This research study addresses the advantages and difficulties of Cloud Computing (CC) in Supply Chain Management (SCM). An overview of the current state of SCM and the difficulties businesses in this sector confront is presented at the beginning of the article. It then explores how cloud-based solutions can address these challenges, such as through the use of real-time data analytics, collaborative platforms, and intelligent automation. Additionally, the paper investigates the potential risks and challenges associated with cloud-based SCM, including data security and privacy concerns, vendor lock-in, and the need for robust disaster recovery plans. To provide a comprehensive understanding of the topic, the paper includes a case study that illustrates how a company successfully implemented cloud-based SCM solutions to improve their operations. The paper concludes by highlighting the key takeaways and insights from the research, and by identifying potential future directions for research in this field. Overall, this study delivers insightful information about the function of CC in SCM and offers useful suggestions for companies looking to use this technology to enhance their supply chain operations.

The study explored trust in the accounting information system and tested its compatibility with the credit granting decision level. The study also hypothesized that whenever the confidence in the current accounting information system is high, the level of the decision to grant credit is high, and vice versa. To test this assumption, the study used partial least squares structural equation modelling (PLS-SEM). This method is usually preferred when the goal of the research is to develop theory and explain variance or predict structures. The survey design approach was adopted in the commercial banks in Jordan, where 225 valid questionnaires were retrieved for statistical analysis. The results demonstrate a direct and significant effect on GCD in commercial banks. Moreover, the results of this paper show that cloud computing (CC) mediates the relationship between the independent variable (Accounting Information System Trust (AIS-Trust) with the dependent variable (Grant Credit Decision (GCD)).

Cloud computing (CC) has been used in several industries and domains. However, the use of CC in governmental organization is still limited. The purpose of this study is to examine the CC usage among governmental organizations in Saudi Arabia. The population of this study are Information technology (IT) professionals working for governmental organizations in Saudi Arabia. Purposive sampling was used to collect the data from the respondents. The questionnaire was distributed, and 211 valid responses were collected. The analysis was conducted using Smart PLS 4.0. The findings showed that perceived usefulness (PU), perceived ease of use (PEOU), external influence, security but not privacy have significant effects on CC usage. The findings also showed that technological readiness moderated the effect of PU, external influence, and security on CC usage. Decision makers are recommended to enhance the perception of the benefit of CC and conduct more training courses to ease the usage of CC.

In 2023, the United Arab Emirates (UAE) Digital Government Strategy 2025 required government entities and companies to participate in transforming the country into a smart nation. The first phase named “digital transformation” focuses on digitizing all operations. As such, accounting information systems (AISs)—which collect, organize, and report financial data—must evolve in alignment with this vision. This study explores how professionals in the UAE’s government-owned aviation industry view AIS adaptation to meet national digital transformation goals. Data were gathered through semi-structured interviews with 17 AIS experts, each with at least two years of experience in both AIS and digital transitions. The responses were then open-coded into themes centered around the objectives, benefits, challenges, and organizational impacts of AIS transformation. The findings reveal that a variety of new technologies are being used. For example, blockchain is being applied to supply chains to enhance partner traceability. AI is being used to analyze large data sets, automate repetitive tasks, and integrate non-financial data, such as for fair value assessments, to support IFRS compliance. AI is also helping to improve GDPR compliance by identifying data vulnerabilities and triggering automated safeguards. Cloud computing is also being adopted to reduce idle capacity and offer scalable flexibility. Nevertheless, some challenges were noted, such as limited employee competence and resistance to adopting new systems.

The purpose of the current study is to examine the potentials provided by big data analytics and cloud computing in supporting entrepreneurial ventures. Quantitative approach was adopted through utilizing a questionnaire that was self-administered by (333) operational managers within entrepreneurial ventures operating in Saudi Arabia. SPSS was employed to screen and analyze gathered primary data. Results of study indicated acceptance of study hypotheses and confirmed that big data analytics and cloud computing are able to open many potentials for entrepreneurial ventures through big data analytics and its high potentials of informed decision making, and cloud computing along with its scalability and flexibility. The study suggested that entrepreneurs and their teams must have the necessary skills and knowledge. Investing in education and training programs can help entrepreneurs and their teams to stay up-to-date with the latest technologies and best practices in these areas. Further recommendations were presented in the study. Examining the potentials provided by big data analytics and cloud computing in supporting entrepreneurial ventures is significant because it can help entrepreneurs to make informed decisions, enhance the customer experience, increase efficiency, gain a competitive advantage, and drive innovation.

The main objective of this study was to examine the effectiveness of a teaching program utilizing cloud computing in enhancing the writing skills of students with autism. The research comprised a group of kids diagnosed with ASD who attended schools situated in the Al-Mafraq Governorate. The initial intention was for the experiment to last for a duration of 30 days. A total of 30 students were included in the study, with 15 students randomly assigned to the experimental group and the remaining 15 students assigned to the control group. Following the implementation of the intervention, the experimental group demonstrated a higher level of performance on assessments measuring language and content abilities compared to the control group. There were no significant differences seen in the writing proficiency scores of the experimental group, both at the follow-up assessment and immediately after the intervention.

The main objective of this research was to find out how well cloud computing works for teaching kids in the early grades to think critically. Participants in the study were a group of early childhood students from schools in the Mafraq Governorate. The duration of the trial was set at one month. Sixty students participated in the study; thirty were randomly assigned to the experimental group and thirty to the control group. Following the intervention, the experimental group performed better than the control group on tests measuring reasoning, interpretation, analysis, and assessment skills. Both in the follow-up assessment and in the time immediately after the intervention, the experimental group and the control group did not vary from one another in terms of critical thinking skill scores.

This study aimed to investigate the effect of cloud computing (CC) and company size on accounting information quality. Data were collected using an online questionnaire which followed the Technology Acceptance Model (TAM). The research sample consisted of 178 respondents from accountants and audit offices in the Emirate of Riyadh. The study adopted a Smart PLS in hypothesis testing. The study's results indicated just a positive relationship between perceived benefit and quality of accounting Information. In addition, there was a clear influence of company size on the relationship between CC and accounting information quality.

This research aims to analyze the direct and indirect influence of the use of Big Data and Cloud Computing Platforms on the smooth processing of financial accounting system data and its implications for the success of village development. This research used quantitative methods, using Saturation sampling techniques, and obtained a sample of 131 respondents who were village financial information system operators, consisting of 131 villages in Pringsewu Regency, Lampung Province, Indonesia. The data collected from the surveys was then analyzed using Structural Equation Modeling-Partial Least Squares (SEM-PLS). The research and data analysis demonstrate that Cloud Computing Platforms significantly enhance the efficiency of processing financial accounting system data. Additionally, Cloud Computing Platforms have a direct and positive influence on the success of village development. Moreover, the efficient handling of financial accounting system data directly and significantly impacts the progress of village development. Furthermore, the application of Big Data has a direct and substantial impact on the effective processing of data in financial accounting systems, as well as on the achievement of success in village development. Ultimately, the efficient data processing of the Financial Accounting System serves as a partial intermediary between the utilization of Big Data and Cloud Computing Platforms, and the achievement of village development in Pringsewu Regency, Lampung Province, Indonesia. Because the independent variable is able to significantly influence both directly and indirectly the dependent variable.

The recent progress of Financial Information System (FIS) has significantly affected businesses’ sustainable production process. Businesses generally employ FIS to automate their operational procedures and increase their corporate efficiencies through improvement in output quality and sustainability. The performance of FIS has been attributed to its key success criteria. Accordingly, this study examined antecedents of FIS intention to use among Small and Medium-Size Enterprises (SMEs) in Jordan at individual level, with specific focus on the acceptance and use of FIS among accounting department employees. Based on 436 respondents from Jordanian SMEs, results showed an impact of COVID-19 risk, trust, performance expectancy, and perceived severity on the intention to use FIS, whereas effort expectancy and perceived vulnerability showed no impact on the intention to use FIS among Jordanian SMEs.