Saudi Cultural Missions Theses & Dissertations
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Item Restricted Unveiling Factors for Sharing of Travel Experiences on YouTube by Inbound Tourists to the Kingdom of Saudi Arabia: A Social Influence Theory Perspective(TAYLOR’S UNIVERSITY, 2024) Alzahrani, Meshari; Lim, JoannThis research aims to investigate how the uploading of travel experiences on YouTube by inbound tourists to the Kingdom of Saudi Arabia is influenced by key determinants and how YouTube plays a role in their decision-making process, as explained by Social Influence Theory. The study employed an explanatory quantitative research method, surveying 402 inbound tourists who use YouTube during their travels. Multiple regression analysis was used to examine the interactions between factors such as Identification with vloggers, Internalization, Social norms, and Perceived Enjoyment in influencing travel decisions. The findings indicate that identification with YouTube vloggers, internalization of travel content, and compliance with social norms have a substantial influence on tourists' destination decision-making in Saudi Arabia, with Perceived Enjoyment playing a moderating role. Both practically and theoretically, this research provides valuable insights for tourism marketers on how to leverage emotional appeal on YouTube to engage potential travellers. Additionally, this study offers a conceptualization of Social Influence Theory within the tourism context, contributing a new perspective on how technology impacts travel behaviour. While few studies have applied Social Influence Theory to the use of YouTube in tourism marketing in Saudi Arabia, this research aligns with Saudi Arabia's Vision 2030, which aims to strengthen the country's international tourism brand.28 0Item Restricted OUT OF SAMPLE PREDICTION OF MULTI-CRITERIA GEOMETRIC DISPERSION THEORY WITH COMPARATIVE STUDY OF WIND ENERGY AND TRANSPORTATION(Case Westren Reserve University, 2024-06-02) Altowijri, Abdulaziz; Malakooti, BehnamThis thesis presents a pivotal study focused primarily on the application of Multi-Criteria Decision Making (MCDM) methodologies to identify the most suitable locations for wind farm development across thirteen regions in Saudi Arabia, an endeavor underscored by the country's significant potential for renewable energy. This research takes into account critical factors such as average wind power density, wind speed, and terrain suitability to guide the decision-making process. In parallel, the thesis also revisits an ancillary study based on a 1987 mode choice survey involving 210 travelers making trips between Sydney, Canberra, and Melbourne, offering a comparative perspective on the utility of MCDM methods across distinct domains. Employing an extensive array of MCDM techniques—including Linear Additive Utility functions, Geometric Dispersion Theory models, Keeney Multiplicative Utility (both with and without value functions), and a Z-Goal-programming method tailored for wind farm location selection and Transportation Mode selection—this analysis is thorough in its critical evaluation of these methodologies' efficacy in forecasting optimal choices. The precision of these models is quantitatively assessed using the Sum of Squares Error (SSE) metric, complemented by a thorough validation framework that includes both a 70% in-sample and a 30% out-of-sample comparison, alongside comparative assessments across models. The culmination of this research underscores the unparalleled predictive prowess of Geometric Dispersion Theory (GDT) models, which demonstrated the lowest SSE, thereby affirming its superior capability in accurately determining optimal wind farm locations in Saudi Arabia. By extension, the GDT models' effectiveness was also mirrored in the mode choice study, further attesting to their robust applicability across different decision-making contexts. This thesis enriches the academic discourse on MCDM applications within the realms of renewable energy site selection and transportation.32 0Item Restricted The Influence of Social Media in Travel Decision-Making: A Case Study of Saudi Arabia(University of Exeter, 2024-01-30) Alosaimi, Areej; Shaw, GarethThis study aims to investigate the influence of social media on Saudi tourist behaviour, focusing on the impact of social media influencers (SMIs) on decision-making including post-COVID-19 pandemic period. A mixed methods approach was used to examine Saudi travel behaviours in-depth. The study implemented online questionnaires to 302 Saudi social media users, employing Factor and Cluster analysis to identify prevalent patterns. It subsequently delivered online, qualitative semi-structured interviews with 12 individuals who had completed the questionnaire and employed a thematic analysis. The questionnaires found that social media is an essential source of information when planning holidays, both before and during travel. Suggesting that holiday planning is no longer limited to the pre-travel phase but continues throughout the holiday. A key reason to use social media during a holiday was to facilitate micro-decisions, which occur continually. This shift indicates that social media has made holiday planning a dynamic, ongoing process, enabling tourists to search and decide on their next experiences at any given destination. Additionally, it reveals differences in demographics in social media usage and the impact of SMIs on holiday planning. Generation Z (Gen Z) and millennials show a greater reliance on social media and are more trusting of influencer recommendations. However, information adoption from SMIs depends significantly on the similarity with the influencers, their perceived expertise, trustworthiness and provide quality information. Also, the content offered by SMIs post-covid-19 has helped to plan holiday and reduce perceived travel risks. Semi-structured interviews suggest that SMIs are seen as experienced and knowledgeable, helping followers in travel decision-making. The credibility of SMIs is linked to their perceived similarity with followers, but can be compromised by inauthentic, excessive, misleading, or sponsored content. Post-COVID-19, the content from SMIs has become valuable in influencing travel decisions, offering timely updates and clear guidance on safety and restrictions. This highlights the potential for travel organizations to leverage SMIs' persuasive skills and sponsored content for effective marketing campaigns. This study benefits marketers and Saudi policymakers in developing social media marketing strategies to promote the country as a holiday destination. Which is aligns with the Vision 2030's objectives positioning Saudi Arabia as a vibrant tourist hub.69 0Item Restricted Developing A Sustainable Water Resources Management Assessment Framework (SWRM-AF) for Arid and Semi-Arid Regions(University of Birmingham, 2024-06-03) Alsaeed, Badir Saad S; Hunt, DexterThe rapidly growing world population highlights the need for evaluation methods like indicator-based water sustainability frameworks (IBWSFs) to assess and improve water resources management (WRM) practices. This is particularly important in arid and semi-arid regions (ASAR) where water resources are scarce. Furthermore, a particular IBWSF that fully fits the context of ASAR could not be found in the literature. Therefore, a sustainable water resource management assessment framework (SWRM-AF) has been developed, specifically tailored to evaluate water use in the domestic sector of countries with similar water conditions to those of the Gulf Cooperation Council (GCC) countries. The first step in the process of developing the SWRM-AF is to create a conceptual SWRM-AF, which consists of four components (i.e., three pillars of sustainability: environment, economy, and society plus infrastructure) underpinned with 24 selected indicators. These indicators were chosen rigorously through an extensive literature review. Each indicator is provided with a brief description and justification. One contribution of this research is that, for the first time, every indicator is presented with clear and straightforward instructions represented by coloured-code tables to explain how to evaluate each. In addition, social indicators such as the ‘intervention acceptability’ and environmental indicators to tackle the impact of the desalination treatment plants have been included to form a more holistic framework applicable to GCC countries. The second step is to utilise the Delphi technique as a participatory method to refine and validate the conceptual framework. This technique employs an iterative questionnaire to achieve consensus, through which 60 expert stakeholders from the GCC countries were invited to assess each indicator across four components and assign their respective weights. This process, through two rounds, resulted in a final version of SWRM-AF consisting of 4 equal-weight components and 17 indicators. Also, it was found that indicators within the social, economic, and infrastructure components should carry equal weights, while indicators within the environmental component should be assigned different weights. Lastly, data about the water sector of the Kingdom of Saudi Arabia (KSA), which was selected as an example of GCC countries, were collected to give a comprehensive idea about the overall water situation. Then, an application of the final SWRM-AF to the WRM of the domestic sector of the KSA, focusing on its current practices and assumptions of possible future scenarios, is presented.9 0Item Restricted On Evaluating Cyber Defense by Humans and Reinforcement Learning Agents(Saudi Digital Library, 2023-12-09) Aljohani, Asmaa; Jones, JamesA significant factor that drives the investment in/integration of a cyber defense technique is its proven effectiveness, in terms of performance, usability, and security, against an intended adversary. Measuring the effectiveness of security defenses is complex, mainly because evaluation is a never-ending process, a natural outcome of evolving technologies and adversarial capabilities. To facilitate cyber defense evaluation, it is, thus, imperative to examine novel methods through which researchers could gain a deeper understanding of adversarial behavior from both technical and cognitive perspectives. To this purpose, the first part of this dissertation investigated the applicability of using two popular paid crowdsourcing platforms to run hacking experiments (i.e., Capture-the-Flag challenges). Paid crowdsourcing platforms can potentially facilitate studies in the Oppositional Human Factors (OHF), a field that considers attackers’ cognitive biases when examining the effectiveness of defensive techniques. Such platforms are unique in that they offer schemes eliciting real-world adversarial behaviors (e.g., maliciousness) while minimizing the constraints imposed by typical recruitment methods. Findings showed that the platforms vary significantly in data quality and workers’ technical skills. As a result, I examined the possibility of using Prolific to conduct a randomized study to analyze attackers’ cognitive biases and limitations when they encounter deception under an incentive-compatible scheme (i.e., monetary) and a design different from prior studies. Findings showed consistent behavioral patterns between the populations under consideration but revealed some shortcomings of online cybersecurity experimentation. As online experimentation with qualified human participants remains challenging, the third part of this research examined another alternative in which datasets from experimental psychology studies designed to analyze deficits in decision-making processes (e.g., gambling tasks) are used to guide the design of human-like cyber agents. More specifically, I investigated the role memory systems and settings play in predicting the behavior of healthy and unhealthy populations. The motivation behind this work came from the realization that healthy individuals and individuals with pathological tendencies—the latter are more inclined to commit cyber crimes [5]—exhibit different risk attitudes that could be partially attributed to how memories are processed and used to guide future decisions. The results demonstrated differences in the role memory systems and settings play in predicting actions taken by the populations under consideration. Having examined the role of memory in predicting real-world behavior, I augmented reinforcement learning agents with similar settings, analyzed the agents’ behavior in simulated network environments, and observed interactions between the type of memory systems used to guide the agents’ learning process, the type of experiences used in the learning process, the underlying learning strategy, and the observation spaces. The results highlighted the importance of analyzing the aforementioned factors when designing predictive models for adversarial decision-making.70 0Item Restricted Experiences of Relatives in ICU Caregiver Role: Narrative Exploration of Psychosocial Factors Underpinning Their Decision-Making.(Saudi Digital Library, 2023-11-19) Alsubiei, Sarah; Mgawadere, FlorenceBackground: Caring for a patient admitted to the intensive care unit (ICU) may cause significant stress, anxiety, and depression that undermine family members’ ability to participate in healthcare provision. Unfortunately, caregivers’ and family members’ experiences have not been studied well in the scholarly literature, so it is not clear what factors affect their effective involvement in decision-making and how they overcome stress. Therefore, this study aimed to understand psychosocial factors that underpin the decision-making experiences of family caregivers of critically ill patients in intensive care units. Methods: A structured narrative review was conducted using three databases; PubMed, Elsevier, and Willey Online. Key search terms used were: "((family decision) OR (decision-making)) AND (psychosocial factors) AND ((ICU) OR (intensive care units))", "(experiences of relatives) AND ((ICU) OR (intensive care units)) AND ((caregiver role) OR (significant others))", and "(decision-making role OR family decision) AND ((family members) OR (caregivers)) AND ((ICU) OR (intensive care units))". Duplicates were removed manually and all studies that did not meet the review criteria were removed. Results: Forty (40) studies conducted in different settings were included in this review. Caregivers often experienced communication problems and struggled with psychological effects resulting from stress, financial difficulties, and emotional burden of care. Anxiety, post-traumatic stress disorder (PTSD), frustration, helplessness, and burnout, affected caregivers’ decision making. Notably, social support networks, family support, and positive family functioning were found to improve caregivers’ well-being and help them remain resilient and engaged in care. Conclusion: Most studies reported psychological problems that affected caregivers’ participation in decision making on the care of their critically ill relatives. However, social support was not always enough to facilitate caregivers’ decision-making, so it is important to adopt innovative solutions such as a family systems theory, family-centred care, decision aids, and improved communication, among others, to make sure that caregivers are well-informed, supported, and empowered to make the best decisions for their loved ones. Given the lack of overall knowledge on psychological factors underpinning caregivers’ decision-making in ICUs, more research on this topic is strongly recommended.45 0