2026 International Conference on Data-Driven Economy and Information Management
Nanjing, China | August 7-9, 2026
The 2026 International Conference on Data-Driven Economy and Information Management (DDIM 2026) will take place in Nanjing, China, from August 7 to 9, 2026. It provides a premier platform for researchers, practitioners, and industry experts to share cutting-edge research, innovative applications, and practical insights at the intersection of economic management, digital technologies, and information systems. This conference emphasizes the role of data-driven approaches, digital transformation, and intelligent management in shaping the modern economy.
We welcome submissions that address both theoretical and practical challenges, leveraging artificial intelligence, big data, blockchain, and other emerging technologies to enhance economic performance, digital markets, and sustainable management practices.
Important Date
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Full Paper Submission Date June 2, 2026 |
Registration Deadline July 23, 2026 |
Notification Date July 7, 2026 |
Conference Dates August 7-9, 2026 |
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The topics of interest for submission include, but are not limited to: I. Data-Driven Economy
Ⅱ. Commerce & Digital Markets
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All papers submitted to the conference will be assigned to the respective program committees based on factors such as submission date and topic relevance. Each program committee will then coordinate the peer review process, ensuring rigorous evaluation and making final decisions on acceptance and publication. The submission will first be reviewed for its topic and length, then go through an originality check. The peer-review process will begin soon after the paper is found to be qualified. The paper will be sent to have a double-blind peer review by 2 reviewers. They will judge the paper based on the theme, coverage, innovation, integrity, depth, and language. If the paper is accepted, notification of acceptance and review comments will be sent to the author via email. The actual review time may be different under certain situations. |
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Big data analytics for economic decisions
