A New Decision Support System for Enhancing Tourism Destination Management and Competitiveness

Abstract

The feedback provided by tourists is a key factor in the success of any tourist destination, as it serves as an indicator of the level of satisfaction with various aspects of their stay. This paper introduces a new decision support system designed to assist stakeholders of tourist destinations in making informed decisions regarding amenities and activities. It focuses on various aspects such as location, room quality, as well as the quality of the experience and safety related to those amenities and activities. These decisions are crucial for maintaining the competitiveness of the destination and attracting more visitors. The proposed system utilizes two widely used Natural Language Processing (NLP) tasks, namely, text classification for aspect recognition and sentiment analysis to evaluate tourists' satisfaction with that aspect. To address these two NLP tasks, we propose a model based on fine-tuning the Roberta model and an annotated dataset containing comments from tourists. To demonstrate the effectiveness of our proposed method, we present a case study in which we apply our system to the Merzouga destination in the Draa Tafilalet region.