Saudi Cultural Missions Theses & Dissertations
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Item Restricted Employee Readiness for AI Adoption in Riyadh’s Healthcare Sector: Perceptions and Organizational Support(Saudi Digital Library, 2025) Almutairi, Hadeel; Cui, QinquanArtificial intelligence (AI) is widely recognized as a significant driver of digital transformation across several domains, with the healthcare sector identified as one of the most influenced sectors. This research assesses employee readiness for AI among healthcare professionals in Riyadh, Saudi Arabia, with particular attention paid to perceptions (perceived usefulness and ease of use) and organizational support, including training and management support. This study employed a quantitative, cross-sectional, and correlational design. A survey was administered to evaluate employee readiness levels and potential predictors of AI readiness. A total of 120 employees participated with overall readiness (M = 4.20, Var=0.64). The regression explained 39.4% of the variance in readiness, with perceived usefulness (B = 0.44, p < 0.001) and training (B = 0.40, p < 0.001) contributing positively to readiness, while management support contributed negatively (B = -0.17, p = 0.011), and ease of use was not significant (B = 0.05, p = 0.574). Independent t-tests and ANOVA confirmed no significant differences in readiness by gender (p = 0.40), job type (p = 0.44), or years of experience (p = 0.56). The results showed that perceived usefulness and training were the strongest predictors of employee readiness for AI. While ease of use was not significant, organizational support had a negative effect. This study contributes to the literature on AI readiness in Saudi healthcare, highlighting perceived usefulness and training as key drivers for AI adoption, while questioning assumptions about the management support role in AI adoption. Healthcare leaders and policymakers should prioritize training, communicate the practical benefits of AI, and ensure that managerial commitment is supported by resources.16 0Item Restricted The Extent of Readiness to adopt and utilize Emerging Technologies in Private Sector Organizations in the Kingdom of Saudi Arabia(Saudi Digital Library, 2025) Ismail, Malik; O'dea, ChristinThis research aims to contribute to bridging the gap in the literature in the field of Managing Technological Change and Information Systems management, by exploring the state of readiness to adopt and utilize emerging technologies in organizations within the Private Sector of the Kingdom of Saudi Arabia. While literature has highlighted the success of the public sector, and factors affecting the adoption of specific technologies, this research contributes findings across different organizations in the Private Sector, with a general definition of Emerging Technologies. This research uses qualitative methodologies to explore context-specific contributors to readiness, which candidates reported in Semi-Structured interviews. Findings reveal that while technological awareness is high, organizational readiness is hindered by legacy IT systems, centralized decision-making, and skills gaps. SMEs exhibited agility in experimentation, while large firms struggled with procurement cycles and hierarchical cultures. The study contributes to existing research by contextualizing digital transformation in the Private Sector of Saudi Arabia, by providing practical insights for Business Leaders seeking to align readiness with national digitalization agendas, while also highlighting skill gaps relevant to educational policy and workforce development.14 0Item Restricted Perceived business model impacts of blockchain and other advanced technologies adoption(University College Cork, 2025) Alshabeeb, Zainab; Daly, Mary; Feller, JosephThe adoption of advanced technologies by organisations can affect all aspects of an organisation’s business model. This is particularly true for disruptive technologies such as blockchain, Internet of Things (IoT), and others. The objective of this study is “To explore the perceived impacts of blockchain and other advanced technologies adoption on an organisation's business model.” A web-based survey was derived by adopting the Business Model Canvas (BMC) (Osterwalder & Pigneur, 2010) as a lens, and 19 business model impacts were identified in prior research. The study employs a mixed-method approach in two phases: an exploratory study with 31 questionnaire responses plus short interviews, and an extended study with 72 survey responses. The exploratory study focuses on blockchain, small and medium enterprises, and Saudi Arabia. The extended study contains several technologies, organisation sizes, and regions. The findings reveal that the majority of respondents (N=72) perceive all 19 business model impacts stemming from adopting advanced technologies in general, although this correlates with organisational size for some impacts. However, the perceived impacts of blockchain adoption as reported by blockchain adopters (N=41) are mixed. The majority of blockchain adopters surveyed do not perceive the anticipated impacts of blockchain adoption, although again this correlates with organisational size and sector. The study makes several key contributions that agree with prior research on the perceived impacts of technology adoption in general, challenging prior research on the perceived impacts of blockchain adoption specifically, and extending current knowledge in terms of the relationships between size, sector, and perceived impacts. The study also contributes to practice, offering insight to managers who are motivated to address the challenges of technology adoption, mitigate negative effects, and maximise positive impacts. Such decision makers can benefit from the insights of the study about the importance of use cases, ROI measurement, and other factors.10 0Item Restricted ACCEPTANCE OF BLOCKCHAIN TECHNOLOGY BY HIGHER EDUCATION INSTITUTIONS IN THE KINGDOM OF SAUDI ARABIA(Aston University, 2025) Alhumayzi, Mohammed; Batista, Luciano; Benson, VladlenaThe increasing adoption of new technologies in the Higher Education Institutions (HEIs) sector highlights the importance of exploring blockchain acceptance among employees. Adopting blockchain, as an emerging technology, is likely to encounter resistance among employees. This study explores this issue. Specifically, this study aims to determine the drivers and hindrances of blockchain acceptance among employees in the HEIs industry. To address this aim, this study proposes a framework that extends the unified theory of acceptance and use of technology (UTAUT) with individual characteristics. The framework represents factors that explain blockchain acceptance. The identified elements are performance expectancy (PE), effort expectancy (EX), social influence (SI), facilitating conditions (FC), trust, perceived security (SEC) and awareness (AW). The relationships among these factors were examined based on a quantitative approach, where an online questionnaire was employed to collect data from administrative and academic staff working for HEIs in the Kingdom of Saudi Arabia (KSA). Partial Least Squares Structural Equation Model (PLS-SEM) and Multi-group Analysis (MGA) techniques were employed to analyse 394 responses. The findings of this study revealed the direct drivers and hindrances of blockchain acceptance, i.e., PE, FC, SEC and AW. Additionally, this study demonstrated the moderating effects of AW between FC and blockchain acceptance. Furthermore, it determined specific indirect effects of the EX, trust and SEC on blockchain acceptance. Moreover, this research detected significant differences between categories’ subsamples and identified the significant factors of blockchain acceptance per subsample. Finally, this research identified where blockchain needs to be adopted most within the HEIs, i.e., financial exchange, certificate management, and students’ assessment areas. The HEIs industry in KSA could use these findings to develop concise strategies that encourage the adoption of blockchain. Scholars might also employ the proposed framework to investigate the adoption of blockchain.35 0Item Restricted Navigating Consumer Resistance: Understanding Barriers to Technology Adoption in the Modern Market Through Systematic Literature Review(University of Essex, 2024-09-11) Alsaidan, Nawaf; Kuanr, AbhisekThis study systematically explores and identifies factors contributing to consumer resistance to technology adoption in modern markets and proposes strategies to address them. The research focuses on three objectives: identifying primary barriers to adoption, analyzing psychological, sociocultural, and functional impacts, and evaluating marketing strategies to mitigate resistance. Using a systematic literature review of 21 studies (2010–2023), the study finds that consumer resistance arises from psychological barriers (e.g., tradition and skepticism), sociocultural influences (e.g., norms and social pressures), and functional issues (e.g., value, risk, complexity). It concludes that holistic approaches addressing all barrier types are essential for effective technology adoption.8 0Item Restricted Navigating Consumer Resistance: Understanding Barriers to Technology Adoption in the Modern Market Through Systematic Literature Review(University of Essex, 2024-09-11) Alsaidan, Nawaf; Kuanr, AbhisekThis study systematically explores and identifies factors contributing to consumer resistance to technology adoption in modern markets and proposes strategies to address them. The research focuses on three objectives: identifying primary barriers to adoption, analyzing psychological, sociocultural, and functional impacts, and evaluating marketing strategies to mitigate resistance. Using a systematic literature review of 21 studies (2010–2023), the study finds that consumer resistance arises from psychological barriers (e.g., tradition and skepticism), sociocultural influences (e.g., norms and social pressures), and functional issues (e.g., value, risk, complexity). It concludes that holistic approaches addressing all barrier types are essential for effective technology adoption.25 0Item Restricted An In-Depth Analysis of the Adoption of Large Language Models in Clinical Settings: A Fuzzy Multi-Criteria Decision-Making Approach(University of Bridgeport, 2024-08-05) Aldwean, Abdullah; Tenney, DanThe growing capabilities of large language models (LLMs) in the medical field hold promising transformational change. The evolution of LLMs, such as BioBERT and MedGPT, has created new opportunities for enhancing the quality of healthcare services, improving clinical operational efficiency, and addressing numerous existing healthcare challenges. However, the adoption of these innovative technologies into clinical settings is a complex, multifaceted decision problem influenced by various factors. This dissertation aims to identify and rank the challenges facing the integration of LLMs into healthcare clinical settings and evaluate different adoption solutions. To achieve this goal, a combined approach based on the Fuzzy Analytic Hierarchy Process (FAHP) and the Fuzzy Technique for Order of Preference by Similarity to Ideal Solution (Fuzzy TOPSIS) has been employed to prioritize these challenges and then use them to rank potential LLM adoption solutions based on experts’ opinion. However, utilizing LLMs technologies in clinical settings faces several challenges across societal, technological, organizational, regulatory, and economic (STORE) perspectives. The findings indicate that regulatory concerns, such as accountability and compliance, are considered the most critical challenges facing LLMs adoption decision. This research provides a thorough and evidence-based assessment of LLMs in the clinical settings. It offers a structured framework that helps decision-makers navigate the complexities of leveraging such disruptive innovations in clinical practice.40 0Item Restricted Impact of Technology Adoption on the Success of E-Commerce Technologies in Small and Medium Enterprises(The University of Newcastle, 2024-02-17) Almtiri, Ziad Hmwd A; Miah, Shah J; Noman, NasimulThe primary task of this research is to investigate the relationship between the adoption of technology and the success of e-commerce technologies in Small and Medium Enterprises (SMEs). The study examines how specific technologies affect the overall performance and profitability of the kingdom of Saudi Arabia’s (KSA) SMEs. To study the connection between these variables, it is essential to consider e-commerce trends among modern SME businesses. E-commerce technologies become more and more evolving and relevant in different business operations, bringing benefits and convenience to all stakeholders involved. Although e-commerce is developing at a higher speed in the KSA country context compared to other countries, there is still scepticism in existing studies and substantial issues to its full adoption were discussed. Therefore, the aim of this research is therefore of paramount task to reveal the positive effect of e-commerce technology and encourage SMEs to incorporate technology adoption into their business plans. For this, the research uses a mix of qualitative and quantitative methods of analysis, namely, a questionnaire, with a positivist interpretation of the collected data. To analyse the data accurately, the study adopts a Descriptive Statistics approach in SPSS platform. All the participants who are involved in the research is subjected and treated ethically following the University of Newcastle ethical guidelines (Protocol Number: H-2022-0290). The main limiting factors for the adoption of e-commerce technologies in the KSA have to do with the perception of e-commerce amongst the SMEs managers. Business Organisations are eager to use new technologies, realising their benefits for their continuous improvement of practices. E-commerce, on the other hand, is blurry in the minds of SMEs practitioners of the KSA, which makes them distrustful, and hence resistant to the adoption of new technologies that impact in developing e-commerce strategies.58 0Item Restricted Fintech and Entrepreneurship: An Assessment Model to Evaluate Policy Instruments for Fintech Adoption by Small and Medium Enterprises (SMEs)(ProQuest, 2023-11-01) Alassaf, Deemah; Daim, Tugrul U.Small and medium enterprises (SMEs) are the engines that drive economic development. They are the backbone of the middle class as they provide social stability, innovation, inclusive growth, and poverty alleviation. SMEs contribute significantly to job creation, employment, tax provision and the Gross Domestic Product (GDP). However, they face inferior conditions and challenges when it comes to their financing compared to that of large enterprises, as well as having a high expectancy of failing. Because of these limitations, SMEs tend to grow slowly since building up higher credit is difficult for them, and in addition to this, they lack access to broad financing channels. Hence, Fintech solutions offer promising potential for improving SMEs’ access to finance through extending them more accessible and available services, more efficient credit risk assessments and reduced transaction costs. These tools can offer a valuable opportunity for ventures that are too small in size, and involve a great deal of risk, or serve a social purpose. While researchers and practitioners have been promoting Fintech as a potential financial safeguard for SMEs’ needs, evidence shows an inadequate adoption rate of SMEs to such solutions. Therefore, this research aims to provide a comprehensive examination for Fintech policy instruments and analyze their effectiveness on increasing the adoption of Fintech by SMEs through evaluating the essential policy targets impacting the adoption of Fintech and assessing their weights and priorities in the context of SMEs. The research was built upon an inclusive hierarchical decision model and a comprehensive literature review. Experts’ insights were utilized to identify the most important factors influencing Fintech adoption and policy effectiveness. The Hierarchical Decision Modeling (HDM) methodology was used to identify the relative importance of those factors proposing a policy evaluation tool to assess the effectiveness of policy instruments on increasing Fintech adoption. To test the practicality and value the research model adds to the research objective, a case study of the policy instrument effectiveness, the Saudi Arabian regulatory sandbox, was conducted. This research presents the identification of seventeen distinct policy targets that fall within four main perspectives along with their relative weights, as it also integrates the desirability curves methodology that measures the importance of each perspective and criterion. The case study was introduced to illustrate how the model could be used to identify the policy instrument’s actual performance in terms of influencing SMEs adoption of Fintech, identify the instrument’s strengths and weaknesses, and offer recommendations and guiding principles on how to improve the detected weaknesses to increase the policy instrument’s effectiveness on increasing the adoption of Fintech by SMEs.38 0Item Restricted Technology Adoption For Language Learning Purposes In Conservative Territories In The Kingdom Of Saudi Arabia(Saudi Digital Library, 2023-10-10) Mubarak, Rami; Millar, Robert McCollTeaching and learning the English language have become crucial endeavours in the Arab world, specifically in the Kingdom of Saudi Arabia. Additionally, using technology for the purposes of learning the English language has also become central to the digital students of this generation. Before the successful adoption of technology for language learning purposes take place, factors that might impact students’ behavioural intention (BI) need to be investigated, particularly in relation to students coming from conservative territories. As such, in the current study, the unified theory of acceptance and use of technology (UTAUT) was extended and utilised as a lens through which to spot these factors, whilst quantitative and qualitative methods were applied to answer the research questions. As for the number of participants, there were 220 males and 263 females. The findings indicated that learning expectancy (LE), effort expectancy (EE), attitude towards using technology (ATUT), hedonic motivation (HM), trust (TR) and habit (HT) had an influence on students’ behavioural intention (BI) towards accepting and using technology to learn the English language in technology-enhanced language learning (TELL) classrooms. In contrast, social influence (SI) and facilitating condition (FC) did not have any impact.18 0