Multilevel Analysis of Employee Satisfaction on Commitment to Organizational Culture: Case Study of Chinese State-Owned Enterprises
This study analyzes the effects of employee satisfaction and demographic indicators on employee commitment to organizational culture at the enterprise level. With data from a survey of 3029 employees from 27 state-owned enterprises (SOEs), a hierarchical linear model (HLM) is used to identify the in...
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Veröffentlicht in: | Mathematical and computational applications 2017-12, Vol.22 (4), p.46 |
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Sprache: | eng |
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Zusammenfassung: | This study analyzes the effects of employee satisfaction and demographic indicators on employee commitment to organizational culture at the enterprise level. With data from a survey of 3029 employees from 27 state-owned enterprises (SOEs), a hierarchical linear model (HLM) is used to identify the influencing factors of employee commitment to organizational culture at the enterprise level. An empirical study indicates that apart from the factors of employee satisfaction and demographic background, four contextual variables of enterprises, namely, comprehensive management, energy intensity, cost-income ratio, and capacity-load ratio, also influence commitment to organizational culture levels. Results show that applying HLM can substantially improve the explanatory power of employee satisfaction factors on commitment to organizational culture using nested enterprise contextual variables. Although measurement scales and satisfaction models have been proposed over the years, only a few studies have addressed the particular nature inherent in Chinese SOEs. HLM, which accounts for the nested data structure and determines the effects of employee satisfaction factors on commitment to organizational culture without bias, is developed in this study. Through an insider view based on empirical work, this research can improve the ability of senior managers to understand the culture and dynamics of organizations, to deliver strong leadership, and to enhance corporate internal management. |
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ISSN: | 2297-8747 2297-8747 |
DOI: | 10.3390/mca22040046 |