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A data-driven approach for extracting and analyzing collaboration patterns at the interagent and intergroup levels in business process

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Abstract

We developed a data-driven approach for extracting and analyzing the interagent and intergroup collaboration patterns centered on the COLLSTRUC language and its related algorithm. The proposed approach is evaluated by comparing it with existing studies related to collaboration patterns and through an empirical evaluation using Volvo IT event logs.

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Acknowledgements

The work described in this study was partially supported by grants from the National Natural Science Foundation of China (Nos. 71461023, 71573030, 71361017, 71640021).

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Authors and Affiliations

  1. College of Computer Science, Inner Mongolia University, Hohhot, Inner Mongolia, People’s Republic of China

    Shanshan Wang

  2. Department of Finance, Southern University of Science and Technology, Shenzhen, Guangdong, People’s Republic of China

    Kun Chen

  3. Faculty of Management and Economics, Dalian University of Technology, Dalian, Liaoning, People’s Republic of China

    Zhiyong Liu

  4. School of Economics and Management, Beihang University, Beijing, People’s Republic of China

    Ren-Yong Guo

  5. School of Management, Hefei University of Technology, Hefei, Anhui, People’s Republic of China

    Jianshan Sun

  6. College of Erdos, Inner Mongolia University, Hohhot, Inner Mongolia, People’s Republic of China

    Qiongjie Dai

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  1. Shanshan Wang
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  2. Kun Chen
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  3. Zhiyong Liu
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  4. Ren-Yong Guo
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Correspondence to Kun Chen.

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Wang, S., Chen, K., Liu, Z. et al. A data-driven approach for extracting and analyzing collaboration patterns at the interagent and intergroup levels in business process. Electron Commer Res 19, 451–470 (2019). https://doi.org/10.1007/s10660-018-9307-x

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  • DOI: https://doi.org/10.1007/s10660-018-9307-x

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