Understanding resident attitudes toward sustainable tourism: evidence from Egyptian ecovillages on perceived benefits and resident support
Bibliographic record
Abstract
Purpose This paper examines the effect of perceived benefits on resident support for sustainable tourism development. It further explores the moderating effects of resident involvement and attachment, drawing on social exchange, place attachment and involvement theories to explain community-based tourism strategies in developing-country contexts. Design/methodology/approach Data was gathered from 323 residents of three Egyptian ecovillages (i.e. Al-Qaramous, Fuwah and Tunis) and were analyzed using partial least squares structural equation modeling (PLS-SEM). Findings Results showed that perceived economic benefits were the most influential factor in residents’ support for sustainable tourism development. In addition, resident involvement and attachment significantly strengthened this benefit–support relationship. Practical implications Findings provide valuable insights for policymakers and destination managers when evaluating the positive and negative effects of economic, social and environmental benefits on resident support. This paper indicates that community-based planning practices, targeted capacity-building interventions and the effective use of local knowledge empower residents, foster genuine engagement in ecotourism destinations and enhance long-term sustainability. Originality/value This paper contributes to the tourism literature by investigating the mutually constitutive effects of perceived benefits, resident involvement and attachment on ecovillage development. It is situated in a developing-country context (Egypt), where the sustainable tourism framework remains underfunded and underexplored.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".