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Adoption of Best Practices in Running and Maintaining IT-Based Information Systems in Higher Learning Institutions

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Abstract

The transition from paper-based to information-technology-based (IT-based) systems has warranted a significant impact on how commercial, administrative, and academic processes are carried out today. This is due to the deployment of numerous Information Systems (IS) that support essential business and institutional activities by facilitating data collection, processing, and dissemination. The deployed IT-based systems are mostly susceptible to processing errors, unacknowledged data modification, data loss, system failures, cyber-attacks, and other potentially detrimental risks. It is, therefore, argued that to ensure trustful and high-quality service delivery through the use of IT-based IS and virtual resources in Higher Learning Institutions (HLIs), IT engineers and managers should have a thorough understanding of IT best practices. Thus, this study develops an IT best practices adoption theoretical framework based on the daily routines of HLIs’ IT engineers and managers. According to the framework, IT system utilization and dependability, knowledge of the sensitivity of information and IT systems, and the budget allotted to IT infrastructure upkeep are the primary drivers of the adoption of IT best practices.

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Acknowledgements

Words of gratitude are expressed to IT engineers and managers who attended the IT management workshop organized by ARES-Belgium in 2021, for their time and commitment in responding to a long questionnaire and targeted interviews during the course of this study. It is believed that they will be enriched by the concluding remarks of this study.

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Correspondence to Chiza M. Christophe.

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This article is part of the topical collection “Computer Supported Education” guest edited by James Uhomoibhi and Beno Csapó.

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Christophe, C.M., Anthony, B., Cibangu, C. et al. Adoption of Best Practices in Running and Maintaining IT-Based Information Systems in Higher Learning Institutions. SN COMPUT. SCI. 5, 361 (2024). https://doi.org/10.1007/s42979-024-02634-6

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