Corporate Social Responsibility in Higher Education: A PLS-SEM Neural Network Approach

被引:23
|
作者
Binsawad, Muhammad Hatim [1 ]
机构
[1] King Abdulaziz Univ, Dept Comp Informat Syst, Jeddah 21589, Saudi Arabia
来源
IEEE ACCESS | 2020年 / 8卷
关键词
ANN; corporate social responsibility; education; PLS SEM; Saudi Arabia; MODEL;
D O I
10.1109/ACCESS.2020.2972225
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Corporate social responsibility (CSR) has become vital to the competitiveness of organizations. However, there is very limited research on CSR in the context of higher education. Therefore, this study investigates the impact of CSR factors on the university competitiveness with other universities. The contribution of this study includes applying a multi-analytical methodology by applying Partial Least Squares- Structural Equation Modelling (PLS-SEM) and Artificial Neural Network (ANN). First, PLS-SEM analysis was applied to measure which CSR factor has the most significant influence on the increased competitiveness of Saudi Arabian universities. Then, an ANN model analysis was applied to rank the relative influence of the significant CSR factors attained from the PLS-SEM analysis. The findings show that the CSR factors such as market-oriented CSR activities, society-oriented CSR activities and workforce-oriented CSR activities have a significant positive impact on increased competitiveness of Saudi Arabian universities. However, based on the ANN findings, society-oriented CSR is the most significant predictor of a university;s increased competitiveness, followed by workforce-oriented CSR and finally by market-oriented CSR. The practical implications of this study provide Saudi universities to focus on society-oriented CSR to maintain and sustain their competitive advantage over other universities.
引用
收藏
页码:29125 / 29131
页数:7
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