[논문]A Theoretical Framework for Closeness Centralization Measurements in a Workflow-Supported Organization

Kim, Min-Joon; Ahn, Hyun; Park, Min-Jae

doi:10.3837/tiis.2015.09.018

A Theoretical Framework for Closeness Centralization Measurements in a Workflow-Supported Organization 원문보기

KSII Transactions on internet and information systems : TIIS, v.9 no.9, 2015년, pp.3611 - 3634

Kim, Min-Joon (School of Integrated Technology, YONSEI UNIVERSITY) , Ahn, Hyun (Department of Computer Science, KYONGGI UNIVERSITY) , Park, Min-Jae (Engineering Innovation Department, R&D Center, BISTel, INC.)

Abstract ▼ AI-Helper

In this paper, we build a theoretical framework for quantitatively measuring and graphically representing the degrees of closeness centralization among performers assigned to enact a workflow procedure. The degree of closeness centralization of a workflow-performer reflects how near the performer is to the other performers in enacting a corresponding workflow model designed for workflow-supported organizational operations. The proposed framework comprises three procedural phases and four functional transformations, such as discovery, analysis, and quantitation phases, which carry out ICN-to-WsoN, WsoN-to-SocioMatrix, SocioMatrix-to-DistanceMatrix, and DistanceMatrix-to-CCV transformations. We develop a series of algorithmic formalisms for the procedural phases and their transformative functionalities, and verify the proposed framework through an operational example. Finally, we expatiate on the functional expansion of the closeness centralization formulas so as for the theoretical framework to handle a group of workflow procedures (or a workflow package) with organization-wide workflow-performers.

주제어

AI 본문요약
AI-Helper

제안 방법

The centrality technique is subdivided into degree-centrality [13], closeness-centrality [12,20], betweenness-centrality [21], and eigenvalue-centrality so as to be elaborately applied into a real organizational world. As one of those efforts, in this paper, we have tried to conceive the algorithmic and procedural framework of closeness centralization measurements and suggested a theoretical guidance to quantitatively analyze and compare the degrees of closeness and prominence among workflow-performers in enacting a workflow procedure.
Our key contribution in this paper is to propose a theoretical framework and its related formalisms for measuring how much close to other workflow-performers by using the social network analysis techniques, particularly the closeness centrality analysis formulas [5]. The centralization of workflow-performers is a typical social network analysis technique identifying the important or prominent performers within a workflow procedure by summarizing the structural relationships among all the performers.
The physical-level abstract of a workflow procedure represents the architectural distribution of its activities in realizing a workflow management system. The scope of this paper conceives a series of theoretical formalisms related with conceptual-level abstract of the workflow model, particularly focusing on the performer-dependency aspect. Recently, workflow modeling techniques [1], organizational intelligence techniques [3, 4], and social network analysis techniques [5] are converging on “workflow-supported people,” which starts from the strong belief that social relationships and collaborative behaviors among people, who are involved in enacting a workflow procedure, affect the overall performance as well as the degrees of working productivity in performing the real business operations under the control of workflow-supported organizations [6].

성능/효과

At this moment, it is important to emphasize that the proposed framework for the closeness centralization measurements of workflow-supported org-social networks be simply not in theoretical formulas but in algorithmic formulas. Through the theoretical framework, so, we can straightforwardly implement an automatic discovery, analysis, and visualization system for the closeness centralization measurements as well as for workflow-supported org-social networking knowledge management and intelligence.
At this moment, it is important to emphasize that the proposed framework for the closeness centralization measurements of workflow-supported org-social networks be simply not in theoretical formulas but in algorithmic formulas. Through the theoretical framework, so, we can straightforwardly implement an automatic discovery, analysis, and visualization system for the closeness centralization measurements as well as for workflow-supported org-social networking knowledge management and intelligence. Likewise, as future works, we need not only to elaborate on the functional expansion of the closeness centralization formulas so as for the theoretical framework to handle a group of workflow procedures (or a workflow package) with organization-wide workflow-performers, but also to develop the remainder centrality analysis techniques, like betweenness and eigenvalue centralities, to be applied to workflow-supported org-social networks.

후속연구

Through the theoretical framework, so, we can straightforwardly implement an automatic discovery, analysis, and visualization system for the closeness centralization measurements as well as for workflow-supported org-social networking knowledge management and intelligence. Likewise, as future works, we need not only to elaborate on the functional expansion of the closeness centralization formulas so as for the theoretical framework to handle a group of workflow procedures (or a workflow package) with organization-wide workflow-performers, but also to develop the remainder centrality analysis techniques, like betweenness and eigenvalue centralities, to be applied to workflow-supported org-social networks.

참고문헌 (25)

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상세보기
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