Online reviews, which are consumer-generated messages, play a vital role in the consumer decision making process especially prior to their purchase adoption (i.e., pre-usage). The objective of this research is to investigate the effects of two-sided online reviews’ contents affecting the consumers' attitudes at the pre-usage stage of a focal experience service. Contrary to one-sided reviews (i.e., only positive or negative information), two-sided reviews contain both positive and negative information about a product/service: Two-sided reviews are considered more informative. Extant studies make an important assumption that there is no information asymmetry between writer/source of two-sided reviews and consumers that read/receive it. Their implicit assumption is that the attitude of the writer/source of the two-sided review is completely transferred to the reader/receiver of the review. Given the subjective nature of two-sided online reviews for experience goods, we contend that such an assumption is flawed because transfer of personal experience in form of attitude towards a focal object/service to others is fraught with ambiguity and uncertainty that can mitigate the transfer. Drawing on ambivalence and prospect theories, our hypothesis states that: the anticipatory ambivalence of the receiver/reader based on a two-sided review content for a focal service is higher than the ambivalent attitude of the source/writer of the review who has already experienced the focal service. Our empirical study, consisting of 1492 subjects from Canada and the United States, supports our stated hypothesis. The implication of our finding is profound. It shows that the extant literature had underestimated the negative attitude of the receiver/reader of the online reviews in their investigation, which confound their findings. To that end, we provide future research direction and implications of our findings in practice. / Thesis / Doctor of Philosophy (PhD)
Identifer | oai:union.ndltd.org:mcmaster.ca/oai:macsphere.mcmaster.ca:11375/28956 |
Date | January 2023 |
Creators | Akgul, Mehmet |
Contributors | Montazemi, Ali Reza, Business Administration |
Source Sets | McMaster University |
Language | English |
Detected Language | English |
Type | Thesis |
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