The asymmetric effect of review valence on numerical rating
| Autor: | Yu Chun Ma, Hao-Chiang Koong Lin, Hsiu-Yuan Tsao, Ming-Yi Chen |
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| Rok vydání: | 2019 |
| Předmět: |
Exploit
media_common.quotation_subject 05 social sciences Sentiment analysis 02 engineering and technology Library and Information Sciences Computer Science Applications Consumer satisfaction Originality 020204 information systems 0502 economics and business 0202 electrical engineering electronic engineering information engineering Brand strength 050211 marketing Valence (psychology) Psychology Social psychology Practical implications Information Systems media_common |
| Zdroj: | Online Information Review. 43:283-300 |
| ISSN: | 1468-4527 |
| Popis: | PurposeThe basic assumption is that there is a symmetric relationship between review valence and rating, but what if review valence and rating were linked asymmetrically? There are few studies which have investigated the situations in which positive and negative online reviews exert different influences on ratings. This study considers brand strength as having an important moderating role because the average rating of existing reviews for a particular product is a heuristic cue for decision makers. Thus, the purpose of this paper is to argue that an asymmetric relationship between review content valence and numerical rating will depend on brand strength.Design/methodology/approachThe authors have conducted a sentiment analysis via text mining, using self-developed computer programs to retrieve a data set from the TripAdvisor website.FindingsThis study finds there is an asymmetric relationship between review valence (verbal) and numerical rating. The authors further find brand strength to have an important moderating role. For a stronger brand, negative review content will have a greater impact on numerical ratings than positive review content, while for a weaker brand, positive review content will have a greater impact on numerical ratings than negative review content.Practical implicationsMarketers could adopt sentiment analysis via text mining of online reviews as a valid measure or predictor of consumer satisfaction or numerical ratings. Strong brands should direct more attention to negative reviews, because in such reviews the negative impact transcends the positive. In contrast, weak brands should aim to exploit as many positive reviews as possible to minimize the impact of any negative reviews.Originality/valueThis study finds there is an asymmetric relationship between review valence (verbal) and numerical rating and considers brand strength to play an important moderating role. The authors have used real data from the TripAdvisor website, which allow people to express themselves in an unsolicited manner, and linked these with the results from the sentiment analysis. |
| Databáze: | OpenAIRE |
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