The study examines the effect of the supply chain finance (SCF) on the corporate financial performance measured in terms of Return on Assets (ROA), Tobin's Q, and Gross Operating Profit (GOP) in the material sector of Saudi Arabia. The study selects a sample of 42 companies from the material sector listed on Tadawul starting in 2008 and ending 2019. A panel regression in terms of pooled OLS, fixed and random effects, and panel GMM is estimated to report the empirical results. The results report a negative and significant effect between the financial performance variables and supply chain finance, specifically with ROA with pooled OLS and fixed and random effects models. The results of panel GMM also show a negative and significant effect between all the financial performance variables and financing supply chain. The results are useful to academicians and the managers in the materials, inventory, and sales sections, and supply chain managers to integrate finance and SCM to achieve corporate benefits.

This study aims at studying the effectiveness of supply and storage management in light of the determinants of demand for health services in Saudi hospitals in an analytical framework. The survey studies the impact of logistical management of medical materials and its vital role in securing the necessary medical resources and supplies for the health institution. The study adopts the descriptive and analytical approach in order to achieve its goals and test its hypotheses, as the study was applied in the hospitals of Al-Kharj Governorate. The study finds that there was a relationship between the methods of supply and storage applied in Saudi hospitals and the determinants of demand for the health services provided. The study recommends working on developing methods of requesting suppliers, developing methods of storing medicines and medical supplies, and distributing them inside the hospital in accordance with economic standards and making use of computer technologies.

The aim of this study is to determine the influencing factors of Supply Chain Management and digitalization of human resource information practices in the small and medium enterprises of Oman. Digitalization of human resource information is the adoption of electronic means to the human resource activities of Supply Chain Management. In this system, the whole human resource activities are implemented through electronic means with the support of information technology (IT) infrastructure. To measure the Digitalizationof Human Resource Information Practices and the performance level of Supply Chain Management, two adopted constructs from two different studies were used. The study samples were taken from the SMEs of Oman. Almost 180 employees of different provinces responded to the questionnaires translated into vernacular language through google forms and a few hardcopy surveys were distributed to different locations with the support of SMEs and few entrepreneurs. The study found a significant positive relationship between the Performance of SCM and the Digitalization of Human Resource Information of a prominent variable electronic communication and other variables were found with no significant relationship. The finding of the study acts as a significant contributor to the existing literature on SCM as well as human resource management.

To ensure competition and survival of business, understanding the indicators or drivers of export performance is important. Based on the organizational learning theory and strategic fit theory, this study aims to test the influence of market exploration strategies (MERS) and market exploitation strategies (METS) on SMEs’ export strategic performance, export financial performance (EFP), and export customer performance (ECP). This study confirms the leading mediating role of product planning and development (PPD) in the effects of MERS and METS on export performance outcomes. The authors collected questionnaire data electronically from 122 experienced SMEs that conduct international transactions in Saudi Arabia. Results from the Analysis of Moment Structures indicate that MERS and METS positively influence export performance; PPD mediates the relationship between MERS and METS in export performance dimensions; and number of sales and ownerships are control variables that influence EFP and ECP, respectively. This study contributes to the literature and society by proposing a framework that addresses the direct and indirect relationships between export marketing strategies and PPD, and their effects on SMEs’ export performance.

This paper attempts to find out various facets of work-life balance (WLB) contribution and relationships with the employees’ working in dairy company in the Kingdom of Saudi Arabia. The study considers 131 employees selected randomly from the Nadec dairy company. Work-life balance Scale developed and standardized by Pareek et al. (2011) [Pareek, U., Purohit, S., & Joshi, A. (2011). Training instruments in HRD and OD. New Del-hi: Tata McGraw- Hills Publishing Company Limited. 287-289.] was used to gather the information from the respondents. Both de-scriptive and inferential statistics are been used to analyze the data. The most prominent findings of the result are: (i) all the facets of work-life balance have positive relationships with each other ex-cept teamwork; (ii) married are scored high in terms of mean on time management and teamwork which statistically indicates an existence of significant difference in contrast to their counterparts and (iii) social needs a component of work-life balance appears as one of the most powerful pre-dictors of personal needs within the employees’ working in the dairy company. The current investigation is an eye-opener for HR professional in the Kingdom to design and implement the certain mechanism to improve the work-life balance of the employees to achieve the Saudi Vision 2030.

The field of online pharmacies is expanding rapidly and has become a crucial component in delivering pharmaceutical services across Saudi Arabia. This study aims to explore the factors influencing the adoption of online pharmacies by the Saudi population, utilizing an enhanced version of the Unified Theory of Acceptance and Use of Technology (UTAUT) framework. This study employed a cross-sectional design, utilizing an online questionnaire that was pre-validated and shared via social media channels between August 2024 and October 2024. The study focused on Arabic-speaking individuals aged >18 years. The gathered data were examined through structural equation modeling (SEM) using AMOS software (v.22.0). The study found that the UTAUT model demonstrates strong applicability in explaining the adoption of online pharmacies, accounting for 62.4% (R² = 0.624) of the variance in behavioral intention. Among the key factors, effort expectancy (p < 0.001) emerges as the most influential predictor of behavioral intention, followed by facilitating conditions (p 0.05) do not have a statistically significant impact on behavioral intention. The study results would help formulate more effective strategies for establishing online pharmacy operations in developing nations like Saudi Arabia. This study contributes to enhancing the traditional UTAUT model through the integration of additional factors such as health literacy, personal innovativeness, perceived risk, and perceived trust. These variables introduce new dimensions to the existing literature on online pharmacies.

The six GCC states share similar economic, geographic and socio-cultural characteristics and also face with similar challenges in terms of energy perspective. This study plans to focus on the eco-nomic and energy efficiency of the six GCC states. In the process, the study ranks the GCC states in terms of their efficiency scores. These efficiencies are computed through Data Envelopment Analysis. The economic efficiency is calculated for all six GCC states. Capital and labor are the inputs and GDP is the output. In this survey, Saudi Arabia maintains the highest efficiency score of 0.94, closely followed by Qatar (0.92), Kuwait (0.89), Bahrain (0.83), Oman (0.81) and UAE (0.67). There is a huge gap between the economic efficiency scores of Saudi Arabia and UAE. The environmental efficiency scores are calculated using CO2 emissions as output and electric power consumption and energy as input. Again, the highest efficiency score is for Saudi Arabia (0.91) followed by Oman (0.87), Kuwait and Bahrain have a tie for the 3rd position with a score of 0.74. Finally, the laggards are UAE (0.65) and Qatar (0.62). Again, there is a huge gap between the best and the worst performers. The case of two countries is worth mentioning. Qatar is ranked second in terms of economic efficiency while it was ranked sixth in terms of economic efficiency. Oman was ranked fifth in terms of economic efficiency while it was ranked second in terms of environmental efficiency. Finally, an average of economic and environmental efficiency are taken to compute the composite index. Saudi Arabia has the first place followed by Oman, Kuwait, Bahrain, Qatar and UAE.

This work focusses on the crack growth behaviour of the compact tension specimen under mixed-mode loading, and numerical investigation using ANSYS Mechanical APDL 19.2 extended finite element software with different loading angles. The fatigue life is predicted under constant amplitude fatigue loading using the Paris’ law. The predicted values of the fatigue life in the present study provide consistency with the experimental and numerical results. In addition, the study showed that the direction of crack growth follows the same literature trend of experimental results. According to the results of the crack growth path, there is no effect of changing the geometries thicknesses on the crack growth trajectory. Its only effect is the resistance to higher plastic deformation which decreases as the thickness increases.

In the rapidly evolving landscape of higher education, Social media marketing (SMM) has evolved a critical factor in shaping brand perception (B.P.) and the decision-making process of prospective students in India. This paper intends to explore the intricate dynamics among Social media (S.M.), influencer marketing, and the selection of higher academic institutes (HEIs), focusing on understanding how these factors shape students' perceptions. We conducted this research on 560 students, who represented the research's population. SEM-PLS was applied to analyze the data and acquire procedures. Surveys on the Internet were used. Employing exogenous/endogenous elements to create sequences, the SEM approach examines causal associations among elements. It provides solutions to research into causation in dimensional and structural frameworks. According to the research's findings, selecting HEI is positively impacted by SMM initiatives. The aspects of SMM activities (electronic word-of-mouth (eWOM), personalization, interaction, and trendiness) affect the HEI selection. In addition, personalization and two have an impact on perceptions of the brand. Understanding and utilizing the efficacy of S.M. and influencer marketing will be crucial for HEIs looking to draw in and hold on to potential students as the higher education environment keeps evolving in the age of digitization.

The rule based categorization approaches such as associative classification have the capability to produce classifiers rival to those learned by traditional categorization approaches such as Naïve Bayes and K-nearest Neighbor. However, the lack of useful discovery and usage of categorization rules are the major challenges of rule based approaches and their performance is declined with large set of rules. Genetic Algorithm (GA) is effective to reduce the high dimensionality and improve categorization performance. However, the usage of GA in most researches is limited in the categorization preprocessing stage and its results is used to simplify the categorization process performed by other categorization algorithms. This paper proposed a hybrid GA rule based categorization method, named genetic algorithm rule based categorization (GARC), to enhance the accuracy of categorization rules and to produce accurate classifier for text mining. The GARC consists of three main stages; namely, search space determination, rule discovery with validation (rule generation), and categorization. The experimental results are carried out on three Arabic text datasets with multiple categories to evaluate the efficiency of GARC. The results show that a promising performance was achieved by using GARC for Arabic text categorization. The GARC achieves the best performance with small feature space in most situations.