Is Sharing Caring? : A Quantitative Study of Consumers Intention to Write Online Product Reviews.

Sammanfattning: Background: Electronic Word of Mouth (eWOM) is something that lately has gained increasing relevance and importance when it comes to consumers purchase decisions. Online reviews are considered to be the most important and reliable form of eWOM and it refers to when consumers communicate with other consumers online regarding their previous shopping experiences. In order to increase the generalizability and understanding of motives that influence consumers intention to write online reviews, authors of previous studies have suggested that future research should intend to focus on motives that influence intention to write online reviews in other contexts that are not aimed towards the service industry. Purpose: The purpose of this study is to explain how personal- and social motives influence consumers intention to write online product reviews. Methodology: For this explanatory study, a quantitative strategy with a cross-sectional research design were used in order to test the model founded on two major hypotheses. The data was gathered through a self-completed questionnaire with a sample of 222 respondents. Findings: In this study, two major hypotheses were conducted in order to explain how personal motives and social motives influence consumers intention to write online product reviews. After analysing the data that emerged from the survey, a conclusion can be drawn that the hypothesis concerning personal motives and its influence on consumers intention to write online product reviews was accepted whereas the hypothesis concerning social motives was rejected. Conclusion: In this study, it has been recommended that future studies should test the suggestions found in this study with a more diverse sample in order to increase the generalizability of the theoretical implications. Furthermore, directions for future research will also recommend testing the modified model that emerged in this paper in order to detect if there are any additions that need to be added to increase the predictability of the findings.