A discussion on domain modeling in an example of motivation-based human resource management

Keiichi Ishibashi, Masaaki Hashimoto, Keiichi Katamine, Ryoma Shiratsuchi, Keita Asaine, Takako Nakatani, Naoyasu Ubayashi, Yoshihiro Akiyama

Research output: Chapter in Book/Report/Conference proceedingConference contribution

3 Citations (Scopus)

Abstract

This paper proposes a domain model comprising a static model, dynamic model and scenario generation method for providing a foundation for motivation-based human resource management. One of the main concerns of managers when establishing a management method in an organization, is the individual members' motivation for the method. It is, however, difficult to manage the members' motivation, because the human resource is very complicated. We therefore, propose a domain model by applying Lawler's motivation model. Using this model, we analyze an actual example of successfully establishing CCPM (Critical Chain Project Management) in a company. We discuss primarily the stability of states, motivation, understanding of individuals' roles and their relationship.

Original languageEnglish
Title of host publicationKnowledge-Based Software Engineering. Proceedings of the Eighth Joint Conference on Knowledge-Based Software Engineering
PublisherIOS Press
Pages32-41
Number of pages10
Edition1
ISBN (Print)9781586039004
DOIs
Publication statusPublished - Jan 1 2008
Externally publishedYes

Publication series

NameFrontiers in Artificial Intelligence and Applications
Number1
Volume180
ISSN (Print)0922-6389

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All Science Journal Classification (ASJC) codes

  • Artificial Intelligence

Cite this

Ishibashi, K., Hashimoto, M., Katamine, K., Shiratsuchi, R., Asaine, K., Nakatani, T., ... Akiyama, Y. (2008). A discussion on domain modeling in an example of motivation-based human resource management. In Knowledge-Based Software Engineering. Proceedings of the Eighth Joint Conference on Knowledge-Based Software Engineering (1 ed., pp. 32-41). (Frontiers in Artificial Intelligence and Applications; Vol. 180, No. 1). IOS Press. https://doi.org/10.3233/978-1-58603-900-4-32