Possibilistic regression analysis of influential factors for occupational health and safety management systems

Azizul Azhar Ramli, Junzo Watada, Witold Pedrycz

    Research output: Contribution to journalArticle

    19 Citations (Scopus)

    Abstract

    The code of occupational health and safety (OHS) is an influential regulation to improve the on-the-job safety of employees. A number of factors influence the planning and implementation of OHS management systems (OHSMS). The evaluation of OHSMS practice is the most important component when forming a health and safety environmental policy for employees. The objective of this research is to develop an intelligent data analysis (IDA) in which possibilistic regression being endowed with a convex hull approach is used to support the analysis of essential factors that influence OHSMS. Given such subjective terms, the obtained samples can be conveniently regarded as fuzzy input/output data represented by membership functions. The study offers this vehicle of intelligent data analysis as an alternative to evaluate the influential factors in a successful implementation of OHS policies and in this way decrease an overall computational effort. The obtained results show that several related OHSMS influential factors need to be carefully considered to facilitate a successful implementation of the OHSMS procedure.

    Original languageEnglish
    Pages (from-to)1110-1117
    Number of pages8
    JournalSafety Science
    Volume49
    Issue number8-9
    DOIs
    Publication statusPublished - 2011 Oct

    Fingerprint

    Safety Management
    Occupational Health
    Regression analysis
    regression analysis
    Regression Analysis
    Health
    health
    management
    on-the-job safety
    data analysis
    employee
    Personnel
    Codes (standards)
    Environmental Policy
    Safety
    Membership functions
    environmental policy
    Practice Management
    Health Policy
    Statistical Factor Analysis

    Keywords

    • Intelligent data analysis
    • Occupational health and safety management systems
    • Possibilistic regression analysis

    ASJC Scopus subject areas

    • Safety Research
    • Public Health, Environmental and Occupational Health
    • Safety, Risk, Reliability and Quality

    Cite this

    Possibilistic regression analysis of influential factors for occupational health and safety management systems. / Ramli, Azizul Azhar; Watada, Junzo; Pedrycz, Witold.

    In: Safety Science, Vol. 49, No. 8-9, 10.2011, p. 1110-1117.

    Research output: Contribution to journalArticle

    Ramli, Azizul Azhar ; Watada, Junzo ; Pedrycz, Witold. / Possibilistic regression analysis of influential factors for occupational health and safety management systems. In: Safety Science. 2011 ; Vol. 49, No. 8-9. pp. 1110-1117.
    @article{73af199700f64dc39d71625264091969,
    title = "Possibilistic regression analysis of influential factors for occupational health and safety management systems",
    abstract = "The code of occupational health and safety (OHS) is an influential regulation to improve the on-the-job safety of employees. A number of factors influence the planning and implementation of OHS management systems (OHSMS). The evaluation of OHSMS practice is the most important component when forming a health and safety environmental policy for employees. The objective of this research is to develop an intelligent data analysis (IDA) in which possibilistic regression being endowed with a convex hull approach is used to support the analysis of essential factors that influence OHSMS. Given such subjective terms, the obtained samples can be conveniently regarded as fuzzy input/output data represented by membership functions. The study offers this vehicle of intelligent data analysis as an alternative to evaluate the influential factors in a successful implementation of OHS policies and in this way decrease an overall computational effort. The obtained results show that several related OHSMS influential factors need to be carefully considered to facilitate a successful implementation of the OHSMS procedure.",
    keywords = "Intelligent data analysis, Occupational health and safety management systems, Possibilistic regression analysis",
    author = "Ramli, {Azizul Azhar} and Junzo Watada and Witold Pedrycz",
    year = "2011",
    month = "10",
    doi = "10.1016/j.ssci.2011.02.014",
    language = "English",
    volume = "49",
    pages = "1110--1117",
    journal = "Safety Science",
    issn = "0925-7535",
    publisher = "Elsevier",
    number = "8-9",

    }

    TY - JOUR

    T1 - Possibilistic regression analysis of influential factors for occupational health and safety management systems

    AU - Ramli, Azizul Azhar

    AU - Watada, Junzo

    AU - Pedrycz, Witold

    PY - 2011/10

    Y1 - 2011/10

    N2 - The code of occupational health and safety (OHS) is an influential regulation to improve the on-the-job safety of employees. A number of factors influence the planning and implementation of OHS management systems (OHSMS). The evaluation of OHSMS practice is the most important component when forming a health and safety environmental policy for employees. The objective of this research is to develop an intelligent data analysis (IDA) in which possibilistic regression being endowed with a convex hull approach is used to support the analysis of essential factors that influence OHSMS. Given such subjective terms, the obtained samples can be conveniently regarded as fuzzy input/output data represented by membership functions. The study offers this vehicle of intelligent data analysis as an alternative to evaluate the influential factors in a successful implementation of OHS policies and in this way decrease an overall computational effort. The obtained results show that several related OHSMS influential factors need to be carefully considered to facilitate a successful implementation of the OHSMS procedure.

    AB - The code of occupational health and safety (OHS) is an influential regulation to improve the on-the-job safety of employees. A number of factors influence the planning and implementation of OHS management systems (OHSMS). The evaluation of OHSMS practice is the most important component when forming a health and safety environmental policy for employees. The objective of this research is to develop an intelligent data analysis (IDA) in which possibilistic regression being endowed with a convex hull approach is used to support the analysis of essential factors that influence OHSMS. Given such subjective terms, the obtained samples can be conveniently regarded as fuzzy input/output data represented by membership functions. The study offers this vehicle of intelligent data analysis as an alternative to evaluate the influential factors in a successful implementation of OHS policies and in this way decrease an overall computational effort. The obtained results show that several related OHSMS influential factors need to be carefully considered to facilitate a successful implementation of the OHSMS procedure.

    KW - Intelligent data analysis

    KW - Occupational health and safety management systems

    KW - Possibilistic regression analysis

    UR - http://www.scopus.com/inward/record.url?scp=79958152723&partnerID=8YFLogxK

    UR - http://www.scopus.com/inward/citedby.url?scp=79958152723&partnerID=8YFLogxK

    U2 - 10.1016/j.ssci.2011.02.014

    DO - 10.1016/j.ssci.2011.02.014

    M3 - Article

    VL - 49

    SP - 1110

    EP - 1117

    JO - Safety Science

    JF - Safety Science

    SN - 0925-7535

    IS - 8-9

    ER -