From signals to cues: A typology-based cognitive model of online review processing in peer-to-peer services

Despite an increasing reliance on online reviews in peer-to-peer service environments, limited research has explored how customers cognitively process reviews to inform decision-making. Understanding these mechanisms can enhance customers’ purchase confidence and improve review-based decision-making. This study examines which online reviews are helpful for decision-making through cognitive information processing. Grounded in signalling theory and the Elaboration Likelihood Model, the research adopts a qualitative approach through 20 in-depth interviews with space-sharing customers in South Korea. The analysis identifies six distinct review types: Guiding Positive, Balanced Positive, Exaggerated Positive, Selective Negative, Rational Negative, and Emotional Negative. The findings demonstrate a three-stage evaluation process (filtering, screening, selection) in which trustworthiness, credibility, and helpfulness served as evaluation standards. The signals in each review type serve as requirements that determine the elimination of low cost signals or transition into cues, ensuring that only helpful information supports decision-making. This study proposes an integrated model that combines two theories to illustrate the transition from visible signals to interpreted cues, providing the basis for evaluating online reviews. Strategic insights are also provided for peer-to-peer platform providers to enhance their management of customer purchase decision-making.