Higher education institutions, like nearly all organizations, need to implement information management systems that enable them to handle routine operations easily and, at the same time, generate many types of standardized and ad hoc reports. Higher professional education (HPE) institutions face unique challenges when implementing their computer-based information management systems. Electronic records management systems (ERMSs) help manage the extensive information needed to plan and make well-informed decisions. ERMS is a fairly new addition to organizations, and those organizations are still learning how to use them effectively. Unfortunately, some organizations are still slow to adopt these systems. With this in mind, this paper proposes a framework that identifies the key factors that influence HPEs in adopting their own ERMS. The framework developed in this paper is based on two other models: the unified theory of acceptance and use of technology (UTAUT) and technology-organization-environment (TOE). The questionnaires we distributed to 364 respondents in the HPE sector to collect the views of as many stakeholders as possible. These survey responses led the study to propose a framework that identifies the critical factors that influence the adoption of ERMSs in HPEs. This framework is expected to guide HPE institutions in understanding the most essential factors (individual, technological, and environmental) that must be addressed to adopt an ERMS.

Learning Analytics Tools (LATs) can be used for informed decision-making regarding teaching strategies and their continuous enhancement. Therefore, LATs must be adopted in higher learning institutions, but several factors hinder its implementation, primarily due to the lack of an implementation model. Therefore, in this study, the focus is directed towards examining LATs adoption in Higher Learning Institutions (HLIs), with emphasis on the determinants of the adoption process. The study mainly aims to design a model of LAT adoption and use it in the above context to improve the institutions' decision-making and accordingly, the study adopted an extended version of Technology Acceptance Model (TAM) as the underpinning theory. Five experts validated the employed survey instrument, and 500 questionnaire copies were distributed through e-mails, from which 275 copies were retrieved from Saudi employees working at public HLIs. Data gathered was exposed to Partial Least Square-Structural Equation Modeling (PLS-SEM) for analysis and to test the proposed conceptual model. Based on the findings, the perceived usefulness of LAT plays a significant role as a determinant of its adoption. Other variables include top management support, financial support, and the government's role in LATs acceptance and adoption among HLIs. The findings also supported the contribution of LAT adoption and acceptance towards making informed decisions and highlighted the need for big data facility and cloud computing ability towards LATs usefulness. The findings have significant implications towards LATs implementation success among HLIs, providing clear insights into the factors that can enhance its adoption and acceptance. They also lay the basis for future studies in the area to validate further the effect of LATs on decision-making among HLIs institutions. Furthermore, the obtained findings are expected to serve as practical implications for policy makers and educational leaders in their objective to implement LAT using a multi-layered method that considers other aspects in addition to the perceptions of the individual user.

An electronic records management system (ERMS) is tightly linked with most of the daily activities of educational organisations and leads to enhance their performance and decision-making. The aim of this article is to identify the significant factors that could influence the ERMS adoption in higher professional education (HPE). The methodology of this article started with identifying the factors through theory analysis and literature and also recommended by experts. Technology–organisation–environment (TOE) theory was used for factor classification. Qualitative approach was used through the interview with experts to validate and verify the proposed framework. This article presents the results of a study which identifies the issues involved in the utilisation and adoption of ERMS. More than 100 previous works and six well-known theories were critically reviewed to identify the main factors for successful ERMS adoption in different areas with the aim of proposing a taxonomic framework that can depict and identify the main factors that have an impact on the success of ERMS adoption. The proposed framework includes 11 factors categorised into three dimensions. The framework is validated and verified by experts. The adoption factors identified here provide a sound theoretical basis for research to understand, support and facilitate the adoption of ERMS to HPE benefit. The proposed framework could help to improve educational outcomes and the successful implementation of ERMS.

In the modern world, the amount of information stored in modern technology has been exponentially increasing. Access to vast amounts of information has changed how governments, institutions, organizations, and individuals conduct their business and record keeping. The increased use of cloud computing in conjunction with information and communication technologies (ICT), office automation, and digitalization has altered how electronic records are generated. Organizations should embrace this emerging environment to ensure competent operations and regulatory compliance well into the future. The absence of framework makes it difficult to implement the Electronic Records Management System (ERMS). Thus, this study proposed a framework for ERMS implementation and identified the most critical factors that are related to the ERMS characteristics and cloud characteristics. The ERMS implementation will improve Yemeni public sector educational institution competency and such implementation will be facilitated by the proposed framework. The study uses the Technology Acceptance Model 3 (TAM3) to implement a cloud Electronic Records Management System (ERMS). In addition to that, the study used a quantitative approach method and distributed questionnaires to 350 academicians and managers in the Yemeni public education sector. Variable relationships were identified using Partial Least Square-Structural Equation Modelling (PLS-SEM) through a second-order analysis method. All the identified factors were found to be essential and have a significant relationship with the behavioral intention to implement ERMS. The findings also revealed that ERMS plays a substantial and vital role in the competency of educational organizations. In other words, the study results demonstrated the importance of ERMS and Cloud dimension to ERMS implementation as well as the significant effect of ERMS implementation on public sector educational competency. These findings of the study have the potential to assist in shaping the direction of theory and empirical studies concerning the ERMS, particularly in its implementation to support the competency of educational institutions.

Although electronic records management system (ERMS) is important in bringing about the productivity of organizations, majority of them refuse to implement it, while a few embark on implementing it blindly, without guidance, which often results in failure. This study, therefore, proposed a model for ERMS adoption to support the productivity and performance of Higher Professional Education (HPE) institutions in the Yemeni context. This study used the Unified Theory of Acceptance and Use of Technology (UTAUT) and a mixed explanatory approach to gather quantitative and qualitative data. Data was then analyzed through the use of SPSS 21, with SEM and Smart PLS V3 software used to test the proposed model. The model was also confirmed by five experts who were interviewed to obtain qualitative data. Based on the analysis results, all the fit indices met the recommend values range that assumed the acceptability of the developed model. The model was found to be of good fit and the theory upon which the model was developed was stable. The quantitative findings showed that performance expectancy, effort expectancy, social influence, facilitating conditions, policy and training have a significant relationship with the ERMS adoption which in return has a significant relationship with HPE organizations’ productivity. This was supported by the qualitative results, confirming the theoretical study and contributing to the understanding of ERMS adoption among HPEs. Such adoption ensures the educational institutions’ productivity.