Forecasting blockchain adoption in supply chains based on machine learning

Evidence from Palestinian food SMEs

Bibliographic Data

ID21295484
AuthorsIhab K A Hamdan (0000-0002-9591-7238, University of Science and Technology Beijing School of Computer and Communication Engineering), Wulamu Aziguli (University of Science and Technology Beijing School of Computer and Communication Engineering), Aziguli Wulamu (0000-0001-7228-7838, University of Science and Technology Beijing), Dezheng Zhang (0000-0002-3456-5259, University of Science and Technology Beijing School of Computer and Communication Engineering), Eli Sumarliah (0000-0002-8680-8558, University of Science and Technology Beijing School of Economics and Management), Kamila Usmanova (0000-0003-1509-9878, University of Science and Technology Beijing School of Economics and Management)
Year2022
Volume124
Issue12
Pages4592-4609
Publication date2022-11-03
Peer ReviewedYes
Open AccessNo
TypeARTICLE
VenueBritish Food Journal (JOURNAL)
Journal identifiersISSN: 0007-070X • E-ISSN: 1758-4108
PublisherEmerald (PUBLISHER)
DOI10.1108/bfj-05-2021-0535
OpenAlexW4210849651
LanguageEN
Citations received5
References cited29

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

Affect (linguistics) · Blockchain · Business · Creativity · Knowledge management · Machine learning · Originality · Palestine · Structural equation modeling · Supply chain · Supply chain management · Technology Acceptance Model · Usability · Value (mathematics) · Blockchain Technology Applications and Security · Computer Science · Marketing · Psychology · Social Psychology · Supply Chain and Inventory Management · Sustainable Supply Chain Management

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