4.5 Article

Identifying the Component Structure of Satisfaction Scales by Nonlinear Principal Components Analysis

Journal

QUALITY TECHNOLOGY AND QUANTITATIVE MANAGEMENT
Volume 7, Issue 2, Pages 97-115

Publisher

NCTU-NATIONAL CHIAO TUNG UNIV PRESS
DOI: 10.1080/16843703.2010.11673222

Keywords

CATPCA; Herzberg; monotonic transformations; multiple group method; nonlinear principal components analysis; satisfaction survey data; scale construction

Funding

  1. Netherlands Organization for Scientific Research [451-02-058]

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The component structure of 14 Likert-type items measuring different aspects of job satisfaction was investigated using nonlinear Principal Components Analysis (NLPCA). NLPCA allows for analyzing these items at an ordinal or interval level. The participants were 2066 workers from five types of social service organizations. Our results suggest that taking into account the ordinal nature of the items was most appropriate. On the basis of a stability study, a two-component structure was found, from which we extracted two subscales (Motivation and Hygiene) with reliabilities of .81 and .77. A Multiple Group analysis confirmed this structure. We also investigated whether workers in the five types of organizations differed with respect to the component structure, employing a feature of the program CATPCA. We found that the organizations did not differ much with respect to the job satisfaction components.

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