Sustainability of community-based mangrove ecotourism in Bali, Indonesi

Bali is a world tourist destination that is famous for having various types of interesting maritime tourism, including mangrove areas which are typical of equatorial regions. The purpose of this study is to develop a model that can predict the sustainability of ecotourism in the mangrove area in Bali based on the approach of empowering local potential and empowering the community. Data analysis was carried out using Bayesian Network analysis, where input was based on the results of the FGD. The results show high probability of realizing the sustainability of ecotourism, where the most influential variables are community participation and local product developers or mangrove-based products. In addition, the condition of the mangrove forest also needs attention, considering that the sustainability of mangrove ecotourism is very sensitive to changes in the condition of the mangrove forest. The three main variables have reflected the combination of the three elements of sustainability, namely people-social (community participation), planet-environment (mangrove forest condition), and profit-economic (developing of mangrove-based products). Mangrove ecotourism development in Bali should be focused on increasing community participation and the development of mangrove-based products.

Authors

Publication Details

Journal
Decision Science Letters
Published
2025-01-01
DOI
https://doi.org/10.5267/j.dsl.2025.3.010
Citations
1
Primary Topic
Community-based Tourism Development and Sustainability
Type
article
Field-Weighted Citation Impact
4.20

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Sustainability of community-based mangrove ecotourism in Bali, Indonesi

Made Kembar Sri Budhi, Ni Nyoman Reni Suasih, I Nyoman Mahaendra Yasa, Ni Komang Ayu Rustini et al.
1 citations
Decision Science Letters
Community-based Tourism Development and Sustainability
4.20
article

Sustainability of community-based mangrove ecotourism in Bali, Indonesi

Made Kembar Sri Budhi, Ni Nyoman Reni Suasih, I Nyoman Mahaendra Yasa, Ni Komang Ayu Rustini, Ida Ayu Nyoman Saskara, Ni Putu Nina Eka Lestari, Ni Luh Tesi Riani
article en
1 citations

Abstract

Bali is a world tourist destination that is famous for having various types of interesting maritime tourism, including mangrove areas which are typical of equatorial regions. The purpose of this study is to develop a model that can predict the sustainability of ecotourism in the mangrove area in Bali based on the approach of empowering local potential and empowering the community. Data analysis was carried out using Bayesian Network analysis, where input was based on the results of the FGD. The results show high probability of realizing the sustainability of ecotourism, where the most influential variables are community participation and local product developers or mangrove-based products. In addition, the condition of the mangrove forest also needs attention, considering that the sustainability of mangrove ecotourism is very sensitive to changes in the condition of the mangrove forest. The three main variables have reflected the combination of the three elements of sustainability, namely people-social (community participation), planet-environment (mangrove forest condition), and profit-economic (developing of mangrove-based products). Mangrove ecotourism development in Bali should be focused on increasing community participation and the development of mangrove-based products.

Decision Science LettersVol. 14(3)
Universitas Udayana
Openalex Percentile: Top 8%
Community-based Tourism Development and Sustainability
4.20
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.