The quality dimensions and acceptance of the newly launched e-procurement system (SIPLah) in Indonesian schools: Insights from a comprehensive dataset

• Published in: Data in brief Vol. 55; p. 110613
• Main Authors: Susanto, Harnowo, Martono, Trisno, Wardani, Dewi Kusuma, Sangka, Khresna Bayu, Wahyono, Budi
• Format: Journal Article
• Language: English
• Published: Netherlands Elsevier Inc 01.08.2024; Elsevier
• Subjects: Data; E-procurement; Indonesia; SIPLah; Technology Acceptance Model (TAM); E-procurement; Technology Acceptance Model (TAM); SIPLah; Indonesia
• ISSN: 2352-3409; 2352-3409
• DOI: 10.1016/j.dib.2024.110613

The Indonesian Ministry of Education and Culture launched a new e-procurement system for schools, known as SIPLah, in June 2019. This paper introduces a dataset comprising responses from middle school principals to a questionnaire focusing on the quality dimensions of the newly implemented e-procurement system and their acceptance of this technology. The dataset encompasses responses from 3110 middle schools, representing nearly all Indonesian provinces, and offers valuable indicators for assessing the system's quality dimensions and acceptance. These quality dimensions include processing, content, usability, training, and professionalism, while constructs for evaluating system acceptance comprise perceived ease of use, perceived usefulness, attitude, and intention to continue using. Data collection occurred from August 31 to September 30, 2023, utilizing an online questionnaire administered via Google Forms. Collaboration with the Indonesian Ministry of Education, Culture, Research, and Technology facilitated the distribution of the survey questionnaire to middle school principals across Indonesia through WhatsApp Messenger. This dataset holds significant potential for research exploring the impact of e-procurement system quality on schools' acceptance and for providing insights to policymakers and government officials regarding schools' perceptions of the system's quality and acceptance. As supplementary material, the dataset is made available to facilitate its reuse and further analysis by the research community.