Citation

Pachayappan, Neetha Kumari and Logeswaran, Aravindan Kalisri and Alias, Mazni and Ramayah, T. and Annamalah, Sanmugam and Yap, Voon Choong (2024) Demystifying Knowledge Work Practices and Performance in the Public Sector. Emerging Science Journal, 8 (5). pp. 1917-1939. ISSN 2610-9182

Text Demystifying Knowledge Work Practices and Performance in the Public Sector _ Pachayappan _ Emerging Science Journal.pdf - Published Version Restricted to Repository staff only Download (3MB)

Abstract

The performance of the public sector, especially its officers, is vital to a nation’s growth in light of the challenges clouding public service. Despite numerous efforts and initiatives, the level of efficiency of Malaysian public sector officers remains feeble, and public dissatisfaction has led to criticism of the administration. Therefore, addressing issues surrounding the performance of public sector officers is imperative to improve public perception. Guided by Drucker’s knowledge work productivity theory, this research aims to discover the relationship between knowledge work practices toward affective commitment (AC) and knowledge worker performance (KWP). This research adopted a cross-sectional design involving a survey of 395 administrative and diplomatic officers who were recruited via stratified random sampling. A variance-based structural equation modeling using Smart PLS 4.0 was conducted to analyze the data. Results show that job crafting (JC) and continuous learning (CL) improve KWP, job-related innovation (JRI) does not impact KWP, and AC exerts a mediating impact on the relationship between knowledge work practices and KWP. This study provides impetus to knowledge productivity and human behavior by integrating JC into Drucker’s theory

Item Type:	Article
Uncontrolled Keywords:	Knowledge Worker Performance, Affective Commitment, Productivity
Subjects:	H Social Sciences > HD Industries. Land use. Labor > HD28-70 Management. Industrial Management > HD30.2 Electronic data processing. Information technology. Including artificial intelligence and knowledge management
Divisions:	Faculty of Management (FOM)
Depositing User:	Ms Nurul Iqtiani Ahmad
Date Deposited:	03 Dec 2024 02:18
Last Modified:	03 Dec 2024 02:18
URII:	http://shdl.mmu.edu.my/id/eprint/13165

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