A methodology for the assessment of management development needs in industry Public Deposited

http://ir.library.oregonstate.edu/concern/graduate_thesis_or_dissertations/3x816r642

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  • The primary purpose of this study was to develop and field test a methodology for the assessment of management development needs in industry. The population used to test this methodology consisted of 113 first-line and middle management personnel in three High-Tech companies in the State of Oregon. A mail questionnaire with Likert-type scales was developed for the study. Respondents were asked to: (a) rate the importance of selected competencies to their jobs and (b) rate the extent to which the needs were being met in their companies. The discrepancies between the two categories were used to measure the actual training needs. The statistical procedures used to analyze the data were: two-way ANOVA, R-mode factor analysis, and discriminant analysis. The instrument effectively measured what it was intended to measure. Several inconsistencies between the mean rankings for "importance of competency" and "extent to which needs are being met" were identified. Significant differences were found among the three companies and two levels of management. Out of 69 F tests on the "importance of competency" category, 24 were rejected at the .05 level of significance. Six out of 69 F tests on the "extent to which needs are being met" were rejected. The Newman-Keuls multiple comparison procedure was used to further test the rejected null hypotheses. The factor analysis, R-mode procedure generated six clusters of competencies in the "importance of competency" category and seven in the "extent to which needs are being met" category. In both categories, competencies related to productivity issues formed the first factors and accounted for high percentages of the common variance. The discriminant analysis procedure classified 76.58 percent of the respondents in the "importance of competency" category and 78 percent in the "extent to which needs are being met" category into the companies to which they actually belonged. Out of 23 variables, 7 were identified as discriminant variables in each category.
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  • 1986
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