A Model-Driven IS 4.0 Development Framework for Railway Supply Chain

Authors

  • Mailasan Jayakrishnan School of Computing and Data Science, Xiamen University Malaysia, Jalan Sunsuria, Bandar Sunsuria, 43900 Sepang, Selangor Darul Ehsan,, Malaysia http://orcid.org/0000-0002-7807-1621
  • Abdul Karim Mohamad Centre for Advanced Computing Technology, Faculty of Information & Communication Technology, Universiti Teknikal Malaysia Melaka, Hang Tuah Jaya, 76100, Durian Tunggal, Melaka, Malaysia
  • Mokhtar Mohd Yusof Faculty of Computer and Information Technology, Al-Madinah International University, Pusat Perdagangan Salak 2, No.18, Jalan 2/125e, Taman Desa Petaling, 57100 Kuala Lumpur, Malaysia

DOI:

https://doi.org/10.15575/join.v7i2.794

Keywords:

Digitalization, Information System, Industry Revolution, Railway Industry, Supply Chain

Abstract

Railway Industry (RI) in Malaysia possess below-average Information System (IS) skills and seldom use the IS for decision making at their operation level while they likewise discover digital transformation adaption is crucial and hence RI in Malaysia are in the slow mass of adapter classification. Perceiving the significant task of IS to RI in the economy, the government is resolved to assist and support the improvement of IS to guarantee their sustainability and competitiveness. IS framework being significant because it set up the computerized industry, lively digital, who can structure with simple to utilize and basic dynamic interaction. The present IS model utilized in Malaysia depends on the knowledge and experience of the specialist like system developers and academicians. The maximum of these IS models to identify the visual view of performance in RI are precise and are not strategized toward railway utilize and do not give prescriptive evaluation. The issue is no transition development and the absence of industry capacity to do the transition phases. This research focuses on the technology parameters influencing the adaption of IS to assist decision-makers, administrative bodies, and IS analysis to approach the advantages of its continued and expected improvement in the RI.

Author Biography

Mailasan Jayakrishnan, School of Computing and Data Science, Xiamen University Malaysia, Jalan Sunsuria, Bandar Sunsuria, 43900 Sepang, Selangor Darul Ehsan,

Lecturer,

School of Computing and Data Science,

Xiamen University Malaysia.

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Published

2022-12-29

Issue

Vol. 7 No. 2 (2022)

Section

Article

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