Location
260-092, Owen G. Glenn Building
Start Date
12-15-2014
Description
This research attempts to understand user adoption of fashionable technologies (e.g., iPhone or iPad) and the influence of fashion waves on adopters of both fashionable and non-fashionable technologies. A research model was developed based on the regret theory. We tested the model by examining 20,122 customer reviews collected from Amazon.com. A theory-driven naïve Bayes classifier was developed to analyze the regret elements of customer reviews automatically. The data largely supported the research model. Specifically, we found that adopters of non-fashionable phones experience higher levels of regret and lower satisfaction during the fashion wave, i.e., when a new fashionable phone was released. In contrast, adopters of earlier editions of fashionable phones welcomed the new fashionable phone, displaying lower levels of regret and higher satisfaction during the fashion wave period. The findings have significant implications for information systems research and practices.
Recommended Citation
Sun, Heshan; Luo, Feng; London, Jake; and Jiao, Xiong, "Fashionable Technology, Fashion Waves, and Post-Adoption Regret and Satisfaction" (2014). ICIS 2014 Proceedings. 54.
https://aisel.aisnet.org/icis2014/proceedings/HumanBehavior/54
Fashionable Technology, Fashion Waves, and Post-Adoption Regret and Satisfaction
260-092, Owen G. Glenn Building
This research attempts to understand user adoption of fashionable technologies (e.g., iPhone or iPad) and the influence of fashion waves on adopters of both fashionable and non-fashionable technologies. A research model was developed based on the regret theory. We tested the model by examining 20,122 customer reviews collected from Amazon.com. A theory-driven naïve Bayes classifier was developed to analyze the regret elements of customer reviews automatically. The data largely supported the research model. Specifically, we found that adopters of non-fashionable phones experience higher levels of regret and lower satisfaction during the fashion wave, i.e., when a new fashionable phone was released. In contrast, adopters of earlier editions of fashionable phones welcomed the new fashionable phone, displaying lower levels of regret and higher satisfaction during the fashion wave period. The findings have significant implications for information systems research and practices.