Browsing by Author "Al-Emran, Mostafa"

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    A SYSTEMATIC REVIEW OF CRYPTDB: IMPLEMENTATION, CHALLENGES, AND FUTURE OPPORTUNITIES
    (Journal of Management Information and Decision Sciences, 2021) Yousuf, Hana; A. Salloum, Said; Aburayya, Ahmad; Al-Emran, Mostafa; Shaalan, Khaled
    In the case of compromised databases or interested database managers, CryptDB has been built for validated and realistic protection. CryptDB operates through encrypted data while executing SQL queries. The key concept of the SQL-aware encryption technique is to map SQL operations to encryption methods, adjustable query-driven encryption which facilitates CryptDB to modify the encryption level of data depending on user queries and to alter the data through layered encryption levels in an efficient manner. The systematic literature review in this paper shows that there is ongoing research regarding the implementation of CryptDB in new applications such as cloud computing and management information systems. Experiments are being conducted to improve the encryption schemes and layers to avoid data leakage when CryptDB is applied in dynamic applications. Further, there are studies on alternative query-processing systems to improve the performance and throughput. However, CryptDB is found to be the only practical approach to process the queries for encrypted data.
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    An Innovative Study of E-Payment Systems Adoption in Higher Education: Theoretical Constructs and Empirical Analysis
    (International Journal of Interactive Mobile Technologies, 2019) A. Salloum, Said; Al-Emran, Mostafa; Khalaf, Rifat; Habes, Mohammed; Shaalan, Khaled
    Examining the adoption of e-payment systems is not a new research topic. Nevertheless, studying the factors affecting the adoption of epayment systems in higher educational institutions is a new research trend. Thus, this study is considered one of the few that attempts to investigate the fac tors affecting the e-payment systems adoption in six different universities in the United Arab of Emirates (UAE). A total number of 289 students took part in the study. This study proposed a new research model in which the students’ intention to use the e-payment systems are affected by five different factors including perceived benefit, performance expectancy, perceived risk, perceived security/privacy, and trust. The partial least squares-structural equation modeling (PLS-SEM) approach was used to validate the research model. The empirical results suggested that perceived benefit and performance expectancy have a significant positive relationship with the students’ intention to use e-payment systems, whereas perceived security/privacy and perceived risk exhibited a significant negative relationship. However, the results triggered out that trust has an insignificant relationship with the students’ intention to use e-payment systems. The results acquired from this research provide a fresh and an up-to-date information on the e-payment systems adoption in the higher educational institutions.
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    ASystematic Review on Blockchain Adoption
    (MDPI, 2022) AlShamsi, Mohammed; Al-Emran, Mostafa; Shaalan, Khaled
    : Blockchain technologies have received considerable attention from academia and industry due to their distinctive characteristics, such as data integrity, security, decentralization, and reli ability. However, their adoption rate is still scarce, which is one of the primary reasons behind conducting studies related to users’ satisfaction and adoption. Determining what impacts the use and adoption of Blockchain technologies can efficiently address their adoption challenges. Hence, this systematic review aimed to review studies published on Blockchain technologies to offer a thorough understanding of what impacts their adoption and discuss the main challenges and opportunities across various sectors. From 902 studies collected, 30 empirical studies met the eligibility criteria and were thoroughly analyzed. The results confirmed that the technology acceptance model (TAM) and technology–organization–environment (TOE) were the most common modelsforstudying Blockchain adoption. Apart from the core variables of these two models, the results indicated that trust, perceived cost, social influence, and facilitating conditions were the significant determinants influencing several Blockchain applications. The results also revealed that supply chain management is the main domain in which Blockchain applications were adopted. Further, the results indicated inadequate exposure to studying the actual use of Blockchain technologies and their continued use. It is also essential to report that existing studies have examined the adoption of Blockchain technologies from the lens of the organizational level, with little attention paid to the individual level. This review is believed to improve our understanding by revealing the full potential of Blockchain adoption and opening the door for further research opportunities.
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    Chatbot Adoption: A Multiperspective Systematic Review and Future Research Agenda
    (IEEE, 2023) Alsharhan , Abdulla; Al-Emran, Mostafa; Shaalan, Khaled
    —Studies on Chatbot adoption are gaining traction across different fields. Previous studies have outlined several drivers of Chatbot adoption through the lenses of various tech nology adoption theories. However, these studies have not been thoroughlyreviewedandsynthesized.Therefore,thisarticleaimsto analyzethetechnologyadoptiontheories,antecedents,moderators, domains, methodologies, and participants through a multiperspec tive viewpoint. Out of 3942 studies collected, 219 studies were ana lyzed. The main findings indicated that the technology acceptance model, social presence theory, and computers are social actors are the main dominant theories in explaining Chatbot adoption. MoststudiesfocusedonexaminingtheusageintentionofChatbots, with limited investigations on actual use and continuous intention. Nearly 63% of the analyzed studies did not employ moderators, andthose that did tend to do so mostfrequently focused on gender, Chatbot/technical experience, andage.Thisarticle presents afresh viewpoint that deepens our understanding of Chatbot adoption and proposes several agendas for future research. The agenda incorporates research directions for Chatbots adoption in general and generative artificial intelligence in specific. It also offers sev eral theoretical contributions and provides relevant information to Chatbot developers, decision-makers, practitioners, IT vendors, and policymakers.
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    Factors Affecting Autonomous Vehicles Adoption: A Systematic Review, Proposed Framework, and Future Roadmap
    (Taylor & Francis online, 2023) Al Mansoori, Saeed; Al-Emran, Mostafa; Shaalan, Khaled
    Autonomous vehicles (AVs) offer several benefits, such as improving road safety, mitigating traffic congestion, and reducing fuel consumption and gas emissions. Despite these benefits, their adop tion rate remains limited due to various factors influencing users’ decisions. While previous studies have identified numerous factors influencing AV adoption using various adoption frameworks, the factors have not been comprehensively analyzed and synthesized. Thus, this systematic review aims to bridge this gap by identifying and classifying the factors influencing the adoption of AVs. Out of 3,532 collected research papers, 71 empirical studies were analyzed thoroughly. The find ings demonstrated that the technology acceptance model (TAM) was the most widely used model for investigating AV adoption. The identified factors in the analyzed studies were classified into distinct categories: psychological and behavioral factors, technological factors, social factors, envir onmental factors, security and privacy factors, AV-related factors, risky and negative factors, condi tional factors, and monetary factors. We have proposed an AV adoption framework grounded in this taxonomy to direct subsequent empirical research. We have also highlighted numerous agen das to serve as a blueprint for future AV adoption studies. This review offers various theoretical insights and actionable recommendations for multiple AV research, development, and implemen tation stakeholders.
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    Factors affecting the E-learning acceptance: A case study from UAE
    (E-learning . Technology acceptance . Knowledge sharing . Technology innovativeness. System quality. Trust, 2018) A. Salloum, Said; Al-Emran, Mostafa; Shaalan, Khaled; Tarhini, Ali
    The main objective of this article is to study the factors that affect university students’ acceptance of E-learning systems. To achieve this objective, we have proposed a new model that aims to investigate the impact of innovativeness, quality, trust, and knowledge sharing on E-learning acceptance. Data collection has taken place through an online questionnaire survey, which was carried out at The British University in Dubai (BUiD) and University of Fujairah (UOF) in the UAE. There were 251 students participated in this study. Data were analyzed using SmartPLS and SPSS. The Structural Equation Modelling (SEM) has been used to validate the proposed model. The outcomes revealed that knowledge sharing and quality in the universities have a positive influence on E-learning acceptance among the students. Innovativeness and trust were found not to significantly affect the E-learning system acceptance. By identifying the factors that influence the E-learning acceptance, it will be more useful to provide better services for E-learning. Other implications are also presented in the study.
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    Medical data integration using HL7 standards for patient’s early identification
    (PLOS ONE, 2021) A. AlQudahl, Adi; Al-Emran, Mostafa; Shaalan, Khaled
    Integration between information systems is critical, especially in the healthcare domain, since interoperability requirements are related to patients’ data confidentiality, safety, and satisfaction. The goal of this study is to propose a solution based on the integration between queue management solution (QMS) and the electronic medical records (EMR), using Health Level Seven (HL7) protocols and Extensible Markup Language (XML). The proposed solu tion facilitates the patient’s self-check-in within a healthcare organization in UAE. The solu tion aims to help in minimizing the waiting times within the outpatient department through early identification of patients who hold the Emirates national ID cards, i.e., whether an Emir ati or expatriates. The integration components, solution design, and the custom-designed XML and HL7 messages were clarified in this paper. In addition, the study includes a simula tion experiment through control and intervention weeks with 517 valid appointments. The experiment goal was to evaluate the patient’s total journey and each related clinical stage by comparing the “routine-based identification” with the “patient’s self-check-in” processes in case of booked appointments. As a key finding, the proposed solution is efficient and could reduce the “patient’s journey time” by more than 14 minutes and “time to identify” patients by 10 minutes. There was also a significant drop in the waiting time to triage and the time to fin ish the triage process. In conclusion, the proposed solution is considered innovative and can provide a positive added value for the patient’s whole journey.
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    Technology Acceptance in Healthcare: A Systematic Review
    (MDPI, 2021) A. AlQudah, Adi; Al-Emran, Mostafa; Shaalan, Khaled
    Understanding the factors affecting the use of healthcare technologies is a crucial topic that has been extensively studied, specifically during the last decade. These factors were studied using different technology acceptance models and theories. However, a systematic review that offers extensive understanding into what affects healthcare technologies and services and covers distinctive trends in large-scale research remains lacking. Therefore, this review aims to systematically review the articles published on technology acceptance in healthcare. From a yield of 1768 studies collected, 142 empirical studies have met the eligibility criteria and were extensively analyzed. The key findings confirmed that TAM and UTAUT are the most prevailing models in explaining what affects the acceptance of various healthcare technologies through different user groups, settings, and countries. Apart from the core constructs of TAM and UTAUT, the results showed that anxiety, computer self-efficacy, innovativeness, and trust are the most influential factors affecting various healthcare technologies. The results also revealed that Taiwan and the USA are leading the research of technology acceptance in healthcare, with a remarkable increase in studies focusing on telemedicine and electronic medical records solutions. This review is believed to enhance our understanding through a number of theoretical contributions and practical implications by unveiling the full potential of technology acceptance in healthcare and opening the door for further research opportunities.
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    Toward an Integrated Model for Examining the Factors Affecting the Acceptance of Queue Management Solutions in Healthcare
    (IEEE, 2022) Ahmad AlQudah, Adi; Al-Emran, Mostafa; U. Daim, Tugrul; Shaalan, Khaled
    Despite the previous article on technology adoption and the importance of users’ intention to use various technologies in healthcare, users’ acceptance of queue management solutions (QMS) has rarely been measured. The key driver for this article is to evaluate the constructs that have an influence on the acceptance of QMS in the healthcare domain. To achieve this purpose, this article proposes an integrated model based on the integration of various constructs extracted from different theoretical models, including the unified theory of acceptance and use of technology (UTAUT), technology acceptance model (TAM), and social cognitive theory (SCT) along with trust and innovativeness as external factors. The data were collected using an online questionnaire survey from 242 healthcare professionals. The structural equation modeling technique has been employed to validate the model. In general, the results exposed that the suggested model has explained 66.5% of the total variance in the behavioral intention to use QMS. The proposed model is believed to be helpful in exploring the acceptance of other information technologies in the healthcare domain, and the results can provide valuable knowledge to managers and decision-makers in healthcare organizations.
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    Understanding key drivers affecting students’ use of artificial intelligence-based voice assistants
    (2022) Hamad Al Shamsi, Jawaher; Al-Emran, Mostafa; Shaalan, Khaled
    Artificial intelligence (AI)-based voice assistants have become an essential part of our daily lives. Yet, little is known concerning what motivates students to use them in educational activities. Therefore, this research develops a theoretical model by extending the technology acceptance model (TAM) with subjective norm, enjoy ment, facilitating conditions, trust, and security to examine students’ use of AI based voice assistants for instructional purposes. The developed model was then validated based on data collected from 300 university students using the PLS-SEM technique. The results supported the role of enjoyment, trust, and perceived ease of use (PEOU) in affecting the perceived usefulness (PU) of voice assistants. The empirical results also showed that facilitating conditions and trust in technology strongly influence the PEOU. Contrary to the extant literature, the results indicated that subjective norm, facilitating conditions, and security did not impact PU. Simi larly, subjective norm and enjoyment did not affect PEOU. This research is believed to add a holistic understanding of the key drivers affecting students’ use of voice assistants for educational purposes. It offers several theoretical contributions and practical implications on how to successfully employ these assistants.
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    Understanding key drivers affecting students’ use of artificial intelligence-based voice assistants
    (Springer, 2022) Hamad Al Shamsi, Jawaher; Al-Emran, Mostafa; Shaalan, Khaled
    Artificial intelligence (AI)-based voice assistants have become an essential part of our daily lives. Yet, little is known concerning what motivates students to use them in educational activities. Therefore, this research develops a theoretical model by extending the technology acceptance model (TAM) with subjective norm, enjoy ment, facilitating conditions, trust, and security to examine students’ use of AI based voice assistants for instructional purposes. The developed model was then validated based on data collected from 300 university students using the PLS-SEM technique. The results supported the role of enjoyment, trust, and perceived ease of use (PEOU) in affecting the perceived usefulness (PU) of voice assistants. The empirical results also showed that facilitating conditions and trust in technology strongly influence the PEOU. Contrary to the extant literature, the results indicated that subjective norm, facilitating conditions, and security did not impact PU. Simi larly, subjective norm and enjoyment did not affect PEOU. This research is believed to add a holistic understanding of the key drivers affecting students’ use of voice assistants for educational purposes. It offers several theoretical contributions and practical implications on how to successfully employ these assistants.