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Commercial banks are the catalysts for meeting the financing needs of small and medium enterprises (SMEs). However, not all commercial banks are equally attractive to SMEs because of differences in banking services’ key attributes. Moreover, customers’ preferences vary between Islamic and conventional banks. This paper aims to identify factors motivating SMEs to establish business ties with banks in Oman.

The authors collected data from 217 SMEs through a questionnaire survey. The data were analyzed using a t-test and structural equation modeling (SEM). In addition, the research applies the theory of planned behavior as a theoretical framework.

The t-test results show that SMEs place greater emphasis on electronic banking, convenient locations, religious beliefs and favorable terms and conditions. The results from the SEM analysis show that the SMEs in Oman consider attractive packages, including favorable rates, transaction processing time, fees and the availability of technology-enabled services, when choosing a bank. Moreover, customers who are aware of Islamic banking products are optimistic about the future of Shariah-based banking.

As a Muslim-majority country, Oman lags behind its Gulf Cooperative Council peers in terms of the development of the Islamic banking system. For the success of this mode of financing, it is essential to know which factors SMEs prioritize to establish ties with Islamic banks. Hence, the research is expected to provide new information for bank management to devise financial products attractive to investors.

Demand forecasts are a key component of planning efforts and are crucial for managing core operations. This study aims to evaluate the use of several machine learning (ML) algorithms to forecast demand for residential construction in Jordan.

The identification and selection of variables and ML algorithms that are related to the demand for residential construction are indicated using a literature review. Feature selection was done by using a stepwise backward elimination. The developed algorithm’s accuracy has been demonstrated by comparing the ML predictions with real residual values and compared based on the coefficient of determination.

Nine economic indicators were selected to develop the demand models. Elastic-Net showed the highest accuracy of (0.838) versus artificial neural networkwith an accuracy of (0.727), followed by Eureqa with an accuracy of (0.715) and the Extra Trees with an accuracy of (0.703). According to the results of the best-performing model forecast, Jordan’s 2023 first-quarter demand for residential construction is anticipated to rise by 11.5% from the same quarter of the year 2022.

The results of this study extend to the existing body of knowledge through the identification of the most influential variables in the Jordanian residential construction industry. In addition, the models developed will enable users in the fields of construction engineering to make reliable demand forecasts while also assisting in effective financial decision-making.

This paper aims to examine the effects of corporate governance mechanisms (board chairman independence, board independent director meeting attendance, audit committee size and audit committee meetings) on the environmental, social and governance (ESG) and its individual component disclosures of listed firms in Saudi Arabia.

The study used unbalanced panel data obtained from the Bloomberg data set over 11 years, from 2010 to 2020.

The findings indicate that board chairman independence (BCI) and audit committee size (AC size) have a significant negative and positive association with ESG disclosure, respectively. However, the results show that board independent director meeting attendance (BIMA) and audit committee meetings (AC meetings) do not significantly influence ESG disclosure. Regarding the individual dimensions (components), the results show that only BIMA has a significant negative association with environmental disclosure. Besides, only BCI and AC meetings have a significant positive association with social disclosure. Also, only BIMA and AC size have a significant positive and negative relationship with governance disclosure, respectively.

The study used a sample of 29 listed companies in Saudi Arabia. Each firm has at least four years of ESG disclosures. Besides, the paper considered only four corporate governance attributes, comprising two each for the board and audit committee.

The results provide insights to regulators, boards of directors, managers and investors to enhance ESG and its components’ reporting toward the sustainable operations and better performance of Saudi firms.

This study is among the few that provide empirical evidence on how some essential corporate governance attributes that have not been given adequate attention by prior studies (board chairman independence, board independent directors’ meeting attendance, audit committee size and audit committee meetings) influence not only ESG reporting as a whole but also its individual dimensions (components).