Geographic information systems adoption model: A partial least square-structural equation modeling analysis approach
Heliyon, ISSN: 2405-8440, Vol: 10, Issue: 15, Page: e35039
2024
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Study Findings on Data Systems Detailed by Researchers at Universiti Kebangsaan Malaysia (Geographic information systems adoption model: A partial least square-structural equation modeling analysis approach)
2024 SEP 02 (NewsRx) -- By a News Reporter-Staff News Editor at Information Technology Daily -- Investigators discuss new findings in data systems. According to
Article Description
The ability of Geographic Information System (GIS) to organize, analyze, visualize and integrate spatial data has been at the top of its primary uses among professional industries. However, considering the extensive adoption of Information System (IS) throughout history for government organizations’ or citizens' disaster response, the implementation of geographical elements is still minimal. Previous GIS models and framework studies, particularly in developing countries, were affected by pandemic pressure, competitiveness pressure, change management, and security factors. Thus, this study aims to develop a model for the successful adoption of GIS using the Technology Acceptance Model (TAM), and De Lone and Mc Lean Information Success Model and analyze the applicability of the existing factors to enhance the performance of Public Sector Organizations (PSOs). From the study, a new conceptual framework was proposed to examine the effects of factors on GIS adoption that impact performance among PSOs from the perspective of Saudi Arabia. Quantitative methods were used to collect data through a questionnaire distributed to 350 respondents from PSO, and only 272 were found to be valid. Partial Least Square Structural Equation Modeling (PLS-SEM) validated the GIS model. The finding revealed that system quality, service quality, change management, competitiveness pressure, perceived ease of use, perceived usefulness, and security factors significantly and positively affected GIS adoption. The study also showed that GIS adoption substantially affected PSO performance. The proposed model provides insight into how GIS adoption can eventually enhance performance among PSOs. In essence, the study contributes to the running of PSO and the decisions taken by policymakers.
Bibliographic Details
http://www.sciencedirect.com/science/article/pii/S2405844024110705; http://dx.doi.org/10.1016/j.heliyon.2024.e35039; http://www.scopus.com/inward/record.url?partnerID=HzOxMe3b&scp=85200106499&origin=inward; http://www.ncbi.nlm.nih.gov/pubmed/39170420; https://linkinghub.elsevier.com/retrieve/pii/S2405844024110705
Elsevier BV
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