Customer revisit intention to restaurants: Evidence from online reviews
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One of the generally recognized marketing principles is that retaining customers is more profitable than winning prospective customers. Therefore, how to retain existing customers and improve their repeat purchases is an important consideration for practitioners to gain profit. The purpose of this study is to investigate factors influencing customer revisit intention to restaurants by analyzing online reviews. We used regression analysis to analyze quantitative scores of 10,136 restaurant reviews collected from an online life community in China, and found that food quality, price and value, service quality, and atmosphere are the antecedents of restaurant customers’ revisit intention, and that restaurant type moderates the effect of customer satisfaction with service quality, atmosphere, and price and value on revisit intention. We also used text mining technology to identify detailed evaluation indicators in each dimension and explore customers’ evaluation behavior characteristics. We found that food quality and, price and value have four indicators while service quality and atmosphere have two indicators. The results are useful for restaurant operators to take effective actions to attract more customers to revisit.
KeywordsRevisit intention Customer satisfaction Online reviews Regression analysis Text mining
This work is partly supported by the National Natural Science Foundation of PRC (No. 71171067,71328103 and 70890082) and Postdoctoral Science-research Developmental Foundation of Heilongjiang province (No. LBH-Q11114).
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