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Impact of individual and organizational factors on job satisfaction: A comparison of multilevel models and multiple regression models using different data arrangements

Published online by Cambridge University Press:  07 October 2013

Jun Yi Hsieh
Jun Yi Hsieh*
Affiliation:
Department of Public Affairs, University of Taipei, Taipei, Taiwan
*
Corresponding author: [email protected]
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Abstract

Typically most studies of individual employees perceptions of the work place adopt multiple regression models (ordinary least squares [OLS]) which ignore inherent clustering in their data. However, such an approach does not supply unbiased and accurate answers to research questions. This study intends to simulate three data alternatives – weighted, disaggregated (individual level), and aggregated (organizational level) using the OLS and multilevel models to compare the results of different research designs. To answer the research questions, the current study investigates the impact of individual and organizational factors on job satisfaction, using a 2000 USA National Partnership for Reinventing Government survey. This study presents the methodological misuse and measurement errors of the previous research and presents guidelines for future research.

Keywords

multiple regression modelmultilevel modelaggregationjob satisfactionpublic employee
Type
Methodology
Information
Journal of Management & Organization , Volume 19 , Issue 1 , January 2013 , pp. 44 - 59
Copyright
Copyright © Cambridge University Press and Australian and New Zealand Academy of Management 2013 

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