Multigranulation rough set model in hesitant fuzzy information systems and its application in person-job fit
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ORIGINAL ARTICLE
Multigranulation rough set model in hesitant fuzzy information systems and its application in person‑job fit Chao Zhang1 · Deyu Li1 · Yanhui Zhai1 · Yuanhao Yang2 Received: 12 December 2016 / Accepted: 29 November 2017 © Springer-Verlag GmbH Germany, part of Springer Nature 2017
Abstract Person-job fit is a significant issue in the variety of critical business intelligence applications that aims to match suitable professional abilities with job demands for each job seeker, and many studies based on fuzzy sets have been developed on this topic. Among different types of fuzzy sets, hesitant fuzzy sets are usually utilized to handle situations in which experts hesitate among several values to evaluate an alternative. Recently, various hesitant fuzzy decision making methods have been established, but none of them can be used to solve group decision making problems by means of the multigranulation rough set model and the TODIM (an acronym in Portuguese of interactive and multi-criteria decision making) approach. Thus, to solve problems of hesitant fuzzy information analysis and group decision making for person-job fit, we construct a new multigranulation rough set model, named hesitant fuzzy multigranulation rough sets, through combining hesitant fuzzy sets with multigranulation rough sets. Then in order to express the decision making knowledge base more reasonably, we extend the proposed model from single universe to two universes. At last, by utilizing the TODIM approach, we propose a general decision making method that is applied to person-job fit, and the effectiveness of the proposed decision making method is demonstrated by a case study. Keywords Hesitant fuzzy sets · Group decision making · Hesitant fuzzy multigranulation rough sets · TODIM · Person-job fit
1 Introduction With the increasingly fierce competition in many business domains, person-job fit, which refers to the relation between employee characteristics and job characteristics, tends to exert an ever-growing influence on the market success of various firms. Moreover, it is generally believed that personjob fit reduces turnover intention and increases organizational commitment [8]. To cope with this complicated decision making problem, many scholars have constructed the relation between the set of job demands and the set of job seeker’s actual skills. Particularly, due to the management, * Deyu Li [email protected] 1
Key Laboratory of Computational Intelligence and Chinese Information Processing of Ministry of Education, School of Computer and Information Technology, Shanxi University, Taiyuan 030006, Shanxi, China
Statistical and Genomic Epidemiology Laboratory, Institute of Health and Biomedical Innovation, Brisbane, Australia
2
storage and extraction of various useful information available to job seekers is not always presented as crisp data, it is acknowledged that fuzzy approaches own many advantages for dealing with uncertain situations in person-job fit. Within the framework of fuzzy sets [35], the membership degree o
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