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Rating valence versus rating distribution: perceived helpfulness of word of mouth in e-commerce
The success of e-commerce (EC) platforms depends heavily on word of mouth (WOM). Therefore, it is important to understand the characteristics of WOM, an aspect of consumer behavior, and using this knowledge to create customer experiences that helps the business to remain competitive. The factors tha...
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer International Publishing
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9533260/ https://www.ncbi.nlm.nih.gov/pubmed/36213378 http://dx.doi.org/10.1007/s43546-022-00338-8 |
Sumario: | The success of e-commerce (EC) platforms depends heavily on word of mouth (WOM). Therefore, it is important to understand the characteristics of WOM, an aspect of consumer behavior, and using this knowledge to create customer experiences that helps the business to remain competitive. The factors that influence consumer behavior are classified into four types: the amount of WOM, text characteristics, reviewer characteristics and valence. However, the perspective of rating distribution is missing. This information has been provided to consumers on major EC platforms to help them improve their product quality product quality. Previous research is limited because it is difficult to quantify the improvement in their judgments. Therefore, this study investigates the impact of rating valence and distribution of ratings for personal computers through a randomized controlled trial in an online survey environment. The results show that rating valence has a greater impact on purchase intention than rating distribution. However, rating distribution, which is polarized both positively and negatively, contributes to WOM intention to help. In addition, the polarized rating distribution has a positive impact on consumers who prefer online purchases but a negative impact on consumers who prefer offline purchases as it gives the impression of risk. Therefore, EC platform operators should consider rating distribution as a recommended product algorithm. |
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