In the era of big data, data, information, and knowledge are important resources for enterprises. With the production of massive data inside and outside the enterprise, paying attention to the processing and analysis of big data can bring great value to the enterprise, adapting to the changing economic environment. Facing the need for data mining, the disadvantages of traditional information systems begin to show. Due to the influence of factors such as high cost, low efficiency, and long construction cycles, the existing information systems make it difficult to obtain large amounts of accounting data and mining knowledge to provide a scientific basis for business managers’ decisions in time.

In the era of big data, the information department that deals with the most data is facing problems of processing and analyzing big data. By using cloud computing and other technologies to fully mine and analyze big data, the problems of information island, lack of resources, and lagging decision-making are solved, business integration and information resource sharing are realized, the relevance of information quality is improved, and new ideas can then be provided for managers' decision-making. Using emerging information technology to build a more efficient big data analysis platform and mobile information system not only provides a theoretical basis for improving the information-theoretical system but also provides practical significance for enhancing the core competitiveness of enterprises.

This Special Issue mainly focuses on big data analytics in mobile information systems in the digital economy era. This Special Issue aims to publish the latest, high-quality work related to big data and mobile information systems. We also encourage research based on end-user computing. We welcome both original research and review articles.

Potential topics include but are not limited to the following:

• Structure analysis of smart mobile medical information systems based on big data
• Command information system architecture based on mobile information systems
• Budget management information systems for small and medium-sized enterprises
• Service composition approaches for mobile information systems
• Railway passenger transport user portrait systems based on big data
• Geographical information system parallelization for spatial big data processing
• Management and application of mobile big data
• Intelligent medical big data systems
• Intelligent logistics management information systems
• Big data and smart aviation information management systems
• Big data technology-based agricultural information systems
• Big data and machine learning-based secure healthcare frameworks
• Big data analytics for knowledge generation in tourism destinations
• Enabling smarter societies through mobile big data fogs and clouds