Earticle

초록

영어

Over the past decade, the hotel industry has made significant strides in environmental sustainability by implementing eco-friendly practices such as water and energy conservation, recycling, and air quality preservation. This study uses online reviews as the primary data source to explore key factors influencing customer satisfaction and experiences in eco-friendly hotels in Nepal. A total of 16,794 reviews were collected from the top 13 eco-friendly hotels via Google.com using an instant data scraper. After filtering and processing, 7,899 relevant words were analyzed using text mining and semantic network analysis. The frequency analysis of the 100 most common words highlighted essential aspects of guest satisfaction, such as excellent service, quality amenities, nature, and peaceful environments, priorities frequently mentioned in guest feedback. Keyword visualization revealed that central terms like place, room, staff, and service were key hubs shaping customer perceptions. The CONCOR analysis identified four main clusters: outdoor adventure, guest experience, location, and hotel facilities, providing insight into what customers value most during their stays. Findings showed that scenic locations, opportunities for outdoor adventure, and high-quality facilities significantly enhance guest satisfaction in Nepalese eco-friendly hotels. At the same time, the study demonstrates a slowly growing preference for sustainable tourism, reflected by frequent mentions of terms like eco, nature, park, and green. This study's reliance on a single data source (Google.com) poses a limitation. Additionally, anonymous reviews may introduce bias through fake or manipulated content. Nonetheless, eco-friendly hotels can better meet guest expectations and support environmentally conscious tourism by focusing on sustainability and enhancing service quality.

목차

ABSTRACT
Ⅰ. Introduction
Ⅱ. Literature Review
2.1 Eco-Friendly Hotel
2.2 Customer Experience and Satisfaction in Eco-Friendly Hotels
2.3 The Role of Electronic Word of Mouth (eWOM) on Hotels
2.4 Text Mining and Semantic Network Analysis
Ⅲ. Methodology
3.1. Sample Design and Data Collection
3.2 Data Analysis
Ⅳ. Result
4.1 Frequency Analysis
4.2 Semantic Network Analysis
Ⅴ. Conclusion and Discussion
5.1 Practical and Academic Implications
5.2 Limitation
References

저자

• Thaman Khattri [ Master Student, Department of Global Hospitality Management, Kyungsung University ]
• Chawahang Yamphu [ Master Student, Department of Global Hospitality Management, Kyungsung University ]
• Hyun-Jeong Ban [ Assistant Professor, School of Global Studies, Kyungsung University ] Corresponding Author

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