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Antecedents of blockchain adoption in the poultry supply chain: An extended UTAUT model

Author

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  • Lavaei Adaryani, Rasool
  • Palouj, Mojtaba
  • Karbasioun, Mostafa
  • Asadi, Ali
  • Gholami, Hesamedin
  • Kianirad, Ali
  • Joodi Damirchi, Milad

Abstract

Currently, blockchain adoption as an emerging technology is in its infancy in most developing countries such as Iran. However, there is a current paucity of empirical research focusing specifically on the antecedents of blockchain adoption in the context of these countries. This study aims to investigate the behavioral intention (BI) to use blockchain by extending the Unified Theory of Acceptance and Use of Technology (UTAUT) model, incorporating subjective and objective knowledge, trust in technology, and information literacy. The proposed structural model was assessed by partial least squares structural equation modeling (PLS-SEM) using the data from 275 senior managers of Iranian poultry supply chains. The results showed that effort expectancy and performance expectancy were the most influential variables in predicting the BI to use blockchain technology, respectively. Furthermore, objective knowledge had an impact on the intention to use blockchain. However, subjective knowledge was not found to have any effect. The proposed model including the moderating effects of trust in technology and information literacy showed a higher predictive power. Trust in technology moderated the relationship between performance expectancy and behavioral intention, and information literacy moderated the relationship between technical infrastructure, as one of the facilitating conditions, and behavioral intention. The theoretical and practical implications are discussed in the paper.

Suggested Citation

  • Lavaei Adaryani, Rasool & Palouj, Mojtaba & Karbasioun, Mostafa & Asadi, Ali & Gholami, Hesamedin & Kianirad, Ali & Joodi Damirchi, Milad, 2024. "Antecedents of blockchain adoption in the poultry supply chain: An extended UTAUT model," Technological Forecasting and Social Change, Elsevier, vol. 202(C).
    • Handle: RePEc:eee:tefoso:v:202:y:2024:i:c:s0040162524001057
    DOI: 10.1016/j.techfore.2024.123309
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