Formal approach for discovering work transference networks from workflow logs

Autor: Kwang-Hoon Kim, Hyun Ahn
Rok vydání: 2020
Předmět:
Zdroj: Information Sciences. 515:1-25
ISSN: 0020-0255
DOI: 10.1016/j.ins.2019.11.036
Popis: This paper proposes a formal principle for discovering work transference networks of workflow-supported organizational employees from workflow enactment histories contained in event logs. This originates from the strong belief that those work transference networks, hidden in workflow enactment activities and histories, can both connote the degree of work sharing and work relevancy between workflow performers and denote their degree of work intensity. In this paper, we devise a series of formal definitions and algorithms for discovering a work transference network from a workflow procedure, and from its enactment histories in event logs. The final goal of the paper is to theoretically build the principle of fidelity into workflow human resource planning and its performance, via a novel concept of work transference networks that can be discovered from a workflow model and, moreover, rediscovered from its enactment history. In deploying the proposed principle, we base the formal representation on information control net theory, which can graphically and mathematically represent workflow procedures. We apply directed graph theory to formally and graphically define the work transference network model proposed in this paper. For the sake of verifying and validating the proposed concepts and algorithms, we implement a work transference network rediscovery system, and apply it to a workflow enactment event log dataset, in an experimental study. Finally, we describe the implications of discovering and rediscovering work transference networks, as a human resource management and evaluation technique, in workflow-supported enterprises and organizations.
Databáze: OpenAIRE
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