Muaadh Mukred
@sunway.edu.my
Sunway Business School
Sunway University
RESEARCH, TEACHING, or OTHER INTERESTS
Computer Science, Artificial Intelligence, Information Systems, Software
Scopus Publications
Scholar Citations
Scholar h-index
Scholar i10-index
Scopus Publications
Muaadh Mukred, Umi Asma’ Mokhtar, Burkan Hawash, Hussain AlSalman, and Muhammad Zohaib
Elsevier BV
Wei Wen Chi, Tiong Yew Tang, Narishah Mohamed Salleh, Muaadh Mukred, Hussain AlSalman, and Muhammad Zohaib
Institute of Electrical and Electronics Engineers (IEEE)
Muaadh Mukred, Umi Asma' Mokhtar, and Burkan Hawash
Penerbit Universiti Kebangsaan Malaysia (UKM Press)
This qualitative study aims to examine the ChatGPT acceptance as a learning tool for academics by identifying factors influencing its acceptance and adoption. In academia, an exciting development is the significant attention directed toward ChatGPT, an AI-based conversational agent, as a potential learning. Nevertheless, more knowledge and information are needed concerning the determinants of its acceptance and use among academics. This study answers the need by conducting semi-structured interviews with ten academics from different disciplines and academic levels, selected through purposive sampling. Following the interview sessions, the interviews were transcribed and analysed using thematic analysis to highlight major themes and patterns. Based on the findings obtained, the academics displayed positive attitudes towards adopting ChatGPT as a learning tool, which holds the potential to resolve challenges faced during the system's teaching and learning process. The significant factors influencing ChatGPT acceptance and use are perceived usefulness, ease of use, credibility, and compatibility with the current teaching and learning methods. Additionally, the prior experience of academics with using AI-based tools and their proficiency in their use have a key role in their ChatGPT acceptance and adoption. The significant contribution of this study to literature is related to the adoption of AI-based tools in the field of academics and the determination of the factors that influence ChatGPT adoption and use for learning. Practically, the study also contributes to educational institutions and developers by providing a guideline for effective ChatGPT design and implementation for optimum potential and enhancement of the teaching and learning experience within academia. Keywords: ChatGPT, technology adoption, learning tools, technology and education, qualitative approach.
Sabir Shah, Asim Munir, Abdul Waheed, Amerah Alabrah, Muaadh Mukred, Farhan Amin, and Abdu Salam
MDPI AG
Underwater Wireless Sensor Networks (UWSNs) obtains more attention due to their wide range of applications such as underwater oil field discovery, Tsunami monitoring systems, surveillance systems, and many more. In such a resource-constrained environment, sensors are more vulnerable to malicious attacks. Node authentication and secure communication is one of the vital issues in UWSNs. In this study, a secure and lightweight key management framework for UWSNs is proposed. The proposed framework includes key generation, key distribution, revocation, and authentication mechanisms along with lightweight implementation, and scalability. We use an elliptic curve-based algorithm for key distribution, and certificate revocation list (CRL) for key revocation. We also examine the performance of the proposed framework taking into account the amount of communication overhead as well as the level of security. The simulation results show that the proposed framework provides better security with less communication overhead compared to existing frameworks. This framework can be used for secure data communication in UWSNs, which has various applications in oceanography, environmental monitoring, and military operations.
Muaadh Mukred, Fahad M Alotaibi, Zawiyah M Yusof, Umi Asma’ Mokhtar, Burkan Hawash, and Waleed Abdulkafi Ahmed
SAGE Publications
Enterprise resource planning (ERP) has been found to have a key role in the management of higher learning institutions (HLIs) and schools. However, the literature shows no universal model to support and shed light on the adoption of ERP, which lessens the chances for an effective ERP adoption and usage. Therefore, a new model is needed for successful adoption and the eventual enhanced decision-making, and as such, there is a need to investigate the factors that can bring about ERP system adoption. Models for ERP adoption in literature are few and far between, and what few exist are not applicable as they do not cover all the major factors that can contribute to adoption success. Hence, in this article, an ERP adoption model was brought forward for HLIs for the promotion of their decision-making process. The model was developed through the integration of DeLone and McLean’s information success model and the technology, organisation and environment (TOE) theory. The study distributed 500 survey questionnaire copies online and collected 364 from HLIs respondents, after which they were retrieved, and data were analysed through partial least squares structural equation modeling (PLS-SEM) 3 statistical software. On the basis of the obtained analysis findings, technological, organisational and environmental factors had significant and positive effects on ERP adoption, and ERP adoption had a positive and significant effect on the decision-making of HLIs. The entire factors were found to be significant in their effects, and ERP adoption sufficiently explained variance extracted from decision-making. The study contributes to the literature through the pioneering measurement of factors categorised under technological, organisational and environmental dimensions, with ERP adoption and decision-making encapsulated in a single model.
Muaadh Mukred, Waleed Abdulkafi Ahmed, Umi Asma’ Mokhtar, and Burkan Hawash
Springer Nature Switzerland
Burkan Hawash, Muaadh Mukred, Umi Asma’ Mokhtar, and Mohammed Islam Nofal
Informing Science Institute
Aim/Purpose: The use of digital technology, such as an electronic records management system (ERMS), has prompted widespread changes across organizations. The organization needs to support its operations with an automation system to improve production performance. This study investigates ERMS’s potentiality to enhance organizational performance in the oil and gas industry. Background: Oil and gas organizations generate enormous electronic records that lead to difficulties in managing them without any system or digitalization procedure. The need to use a system to manage big data and records affects information security and creates several problems. This study supports decision-makers in oil and gas organizations to use ERMS to enhance organizational performance. Methodology: We used a quantitative method by integrating the typical partial least squares (SEM-PLS) approach, including measurement items, respondents’ demographics, sampling and collection of data, and data analysis. The SEM-PLS approach uses a measurement and structural model assessment to analyze data. Contribution: This study contributes significantly to theory and practice by providing advancements in identity theory in the context of big data management and electronic records management. This study is a foundation for further research on the role of ERMS in operations performance and Big Data Management (BDM). This research makes a theoretical contribution by studying a theory-driven framework that may serve as an essential lens to evaluate the role of ERMS in performance and increase its potentiality in the future. This research also evaluated the combined impacts of general technology acceptance theory elements and identity theory in the context of ERMS to support data management. Findings: This study provides an empirically tested model that helps organizations to adopt ERMS based on the influence of big data management. The current study’s findings looked at the concerns of oil and gas organizations about integrating new technologies to support organizational performance. The results demonstrated that individual characteristics of users in oil and gas organizations, in conjunction with administrative features, are robust predictors of ERMS. The results show that ERMS potentiality significantly influences the organizational performance of oil and gas organizations. The research results fit the big ideas about how big data management and ERMS affect respondents to adopt new technologies. Recommendations for Practitioners: This study contributes significantly to the theory and practice of ERMS potentiality and BDM by developing and validating a new framework for adopting ERMS to support the performance and production of oil and gas organizations. The current study adds a new framework to identity theory in the context of ERMS and BDM. It increases the perceived benefits of using ERMS in protecting the credibility and authenticity of electronic records in oil and gas organizations. Recommendation for Researchers: This study serves as a foundation for future research into the function and influence of big data management on ERMS that support the organizational performance. Researchers can examine the framework of this study in other nations in the future, and they will be able to analyze this research framework to compare various results in other countries and expand ERMS generalizability and efficacy. Impact on Society: ERMS and its impact on BDM is still a developing field, and readers of this article can assist in gaining a better understanding of the literature’s dissemination of ERMS adoption in the oil and gas industry. This study presents an experimentally validated model of ERMS adoption with the effect of BDM in the oil and gas industry. Future Research: In the future, researchers may be able to examine the impact of BDM and user technology fit as critical factors in adopting ERMS by using different theories or locations. Furthermore, researchers may include the moderating impact of demographical parameters such as age, gender, wealth, and experience into this study model to make it even more robust and comprehensive. In addition, future research may examine the significant direct correlations between human traits, organizational features, and individual perceptions of BDM that are directly related to ERMS potentiality and operational performance in the future.
Muaadh Mukred, Zawiyah M. Yusof, Waleed Abdulkafi Al-Moallemi, Umi Asma’a Mokhtar, and Burkan Hawash
SAGE Publications
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.
Norah Basheer Alotaibi and Muaadh Mukred
Elsevier BV
Muaadh Mukred, Burkan Hawash, Mohammed Islam Nofal, Umi Asma Mokhtar, and Zawiyah M. Yusof
IEEE
The generated recorded information, sometimes known as electronic records, is the focus of this article, exploring how these records might help an organization improve its overall competency. As a result, the performance of an organization can be boosted, allowing the business to maintain its competitiveness and promote accountability and transparency at the same time. With the help of Electronic Records Management Systems, records may be efficiently and successfully managed. The ultimate goal for ERMS is to obtain the right information at the right time for the right person, eventually improving organizational competency. Records must also be kept to comply with federal laws and regulations, especially in a big data environment. “Big data” refers to data with high volume, velocity, variety, validity, and high value. Capturing and storing big data necessitates a wide range of new tools and techniques and is used to make better decisions for improving organizations' management and competencies. Big data and ERMS and how ERMS might improve public sector organizations' competence are the main goals of this study.
Faiza Shah, Yumin Liu, Yasir Shah, Ijaz Ul Haq, Muaadh Mukred, Saddam Hussain, and Mahfoudh S. Alasaly
Hindawi Limited
Recent advances in data analysis and processing methods can improve the ability of computational applications to perform complex steps of different tasks. With the progress of information and communication technologies (ICT), Blockchain-based complex data processing for transaction analysis and smart contract agreement has become a new research area in the fields of mathematics and computation. Stability of financial sector based on the ICT is a core component for growing the economics of medium and small enterprises. This stability brings the innovation to businesses productivity, while the management of information takes more prospective for improving the efficiency and more ways for innovating the business of products. In this study, we use the autoregressive distribution lag (ARDL) model with Blockchain-based complex data processing approach to emphasize the role of ICT in the field of trade credit maintainability. Actually, the ICT connects the industries in the entire world and makes business sectors that use its technologies be more advanced. Based on the ARDL model conducted on the records gathered from 2000 to 2019, the analysis concludes that the ICT-based complex data processing is a critical component of trade credit. The statistics of ICT are chosen based on the economy penetrations through the Internet and mobile phones. The causality exposed between the trade credit and ICT is bidirectional in nature. Also, it is found that the usage of mobile phones has a substantial influence on the business sectors, as a substantial amount of trading and business transactions are conducted over the phone. Therefore, the primary concern is the association between the Blockchain and trade credit, which is thoroughly discussed in this work. The trade credit improves the stability of financial sector and the Blockchain supports its maintainability by the role of ICT. The results of the study can help the business stakeholders and investors to estimate the marketing for future useful execution.
V. Sridhar, K. V. Ranga Rao, V. Vinay Kumar, Muaadh Mukred, Syed Sajid Ullah, and Hussain AlSalman
Hindawi Limited
Computational intelligence methods play an important role for supporting smart networks operations, optimization, and management. In wireless sensor networks (WSNs), increasing the number of nodes has a need for transferring large volume of data to remote nodes without any loss. These large amounts of data transmission might lead to exceeding the capacity of WSNs, which results in congestion, latency, and packet loss. Congestion in WSNs not only results in information loss but also burns a significant amount of energy. To tackle this issue, a practical computational intelligence approach for optimizing data transmission while decreasing latency is necessary. In this article, a Softmax-Regressed-Tanimoto-Reweight-Boost-Classification- (SRTRBC-) based machine learning technique is proposed for effective routing in WSNs. It can route packets around busy locations by selecting nodes with higher energy and lower load. The proposed SRTRBC technique is composed of two steps: route path construction and congestion-aware MIMO routing. Prior to constructing the route path, the residual energy of the node is determined. After that, the residual energy level is analyzed using softmax regression to determine whether or not the node is energy efficient. The energy-efficient nodes are located, and numerous paths between the source and sink nodes are established using route request and route reply. Following that, the SRTRBC technique is used for congestion-aware routing based on buffer space and bandwidth capability. The path that requires the least buffer space and has the highest bandwidth capacity is picked as the optimal route path among multiple paths. Finally, congestion-aware data transmission is used to minimize latency and data loss along the route path. The simulation considers a variety of performance metrics, including energy consumption, data delivery rate, data loss rate, throughput, and delay, in relation to the amount of data packets and sensor nodes.
Ramzi Salah, Muaadh Mukred, Lailatul Qadri binti Zakaria, Rashad Ahmed, and Hasan Sari
Hindawi Limited
Named entity recognition (NER) is fundamental in several natural language processing applications. It involves finding and categorizing text into predefined categories such as a person's name, location, and so on. One of the most famous approaches to identify named entity is the rule-based approach. This paper introduces a rule-based NER method that can be used to examine Classical Arabic documents. The proposed method relied on triggers words, patterns, gazetteers, rules, and blacklists generated by the linguistic information about entities named in Arabic. The method operates in three stages, operational stage, preprocessing stage, and processing the rule application stage. The proposed approach was evaluated, and the results indicate that this approach achieved a 90.2% rate of precision, an 89.3% level of recall, and an F-measure of 89.5%. This new approach was introduced to overcome the challenges related to coverage in rule-based NER systems, especially when dealing with Classical Arabic texts. It improved their performance and allowed for automated rule updates. The grammar rules, gazetteers, blacklist, patterns, and trigger words were all integrated into the rule-based system in this way.
Burkan Hawash, Umi A. Mokhtar, Zawiyah M. Yusof, Muaadh Mukred, and Abdulguddoos S. A. Gaid
IEEE
The Internet of Things (IoT) is defined as a potentially effective means of integrating multiple technologies to support the oil and gas (O&G) sector as a network of physical objects connected to the Internet. In Yemen, O&G organizations can embedded vehicles, equipment, buildings, fire siren and wells with electronics, software, sensors, and network connectivity that is now evolving. It is assumed that in one way or another, everything should be connected to one network to ease processes of business. To make IoT a reality, and not only remain academic, O&G sector must be able to engage in and pick up this technology in its day-to-day activities. Several studies have explored IoT’s potential for numerous organizations. However, IoT remains inadequately applied by organizations, including O&G sectors in developing countries. This article attempts to identify the factors that influence users to adopt IoT in the O&G sector in Yemen. Based on a study of prior tests, drivers were identified. Furthermore, a framework is proposed based on information system adoption theory which is the technology-organization-environment (TOE). Partial least squares structural equation modeling (PLS-SEM) has become a popular tool for analyzing such relationships is applied to a survey of 390 IoT users, with results indicating that the factors selected in this study significantly affected the IoT adoption in the Yemeni O&G sector. This study is enabling O&G organizations to understand the factors of IoT adoption, to improve their framework of business and investment in IoT and to inspire researchers to continue research into other IoT adoption or implementation factors.
Nouf Abdulaziz Alzahrani, Siti Norul Huda Sheikh Abdullah, Ibrahim Mohamed, and Muaadh Mukred
Hindawi Limited
The development of fuzzy sets in geographic information systems (GIS) arose out of the need to handle uncertainty and the ability of soft computing technology to support fuzzy information processing. Fuzzy logic is an alternative logical foundation coming from artificial intelligence (AI) technology with several useful implications for spatial data handling. GIS has been found to have a crucial role in the performance of public sector organizations (PSO). However, the literature shows no universal model to support and shed light on GIS adoption, which lessens the chances for effective GIS adoption and usage. Therefore, a new model is needed for successful adoption and eventual enhanced organization’s performance. Thus, there is a need to investigate the factors that can bring about GIS adoption. Models for GIS adoption in literature are few and far between, and the few that exist are not applicable as they do not cover all the significant factors that can contribute to adoption success. Hence, this paper brought a GIS adoption model for PSOs to promote their performance. The model was developed through the extension of the Technology Acceptance Model (TAM) in addition to the DeLone and McLean’s Success Model. The study involved interviews with ten experts in ranking the extracted factors, and data was analyzed through thematic analysis. On the basis of the obtained analysis findings, the fundamental factors were found to be significant in their effects, and GIS adoption sufficiently related to the overall performance. Thus, the study contributes to the body of knowledge by filling the gap in the literature.
Hanan Mohammed Oumran, Rodziah Binti Atan, Rozi Nor Haizan Binti Nor, Salfarina Binti Abdullah, and Muaadh Mukred
Hindawi Limited
Currently, higher learning institutions (HLIs) are facing their most challenging problem in inefficient information management. The knowledge management system (KMS) application calls for providing several benefits to lecturers and students, producing daily information, documenting records for evidence of a transaction, and eventually improving the decision-making process. Knowledge management can be coupled with fuzzy logic to deal with imprecision and uncertainty of data in a KMS. The ICT dynamic development has shifted the HLI operations from manual to electronic-based handling of related information. KMS is one of the systems that are of significant consideration in this regard. Nevertheless, such a system has not been extensively adopted as expected due to users’ rejection of its use. In the present paper, the factors affecting the decision to adopt/reject KMS are highlighted. The study is qualitative and entails a critical review of the related literature concerning the topic, backed by interviews. KMS experts working with highly reputable HLI were interviewed. A total of 11 factors were focused on in light of their effect on the decision to adopt/reject KMS, as argued by the technological adoption theories and literature review. All the factors were validated and placed in ranks by the experts. From the results, a novel conceptual framework of KMS adoption was developed for Libyan HLIs to bring about technology adoption and improved decision-making.
Muaadh Mukred, Z. M. Yusof, U. A. Mokhtar, A. Sadiq, Burkan Hawash and W. Ahmed
Korean Society for Internet Information (KSII)
Electronic Records Management System (ERMS) is a computer program or set of applications that is utilized for keeping up to date records along with their storage. ERMS has been extensively utilized for enhancing the performance of academic institutions. The system assists in the planning and decision-making processes, which in turn enhances the competencies. However, although ERMS is significant in supporting the process of decision-making, the majority of organizations have failed to take an initiative to implement it, taking into account that are some implementing it without an appropriate framework, and thus resulted in the practice which does not meet the accepted standard. Therefore, this study identifies the factors influencing the adoption of ERMS among employees of HLI in Yemen and the role of such adoption in the decision-making process, using the Unified Theory of Acceptance and Use of Technology (UTAUT) along with Technology, Organization and Environment (TOE) as the underpinning theories. The study conducts a cross-sectional survey with a questionnaire as the technique for data collection, distributed to 364 participants in various Yemeni public Higher Learning Institutions (HLI). Using AMOS as a statistical method, the findings revealed there are significant and positive relationships between technology factors (effort expectancy, performance expectancy, IT infrastructure and security), organizational factors (top management support, financial support, training, and policy),environmental factors (competitiveness pressure, facilitating conditions and trust) and behavioral intention to adopt ERMS, which in return has a significant relationship with the process of decision-making in HLI. The study also presents a variety of theoretical and empirical contributions that enrich the body of knowledge in the field of technology adoption and the electronic record’s domain.
Burkan Hawash, Umi Asma’ Mokhtar, Zawiyah M. Yusof, and Muaadh Mukred
Emerald
Purpose Identification of factors for electronic records management system (ERMS) adoption is important as it allows organizations to focus their efforts on these factors to ensure success. The purpose of this paper is to identify the factors that influence ERMS adoption in the Yemeni oil and gas (O&G) sector. Design/methodology/approach This paper conducts a systematic literature review (SLR) to extract the most common factors that could facilitate successful ERMS adoption. Information technology (IT) experts were asked to rank the extracted factors via an e-mail questionnaire and to recommend specific critical success factors that must be given extra attention to increasing the success of ERMS adoption. Essentially, the proposed methodology is technology-organization-environment (TOE) modeling to examine the important factors influencing decision-makers in the Yemeni O&G sector regarding ERMS adoption. Findings This paper identifies factors influencing ERMS adoption based on SLR and an expert-ranking survey. The data that were collected from IT experts were analyzed using the statistical package for the social sciences. The results showed that only 12 out of 20 factors were significant. The experts then added three new factors, resulting in 15 significant factors classified into the three dimensions as follows: technology, organization and environment. Originality/value Limited studies have been carried out in the context of the O&G sector, even among developed countries such as Canada, the UK and Australia. These studies have focused on a limited number of factors for ERMS adoption targeting better utilization of human resources, faster and more user-friendly system responses and suitability for organizational ease. This paper explores the factors that may prove useful in adopting of ERMS in the O&G sector of developing countries, similar to Yemen.
C. Priya, G. Suseendran, D. Akila, and B. Vivekanandam
Springer Singapore
Muaadh Mukred, Zawiyah M. Yusof, Nor Azian Binti Md. Noor, Bakare Kazeem Kayode, and Ruqiah Al-Duais
Springer International Publishing
Muaadh Mukred and Zawiyah M. Yusof
IGI Global
This article discusses the relationship between educational institutes that use ERMS and the performance of those institutions. This article uses a mixed explanatory method that incorporated quantitative and qualitative approaches. The quantitative method collected the responses from 364 participants. This was followed by a qualitative approach where experts were interviewed to verify the model. The results generated using the quantitative approach demonstrated that the quality of the system, information, and service as well as the security provided by the system had a significant positive relationship with the successful adoption of ERMS, which in turn improved performance. Moreover, the qualitative results that gathered through the experts confirmed the findings and contributed to enriching the understanding of the adoption of ERMS in educational institutions.
Muaadh Mukred, Zawiyah Mohamad Yusof, Umi Asma’ Mokhtar, and Fariza Fauzi
SAGE Publications
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.
Muaadh Mukred, Zawiyah M. Yusof, and Fahad M. Alotaibi
Institute of Electrical and Electronics Engineers (IEEE)
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 paper, therefore, proposed a model for the ERMS adoption to support the productivity and performance of higher professional education (HPE) institutions in the Yemeni context. This paper used the unified theory of acceptance and use of technology (UTAUT) and a mixed explanatory approach to gather quantitative and qualitative data. Data were 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 recommended values range that assumed the acceptability of the developed model. The model was found to be of a 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 the ERMS adoption among HPEs. Such adoption ensures educational institutions’ productivity.
Muaadh Mukred, Zawiyah M. Yusof, Fahad M. Alotaibi, Umi Asma' Mokhtar, and Fariza Fauzi
Institute of Electrical and Electronics Engineers (IEEE)
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.