| Summary: | 碩士 === 國立臺灣科技大學 === 工業管理系 === 90 === Job analysis data is central to effectively managing the human resource of an organization, including recruiting, selection, training, and personnel development, performance evaluation, and wage and salary administration. The current study created a database containing the job sample of 907 job titles from the Employment and Vocational Training Administration. For each job title, 79 specific variables, falling in six major classes (required education and experience, talent, interest, worker''''s characteristics, physical demands, task environment) will be coded for the job analysis database.
Factor analysis and multiple regression analysis were applied to derive the wage determinants for predicting the average wage level of professionals, technical, clerical, service, farm, and craft workers, operatives, and other workers. For each job title, 79 job analysis variables were factor analyzed, using principal components analysis with Varimax rotation. The 9-factor (occupational hazard, verbal communication education and training, visual acuity, body agility, and manual ability) solution explained 58.4% of the variance. Multiple regression analysis was then applied to determine the equation for predicting the average wage level for various types of workers based on the critical job factors. The result indicated that education, experience and professional certificate, experience, and training) were found to be highly correlated with the average wage and salary of 907 job titles. The results can be utilized by the human resource department for the development of wage and salary policies.
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