The aim of this degree project is to gain a deeper understanding of how online reviews affect consumers' purchase intentions when purchasing high-involvement products. Exploring the differences of effect between two separate generations of consumers, Generation Z and Millennials. The age intervals have been 18-41, 18-25 for Generation Z consumers and 26-41 for Millennials. This research is utilizing a deductive approach paired with a quantitative research strategy. The primary data collection method has been through an internet-based self-completed questionnaire, whereas the data later on has been analyzed. The analysis has been conducted through the Statistical Package for Social Sciences (SPSS) program allowing for the researchers to perform a series of statistical analyses. From the empirical findings and analysis conducted, it was concluded that all of the hypotheses were disproven and rejected, showing no significant difference. Through SPSS a series of independent sample t-tests were conducted to extract two means for the two generations. The statistical output displayed a higher level of impact on Millennials consumers contrary to the hypothesis, predicting Generation Z’s purchase intentions being significantly more impacted. Through SPSS the researcher have been able to compare how each generation compare against each other in terms of all the variables making up purchase intention (Involvement, Argument Quality, Source Credibility, Information Usefulness), but also performed t-tests to see how their answers differentiate in each question as well. This study could provide marketers with very insightful knowledge about how online reviews affect consumers differently, allowing for adaptation and optimizations.
Identifer | oai:union.ndltd.org:UPSALLA1/oai:DiVA.org:lnu-113831 |
Date | January 2022 |
Creators | Vu, Thi Mai Anh, Zeremichael, Simon, Wåhlberg, Sandra |
Publisher | Linnéuniversitetet, Institutionen för marknadsföring (MF) |
Source Sets | DiVA Archive at Upsalla University |
Language | English |
Detected Language | English |
Type | Student thesis, info:eu-repo/semantics/bachelorThesis, text |
Format | application/pdf |
Rights | info:eu-repo/semantics/openAccess |
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