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Most Downloaded Cert

Hew, Dr Lee and Tan posing with their certificate.

UTAR researchers and lecturers from the Faculty of Business and Finance, namely Garry Tan Wei Han, Hew Jun Jie and Dr Lee Voon Hsien were awarded the “Most Downloaded Cert” for their research titled “Cloud Computing in Manufacturing: The Next Industrial Revolution in Malaysia”. The award was presented by Elsevier (USA)’s Expert Systems with Applications (ESWA) journal.

The research was co-written by Prof Ooi Keng Boon from UCSI University and Hew Teck Soon from the University of Malaya. It aimed to address the contemporary “Industry 4.0” in Malaysia. It explored how performance expectancy (PE), effort expectancy (EE), firm size (FS), top management support (MS) and absorptive capacity (AC) of cloud computing technology can lead to innovativeness (IN) and firm performance (FP) among the manufacturing firms. They analysed 188 managerial positions using Partial Least Squares (PLS) Structural Equation Modelling (SEM) analysis, together with the Artificial Neural Network (ANN) analysis.

From the research, it was revealed that PE, FS and AC have a positive significant influence on IN; while IN positively influences FP. This research offers a valuable perspective on the applicability of cloud computing technology to improve IN and FP, and subsequently be aligned with Industry 4.0, the next industrial revolution.

“We are truly honoured to get this paper published in ESWA, which is currently a quartile one Journal in “Computer Science, Artificial Intelligence”, “Engineering, Electrical & Electronic” and “Operations Research & Management Science”. Through this award, we also recognised the importance of researching on a contemporary issue. As this paper is addressing the hot “Industry 4.0” issue in Malaysia, it not only interests the readers, but we believed it also contributed to the paper making into the list of top 25 most downloaded articles. We are definitely motivated to publish more papers that are related to the latest trend in the industry,” said Dr Lee.

She also added, “As much as this award is important to us, this award is also important to the University because the “Most Downloaded Certificate” is only given to the top 25 most downloaded articles from ESWA in the last 90 days. Given that ESWA is currently a quartile one journal, many authors all over the world are motivated to publish in ESWA. For example, in 2016, ESWA has published 630 articles in total. It is hard to stand out among these high-quality articles and make into the list of top 25 most downloaded articles, as we have to compete with the authors around the globe. With this award, we have certainly shown to the world that UTAR is always up to date on the latest developments in the industry and constantly encourages its staff to research on the latest trends.”

The researchers also believed that the research will add value in providing an extended literature for the future reference of scholars by providing them with information on cloud computing and IT/IS models and with critical insights of a developing country. They also mentioned that for practitioners, the research ascertains the benefits of cloud computing adoption on firm’s innovativeness and overall performance, so that the local firms can be groomed to increase its competitiveness and share technical know-how. The trio was also previously awarded a certificate of publication recognition from the Tourism Management journal.
ESWA is a refereed international journal whose focus is on exchanging information relating to expert and intelligent systems applied in industry, government, and universities worldwide. The journal publishes papers dealing with the design, development, testing, implementation, and/or management of expert and intelligent systems, and also to provide practical guidelines in the development and management of these systems.

The ESWA journal is currently indexed with Clarivate Analytics’ Science Citation Index Expanded (SCIE), and holding an impact factor of 3.928 as per JCR 2016.

拉曼大学 Universiti Tunku Abdul Rahman (UTAR)
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