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    ICEMBDA

    Proceedings of the 4th International Conference on Economic Management and Big Data Applications, ICEMBDA 2023, October 27–29, 2023, Tianjin, China

    The 4th International Conference on Economic Management and Big Data Applications was successfully held in Tianjin, China from October 27th to 29th, 2023. This conference served as a platform for researchers, scholars, and industry professionals to exchange knowledge and insights in the field of ec…

    The 4th International Conference on Economic Management and Big Data Applications was successfully held in Tianjin, China from October 27th to 29th, 2023. This conference served as a platform for researchers, scholars, and industry professionals to exchange knowledge and insights in the field of economic management and the application of big data. The conference held great significance in advancing the understanding and application of economic management and big data. By bringing together experts from around the globe, the conference facilitated the exchange of innovative ideas and research findings, contributing to the development of these fields. The topics covered during the conference showcased the latest advancements and trends in enterprise economic statistics, information evaluation, blockchain technology, industrial structure optimization, information retrieval, data regression analysis, intelligent Internet of Things platforms, and data encryption.

    The discussions and presentations during the conference allowed participants to explore new methodologies, strategies, and technologies that can enhance economic management practices and leverage the potential of big data. The conference provided a platform for scholars and practitioners to share their experiences, insights, and best practices, fostering collaboration and networking opportunities.

    Furthermore, the proceedings were published, ensuring the dissemination of valuable research findings to a wider audience. The collective knowledge and research presented at the conference will contribute to the academic community, industry professionals, and policymakers, enabling them to make informed decisions and develop effective strategies in the fields of economic management and big data applications.

    Overall, the 4th International Conference on Economic Management and Big Data Applications played a pivotal role in promoting knowledge exchange, fostering innovation, and shaping the future of economic management by harnessing the power of big data.

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    Editor(s): Jianguo Liu (Shanghai University of Finance and Economics, China), Haifeng Li (Dalian Jiaotong University, China) and Sikandar Ali Qalati (Jiangsu University, China)
    Publisher
    EAI
    ISBN
    978-1-63190-444-8
    ISSN
    2593-7642
    Series
    CORE
    Conference dates
    27th–29th Oct 2023
    Location
    Tianjin, People's Republic of China
    Appeared in EUDL
    2024-01-19

    Copyright © 2024–2025 EAI

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    • A Power Generation Side Energy Storage Power Station Evaluation Strategy Model Based on the Combination of AHP and EWM to Assign Weight

      Research Article in Proceedings of the 4th International Conference on Economic Management and Big Data Applications, ICEMBDA 2023, October 27–29, 2023, Tianjin, China

      Chunyu Hu, Chunlei Shen, Yifan Zhou, Zezhong Kang
    • An Explainable Enterprise Credit Evaluation Method Based on Logistic Regression Integration

      Research Article in Proceedings of the 4th International Conference on Economic Management and Big Data Applications, ICEMBDA 2023, October 27–29, 2023, Tianjin, China

      Bin Zhai, Fanyu Wang, Zhenping Xie, She Song
    • E-commerce Development in Rural Anhui: Insights from a Resident Survey

      Research Article in Proceedings of the 4th International Conference on Economic Management and Big Data Applications, ICEMBDA 2023, October 27–29, 2023, Tianjin, China

      Jian Yang
    • Empirical Research on Population Structure and Housing Demand under the Data Mining Classification Model

      Research Article in Proceedings of the 4th International Conference on Economic Management and Big Data Applications, ICEMBDA 2023, October 27–29, 2023, Tianjin, China

      Panpan Li, Aifei Yin, Zhuanping Du
    • Exploration of Blockchain Technology and IPFS Distributed Storage System in UGC Model

      Research Article in Proceedings of the 4th International Conference on Economic Management and Big Data Applications, ICEMBDA 2023, October 27–29, 2023, Tianjin, China

      Zhexi Gu, Lijun Yang, Baolin Liu
    • Impact of Cross-Boundary Behavior on Team Innovation

      Research Article in Proceedings of the 4th International Conference on Economic Management and Big Data Applications, ICEMBDA 2023, October 27–29, 2023, Tianjin, China

      Chengzhao Luo, Haoqing Ding
    • Multi Model Establishment of Enterprise Case Aided Decision-making Based on Data Analysis

      Research Article in Proceedings of the 4th International Conference on Economic Management and Big Data Applications, ICEMBDA 2023, October 27–29, 2023, Tianjin, China

      Kunying Li, Xuwei Jiang, Xu He, Siwen Yin
    • Optimization Research on the Performance Appraisal Process of Civil Servants Based on the OEEF Model

      Research Article in Proceedings of the 4th International Conference on Economic Management and Big Data Applications, ICEMBDA 2023, October 27–29, 2023, Tianjin, China

      Han Qiu, Hongyun Chen, Yan Zhang, Linlin Zhang
    • Research and Analysis on the Optimization of Live Streaming Path in the New Era Based on Big Data Algorithm

      Research Article in Proceedings of the 4th International Conference on Economic Management and Big Data Applications, ICEMBDA 2023, October 27–29, 2023, Tianjin, China

      Xinghan Li, Jinjie Dong, Quan Yuan, Jiawei Liu
    • Research on Pesticide Registration Test and Traceability System Based on Blockchain

      Research Article in Proceedings of the 4th International Conference on Economic Management and Big Data Applications, ICEMBDA 2023, October 27–29, 2023, Tianjin, China

      Yuhang Ding, Fei Sun, Jun Zhao, Shenxin Liu, Zifeng Wang, Jie Huang
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