With management practice problems becoming more and more complex, the large-group decision making based on modern information technology has been a noteworthy research topic recently. The large-group decision making may be influenced by expert's knowledge structure,which is not considered in existing methods. In order to solve above problem, the properties and characteristics are described and defined from three perspectives such as territoriality, incompleteness and reliability, and the mechanism for extracting incomplete inference information is presented by applying basic belief assignment function. Then the methods and theorems are constructed for fusing inference information of individual expert and expert's group respectively with compensatory strategy and non-compensatory strategy, both of which are technologically based on evidence reasoning rule. The procedure of multiple attribute large-group decision-making method with incomplete information by considering expert's knowledge structure is proposed by following the fusion thought that "from individual fusion to group fusion". The numerical comparison analysis shows the proposed method is scientific and effective finally. The innovation points of the proposed method are not only to reflect the influences by expert's knowledge structure within the mechanism for extracting incomplete inference information, but also to distinguish the differences between expert reliabilities and attribute weights and reflect the compensatory among attributes and the non-compensatory among experts. This will play an important supporting role in improving and ensuring the efficiency and effectiveness of large group decision making.
DU Yuan-wei, WANG Su-su, YANG Ning, ZHOU Wen
. Multiple Attribute Large-group Decision-making Method with Incomplete Information by Considering Expert's Knowledge Structure[J]. Chinese Journal of Management Science, 2017
, 25(12)
: 167
-178
.
DOI: 10.16381/j.cnki.issn1003-207x.2017.12.018
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