Online Review Helpfulness: A Literature Review

Online Review Helpfulness: A Literature Review

Mehmet Akgul, Ali Reza Montazemi
Copyright: © 2025 |Pages: 16
DOI: 10.4018/978-1-6684-7366-5.ch055
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Online platforms, such as Yelp and TripAdvisor, have facilitated ubiquitous and convenient access to a large number of online reviews about almost any product/service. Hence, it is imperative to understand what makes a review helpful for the consumers to make a decision about the adoption of the focal product/service. Drawing on Berlo's sender-message-channel-receiver model, the authors identify factors affecting online review helpfulness from the extant literature. Such understanding is critical to the review platforms and organizations to mitigate review helpfulness.
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Although consumers have access to a vast number of reviews available on consumer review sites, weblogs, or social network sites, this also brings additional challenges and costs. It is not only time-consuming to find and read the reviews, but the amount of information also makes it difficult for the consumer to process and judge reviews as a result of the information load. Information load refers to “a complex mixture of the quantity, ambiguity and variety of information that people are forced to process. As load increases, people take increasingly strong steps to manage it” (Weick, 1995, p. 87). Roetzel (2019) modelled this information load and decision-making process as an inverted U curve, depicted in Figure 1. As shown in Figure 1, the decision-making performance (“the probability of achieving the best possible decision” (Roetzel, 2019, p.484)) increases as the information increases up to some point. After the optimal point, the performance decreases. This may happen according to two reasons: cognitive capacity constraints and resource capacity constraints.

Figure 1.

Information and decision-making performance (Roetzel, 2019)


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