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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.