Knowledge Management System for Railway Supply Chain Perspective

Authors

  • Mailasan Jayakrishnan Centre for Advanced Computing Technology, Faculty of Information & Communication Technology, Universiti Teknikal Malaysia Melaka, 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, Malaysia
  • Mokhtar Mohd Yusof Faculty of Computer and Information Technology, Al-Madinah International University, Kuala Lumpur, Malaysia

DOI:

https://doi.org/10.15575/join.v5i2.675

Keywords:

Decision Making, Information System, Knowledge Management, Railway Industry, Supply Chain

Abstract

Knowledge Management System (KMS) is a monitoring system that emphasizes the desired and actual performance of an industry. Aligning KMS to viably execute the Railway Industry methodology and supply chain operations utilizing legitimate knowledge management capabilities. Yet KMS controls the planning and priorities through action controls that emphasize on operational control level, result controls toward the strategic planning level, personnel controls on retaining the right operation with the right skills, and transaction control on the accurate and complete legal transactions for ensuring strategic management. Therefore, we have come up with a dynamic KMS for the Railway Supply Chain context that focuses on operational, tactical, and strategic perspectives on the information sources, value, analytics, and requirement for current and future drivers of an industry perspective. Moreover, this KMS aims to redesign the Information System by promoting a reductionist approach to problem-solving and best decision-making practices within an industry context.

References

Z. Yao, Z. Yang, G. J. Fisher, C. Ma, and E. (Er) Fang, “Knowledge complementarity, knowledge absorption effectiveness, and new product performance: The exploration of international joint ventures in China,†Int. Bus. Rev., vol. 22, no. 1, pp. 216–227, Feb. 2013.

M. A. Jayakrishnan, A. K. Bin Mohamad, and M. B. M. Yusof, “Integrating the Features of Knowledge Management (KM) and Business Intelligence (BI) for Developing Organizational Performance Framework—A Diagnostics Dashboard,†Adv. Sci. Lett., vol. 24, no. 3, pp. 1795–1799, 2018.

C. E. Connelly, D. Zweig, J. Webster, and J. P. Trougakos, “Knowledge hiding in organizations,†J. Organ. Behav., vol. 33, no. 1, pp. 64–88, Jan. 2012.

M. Jayakrishnan, “Analysis Of Socio-Technical Factors In Business Intelligence Framework Case Study Of Higher Learning Institution,†Universiti Teknikal Malaysia Melaka, 2018.

S. P. Turner, The social theory of practices: tradition, tacit knowledge and presuppositions. John Wiley & Sons., 2018.

P. Soto-Acosta and J.-G. Cegarra-Navarro, “New ICTs for Knowledge Management in Organizations,†J. Knowl. Manag., vol. 20, no. 3, pp. 417–422, May 2016.

M. Jayakrishnan, A. K. Mohamad, and M. M. Yusof, “Digitalization Railway Supply Chain 4.0: Enterprise Architecture Perspective,†Int. J. Adv. Trends Comput. Sci. Eng., vol. 9, no. 5, pp. 9056–9063, 2020.

W. Y. Ng, “Adoption of Building Information Modelling (BIM) on Railway Transportation Project in Malaysia,†UTAR, 2018.

B. Afsar, M. Masood, and W. A. Umrani, “The role of job crafting and knowledge sharing on the effect of transformational leadership on innovative work behavior,†Pers. Rev., vol. 48, no. 5, pp. 1186–1208, Aug. 2019.

I. Bleiklie, The new public management and the pursuit of knowledge. LOS Senter, 1994.

M. Jayakrishnan, A. K. Mohamad, and A. Abdullah, “A Systematic Literature Review in Enterprise Architecture for Railway Supply Chain of Malaysia Transportation Industry,†Int. J. Eng. Res. Technol., vol. 12, no. 12, pp. 2473–2478, 2019.

G. D. Jenkins and N. Gupta, “The payoffs of paying for knowledge,†Natl. Product. Rev., vol. 4, no. 2, pp. 121–130, 1985.

K. A. Al-Busaidi and L. Olfman, “Knowledge sharing through inter-organizational knowledge sharing systems,†VINE J. Inf. Knowl. Manag. Syst., vol. 47, no. 1, pp. 110–136, Feb. 2017.

M. Jayakrishnan, A. K. Mohamad, and M. M. Yusof, “Understanding Big Data Analytics ( BDA ) and Business Intelligence ( BI ) Towards Establishing Organizational Performance Diagnostics Framework,†Int. J. Recent Technol. Eng., vol. 8, no. 1, pp. 128–132, 2019.

Downloads

Published

2020-12-10

Issue

Section

Article

Citation Check

Most read articles by the same author(s)

Similar Articles

1 2 3 4 5 6 7 8 9 10 > >> 

You may also start an advanced similarity search for this article.