GAITDI 2026/The ACM ICPS Conference Proceeding View all insights
The Role of Machine Learning in Reducing Healthcare Costs: The Impact of Medication Adherence and Preventive Care on Hospitalization Expenses
This study reveals the important role of prevention care and medication adherence in reducing hospitalizations. By using a structured dataset of 1,171 patients, four machine learning models Logistic Regression, Gradient Boosting, Random Forest, and Artificial Neural Networks are applied to predict five-year hospitalization risk, with the Gradient Boosting model achieving the highest accuracy of 81.2%. The result demonstrated that patients with high medication adherence and consistent preventive care can reduce 38.3% and 37.7% in hospitalization risk. The finding also suggests that targeted preventive care can have positive Return on Investment (ROI), and therefore ML models can effectively direct personalized interventions and contribute to long-term medical savings.
Copyright (c) 2026 Yixin Zhang, Yisong Chen (Author) https://creativecommons.org/licenses/by/4.0
The Impact of Data Assets on the Growth of Information and Communication Enterprises
In the era of the digital economy, the progress and expansion of enterprises are intricately tied to the effective management and utilization of their data assets. However, there has been a notable lack of research directly investigating the influence of data assets on enterprise growth. This paper aims to address this research gap by developing a theoretical framework that correlates data assets with the growth of information and communication enterprises. By analyzing empirical data sourced from Shanghai and Shenzhen A-share listed information and communication enterprises spanning from 2010 to 2023, the study demonstrates that data assets play a significant role in promoting the growth of these enterprises. Sub-sample regression shows that, compared with computer, communication and other electronic equipment manufacturing enterprises, data assets play a more obvious role in promoting the growth of information transmission, software and information technology service enterprises. The conclusion provide empirical evidence and important enlightenment for information and communication enterprises to achieve sustainable growth.
Copyright (c) 2026 Li Zhou, Shaoxin Xiang, Yexin Tian (Author) https://creativecommons.org/licenses/by/4.0
Research on the Impact of China's Low Carbon City Pilot on High-Quality Economic Development Based on the Difference-in-Differences Model
This paper takes China’s low-carbon city pilot as a quasi-natural experiment and constructs a multi-period difference-in-differences model to comprehensively evaluate the impact of the low-carbon city pilot on the high-quality development of urban economy. The study finds that the low-carbon city pilot has significantly promoted the high-quality development of urban economy. Further research finds that adjusting and optimizing industrial structure and encouraging green technological innovation are important mechanisms by which the low-carbon city pilot promotes the high-quality development of urban economy.
Copyright (c) 2026 Yong Jiang, Xia Wang, Yunhan Wang (Author) https://creativecommons.org/licenses/by/4.0
Research on Artificial Intelligence Technology Trust of University Teachers
With the deep integration of artificial intelligence (AI) technology in education, university faculty’s trust in AI directly influences their adoption willingness and teaching effectiveness. This study employs a questionnaire survey method to collect 200 samples, systematically examining the current state of AI trust among university teachers through the framework of Technology Trust Theory. Descriptive statistical analysis reveals that teachers’ overall trust in AI technology remains moderate. T-test analysis identifies gender based differences in technical trust, while one-way ANOVA furthe demonstrates variations across age, educational background, academic rank, discipline, institution type, and teaching experience. Notably, teachers’ educational qualifications and institutional types significantly impact their AI trust levels.
Copyright (c) 2026 Yingying Nie, Yankun Cui, Shanshan Lou (Author) https://creativecommons.org/licenses/by/4.0
Research on the coupling and coordinated development of new quality productivity and carbon emission efficiency and influencing factors
It is of great significance for China to study the internal relationship and coordination level between new productivity and carbon emission efficiency. Based on the panel data of 30 provinces and cities in China from 2014 to 2022, this paper measures the level of new productivity, carbon emission efficiency and their coupling coordination, and studies the main factors with the help of xgboost and shap model. The results show that the coupling coordination level of China is on the rise, and the coupling coordination level of the eastern region is much higher than that of the central and western regions; Per capita disposable GDP. The first three factors are promotion and the last two are inhibition. With the increase of disposable income, urban employment has changed from negative adjustment to positive adjustment, and the length of optical cable has a positive adjustment effect on GDP.
Copyright (c) 2026 Xinze Wei, Shuyao Wu, Ya Wu, Xingyi Wang, Ruoqing Ni (Author) https://creativecommons.org/licenses/by/4.0
Optimization of Cost Control Based on the Value Chain in the Context of Digital Transformation—A Case Study of Zhengzhou Coal Mining Machinery Group
The ”14th Five-Year Plan” for the national economic and social development of China proposes to guide enterprises in strengthening digital thinking and accelerating digital transformation, aiming to enhance operational efficiency and supply chain collaboration through data-driven approaches. Traditional manufacturing is a major engine of economic growth, with its value chain spanning the entire product lifecycle. However, due to outdated production methods, imperfect supply chains, and poor industry cluster collaboration, the value chain of China’s traditional manufacturing faces such as inefficiency, weak cost control, and inadequate supply chain collaboration. From the perspective of the value chain, achieving cost reduction and efficiency improvement through digital transformation is highly valuable. This article explores the impact paths and effects of digital transformation on cost control from the perspectives of internal and external value chains, including R&D, production, sales, and both supply and client ends, providing experience references for cost control-oriented digital transformation for enterprises in the same industry.
Copyright (c) 2026 Xiaolin Dong, Yuyang Zhang, Ying Ma (Author) https://creativecommons.org/licenses/by/4.0
The Mutual Compensatory Effect of Artificial Intelligence Development and Labor Structure Changes
The rise of artificial intelligence has brought a wide and far-reaching impact on the economy and society. This paper uses the industrial robot data of 13 APEC countries released by IFR and uses the instrumental variable method to empirically test the mutually constructed compensation effect of labor structure changes and artificial intelligence development. Based on previous literature research on artificial intelligence, this paper explores the decline in population growth rate and aging intensified aging included in population structure changes, and comprehensively studies its promotion effect on artificial intelligence, and examines whether the development of artificial intelligence can have a compensatory effect on the social economy and obtain the ”intelligent dividend” when the ”demographic dividend” fades.
Copyright (c) 2026 Min Chen, Yinghui Xiao, Liangrui Zhang, Lu Guo (Author) https://creativecommons.org/licenses/by/4.0
The Impact of China's New Environmental Protection Law on Firm-Level Capital Expenditure
This study seeks to analyze the impact of the new Environmental Protection Law (EPL) on corporate expenditures in China. Using the Chinese A-share listed firm from 2012-2019, we find that the application of the EPL had a significant adverse effect on enterprises’ expenditures. Private enterprises showed that the impact of the EPL on investment in fixed assets and other long-term assets was not significant in the first phase of the law’s implementation, but after the implementation of the law, the enterprises significantly reduced their capital expenditures (Capex.). Whether it is a public or private labor-intensive or non-labor-intensive enterprise, the expenditure is adversely affected, both before and after the Environmental Protection Law’s enactment. The panel data analysis and multivariate regression and PSM-DID method are used to verify our results, and the robustness of the conclusion is proven.
Copyright (c) 2026 Ying Liu, Wenzheng Chen, Chengyang Nie (Author) https://creativecommons.org/licenses/by/4.0
The impact and effect evaluation of digital transformation on cost control from the perspective of value chain
The 14th Five-Year Plan clearly points out that to guide enterprises to promote digital transformation, as an important engine of China’s economic growth, the value chain of traditional manufacturing industry is a key link throughout the whole process of product manufacturing. Due to the backward production methods of traditional manufacturing industry, its value chain leads to low efficiency and poor cost control effect, so it is urgent to reduce costs and increase efficiency from the perspective of enterprise value chain. Taking Zhengzhou Coal Machinery as an example, this paper studies the impact and effect evaluation of digital transformation on cost control from the perspective of value chain, aiming at providing cost-control-oriented digital transformation experience for enterprises in the same industry.
Copyright (c) 2026 Siyu Zhang, Yiming Yang, Yuan Wang, Ying Ma (Author) https://creativecommons.org/licenses/by/4.0
Research on the impact of green fiscal on carbon emissions based on the fixed effect model with panel data
Green fiscal policy tools are an important innovation in the modern fiscal system. A series of fiscal policies to promote green governance have been introduced one after another, which is of great significance to achieving carbon emission reduction. Based on this, this study uses 29 provinces in China from 2007 to 2021 as data samples, constructs a green fiscal indicator system, studies the mechanism of green fiscal on carbon emission reduction, and conducts heterogeneity analysis. Research shows that green fiscal significantly reduces carbon emission levels, and this result still holds after robustness testing; in the mechanism analysis, green fiscal can significantly improve energy efficiency, and the Sobel test shows that energy efficiency has a mediating effect on green fiscal carbon emission reduction; in the heterogeneity analysis, the carbon emission reduction effect of green fiscal is more significant in the central and western regions. Finally, corresponding policy recommendations are put forward to help reduce carbon emissions.
Copyright (c) 2026 Guiping Chen, Jinyi Wu, Shiyu Wang (Author) https://creativecommons.org/licenses/by/4.0
The Generative AI Revolution in Finance: Foundational Logic, Emerging Risks, and Governance Paths
Generative artificial intelligence is a powerful engine of new quality productivity and now is profoundly changing the service models and value creation logic of the financial industry. This article believes that the empowerment of GenAI to financial industry is mainly since there is a large data foundation in the industry, while GenAI can be handier when facing complex data. The technique upgrade and application of GenAI make breakthroughs in solving problems caused by information asymmetry in the traditional financial market, especially for risk management and control. But every coin has two sides, while the banking industry enjoys the convenience brought by AI, it cannot ignore data leakage, black box dilemma caused by AI algorithms, and the systemic risks brought by model instability. Therefore, based on the study of the underlying logic and emerging risks of GenAI empowering the financial industry, this article proposes the governance paths to better play the positive role of AI in financial industry.
Copyright (c) 2026 Jing Wang, Zushan Wang (Author) https://creativecommons.org/licenses/by/4.0
Study on income increase effect of agricultural production structure adjustment
In recent years, with the rapid economic development, in order to help farmers increase their income, China has increased the intensity of agricultural production structure adjustment, but the analysis of the effect of agricultural production structure adjustment on farmers’ income increase is not in-depth. In this paper, the regression model is used to analyze the effect of agricultural production structure adjustment on farmers’ income. The results show that the adjustment of agricultural production structure in Hubei Province has a positive effect on farmers’ income. Therefore, establishing the full coverage system, innovating the development path of the service industry, promoting the modernization of agricultural production, and accelerating the innovation of agricultural science and technology are conducive to increasing farmers’ income.
Copyright (c) 2026 Min Nian, Kao Gao, Chang Gao (Author) https://creativecommons.org/licenses/by/4.0
A Research on the Pathways for Preventing Financial Risks in the Social Credit System Based on the Digital Economy
Against the backdrop of the deep penetration of the digital economy into the financial field, the social credit reporting system, as the core infrastructure for risk prevention, is crucial to maintaining financial stability. This paper constructs a big social credit data development index (SCDBI) with 5 dimensions and 23 indicators and uses the entropy value method and panel data fixed effect model to empirically analyze the quantitative relationship between the digital level of the credit reporting system and financial risks. The study found that for every unit increase in SCDBI, the regional non-performing loan ratio dropped significantly by 0.72 percentage points (p<0.01), and data infrastructure and digital technology momentum are the core driving factors. Combined with the practical verification of Suzhou Digital Credit Investigation Experimental Zone, the data coverage breadth increased by 22 percentage points to increase the financing satisfaction rate to 92.38%, and the non-performing rate was reduced by 1.2 percentage points. The research proposes that by strengthening the integration of data elements, upgrading intelligent evaluation models, and improving diversified collaboration mechanisms, we should build a credit risk prevention system that adapts to the digital economy. Research provides a quantitative basis and practical path for financial risk governance in the new era.
Copyright (c) 2026 Yi Song, Sihan Liu (Author) https://creativecommons.org/licenses/by/4.0
Research on the Impact Mechanism of Anti-globalization Impact on the Restructuring of Manufacturing Industry Chain
Based on the database of the Asian Development Bank and the Global Value Chain Research Institute of the University of International Business and Economics, this paper uses panel data from 2008 to 2018 to investigate the impact of anti-globalization on the industrial chain restructuring of China’s manufacturing industry and its mechanism from two aspects of connection and status. It is found that the impact of anti-globalization has a significant negative impact on the restructuring of China’s manufacturing industry chain, and its degree of inhibition on the status restructuring of the industry chain is deeper than that on the linkage restructuring of the industry chain. The reverse impact of globalization mainly affects the level of industrial chain reconstruction through three channels: restricting technology spillover effect, enhancing financing constraint effect and weakening human capital enhancement effect.
Copyright (c) 2026 Yue Liu, Huiling Liu, Weixue Han (Author) https://creativecommons.org/licenses/by/4.0
Research on the Impact of Generative Artificial Intelligence on Electronic Engineering
Generative artificial intelligence (GAI) is a technology that generates text, pictures, sound, video, code and other content based on algorithms and models. GAI cannot be separated from the development and application of deep learning and neural network technology, and GAI has become a transformative force in all walks of our economy, society, industries and our life. This paper systematically studies the profound impact of GAI on Electronic Engineering from many aspects, such as circuit design, electronic programming, electronic testing, electronic management control and electronic engineering measurement, and its industry. Based on the literature, it analyzes how GAI accelerates the innovation of electronic engineering and electronic engineering industry, improves efficiency and promotes interdisciplinary integration. At the same time, the paper also emphasizes that GAI will have an impact on the learning model of electronic engineering. Finally, the paper concludes that the impact of GAI on Electronic Engineering across all sectors and a strong governance framework is needed to ensure its healthy development.
Copyright (c) 2026 Haoxiang Zhang, Chuanhao Nie (Author) https://creativecommons.org/licenses/by/4.0
The explosive growth of generative artificial intelligence (GenAI) has not only reshaped the social value of ”knowledge” and ”learning,” but intensified structural anxieties behind the sharp decline in higher education enrollment rates. Through quantitative analysis and thematic clustering methods, this study systematically reviewed 167 relevant papers between 2017 and 2025. Six research topics were highlighted: Educational Technology, Digital Literacy and AI, Teacher Education, Personalized Learning, Teacher Role Transformation, and Educational Equity and Ethics. The analysis identified research trends in AI in Digital Education, with in-depth exploration of typical applications including AI-driven personalized learning content recommendation systems, automated grading systems, automated evaluation and feedback mechanisms, learning analytics and re-recommendation systems, and conversational virtual tutors. Furthermore, the study identified challenges in AI applications within digital education and outlined future development directions for this field. It provides evidence for universities to redefine the value of education under the background of dealing with the double pressure of declining birth rate and online substitution.
Copyright (c) 2026 Muyao Liu, Sihan Liu (Author) https://creativecommons.org/licenses/by/4.0
Integrating Generative AI with Human-Centered Pedagogy: An Innovative Path for Vocational Education
The proliferation of Generative AI necessitates a re-evaluation of educational strategies, particularly in vocational fields. Traditional vocational education faces challenges like limited resource access, high software costs, and a lack of personalized feedback. This paper explores how integrating generative AI, guided by a human-centered philosophy, can address these issues. Through a qualitative analysis of four pedagogical interventions at a vocational school (e-commerce, art, math, and computer science), we find that AI, as a pedagogical co-pilot, boosts instructional efficiency, nurtures creativity, and enables individualized learning. The case studies show AI’s ability to lower costs, remove practice barriers, and provide data-driven insights. We synthesize these findings into a conceptual framework for human-centered AI integration, emphasizing AI’s role in empowering educators and learners. This research offers a transferable model and discusses ethical considerations for creating effective and equitable learning environments.
Copyright (c) 2026 Tingjie Xu, Yisong Chen (Author) https://creativecommons.org/licenses/by/4.0
The application of artificial intelligence in education is undergoing a paradigm shift from ”tool embedding” to ”system reshaping”. This study uses 1,181 relevant articles from the 2013-2025 Web of Science core collection as samples, employing a combination of bibliometric analysis and thematic content analysis to map the spatiotemporal evolution, knowledge networks, and research hotspots in this field. The findings reveal that annual publications surged from 1 in 2013 to 715 in 2025, with citation counts reaching 8,385. Since 2024, the field has demonstrated ”dual leaps in quantity and quality”. Major research contributors include China, USA, and Australia, with papers predominantly published in the journal Education and Information Technologies. Research themes can be categorized into six major sectors, extending to eight application scenarios such as language learning, basic education, special education, and teacher development. Current studies predominantly adopt cross-sectional designs, lacking long-term tracking and causal inference, while insufficient attention is given to rural areas, low-resource languages, and special education contexts. Ethical risk governance frameworks also require further refinement. This paper proposes future research directions focusing on three dimensions: paradigm innovation, contextual expansion, and ethical governance, aiming to provide references for advancing AI in Education research and informing policy practices.
Copyright (c) 2026 Li Zhou, Shoufang Zhang, Yexin Tian (Author) https://creativecommons.org/licenses/by/4.0
Effect of Commitment-based Human Resource Management Practices on Employee Voice Behavior: The Roles of Perceived Insider Status and Organizational Embeddedness
Employee voice behavior shown by employees independently for the long-term development of the organization plays an important role in the performance improvement of the enterprise and has been a hot research topic in the academic circle. On the basis of 256 employee-leader paired questionnaires and using multiple regression analysis, this paper explores the mechanism of how commitment-based human resource management practices (CBHRMPs) affect employee voice behavior. The findings indicate that employee voice behavior is positively effected by CBHRMPs while it is totally mediated by perceived insider status. What’s more, the mediation effect is positively moderated by organizational embeddedness. This study has both important theoretical and practical significance on how to stimulate employee voice behavior.
Copyright (c) 2026 Xinyi Zheng, Xiaohan Wang (Author) https://creativecommons.org/licenses/by/4.0
Green Logistics Discovery Strategy of Agricultural Products Under Low Carbon Economy
This article starts from the perspective of low-carbon economy, reviews literature on green logistics evaluation in recent years, and combines the current development status of agricultural product logistics in Linyi City. Using literature induction method, a green logistics evaluation index system for agricultural products in Linyi City is established. Using the Analytic Hierarchy Process, evaluate the development of green logistics for agricultural products in Linyi City, analyze the influencing factors of green logistics for agricultural products in Linyi City, and finally propose corresponding countermeasures based on the indicator system.
Copyright (c) 2026 Bo Zhang, Jingyi Guan, Meicheng Qu, Xinru Liu (Author) https://creativecommons.org/licenses/by/4.0
The Application of ChatGPT in Economics Teaching: Scenarios, Deficiencies and Strategies
ChatGPT, as a large-scale language model, will profoundly influence and reshape the existing education and teaching model. This paper comprehensively analyzes the key technologies and core functions of ChatGPT and its application value in the education industry, and further emphasizes the unique advantages and potential value of ChatGPT in the teaching of economics courses. On this basis, the paper focuses on the application of ChatGPT in teaching, learning and evaluation of economics courses, and emphasizes several disadvantages of ChatGPT in education, including cheating and academic dishonesty, difficulty in ensuring the authenticity of answers, which may weaken students’ self-learning ability, and challenges to the essence of education. In view of this, this paper puts forward countermeasures from two aspects of technology and system respectively: technically, we should improve the accuracy of the content and enhance the controllability of the application process; systemically, we should improve the mathematical intelligence of the educational subject and strengthen the academic normative management.
Copyright (c) 2026 Zhihui Shen, Wentao Zhu (Author) https://creativecommons.org/licenses/by/4.0
Research on the Mechanism of Coordinated Development between Digital Transformation of Vocational Education and New Quality Productivity under the United front
In the new technology wave, the vigorous development of cutting-edge technologies such as big data, cloud computing, and artificial intelligence has made the digital transformation of vocational education an inevitable trend, and the rapid development of new quality productivity has provided strong support for it. This paper focuses on the mechanism of the United Front empowering the digital transformation of vocational education and the coordinated development of new quality productivity. It is found that the United Front relies on resource integration, platform building, collaborative innovation and talent co-cultivation mechanisms to optimize the allocation of vocational education resources, make efficient use of them, and deeply integrate them with innovative technologies, thereby improving the quality and efficiency of education and cultivating a large number of high-quality technical talents. However, there are challenges in the collaborative cooperation of multiple subjects. The different interests and development goals of the government, enterprises, and schools have caused cooperation difficulties. It is necessary to establish an effective communication and coordination mechanism to clarify responsibilities and obligations, strengthen policy guidance and incentives, build a resource sharing platform, promote collaborative innovation, and strengthen talent co-cultivation. Strategies such as these are critical, and can provide specific paths and practical guidance for the digital transformation of vocational education and the coordinated development of new quality productivity, thereby improving the level and competitiveness of national vocational education and promoting high-quality economic and social development.
Copyright (c) 2026 Mi Liu, Liping Jin, Tingjie Xu, Zhenyuan Cai, Yu Meng, Juan Liu, Chuanhao Nie (Author) https://creativecommons.org/licenses/by/4.0
Research on Personalized Education for Business Talents Based on Big Data Driven Student Portrait
With the impact of technological changes such as artificial intelligence, big data, cloud computing and blockchain, the business environment has undergone disruptive restructuring and innovation. The digital economy has brought about changes in talent demand and supply, leading to changes in the knowledge system and quality capabilities of business talents in the new era. This trend of change places high demands on the personalized cultivation of new business talents. Based on the analysis of the Spark platform, this article proposes to establish a student ”portrait” feature library that can fully depict students’ personal characteristics through pre-processing, statistics, and analysis of raw data on campus student behavior, in order to analyze and predict students’ learning needs, recommend personalized learning plans for students, and ultimately achieve the goal of providing personalized business talents for the development of the new economy.
Copyright (c) 2026 Yan Cheng, Yingfang Zhao (Author) https://creativecommons.org/licenses/by/4.0
Analysis of the Influencing Factors on the Financing Efficiency of High-Tech Listed Companies in Wuhan Based on the DEA Model
This paper analyzes the financing efficiency of 49 high-tech listed companies in Wuhan from both static and dynamic perspectives from 2020 to 2022, and finds that the financing efficiency of high-tech listed companies in Wuhan is showing a downward trend. Subsequently, using the grey relational model analysis, it was found that the main influencing factor on the financing efficiency of Wuhan high-tech listed companies is the circulation of market currency at the macro level and the profitability of enterprises at the micro level.
Copyright (c) 2026 Qiao Yang, Xinru Liu (Author) https://creativecommons.org/licenses/by/4.0
Application of AI with Fintech in financial services sector
During past several decades, amazing technology advance in Artificial Intelligence (AI), Big data and Machine Learning have been achieved and witnessed. AI plays a vital role in the digital transformation process of all sectors, especially within the domain of Finance. This paper reviews the application of AI with Fintech in financial services sector, analyzing how AI, Machine Learning, big data analytics and other Fintech techniques are being deployed to improve decision-making such as credit scoring, risk management, portfolio management and market prediction, improve efficiency and reduce costs while enhancing customer experience and engagement at the same time. The paper synthesizes recent advancements in AI’s application along with the evolution of Fintech in the financial sectors, summarizes AI techniques used, explore most common application areas of AI techniques, and discusses potential challenges AI brings to humans. It highlights how AI is reshaping the landscape of financial industry, and what academics, regulators, financial institutions, and Fintech companies need to do to leverage the benefits of AI while addressing the potential risk or problems it brings to the whole society and economy.
Copyright (c) 2026 Jing Liu, Jingjing Duan (Author) https://creativecommons.org/licenses/by/4.0
A Study about University Teachers’ Intentions Regarding Students’ Usage on AI Tools: An Empirical Analysis Based on Involvement, Trust, and Perceived Risk
As the rise on generative artificial intelligence (GAI) in education, university teachers’ attitudes have become more vital in the adoption and ethical governance of AI tools. Based on a survey of 789 humanities faculty members in universities across Guangdong Province, the study finds that teachers’ involvement and trust significantly predict their intention how to adopt AI tools, while perceived risk negatively influences their thoughts. At the meanwhile significant differences are observed across gender, age, academic rank and usage frequency. The study contributes to the theoretical construction of AI educational technology acceptance models and offers practical guidance for AI literacy training, differentiated promotion strategies, and regulatory frameworks in higher education.
Copyright (c) 2026 Huijun Xiao, Shenglun Shen (Author) https://creativecommons.org/licenses/by/4.0
The Impact of Government Health Spending on Household Consumption: An AI-Driven Empirical Study
The downward pressure on China’s economy is great, and the growth pace tends to be slow. In this context, how to effectively promote economic development and actively promote residents’ consumption while ensuring the health of people’s livelihood has become an important problem to be solved urgently in China. This study collected relevant data from 2000 to 2022 and used regression analysis method to deeply explore the internal relationship between government health expenditure, per capita disposable income of residents and consumer price index and consumer expenditure. The results show that there is a negative correlation between government health expenditure and household consumption expenditure, while per capita disposable income and consumer price index are positively correlated with household consumption expenditure. Further analysis of the reasons behind it shows that the increase of government health expenditure often leads to the corresponding decrease of public expenditure in other fields, especially when the government’s financial resources are limited, the redistribution of such resources will affect key areas such as education and infrastructure construction, and then indirectly affect residents’ consumption. In addition, a higher amount of government health expenditure may be passed on to residents by raising taxes or public service fees, thus inhibiting residents’ consumption. On the other hand, with the increase of the per capita disposable income of residents, the disposable funds in the hands of residents are more abundant and their spending power is enhanced. The consumer price index can reflect the level of inflation to a certain extent, and moderate inflation can stimulate residents’ willingness to consume, thus increasing the demand for all kinds of goods and services.— Based on the above conclusions, in order to effectively promote consumption and promote sound economic development, the following suggestions are put forward: adhere to the leading position of the government, allocate health expenditure scientifically and reasonably, build a sound health evaluation system, and continuously optimize the health system, so as to help consumption upgrade and realize the coordinated development of economy and people’s livelihood security.
Copyright (c) 2026 Chengcheng Dai, Shengrong Lu, Yunhan Wang (Author) https://creativecommons.org/licenses/by/4.0
A Research on the Impact of Market Structure on Deposit and Loan Pricing Using Financial Technology Innovation Pricing Model
The pricing of commercial bank deposits and loans is a key link in optimizing the allocation of credit resources through the price mechanism by means of indirect financing. Under the background of the rapid development of financial technology, the mechanism of commercial bank deposit and loan pricing becomes much more complicated. On the one hand, the changes in the market structure and competitive landscape of China’s banking industry are bound to change the pricing behavior of commercial banks. On the other hand, financial technology innovation will have a significant impact on deposit and loan pricing at both the micro and meso industry levels. On the basis of theoretical analysis, this paper constructs a financial technology innovation pricing model and conducts empirical research. It is found that not only is there a significant direct correlation between market structure and financial technology innovation with the pricing of commercial bank deposits and loans, but the market structure pathway is also a key indirect mechanism affecting the pricing of commercial bank deposits and loans. Variables such as financial technology innovation, risk-taking, equity capital, benchmark interest rates, and actual output all have indirect effects on the pricing ability of commercial bank deposits and loans through the market structure pathway. This provides evidence support and feasible suggestions for further optimizing the market structure, promoting financial technology innovation, and improving the efficiency of deposit and loan pricing in China’s commercial banking industry.
Copyright (c) 2026 Zhigang Zhou, Shengyang Yan, Xiaodan Wan (Author) https://creativecommons.org/licenses/by/4.0
Artificial Intelligence and Corporate Innovation: Corporate Restructuring and Financing Constraints
Can corporate mergers and acquisitions alleviate their own financing constraints? Previous studies on financing constraints mostly focused on the measurement of financing constraints and their effects on enterprise performance but did not deeply discuss the transmission mechanism of enterprise behavior to financing constraints. This paper uses the financial data of Chinese listed companies and the database of mergers and acquisitions to measure the financing constraints by investment cash flow sensitivity and SA index and analyzes the influence of mergers and acquisitions on financing constraints. The empirical results show that the acquisition behavior of listed companies can alleviate the financing constraints of enterprises, and this mechanism has a more obvious effect in the post-financial crisis period. Moreover, combined with the actual situation in China, the functions of enterprises with different acquisition methods and different equity attributes will be different. But on the whole, with the rise of financial instruments and Internet finance, it is also a good strategy for enterprises to use a variety of financial instruments to carry out mergers and acquisitions to ease financing constraints.
Copyright (c) 2026 Wensong Yu, Shanshan Lou (Author) https://creativecommons.org/licenses/by/4.0
Urban Investment Attraction Performance and Technological Innovation-driven New Economic Development Strategy
Attracting investment plays an important role in promoting the economic development of Chinese cities. As a major strategic focus of the country, such as “one belt and one road”, the Yangtze River economic belt and the rise of central China, Wuhan seizes the opportunity to actively develop a new economy driven by technological innovation by attracting investment. Through the construction of the index system for the performance evaluation of urban investment promotion, this paper makes an empirical analysis of the performance of investment promotion in Wuhan by using the entropy method, and finds that in the process of developing a new economy driven by technological innovation, Wuhan has a better performance in resource conservation and environmental protection, but there are some problems, such as insufficient technological innovation ability, poor effect of industrial upgrading, insufficient social responsibility and unstable performance of investment promotion. Only by adopting innovative strategies in introducing and cultivating technological innovation ability, guiding industrial upgrading, earnestly fulfilling social responsibility and maintaining the steady growth of investment promotion performance can we improve the performance of investment promotion in Wuhan and realize the sustainable development of a new economy driven by technological innovation.
Copyright (c) 2026 Shengyang Yan, Zimu Yan, Jiahui Ren (Author) https://creativecommons.org/licenses/by/4.0