Predicting Women's Involvement for Sustainable Tourism in the Local Economy: A Bayesian Network Approach

Abstract

This study aims to explore the main factors influencing women's involvement and analyze the interaction between variables to develop policy recommendations that enhance women's involvement in tourism sustainability in Penglipuran Village. This research will use prospective analysis methods, specifically MICMAC Analysis and Bayesian Belief Network (BBN). The study's results identified several potential variables affecting women's involvement, such as awig-awig, gender equality, women empowerment, infrastructure, customary institutions, skills, and culture. Additionally, the study discusses how managing five key nodes with a 100% probability led to a 20% increase in women’s engagement and a 5% increase in tourism sustainability. The findings of this study emphasize the crucial role of handling infrastructure and customary institutions supporting women's tourism involvement. Women are expected to have equal access to resources and opportunities, alongside promoting women’s empowerment.