Abstract: The deepening of economic globalization has made corporate social responsibility a key support for multinational enterprises to foster international competitiveness. The intensification of management conflicts caused by cultural differences has become the core obstacle to the effective implementation of corporate social responsibility. Based on Hofstede's cultural dimension theory and combined with practical cases of Chinese enterprises' overseas operations and research data from the World Business Council for Sustainable Development, this article analyzes the mechanism of cultural differences on corporate social responsibility practice. From five dimensions of cultural adaptation optimization, cross-cultural communication upgrading, professional talent cultivation, dynamic integration of standards, and performance evaluation improvement, a cross-cultural management framework for corporate social responsibility in a globalized business scenario is established. Field research and data verification confirm that power distance and collectivism/individualism exert the most prominent impact on the implementation quality of CSR. The flexible balance between localization adaptation and globalization standards can promote a 35.2% increase in the success rate of corporate social responsibility projects. This study provides viable approaches for multinationals to address cross-cultural corporate social responsibility management difficulties and achieve long-term operation. Read More

Abstract: The deepening of digital transformation and the deep integration of financial technology and commercial bank management have not only optimized business processes and improved service quality and efficiency, but also presented new characteristics of increased concealment and diversified causes of operational risks. Traditional operational risk management frameworks are facing adaptability challenges. Based on the regulatory rules of the National Administration of Financial Regulation (NAFR), authoritative industry statistical data, and the practical application of financial technology in state-owned large banks, this article systematically analyzes the dual impact of financial technology on bank operational risk, sorts out the existing weaknesses and underlying causes of risk management, and proposes adaptive optimization solutions. Practice has shown that although financial technology effectively reduces traditional risks related to manual operations, it also gives rise to new risks such as data security and algorithm model bias. In addition, the insufficient supply of interdisciplinary talents and the lagging iteration of internal control systems continue to constrain the effectiveness of risk control. This study can provide practical references for commercial banks to improve their operational risk management system and strengthen their risk prevention and control capabilities through the use of financial technology, and help banks achieve stable operations in digital transformation. Read More

Abstract: This article reviews the historical evolution of regulations related to used car sales in the United States, analyzes how these regulations affect the presentation of vehicle information on online used car platforms, and discusses how platforms can establish and improve consumer trust within this legal framework. The author believes that with the continuous improvement of the legal system and business practices of the federal and state governments in the United States, it is an important external driving force to promote the reform of platform information disclosure and standardization. Consumer trust maintenance is a comprehensive and systematic process that includes information quality, platform guarantee measures, credit evaluation system, and social supervision. The article aims to provide a theoretical perspective for understanding the normative development of the US used car online market and to provide some reference for the healthy and benign development of China's used car online market through the study of the correlation between rule changes, innovative presentation methods, and the formation of trust relationships. Read More

Abstract: Against the background of accelerated urbanization and increasing demand for ecological protection, land use change has significant impacts on regional ecological security and sustainable development. Based on land use data of Sichuan Province for the years 2000, 2010, and 2020, this study systematically analyzes the characteristics of land use change from the perspectives of temporal variation, type conversion, and spatial patterns by integrating the land use transition matrix and the standard deviational ellipse method. The results show that from 2000 to 2020, the land use structure in Sichuan Province underwent significant adjustments, with forest and built-up land continuously increasing, while cropland and grassland showed a declining trend. Land use conversion was mainly characterized by mutual transformations among cropland, grassland, and forest, accompanied by the conversion of cropland to built-up land, presenting an overall pattern of “cropland shifting toward ecological land and built-up land.” The spatial distribution pattern was strongly constrained by topographic conditions, forming a basic pattern of “plateau forest-grassland, basin agriculture, and urban agglomeration,” with the overall structure remaining relatively stable over the 20-year period. The spatial distribution directions of different land use types were generally stable, and the migration of the centers of gravity was limited. Among them, cropland exhibited relatively significant changes, while built-up land showed a continuous expansion trend. The findings of this study can provide a scientific reference for optimizing regional land use allocation and ecological protection. Read More

Abstract: Inefficient investment and persistent overcapacity remain central concerns in modern economies, particularly in contexts where capital markets and corporate governance structures are imperfect. This paper examines the role of patient capital in mitigating these problems from the perspective of factor allocation. Rather than treating inefficient investment as a purely behavioral or agency-driven phenomenon, the analysis situates it within a broader framework of resource misallocation within firms. Patient capital, characterized by long investment horizons and tolerance for delayed returns, is argued to influence firms not only by alleviating financing constraints but also by reshaping internal allocation mechanisms and governance structures. Building on existing empirical and theoretical insights, the paper develops a mediation framework in which factor allocation efficiency serves as the transmission channel linking patient capital to investment outcomes. The analysis suggests that patient capital reduces both overinvestment and underinvestment by stabilizing expectations and altering the criteria through which resources are deployed. The findings contribute to the literature by integrating capital structure, governance, and allocation efficiency into a unified analytical perspective. Read More

Abstract: To address the problem of customer purchase behavior prediction in bank term-deposit services,  this paper develops a machine-learning-based prediction framework using the bank marketing dataset. First, the raw data are processed through missing-value inspection, categorical variable encoding, relevant feature selection, imbalance handling, and data standardization. Then, three models, namely Random Forest, Logistic Regression, and LightGBM, are constructed to analyze customer attributes, marketing-related attributes, and economic background attributes. Experimental results show that, among the three models, LightGBM achieves the best overall performance, with an accuracy of 91.95% and a test F1-score of 60.22%, outperforming both Random Forest and Logistic Regression. Further analysis indicates that features such as call duration and campaign frequency have strong influence on customer subscription decisions. The results demonstrate that machine learning methods can effectively improve the accuracy of identifying potential term-deposit customers, and provide useful data support for precision marketing and resource optimization in banking services. Read More

Abstract: As climate issues become more frequent, the government's macro-climate policy regulation plays an increasingly important role in financial markets. Based on this, this article starts from four types of futures products in the futures market: food, agricultural products, energy, and chemicals, and explores the potential effects caused by climate policy uncertainty at the level of climate transition risks. The research results show that climate policy changes in the current period are significantly positively correlated with the price index of grain, agricultural products, and energy futures products, and are significantly negatively correlated with the price index of chemical futures products. These results are still robust after lag one period and adding control variables. Climate policy uncertainty has a great impact on futures product prices. Read More

Abstract: In the context of the rapidly evolving digital economy, digital transformation has emerged as a critical strategic priority for enterprises seeking to enhance management efficiency and sustain competitive advantage. Despite the growing recognition of its importance, many enterprises continue to struggle with effectively integrating digital technologies into their management systems, resulting in significant gaps between technological investment and actual management outcomes. This paper examines the relationship between digital transformation and enterprise management efficiency from the perspective of business administration. By employing literature analysis and theoretical discussion, this study systematically investigates how digital transformation influences key management dimensions, including information transmission, resource allocation, decision-making quality, and organizational flexibility. Furthermore, the paper identifies five major challenges that enterprises encounter during digital transformation, namely, the lack of a clear digital strategy, insufficient digital talents and capabilities, organizational resistance and cultural barriers, weak data governance and information security, and the imbalance between technology investment and management return. On this basis, a set of practical paths is proposed to guide enterprises in improving management efficiency through digital transformation, encompassing strategic planning, talent development, organizational optimization, data governance enhancement, and performance evaluation mechanism construction. The findings suggest that digital transformation, when effectively aligned with management innovation, can substantially improve enterprise management efficiency and support sustainable organizational development. This study contributes to the existing literature by offering an integrated framework that connects digital transformation practices with concrete management improvement strategies, providing … Read More

Abstract: Corporate venture capital is a window for incumbents to acquire new technologies, and it is also a key force to promote the growth of new ventures, the birth of unicorns and industrial innovation. Combined with the research status and development trend of CVC at home and abroad, the symbiotic unit, symbiotic relationship and symbiotic environment of symbiosis theory are embedded into the practice of corporate venture capital, aiming to build a multi-actors interaction mode driven by corporate venture capital. On this basis, the CVC driven multi-actors value co-creation integration system is built from the perspective of value creation, and the path selection of multi-actors value co-creation is proposed from the macro-level to create the "sensor + adapter" between the enterprise and the environment, the meso level to build the "channel" for the exchange of resources between enterprises, and the micro-level to improve the cognitive ability and creativity of individuals/teams. All these are to improve the ecological construction of equity investment market and promote the harmonious development of large and medium-sized enterprises. Read More

Abstract: Promoting the development of emerging technologies by contexts has become an important part of China's industrial policy. Research on the formation mechanism of new quality productivity is of great significance for the application of emerging technologies. Based on the pioneering innovation of XAG company in agricultural plant protection UAV, the exploratory case study was carried out, and the formation mechanism of new productivity with the logic of "Contexts discovery of emerging technologies - Adaptation of emerging technologies to contexts - Iteration of major functions of emerging technologies - Iteration of secondary functions of emerging technologies - Ecological development of emerging technologies" was summarized. The research finds that the promotion and application of emerging technologies depend on finding appropriate contexts for them, and emerging technologies have competitive advantages in these contexts; The prerequisite for the application of emerging technologies in the scene is that its main functions can meet the needs of the scene and are constantly upgraded, and then its secondary functions are upgraded, and finally the ecological application of emerging technologies is realized. The research provides a theoretical basis and practical reference for the research and development of emerging technologies for the scene. Read More

Abstract: Exploring the spatial configuration of rural settlements for low-carbon development is of great significance for addressing global climate change and promoting sustainable urban-rural transitions. It also constitutes a critical component in achieving China’s “Dual Carbon” goals. Existing studies predominantly focus on the singular dimensions of morphology, size, or function, which limits their capacity to address the complex demands of systemic decarbonization in rural areas. Taking Longxi County, a typical loess hilly-gully region on the Loess Plateau, as a case study, this research constructs a three-dimensional analytical framework integrating “Morphology, Size, and Function”. By employing spatial analysis, K-means clustering, this paper examines the evolution of rural settlements from 2000 to 2020. The results indicated a trend of agglomerative restructuring in settlement morphology, evolving from scattered points to clustered patches. Settlement sizes were characterized by polarization towards large villages and decline of small ones, while functions transitioned from production-dominated to diversified. Both total carbon emissions and emission intensity increased significantly, forming "high-carbon corridors" along transportation arteries and "high-carbon poles" in valley areas. M₂-S₁-F₄ and M₃-S₁-F₄ types demonstrated relatively superior low-carbon performance, whereas M₂-S₁-F₂ and large-scale settlements exhibited higher emissions. Read More

Abstract: With the rapid advancement of Artificial Intelligence (AI) technology and the continuous restructuring of the digital economy, the traditional economics teaching system can hardly meet the requirements of talent cultivation and disciplinary development in the new era, confronting prominent issues including the disconnection between theory and practice, rigid teaching models, and backward application of AI technology. Based on modern educational theories such as personalized learning and industry-education integration, and considering the abstract, empirical, and applied characteristics of economics courses, this paper systematically examines the advantages and transformative opportunities of AI in economics teaching. It thoroughly elaborates on the inherent logic and practical necessity of economics teaching reform in the context of AI, constructs a systematic reform path of "goal reconstruction—system optimization—model innovation—practice enhancement—evaluation reform," and puts forward supporting measures from four dimensions: technology, faculty, resources, and students. Guided by the construction of new liberal arts, this research enriches the theoretical system of economics teaching reform, provides operable practical references for the intelligent transformation of university economics courses, facilitates the in-depth integration of economics teaching and AI technology, cultivates compound economic talents with data thinking, practical capabilities, and innovative literacy, and highlights the disciplinary value and contemporary mission of economics in "applying knowledge to practical use." Read More

Abstract: A financial analysis of iFlytek, a bellwether in China's artificial intelligence industry, reveals that while the company's assets have been consistently expanding, its profitability has been on a continuous decline in recent years. Therefore, this paper attempts to apply time series models to forecast the company's net profit for the period 2025–2027, aiming to provide decision-making insights for both investors and management. Read More

Abstract: Against the dual backdrop of intensifying global climate change and the deepening of Sustainable Development Goals, the synergistic advancement of low-carbon transition and resilience building has emerged as a critical pathway for the international community to address complex environmental risks. This study constructs a comprehensive evaluation indicator system for urban resilience and low-carbon development in the Yellow River Basin. By employing the entropy-weighted TOPSIS model and the coupling coordination degree model, it quantifies the synergy level between urban resilience and low-carbon development in the Yellow River Basin from 2006 to 2021 and reveals its spatio-temporal evolution characteristics. Furthermore, Geographic Detector is utilized to identify key driving factors, and finally, the Spatial Durbin Model is applied to explore their spatial effects. The results indicate that from 2006 to 2021, the overall urban resilience level in the Yellow River Basin exhibited a fluctuating upward trend, displaying a spatial gradient pattern where the lower reaches surpass the middle reaches, which in turn exceed the upper reaches. Low-carbon development demonstrated phased acceleration, although the energy transition lagged, with a spatial pattern characterized as "high in the east and low in the central and western regions." The coupling coordination degree between the two increased from 0.29 to 0.45, with regional disparities widening; the lower reaches experienced the fastest improvement and formed high-value agglomeration areas, the middle reaches showed accelerated catch-up growth, while progress in the upper reaches remained sluggish. The effect of the "Low-Carbon City" pilot policy initially declined and subsequently increased, exhibiting siphonic spillovers. Gross Domestic Product and fiscal expenditure emerged as the most dominant driving factors, with the synergy between economy and resources constituting a key impetus. The spatial spillover effects of … Read More