![]() A focus on food, menu offerings, ambiance, and service create buzz in social media. Three distinct types of clues – functional, mechanic, and humanic –explain a customer's overall perception of a dining experience that lead to satisfaction or dissatisfaction. After retrieving 2214 usable customer comments on, using a coded web spider, a series of both qualitative (e.g., tag clouds, word networks, and word trees were created using data visualization techniques) and quantitative (e.g., MANOVA) data analysis techniques were deployed to detect the satisfiers and dis-satisfiers of different types of restaurants. The aim of this research is to analyze online customer reviews for restaurants and underpin the restaurant satisfiers and nature of online restaurant reviews. Such techniques may help identifying the precursors of service satisfiers and dis-satisfiers of restaurants. The findings are also suggestive of the importance for hoteliers to continuously monitor the hugely available and easily accessible electronic guest feedback/electronic word of mouth (eWOM), that in the present electronic era, travels extremely fast, far and wide, critically influencing the image and sales of a hotel.Īnalyzing data from user-generated websites with data mining practices can suggest meaningful insights into services performances. The research concludes that in a highly competitive hotel business environment an insight into guest reviews is vital for hoteliers to lay out a road map for improving the various services on offer in an accommodation property. The results reveal that the 'room', 'staff', hotel 'transport connectivity', 'food', and 'proximity' to other shopping and eating outlets, are the main concerns addressed by guests either as 'compliments' or 'complaints' in their word-of-mouth feedback. The purpose of the study is to investigate the user-generated content of guests' hotel reviews available on TripAdvisor to identify the most scrutinized and discussed dimensions of a hotel by hotel guests. ![]()
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