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

A data-driven approach for extracting and analyzing collaboration patterns at the interagent and... Electron Commer Res https://doi.org/10.1007/s10660-018-9307-x A data‑driven approach for extracting and analyzing collaboration patterns at the interagent and intergroup levels in business process 1 2 3 4 Shanshan Wang  · Kun Chen  · Zhiyong Liu  · Ren‑Yong Guo  · 5 6 Jianshan Sun  · Qiongjie Dai © Springer Science+Business Media, LLC, part of Springer Nature 2018 Abstract We developed a data-driven approach for extracting and analyzing the interagent and intergroup collaboration patterns centered on the COLLSTRUC lan- guage 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. Keywords Interagent and intergroup perspectives collaboration patterns · Business-process performance · Process event logs * Kun Chen chenk@sustc.edu.cn Shanshan Wang cswangss@imu.edu.cn College of Computer Science, Inner Mongolia University, Hohhot, Inner Mongolia, People’s Republic of China Department of Finance, Southern University of Science and Technology, Shenzhen, Guangdong, People’s Republic of China Faculty of Management and Economics, Dalian University of Technology, Dalian, Liaoning, People’s Republic of China School of Economics and Management, Beihang University, Beijing, People’s Republic of China School of Management, Hefei University of Technology, Hefei, Anhui, People’s Republic of China College of Erdos, Inner Mongolia University, Hohhot, Inner Mongolia, People’s Republic of China 1 3 S. Wang et al. 1 Introduction Collaboration aims to maximize the joint effort of all participants towards accom- plishing a joint goal [1]. Collaborative patterns, which are recurring fragments of the collaboration interaction process, play a critical role in collaboration http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Electronic Commerce Research Springer Journals

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

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Publisher
Springer US
Copyright
Copyright © 2018 by Springer Science+Business Media, LLC, part of Springer Nature
Subject
Business and Management; IT in Business; Data Structures, Cryptology and Information Theory; Operations Research/Decision Theory; Computer Communication Networks; Business and Management, general; e-Commerce/e-business
ISSN
1389-5753
eISSN
1572-9362
D.O.I.
10.1007/s10660-018-9307-x
Publisher site
See Article on Publisher Site

Abstract

Electron Commer Res https://doi.org/10.1007/s10660-018-9307-x A data‑driven approach for extracting and analyzing collaboration patterns at the interagent and intergroup levels in business process 1 2 3 4 Shanshan Wang  · Kun Chen  · Zhiyong Liu  · Ren‑Yong Guo  · 5 6 Jianshan Sun  · Qiongjie Dai © Springer Science+Business Media, LLC, part of Springer Nature 2018 Abstract We developed a data-driven approach for extracting and analyzing the interagent and intergroup collaboration patterns centered on the COLLSTRUC lan- guage 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. Keywords Interagent and intergroup perspectives collaboration patterns · Business-process performance · Process event logs * Kun Chen chenk@sustc.edu.cn Shanshan Wang cswangss@imu.edu.cn College of Computer Science, Inner Mongolia University, Hohhot, Inner Mongolia, People’s Republic of China Department of Finance, Southern University of Science and Technology, Shenzhen, Guangdong, People’s Republic of China Faculty of Management and Economics, Dalian University of Technology, Dalian, Liaoning, People’s Republic of China School of Economics and Management, Beihang University, Beijing, People’s Republic of China School of Management, Hefei University of Technology, Hefei, Anhui, People’s Republic of China College of Erdos, Inner Mongolia University, Hohhot, Inner Mongolia, People’s Republic of China 1 3 S. Wang et al. 1 Introduction Collaboration aims to maximize the joint effort of all participants towards accom- plishing a joint goal [1]. Collaborative patterns, which are recurring fragments of the collaboration interaction process, play a critical role in collaboration

Journal

Electronic Commerce ResearchSpringer Journals

Published: May 30, 2018

References

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