Search Results (2,861)

Technology-based small and micro enterprises play a crucial role in national economic and social development. Managing their credit risk effectively is key to ensuring their healthy growth. This study is based on corporate credit management theory and Wu’s three-dimensional credit theory. It clarifies the credit concept and measurement logic of these enterprises, considering their unique development characteristics in China. A credit evaluation system is constructed, and an innovative method combining machine learning with comprehensive evaluation is proposed. This approach aims to assess the credit status of technology-based small and micro enterprises in a thorough and objective manner. The study finds that, first, the credit level of these enterprises is currently moderate, with little variation. Second, financial information remains a key factor in credit evaluation. Third, the ML-AHP (Machine Learning-Analytic Hierarchy Process) combined weighting method effectively integrates subjective experience with objective data, providing a more rational assessment. The findings provide theoretical references and practical guidance for the healthy development of technology-based small and micro enterprises, early credit risk warning, and improved financing efficiency. Full article

Using data from 188 traditional energy companies listed on China’s A-share market from 2012 to 2023, this study adopts the double-difference method to assess the changes in the green investment of traditional energy companies before and after the implementation of environmental regulation policies in depth and further explores the actual effects and potential risks of green investment on the green transformation of traditional energy companies. This study shows that the environmental regulation policies significantly increased the green investment of traditional energy enterprises, but this increase did not effectively promote the overall green transformation of the enterprises; rather, they became more focused on meeting the current compliance requirements while ignoring the fundamental green technological innovation and production mode change. Further analysis reveals that, as environmental standards continue to rise, the increasing green investment expenditure of traditional energy companies for meeting the standards will continue to outpace the growth in capital inflows of traditional energy companies, resulting in a threat to the financial soundness of the companies in the short term and a significant increase in financial pressure. In the long run, the lack of sustained and stable external financial support for a long period of time will not only constrain the green transformation process of enterprises but may also pose a serious threat to the survival foundation of enterprises and even lead to the elimination of enterprises in fierce market competition. Full article

This study aims to understand how InsurTech has developed in Korea. To achieve this, we collected InsurTech-related news articles published in the Korean media over the past eight years. Using a relatedness analysis based on the TopicRank algorithm, a text-mining technique, we extracted the top keywords associated with InsurTech by year. The extracted keywords were analyzed and discussed in terms of development trends: which technologies gained prominence over time, who the key players were, and what solutions were introduced. The analysis revealed several key trends in InsurTech’s development in Korea. First, regarding changes in InsurTech technology, blockchain and the Internet of Things initially garnered significant attention, but artificial intelligence and big data later emerged as more critical technologies. Second, in terms of market players, government agencies and research institutes initially created forums for discussion, such as seminars to draw social attention to InsurTech. Over time, innovative startups entered the market, general agencies specializing in insurance brokerage gained prominence in the online marketplace, and the entry of Big Tech platforms further diversified the market. Finally, in terms of InsurTech-related insurance solutions, early attention was focused on developing new products. However, the trend gradually shifted toward improving the accessibility and convenience of existing insurance services. Additionally, asset management and payment settlement services—linked to financial services beyond traditional insurance—emerged, along with new concepts such as healthcare, which reshaped the approach to insurance services. This study contributes to understanding how InsurTech has evolved by identifying key trends in emerging technologies, leading market players, and innovations in the insurance value chain. The Korean case provides insights that may help explore similar patterns in other countries. Full article

The protection of agricultural heritage sites has become a global human responsibility and consensus. However, the potential effect of agricultural heritage sites on the green development of agriculture has currently been ignored. Since ancient times, China has been founded on agriculture, and the number of important agricultural cultural heritages ranks first in the world, with strong representativeness. The two-way fixed effects model was employed to empirically test the positive impact of agricultural heritage site protection on the green development of agriculture, utilising data from 30 provincial units in China over a 21-year period from 2001 to 2021 in this paper. Additionally, a mediating effect model was used to test the potential mechanism. The specific conclusions are as follows: firstly, the protection of agricultural heritage sites has a significant positive effect on the green development of agriculture; secondly, the protection of agricultural heritage sites can advance the agricultural industrial structure, increase the land transfer rate, strengthen the construction of new agricultural management organisations, enhance financial investment in supporting, and promote green technology innovation. The five paths were found to have passed the mediation effect test. Thirdly, the positive effect of protecting agricultural heritage sites on the green development of agriculture is heterogeneous. Specifically, the effect is more pronounced in the eastern and central regions, particularly in areas with higher levels of AI development and lower urbanisation. The ultimate objective is to utilise evidence from China to develop nature-based solutions for the protection and utilisation of agricultural heritage and green development of agriculture in other world agricultural heritage sites. Full article

Urban green development is crucial for citizen well-being and serves as a key pillar of sustainable development strategies. Collaborative governance mechanisms help address management, technical, and financial challenges in urban green development. The renovation of old residential communities within the context of urban renewal is becoming a focal point in the development of Chinese cities. To promote green development in the renovation of old residential communities in China, this study introduces the collaborative governance mechanism of government–social capital cooperation and identifies the factors influencing social capital participation in green development. A hybrid approach is proposed, combining grounded theory, IGAHP subjective weighting, CRITIC objective weighting, game theory, and ISM. This approach is applied to identify, evaluate, and analyze the factors driving social capital participation in the green renovation of old residential communities. The results indicate that government incentives and constraints, policy support, the costs and benefits of implementing green renovation, the development of green renovation technologies, and construction technical abilities significantly influence the decision-making of social capital. The findings provide theoretical support for decision-making by governments and social capital in participating in the green renovation of old residential communities and offer a methodological reference for analyzing social capital participation in other urban green development projects and for further policy formulation. Future research should focus on examining social capital involvement in other types of urban green development projects. Full article

This study explores the relationships between the digital economy, R&D investment, and carbon emissions, as well as the mediating role of financial technology (fintech). Despite a growing body of research, the impact of the digital economy on carbon emissions remains contested, partly due to the limited scope and inconsistent measures in existing studies. Additionally, while R&D is a pivotal driver of modern development, its potential quadratic effects on carbon emissions in China remain unexplored. By employing a comprehensive Digital Economy Index and analyzing panel data from 2011 to 2020 across Chinese regions, this study provides new insights into how digitalization and innovation influence carbon emissions. The findings reveal a positive linear correlation between the digital economy and CO₂ emissions over the last decade. Moreover, R&D investments exhibit an inverse U-shaped relationship with emissions, acting as an effective factor in reducing CO₂ emissions. Notably, the turning point of this relationship occurs in Quadrant I, where most regions are clustered, indicating substantial efficiency gains from early-stage R&D investments and their significant potential to enhance sustainable development. Furthermore, fintech emerges as a significant mediator in the R&D–emissions dynamic, underscoring its critical role in this context. Full article

This study examines the integration of multi-real-option valuation and security token offering (STO) as an innovative approach to real estate project financing. The case study of Aspen Resort Development serves to illustrate this methodology. The traditional discounted cash flow (DCF) method is frequently ill-suited to the dynamic and uncertain nature of long-term real estate projects, particularly in regard to the ability to adapt to market fluctuations. In order to address these limitations, this study employs a multi-real-option model with a binomial lattice framework, thereby facilitating flexible decision-making in various investment stages. The analysis demonstrates that the STO-based project financing (STO-PF) model offers enhanced financial performance and strategic advantages in comparison to the conventional DCF approach. Furthermore, the STO-PF model has the effect of increasing liquidity, expanding investment accessibility, and improving risk management through the utilization of digital platforms. By quantifying the project’s extended net present value (ENPV), the integration of STOs with real-options models can facilitate optimal investment decisions in the context of a high level of market volatility. Consequently, the STO-PF model is determined to yield a project value (E) of USD 7.34 million and a real-options value (ROV) of USD 3.69 million. This is markedly higher than the net present value (NPV) of USD 3.65 million derived from the traditional project finance (PF) model. Furthermore, the put option for the second investment stage contributes USD 16.45 million to the overall value of the project, thereby demonstrating the flexibility and strategic advantages of the STO framework in comparison to static NPV analysis. The Aspen project serves as a case study, demonstrating the financial viability of phased investments in dynamic market conditions. It contributes to the theoretical understanding of STO-based financing and provides practical insights for developers seeking flexible and innovative financing solutions in the real estate sector. Further research is required to confirm the applicability of STOs in diverse market environments and regulatory contexts. Additionally, in-depth research is necessary to integrate emerging technologies, such as artificial intelligence and machine learning, into multi-real-option-based financial platforms. This integration aims to enhance financial modeling and decision-making processes, as well as to facilitate the integration of digital technologies in this field. Only then can the development and implementation of smart construction development advance. Full article

Environmental sustainability concerns have led to an increased focus on climate finance, resulting in substantial investments to boost financial sector development. However, recently, climate initiatives have encountered multiple policy uncertainties. This study aims to empirically investigate the impact of U.S. climate policy uncertainty (CPU) on Indian financial inclusion, in addition to exploring the moderating role of institutional quality on the aforementioned relationship. To achieve the above objectives, we first constructed two separate indexes for financial inclusion using the weighted method and principal component analysis. Next, to empirically estimate the above relationship, we employed the two-step system-generalized method of moments (Sys-GMM) and the sequential (two-stage) linear panel data model (SELPDM) on the sample data from 2000–2022. The Sys-GMM estimate test validated that climate policy uncertainty negatively influences India’s financial inclusion. However, institutional regulation and governance assist in moderating the negative influence of U.S. climate policy uncertainty on Indian financial inclusion initiatives. Furthermore, the study also confirmed that various dimensions of institutional regulation and governance exert a positive and significant effect on financial inclusion. Finally, the study validates that economic growth and technological advancement assist financial inclusion initiatives in India. The study is an original work and offers several policy recommendations. Full article

This study uses the implementation of the watershed compensation policy as a quasi-natural experiment and selects a sample of 53 cities located within the four major watersheds from 2005 to 2022. By employing a staggered difference-in-differences model and a synthetic control difference-in-differences model, the study investigates how watershed compensation policies influence green technology innovation ecosystems and delves into the underlying mechanisms that are responsible for these impacts. The research reveals the following findings: (1) The introduction of the watershed compensation policy markedly boosts the development of green technology innovation ecosystems in the pilot cities, and this finding remains consistent following a series of robustness checks. (2) An analysis of the mechanisms indicates that the watershed compensation policy exerts its impact on the advancement of green technology innovation ecosystems through a reduction in carbon emission intensity and the enhancement of wastewater treatment efficiency. (3) The influence of the watershed compensation policy on green technology innovation ecosystems varies according to the level of public financial expenditure and labor productivity. This research offers a factual foundation for comprehending the effects of watershed compensation policies on the innovation of green technologies within China. Full article

The rapid economic growth in Southeast Asia has heightened concerns about its environmental sustainability, particularly in relation to CO₂ emissions. Despite the growing focus on climate change mitigation, the region faces significant challenges in balancing economic development, energy transitions, and environmental conservation. Existing studies often overlook the complex interplay between these factors, leaving a critical gap in understanding how tailored strategies can address country-specific dynamics. To bridge this gap, this study introduces the “Sustainable Energy-Environment Nexus” (SEEN) framework, which integrates economic growth, energy transitions, and environmental conservation as interconnected elements necessary for achieving carbon neutrality in both the short and long run. Using data from eight Southeast Asian countries (Indonesia, Malaysia, China, South Korea, Vietnam, Singapore, Thailand, and Japan) over the period 1990–2023, this study employs the Autoregressive Distributed Lag (ARDL) approach and the Vector Error Correction Model (VECM) technique to analyze the relationships between CO₂ emissions, GDP, financial development, forest areas, renewable energy, non-renewable energy consumption, and trade openness. The findings reveal that GDP and non-renewable energy consumption significantly drive CO₂ emissions in countries like Indonesia, Malaysia, Japan, and South Korea. Conversely, forest areas, financial development, renewable energy, and trade openness are effective in reducing emissions in countries such as Vietnam and China. This study highlights the critical role of renewable energy adoption while addressing challenges such as inadequate infrastructure and limited technology transfer. It also identifies opportunities for regional cooperation in innovation and policy harmonization. To support sustainable energy development, tailored policy recommendations include incentivizing investments in renewable energy, enhancing technology transfer, expanding forest conservation efforts, and aligning regional renewable energy targets across ASEAN. The SEEN framework provides a robust foundation for advancing research and policy design aimed at reducing CO₂ emissions and promoting environmental sustainability across Southeast Asia. Full article

With the advancement of the Internet, social media platforms have gradually become powerful in spreading crisis-related content. Identifying informative tweets associated with natural disasters is beneficial for the rescue operation. When faced with massive text data, choosing the pivotal features, reducing the calculation expense, and increasing the model classification performance is a significant challenge. Therefore, this study proposes a multi-strategy improved black-winged kite algorithm (MSBKA) for feature selection of natural disaster tweets classification based on the wrapper method’s principle. Firstly, BKA is improved by utilizing the enhanced Circle mapping, integrating the hierarchical reverse learning, and introducing the Nelder–Mead method. Then, MSBKA is combined with the excellent classifier SVM (RBF kernel function) to construct a hybrid model. Finally, the MSBKA-SVM model performs feature selection and tweet classification tasks. The empirical analysis of the data from four natural disasters shows that the proposed model has achieved an accuracy of 0.8822. Compared with GA, PSO, SSA, and BKA, the accuracy is increased by 4.34%, 2.13%, 2.94%, and 6.35%, respectively. This research proves that the MSBKA-SVM model can play a supporting role in reducing disaster risk. Full article

The transition to sustainable mobility is one of the most pressing and complex challenges for the automotive industry, with impacts that extend beyond the mere reduction of emissions. Electric vehicles, while at the center of this evolution, raise questions about the consumption of natural resources, such as lithium, copper, and cobalt, and their long-term sustainability. In addition, the introduction of advanced technologies, including artificial intelligence (AI) and autonomous systems, brings new challenges related to the management of components and materials needed for their production, creating a significant impact on supply chains. The growing demand for electric and autonomous vehicles is pushing the industry to rethink production models, favoring the adoption of circular economy principles to minimize waste and optimize the use of resources. To better understand the implications of this transition, this study adopts a multiple case study methodology, which allows in-depth exploration of different contexts and scenarios, and analysis of real cases of dismantling and recycling of internal combustion engines (ICEs) and electric vehicles (EVs). The research includes a financial simulation and a comparison of revenues from the dismantling of ICE and EV vehicles, highlighting differences in the value of recycled materials and the effectiveness of circular economy practices applied to the two types of vehicles. This approach provides a detailed overview of the economic benefits and challenges related to the management of the end of life of vehicles, helping to outline optimal strategies for a sustainable and cost-effective future in the automotive sector. Full article

Agricultural production faces the dual challenge of increasing output while ensuring efficient resource utilization and environmental sustainability amid escalating global climate change and relentless increases in human demand. This study used provincial panel data from China from 2001 to 2022 to address these challenges. It systematically evaluated the dynamic evolution of agricultural green total factor productivity (AGTFP) by selecting “resources” and “energy” as core input factors and adopting a dual-output approach focused on “economic” and “low-carbon” outcomes. This study thoroughly analyzed the synergistic mechanisms of factors such as natural endowment, agricultural technology, economic development, and environmental regulation, exploring their impact on AGTFP enhancement through the innovative application of the dynamic fuzzy-set qualitative comparative analysis (fsQCA) method. There was a significant upward trend in AGTFP across China, indicating notable progress in green agricultural development. Additionally, three pathways promoting AGTFP improvement were identified: resource–economy-driven, technology–policy-guided, and multifactor-synergy. Simultaneously, two modes constraining AGTFP enhancement were uncovered: economy–policy suppression and human capital–economy suppression, highlighting the pivotal role of regional economic development and the conditionality of converting natural resource advantages. Moreover, the contributions of these pathways to AGTFP exhibited notable temporal dynamics. Major economic events, such as the 2008 financial crisis and policy shifts, including the 2012 “Ecological Civilization” strategy, significantly altered the effectiveness of existing configurations. Our analysis of regional heterogeneity revealed distinct geographical patterns, with the resource–economy-driven model predominantly observed in central regions and the technology–policy-guided and multi-factor-synergy models more prevalent in central and eastern regions. These findings highlight the importance of formulating differentiated policies tailored to the specific needs and stages of development in different regions. Specifically, enhancing the synergy between resource management and economic development, optimizing technology–policy integration, and promoting coordinated multisectoral development are critical to fostering sustainable agricultural practices. This research provides crucial empirical evidence for shaping targeted policies that can drive green agricultural development across diverse regional contexts. Full article

The concept of digital maturity has gained prominence in the context of digital transformation. It refers to an organization’s ability to effectively adapt to changing environments using digital technologies. At the same time, the dynamic capabilities of an organization play a crucial role in maintaining a competitive advantage. These capabilities allow organizations to integrate, build, and reconfigure competencies in response to market dynamics. Despite empirical evidence supporting the impact of dynamic capabilities on competitive advantage, there remains a need to explore the specific mechanisms driving this relationship. Moreover, in traditional industries experiencing digital disruption, understanding digital maturity as an intermediate outcome becomes essential. This study focuses on the Palestinian financial sector and investigates the significance of digital maturity in the context of dynamic capabilities. Primary data were collected through an online questionnaire survey, and a model was estimated through a SEM-PLS methodology. The results highlight a strong relationship between dynamic capability and competitive advantage. Thus, digital maturity plays a crucial role in enhancing strategic planning efficiency through the implementation of dynamic capabilities. Full article

The high-quality development of urban innovation provides important support for implementing new development concepts, constructing new development patterns, and promoting high-quality development. Based on the Technology–Organization–Environment (TOE) theoretical analysis framework, this paper takes 19 first-tier cities and 30 second-tier cities as research samples, explores the multiple path combinations of the business environment on urban high-quality development from a configuration perspective, and uses the fsQCA method. The research results show that the following are true: (1) The innovation ecology is the sole necessary condition for the high-quality development of urban innovation development; (2) efficient financial services and comprehensive market size play a crucial role in enabling cities to achieve high-quality innovation development; and (3) there are three configurations driving high-quality urban innovation development, namely the “Balanced Synergy Pathway”, the “Organizational Synergy Pathway”, and the “Technological Synergy Pathway”. This study explores the impact of the coupling of the business environment on the high-quality development of urban innovation, reveals the diverse configuration relationships of the business environment in urban high-quality development, and has important theoretical and practical significance for the high-quality development policies of cities. Full article