Motivation continuum and its effect on electric vehicle acceptance in India
Bibliographic record
Abstract
Purpose The motivation to choose an electric vehicle (EV) is guided by principles of personal values, perceived rewards and preferences. While the benefits of sustainable transportation are known, the acceptance of EVs and the motivation to purchase them is not satisfactory in India. An assessment of the motivation continuum, a range of intrinsic to extrinsic personal and societal drives that encourage specific choices, explains the lack of EV adoption in the country. This study aims to examine the effect of motivation types on EV adoption intentions and also explores the moderating role of gender in this context. Design/methodology/approach By incorporating constructs from the self-determination theory, the study expands on the technological acceptance model. It uses the structural equation modelling method to test the hypotheses and presents an analysis of responses from 351 participants. Findings The findings suggest that there are significant relationships between external, identified, integrated motivation and EV buying intentions. The influence of gender on EV adoption is also explored. Originality/value This study provides an in-depth analysis of varied motivational types on EV buying intentions and the moderating effects of gender on these relationships.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".