Economics & Management Information

A Design and Research of Pharmacy Management Robot Based on Artificial Intelligence

2025-06-29T16:32:38+08:00

In order to solve the problems of long queuing time, low efficiency of manual dispensing and high risk of errors in traditional hospital pharmacies, this study designed and developed a pharmacy management robot system integrated with artificial intelligence technology. Through the integration of automatic robotic arm, AI visual recognition and Internet of things perception technology, the system innovatively realizes the intelligent management function of the whole drug process: It includes high-precision drug visual recognition and two-dimensional code scanning, accurate cover opening and drug distribution of multi-axis manipulator, omnidirectional mobile chassis driven by ROS robot operating system, and multi-sensor fusion navigation system based on laser radar and depth camera. Among them, the intelligent packaging module developed by the product solves the problem of insufficient opening accuracy of existing pharmacy robot medicine bottles through the precise lid opening technology of mechanical arm, effectively optimizes the efficiency of drug distribution and the quality of medical service, and becomes an innovative breakthrough in the field of intelligent pharmacy management.

Analysis of the Impact of Financial Technology on Capital Allocation Efficiency—Empirical Evidence from Chinese A-Share Listed Companies

2025-04-23T15:38:47+08:00

Improving the efficiency of corporate capital allocation is the microfoundation for promoting high-quality economic development. Starting from the Cobb-Douglas production function, this paper constructs a theoretical model of the impact of finance technology on capital allocation efficiency. Based on this, an empirical test of the impact and mechanism of financial technology on capital allocation efficiency is conducted using data from Chinese A-share listed companies from 2008 to 2023. The research indicates that: (I) The improvement of financial technology levels could significantly reduce the deviation of capital allocation from the ideal state and improve capital allocation efficiency; (II) Financial technology could enhance corporate governance levels, thereby improving the efficiency of corporate capital allocation; (III) The enhancement of financial technology levels could restrain excessive investment and underinvestment behaviors in enterprises, promoting the improvement of capital allocation efficiency; (IV) The higher the level of financial technology is, the more significant effect on improving capital allocation efficiency would be.

Construction, Completeness Proof and Empirical Study of Cross-Border E-Commerce Market Measure Space

2025-07-01T14:55:22+08:00

Against the backdrop of the deep integration of the global digital economy and cross-border e-commerce, and addressing the lack of measure theory and quantitative analysis challenges for high-dimensional dynamic data in this field, this study constructs a measure theory system for cross-border e-commerce markets that combines mathematical rigor and economic interpretability based on Carathéodory’s extension theorem. Based on functional analysis and measure theory, the study defines the market fundamental set as the topological product space of a time index set and a multi-dimensional transaction state space. By constructing a combined structure of a left-open right-closed interval semiring and a power set semiring that satisfies the closure of Boolean algebra operations, an algebraic framework is established for the unified measurement of continuous and discrete variables. On the semiring structure, a σ-finite premeasure integrating Lebesgue measure and counting measure is defined. With the help of the countable covering mechanism generated by outer measure and the measure screening rules of Carathéodory’s measurability condition, the axiomatic extension from premeasure to complete measure on the σ-algebra is completed. Through the verification of Carathéodory’s condition for subsets of null sets and the transmission of outer measure monotonicity, the completeness of the measure space is strictly proved, and the core property that “subsets of null sets must be measurable” is established, providing a solid measure-theoretic foundation for mathematical modeling of cross-border e-commerce markets. At the empirical analysis level, the study uses micro-panel data on global cross-border e-commerce transactions from 2018 to 2024. Through the Kolmogorov-Smirnov test in non-parametric hypothesis testing, the distribution isomorphism between the theoretical measure and empirical data is verified. Based on the measure space theory, a Generalized Method of Moments (GMM) panel regression model is constructed. System GMM and Difference GMM estimation methods are used to handle endogeneity issues. Combined with instrumental variable methods and lag variable techniques, key parameters such as the logarithmic elasticity of economic scale between importing and exporting countries, the spatial decay effect of geographical distance, and the asymmetric inhibitory effect of tariff policies are quantitatively analyzed. A graph neural network model integrating measure theory is innovatively designed. By introducing a completeness regular term, the measure constraints on null sets and their subsets are achieved. Combined with the SHAP value interpretability analysis method, the marginal contribution of each characteristic variable in model decision-making is revealed. The study finds that the constructed measure space not only satisfies the axiomatic requirements of modern measure theory such as completeness and σ-finiteness, but also through the empirical tests of the GMM model and graph neural network, it is confirmed that it can effectively characterize the economic scale effect, spatial distance decay law, and policy sensitivity characteristics in cross-border e-commerce transactions, providing a methodological innovation paradigm based on measure theory for quantitative analysis in the field of international business in the digital economy era.

The Application of Artificial Intelligence in the Investment Field

2025-06-05T14:29:16+08:00

The application of artificial intelligence technology in the financial sector has brought about significant transformations across the entire financial industry, giving rise to innovative financial services such as intelligent financial advisory, intelligent credit assessment and monitoring and intelligent customer service. However, the application of AI technology in financial sector also faces a series of challenges and difficulties. To enhance core research and development capabilities, it is necessary to integrate and utilize big data resources, build and improve a secure and widely shared data ecosystem, establish and optimize multiple risk prevention mechanisms, and improve the risk control level of AI technology. Reforms and improvements in financial regulatory mechanisms are needed to achieve comprehensive oversight of the application of AI technology in the financial sector, providing favorable conditions for promoting innovative and standardized development in the financial industry.