The DOI matches its Crossref record; 33 of the 33 references it cites were found in a registry or an index.
Understanding the Blockchain technology adoption in supply chains-Indian context
Abstract
Blockchain technology (BT) is expected to bring a revolutionary paradigm shift in the manner the transactions are carried in the supply chains. BT provides better visibility and transparency by removing the disadvantages of trust related issues in a supply chain. In this paper, we advance the literature on BT and its adoption in the supply chain by developing, and statistically validating a model for understanding the user perceptions on BT adoption. The model is based on the integration of three adoption theories- technology acceptance model (TAM), technology readiness index (TRI) and the theory of planned behaviour (TPB). Based on a survey of 181 supply chain practitioners in India the proposed model was tested using structural equation modelling. The study found that the TRI constructs- Insecurity and discomfort have an insignificant effect on the perceived ease of use and usefulness. Perceived usefulness, attitude, and perceived behavioural control affect the behavioural intention. Subjective norm has a negligible impact on behavioural intention. This is one of the preliminary studies on BT adoption in supply chain and the findings imply that the supply chain practitioners perceive BT adoption free of efforts and would help them to derive maximum benefits for improving the supply chain effectiveness.
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Cited by
Dutta, P., Choi, T.-M., Somani, S., & Butala, R. (2020) · Transportation Research Part E: Logistics and Transportation Review · doi:10.1016/j.tre.2020.102067 · Cited by 1,545
Pournader, M., Shi, Y., Seuring, S., & Koh, S. C. L. (2020) · International Journal of Production Research · doi:10.1080/00207543.2019.1650976 · Cited by 854
Tsolakis, N., Schumacher, R., Dora, M., & Kumar, M. (2023) · Annals of Operations Research · doi:10.1007/s10479-022-04785-2 · Cited by 325
Rodríguez-Espíndola, O., Chowdhury, S., Dey, P. K., Albores, P., & Emrouznejad, A. (2022) · Technological Forecasting and Social Change · doi:10.1016/j.techfore.2022.121562 · Cited by 279
Nandi, M. L., Nandi, S., Moya, H., & Kaynak, H. (2020) · Supply Chain Management: An International Journal · doi:10.1108/scm-12-2019-0444 · Cited by 269
Metadata
- Authors
- Kamble, S., Gunasekaran, A., & Arha, H.
- Venue
- International Journal of Production Research
- Publisher
- Informa UK Limited
- Published
- 2018-09-08
- Volume
- 57
- Issue
- 7
- Pages
- 2009-2033
- ISSN
- 0020-7543 (ISSN-L)
- 1366-588X
- OpenAlex
- W2890784719
- Cited by
- 960
- References
- 33
- FWCI
- 87.66
- Type
- journal article
- Language
- en
- Open access
- closed
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
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