Role of Egoistic and Altruistic Values on Green Real Estate Purchase Intention Among Young Consumers: A Pro-Environmental, Self-Identity-Mediated Model
Bibliographic record
Abstract
This study explores the role of egoistic and altruistic values on green real estate purchase intention among young consumers in Canada aged between 20 and 40 years. In addition, this study examines the mediating effects of pro-environmental self-identity between social consumption motivation and green real estate purchase intention. A quantitative cross-sectional research design with an explanatory nature is employed. A total of 432 participating consumers in Canada, comprising 44% men and 48% women, with a graduate educational background accounting for 46.7%, and the ages between 24 and 35 contributing 75.2%, were part of the study, and the data collection used a survey method with a purposive sampling, followed by a respondent-driven method. Descriptive and inferential statistics were performed on the scales used for the study variables. A structural equational model and path analysis were conducted to derive the results, and the relationships were positive and significant. The study results infer the factors contributing to green real estate purchase intention, including altruistic value, egoistic value, social consumption motivation, and pro-environmental self-identity, with pro-environmental self-identity mediating the relationship. This study emphasizes the relevance of consumer values in real estate purchasing decisions, urging developers and marketers to prioritize ethical ideas, sustainable practices, and building a feeling of belonging and social connectedness. Offering eco-friendly amenities and green construction methods might attract clients, but creating a secure area for social interaction is critical. To the best of the authors’ knowledge, this research is the first to explore the role of egoistic and altruistic values on purchase intention, mainly in the housing and real estate sector, with the target consumers being young consumers in Canada.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".