SACM - Malaysia
Permanent URI for this collectionhttps://drepo.sdl.edu.sa/handle/20.500.14154/9660
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Item Restricted IMPACT OF THE INTERNET OF THINGS, DYNAMIC CLOUD CAPABILITIES, ARTIFICIAL INTELLIGENCE, DIGITAL CAPABILITIES, DIGITAL INNOVATION, AND IT FLEXIBILITY ON FIRM PERFORMANCE(UTM, 2025) Alqahtani, Miad Murayh; Singh, HarcharanjitThe rapid evolution of digital technology in the banking sector presents both opportunities and challenges, particularly in the context of Islamic banking in Kingdom of Saudi Arabia (KSA), where the integration of technology must align with Shariah principles. This study investigates the impact of Internet of Things (IOT), dynamic cloud capabilities, artificial intelligence (AI), digital capabilities, digital innovation, and IT flexibility on firm performance within the Islamic banking n KSA. The research used a quantitative research design based on a deductive approach. Moreover, survey questionnaires were administered to 605 middle-level managers across four (4) major Islamic banks in KSA. The data were analyzed using Statistical Package for the Social Sciences (SPSS) and Partial Least Squares Structural Equation Modeling (PLS-SEM), facilitating exploratory data analysis, confirmatory factor analysis, path analysis, and mediation and moderation analyses. from Based on fourteen hypothesis developed on seven (7) hypothesis were supported. The research found a positive and significant relationship between IOT capabilities, AI capabilities and digital innovation with firm performance. However, there is no relationship between dynamic cloud capabilities and firm performance. The research also found a positive and significant relationship between AI capabilities on digital innovation. However, there is no relationship between (IOT capabilities, dynamic cloud capabilities) and digital innovation. In addition, the research found digital innovation mediate the relationship between AI capabilities, and firm performance. However, it is found that digital innovation does not mediate the relationship between (IOT capabilities, dynamic cloud capabilities) and firm performance. The research also found that digital capabilities moderate the relationship between AI capabilities and digital innovation. However, digital capabilities do not moderate the relationship between (IOT capabilities, dynamic cloud capabilities) and digital innovation. Likewise, the research found IT Flexibility moderate the relationship between digital innovation, and firm performance. The research results, expanded the theoretical body of knowledge through its research findings from the context of Islamic banks in KSA. The results are important to the stakeholders of Islamic banks in KSA, as it underscored the critical role of strategic digital technology integration and innovation in enhancing its competitiveness and operational efficiency. The research also provided valuable insights for the policymakers to develop policy that would enhance firm performance in Islamic Banking in KSA. The research results are limited to the Islamic banking in KSA; and cannot be generalized to the entire banking sector in KSA.5 0Item Restricted Guest Satisfaction The Role of Digital and Contacless Service in the Post Covid 19 Era(Taylor's University, 2025) Alghamdi, Fatimah; Abdulrazak, DhiyaThe COVID-19 pandemic has drastically altered the landscape of various sectors, including the hotel and hospitality industry. With the necessity for social distancing and the resultant increase in digital interactions, hospitality businesses have increasingly adopted digital and contactless service methods. In view of this, this study investigates the role of digital and contactless services in enhancing guest satisfaction in the post-COVID-19 era. It attempts to explore the extent to which these services have promoted guest satisfaction, the challenges encountered in their implementation, and the strategies employed to overcome these challenges. The study will make use of quantitative method with data to be collected from the representatives of the hotel guests in the hospitality sector using random sampling technique based on Israel (2012) sample size. A questionnaire of a 5-point Likert scale is used in this investigation. The data collected are analyzed with the aid of SPSS. The findings show that that satisfaction of guest was high in the post-covid-19 era and that digital service plays an enormous role in ensuring guest satisfaction.1 0Item Restricted CELEBRITY ENDORSEMENT AND ITS INFLUENCE ON THE SUCCESS OF SPORTS TOURISM IN SAUDI ARABIA.(Taylor's University, 2025) Alshammari, Majed; Katahenggam, NagathisenCelebrities play an important role in the advertising for creating and enhancing brand image and equity in order to differentiate their products from competitive companies. Thus, the purpose of this study was to examine the influence of celebrity endorsement on sports tourism in Saudi Arabia with a view to finding out the factors that influence the choice of celebrity endorsement, and the degree of influence of celebrity endorsement on sports tourism in Saudi Arabia. The study employed a quantitative design collecting data with the aid of questionnaire from the selected respondents. SPSSv27 was used to analyze the data. It was found, among others, that celebrities positively influence public perceptions of Saudi Arabia as a sports destination and that such factors as cultural alignment and religion of the celebrity influence the choice of celebrity endorsement and its effectiveness. Thus, it was revealed that there is a significant relationship between those celebrity endorsement and success of sport tourism. It was concluded that celebrities who share Saudi cultural values and customs should be given preference in endorsements.10 0Item Restricted To Increase the Awareness of Techno-Entrepreneurship Among Saudi Arabian Women in Saudi Arabia(Universiti Teknologi Malaysia, 2025-01-31) alqahtani, malak; Alhaimi, Basheer MohammedThis research examines the advancement of technological entrepreneurship among women, focusing on overcoming barriers and fostering innovation. The study explores the challenges women entrepreneurs face in the tech industry, their strategies for success, and the support systems necessary for sustained growth. Through interviews with women entrepreneurs and collaboration with industry stakeholders, this research highlights the critical factors influencing women's participation in technological entrepreneurship. The study identifies key obstacles such as gender biases, limited access to funding, and inadequate mentorship opportunities, while also showcasing successful case studies of women who have excelled in this field. Additionally, it explores the role of education, networking, and government policies in shaping a more inclusive entrepreneurial ecosystem. Findings reveal that targeted interventions, such as providing access to funding, mentorship, and training programs, can significantly enhance women's involvement in the tech industry. The research also emphasizes the importance of creating culturally sensitive and inclusive initiatives to empower women and bridge the gender gap in entrepreneurship.This study contributes to the growing body of literature on technological entrepreneurship and offers practical recommendations for policymakers, educators, and industry leaders to support women in their entrepreneurial journeys.16 0Item Restricted Aspect-Based Sentiment Analysis on Healthcare Services Uding pre-trained Languges Model(Malaya University, 2025) Alkathiri, Sarah; Sabri, AznulThis research explores the application of various computational models for aspect- based sentiment analysis (ABSA) of healthcare reviews, a critical component of enhancing healthcare services through feedback analysis. With the rapid expansion of online health platforms, the volume of textual reviews generated by patients provides a rich source of data for understanding patient satisfaction and areas needing improvement. The research thoroughly assesses various models, encompassing conventional statistical models, recurrent neural networks (RNNs), and sophisticated transformer-based models like BERT, RoBERTa, and DistilBERT. Each model was assessed based on its ability to accurately classify sentiments tied to specific aspects of healthcare services, such as cleanliness, staff behavior, and treatment efficacy. Two primary feature extraction techniques, Bag of Words (BoW) and Term Frequency-Inverse Document Frequency (TF-IDF), were employed to transform raw text into a suitable format for model ingestion. Our findings demonstrate that while traditional models offer quick and interpretable results, they sometimes lack the nuanced understanding of context provided by more sophisticated deep learning and transformer models. RNNs, particularly LSTM and BiLSTM, were effective in capturing temporal dependencies in text data, essential for comprehending longer patient feedback.17 0Item Restricted PERCEIVED VALUE AS A MODERATOR ON RELATIONSHIP BETWEEN SERVICE QUALITY AND SATISFACTION PILGRIMS IN SAUDI ARABIA(University Technology Mara, 2025) dubayl, Hanadi Al bu; Gani, Arni bt AbdulIn Umrah, service quality is paramount due to the unique nature of the Umrah experience. Ensuring smooth and efficient services, such as transportation, accommodation, safety, and food & beverages, is crucial for meeting pilgrims' expectations. Pilgrims' satisfaction in Umrah is closely tied to the seamless execution of services, commitment to religious protocols, and personalized attention from Saudi Arabia and service providers. This study aims to assess the impact of service quality on pilgrims’ satisfaction with the services received. And to examine the role of perceived values as the moderating factor between service quality and satisfaction. This study employed a quantitative approach with convenient sampling to analyze service quality in Umrah in Saudi Arabia. The sample consists of 138 Malaysian pilgrims who have performed Umrah at least once in the last five years. The data was gathered through the distribution of the questionnaire, following which it was run by SPSS 27&30 for further analysis. The study results showed that the regression model accounts for 80.5% of the variation in Perceived Value, and the correlation matrix shows that most of the variables are positively correlated. Finally, perceived value moderates the relationship between service quality and satisfaction in some dimensions of service quality, enhancing its impact on satisfaction. However, in other dimensions, the perceived value did not have a significant effect on the satisfaction of pilgrims.9 0Item Restricted The Contribution Of Public Relations In Reducing Employee Resistance To Organisational Change: The Case Of Saudi Telecommunication Company(Universiti Sains Malaysia, 2025) Shaya, Mohammed; Ahmad, JamilahResistance to the process of organisational change is damaging to an organisation and its employees as it is regarded as a significant reason for failure in executing the process. This study explored employee resistance to organisational change in Saudi Arabia’s Saudi Telecommunications Company (STC) and how public relations (PR), can act as one of the initiatives to implement changes successfully. This research had three objectives: to understand the role of public relations in Saudi Telecommunications Company based on the principles of relationship management theory, to analyse employee resistance issues during organisational change in Saudi Telecommunications Company based on aspects of Lewin’s change management theory, and to recommend a public relations framework to manage employees’ resistance to organisational change in Saudi Telecommunications Company. The study adopted a qualitative research design, and the data were collected using in-depth interviews, which were conducted with 12 public relations Saudi Telecommunications Company employees at the company’s headquarters in Riyadh and five other Saudi Telecommunications Company branches in Jeddah, Mecca, Al-Madinah, Dammam, and Abha. The informants, who comprised public relations directors and practitioners in the public relations departments of each of the six Saudi Telecommunications Company branches actively engaged in change management, were selected using the purposive sampling method. These individuals possess relevant expertise in addressing internal challenges that have the potential to impact the company’s image, such as employee resistance. The obtained data were analysed and organised using the thematic analysis method. Findings revealed that organisational change can leave some employees with negative emotions of fear, a lack of identity, a lack of motivation, and elevated stress levels, which can lead to increased levels of employees’ resistance to change. Thus, public relations can help the management system and employees reduce this resistance by involving employees in the change process, creating a more positive environment, and building better relationships and effective communication. The findings also indicate that the public relations department plays a crucial role in augmenting organisational performance through effective communication, reputation management, stakeholder engagement, crisis response, and strategic decision-making. Ultimately, the study offered several implications and recommendations for future studies on the role of public relations in Saudi Arabia in response to employee resistance.13 0Item Restricted PERSONALIZING TOURIST EXPERIENCE IN SAUDI ARABIA BY LEVERAGING MACHINE LEARNING(University of Malaya, 2025) Abuhasha , Rayan Omar s; Mohamed, Riyaz Ahamed Ariyaluran HabeebSaudi Arabia is rapidly emerging as a global tourist destination, driven by its vision to diversify the economy and prioritize the tourism sector. While the Kingdom offers diverse attractions, existing recommendation systems lack personalization, often providing generic itineraries that fail to cater to individual preferences. Motivated by the need to enhance the tourism experience and attract a broader audience, this study leverages machine learning algorithms to create a personalized recommendation system. The objective of this project is to address challenges in information gathering and itinerary planning by developing a hybrid recommendation model that combines collaborative filtering, knowledge-based filtering, and supervised learning. The system utilizes datasets containing user preferences, attraction profiles, and sentiment data to generate tailored recommendations. Evaluation metrics, including hit rate, precision, recall, and f1-score were used to assess model performance, demonstrating the hybrid model's accuracy and relevance compared to standalone approaches. Results indicate that the proposed system successfully delivered personalized travel plans, which simplify decision-making, and offers a unique travel experience to travelers. This study contributes to the Kingdom’s Vision 2030 by fostering innovation in the tourism sector, making Saudi Arabia a more attractive destination for global visitors. Future work will focus on integrating real-time data, multi-language support, and advanced deep learning techniques to further enhance the system's capabilities.3 0Item Restricted RESOURCE MANAGEMENT ALGORITHMS FOR SOFTWARE DEFINED NETWORKS-BASED EDGE-CLOUD COMPUTING(University Putra Malaysia, 2024) Alomari, Amirah Hassan; Subramaninam, Shamala A/P KThe integration of Software-Defined Networking (SDN), Edge Computing, and Cloud Computing represents a transformative synergy in modern network and computing architectures. SDN enhances network flexibility by separating control and data planes, a concept that becomes particularly valuable when combined with edge computing, which places computational resources closer to data sources. Cloud computing complements these advantages by offering scalable and on-demand resources to a wide range of applications and workloads, and ensuring resource availability across the network. Recent advancements consider the adoption of SDN infrastructure to empower cloud and edge computing for dynamic controllability and manageability. However, the integration of SDN into cloud and edge poses key challenges, including suboptimal resource utilisation in heavily-loaded SDN-Cloud networks, which leads to network congestion, QoS violations, and increased power consumption. Additionally, controller congestion in SDN systems leads to delays, reduces scalability, and prevents the system to handle high traffic loads efficiently, posing a significant challenge for optimising network performance. While conflicts in prioritisation complicate the efficient allocation of resources, which can degrade QoS and network efficiency. To address these challenges, three algorithms are proposed for SDN-Cloud and SDN Edge-Cloud platforms. The Dual-Phase Virtual Machine (VM) allocation algorithm (D-Ph) optimises resources in SDN-Cloud networks, considering processing capacity and memory requirements, to enhance QoS and power efficiencies. The Queue Theory Model-based Adaptive Reinforcement Learning Algorithm (QTM-ARL) optimises load balancing in SDN Edge-Cloud platform while maintaining QoS constraints. Priority-Aware Scheduler (PASQ) based on QoS constraints and incorporated with rate limit mechanism, manages network traffic efficiently while prioritising VoIP traffic over video streaming to enhance network performance. The proposed algorithms are investigated for performance through eventdriven simulation (CloudSimSDN) and MATLAB, employing real workload datasets and delay-sensitive applications. Results demonstrate D-Ph's efficiency in balancing network performance and power consumption in heterogeneous heavily-load large-scale SDN-Cloud networks based on response time, network and CPU performance, QoS violation rate, and power consumption. Furthermore, QTM-ARL's effectiveness in maintaining QoS in hierarchical multi-controller system with fluctuating data flows, and PAS-Q's ability to prioritize low-latency VoIP traffic over video streaming while achieving the desired level of service quality for real-time communication applications and thus fair resource utilisation. Future research can explore advanced AI, emerging technologies, eco-friendly practices, and adaptive SDN architectures to enhance the efficiency, security, and sustainability of SDNbased Edge-Cloud systems.8 0Item Restricted A FRAMEWORK FOR SMART CONTRACT EVALUATION AND SELECTION USING MULTI-CRITERIA ANALYSIS(UNIVERSITI MALAYA, 2024) Alshahrani ,Norah Mohammad R; Mat Kiah, Miss LaihaNumerous smart contract frameworks have been proposed in academic literature and implemented in the industry, for a number pf blockchain platforms such as Ethereum, Corda, and Hyperledger Fabric. Choosing among these frameworks involves a multicriteria decision-making (MCDM) process with various evaluation and selection criteria, including security, financial aspects, and technical considerations. To address this complexity, this research aims to develop a comprehensive framework for standardizing the evaluation criteria and building a selection process for smart contracts. This framework will assist in evaluating critical criteria and selecting the most suitable smart contract framework from the available alternatives. Existing approaches for MCDM-based blockchain evaluation and selection are often not tailored specifically to smart contracts. These approaches are typically general and lack comprehensiveness, often designed for specific case studies. Multi-criteria analysis is employed in this research to determine the optimal option based on the decision-maker’s preferences. Among the available MCDM techniques, the Decision by Opinion Score Method (DOSM) was utilized, which has been applied across diverse fields, including financial institutions and operating businesses. However, this technique does not provide the functionality of explicit criteria for weight measurement. Therefore, a modified version of DOSM that incorporates explicit weight measurement is proposed in this research. The proposed framework consists of five phases. In the first phase, the final set of criteria is identified and examined through expert opinions and the Fuzzy-Delphi method. An improved version of the fuzzy DOSM technique with an explicit weight mechanism is employed in the second stage. The third phase involves identifying and evaluating smart contract alternatives using the criteria identified in phase one. In the iv fourth phase, developed and assessed the opinion score weighting algorithm (NS-WFDOSM), This algorithm modifies FDOSM and incorporates a Neutrosophic Fuzzy Sets (NFSs) environment to measure the weights explicitly and rank the alternatives. In the final phase, a sensitivity analysis module to study the behavior of the new weight technique and its impact on alternative ranking is developed. The inclusion of weight parameters in the proposed framework facilitates the identification of influential criteria in the ranking procedure. The research methodology adopts a quantitative approach to determine critical criteria for smart contracts. Different numerical samples obtained through a closed-ended questionnaire survey are applied in various scenarios to collect data regarding the essential criteria of the subject under investigation. Results indicated the following: (1) The FW-DOSM method efficiently weights the criteria for smart contract blockchain. (2) The NS-FW-DOSM method successfully ranks smart contract blockchain frameworks. (3) Given the binary nature of the selected data, the variation of the criteria, and an increase in the number of alternatives, no significant changes were observed in the final framework among different 𝛼 values. The validation of the framework results was confirmed using sensitivity analysis. The implications of this study can assist administrators in various organizations in selecting the most appropriate and confident smart contract framework and guide future directions for system developers. In conclusion, NS-WF-DOSM is extensively discussed and compared with different MCDM methods from ranking and weighting perspectives. The results demonstrate that NS-WF-WDOSM produces more logical outcomes than other MCDM methods.5 0