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dc.contributor.authorÜlker, Bengisu
dc.contributor.authorLim, Sigurd
dc.date.accessioned2022-08-26T07:16:43Z
dc.date.available2022-08-26T07:16:43Z
dc.date.issued2022
dc.identifier.urihttps://hdl.handle.net/11250/3013690
dc.description.abstractIn this thesis, the aim is to investigate the effect of numerical values and words on the consumer decision process. Previous research has studied the effect of online rating and review systems and how they influence consumer behavior and purchase decisions. While some studies have argued that reviews have a greater impact on users, others have argued that rating scores are more important. The main purpose of this study is to question whether participants are more affected by numerical data. In order to understand this relationship, an online experiment was conducted to analyze people’s preference on numeral ratings and written reviews and how these two elements in a website affect their behavior. The online experiment with a survey was conducted on 303 participants, mainly NHH students. We tested three types of products: books (Goodreads), restaurants (TripAdvisor) and coffee machines (Amazon). Two dummy pages were created for each product type, one of them had high numerical rating and negative written reviews, the other one had low numerical rating and positive written reviews. Instead of showing all three categories to the participants, they were shown two of them. Results illustrate that participants prefer the combination of low numerical rating and positive written reviews rather than the combination of high numerical rating and negative reviews. In addition, participants that preferred high numerical rating and negative reviews had higher level of confidence than the other group. Furthermore, we present a nuanced discussion based on the presented results and findings.en_US
dc.language.isoengen_US
dc.subjectbusiness analyticsen_US
dc.subjectmarketing and brand managementen_US
dc.titleOnline Ratings and Reviews: Are numerical ratings more persuasive than written reviews?en_US
dc.typeMaster thesisen_US
dc.description.localcodenhhmasen_US


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