Exploring employee acceptance of industrial vehicle-to-grid systems
The role of trust, perceived barriers and benefits
Bibliographic Data
| ID | 21402008 |
|---|---|
| Authors | Lisa Drees (University of Duisburg-Essen, corresponding author), David Meyer (0000-0003-0979-118X, University of Duisburg-Essen), Heike Proff (0000-0001-7226-1814, University of Duisburg-Essen) |
| Year | 2026 |
| Volume | 227 |
| Pages | 124648 |
| Publication date | 2026-06-01 |
| Peer Reviewed | Yes |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Technological Forecasting and Social Change (JOURNAL) |
| Journal identifiers | ISSN: 0040-1625 • E-ISSN: 1873-5509 |
| Publisher | Elsevier BV (PUBLISHER) |
| DOI | 10.1016/j.techfore.2026.124648 |
| OpenAlex | W7139929083 |
| Language | EN |
| References cited | 80 |
The transportation industry is under growing pressure to reduce vehicle emissions. Especially vehicle-to-grid technology can leverage decarbonisation by utilising car batteries as storage for renewable energy, thereby addressing the shortfall in energy storage capacity. This technology offers substantial benefits especially for firms with high energy demand. However, widespread adoption requires employee willingness to participate in vehicle-to-grid charging, an area that has not been explored. Using structural equation modeling, this study evaluates employee acceptance of industrial vehicle-to-grid technology through an integrated model combining the Technology Acceptance Model with trust, perceived barriers, and benefits. Our study examines the acceptance of an emerging industrial system not yet commercially available, positioning it within the research area of technological forecasting and modelling. The findings indicate that perceived barriers negatively affect attitude towards the technology, while trust influences attitude and benefits positively. The relationship between perceived benefits and behavioural intention was not statistically significant. Additionally, group differences were observed between respondents based on their knowledge of the technology and electric vehicles in general. The research offers insights for firms and policymakers for fostering trust through standardised data protocols, decreasing perceived barriers by offering a range of flexible charging contracts, and creating knowledge about the benefits in test studios
Affect (linguistics) · Key (lock) · Technology Acceptance Model · Work (physics) · Electric Vehicles and Infrastructure · Human-Automation Interaction and Safety · Transportation and Mobility Innovations
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| Citation velocity | historical |
|---|---|
| Highly cited | No |