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

Muhammad Hatim Binsawad

doi:10.1109/access.2020.2972225

Muhammad Hatim Binsawad

Open Access

https://doi.org/10.1109/access.2020.2972225

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Journal: IEEE Access	Publication Date: Jan 1, 2020
Citations: 61	License type: CC BY 4.0

Affiliation: King Abdulaziz University

Abstract

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.

Highlights

Understanding and addressing corporate social responsibility (CSR) is advised for any kind of business or organization [1]
DISCUSSIONS, IMPLICATONS AND CONCLUSION The study shows that the two-step approach (PLS-SEM and Artificial Neural Network (ANN)) offer in-depth findings compared to single step Partial Least Squares- Structural Equation Modelling (PLS-SEM) method
There are some nominal differences, which are due to the non-linear nature and the high prediction accuracy of the ANN model

Summary

Introduction

Understanding and addressing corporate social responsibility (CSR) is advised for any kind of business or organization [1]. It is suggested that CSR can be of great assistance in invigorating the competitivity and operations of an organization, given that global competitivity keeps following remarkable trends [2]. CSR has been accepted and become prominent as a business tool; it is thought to elevate social development [3]. In order to maintain competitiveness, managers should come up with ways their organizations can develop economic competitiveness, ecological sustainability and social responsibility [2], [3]. If an organization makes efforts towards social responsibility, there are benefits for both the organization and society [3].

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