Mission-Critical Group Decision-Making: Solving the Problem of Decision Preference Change in Group Decision-Making Using Markov Chain Model

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Author(s): Huizhang Shen (Shanghai Jiaotong University, China), Jidi Zhao (University of New Brunswick, Canada)and Wayne W. Huang (Ohio University, USA)
Copyright: 2010
Pages: 24
Source title: Technological Advancement in Developed and Developing Countries: Discoveries in Global Information Management
Source Author(s)/Editor(s): M. Gordon Hunter (University of Lethbridge, Canada)and Felix B. Tan (Auckland University of Technology, New Zealand)
DOI: 10.4018/978-1-60566-920-5.ch016

Keywords: Digital Divide & Developing Countries / Engineering Science Reference / Global Information Technology / Government & Law

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Abstract

Review on group decision support systems (GDSS) indicates that traditional GDSS are not specifically designed to support mission-critical group decision-making tasks that require group decision-making to be made effectively within short time. In addition, prior studies in the research literature have not considered group decision preference adjustment as a continuous process and neglected its impact on group decision-making. In reality, group members may dynamically change their decision preferences during group decision-making process. This dynamic adjustment of decision preferences may continue until a group reaches consensus on final decision. This article intends to address this neglected group decision-making research issue in the literature by proposing a new approach based on the Markov chain model. Furthermore, a new group decision weight allocation approach is also suggested. A real case example of New Orleans Hurricane Katrina is used to illustrate the usefulness and effectiveness of the proposed approaches. Finally, the article concludes with the discussion on the proposed approaches and presents directions for future research.

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Mission-Critical Group Decision-Making: Solving the Problem of Decision Preference Change in Group Decision-Making Using Markov Chain Model

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