An Enhanced Collaboration Model for Electronic Information Sharing among Yemen Public Universities and YCIT-HE
- Eman Yahya Othman Maroof , Faculty of Computer Studies, Arab Open University, Saudi Arabia.
- Omar Ahmed Abdulkader , Faculty of Computer Studies, Arab Open University, Saudi Arabia.
- Saman Iftikhar , Faculty of Computer Studies, Arab Open University, Saudi Arabia.
- Kiran Fatima , Technical and Further Education (TAFE), New South Wales, Australia.
ABSTRACT
Objective: Electronic Information Sharing (EIS) is crucial for supporting everyday transactions and decision-making in the higher education sector, enabled by advancements in Information and Communication Technology (ICT). This study aims to develop an Electronic Information Sharing (EIS) model to improve data exchange between Yemen's public universities and the Yemen Center of Information Technology of Higher Education (YCIT-HE). It seeks to address the existing limitations in electronic data exchange, which lead to delays in services and decision-making. Methods: The study proposes an EIS model built on three theoretical foundations: Social Exchange Theory (SET), Information Sharing Theory (IST) and Layered Behavior Model (LBM). This model is designed to assist university management in planning and managing the technological, organizational, and environmental aspects of EIS. Results: The findings highlight three key dimensions and ten pivotal factors that can significantly enhance EIS between Yemen's public universities and YCIT-HE. Implications to Research and Practice: Future research can build on this foundation by testing and refining the proposed model in different educational and organizational contexts. By applying this model, public universities in Yemen can strengthen their collaboration with the YCIT-HE, ultimately improving service delivery and supporting a more efficient higher education ecosystem. The proposed EIS model provides a strategic framework for improving information sharing between public universities in Yemen and YCIT-HE. By addressing critical technological, organizational, and environmental factors, the model can contribute to reducing delays in services and improving decision-making processes.