Exploring the Ramifications of Unorganized Tourism Practices and Associated Challenges in the Sikkim Himalayas Through Machine Learning Approach

Abstract

Sikkim Himalayas serves as a prominent destination for tourists from across the globe, who come to experience its natural beauty and cultural heritage. However, prolific tourism activities without proper planning and management have led to numerous challenges in the region. This study aims to explore the ramifications of unorganized tourism practices and associated challenges in Sikkim Himalayas, based on extensive data and information collected through machine learning. Feature engineering involves extracting meaningful information from raw data to make accurate predictions or decisions. Our findings reveal that unregulated tourism activities have led to environmental degradation, ecological imbalances, cultural erosion, and over-exhaustion of resources in the region. Furthermore, the lack of a coordinated approach to tourism planning and management has contributed to inadequate infrastructure, poor sanitation, and unchecked social and economic disparities. The study also highlights the challenges faced by local communities, who bear the brunt of such unorganized tourism practices, including displacement, loss of traditional livelihoods, and marginalization. The study emphasizes the urgent need for a sustainable tourism framework that promotes responsible tourism practices, local community involvement in decision-making, and conservation efforts to protect the environment and cultural heritage of the Sikkim Himalayas. The findings of this study can serve as an important input for policymakers, tourism planners, and researchers to develop sustainable tourism practices that balance economic development with environmental and social well-being.