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Record W4408240655 · doi:10.1108/jeas-07-2024-0262

Motivation continuum and its effect on electric vehicle acceptance in India

2025· article· en· W4408240655 on OpenAlexaff
Stanny Dias, Benny Godwin J. Davidson, Arun Antony Chully, Pradeep Hari Pendse

Bibliographic record

VenueJournal of economic and administrative sciences. · 2025
Typearticle
Languageen
FieldEngineering
TopicElectric Vehicles and Infrastructure
Canadian institutionsUniversity of the Fraser Valley
Fundersnot available
KeywordsPsychologyElectric vehiclePhysicsThermodynamics

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.318
Threshold uncertainty score0.251

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.010
GPT teacher head0.257
Teacher spread0.246 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations3
Published2025
Admission routes1
Has abstractyes

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