Article ID Journal Published Year Pages File Type
350345 Computers in Human Behavior 2015 17 Pages PDF
Abstract

•Adoption studies focus on technological drivers of use intention.•We examine user characteristics and lifestyle as additional drivers of cloud adoption.•Cloud non-adopters perceive high risk and low trialability/observability.•Cluster analysis reveals three lifestyles among cloud adopters and non-adopters.•Only one lifestyle group represents a “cloud lifestyle” and intends to adopt.

Sociology and modernist theories have long emphasized the central role of lifestyle in processes of self-identity and attitude formation. Furthermore, lifestyle has been used to great effect in marketing and health research to predict attitudes, cognitions, and behaviors, but has largely been ignored in the IS field. In this study, we demonstrate the potential usefulness of incorporating lifestyle into IS research by using lifestyle cluster segmentation in the context of technology adoption. Based on a U.S. national random sample of 402 non-cloud service users, we propose, analyze, and validate a multi-faceted model of cloud technology adoption that integrates technology attributes—the dominant predictors in IS adoption and acceptance models—with a range of demographic, domestic, leisurely and professional variables for providing a holistic theoretical understanding of and practical insights into the technology adoption process.

Related Topics
Physical Sciences and Engineering Computer Science Computer Science Applications
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