Abstract
In developed nations, the advent of distributed ledger technology is emerging as a new instrument for improving the traditional system in developing nations. Indeed, adopting blockchain technology is a necessary condition for the coming future of organizations. The distributed ledger technology provides better transparency and visibility. This study investigated the features that may influence the behavioral intention of energy experts to implement the distributed ledger technology for the energy management of developing countries. The proposed model is based on the Technology Acceptance Model construct and the diffusion of the innovation construct. Based on a survey of 178 experts working in the energy sector, the proposed model was tested using structural equation modeling. The findings showed that perceived ease of use, perceived usefulness, attitude, and cost saving had a positive and significant impact during the blockchain technology adoption. However, innovativeness showed a positive effect on the perceived ease of use whereas an insignificant impact on the perceived usefulness. The present study offers a holistic model for the implementation of innovative technologies. For the developers, it suggest rising disruptive technology solutions.
Original language | English |
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Article number | 4783 |
Number of pages | 22 |
Journal | Energies |
Volume | 13 |
Issue number | 18 |
DOIs | |
Publication status | Published - 14 Sept 2020 |
Bibliographical note
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.Funder
This work was funded by the Researcher Supporting Project (RSP-2020/250), King Saud University, Riyadh, Saudi Arabia.Keywords
- Adoption theories
- Blockchain
- DLT
- Energy sector
- TAM
ASJC Scopus subject areas
- Renewable Energy, Sustainability and the Environment
- Energy Engineering and Power Technology
- Energy (miscellaneous)
- Control and Optimization
- Electrical and Electronic Engineering