The DOI matches its Crossref record; 150 of the 150 references it cites were found in a registry or an index.
Industry 4.0 and the supply chain digitalisation: a blockchain diffusion perspective
Abstract
The emergence of Industry 4.0 has brought in its wake an important number of challenges and opportunities for organisations across the globe. To cope with such a fast-changing environment, organisations have been steadily implementing different types of technologies, and at different stages. One of the most disruptive and promising technology is blockchain, and its potential to transform various aspects of organisations’ business and operations, including the supply chain relationships, is tremendous. In line with the global research trend in this domain, this paper proposes a multi-stage model of adoption (intention, adoption, and routinisation stages), for a better understanding of blockchain diffusion across supply chains. We drew on the diffusion of innovations theory, the resource-based view, dynamic capability, the technology adoption model, and the institutional theory to propose a multi-stage model. We validated the model using PLS-SEM, which was applied on data collected in India and the U.S. Our results showed that, from one country to another, there are essential differences in the variables that determine blockchain innovation and in the stage of diffusion. Additionally, our proposed model provided a good explanation at all stages of blockchain diffusion. This study offers significant and valuable contributions in terms of theory and management.
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Cites
Evaluating structural equation models with unobservable variables and measurement error
Fornell, C., & Larcker, D. F. (1981) · Journal of Marketing Research · doi:10.1177/002224378101800104 · Cited by 109,190
Perceived usefulness, perceived ease of use, and user acceptance of information technology
Davis, F. D. (1989) · MIS Quarterly · doi:10.2307/249008 · Cited by 68,483
Firm Resources and Sustained Competitive Advantage
Barney, J. (1991) · Journal of Management · doi:10.1177/014920639101700108 · Cited by 48,334
User Acceptance of Information Technology: Toward A Unified View1
Venkatesh, V., Morris, M. G., Davis, G. B., & Davis, F. D. (2003) · MIS Quarterly · doi:10.2307/30036540 · Cited by 45,035
DiMaggio, P. J., & Powell, W. W. (1983) · American Sociological Review · doi:10.2307/2095101 · Cited by 38,435
Absorptive Capacity: A New Perspective on Learning and Innovation
Cohen, W. M., & Levinthal, D. A. (1990) · Administrative Science Quarterly · doi:10.2307/2393553 · Cited by 35,728
DiMaggio, P. J., & Powell, W. W. (2004) · Advances in Strategic Management · doi:10.1016/s0742-3322(00)17011-1 · Cited by 25,802
User Acceptance of Computer Technology: A Comparison of Two Theoretical Models
Davis, F. D., Bagozzi, R. P., & Warshaw, P. R. (1989) · Management Science · doi:10.1287/mnsc.35.8.982 · Cited by 25,709
A Theoretical Extension of the Technology Acceptance Model: Four Longitudinal Field Studies
Venkatesh, V., & Davis, F. D. (2000) · Management Science · doi:10.1287/mnsc.46.2.186.11926 · Cited by 23,066
Self-Reports in Organizational Research: Problems and Prospects
Podsakoff, P. M., & Organ, D. W. (1986) · Journal of Management · doi:10.1177/014920638601200408 · Cited by 17,102
Cited by
Elia, S., Giuffrida, M., Mariani, M. M., & Bresciani, S. (2021) · Journal of Business Research · doi:10.1016/j.jbusres.2021.04.010 · Cited by 426
Ivanov, D. (2024) · IEEE Transactions on Engineering Management · doi:10.1109/tem.2021.3095193 · Cited by 336
Metadata
- Authors
- Wamba, S. F., & Queiroz, M. M.
- Venue
- Production Planning & Control
- Publisher
- Informa UK Limited
- Published
- 2020-08-27
- Volume
- 33
- Issue
- 2-3
- Pages
- 193-210
- ISSN
- 0953-7287 (ISSN-L)
- 1366-5871
- OpenAlex
- W3082103041
- Cited by
- 298
- References
- 150
- FWCI
- 36.73
- Type
- journal article
- Language
- en
- Open access
- closed
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