Interval-valued 2-tuple hesitant fuzzy linguistic term set and its application in multiple attribute decision making

[EN] The hesitant fuzzy linguistic term sets can retain the completeness of linguistic information elicitation by assigning a set of possible linguistic terms to a qualitative variable. However, sometimes experts cannot make sure that the objects attain these possible linguistic terms but only provide the degrees of confidence to express their hesitant cognition. Given that the interval numbers can denote the possible membership degrees that an object belongs to a set, it is suitable and convenient to provide an interval-valued index to measure the degree of a linguistic variable to a given hesitant fuzzy linguistic term set. Inspired by this idea, we introduce the concept of interval-valued 2-tuple hesitant fuzzy linguistic term set (IV2THFLTS) based on the interval number and the hesitant fuzzy linguistic term set. Then, we define some interval-valued 2-tuple hesitant fuzzy linguistic aggregation operators. Afterwards, to overcome the instability of subjective weights, we propose a method to compute the weights of attributes. For the convenience of application, a method is given to solve the multiple attribute decision making problems with IV2THFLTSs. Finally, a case study is carried out to validate the proposed method, and some comparisons with other methods are given to show the advantages of the proposed method.The work was supported in part by the National Natural Science Foundation of China (Nos. 71501135, 71771156), the China Postdoctoral Science Foundation (2016T90863, 2016M602698), the Fundamental Research Funds for the central Universities (No. YJ201535), and the Scientific Research Foundation for Excellent Young Scholars at Sichuan University (No. 2016SCU04A23).Si, G.; Liao, H.; Yu, D.; Llopis Albert, C. (2018). Interval-valued 2-tuple hesitant fuzzy linguistic term set and its application in multiple attribute decision making. Journal of Intelligent & Fuzzy Systems. 34(6):4225-4236. https://doi.org/10.3233/JIFS-171967S4225423634

Maturity assessment of social customer knowledge management (SCKM) using fuzzy expert system

Organizations which provide electronic services do not have a logically structured strategy for implementing Customer Knowledge Management through Social media (SCKM). By assessing the position of SCKM, organizations can have a clear understanding of their maturity level and find their future investment interests. This research examined the maturity assessment of SCKM utilizing a fuzzy expert system. It consisted of a-four-stage procedure. The maturity model is based on 11 critical success factors, including strategy, leadership, information technology, knowledge management, culture, process, resources, business intelligence, security, social customer, and assessment. Results showed that the studied organization has covered 48.2% of maturity on the first level and 51.8% on the second level. Thus, to increase productivity, it is indispensable for organizations to act in a targeted way. The fuzzy expert system is not designed specifically for a case study, but can be utilized as a reference for in-depth analysis of the organizational readiness for SCKM implementation and development within organizations, which provide e-services applications