Analyzing the Impact of Corporate Social Responsibility on Employee Satisfaction Using a Hybrid SEM-ANN Approach
Анализ влияния корпоративной социальной ответственности на удовлетворённость сотрудников с использованием гибридного подхода SEM–ANN
2025-04-29
SCID: 54.1/nt59km28
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Artificial neural networksCorporate social responsibilityEmployee satisfactionHybrid SEM-ANNStructural equation modeling
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Abstract (AI)
In the conditions of modern market dynamics, corporate social responsibility (CSR) is increasingly evolving from a formal ethical principle into a powerful strategic instrument, key to achieving sustainable growth and long-term competitive advantage. Companies that integrate CSR into their business not only affirm the values of social responsibility, but also position themselves as reliable and ethically oriented actors, thereby winning the trust of investors, motivating employees and building a stable base of loyal consumers. Hence, the aim of this research is to determine, through empirical analysis, to what extent and in what way individual aspects of corporate social responsibility influence employee perception and satisfaction, as well as to develop a predictive model of their mutual connection. The specific hybrid SEM-ANN methodology in the CSR field was applied to obtain more precise results than standard data analysis methods, which fulfilled the literature gap in this research field. The detailed hypotheses designed were empirically tested using SEM methodology and indicated a positive association between the social and stakeholder aspects with employee satisfaction. These outcomes were confirmed by the results of the ANN models. The findings obtained are not only theoretical, but also have a useful application in the real business environment, which is reflected in the development of strategies that can serve as a road map for organizations in achieving employee satisfaction. This could lead to a change in organizational culture with an emphasis on ethical business and greater responsibility towards society and stakeholders.
Key Findings
1
Artificial neural network models confirm the positive relationships identified through SEM, supporting the hybrid methodology’s findings.
2
Social and stakeholder-related CSR aspects show positive associations with employee satisfaction in the structural equation modeling analysis.
3
The findings support CSR-based organizational strategies aimed at improving employee satisfaction, ethical culture, and responsibility toward society and stakeholders.
4
The hybrid SEM-ANN approach is presented as providing more precise CSR analysis than standard analytical methods and addressing a stated literature gap.
5
The study empirically examines how distinct corporate social responsibility dimensions influence employees’ perceptions and satisfaction.
Research Object
Corporate social responsibility practices in companies and employees
Research Subject
The influence of CSR’s social and stakeholder aspects on employee perception and satisfaction, including their predictive relationship
Publication Details
Publication Date
2025-04-29
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