## 6 Conclusions
### Theoretical and Managerial Implications  
This article provides some theoretical contributions. First, this paper demonstrates the contribution of big data to innovative methods of examining consumer behavior in hotel management using UGC. This paper highlights that semantic analysis on big data can be implemented using available software and can be conducted in other research fields related to hospitality, such as consumer and employee satisfaction, hotel performance, spending patterns, etc. While the results of this paper are based on online reviews posted on a particular hotel website, they describes the way customers present their experiences in recommendations. Second, analyzing UGC offers scholars an innovative perspective on exploring consumer satisfaction that yields more accurate reports of consumers' experiences than survey methods, such as customer surveys or interviews, due to the open structure of the texts. Online reviews describe consumer perception more coherently and comprehensively compared to consumer ratings. Hotel guest reviews provide significant information for both customers and service providers. Consumers consider UGC as one of the most reliable data sources and use recommendations as a tool for making hotel booking decisions. On the other hand, service providers can use hotel guest recommendations to gather input from consumers and formulate and evaluate marketing strategies. Customer reviews offer updated and complete information and can be considered as an important communication channel between customers and hotel managers. Both positive and negative reviews affect possible consumers' attitudes about online hotel booking, since they impact the online transaction stages of both the information phase and the after-sales phase. From a practical perspective, this paper provides significant insights for hoteliers because the use of LSA offers an effective method for analyzing significant amounts of text. Hotel managers can often implement big data analysis to define the aspects of consumer satisfaction and dissatisfaction within a timeline. Hence, hotel managers can identify their hotels' performance and implement specific improvement actions dynamically. The hotel's success is not guaranteed if big data are used. Business analysts are required to transform complex data into valuable information. Thus, hotel managers should be aware of how big data can be used to create value and how they can be used to improve hotel performance and success. Hotel guest reviews provide meaningful knowledge to potential consumers that permit them to understand the services and facilities provided during their accommodation. The classification of hotel guest reviews into the following categories, namely, \"positive\", \"negative\", or \"neutral\", assists hotel managers in gaining a better understanding of consumer experiences and the factors that affect consumer satisfaction or dissatisfaction. Defining the factors of consumer satisfaction and dissatisfaction could support hoteliers to effectively use eWOM by conducting improvements to particular attributes of their services. To enhance consumer demand by enhancing satisfaction and reducing dissatisfaction, hotel managers should improve their products or services and understand consumers' concerns. Therefore, hotel managers may make better decisions regarding segmentation processes and marketing strategies if they have a better grasp of their customers' profiles, needs, and attitudes. This paper highlights that, in order to increase hotels' products and services, hoteliers should focus on improving operational performance characteristics, such as room quality and staff performance, as these aspects increase consumer satisfaction. Among the customer satisfaction factors, location was the essential factor which affected guest satisfaction. For future hotels, accessibility and hotel location have to be taken into consideration, as they are significant dimensions of consumer satisfaction.