Abstract: The real estate market is a crucial pillar of the national economy. As an international financial center, Shanghai boasts a highly active real estate market with distinct price fluctuations, becoming a key area for regulatory policies. Interest rates, as core macroeconomic regulation tools, including traditional bank lending rates and the Loan Prime Rate (LPR) since its 2019 reform, exert significant impacts on real estate prices through the transmission mechanisms of the IS-LM model and credit rationing theory. The 2019 LPR reform has formed a "dual interest rate system", but the combined impacts, effect differences and synergistic effects of the two rates on Shanghai’s real estate prices have not been systematically explored based on classic economic theories. Based on Shanghai’s time-series data from 2001 to 2024, this work constructs an econometric model combined with relevant theories to empirically analyze the impact mechanism of the dual interest rates on Shanghai’s real estate prices. The results indicate that both rates have significant negative impacts on Shanghai’s housing prices and exhibit synergistic regulatory effects; the LPR has a stronger impact on housing prices with an elasticity coefficient of -3.5, higher than that of traditional bank lending rates (-2.8); the transmission lag of LPR is 2–3 quarters, while that of traditional bank lending rates is 3–4 quarters; purchase restriction policies and land supply can significantly weaken the impact of interest rates on real estate prices. This study fills the research gap in the impact of the "dual interest rate system" on real estate prices in megacities after the LPR reform, provides quantitative references for optimizing the interest rate regulation policy of Shanghai’s real estate market, and offers a reference for real estate regulation in similar cities. Read More

Abstract: The relocation of labor-intensive manufacturing from China to ASEAN since 2012 reconfigures the regional division of labor rather than constituting zero-sum industrial transfer. Treating production tasks as the unit of analysis, we integrate global value chain theory, regional value chain analysis, the flying geese model, new economic geography, and the trade-in-tasks literature to identify three reorganization margins—extensive, intensive, and regional integration—shaped by RCEP’s institutional architecture. Drawing on the GVC upgrading literature, we differentiate capability-deepening integration, which builds host-country productive capacities, from capability-thinning assembly operations that entrench dependence on external suppliers. The framework yields implications for China’s industrial upgrading and ASEAN’s industrialization prospects. Read More

Abstract: The rapid development of fintech is profoundly transforming the competitive landscape of traditional banking. This study examines how fintech redefines the competitiveness of conventional banks, systematically analyzing its structural impacts across three dimensions: services, products, and channels, proposing pathways for enhancing competitiveness through digital transformation. Research findings reveal that: at the service level, fintech improves efficiency through intelligent customer service and automated processes, replacing traditional offline service models; at the product level, big data and artificial intelligence drive credit approval, risk management, and wealth management toward smarter and more precise operations; at the channel level, the rise of digital platforms and scenario-based financial services has reshaped customer engagement methods, undermining the traffic advantages of physical branches. Building on this, the study conducts an in-depth analysis using China Merchants Bank and CITIC Bank as case studies. China Merchants Bank's "AI First" strategy demonstrates how AI can be fully integrated into banking service systems, risk control frameworks, and operational processes, facilitating a transition from digitalization to intelligentization. CITIC Bank's "Xiaotianyuan" enterprise ecosystem platform exemplifies how banks leverage a "free standard edition & ecosystem integration" model to deeply embed financial services throughout corporate operations, including business management, finance, capital allocation, and taxation, transforming themselves from financial product providers into digital ecosystem infrastructure providers. The research findings indicate that fintech is not a disruptor of traditional banks but rather a catalyst for reshaping their competitiveness; traditional banks should achieve a strategic transformation from "passive response" to "active leadership" through systematic innovation in their service, product, and channel … Read More

Abstract: Against the intelligent manufacturing and new quality productive forces context, generative AI (AIGC) has reconstructed manufacturing R&D, production, quality inspection and supply chain links. Most existing AIGC transformation studies concentrate on well-resourced large listed manufacturers, with scarce quantitative empirical evidence for traditional hardware small and medium enterprises (SMEs) regarding transformation gains and cost pressures. Taking 41 Wenzhou hardware SMEs from 2021 to 2025 as balanced panel samples, this research adopts a two-way fixed-effects DID model to quantify the causal effects of AIGC adoption. Benchmark regressions prove AIGC significantly boosts SME performance: cutting new product R&D cycles by 32.6%, lowering unit manufacturing costs by 18.3% and raising total factor productivity (TFP) by 14%. Such benefits are more pronounced for medium firms with 20-50 million RMB annual revenue and 8-15 years of operation; placebo, variable substitution and parallel trend tests validate result robustness. Cost measurement identifies three key burdens: one-off equipment expenses 11.37% of annual net profit, annual system operation fees (6.99%) and compound talent costs (8.97%). Major transformation obstacles cover industrial AI talent shortages, mismatched universal AIGC models, limited profit margins and inadequate cluster digital ecosystems. Drawing on cost-benefit results, this paper puts forward dual micro-macro solutions: lightweight SaaS AIGC subscriptions for firms, plus tiered subsidies, shared industrial AI platforms and school-enterprise talent training schemes for governments. This research fills the SME AIGC transformation research and supplies actionable empirical references for industrial clusters and local policymakers. Read More

Abstract: This paper investigates the commercialization model of TikTok, tracing its development history, revenue generation mechanisms, and market strategies. Through a module analysis based on the Business Model Canvas, it aims to elucidate its current status, core logic, and future trends, providing theoretical and practical references for the commercialization of short-video platforms. The study reveals that TikTok has established a closed-loop ecosystem of "content–traffic–transaction," with its revenue structure dominated by advertising, rapid growth in e-commerce operations, and live streaming serving as a crucial supplement. Nevertheless, the platform continues to face persistent challenges, including an underdeveloped product governance framework, rising costs of traffic acquisition, and increasing compliance management difficulties. Read More

Abstract: With the rapid development of artificial intelligence (AI) in recent years, the form of cross-border business for companies around the world has changed significantly. Systematically explore how artificial intelligence (AI) technology can be used to help multinational enterprises (MNEs), especially those originating from or expanding in emerging economies, optimise their overseas layout and international development strategy in this study. Based on the resource-based view and the Uppsala model for internationalisation, this paper examines how artificial intelligence addresses the problems of foreignness liability and improves cross-border operating efficiency simultaneously. The proposed integration paths are: AI-driven prediction of market demand, algorithmic localisation of the supply chain, and cross-cultural natural language processing for consumer communication. This paper will also point out institutional and infrastructureal deficiencies that limit the application of AI in the development world. AI-Assisted Strategic Planning can therefore optimise the allocation of foreign direct investment and accelerate the speed of market entry. In short, the above research provides all-encompassing theoretical support for using AI as a leading strategic asset to help enterprises obtain a sustainable competitive advantage and expand dynamically in the era of digitalisation. Read More

Abstract: This paper reviews moral licensing theory by examining its origin, development, core concepts, theoretical models, moderating variables, applications, and future trends. The theory originated in early research on moral psychology. Early studies focused on social discrimination, and later research extended the theory to multiple domains. Its core idea is that prior moral behavior may create a psychological tendency to relax moral constraints in subsequent behavior. This review also discusses the theory's explanatory models, forms of licensing, extended research fields, and future directions, with the aim of deepening understanding of the decision-making mechanisms underlying human moral behavior. Read More

Abstract: Against the backdrop of rapid development in the digital economy, China's e-commerce industry has experienced explosive growth, accompanied by the persistent industry pain point of high return rates. Return rates in fast-moving consumer goods sectors such as apparel and cosmetics are generally high, with some live-streaming e-commerce platforms experiencing return rates exceeding 60%, directly causing industry average annual loss costs to exceed standards and severely constraining the sustainable development of the e-commerce industry. Some e-commerce platforms, in an effort to reduce merchants' return costs, have introduced algorithmic strategies such as "high-refund population shielding," yet these have sparked large-scale algorithmic discrimination controversies due to single metrics and insufficient transparency, both damaging consumers' legitimate rights and undermining market transaction fairness. This paper takes "bidirectional fairness" as its core orientation, focusing on the three-party interest balance of "user-merchant-platform," and constructs a data-driven return merchandise resale optimization system integrating multi-dimensional indicators of "merchandise damage degree-user preference-merchant responsibility ratio." The research employs literature research, empirical analysis, questionnaire surveys, and case analysis methods, based on return records and user behavior data from a major domestic e-commerce platform's apparel category from 2022-2024, to verify the practical effects of the optimization strategies. Results demonstrate that the proposed optimization strategies can effectively reduce algorithmic discrimination complaints in the apparel industry, decrease industry loss costs, and significantly improve the secondary transaction rate of returned merchandise. This research fills the research gap in algorithmic discrimination avoidance in the return merchandise resale field, enriches data-driven reverse logistics management theory, and provides … Read More

Abstract: In the promotion of lean production, workshop sites are frequently plagued by poor operation processes, prominent operator fatigue, and mismatched human-machine coordination. Taking a machinery processing and assembly workshop as the research object, this paper adopts literature review and on-site tracking investigation. Supported with human factors engineering theories including biomechanics, cognitive load and operation motion analysis, hidden human factor defects in the existing operation processes are identified and diagnosed. On this basis, process optimization schemes are designed from the perspectives of motion simplification, workstation layout adjustment, operation task redistribution and auxiliary equipment deployment. After the implementation of optimization schemes, the risk of musculoskeletal injuries is controlled, invalid motions and operation fatigue are alleviated, and operation efficiency and operating comfort are both improved. Read More

Abstract: Driven by the booming development of digital retail, fresh food e-commerce has expanded rapidly in recent years, while its supporting cold chain logistics system still faces prominent operational problems, including unreasonable route planning, high comprehensive distribution costs, excessive product spoilage, and substantial carbon emissions. To address the multi-constraint and multi-objective optimization characteristics of fresh food last-mile distribution, this study constructs a comprehensive cold chain distribution path optimization model that integrates transportation cost, perishable loss cost, hybrid time window penalty cost, and carbon emission cost. On this basis, an improved adaptive genetic algorithm (IAGA) is proposed to solve the established model, which dynamically adjusts crossover and mutation probabilities during iterations and effectively overcomes the premature convergence and local optimal defects of the traditional genetic algorithm (TGA). Numerical simulation and comparative experiments based on real-world fresh e-commerce distribution scenarios are conducted. The results demonstrate that the proposed model and algorithm can significantly reduce total distribution costs, cut carbon emissions, and mitigate time penalty losses, thereby improving the overall operational efficiency and low-carbon sustainability of cold chain distribution systems. This research provides a reliable theoretical reference and practical operational strategy for refined and green path scheduling management of fresh cold chain logistics enterprises. Read More

Abstract: This paper examines the value and realization paths of customer participation in mass customization. From the perspective of production and operations management, it analyzes how customer participation balances individualized product demand and scale requirements through modular design, digital tools, and flexible production systems. The study shows that customer participation should be understood as 'value co-creation under constraints.' Customers participate in part of the production process within a standardized modular framework predefined by the firm. This participation helps firms reduce the cost of demand mismatch, activate momentum for product iteration, and build differentiated competitive advantages. Its realization depends on the coordination of modular production, digital technology, and differentiated supply chains. It also faces challenges such as conflict between customers' willingness and ability to participate and insufficient efficiency in enterprise value conversion. The paper ultimately emphasizes the need to optimize production system design and supply chain coordination in order to improve the efficiency of value conversion. Read More

Abstract: With the continuous deepening of global economic integration and the rapid growth of cross-border trade volume, international cross-border logistics systems have become increasingly complex and vulnerable to external uncertain shocks. Multiple risk factors including regional geopolitical fluctuations, international freight market instability, trade policy adjustments and global public health emergencies have significantly increased the operational risks of cross-border logistics activities. Clarifying the developmental evolution, research hotspots and existing deficiencies of global cross-border logistics risk research is crucial for optimizing international logistics layout and enhancing global supply chain stability. Based on the standard PRISMA systematic review framework, this study collects 218 high-quality academic papers focusing on global cross-border logistics risks from Web of Science and Scopus databases covering the period from 2015 to 2025. Through bibliometric statistical analysis and in-depth thematic content sorting, this paper systematically analyzes the annual publication trends, keyword hotspot distribution and core research dimensions in this field. Statistical results show that the overall publication volume of cross-border logistics risk research has increased by 187% in the past decade. The research focus has gradually shifted from traditional single economic cost risk assessment to multi-dimensional comprehensive research covering geopolitical shock, digital risk prevention and supply chain resilience enhancement. This paper systematically summarizes four core research categories of cross-border logistics risks, analyzes existing research limitations such as insufficient discussion on emerging market logistics risks and lack of dynamic early warning mechanism research, and puts forward targeted future research directions. The research outcomes can provide solid theoretical support for global logistics risk management and operational … Read More

Abstract: The Belt and Road Initiative (BRI), launched in 2013, has become a defining framework for China-ASEAN economic cooperation, reshaping regional investment patterns through large-scale infrastructure development, trade facilitation, and financial integration. This paper examines the multidimensional impact of BRI on ASEAN’s investment environment across four mechanisms: infrastructure connectivity, trade and investment facilitation, industrial park agglomeration, and financial support. Drawing on official trade and investment data from 2013 to 2025, the study employs a combination of descriptive statistical analysis and in-depth case studies of three landmark projects—the China-Laos Railway, the Jakarta-Bandung High-Speed Railway, and the Thai-Chinese Rayong Industrial Park—to identify the specific channels through which BRI influences host-country investment attractiveness. The findings reveal that BRI infrastructure projects generate substantial investment multiplier effects, reducing logistics costs by 30%-40% along key corridors and catalyzing follow-on industrial investment. Industrial parks established under the BRI framework create agglomeration economies that lower entry barriers for foreign investors, while complementary financial mechanisms, including the Asian Infrastructure Investment Bank (AIIB) and expanded RMB settlement networks, address long-standing financing gaps in the region. The comparative case analysis further demonstrates that BRI’s impact follows differentiated pathways depending on host countries’ development levels: transport connectivity as a catalyst for least-developed economies, technology demonstration effects for emerging industrial nations, and industrial park deepening for institutionally mature markets. The paper concludes with policy recommendations for enhancing the quality and sustainability of BRI-driven investment in ASEAN. Read More

Abstract: In this era of deep integration between globalisation and digitalisation, the digital wave is sweeping across the globe at an unprecedented pace. The synergistic deepening of digital industrialisation, industrial digitalisation, digital governance and data valorisation is profoundly reshaping the division of labour within global value chains. Against this backdrop, this study utilises observational data on Chinese listed companies on the Shanghai and Shenzhen A-share markets from 2012 to 2023 to construct a three-dimensional mediating transmission pathway framework, systematically investigating the impact effects and transmission pathways of digital transformation on corporate export competitiveness. Empirical findings indicate that digital transformation can significantly enhance firms’ export competitiveness, and that it does so through the interplay of three dimensions: resource allocation, production operations and governance levels; simultaneously, this promotional effect exhibits marked heterogeneity in terms of property rights, production factors and geographical location. Read More

Abstract: Employment is the foundation of people’s livelihood and a crucial driver of economic growth. Against the backdrop of intensified economic downturn and deep integration of digital technologies, private enterprises, as the "main force" supporting over 80% of urban employment, face a pivotal challenge: whether their digital transformation can solidify the "employment reservoir." Based on data from China’s A-share listed companies between 2013 and 2023, this study empirically examines the impact of digital transformation on employment scale in private enterprises and its underlying mechanisms.  The findings reveal that digital transformation expands employment scale in private enterprises, with this effect being more pronounced in firms with higher education levels, mid-to-high-skilled labor, and those located in larger cities. Mechanism analysis demonstrates that digital transformation drives employment expansion by broadening business scale and enhancing productivity. Specifically, digital technologies extend market boundaries and business complexity, leading to increased demand for various types of labor. Simultaneously, efficiency gains from technological applications also structurally facilitate the reallocation of labor resources, thereby driving overall employment growth.  The research conclusions provide empirical evidence for comprehensively assessing the actual impact of digital transformation on employment markets in China’s private enterprises. They also offer policy insights into balancing employment stability and labor structure optimization while advancing the development of the digital economy. Read More

Abstract: Against the backdrop of deepening economic globalization and regional integration, the Asian financial crisis and global financial turbulence have highlighted the need to build a regional financial safety net. As the core economic blocs of East Asia, China and ASEAN's currency swap cooperation has become a key institutional arrangement for responding to external shocks and maintaining regional financial stability. This article focuses on the current state of the China-ASEAN currency swap mechanism, its role in regional financial stability, and the existing challenges, exploring how it can enhance regional financial resilience through institutional design and practical innovation. This study aims to provide theoretical reference for improving China-ASEAN financial cooperation and practical insights for emerging market countries to build an independent and controllable regional financial system. It also has theoretical value for promoting the diversification of the global financial governance system and enhancing the financial voice of developing countries. Read More