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Publication date: 16 January 2025

Cong Gao, Kay-Hooi Keoy and Ai-Fen Lim

The purpose of this study is to investigate the primary determinants influencing the acceptance of generative artificial intelligence (GAI) adoption within Blockchain-enabled…

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Abstract

Purpose

The purpose of this study is to investigate the primary determinants influencing the acceptance of generative artificial intelligence (GAI) adoption within Blockchain-enabled environments. Further research will examine the impact of GAI adoption on supply chain efficiency (SCE) through the enhancement of Blockchain.

Design/methodology/approach

Drawing on innovation diffusion theory (IDT), this study used partial least square structural equation modelling (PLS-SEM) to look into the hypotheses. The data were gathered via online questionnaires from employers of Chinese supply chain enterprises that have already integrated Blockchain.

Findings

The findings of this study demonstrate that relative advantages (RAs), compatibility, trialability and observability have a significant positive effect on GAI adoption, while complexity harms GAI adoption. Above all, the GAI adoption has significantly enhanced Blockchain, thus effectively improving SCE.

Practical implications

The outcomes from this study furnish enterprises and organizations with valuable insights to proficiently integrate GAI and Blockchain capability, optimize supply chain management and bolster market competitiveness. Also, this study will help accelerate the successful integration of business processes and attain Sustainability Development Goals 9, industrial growth and industrial diversification.

Originality/value

To the extent of the author’s knowledge, the current status of the GAI study remains largely exploratory, and there is limited empirical evidence on integrating Blockchain capability and GAI. This research bridges the knowledge gap by fully revealing the optimal integration of these two transformative technologies to leverage their potential advantages in supply chain management.

Details

Journal of Systems and Information Technology, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 1328-7265

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