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A Fuzzy Collaborative Assessment Methodology for Partner Trust Evaluation
Author(s) -
Ayadi Omar,
Halouani Nesrin,
Masmoudi Faouzi
Publication year - 2016
Publication title -
international journal of intelligent systems
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.291
H-Index - 87
eISSN - 1098-111X
pISSN - 0884-8173
DOI - 10.1002/int.21791
Subject(s) - comity , computer science , fuzzy logic , objectivity (philosophy) , context (archaeology) , ranking (information retrieval) , fuzzy set , knowledge management , information retrieval , artificial intelligence , paleontology , philosophy , epistemology , political science , law , biology , jurisdiction
Trust level assessment within collaborative networks is an interesting issue in the partner evaluation and partner selection literature. This paper proposes a fuzzy collaborative assessment methodology for partner trust evaluation within horizontal collaborative networks. The proposed approach concerns a group evaluation context where a decision‐making comity associated with a manufacturer needs to evaluate its company's partners for their ranking purposes. Different expertise levels are attributed to the comity members. In this paper, trust level is evaluated based on information‐sharing attributes considered in the literature as critical influencing factors. Different weights are associated with these attributes with respect to their corresponding influence on trust. The semantic fuzzy partitioning method is considered for the collaborative trust assessment based on unbalanced linguistic term sets representing information‐sharing attributes. The developed approach is applied to a real case showing its effectiveness and its objectivity.