Universiti Teknologi Malaysia Institutional Repository

Factors that affect spatial data sharing in Malaysia

Hamamurad, Qasim Hamakhurshid and Mat Jusoh, Normal and Ujang, Uznir (2022) Factors that affect spatial data sharing in Malaysia. ISPRS International Journal of Geo-Information, 11 (8). pp. 1-18. ISSN 2220-9964

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Official URL: http://dx.doi.org/10.3390/ijgi11080446

Abstract

This paper examines the phenomena of the local government’s inadequate reaction to the national programme of geographical infrastructure for the effective sharing of spatial data in Malaysia. We investigate the determinants of sharing data for Malaysia’s spatial data infrastructure (SDI) and aim to define the model for spatial data-sharing of Malaysia’s local SDI. The main contribution of this paper is an explanation of the novel methodology to study factors that affect spatial data sharing including a new qualitative analysis method through an interview with people concerned in this field, including engineers, technicians and academics, which was undertaken in Kuala Lumpur, and a new methodology to identify the necessary approach that affects spatial data sharing. An interview and a questionnaire were used in this study as part of a sequential exploratory approach. Among land use, Plan Malaysia, and Telekom Malaysia Berhad TMOne, 15 participants were interviewed in-depth to obtain their responses, and 83 individuals took part in the survey questionnaires. Interview data were measured by content analysis, while questionnaire data were measured by partial least squares analysis. In the structural model analysis, Smart PLS was used to choose the fit items based on validity and reliability measurements. According to the hypothesis measurement, technology and organisation both significantly affect the practice of spatial data sharing, but human resources and spatial data do not significantly affect it. All R-Squared values represent a value above 56 per cent for the human resource aspect, technology aspect and spatial data aspect. However, the R-Square value for spatial data sharing is 47%. Spatial data and human resources have a less substantial impact on spatial data sharing; hence, this study proposes a national awareness programme and mentoring to improve local SDI support for spatial data sharing.

Item Type:Article
Uncontrolled Keywords:data sharing, geospatial, partial least square (PLS)
Subjects:H Social Sciences > HD Industries. Land use. Labor > HD30.213 Management information systems. Decision support systems
Divisions:International Business School
ID Code:102741
Deposited By: Narimah Nawil
Deposited On:18 Sep 2023 04:20
Last Modified:18 Sep 2023 04:20

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