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1 – 2 of 2Ihab K. A. Hamdan, Wulamu Aziguli, Dezheng Zhang, Eli Sumarliah and Kamila Usmanova
This paper seeks to discover whether the technical, organisational and technology acceptance model (TAM) factors will significantly affect the adoption of blockchain technology…
Abstract
Purpose
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.
Design/methodology/approach
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.
Findings
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.
Originality/value
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.
Details
Keywords
Ihab K.A. Hamdan, Eli Sumarliah and Fauziyah Fauziyah
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…
Abstract
Purpose
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.
Design/methodology/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.
Findings
The results reveal perceived benefit and ease of use as the most influential determinants of the TAB.
Originality/value
This research is an initial effort to examine factors influencing TAB in the perspective of SMEs in Palestine using machine learning algorithms.
Details