All of the articles in this proceedings volume have been presented at the 2026 5th International Conference on Mathematical Statistics and Economic Analysis (MSEA 2026) during July 17-19, 2026 in Guiyang, China. These articles have been peer reviewed by the members of the Scientific Committees and reviewers...

With the explosive growth of medical data and the rapid development of AI technology, medical diagnosis is transforming from traditional experience-driven to data-driven, and a single machine learning model is often difficult to meet the clinical requirements in medical diagnosis due to problems such...

This study investigates BYD’s entry into Thailand’s electric vehicle (EV) market through quantitative and qualitative analysis, focusing on market demand, competitive dynamics, and strategic decision-making. Findings reveal that Thailand’s EV market is driven by government policies (e.g., the “EV 3.5...

With the deepening of reform and opening-up, China’s domestic economy has evolved into an extraordinarily complex and diverse landscape, where social issues stemming from rat-race competition have become particularly pronounced. This paper utilizes questionnaire data from Chinese A-share listed companies...

With the rapid development of the logistics industry and the continuous expansion of the scale of airports, the airport economy, as an emerging industrial development mode different from the economy centered on the airport and the aviation economy, is playing a crucial role in the economic development...

High-dimensional portfolio optimization ( N ≈ T ) inherently suffers from ill-conditioned covariance estimates, causing unstable weights and excessive transaction costs. This paper proposes a dynamic...

Adult obesity has been extensively studied in economics and public health, yet the empirical role of ambient climate conditions remains underexplored. This paper examines the relationship between average ambient temperature and adult obesity using U.S. county-level panel data from 2006 to 2018. Using...

Collective motion is a phenomenon widely observed in biological systems and engineering multi-agent networks, where a large number of individuals achieve coordinated movement through dispersed local interactions. Typical examples include flocks of birds, schools of fish, and swarms of robots. Although...

The rapid integration of artificial intelligence and information technology has transformed the feasibility of cross-regional remote work. Yet, as these mobile professionals migrate, they inevitably precipitate competition over local social resources that are strictly bound by capacity limits. To capture...

In the context of global financial digital transformation and evolving cross-border financial risk patterns, research on the digital financial risk transmission mechanism and systematic governance framework has become a key focus. Using bibliometric analysis and systematic evaluation, this paper selects...

This study integrated explainable machine learning with econometrics to analyze economic drivers of China–U.S. mobile communication device exports. A SHAP-based Random Forest approach with both time-series and resampling robust validation was employed to assess variable quality. Furthermore, dependent...

This paper utilizes data from China A-share listed companies from 2010 to 2024 and employs the difference-in-differences method to analyze the impact of green finance pilot zone policies on corporate green innovation, exploring whether they promote substantive innovation or trigger strategic innovation....

This paper investigates the causal relationship between logistics efficiency and export structure upgrading. Using a panel dataset of 31 Chinese mainland provinces from 2011 to 2023 with 403 valid observations, we construct a comprehensive logistics efficiency index (EFFI) and an export structure upgrading...

Audit quality significantly improves TFP of Chinese A-share firms by optimizing resource allocation. Financing constraints weaken this effect, while digital transformation strengthens it, highlighting the need to enhance auditing, digitalization, and financing conditions.

With the widespread application of artificial intelligence (AI) technology in the recruitment sector, AI interviews have emerged as a crucial tool for organizations to screen job candidates. However, there are significant individual differences in candidates’ acceptance of AI interviews; notably, a subset...

This study employs statistical methods including geographical concentration, industrial deviation degree, factor analysis, grey correlation analysis, and coupling coordination degree model to construct a comprehensive system of population structure and economic development. It investigates the coordination...

Using Chinese A-share listed companies from 2016 to 2024 as the research sample, this study examines the effect of optimism bias in earnings forecasts on earnings management and its transmission mechanism from the perspective of managerial overconfidence. Because the conventional optimistic earnings...

The reduction of carbon dioxide emissions is receiving increasingly more attention from the international community. Nevertheless, what are the primary factors that impact carbon dioxide emissions? How to curb carbon dioxide emissions without blocking economic development? Based on a panel data of China...

With the deepening of power market reforms, the participation of new market entities such as virtual power plants and load aggregators in multi-market transactions has become a significant trend. This paper establishes a bidding model for aggregators based on multi-market coordination, coordinating and...

Using data on China’s state-owned A-share listed firms from 2013 to 2023, this study examines how AI penetration affects innovation performance. A two-way fixed-effects model is employed, with invention patent applications as the dependent variable and AI word frequency (via Python text recognition)...

Taking 12 provinces in western China as research objects, this paper constructs a regional innovation ecosystem index using the DP2 method based on 2014–2023 panel data. It integrates hierarchical standard deviational ellipses, exploratory spatial data analysis, K-Means optimized nested Theil decomposition,...

During expressway reconstruction and expansion, in-situ bridge reconstruction requires existing decks and piers to be demolished and new decks to be erected while traffic is kept open. To assess the resulting traffic safety risks, this study proposes an integrated method combining D-S evidence theory...

Technological progress has become a core driver of high-quality corporate development for China’s pursuit of common prosperity, yet intra-firm income distribution inequality has become increasingly prominent. This paper empirically examines the impact of technological advancement on intra-firm income...

Detecting financial misreporting is a multi-trillion-dollar problem and a notorious failure mode of off-the-shelf machine learning: modern deep models reach striking in-sample accuracy yet collapse under regulatory regime shifts and adversarial managerial adaptation. We argue that this brittleness reflects...

This study examines how institutional investors’ simultaneous debt and equity positions shape corporate tax avoidance. Because dual holders share in both equity-side tax benefits and debt-side downside risk, they may alter firms’ tax planning incentives. Using U.S. public firms from 1990 to 2010, we...

In February 2014, China’s Ministry of Finance revised and issued the Accounting Standards for Business Enterprises No. 33—Consolidated Financial Statements (CAS 33), which aligns substantially with IFRS 10. The implementation of this new accounting standard and its role in regulating consolidated financial...

Driven by new power system construction and digital upgrade, AI reshapes post setup of power supply enterprises[1,2]. Based on technology disruption and human-machine collaboration theories[3,4], this paper builds a four-dimension (technology maturity, business adaptability, safety constraint, organizational...

This paper establishes a five-dimensional evaluation system for integrated flexible teams to adapt to cross-specialty operation of integrated energy distribution networks. Combining AHP and Entropy Weight-TOPSIS, we quantitatively assess 12 practical teams and adopt a constraint coefficient to analyze...

Quantitative analysis of the exhibition (MICE) economy lies between black-box forecasters that ignore policy and causal toolkits that ill-handle networked, text-rich data. We propose ExpoCast, delivering counterfactual demand forecasting and subsidy evaluation from one estimator: a heterogeneous spatio-temporal...

Artificial Intelligence (AI) digital transformation puts forward higher requirements for digital literacy of skilled talents in power enterprises. Aiming at the defects of imperfect indicator framework and excessive subjectivity in existing evaluation works, this paper adopts two-round Delphi method,...

AI reconstruction of grid business processes optimizes stock human resource allocation, yet existing evaluation lacks multi-dimensional quantitative frameworks combining intelligent efficiency and talent transformation. This paper constructs a five-dimensional index system via two-round Delphi screening,...

Digital transformation reshapes grid frontline labor, while single-index evaluation fails to measure staff contributions under digital labor value accounting. This paper builds a multi-dimensional index system through Delphi, AHP-entropy weighting and optimized TOPSIS for quantitative assessment. Based...

Due to the ability to faithfully reconstruct real-world 3D scenes, point cloud data are widely used in fields such as digital twins and scene understanding. However, manual annotation of large-scale point clouds is inefficient, whereas point-cloud semantic segmentation technology can extract the geometric...

Small and medium-sized enterprise (SME) credit risk assessment is an essential challenge for financial institutions because SME borrowers are characterized by high economic relevance, information opacity, diverse operating histories, and sensitivity to loan terms. This study presents an empirical comparison...

Drawing on Upper Echelons Theory and Emergence Theory, this study examines how TMT heterogeneity—in age, education, and professional background—affects ESG performance in Chinese A-share manufacturing listed firms (2013–2023), and tests the mediating role of strategic choice. Results show that overall...