Understand customer satisfaction through customer online reviews of online food delivery apps

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School of Business | Master's thesis
Degree programme
Information and Service Management (ISM)
​Online food delivery (OFD) industry has recently gained popularity, especially after the onset of the COVID-19 pandemic. Like other service businesses, customer satisfaction plays a crucial role in the success of OFD companies. Online reviews, through which customers nowadays express their opinions about products or services, have recently been used to examine customer satisfaction in both academia and business world. However, there is limited research on this topic in the context of OFD. This study aims to understand OFD customer satisfaction via online reviews by examining more than 24000 online reviews from Apple App Store and Google Play Store of two OFD services that operate mainly in Europe. ​In this study, various natural language processing methods and Latent Dirichlet Allocation topic modeling method were used to process data and operationalize variables. Drawing on the definition of customer satisfaction in the extant literature, a customer satisfaction conceptual model, that investigates the effects of review subjectivity, and negative emotions (sadness, disgust, and anger) on review ratings, was developed and tested by multiple linear regression. Those effects on review ratings are also examined across review topics. ​The results reveal that negative emotions (sadness, disgust, and anger) are negatively associated with review ratings. Reviews written in a more subjective manner have higher numeric ratings; however, negative emotions moderate this effect. In addition, the degrees of these effects vary across different review topics, unveiling the role of review topics in impacting review ratings. These findings help enhance our understanding of the role of subjectivity, negative emotions, and review topics in online reviews with respect to OFD customer satisfaction management. However, it still requires caution when generalizing the findings to other contexts. ​This study expands on earlier research efforts regarding online reviews and customer satisfaction by introducing a customer satisfaction conceptual model that uses both subjectivity and emotional aspects of the textual reviews to explain review ratings. Moreover, this research offers vital insights and suggests beneficial practical recommendations for OFD businesses to improve their services and ensure customer satisfaction. This study also contributes to the groundwork for future research that establishes a more sophisticated customer satisfaction framework, examines OFD aspects across regions and cultures, and performs competitor benchmarking.
Thesis advisor
Liu, Yong
customer satisfaction, online reviews, online food delivery, text mining
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