Journal of World Economy

Application of Functional Regression Model on OADR-YADR Relation: The Case of Greece

Goran Miladinov — 2025-12-30

In the social security system and healthcare system, the process of demographic aging is of major interest. The current research work provides a statistical method based on functional time series regression analysis to improve old-age dependency ratio modeling for the Greek population. The functional time series regression-based model was applied to the old-age dependency ratio and young-age dependency ratio of the Greek population over the years from 1980 to 2023. The estimation of the functional regression model was used to model the relationship between the two age dependency ratios. Therefore, the functional regression model was used to measure the impact of the functional coefficient on young–age dependency ratio and old-age dependency ratio differences. The research findings revealed a varying functional-coefficient with a strong negative function of young-age dependency of the Greek population over the last years. The results confirm a broader usage of the functional regression models to provide more accurate estimates in demography, public health, and age-related policy studies.

Toward Regulatory Compliance in DAO Governance: From Regulatory Rule Engines to On-Chain Audit Report Generation

Allen Lin — 2025-12-30

Decentralized Autonomous Organizations (DAOs) face inherent institutional conflicts between their decentralized governance structures, tokenized incentive mechanisms, and rigid global regulatory frameworks—with the U.S. regulatory landscape (SEC, OFAC, FinCEN) emerging as the most stringent and impactful. In 2024, 7 U.S.-based DAOs were subject to SEC investigations (aggregate penalties of $12.8 million), 18% incurred FinCEN sanctions for OFAC-sanctioned address interactions, and 68% of Base chain DAOs were denied institutional capital due to inadequate compliance documentation. Grounded in institutional economics (regulatory adaptation theory), RegTech principles, and blockchain traceability, this study proposes a “three-dimensional compliance adaptation framework” for DAO governance—integrating a regulatory rule engine (quantitative alignment with U.S. rules), automated on-chain audit report generation (transparency assurance), and dynamic governance optimization (securities risk mitigation). Drawing on the development of the “DAO Shield Pro” system and empirical testing across 7 representative U.S. Base chain DAOs (3 AI-focused, 2 meme-based, 2 investment-focused) over a 6-month period (March–August 2025), the framework achieves: (1) a 67.9% reduction in average compliance risk scores (from 3.8 to 0.98), (2) a 45.6-percentage-point increase in U.S. institutional investor participation (from 7.8% to 53.4%), (3) a 100% SEC regulatory inquiry acceptance rate, and (4) a 64.2% reduction in monthly compliance labor costs (from $19,200 to $6,870). This research fills critical gaps in DAO compliance scholarship by providing a theoretically rigorous, technically actionable, and empirically validated solution tailored to U.S. regulatory requirements (SEC Howey Test, OFAC sanctions screening, PCAOB auditing standards). It advances the field by quantifying ambiguous regulatory rules into executable on-chain logic and delivers a replicable paradigm for global DAO regulatory adaptation—strengthening U.S. competitiveness in the Web3 ecosystem and unlocking an estimated $42–$58 billion in latent institutional investment.

“Industry Cognition + Capital” Dual-Driven Model: Innovation in Composite Equity Investment

Zhile Tan — 2025-12-30

This paper focuses on the core demand of the equity investment industry to transition from “capital-driven” to a collaborative model of “industry + capital.” Addressing the pain points of traditional equity investment, such as information asymmetry, weak post-investment empowerment, and singular exit paths due to an overemphasis on capital, this study employs value chain theory and collaborative innovation theory to systematically define the core connotations of “industry cognition” (including track selection, enterprise identification, and post-investment empowerment) and “capital” (including capital allocation, post-investment services, and exit design). It constructs a dual-driven mechanism throughout the “decision – post-investment – exit” process and supports it with organizational structures (Industry Research Center, Post-Investment Empowerment Department) and institutional safeguards (collaborative decision-making, interest alignment). Through literature review, case analysis (Hillhouse Capital’s hard technology “industry merger and acquisition” model and Sequoia China’s consumer “ecologized capital” model), and comparative analysis, the practical value of the dual-driven model is verified.

The Design and Practical Path of Cross-Border Traceability System for Medicinal and Chemical Products — A Multi-Dimensional Empirical Study Based on Blockchain and Internet of Things

Die Wang — 2025-12-30

In the cross-border trade of medicinal and chemical intermediates, industry pain points such as information silos leading to traceability disruption, low credibility of quality control data, and poor regulatory coordination efficiency are prevalent, with small and medium-sized trading enterprises being particularly affected. This study takes norfloxacin and cefotaxime active ester as typical research objects, integrating the tamper-proof characteristics of blockchain with the real-time perception technology of the Internet of Things (IoT) to construct a lightweight cross-border traceability system covering the entire chain from production to storage, logistics, customs clearance, and terminal use. The system is based on a “three-layer, nine-module” structure. An empirical test was conducted using the trade data of Wuhan Kuda Hui Trading Co., Ltd. from 2022 to 2024. The results indicate that the system can increase the completeness of traceability information to 99.2%, raise the customs clearance rate in the EU to 96%, shorten the quality control abnormal response time to 2.5 hours, and reduce the cross-border delivery cycle to 28 days. Additionally, the “three-stage promotion” low-cost practical path designed for small and medium-sized trading enterprises ensures feasibility and cost controllability, with strong replicability. The study provides a quantifiable and implementable technical solution and practical paradigm for cross-border traceability of medicinal and chemical products, effectively solving the core industry pain points.

Next-Generation Financial Transaction Informatization: From “Tool Empowerment” to “Intelligent Decision-Making”

Jun Xin — 2025-12-30

The global financial transaction informatization is currently at a critical transition period towards “intelligent decision-making,” with “data silos,” “capability disconnections,” and “path ambiguity” forming the core bottlenecks of the industry. A 2023 survey of global asset management institutions revealed that only 23% of the institutions have completed the transformation to intelligent decision-making, while the rest remain at the basic tool automation stage. This study employs a mixed research design of analytic hierarchy process (AHP), entropy weight method, event study method, and panel data regression to construct a three-dimensional dynamic evolution model of “technology maturity-business integration-decision-making contribution.” It delineates a four-stage evolution path and quantifies the characteristics, revealing the catalytic effect of dual-domain capability integration and defining the critical threshold for intelligent decision-making dominance. The findings indicate that dual-domain integration can shorten the informatization upgrade cycle by 38%; “data sharing rate ≥80%, AI model out-of-sample accuracy ≥85%, and cross-departmental collaboration efficiency ≥75%” are the necessary conditions for transitioning from “intelligent assistance” to “decision-making dominance.” This study fills the academic gap in “dual-domain collaborative evolution,” providing a quantifiable practical guide for the digital transformation of financial institutions, with both theoretical and practical significance.

Cross-Border E-Commerce TikTok Live Streaming Data Three-Dimensional Optimization Model Construction and Empirical Study — Based on Singaporean Technology Product Markets and Scenario Migration to U.S. Warehousing Services

Yiyang Wu — 2026-01-19

In zero-paid-traffic scenarios, TikTok technology live streams typically face a systemic dilemma characterized by scarce traffic entry points, inadequate audience retention, and depressed average order values. Extant research predominantly focuses on low-involvement product categories and paid growth strategies, leaving a theoretical gap in systematic investigation of organic growth mechanisms for high-involvement technology products. Grounded in attention economy theory and collaborative optimization theory, this study employs 42 live streams featuring 15 technology products from Tesen Global Technology in Singapore as a natural experiment. We construct a three-dimensional collaborative optimization model encompassing “time slots—scripts—product mix” and implement real-time attention allocation via online gradient descent algorithms, while dynamically iterating product combinations through Thompson Sampling. Validation using 73-day panel data demonstrates that post-intervention, organic follower growth increased by 208%, conversion rates rose by 125%, average order value climbed by 20.5%, and cumulative advertising expenditure savings reached $12,000; 5,000 randomization permutation tests confirm robust effects (p<0.01). Furthermore, applying service marketing theory, we migrate the model to the U.S. small-to-medium warehousing sector, proposing an “inventory turnover rate visualization live stream + service package matrix” approach, which is projected to reduce customer-per-lead costs (CPL) from $180 to $90. This research establishes a multi-dimensional collaborative optimization framework for live streaming, filling theoretical voids regarding high-involvement product growth in zero-ad-spend contexts and providing a replicable methodological paradigm for organic cross-border e-commerce expansion.

The Path to Enhancing Corporate Inventory Turnover Efficiency Through Seamless Integration of ERP and WMS

Yanmin Qiu — 2026-01-19

Targeting the core pain points of slow inventory turnover in the fast-moving consumer goods (FMCG) industry, such as “data fragmentation, process disconnection, and cost-efficiency imbalance” in the integration of ERP and WMS, this paper constructs a three-tier enhancement model of “data integration – process reengineering – intelligent optimization.” It systematically reveals the internal transmission mechanism of “data granularity – process collaboration – inventory turnover rate.” Based on panel data from 15 FMCG companies with annual revenues of ≥5 billion yuan, an empirical comparison is conducted among the control group (traditional batch processing integration), experimental group 1 (only data integration), and experimental group 2 (full three-tier model). The study quantifies the efficiency differences and cost boundaries of different integration modes. The findings indicate that the three-tier model can reduce inventory turnover days from 45 days to 32 days (a relative improvement of 29%), lower the stockout rate to 3.2%, and decrease system maintenance costs by 38% compared to the “real-time synchronization” solution. The transmission coefficient of “data – process – efficiency” reaches 0.63 (p<0.001), and the optimal data synchronization frequency for the FMCG industry is 4 times per day (with a system load rate ≤60%) (Qi, Z., 2025). Case studies of Unilever and Nestlé Wyeth verify the practical effectiveness of the model and correct the traditional perception that “real-time integration is necessarily the best.” This paper provides a quantifiable and implementable path for the digital collaboration of supply chains in FMCG companies and enriches the theoretical system in the field of supply chain management and system integration.

Data-Driven Decision-Making Model for Overseas Market Growth of U.S. Enterprises in the Digital Economy Era: Theoretical Construction and Empirical Research

Chunzi Wang — 2026-01-19

The global digital economy reached a scale of 55.3 trillion US dollars in 2024, accounting for 47.6% of the global GDP. The proportion of overseas revenue of U.S. enterprises has been continuously increasing, with the average for S&P 500 enterprises reaching 38.2% in 2023. Data has become a core production input for enterprises’ overseas expansion. This study aims to construct a data-driven decision-making model for the overseas market growth of U.S. enterprises in the digital economy context, and to reveal the inherent relationship between data resources, analytical capabilities, and growth performance. A mixed research method is adopted, including panel data regression, structural equation modeling, and multiple case studies. The core innovation lies in constructing a full-chain theoretical model of “data resources – data capabilities – decision-making efficiency – growth performance” and quantifying the contribution coefficient of data-driven approaches. This research enriches the international business theory system and provides a quantifiable decision-making framework for U.S. enterprises in formulating overseas strategies.

Sustainability Optimization in North American Cross-Border Logistics Networks

Xiaoying Nie — 2026-01-19

Given that North American cross-border logistics account for 7.3% of global carbon emissions and enterprises are confronted with the practical dilemma of “high decarbonization costs,” coupled with the existing research focusing predominantly on single transportation modes and the failure to internalize carbon costs, this study embarks on a novel approach by internalizing carbon costs. It constructs a carbon footprint-sensitive multimodal transportation path algorithm. Leveraging 1.5 million freight waybills data from five core cross-border corridors in North America (two U.S.-Canada and three U.S.-Mexico) between 2021 and 2023, this study calculates the unit carbon emission coefficients for dry goods, cold chain, and hazardous materials under maritime, rail, and road transportation modes. A cost-carbon balanced optimization model is established with dual objectives of minimizing comprehensive costs and carbon emissions. The empirical case analysis of electronic components transportation across the U.S.-Mexico border at El Paso-Juarez reveals that the optimized path combining maritime and rail transportation, compared with the traditional road-dominated path, can achieve a 40.6% reduction in carbon emissions (monthly carbon emissions decreased from 1,280tCO₂ to 760tCO₂), with a net cost increase of only 3.2%. When the carbon price rises to USD 100 per ton of CO₂, the model automatically increases the proportion of rail transportation to 65%, achieving a decarbonization rate of 58%. The study confirms that internalizing carbon costs can effectively balance the economic efficiency and environmental decarbonization goals of North American cross-border logistics. The substitution of some road transportation by maritime and rail transportation is identified as the core path for regional logistics decarbonization. The large-scale promotion of this path across the top ten cross-border corridors in North America has an annual decarbonization potential of 1.42 million tons of CO₂.

Technological Convergence of the Economies of the USA, China, Russia, India and Japan in the Core 5 Format

Evgeniy Bryndin — 2026-01-22

The technological convergence of the economies of the United States, China, Russia, India, and Japan within the Core 5 framework is a complex and multifaceted process, encompassing technology exchange, joint innovation projects, digital integration, and infrastructure development. The key aspects of technological convergence are, first, global supply chains and technological integration; second, joint research projects; third, the development of digital platforms and infrastructure; and fourth, regulatory and strategic initiatives. The United States and Japan are involved in international supply chains for high-tech components such as semiconductors, software, and electronics. Russia is pursuing integration in space and nuclear energy. Through international programs and initiatives, the countries are collaborating in artificial intelligence, quantum technologies, energy-efficient solutions, and cybersecurity. For example, joint research centers and university projects facilitate the exchange of knowledge and technology. Countries are investing in the creation of national digital platforms, cloud services, and 6G/7G infrastructure, facilitating interregional integration. Governments are taking measures to stimulate innovation and the development of technology sectors. Technological convergence between the United States, China, Russia, India, and Japan continues to develop, amidst both cooperation and competition. A significant trend is the growing desire in the technology sector to develop new forms of international cooperation, which is impacting the global technology landscape and the economic stability of these countries.

Research on the Protection Path of Minority Shareholders’ Rights and Interests Under the Mandatory Delisting System

Min Yang — 2026-01-26

With the continuous development of the capital market, the mandatory delisting system has become an important means to maintain market health. Since the implementation of the Opinions on Strictly Implementing the Delisting System, the number of listed enterprises subject to mandatory delisting has increased sharply, significantly enhancing the market’s capacity for clearing out inefficient entities. However, the issue of minority shareholders’ rights and interests being impaired during the delisting process has become increasingly prominent, making the protection of these rights a major social concern. Taking the mandatory delisting case of Guanghui Automotive, whose stock closed below 1 yuan for 20 consecutive trading days, as the research object, this paper explores the internal and external causes of the company’s mandatory delisting against the backdrop of the current delisting system. It further analyzes the root causes of the infringement on minority shareholders’ rights and interests, and proposes targeted counter-measures including improving the information disclosure system, strengthening accounting supervision, implementing compensation mechanisms, perfecting the representative litigation system, and enhancing investor education. This study aims to provide theoretical support and practical reference for protecting minority shareholders’ rights and interests under the capital market delisting system, and promote the construction of a more fair, transparent, and efficient capital market environment.