期刊
JOURNAL OF THE OPERATIONAL RESEARCH SOCIETY
卷 69, 期 9, 页码 1435-1444出版社
TAYLOR & FRANCIS LTD
DOI: 10.1080/01605682.2017.1398203
关键词
Multi-criteria group decision-making; analytical hierarchy process; experts' weights; investment decision-making
资金
- National Natural Science Foundation of China [71433001, 71725001, 71471149, 71325001]
- Less Developed Regions of the National Natural Science Foundation of China [71761014]
- 13th five-year plan for the development of philosophy and social sciences of guangzhou [2017GZZK53]
- National Social Science Foundation of China [15ZDB153]
- Youth Science and Technology Project of Department of Education of Jiangxi Province [GJJ150512]
- Education Science Thirteen Five Plan of Jiangxi Province [16ZD019]
- 2016 Soft Science Research Project of Jiangxi Province [20161BBA10081]
- 2016 National Statistical Science Research Project [2016416]
- Postdoctoral Science Foundation Project of China [160448]
- [2003414092]
- [2700050384]
In this paper, we investigate group decision-making in a multi-criteria complex environment using an analytical hierarchy process (AHP) seeking to solve the problem of how to effectively aggregate individual preferences to reach a group consensus. Currently, the two methods considered most useful for aggregating individual preferences are the aggregation of individual judgments (AIJ) and the aggregation of individual priorities (AIP). These two aggregation methods involve two independent stages, which disconnect the processes from each other, and the relationship between the two has not yet been researched. Besides, the authorities of different experts can vary, as they are restricted by the individuals' expertise and experiences as well as the complexity of real-world applications. In this article, a new consensus facilitation model for AHP group decision-making that takes into account experts' weights, called EWAHP-GDM, is established to address these aspects. In this model, two aggregation methods are unified and integrated in group decision-making with AHP. We present the quantification steps for the experts' weights and conduct an empirical analysis to verify our model by comparing it with four classic models/methods. The numerical results demonstrate that our model can provide effective investment strategy selection in investment decision-making.
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