Factors Influencing Data Quality in Malaysian Public Sector Immovable Asset Management Strategy

Mohd Suharizal Mahamad Subri, Maimunah Sapri, Hariati Abdullah Hashim, Siti Fadzilah Ayob and Madihah Md Fadil
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Mohd Suharizal Mahamad Subri: Integrated Asset Management Planning Branch, Jabatan Kerja Raya Malaysia Faculty of Built Environment and Surveying, Universiti Teknologi Malaysia
Maimunah Sapri: Faculty of Built Environment and Surveying, Universiti Teknologi Malaysia
Hariati Abdullah Hashim: Faculty of Built Environment and Surveying, Universiti Teknologi Malaysia
Siti Fadzilah Ayob: Faculty of Built Environment and Surveying, Universiti Teknologi Malaysia
Madihah Md Fadil: Centre of Diploma Studies, Department of Management UTMSPACE

International Journal of Research and Innovation in Social Science, 2025, vol. 9, issue 1, 1715-1727

Abstract: Organizations with large, immovable assets, particularly in the public sector, are facing growing demands to improve efficiency and sustainability. Recent advancements in asset management strategies have intensified the need to identify optimal methods for managing engineering assets to achieve consistent, desired outcomes. The quality of immovable asset data plays a crucial role in asset management, directly impacting operational efficiency. However, while data availability is increasing, having more data does not necessarily improve the effectiveness of sustainability efforts in managing these assets. Many organizations lack a structured approach to information quality management, as the factors affecting information quality often go unrecognized. Addressing gaps in previous research, this study seeks to identify the factors that influence the quality of immovable asset information in asset management. Qualitative data were gathered through semi-structured interviews with eight industry experts in asset management. The findings from this research can guide the development of sustainable policies, strategies, and programs related to data quality, enhancing decision-making in asset management.

Date: 2025
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