Location
260-092, Owen G. Glenn Building
Start Date
12-15-2014
Description
This study investigates how potential adopters of mobile applications utilize online review systems to inform their perceptions on the application’s technology characteristics and thus inform their eventual adoption decision. Informational cascades and herding behavior theories are combined with the Innovation Diffusion Model and the Theory of Planned Behavior (TPB) to develop a research model. The review characteristics of aggregate review valence, overall rating, and review volume are related to the perceived technology characteristics of relative advantage, compatibility, and complexity. These, in turn, use the TPB as a lens to tie it all to the behavioral intention to adopt the mobile application. An online survey yielded 448 responses for analysis. The results yield some important insights and raises new questions for future evaluation.
Recommended Citation
Liu, Fengkun and Brandyberry, Alan, "Exploring the Effects of Aggregate Review Characteristics on Mobile Application Adoption" (2014). ICIS 2014 Proceedings. 65.
https://aisel.aisnet.org/icis2014/proceedings/HumanBehavior/65
Exploring the Effects of Aggregate Review Characteristics on Mobile Application Adoption
260-092, Owen G. Glenn Building
This study investigates how potential adopters of mobile applications utilize online review systems to inform their perceptions on the application’s technology characteristics and thus inform their eventual adoption decision. Informational cascades and herding behavior theories are combined with the Innovation Diffusion Model and the Theory of Planned Behavior (TPB) to develop a research model. The review characteristics of aggregate review valence, overall rating, and review volume are related to the perceived technology characteristics of relative advantage, compatibility, and complexity. These, in turn, use the TPB as a lens to tie it all to the behavioral intention to adopt the mobile application. An online survey yielded 448 responses for analysis. The results yield some important insights and raises new questions for future evaluation.