Online reviews have become ubiquitous in modern day business environment. They shape consumer perception regarding a product or service, and thereby affect sales and profits of a business. Extant work on online review influence has investigated mechanisms by which a review may affect consumers’ decisions. The studies, however, have ignored the possibility of a change in the impact of drivers of influence over time, as more reviews are posted. This study attempts to bridge the gap. Drawing from elaboration likelihood model (ELM) and Simon’s theory of bounded rationality, hypotheses regarding temporal changes in the impact of drivers of influence have been proposed. The hypotheses have been tested based on online review data from Yelp.com. Additionally, in this study, it has been recognized that the gap or difference between review content being created and that needed by consumers to support decisions is more important than an understanding of the latter alone. Therefore, a set of hypotheses have been proposed regarding changes in review content characteristics over time, tested over the same dataset, and compared with the findings on temporal changes in the impact of drivers of review influence. The insights from this study have important implications for both theory and practice and have been discussed.
Bagheri, Seyedehsaba and Ridley, Gail, "Organisational Cyber Resilience: research opportunities" (2017). ACIS 2017 Proceedings. 102.