Predictors for distributed ledger technology adoption: integrating three traditional adoption theories for manufacturing and service operations

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Abstract

It is expected that blockchain technology will bring a disruptive paradigm shift in the manner in which transactions are conducted in the manufacturing and service enterprises. By eliminating the drawbacks of trust-related issues in a business chain, the distributed database of blockchain can bring transparency with pseudonymity and irreversibility of records. In this paper, we advance the limited literature on DLT and its adoption in the manufacturing and service enterprises. The proposed model is based on the integration of three traditional adoption theories namely Technology Acceptance Model (TAM), Technology Readiness Index (TRI) and Theory of Planned Behavior (TPB). Based on a survey of 211 experts of Pakistan, the proposed model was tested using structural equation modelling. The study result confirms that Theory of Planned Behavior and TAM play a key role in the disruptive technology implementation. It is one of the early studies on blockchain technology adoption in the manufacturing and service enterprises and the study results indicate that more manufacturing and service industries are transforming to intelligent operations. Smart manufacturing system through blockchain applications has become the focus of attention of businesses.

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Ullah, N., Mugahed Al-rahmi, W., & Alkhalifah, A. (2021). Predictors for distributed ledger technology adoption: integrating three traditional adoption theories for manufacturing and service operations. Production and Manufacturing Research, 9(1), 178–205. https://doi.org/10.1080/21693277.2021.1976963

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