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This paper seeks to discover whether the technical, organisational and technology acceptance model (TAM) factors will significantly affect the adoption of blockchain technology (ABT) amongst SMEs.

The research employs structural equation modelling (SEM) and a machine learning approach to identify factors influencing the ABT behaviour that leaders can use to predict the prospect of the ABT in their enterprises. Information was collected from 255 respondents representing 166 SMEs in the food industry, Palestine.

The analyses reveal that the ABT is positively and significantly shaped by TAM factors: (1) perceived benefits and (2) perceived ease of using blockchain. Simultaneously, the former is significantly influenced by compatibility and upper management support, while the latter is affected by complexity. Finally, education and training affect both factors.

This paper is amongst the first attempts to examine the ABT behaviour in the food industry using the integration of SEM and machine learning approach.

The study aims to deliver a decision support system for business leaders to estimate the potential for effective technological adoption of the blockchain (TAB) with a machine learning approach.

This study uses a Bayesian network examination to develop an extrapolative system of decision support, highlighting the influential determinants that managers can employ to predict the TAB possibilities in their companies. Data were gathered from 167 SMEs in the largest industrial sectors in Palestine.

The results reveal perceived benefit and ease of use as the most influential determinants of the TAB.

This research is an initial effort to examine factors influencing TAB in the perspective of SMEs in Palestine using machine learning algorithms.

This research sought to determine the impact of the management of electronic customer relationships through applying 5IS model on the mental image of Umniah Mobile Network Operator Company’s customers in Amman City. To fulfill the goals of the study, the researcher adopted the descriptive, analytic method. He developed an instrument to collect the data through a questionnaire, which was distributed through the simple, random sampling method over 700 customers of Umniah Company, in the City of Amman, out of which 400 analyzable questionnaires were retrieved. The researcher further employed the convenient statistical methods applying SPSS 22 Program for data analysis. The study concluded many results such as there is statistically significant impact at the significance level (α < 0.05) for the administration of consumer relationships through the use of 5IS model on the mental image of the provided services of Umniah Mobile Network Operator Company in Amman city. In this concern, the integration component is the most influential in the mental image with the customers of Umniah Company. Therefore, the study recommended the need Umniah Telecom Company has to search for the best means to positively influence shaping the mental image of its products, especially the means through which it can provide more information about its services.

In light of the complex risk and transparency regulations, this paper investigates the factors influencing the level of risk management disclosure by insurance firms in Jordan and Palestine. The characteristics examined were ownership structure, which covers public, institutional and management ownership on risk management disclosure (RMD) utilizing ISO 31000, as well as profitability, leverage, liquidity and firm size.

To achieve the aim of this study, a quantitative research methodology was used. Based on the total number of observations, 232 purposeful annual observations for the study sample were collected between 2016 and 2023 for 10 insurance companies listed on the Palestine stock exchange (Palestinian companies) with 80 observations and 19 companies listed on the Amman stock exchange (Jordanian companies) with 152 observations. This study uses panel data regression with fixed effects models. By employing the 2SLS approach, we comprehensively address the main endogeneity concerns and problems in risk management disclosure RMD of insurance firms in Jordan and Palestine.

The results show that risk management disclosure is significantly influenced by the liquidity and size of an organization. Furthermore, RMD is not significantly affected by profitability, debt, public ownership, institutional ownership or liquidity, whereas business size has a favorable influence.

The findings of this study may not be generalizable to firms in other countries because of the limitations of insurance firms in Palestine and Jordan. Study replication in future studies should consider the potential for bias and differences in data interpretation when utilizing qualitative methodologies to evaluate RMD.

The practical implications emphasize how crucial it is for investors, practitioners and stakeholders to choose firms that are large and have little liquidity because this is linked to high levels of risk management transparency. This knowledge can offer investors an important direction for assessing possible risks and transparency in risk management within the insurance sector framework. The study recommends that the governments of Palestine and Jordan enact laws requiring risk management disclosure according to the ISO 31000:2018 standard, especially in the insurance industry.

This study contributes to the literature by illuminating the relationship between firm size, liquidity and risk management disclosure in insurance companies operating in Jordan and Palestine. Therefore, investors should choose large, relatively liquid companies with strong risk management disclosure. This study offers theoretical insights that may be used as a guide for other research, improving the understanding of the variables influencing risk management disclosure in insurance companies and advancing scientific understanding.