International Journal of Supply Chain Management
Vol 8, No 1 (2019): International Journal of Supply Chain Management (IJSCM)

Decision Tree and Ordinal Logistic Regression Methods for Maintaining University Sutainability

Siew Chin Teoh (Universiti Utara Malaysia)
Mohammed Syazwan Mohd Shokri (Universiti Utara Malaysia)
Rosshairy Abd. Rahman (Universiti Utara Malaysia)



Article Info

Publish Date
27 Feb 2019

Abstract

Recently, there are lots of cases regarding the use of fake account and cyberbullying. The irresponsible attitude is badly affecting the motivation of individual who being attacked and ruining the reputation of organization involved. This study is conducted among university students that aims to determine the factors of choosing fake account as a medium to raise an issue and to identify the impact of cyberbullying towards university’s reputation. About 380 samples were taken from undergraduate and postgraduate students. The data was analyzed using Decision Tree and Ordinal Logistic Regression (ORD) methods. The results show that there are students who have experienced cyberbullying or cyber victimization, which caused by the lack of parental support. The analysis from ORD method shows that fake account could affect university’s reputation. Hence, this research hopefully capable to create awareness among university students and help them to proudly present their university’s great name throughout the world. This is important to ensure the sustainability of community and university.

Copyrights © 2019






Journal Info

Abbrev

IJSCM

Publisher

Subject

Decision Sciences, Operations Research & Management Engineering Environmental Science Industrial & Manufacturing Engineering Transportation

Description

International Journal of Supply Chain Management (IJSCM) is a peer-reviewed indexed journal, ISSN: 2050-7399 (Online), 2051-3771 (Print), that publishes original, high quality, supply chain management empirical research that will have a significant impact on SCM theory and practice. Manuscripts ...