Trialability, observability and risk reduction accelerating individual innovation adoption decisions
- 13 April 2015
- journal article
- Published by Emerald in Journal of Health Organization and Management
- Vol. 29 (2), 271-294
- https://doi.org/10.1108/jhom-08-2013-0171
Abstract
Purpose – The purpose of this paper is to provide a retrospective analysis of computer simulation’s role in accelerating individual innovation adoption decisions. The process innovation examined is Lean Systems Thinking, and the organizational context is the imaging department of an Australian public hospital. Design/methodology/approach – Intrinsic case study methods including observation, interviews with radiology and emergency personnel about scheduling procedures, mapping patient appointment processes and document analysis were used over three years and then complemented with retrospective interviews with key hospital staff. The multiple data sources and methods were combined in a pragmatic and reflexive manner to explore an extreme case that provides potential to act as an instructive template for effective change. Findings – Computer simulation of process change ideas offered by staff to improve patient-flow accelerated the adoption of the process changes, largely because animated computer simulation permitted experimentation (trialability), provided observable predictions of change results (observability) and minimized perceived risk. Research limitations/implications – The difficulty of making accurate comparisons between time periods in a health care setting is acknowledged. Practical implications – This work has implications for policy, practice and theory, particularly for inducing the rapid diffusion of process innovations to address challenges facing health service organizations and national health systems. Originality/value – The research demonstrates the value of animated computer simulation in presenting the need for change, identifying options, and predicting change outcomes and is the first work to indicate the importance of trialability, observability and risk reduction in individual adoption decisions in health services.Keywords
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