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Weng Hoe Lam
Department of Physical and Mathematical Science, Faculty of Science, Universiti Tunku Abdul Rahman, Kampar Campus, Jalan Universiti, Bandar Barat, 31900 Kampar, Perak, Malaysia
Decision Sciences, Operations Research & Management Engineering Environmental Science Industrial & Manufacturing Engineering Transportation

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Data-Driven Decision Analysis on the Selection of Course Programmes with AHP-TOPSIS Model Weng Siew Lam; Weng Hoe Lam; Kah Fai Liew; Soong Cheong Wong
International Journal of Supply Chain Management Vol 7, No 4 (2018): International Journal of Supply Chain Management (IJSCM)
Publisher : International Journal of Supply Chain Management

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Abstract

The course selection has become a favorite issue among the students who pursue their tertiary study in university nowadays. This is because there are a lot of course programmes offered in this knowledge-based education system. Besides that, other factors such as the financial problem, motivation, self-interest, moral support from friends and family are important criteria in the selection of course programmes. The objective of this study is to propose a data-driven conceptual framework to determine the student preference in the selection of course programmes with Analytic Hierarchy Process Technique for Order of Preference by Similarity to Ideal Solution (AHP-TOPSIS) model. Moreover, this study also aims to determine the priority of the decision criteria that influence the selection of course programmes among the students. In this study, the target respondents are the science stream students from Universiti Tunku Abdul Rahman, Malaysia who provide the inputs as data-driven decision analysis on the selection of course programmes. The results of this study show that medical science is the most preferred course programmes among the students followed by engineering, science and lastly information system. On the other hand, career prospect has been identified as the most concerned decision criterion by the student in the selection of course programmes. This study is significant because it helps to determine the most preferred course programme as well as the most influential criteria in the selection of course programmes among the students with the proposed conceptual framework based on AHP-TOPSIS model.
Evaluation on the Preference of Coffee Shop among the Undergraduate Students with Analytic Hierarchy Process Model Weng Siew Lam; Mohd Abidin Bakar; Weng Hoe Lam; Jia Wai Chen; Hui Lee Ma
International Journal of Supply Chain Management Vol 7, No 4 (2018): International Journal of Supply Chain Management (IJSCM)
Publisher : International Journal of Supply Chain Management

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (746.778 KB)

Abstract

Emergence of coffee shop in recent years has proven the demand of coffee shop in modern lifestyle. Nowadays, visitation to coffee shop has become a common trend for most of the undergraduate students for group discussion or chatting. This study aims to evaluate the preference of undergraduate students from Universiti Tunku Abdul Rahman in selecting the coffee shop based on multiple criteria. There are 19 respondents participating in this study who have visited all the 4 selected coffee shops which are Simple Coffee, Bean Caf, Starbucks and Old Town White Coffee. An Analytic Hierarchy Process (AHP) model is proposed to determine the weight of criteria, priority of coffee shop selection in terms of each criterion and the overall performance of the coffee shop. The findings show that the most important criterion is cleanliness, followed by flavor, store atmosphere, sales promotion, speed of service, price and location. Starbucks is the most preferred coffee shop while the followings are Simple Coffee, Bean Caf and Old Town White Coffee. The significance of this study is to propose a conceptual framework to identify the most preferred coffee shop and the most important criteria in coffee shop selection among the undergraduate students by using AHP model.
Co-Authors Hui Lee Ma Jia Wai Chen Kah Fai Liew Mohd Abidin Bakar Soong Cheong Wong Weng Siew Lam