Examining the Effect of Positive Online Reviews on Consumers' Decision Making

Abstract

Online reviews play an important role in consumers' decision making. However, limited studies have been conducted to understand the effects of online reviews on consumers' behavior. Drawing upon the Elaboration Likelihood Model and the valence framework, a research model was developed to investigate the perceived benefits and potential risks brought by positive online reviews. The moderating effect of review skepticism was also examined. Data were collected through on online survey based on consumers' perceptions of the positive reviews from restaurants and food businesses and analyzed with partial least squares. The results indicated that argument quality and source credibility influence information usefulness, which further influences consumers' behavioral intentions. The influence of positive online reviews on perceived risk differs between high and low skepticism consumers. This research offers a more in-depth understanding of consumer information processing in an online context and benefits practitioners by allowing them to better understand consumers.

Examining the antecedents of everyday rumor retransmission

“…Our study considers argument quality instead of argument ambiguity. Prior studies have argued that argument quality or strength determines the receiver's perceptions of information credibility (Li and Suh, 2015;Thomas et al, 2019) and usefulness (Ha and Ahn, 2011;Xiao and Li, 2019). We posit that an everyday rumor that has a definite, complete, and accurate argument but is still factoid information will be more persuasive and more likely to be perceived as trustworthy by the receiver.…”

How Far Can the Message Go Through Online Communication

“…This research engages a programming technique via Haskell language to compose a simulation model to model the peer-to-peer communication and rule out the causality by setting different bands of value in parameters. In the simulated communication system, each agent performs its' role to fulfil the demand of information seeking and simultaneously plays as the information source to influence others through connection and persuasion, for example in the research of Xiao and Li (2019) and Meng (2022).…”

“…The first grounding of this paper lies in the online information exchange (Treiblmaier and Chong, 2011) which is sophisticatedly embedded in an invisible social network, as a collection of characteristics, e.g., membership, relationship, commitment and reciprocity, shared value and practice, and collectivism (Wellman et al, 1996;Erickson, 1997;Ridings and Gefen, 2004;Olmos-Peñuela et al, 2014). Some studies have proposed conceptual frameworks (Mcmillan and Chavis, 1986;Koh and Kim, 2003;Xiao and Li, 2019) and measures (Koh and Kim, 2003;Blanchard, 2007) of sense of online community highlighting three factors: (1) personal identity or membership featured by a sense of belonging (Mcmillan and Chavis, 1986), ( 2) relational factor such as exchange support (Blanchard and Markus, 2002) or influence (Mcmillan and Chavis, 1986;Koh and Kim, 2003), and (3) group internalization inclusive of integration and fulfilment (Mcmillan and Chavis, 1986) and immersion (Koh and Kim, 2003).…”

Factors Influencing Chinese Online Health Service Use

“…Li et al (2018) developed a model based on the valence framework to explore users' health information seeking and sharing intention on social media. Xiao and Li (2019) developed a research model to investigate the perceived benefits and potential risks brought by positive online reviews. When people make decisions to use OHS, they are exposed to both negative valences in terms of perceived risks due to uncertainty and positive valences in terms of perceived value.…”