Search Results (27)

Employer-funded education and training (EFET) has gained increasing attention as a strategic human resource practice for developing human capital and enhancing organizational performance. However, empirical evidence on its effectiveness remains limited in emerging economies, particularly within the Kingdom of Saudi Arabia (KSA), where workforce localization and human capital development are central to Vision 2030. This study examines the associations between EFET participation and three key employee outcomes: motivation, retention intention, and productivity. Using a quantitative research design, data were collected from 200 employees and managers across multiple sectors in KSA through a structured questionnaire. Structural Equation Modeling (SEM) was employed to test the hypothesized relationships while controlling for gender, age, sector, and years of experience. The results indicate that EFET participation is positively and significantly associated with employee motivation, retention intention, and self-reported productivity, with the strongest association observed for retention intention. Model fit indices demonstrate an excellent overall fit, supporting the proposed model’s robustness. By integrating Human Capital Theory with empirical evidence from the Saudi context, this study contributes to the literature by extending understanding of how employer-funded education functions within a non-Western labor market. The findings offer practical implications for organizations and policymakers seeking to optimize education and training investments in support of sustainable workforce development and Vision 2030 objectives. Full article

The study assesses how effectively succession planning and talent management facilitate the establishment of organizational agility, as well as the moderating influence of organizational learning in the context of Saudi-based banking and finance sectors. Based on the Resource-Based View theory, the study indicates that learning culture and human capital are very important as primary sources of competitiveness in turbulent environments. A stratified sampling was used in the data gathering of 400 respondents and the partial least squares structural equation modeling (PLS-SEM). The result shows that there is a positive and statistically significant relationship between succession planning and organizational agility, and, therefore, a consistent stream of leadership makes an organization more adaptable and resilient. On the other hand, talent development was negatively correlated with agility, which implies that the existing training practices do not match agility needs. Representatives of organizational learning moderated the succession planning–agility, leadership readiness, and adaptability relationship in a positive manner, but moderated the talent development–agility relationship in a negative manner, which implies that the organization has a disconnection between learning and talent strategies. It highlights the necessity to redesign HR practices to make them agile, promote the development of adaptive leadership and a culture of learning, and introduce flexible talent policies. This knowledge adds to the theoretical discussion of the dual nature of organizational learning as a facilitator and constraint as well as providing practical ways to enhance competitiveness in dynamic financial markets. Full article

This study examines the association between Saudi banks’ internal adoption of AI-enabled FinTech-related digital tools and their financial performance, sustainability performance, and financial stability over the period 2015–2024. Using a panel dataset of 10 banks, the analysis investigates how the adoption of AI-driven technologies—such as machine-learning credit assessment, robo-advisory systems, and automated compliance tools—is related to market performance (Tobin’s Q), accounting performance (ROA and ROE), financial stability (Z-Score), and sustainability outcomes measured by both Bloomberg ESG Disclosure Score and the LSEG ESG performance-oriented score. To ensure robust inference and reduce simultaneity concerns, the empirical strategy employs Pooled OLS and Fixed Effects Models with Driscoll–Kraay standard errors, as well as a dynamic Fixed Effects Models incorporating lagged dependent variables, lagged independent variables, and shock-interaction terms. Bank-specific characteristics—including size, age, leverage, liquidity, loan-to-deposit ratio, non-performing loans, net interest margin, market capitalization, and board size—are included as controls. The findings indicate a positive and statistically significant relationship between banks’ internal adoption of AI-enabled digital/FinTech-related technologies and their financial performance, sustainability performance, and financial stability. These relationships remain robust across estimation approaches, providing insights for policymakers, regulators, and bank managers seeking to advance digital transformation while safeguarding financial soundness and supporting sustainable development in the Saudi banking sector. Full article

This study investigates the influence of drone technology on the quality of Saudi financial reports through the integration of Artificial Intelligence (AI) and big data. The study’s mixed-method approach is based on a bibliometric analysis of previous studies, along with documentary and content analysis. The results show that external auditors benefit from using drones when inspections are integrated with AI and big data technology. Moreover, this integration can reduce costs for audit firms and shorten the duration of audit engagements, resulting in more efficient and effective auditing. Seven clusters were identified, with ‘big data’ being the highest-frequency term. This study does not consider potential cybersecurity threats that could impact data integrity and decrease financial transparency. Furthermore, environmental issues in Saudi Arabia, such as sandstorms, could compromise the effectiveness of drone-based auditing. However, this study contributes to the ESG literature by demonstrating how integrated audit technology transforms traditional sustainability reporting into continuous, AI-enhanced verification processes. These processes improve financial report quality while supporting Saudi Arabia’s Green Initiative and its goal of achieving net-zero carbon emissions by 2060. The adoption of AI and big data technologies in auditing represents a shift toward more automated and intelligent audit practices. These changes provide practical insights for government authorities, such as the Saudi Capital Market Authority (CMA), and may result in higher-quality financial reports and increased investor confidence. Full article

This study investigates the impact of environmental, social, and governance (ESG) disclosure on value creation in a balanced panel of 100 non-financial Sharia-compliant firms listed on the Saudi Stock Exchange over the period 2014–2023. The analysis employs a combination of econometric techniques, including fixed effects models with Driscoll–Kraay standard errors, Pooled Ordinary Least Squares (POLS) with Driscoll–Kraay standard errors and industry and year dummies, and two-step system generalized method of moments (GMM) estimation to address potential endogeneity and omitted variable bias. Value creation is measured using Tobin’s Q (TBQ), Return on Assets (ROA), and Return on Equity (ROE). The models also control for firm-specific variables such as firm size, leverage, asset tangibility, firm age, growth opportunities, and market capitalization. The findings reveal that ESG disclosure has a positive and statistically significant effect on firm value across all three performance measures. Furthermore, firm size significantly moderates this relationship, with larger Sharia-compliant firms experiencing greater value gains from ESG practices. These results align with agency, stakeholder, and signaling theories, emphasizing the role of ESG in enhancing transparency, reducing information asymmetry, and strengthening stakeholder trust. The study provides empirical evidence relevant to policymakers, investors, and firms striving to achieve Saudi Arabia’s Vision 2030 sustainability goals. Full article

This study explores how corporate social responsibility (CSR) disclosure contributes to sustainable value creation by enhancing intellectual capital (IC) and investigates the moderating role of institutional ownership (IIOW) in this relationship. Using a panel dataset of 828 firm-year observations from non-financial Saudi companies listed on the Saudi Stock Exchange (Tadawul) between 2016 and 2021, the analysis applies feasible generalized least squares (FGLS) regression to test the proposed relationships. The findings reveal a significant positive association between CSR disclosure and IC, underscoring the strategic importance of CSR in building intangible corporate assets. Moreover, IIOW strengthens this association, suggesting that IIOW plays a critical role in promoting sustainability-oriented practices. Robustness checks using alternative proxies and estimation techniques confirm the validity of the results. This study provides novel empirical evidence from Saudi Arabia, contributing to the CSR and IC literature in emerging markets and offering practical insights for policymakers, investors, and corporate leaders aiming to foster long-term organizational resilience. Full article

The aim of this study was to explore how artificial intelligence (AI) impacts the quality of financial reporting, providing insights into new opportunities in this field for the Saudi context. This study employed the UTAUT theory to examine the adoption of AI technology in auditing practices. This study also utilized bibliometric analysis techniques through an academic literature review and content analyses of the documentary evidence. The implication of this study is that non-Big 4 audit firms should adopt AI-powered drones, which consequently enhance decision making, decrease audit fees, and enhance the quality of financial reports, and the efficiency and accuracy of audits. Furthermore, this paper recommends that non-Big 4 audit firms adopting AI should foster a culture of change to ensure quality audits and consistency, overcome resistance to the change, and support the integration of technologies such as AI-driven audit automation. Our study also indicated the importance of integrating AI with the IFRS, developing a new framework for AI in auditing practices, incorporating AI into auditing courses, and modernizing auditing using AI. These implications lead to financial reports of enhanced quality. The results indicated four clusters, with artificial intelligence being the most significant keyword occurrence. This study has limitations, such as the lack of consideration of cyber-attack risks on drones, which may reduce the reliability of financial reports. Based on the findings of this research, audit companies and regulatory agencies in Saudi Arabia, like the Saudi Capital Market Authority (CMA), may evaluate the integration of AI to improve the quality of financial reporting. Implementing AI is expected to enhance the quality of audits, automate reporting, and support regulatory compliance to foster confidence and transparency in the financial industry. Full article

A capital market with greater transparency provides more accurate metrics for measuring corporate performance, which can be utilized to inform market participants’ decisions. Informed risk is crucial to corporate reporting transparency. This empirical study explores the extent to which firms in the Saudi capital market disclose risk information, whether financial or non-financial. A risk disclosure index (RDI) is constructed based on a rigorous literature review of previous studies, considering suggested items related to corporate risk that must be disclosed. The sample comprises 50 corporations, with five companies representing the energy sector, three representing the utility sector, and forty-two representing the materials sector. The findings reveal moderate financial risk disclosure (sample mean 56%) and low non-financial risk disclosure (sample mean 33%) in the Saudi capital market. In the energy sector, the disclosed financial and non-financial risks comprise 57% and 37%, respectively; in the utility sector, these proportions are 56% and 31%, while in the materials sector, they are 54% and 33%, respectively. Regulators should prioritize high-quality, transparent, and comparable risk information disclosure to attract direct foreign investment. To improve their risk disclosure, managers of firms can also employ the RDI to examine the extent of risk their companies face. This study is limited to the annual and board reports of companies in the three sectors. Full article

Concentrated solar power (CSP) has gained traction for generating electricity at high capacity and meeting base-load energy demands in the energy mix market in a cost-effective manner. The linear Fresnel reflector (LFR) is valued for its cost-effectiveness, reduced capital and operational expenses, and limited land impact compared to alternatives such as the parabolic trough collector (PTC). To this end, the aim of this study is to optimize the operational parameters, such as the solar multiple (SM), thermal energy storage (TES), and fossil fuel (FF) backup system, in LFR power plants using molten salt as a heat transfer fluid (HTF). A 50 MW LFR power plant in Duba, Saudi Arabia, serves as a case study, with a Direct Normal Irradiance (DNI) above 2500 kWh/m². About 600 SM-TES configurations are analyzed with the aim of minimizing the levelized cost of electricity (LCOE). The analysis shows that a solar-only plant can achieve a low LCOE of 11.92 ¢/kWh with a capacity factor (CF) up to 36%, generating around 131 GWh/y. By utilizing a TES system, the SM of 3.5 and a 15 h duration TES provides the optimum integration by increasing the annual energy generation (AEG) to 337 GWh, lowering the LCOE to 9.24 ¢/kWh, and boosting the CF to 86%. The techno-economic optimization reveals the superiority of the LFR with substantial TES over solar-only systems, exhibiting a 300% increase in annual energy output and a 20% reduction in LCOE. Additionally, employing the FF backup system at 64% of the turbine’s rated capacity boosts AEG by 17%, accompanied by a 5% LCOE reduction. However, this enhancement comes with a trade-off, involving burning a substantial amount of natural gas (503,429 MMBtu), leading to greenhouse gas emissions totaling 14,185 tonnes CO₂ eq. This comprehensive analysis is a first-of-a-kind study and provides insights into the optimal designs of LFR power plants and addresses thermal, economic, and environmental considerations of utilizing molten salt with a large TES system as well as employing natural gas backup. The outcomes of the research address a wide audience including academics, operators, and policy makers. Full article

The primary purpose of this study was to investigate and present a theoretical model that identifies the most influential factors affecting the adoption of artificial intelligence (AI) by SMEs to achieve sustainable business performance in Saudi Arabia by integrating the Technology–Organization–Environment (TOE) framework. The authors utilized a quantitative method, using a survey instrument for this research. Data for this research were collected from managers working in six different sectors. Subsequently, based on company size, firms were divided into two groups, allowing multi-group analysis of small and medium-sized businesses to explore group differences. Hence, firm size played a moderating role in the conceptualized model. Data analysis was performed on SmartPLS 3, and the results suggest that dimensions of the TOE framework, such as relative advantage, compatibility, sustainable human capital, market and customer demand, and government support, play a significant role in the adoption of AI. Moreover, this study found a significant influence of AI on SMEs’ operational and economic performance. The multi-group analysis (MGA) results reveal significant group differences, with a medium-sized firm strengthening the relationship between relative advantage and AI adoption compared to small-size firms. The findings lead to practical implications for companies on how to increase the adoption of AI to help SMEs embrace their technological challenges in KSA and obtain sustainable business performance to contribute to the economy. Full article

Over the last two decades, the regulators of the financial services sector in Saudi Arabia have aimed to develop a level of fair competition in the provision of banking services across the country. This paper utilizes non-structural approaches, the H-statistic developed by, and the Granger causality test. The second approach involves determining the Granger-based causal relationship between banks’ cost efficiency and competition via data envelope analysis (DEA) using the generalized method of moments (GMM) panel. The study’s data were drawn from 11 traditional banks in Saudi Arabia, covering the period from 2015 to 2021 (yearly data). The results of the non-structural approach, i.e., the H-statistic, demonstrate that the average fund rate had a positive effect on competition; however, the physical capital price index, the index of leverage, and the credit risk negatively affect the total revenue. Furthermore, a positive H-statistic value reflects the positive causality between competition and cost efficiency (higher efficiency results in a higher level of competition). The DEA results indicate that competition in the year 2021 was influenced by the competition level of the previous year (2020); moreover, the relationship between the previous year’s cost efficiency Granger value, the greater availability, and the lower prices of banking products had a significant influence on the competition in the years under consideration (since a positive significant result from the test is available), which reflects the higher level of market structure and the greater availability and lower prices of banking products. Cost efficiency in the year 2021 was also positively influenced by the cost efficiency level of the previous year (2020), with competition forcing efficiency via the cutting of costs. Full article

The Board of directors serves as the primary mechanism for corporate governance, prompting numerous researchers to investigate the influence of its characteristics on the extent of sustainability reporting across various regions worldwide. Hence, this study aimed to examine the impact of human and social board capital, namely, a board of directors’ multiple directorships and level of financial expertise, on the level of sustainability disclosure (SRL) reported by non-financial Saudi companies during the period from 2018 to 2022. To achieve these objectives, 654 firm-year observations belonging to 140 non-financial companies in Saudi Arabia were used. An SRL index was constructed using the following four aspects of sustainability: governance, economic, social, and environmental aspects. At the same time, the most common measurements for independent variables, as found in the literature, were utilized. An OLS regression analysis was performed as the main test of our two hypotheses, and the concluded results demonstrated that both the board of directors’ multiple directorships and its level of financial expertise have significant positive impacts on the SRL. These findings are the first of their kind in the context of Saudi Arabia and can help market regulators, policymakers, and decision-makers in their attempt to achieve the goals of the country’s sustainability initiatives and Vision 2030. Full article

Recently, social media marketing has become an effective tool for restaurants to gain visibility, increase customer engagement, and boost sales. Through social media marketing activities (SMMAs) including customization (CUST), entertainment (ENTR), trendiness (TRND), and interaction (INTR), restaurants can connect with their customers in a dynamic way that may affect their satisfaction and purchasing behavioral intention. Hence, this study primarily aims to empirically explore the individual influence of SMMAs namely CUST, ENTR, TRND, and INTR on social media followers’ satisfaction and purchase intention in a sample of casual-dining restaurants in Saudi Arabia. Furthermore, drawing on the Stimulus-Organism-Response (S-O-R) model, we also seek to investigate the influence of customer satisfaction as a mediating variable in the relationship between CUST-PI, ENTR-PI, TRND-PI, and INTR-PI. Furthermore, to examine the direct influence of CS on PI. In order to meet these objectives, an online survey was created to collect data from a convenience sample of restaurant social media followers. Data from 415 followers were analyzed using the PLS-SEM with a bootstrapping technique to confirm the research hypotheses. The findings of the study illustrated the significant positive effect of CUST, ENTR, and INTR on followers’ purchase intention, respectively. Trendy social media marketing activities did not significantly affect purchase intention. Additionally, CS partially mediated the relationships between CUST, ENTR, INTR, and PI but fully mediated the trendiness-purchase intention relationship. The results from this research can assist restaurant operators to leverage the benefits of social media more effectively by understanding how SMMAs influence customers’ purchase intentions and enhancing their understanding of how customer satisfaction can be used to capitalize on the benefits of social media. Full article

The aim of this study was to investigate and compare investment opportunities in the financial markets of Saudi Arabia, a net oil-exporting country, and Turkey, a net oil-importing country, in the Middle East. The international capital asset pricing model (ICAPM) was extended by considering local factors proxied by country risk (CR) and oil price risk exposures of the excess returns of Saudi Arabia and Turkey. In this study, we employed the extended ICAPM in a two-state Markov-switching setting for the sample period of January 2005 to December 2018 to explore whether the risk premium is time-varying. The results suggested that systematic risk is time-varying depending on the state of the financial markets and is affected by both global and local factors. Saudi Arabia offered higher excess returns during the high-volatility regime compared to that of the World Index and enjoyed higher returns during the low-risk regime from oil price shocks. Turkey was negatively affected by oil price shocks and was rather sensitive to the country’s risk factor, which varied with both the state of the market and the time factor. These findings will be useful to international investors in diversifying their risks. This study differs from others in estimating the risk premium (beta) by taking into account both the local and global factors and the dynamic nature of systematic risk. Full article

The introduction of social media in the restaurant sector has changed the manner in which customers communicate with businesses. Social media marketing activities (SMMAs), such as customization, entertainment, trendiness, and interaction may have a substantial impact on followers’ perceived value and consumer behavioral intentions. Therefore, this research aims to investigate the impact of SMMAs on restaurant social media followers’ purchase intentions (PUR), willingness to pay a premium price (WPP), and e-WoM. Additionally, drawing on the Stimulus-Organism-Response (S-O-R) model, we seek to explore the mediation impact of perceived value (PV) in these relationships. To achieve this, an online questionnaire was developed for data collection from a convenience sample of casual-dining restaurant followers in Saudi Arabia. A sample of 433 social media followers was studied using PLS-SEM for testing the study hypotheses. The findings highlighted the significant positive impact of SMMAs on followers’ PV, PUR, e-WoM, and WPP. Further, PV partially significantly mediated the relationship between SMMAs and their consequences. Consequently, providing relevant, up-to-date, and entertaining content; responsiveness to customer needs and feedback; and positive brand engagement significantly contributed to enhancing restaurant followers’ perceived value, which sequentially improves their purchase intention, boosts positive e-WoM, and promotes the possibility of WPP for restaurant products and services. This research provides restaurant operators and marketers with valuable insights into how SMMAs influence followers’ behavioral intentions and enhances their understanding of how perceived value can be utilized to capitalize on the benefits of social media. Full article