Abstract
Self-quantification technologies offer an unlimited number of opportunities for improving human life, especially in terms of health and well-being. Despite the growing adoption of these technologies worldwide and the increasing scholarly interest, the factors that influence the adoption of quantified self (QS) have only been slightly examined by past research. To close this gap, this research in-progress presents a literature review on the benefits and risks of QS practices and it develops a multidisciplinary research model based on the Extended Valence Framework. This model offers five hypotheses that highlight the importance of considering technological, social and health factors when measuring QS adoption. Data collection with QS users is ongoing. The paper concludes with the design of the research and the expected contributions.
Recommended Citation
De Moya, JF and Pallud, Jessie, "The Determinants of Quantified-Self Adoption: Towards the development of a Risk/Benefit Model" (2019). AMCIS 2019 Proceedings. 35.
https://aisel.aisnet.org/amcis2019/healthcare_it/healthcare_it/35
The Determinants of Quantified-Self Adoption: Towards the development of a Risk/Benefit Model
Self-quantification technologies offer an unlimited number of opportunities for improving human life, especially in terms of health and well-being. Despite the growing adoption of these technologies worldwide and the increasing scholarly interest, the factors that influence the adoption of quantified self (QS) have only been slightly examined by past research. To close this gap, this research in-progress presents a literature review on the benefits and risks of QS practices and it develops a multidisciplinary research model based on the Extended Valence Framework. This model offers five hypotheses that highlight the importance of considering technological, social and health factors when measuring QS adoption. Data collection with QS users is ongoing. The paper concludes with the design of the research and the expected contributions.