Determinants of adoption of mobile health services. Issue 4 (10th August 2015)

• Record Type: Journal Article
• Authors: Lee, Euehun; Han, Semi
• Is Part Of: Online information review. Volume 39:Issue 4(2015)
• Page Start: 556
• Page End: 573
• Publication Date: 2015-08-10
• Subjects: 025.04
• DOI: 10.1108/OIR-01-2015-0007
• Languages: English
• ISSNs: 1468-4527

Abstract

<abstract> <title> <x content-type="archive" xml:space="preserve">Abstract</x> </title> <sec> <title content-type="abstract-heading">Purpose</title> <p> – The purpose of this paper is to explore the mobile health adoption behaviour of potential adopters and to provide guidelines for mobile health success. This study applied both health behaviour and consumer value research and developed an integrated research model to encourage mobile health adoption. </p> </sec> <sec> <title content-type="abstract-heading">Design/methodology/approach</title> <p> – The authors contacted about 1, 800 potential respondents living in Seoul, Korea. The authors used stratified sampling to choose sampling areas and quota sampling to select the final sampling unit. A total of 550 interviews were conducted, and the data were analysed using a structural equation modelling technique with linear structural relations. </p> </sec> <sec> <title content-type="abstract-heading">Findings</title> <p> – The results demonstrate that usefulness, convenience and monetary values of mobile health positively influence adoption intention. Convenience and monetary values are strongly perceived by individuals who have experienced illness, but the effect of illness experiences on the usefulness value is insignificant. Gender, age and income do not influence adoption intention. </p> </sec> <sec> <title content-type="abstract-heading">Originality/value</title> <p> – There is no research yet studies mobile health adoption behaviour in the integrated view of consumer value and the health service research. This integrated adoption model of mobile health can be a response of the calls to develop the mobile health adoption model adapted to the health context and to identify added predictors of the mobile health adoption.</p> </sec> </abstract>