Skip to main content
placeholder image

Team situation awareness measure using semantic utility functions for supporting dynamic decision-making

Journal Article


Abstract


  • Team decision-making is a remarkable feature in a complex dynamic decision environment, which can be supported by team situation awareness. In this paper, a team situation awareness measure (TSAM) method using a semantic utility function is proposed. The semantic utility function is used to clarify the semantics of qualitative information expressed in linguistic terms. The individual and team situation awareness are treated as linguistic possibility distributions on the potential decisions in a dynamic decision environment. In the TSAM method, team situation awareness is generated through reasoning and aggregating individual situation awareness based on a multi-level hierarchy mental model of the team. Individual and team mental models are composed of key drivers and significant variables. An illustrative example in telecoms customer churn prediction is given to explain the effectiveness and the main steps of the TSAM method.

Authors


  •   Ma, Jun
  •   Lu, Jie (external author)
  •   Zhang, Guangquan (external author)

Publication Date


  • 2010

Citation


  • Ma, J., Lu, J. & Zhang, G. (2010). Team situation awareness measure using semantic utility functions for supporting dynamic decision-making. Soft Computing, 14 (12), 1305-1316.

Scopus Eid


  • 2-s2.0-77954688687

Number Of Pages


  • 11

Start Page


  • 1305

End Page


  • 1316

Volume


  • 14

Issue


  • 12

Abstract


  • Team decision-making is a remarkable feature in a complex dynamic decision environment, which can be supported by team situation awareness. In this paper, a team situation awareness measure (TSAM) method using a semantic utility function is proposed. The semantic utility function is used to clarify the semantics of qualitative information expressed in linguistic terms. The individual and team situation awareness are treated as linguistic possibility distributions on the potential decisions in a dynamic decision environment. In the TSAM method, team situation awareness is generated through reasoning and aggregating individual situation awareness based on a multi-level hierarchy mental model of the team. Individual and team mental models are composed of key drivers and significant variables. An illustrative example in telecoms customer churn prediction is given to explain the effectiveness and the main steps of the TSAM method.

Authors


  •   Ma, Jun
  •   Lu, Jie (external author)
  •   Zhang, Guangquan (external author)

Publication Date


  • 2010

Citation


  • Ma, J., Lu, J. & Zhang, G. (2010). Team situation awareness measure using semantic utility functions for supporting dynamic decision-making. Soft Computing, 14 (12), 1305-1316.

Scopus Eid


  • 2-s2.0-77954688687

Number Of Pages


  • 11

Start Page


  • 1305

End Page


  • 1316

Volume


  • 14

Issue


  • 12