Logarithmic least squares fuzzy model for pairwise comparison of nurse performance evaluation

Kaoru Kuramoto, Takahiro Ohno

    Research output: Contribution to journalArticle

    Abstract

    We proposed a "basic model" logarithmic least squares fuzzy model for the pairwise comparison of nurse performance evaluation to reflect the effects of an evaluator's personal preferences and the rate scale used. In this study, we propose a new tranquility model for determining the evaluation elemental membership value estimated from the basic model. First, it involves the gathering of basic checklist data of nurse capability and paired comparison data from a single hospital in Fukushima Prefecture, from which we estimate the essential parameters (each evaluation element's weight wj, evaluation phase k's membership value fk, overall evaluated value Zi) using the basic model. Second, we define Fri as k's membership value in the overall evaluation phase and Ari as the overall evaluation value of the analytic hierarchy process. We then calculate the Kullback-Leibler divergence between Fri and Ari and between Zi and Ari to consider the adequacy of the basic model. Moreover, we estimate the priority of nurse capabilities that should be emphasized using MRTQ, MTQ-1, and MTQ-2 in development of suggestions made in our previous work to consider the adequacy of our model.

    Original languageEnglish
    Pages (from-to)251-258
    Number of pages8
    JournalJournal of Japan Industrial Management Association
    Volume68
    Issue number4E
    DOIs
    Publication statusPublished - 2017 Jan 1

    Keywords

    • Ahp
    • Kullback-Leibler divergence
    • MRTQ
    • Tranquility

    ASJC Scopus subject areas

    • Strategy and Management
    • Management Science and Operations Research
    • Industrial and Manufacturing Engineering
    • Applied Mathematics

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