FBF researchers awarded Most Downloaded Article in Machine Learning with Applications

FBF researchers awarded Most Downloaded Article in Machine Learning with Applications

FBF academics and alumnus awarded Most Downloaded Article in Machine Learning with Applications

Faculty of Business and Finance (FBF) academics, namely Loh Xiu Ming, Dr Leong Lai Ying, Assoc Prof Dr Lee Voon Hsien along with Master of Business Administration (Corporate Management) alumnus Amos Lau Junke were awarded the Most Downloaded Article in Machine Learning with Applications by Elsevier for their research titled “On the way: Hailing a taxi with a smartphone? A hybrid SEM-neural network approach.” This paper was also co-authored with UCSI University academics Assoc Prof Dr Garry Tan Wei Han and Prof Ts Dr Ooi Keng Boon.

The paper aimed to determine the antecedents that affect the adoption of mobile ride-sharing services through the utilisation of an extended Mobile Technology Acceptance Model (MTAM). According to Lau, they did this research when they found there was a lack of understanding in the area of mobile ride-sharing services.

Lau explained, “The concept of ride-sharing was rather new among Malaysians but was greatly disrupting the transportation sector. Hence, the purpose of this research was to look into the minds of consumers and understand their behaviours towards mobile ride-sharing services."

Ride-hailing is a system that allows one’s smartphone to serve as a means of requesting taxi services from the MTB firms which include Grab, ExCab and Pickup2u. In the research, a total of 330 usable responses were analysed using Partial Least Squares-Structural Equation Modeling (PLS-SEM) and Artificial Neural Network (ANN) which yielded novel insights. The research also extended the literature on MTB services from the perspective of a developing country and verified the robustness of using an extended MTAM.

Lau believed that the insights from the research will benefit stakeholders in the transportation sector. He said, “In this research, we identified the factors that would encourage consumers to adopt mobile ride-sharing services. It can be used as a point of reference for companies offering such services to better understand what consumers are looking for and better enhance their ride-sharing services accordingly.”

As an early career researcher, Loh enthused, “This award serves as a huge encouragement for me because it indicates that the subject matter of our research is pertinent not only locally but also in the global setting. With that said, I am more motivated to conduct research that is relevant to the current needs of the general public in the future.”

When asked of any advice they could offer to inspire young researchers, Dr Lee said, “Commitment and determination are two of the most important qualities for a junior researcher to be successful. Great researchers are tenacious in facing obstacles when carrying out their research projects. Even after completion, getting rejected from journals is part and parcel of the publishing process. In such situations, it is important for junior researchers to take it on the chin and not get demotivated.”

Dr Leong also advised researchers to stay positive no matter what the outcome of the final review decision may be. She said, “Do not give up on writing research papers as eventually a right ‘home’ for the paper will be found.  Take all the comments from the reviewers positively and respond to them professionally. Always remember that a rejection is not the end but the beginning of a journey that will lead to a better quality in research publication.”

Elsevier is a Netherlands-based publishing company that has been around for more than 140 years. It aims to advance research with specialisations in scientific, technical, and medical content. Elsevier also helps researchers and healthcare professionals’ advance science and improve health outcomes for the benefit of society. 
The Machine Learning with Applications (MLWA) under Elsevier is a peer-reviewed and open-access journal that focuses on research related to machine learning. The journal is comprised of various research and development in ML, including but not limited to data mining, computer vision, natural language processing (NLP), intelligent systems, neural networks, AI-based software engineering, bioinformatics and their applications in the areas of engineering, medicine, biology, education, business and social sciences. In addition, it also covers a broad spectrum of applications in the community, from industry, government, and academia.

Read/view the papers here:

On the way: Hailing a taxi with a smartphone? A hybrid SEM-neural network approach:

From left: Lau, Loh, Dr Leong and Dr Lee

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