Hebei province. Compared with other hybrid forecasting models, this model has the highest score on five performance indicators and can provide reference for wind farm generation planning, safe grid connection, real-time power dispatching, and practical application of sustainable energy. [ABSTRACT FROM AUTHOR]

Inflation across the globe after the COVID-19 pandemic has shown some persistence and followed an upward trend well above inflation targets and beyond normal historical movements. The Saudi inflation rate followed similar patterns of global trends, surging significantly and persisting well above the pre-pandemic levels. This paper examines determinants of inflation in Saudi Arabia, considering internal and external factors, and evaluates whether inflation responds to common global shocks or is largely influenced by macroeconomic variabilities within the economy. Findings and analyses in this paper are based on both conventional Auto Regressive Distributive Lag (ARDL) and non-linear ARDL (NARDL) models using quarterly level data to capture short-run dynamics and long-run relationships between inflation rate and examined macroeconomics variables, namely oil prices real effective exchange rate, money supply, and government spending. Reported results reveal an asymmetrical relationship between oil price fluctuations and inflation rate volatilities in Saudi Arabia. Inclines in oil prices lead to higher inflation, while the decline in oil prices does not alleviate inflationary pressures, and these results are consistent both in the short-run and the long run. The influence of pass-through real effective exchange rate is also evident in transmitting global shocks to local consumer prices in the long run, where a depreciation in real effective exchange rate results in a higher cost of imported goods, exerting additional stresses on local inflation. For factors within the economy, findings indicate a substantial long-term inflationary effect of money supply on the inflation rate in Saudi Arabia, where a one percent increase in the money supply led to more than one-third increase in inflation in the long run. On the other hand, while the influence of government spending on inflation was statistically significant, its impact is less pronounced in explaining the inflation rate's variations. The analysis reveals that the evaluated variables exert a stronger influence on inflation in the long run. This underscores the critical need for policymakers to consider the cumulative effects of these determinants when formulating effective long-term inflation stabilization policies. [ABSTRACT FROM AUTHOR]

Egypt's average share of global carbon dioxide emissions has been rising from mid-1990s to date. This motivates the present study to identify industries that drive carbon dioxide emissions (as direct emitters and as total emitters with high emission multiplier effects). Environmental input–output analysis is applied to Egypt's 2017–2018 input–output table to measure sectoral emissions. The industries identified as high emitters are linked to Egypt's achievement of Sustainable Development Goals, namely, Goals 7, 8, 9, 12, and 13. The findings indicate that ten industries qualify as environmentally degrading (dirty), having the highest emission multiplier effects (in descending order): electricity, gas, and water; non-metallic mineral products; basic metals; rubber and plastic products; chemicals and chemical products; paper and paper products; food products; hotels and restaurants; transportation and storage; and textiles. Eight of these industries also have high output multiplier effects. This underscores that although potential investment in and the growth of these industries will generate output multiplier effects, they will also be coupled with emission multiplier effects. Five other industries had high emission multipliers, as follows: water and sewerage; beverages; coke and refined petroleum products; extraction of crude petroleum; and mining of metal ores. The growth of these industries would not be in favor of the achievement of SDGs. Policy measures are recommended. [ABSTRACT FROM AUTHOR]

Horizontal ecological compensation represents a significant institutional innovation aimed at advancing ecological civilization and serves as a key functional strategy within China's current management framework. This paper employs the horizontal ecological protection compensation agreement of the Yu-Lu section of the Yellow River Basin as a case study. Using a game theory model and theoretical analysis, the paper explores the underlying connotations, theoretical foundations, and legal characteristics of the basin's horizontal ecological protection compensation mechanism. This analysis reveals several challenges within the existing horizontal ecological protection compensation system in the Yellow River Basin, including the predominance of a single compensation entity, unclear compensation standards, a compensation model limited to monetary transfers, and the absence of an effective dispute resolution mechanism. This paper further examines potential improvements to the horizontal ecological protection compensation framework in the Yellow River Basin from a legal system perspective, with the aim of addressing these practical challenges and fostering the region's ecological, environmental, and economic development. [ABSTRACT FROM AUTHOR]

As the mileage of China's highways increases, the focus of highway development has shifted from construction to maintenance and management. With the rapid increase in highway traffic, the overuse of highways, combined with the effects of climate change, has accelerated the occurrence of highway problems and poses new challenges to maintenance strategies. From a system optimization perspective, this paper examines the problem of determining the optimal timing of preventive maintenance on highways. To overcome the shortcomings of this method, which cannot reflect the economic benefits and costs, the total benefits and costs were calculated for different pavement ages within a given analysis period, based on the framework of life cycle analysis. The maintenance timing program with the highest cost-benefit ratio was taken as the optimum maintenance timing program and an example analysis was adopted to validate the feasibility of this method. When the timing of preventive maintenance is later in a pavement's life cycle, the total life cycle benefit decreases while the total life cycle cost increases. Compared to previous studies, this paper considers both direct and indirect influences simultaneously, showing that indirect influence contributes to shortening the timing of pavement preventive maintenance. [ABSTRACT FROM AUTHOR]

This paper highlights the importance of sustainable practices in supply chain management, focusing on upcycling as a key approach to transforming discarded materials into valuable products. It proposes a conceptual framework based on state-of-art and action research, which integrates traditional wood upcycling with secondary material recovery, addressing gaps in the existing literature and promoting collaboration among manufacturers, waste managers, and designers. The framework emphasizes circular economy practices in the wood sector, aiming to enhance resource efficiency, reduce waste, foster innovation, and support job creation. Key aspects of the conceptual framework for the upcycling supply chain in the wood sector include supply chain restructuring, valorizing secondary wood, developing digital tools, and aligning global stakeholders to advance sustainability goals. [ABSTRACT FROM AUTHOR]

China's economic development has had adverse effects on the environment. Nevertheless, the Chinese government is optimistic about its ability to achieve a harmonious balance between economic growth and environmental sustainability. To this end, the government promotes, guides, and supports green innovation through the provision of policies and the creation of a conducive environment. Enterprises play a vital role in implementing and advancing green innovation, making them essential to realizing green development through their innovative capabilities. The relationship between government and business acts as a bridge between these two entities, fostering a synergistic effect that is crucial for achieving this objective. This paper conducts a comprehensive analysis of the existing literature on government–business relationships and green innovation, both domestically and internationally. Utilizing data envelopment analysis, it accurately measures the green innovation efficiency of 292 prefectural-level cities in China. The paper then employs a combination of a qualitative comparative analysis and a requisite condition analysis to establish the causal link between government–business relationships and green innovation development. Our detailed analysis of the data has identified three modes of driving green innovation: 'government service-oriented', 'policy support-oriented', and 'pro- and clean-oriented'. These modes correspond to the developmental trajectories of China's first, second, and third–fourth–fifth-tier cities, respectively. This paper offers policy recommendations for the systematic reform and optimization of government–business relationships in China. These recommendations are grounded in the three dimensions of the government–business relationship and consider the current conditions of cities at various stages of economic development. The findings and recommendations presented in this paper can serve as valuable insights for policymakers and businesses alike, providing guidance for future initiatives aimed at fostering a more sustainable economy. [ABSTRACT FROM AUTHOR]

With the frequent occurrence of various emergencies, the stable operation of enterprises has been seriously affected, and the research of resilience has received more and more attention in various fields. Enterprise resilience (En_RES) is not only related to corporate survival but is also the key to determining whether a company can realize long-term development. To explore the impact of En_RES on enterprise sustainable development (En_SD), this paper conducts an empirical test using panel regression models based on the data of A-share listed companies in China from 2004 to 2022. It is found that En_RES has a significant positive contribution to En_SD, which is more obvious when the degree of environmental uncertainty is lower, the degree of information sharing is higher, and the degree of business complexity is higher. The mechanism test analysis finds that En_RES can further contribute to En_SD by reducing the bankruptcy risk, improving credit availability, and optimizing resource allocation efficiency. This paper innovatively analyzes and verifies the impact of En_RES on En_SD and its functioning mechanism from the perspective of microenterprises, which not only enrich the theoretical relationship between En_RES and En_SD but also provide important references for enterprises to pay attention to and develop resilience in practice, which can help enterprises better cope with challenges, grasp opportunities, and make contributions to the sustainable development of enterprises. [ABSTRACT FROM AUTHOR]

With increased highway mileage, various types and quantities of infrastructure are equipped on the roadside to improve traffic safety and efficiency but also encounter difficulty in asset management. The collected data are separately stored with diverse formats, granularity and quality, causing repeated acquisitions and islands of information coherence. The life-cycle interoperability of infrastructure data are required to support life-cycle application scenarios in sustainable development. This paper analyzes 459 papers and 538 survey questionnaires to obtain the literature and practical digital requirements, including unified classification and standardized formats, linkage from separated data sources, support for data analysis across different scenarios, etc. To satisfy these requirements, an infrastructure digitalization framework is proposed, including road infrastructure and other data, data governance, life-cycle data integration, application scenarios, regulations and standards, and performance assessment. The application scenarios involve four categories—design and construction, maintenance, operation, and highway administration—each of which contains four or five scenarios. Then, the data integration approach is first developed with master data identification and determination of data elements for data interoperation between different application scenarios, using a modified data–process matrix, correlation matrix, and evaluation factors. A data relationship model is adopted to present static and dynamic correlations from the multi-source data. Numerical experiments are implemented with two practical highway administration and maintenance systems to demonstrate the effectiveness of the data integration approach. Master data identification and data element determination are applied to guide life-cycle data interoperation. [ABSTRACT FROM AUTHOR]