{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T01:31:35Z","timestamp":1760059895923,"version":"build-2065373602"},"reference-count":132,"publisher":"MDPI AG","issue":"8","license":[{"start":{"date-parts":[[2025,7,23]],"date-time":"2025-07-23T00:00:00Z","timestamp":1753228800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Future Internet"],"abstract":"<jats:p>This study explores the challenges hindering the government\u2019s adoption of cloud computing despite its benefits in improving services, reducing costs, and enhancing collaboration. Key barriers include information security, privacy, compliance, and perceived risks. Using the Unified Theory of Acceptance and Use of Technology (UTAUT) model, the study conceptualises a model incorporating privacy, governance framework, performance expectancy, and information security as independent variables, with perceived risk as a moderator and government intention as the dependent variable. The study employs exploratory factor analysis (EFA) based on survey data from 71 participants in Nigerian government organisations to validate the measurement scale for these factors. The analysis evaluates variable validity, factor relationships, and measurement reliability. Cronbach\u2019s alpha values range from 0.807 to 0.950, confirming high reliability. Measurement items with a common variance above 0.40 were retained, explaining 70.079% of the total variance on the measurement items, demonstrating reliability and accuracy in evaluating the challenging factors. These findings establish a validated scale for assessing government cloud adoption challenges and highlight complex relationships among influencing factors. This study provides a reliable measurement scale and model for future research and policymakers on the government\u2019s intention to adopt cloud services.<\/jats:p>","DOI":"10.3390\/fi17080326","type":"journal-article","created":{"date-parts":[[2025,7,23]],"date-time":"2025-07-23T16:04:51Z","timestamp":1753286691000},"page":"326","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["An Exploratory Factor Analysis Approach on Challenging Factors for Government Cloud Service Adoption Intention"],"prefix":"10.3390","volume":"17","author":[{"ORCID":"https:\/\/orcid.org\/0009-0008-2963-752X","authenticated-orcid":false,"given":"Ndukwe","family":"Ukeje","sequence":"first","affiliation":[{"name":"Department of Computer and Information Sciences, Auckland University of Technology, Auckland 1010, New Zealand"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2103-8636","authenticated-orcid":false,"given":"Jairo A.","family":"Gutierrez","sequence":"additional","affiliation":[{"name":"Department of Computer and Information Sciences, Auckland University of Technology, Auckland 1010, New Zealand"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2241-109X","authenticated-orcid":false,"given":"Krassie","family":"Petrova","sequence":"additional","affiliation":[{"name":"Department of Computer and Information Sciences, Auckland University of Technology, Auckland 1010, New Zealand"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3069-1784","authenticated-orcid":false,"given":"Ugochukwu Chinonso","family":"Okolie","sequence":"additional","affiliation":[{"name":"Department of Vocational & Technical Education, Alex Ekwueme Federal University, Nduru-Alike 480101, Nigeria"}]}],"member":"1968","published-online":{"date-parts":[[2025,7,23]]},"reference":[{"key":"ref_1","first-page":"13","article-title":"The Impact of Big Data-Driven Artificial Intelligence Systems on Public Service Delivery in Cloud-Oriented Government Infrastructures","volume":"8","author":"Poudel","year":"2024","journal-title":"J. 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