ASIA unversity:Item 310904400/10070
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    Please use this identifier to cite or link to this item: http://asiair.asia.edu.tw/ir/handle/310904400/10070


    Title: Job Compensable factors and factor weights derived using job analysis data
    Authors: Chia-Fen Chi;Tin-Chang Chang;Jen-Chieh Song
    Contributors: 亞洲大學經營管理學系
    Date: 2006
    Issue Date: 2010-06-10 11:53:31 (UTC+8)
    Publisher: Asia University
    Abstract: Government data on 1,039 job titles in Taiwan were analyzed to assess possible relationships between job attributes and compensation. For each job title, 79 specific variables in six major classes (required education and experience, aptitude, interest, work temperament, physical demands, task environment) were coded to derive the statistical predictors of wage for managers, professionals, technical, clerical, service, farm, craft, operatives, and other workers. Of the 79 variables, only 23 significantly related to pay rate were subjected to a factor and multiple regression analysis for predicting monthly wages. Given the heterogeneous nature of collected job titles, a 4-factor solution (occupational knowledge and skills, human relations skills, work schedule hardships, physical hardships) explaining 43.8% of the total variance but predicting only 23.7% of the monthly pay rate was derived. On the other hand, multiple regression with 9 job analysis items (required education, professional training, professional certificate, professional experience, coordinating, leadership and directing, demand on hearing, proportion of shift working indoors, outdoors and others, rotating shift) better predicted pay and explained 32.5% of the variance. A direct comparison of factors and subfactors of job evaluation plans indicated mental effort and responsibility (accountability) had not been measured with the current job analysis data. Cross-validation of job evaluation factors and ratings with the wage rates is required to calibrate both.
    Relation: Perceptual and Motor Skills,104:1193-1204.
    Appears in Collections:[Department of Business Administration] Journal Article

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