Exploring Jordanian Generation Z's Intention to Purchase Energy-Efficient Home Appliances: Integrating the Theory of Planned Behavior and Perceived Value Theory
Bibliographic record
Abstract
Intensive household energy use contributes to climate change, and electrical appliances are a major source of this consumption. Therefore, using energy-efficient appliances is an effective step to improve efficiency and reduce environmental emissions. Consequently, understanding consumer intentions toward adopting these appliances is crucial as a fundamental step toward achieving the desired environmental transformation. This study aimed to explore university students’ intentions to purchase energy-efficient home appliances through a research model that integrates the Theory of Planned Behavior (TPB) and the Theory of Perceived Value (PV). Data were collected from 348 students from the Bachelor of School of Arts at the University of Jordan using a carefully designed questionnaire. The data were analyzed using SmartPLS. The results showed that students’ intention to purchase energy-efficient appliances was positively influenced by subjective norms, perceived behavioral control, and attitude toward purchasing. This positive attitude was also significantly influenced by price value, environmental value, and functional value. In contrast, conditional, emotional, or social values had no significant impact on students’ attitudes toward purchasing these appliances. Based on these findings, the study presented several recommendations aimed at enhancing consumers’ intentions toward adopting energy-efficient home appliances, thus contributing to a shift toward more sustainable consumption behaviors.
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 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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".