Soft data analytics with fuzzy cognitive maps: Modeling health technology adoption by elderly women

Noshad Rahimi, Antonie J. Jetter, Charles M. Weber, Katherine Wild

Research output: Chapter in Book/Report/Conference proceedingChapter

3 Scopus citations

Abstract

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.

Original languageEnglish (US)
Title of host publicationSmart Innovation, Systems and Technologies
PublisherSpringer Science and Business Media Deutschland GmbH
Pages59-74
Number of pages16
DOIs
StatePublished - Jan 1 2018

Publication series

NameSmart Innovation, Systems and Technologies
Volume93
ISSN (Print)2190-3018
ISSN (Electronic)2190-3026

ASJC Scopus subject areas

  • Decision Sciences(all)
  • Computer Science(all)

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    Rahimi, N., Jetter, A. J., Weber, C. M., & Wild, K. (2018). Soft data analytics with fuzzy cognitive maps: Modeling health technology adoption by elderly women. In Smart Innovation, Systems and Technologies (pp. 59-74). (Smart Innovation, Systems and Technologies; Vol. 93). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-3-319-77911-9_4