User behaviour in sustainable technology: an exploration of endorsement strategy
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Given the lethargic acceptance behaviour of sustainable technologies (STs) by the public, the most crucial factor to contemplate is the influential form of organization endorsement strategy that can effectively enhance user intentions and behaviour. Using the social identity theory (SIT) and source credibility theory (SCT), this research examines the moderating potential of an attractive celebrity (CET) and social media influencer (IET) on user intention and behaviour in low- and high-involvement sustainable technologies (LISPs and HISPs). Based on an SEM-ANN analysis of data from 605 Chinese respondents, our empirical findings show that in the LISPs context, IETs moderate the intention-behaviour relationship positively whereas CETs have the opposite impact. In contrast, the moderating effect of CETs on HISPs is positive, whereas the effect of IETs is negative. Furthermore, it was shown that HISP users’ income level significantly influenced their behaviour, while education level had no significant impact on either category. These outcomes have both theoretical and practical implications in developing resilient strategies to retain users and provide guidance on how to efficiently optimise, integrate, and evaluate the STs.
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Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it