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Record W4410137697 · doi:10.18280/ijsdp.200435

Balancing Ecology, Economy, and Community: An Analytic Network Process (ANP) Framework for Sustainable Ecotourism Development

2025· article· en· W4410137697 on OpenAlexvenueno aff
Ichsan Ichsan, Azhar Azhar, Munardi Munardi, Masdi Masdi, Wulan Dara Sari Arhas

Bibliographic record

VenueInternational Journal of Sustainable Development and Planning · 2025
Typearticle
Languageen
FieldEnvironmental Science
TopicSustainable Development and Environmental Policy
Canadian institutionsnot available
Fundersnot available
KeywordsEcotourismSustainable developmentProcess (computing)EcologyAnalytic network processEnvironmental resource managementBusinessEnvironmental scienceEconomicsGeographyTourismComputer scienceBiologyAnalytic hierarchy process

Abstract

fetched live from OpenAlex

Sustainable ecotourism development requires balancing ecological, economic, and community interests; however, integrated prioritization frameworks remain underdeveloped, particularly in emerging regions.Addressing this gap, this study employs the Analytic Network Process (ANP) to evaluate and rank sustainable ecotourism strategies in North Aceh, Indonesia.Data were collected from 12 key stakeholders, including government officials, academics, and community leaders, through structured pairwise comparisons based on a developed ANP model comprising three clusters and nine sub-strategies.Consistency ratios were verified, and Super Decisions software was utilized for limit matrix convergence.Results indicate that Community-Based Ecotourism Development is the top priority (global priority = 0.188401), followed by Economic Empowerment and Social Equity (0.141022), Technology-Based Ecotourism Development and Environmental Management (0.126867), while Ecotourism Digitalization ranked lowest (0.009748).Sensitivity analysis confirmed the robustness of these rankings.The findings offer actionable insights for policymakers and stakeholders, providing a replicable and adaptable framework for sustainable ecotourism planning in regions with similar socio-ecological dynamics, thus contributing to achieving SDGs 8, 12, and 15.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.444
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.011
GPT teacher head0.274
Teacher spread0.263 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2025
Admission routes1
Has abstractyes

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