TY - CHAP
T1 - Soft data analytics with fuzzy cognitive maps
T2 - Modeling health technology adoption by elderly women
AU - Rahimi, Noshad
AU - Jetter, Antonie J.
AU - Weber, Charles M.
AU - Wild, Katherine
N1 - Publisher Copyright:
© 2018 by the Oncology Nursing Society.
PY - 2018
Y1 - 2018
N2 - Modeling how patients adopt personal health technology is a challenging problem: Decision-making processes are largely unknown, occur in complex, multi-stakeholder settings, and may play out differently for different products and users. To address this problem, this chapter develops a soft analytics approach, based on Fuzzy Cognitive Maps (FCM) that leads to adoption models that are specific for a particular product and group of adopters. Its empirical grounding is provided by a case study, in which a group of women decides whether to adopt a wearable remote healthcare monitoring device. The adoption model can simulate different product configurations and levels of support and provide insight as to what scenarios will most likely lead to successful adoption. The model can be used by product developers and rollout managers to support technology planning decisions.
AB - Modeling how patients adopt personal health technology is a challenging problem: Decision-making processes are largely unknown, occur in complex, multi-stakeholder settings, and may play out differently for different products and users. To address this problem, this chapter develops a soft analytics approach, based on Fuzzy Cognitive Maps (FCM) that leads to adoption models that are specific for a particular product and group of adopters. Its empirical grounding is provided by a case study, in which a group of women decides whether to adopt a wearable remote healthcare monitoring device. The adoption model can simulate different product configurations and levels of support and provide insight as to what scenarios will most likely lead to successful adoption. The model can be used by product developers and rollout managers to support technology planning decisions.
UR - http://www.scopus.com/inward/record.url?scp=85045897426&partnerID=8YFLogxK
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U2 - 10.1007/978-3-319-77911-9_4
DO - 10.1007/978-3-319-77911-9_4
M3 - Chapter
AN - SCOPUS:85045897426
T3 - Smart Innovation, Systems and Technologies
SP - 59
EP - 74
BT - Smart Innovation, Systems and Technologies
PB - Springer Science and Business Media Deutschland GmbH
ER -