Adaptive Structural Model Development for Off-campus Student Housing Preferences using SEM – PLS Analysis

  • Authors

    • Thuraiya Mohd
    • Noraini Johari
    • Suwaibatul Islamiah Abdullah Sani
    • Lizawati Abdullah
    • Nurulanis Ahmad @ Mohamed
    2019-01-18
    https://doi.org/10.14419/ijet.v8i1.7.25973
  • Structural Model, Off-Campus Housing Preference, Students Housing Preferences, SEM-PLS Analysis
  • The immense number of student enrolment has created high demand for student accommodation far exceeding the available on-campus student accommodation provided by universities and colleges. Thus, some students may need to reside off-campus instead. As different groups of society have different preferences and needs, it is crucial to identify the off-campus student housing preferences who are the economically determinant group of people. This paper presents the formulation of a structural model depicting off-campus student   housing preferences. The study presents data collected through a survey conducted via structured questionnaires in likert scale type of questions distributed randomly among off-campus students in selected public and private universities located within the State of           Selangor. The data was analysed using the SEM – PLS. The results from analysis indicate that the four main factors to be considered relating to student housing preferences are: housing environment, location, housing quality, and housing accommodation. Findings of this research will provide a set of guidelines for off-campus student housing preferences that is significant to local authorities, housing developers, Higher Education Institutions (HEIs), students' societies, and also the local communities to be the panacea for                  studentification issues.

     

     

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    Mohd, T., Johari, N., Islamiah Abdullah Sani, S., Abdullah, L., & Ahmad @ Mohamed, N. (2019). Adaptive Structural Model Development for Off-campus Student Housing Preferences using SEM – PLS Analysis. International Journal of Engineering & Technology, 8(1.7), 171-177. https://doi.org/10.14419/ijet.v8i1.7.25973