doi: 10.4304/jsw.5.4.369-377
Research on Knowledge-Based Optimization Model for Top Management Team
2Division of Engineering and Technology Management, National University of Singapore
Abstract—Configuration of top management team (TMT) has very important impact on its efficiency. Extant literature in the research of TMT mainly concentrates on the relationship between TMT characteristics and firm level performances as well as the process mechanism, but rarely on methods for team member selection and TMT configuration. This paper is aimed to address the research gap and design a knowledge-based optimization model for TMT configuration, using multi-objective optimization model. First of all, the relationship between TMT characteristics and its performance is systematically reviewed and a multiple-dimensional evaluation system is proposed to analyze TMT efficiency. Secondly, a multi-objective optimization model of TMT configuration is established by multiple linear regressions. Thirdly, knowledge management techniques are integrated to build the knowledge-based multiple-objective optimization model for TMT configuration. Finally, an experimental system based on our model is applied in a stationery company and achieved great success.
Index Terms—Top Management Team (TMT), knowledge-based optimization, knowledge management system, TMT configuration.
Cite: Weihui Dai, Dan Yu, Yue Yu, "Research on Knowledge-Based Optimization Model for Top Management Team," Journal of Software vol. 5, no. 4, pp. 369-377, 2010.
General Information
ISSN: 1796-217X (Online)
Abbreviated Title: J. Softw.
Frequency: Biannually
APC: 500USD
DOI: 10.17706/JSW
Editor-in-Chief: Prof. Antanas Verikas
Executive Editor: Ms. Cecilia Xie
Abstracting/ Indexing: DBLP, EBSCO,
CNKI, Google Scholar, ProQuest,
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Directory, WorldCat, etcE-mail: jsweditorialoffice@gmail.com
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