Examining the sentiments of online consumer reviews and managerial responses of hotels using a dyadic data analytics approach

Hotels in Malaysia face a stiff competition among each other and the way to retain and improve their competitive advantage is through offering excellent service quality to customers. There is a significant knock-on effect from offering quality services to customers and this is in the form of a great customer satisfaction. A great customer satisfaction reflects on better overall customer experience and subsequently results in customer loyalty. This concept is crucial in the world of electronic word of mouth (eWOM) as reviewers actively leave online remarks on travel portals to express their feelings. The concern is on the negative reviews because they can affect the mind sets of future customers. Hotels must ensure that they pay attention on this area as a big part of what constitutes to a good customer experience is in how well the issues that they bring up are addressed by hoteliers. Therefore, this exploratory study aims to seek insights on the extent that hoteliers in Kuala Lumpur are utilizing the online user reviews that are posted on the renowned travel portal TripAdvisor in managing their service quality. The term dyadic data is used to refer to the data sets that contain interactions between customers and hoteliers and their relationship is based on Stimulus-Response framework. The dyadic data sets contain 777 online reviews and 777 online responses that are scraped by using Web Scraper tool from Chrome extension. They are pre-processed with SAS Enterprise Text Miner sofware, analyzed for Sentiments through Microsoft Power Business Intelligence (Power BI) and then tested for correlations via SPSS Pearson correlation test. Findings from this exploratory research help hoteliers to recognize the trends of online consumer reviews and evaluate the quality of their response strategy to negative reviews. The study also reveals that there exists a significant moderate positive correlation between the online dyadic data. Therefore, hoteliers must seek to improvise on their ways of addressing to the issues raised by customers in the online reviews to improve their service quality and customer satisfaction. Key words: Dyadic data, online customer reviews, managerial responses, stimulus-response, sentiment analysis, customer satisfaction, service qualit