Adoption of Energy-Efficient Home Appliances: Extending the Theory of Planned Behavior
Bibliographic record
Abstract
This research applies an extended theory of planned behavior (TPB) to empirically investigate consumers’ intentions in Pakistan to purchase energy-efficient appliances (EEAs). Most developing countries face energy crises. As a result, many countries consider EEAs to be part of the solution to energy-related problems and teach sustainable consumption behavior to consumers. Previous studies have neglected developing countries in this context, yet developing markets have great potential for EEA adoption. To understand EEA adoption, we incorporated such variables as warm glow benefits, utilitarian environmental benefits, normative beliefs, and moral obligations as antecedents to TPB variables. The moderating effect of eco-literacy between attitude, subjective norms, perceived behavioral control (PBC), and purchase intention toward EEAs are also examined. Data was gathered through a survey questionnaire from 673 Pakistani consumers to empirically test the proposed hypotheses. The results reveal that utilitarian environmental benefits and warm glow benefits significantly influence attitudes toward EEAs. The findings also show a positive effect of normative beliefs on subjective norms. The interaction effect of eco-literacy positively influences the relationship between attitude and purchase intention, with similar results for subjective norms and purchase intention. However, no significant moderating effect of eco-literacy is found between PBC and purchase intention. Furthermore, we performed multi-group analysis to explore significant group differences by utilizing socio-demographic variables such as gender, age, education, and income. The results show significant group differences, with females’ purchasing behavior, younger consumers, and educated consumers being more readily influenced. Finally, insights for policymakers, suggestions and future directions are discussed.
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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 | 0.003 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".