Big data technologies have caused the volume, velocity, and variety of data generated by enterprise information systems to grow exponentially. It has thereby rendered traditional approaches to data management no longer effective. This paper focuses on data storage, management, and analysis strategies for information systems within big data environments and searches for pathways to maximize value. Employing a combined literature review and case study methodology, it systematically reviews existing data management frameworks while integrating corporate practical experience through case studies. The findings indicate that data management activities of an existing information system experience problems, like storage resource management efficiency, the lack of standardized data governance, and inefficient use of analytical technologies. The proposed strategy involving data management hierarchies, data governance, and intelligent analytics can significantly increase the capacity of an information system in creating value from existing data. The research is beneficial and can offer significant help to existing and running enterprises on how they can improve data management practices and gain a competitive edge.

This paper aims to explore the current status and emerging trends of corporate supply chain management within the context of intelligent supply chains by conducting a comparative analysis of the supply chain systems employed by three typical high-tech enterprises, namely Apple, Xiaomi, and Huawei. Adopting a case analysis method, the study systematically examines the theoretical foundations of intelligent supply chains while providing a detailed analysis of the distinctive features and strategic approaches that characterize the supply chain management practices of these three corporations. The findings indicate that Apple has significantly enhanced production efficiency and reduced inventory by implementing a global outsourcing strategy and building an agile and efficient supply chain network. Huawei has remarkably improved operational efficiency and market competitiveness by focusing on digital and intelligent upgrades and constructing a high-end supply chain system integrating intelligent procurement, manufacturing and logistics. Xiaomi has achieved rapid market response and cost control by adopting a hybrid and agile collaborative supply chain model based on ecological cooperation and digital empowerment. The study concluded that the evolution of intelligent supply chains presents both unprecedented opportunities and challenges for corporate supply chain management.

With the continuous development of logistics and online shopping, Cainiao Station, as the last link of the logistics system and an important facility for convenient public services, is gaining increasing importance in urban daily life and industrial development. However, it still has some obvious problems that seriously affect its operational efficiency. This paper uses the methods of ergonomics, facility planning and operations research to analyze the existing problems from the aspects of distribution efficiency, station location design, spatial layout and utilization rate, and user pick-up experience, and puts forward feasible solutions one by one, so as to improve the operational efficiency of the station and the user pick-up experience. Finally, by observing the common problems and operational status of some Cainiao Stations and combining the actual situations of different stations, this paper proposes a set of universally applicable and highly practical optimization templates to improve the operational efficiency and customer satisfaction of Cainiao Station.

The objective of this study is to examine the predictive relationship between the China stock market and the bond market. With the worsening economic environment entering 2024-2025, the stock-bond linkage mechanism has played an increasingly important role in financial forecasts. But through the current forecasts, it has been noticed that the forecasts often ignore the systematic connection of market information between the markets. The construction of the model was focused on a VAR model with the return of the stock market as an exogenous variable, which was contrasted with the traditional ARIMA model, and the nature of the connection between the two markets was evaluated through Granger causality test, variance decompositions, and impulse responses. The outcome of the test showed the superiority of the VAR model in terms of the key predictive accuracy of the forecast, especially regarding the declining trend of the bond market yields. Overall, the findings suggest that the stock market exhibits significant leading and explanatory power over the bond market, indicating that integrating cross-market information can enhance forecasting accuracy and provide more effective quantitative support for asset allocation and risk early warning by leveraging leading indicators from the stock market.

Based on Bourdieu's 'capital-field-habitus’ theoretical framework, this paper conducts a secondary analysis of three empirical studies in the Chinese educational context to illustrate how family cultural capital influences students' academic performance through academic habitus. The results show that there is a stable positive relationship between family cultural capital and academic performance, which is not mainly achieved in a direct way, but through the formation of habitus habits that are consistent with the school assessment rules, which are further manifested in sustained learning behaviours, and finally transformed into academic strengths. In the test score-centred Chinese educational environment, learning habits play a key mediating role in the transformation of cultural capital into academic performance, and the differences in the intensity of the role in different studies are related to differences in educational stages and research designs, and reflect the process by which the educational evaluation mechanism and the structure of learning practices jointly influence the path of capital transformation.