Search results

This paper aims to provide better understanding on this phenomenon, as well as some recommendations to assist in preparing Al technology and its related aspects during crisis like Covid period and beyond.

The study consisted of two phases. Phase one focused on identifying top higher education institutions according to the QS world university ranking. As a result, 180 higher education institutions in the Arab region were found, with the 2022 QS Arab region university ranking. The study selected top 20 performing institutions. Each institution has been assessed according to six metrics including: international student ratio, international research network, international ration, Web impact, citation per page and paper per faculty. Phase two explored the adapted Al applications and their related aspects that are used in each institution using a learning online questionnaire. Pilot tests were used to determine the validity and reliability of the measures.

Numerous factors that lead to enhancing high education using Artificial Intelligence in higher education institutions have emerged from this study. These factors include; knowledge management, trust, learning, technical resources and complexity. First, effective knowledge management assists in maintaining information in a place where it is easy to share and access. Second, trust is considered a critical factor in dealing with uncertainties like covid-19. It needs to be effectively addressed by students and staff members, especially in higher education. Without trust, decisions cannot be successfully made and actions may be delayed or stalled. Third, continuous learning is a key factor that tends to enhance the capability of dealing with new routines or potential challenges. Fourth, technical resources refer to electronic devices and tools that are used by students and academics to interact and share knowledge.

Students and faculty academics perceive things and use Al technology differently, which can lead to misunderstanding and create tension between them. Many higher education institutions have adapted great Al technology applications, but they are significantly less proficient than previously thought at understanding how to leverage this technology to produce helpful solutions to their business difficulties.

This study aims to shed light on the challenges and obstacles (organizational, economic, legal and legislative) to the issuance of Islamic Sukuk in Palestine.

The descriptive analytical approach was adopted to collect data through a questionnaire that was distributed to a simple random sample of (500) male and female employees working in those banks.

The study concluded that the issuance of Islamic Sukuk in Palestine suffers from economic, legal and legislative challenges and obstacles. This includes the lack of interest in using it as a suitable financing tool to finance various economic projects, as it requires the presence of investors with high financial solvency in light of the low contribution of Palestinian legislation and laws to facilitate and encourage their issuance. Hence, there are no regulatory challenges or obstacles.

Few studies examine the issuance of Sukuk in the Palestinian environment, despite the attempts of the Palestinian Monetary Authority to develop Islamic financing instruments.

The necessity of subjecting the issuance of Islamic Sukuk in Palestine and all Islamic financing products to a unified body It is also important to work on spreading the Islamic financing culture related to their issuance, given its positive role in developing and providing the necessary funding for various projects.

The study identifies the level of challenges and obstacles facing the issuance of Islamic Sukuk in Palestinian banks by studying the organizational, economic, legal and legislative dimensions. The study attempts to explore this through the respondents’ opinions. It also focuses on emphasizing the role of this performance in economic development and supporting the elements of investment as a desirable financing alternative.

This study aims to identify the impact of adopting different techniques of artificial intelligence including (expert systems, machine learning, neural networks and algorithms) in improving the quality of accounting information characteristics such as; appropriateness, faithful representation and verifiability in Palestinian industrial enterprises.

Employees from 13 companies registered on the Palestine Stock Exchange for 2023 were selected. Moreover, the sample included 326 randomly chosen participants. A questionnaire was distributed to participants to collect data, and a descriptive-analytical approach was followed to achieve the study’s aim and examine its hypotheses.

The results showed that the use of artificial intelligence techniques (expert systems, machine learning, neural networks and algorithms) has a positive effect on improving the quality of accounting information characteristics (relevance, faithful representation and verifiability). Expert systems, neural network applications and algorithms contribute to developing solutions to various problems in industrial companies; discovering fraudulent practices in financial statements; and obtaining more accurate, faster and more reliable results. Machine learning also links the company’s systems together simultaneously and in an integrated and effective manner.

The research relied on the industrial sector only because expanding society is difficult due to the general conditions in Palestine, and the results may vary between different sectors due to the nature of their work and activity.

Industrial companies’ efforts to benefit from artificial intelligence applications in their work increase the quality of accounting information, which in turn reflects the company’s real situation and helps in making the necessary decisions efficiently and effectively.

This study contributes to directing the attention of financiers and accountants working in Palestinian industrial companies to the importance of applying artificial intelligence techniques to ensure the highest quality characteristics of accounting information through the preparation of accounting programmes that rely on artificial intelligence to operate, thus achieving the maximum degree of advantage in compiling financial data from its sources, operation and conversion into useful financial information for its users.

This study investigates whether there are relationships between the characteristics of the boards of trustees of universities in the Arab region, higher education quality assurance and the output of scientific research.

The descriptive analytical approach was used in this study. The study was conducted on the universities of the Arab region that are included in the classification of the British Institution for the Arab Region: QS Arab Region University.

The findings show that there is an effect of the characteristics of the trustees combined in the universities of the Arab region on ensuring the quality of higher education, other than the output of scientific research. The findings also indicate when measuring the characteristics individually that the trustee system is not effective in the Arab region and it is only formal for nominal purposes.

Most universities in the Arab region do not disclose the data of boards of trustees, their roles, committees, rules of procedure and the nature of their work. A large number of universities also do not operate under the trustee system because the regulations and instructions do not allow this in the country.

This study seeks to improve practitioners knowledge, including boards of trustees, in ensuring the quality of higher education and the output of scientific research.

The research projected the governance model through the characteristics of the boards of directors of for-profit companies on the boards of trustees of universities in the Arab region. The study examines the nature of the characteristics of the boards of trustees that are compatible with its responsibilities, the most important of which is the supervision of the strategy to ensure the quality of higher education research.

This study aims to adopt the Altman model in order to predict the performance of industrial companies listed on the Palestinian Stock Exchange during the period of time between 2013 and 2017.

The study sample consisted of 12 industrial companies listed on the Palestine Stock Exchange, and their financial disclosure period extended for 5 years. Multiple linear regression model was used in the analysis to determine the relationship between the independent variables and the dependent variable where the independent variables were (X₁, X₂, X₃). This study is based on one basic assumption, which is that the Altman's model cannot predict the performance of the Palestinian industrial sector.

The results of the analysis proved the negation of the zero main hypothesis. This means that Altman's model can predict the performance of the Palestinian industrial sector at the level of statistical significance (a = 0.05), as well as the existence of a statistically significant relationship between each of the independent variables (X₂, X₄, X₅) and the dependent variable (Log (Z-score)). Hence, the relationship of X₁ and X₃ with the dependent variable was not statistically significant.

This paper highlights different challenges that face the adaption of Atman's model and performance prediction in the Palestinian industrial sector. The findings of the analysis have the potential to help future researchers in examining and dealing with new challenges.

This paper presents a vital review of adopting Altman's model in the Palestinian industrial sector. A number of recommendations have been made, the most important of which is that most of the companies are located in the red zone. The Altman's model must be adapted in order to fit the Palestinian environment according to the results of statistical analysis and according to a proposed model, which is Log (Z) = −0.653 + 0.72X₂ + 0.18X₄ + 0.585X₅.