Trialability, observability and risk reduction accelerating individual innovation adoption decisions
Author(s)
Hayes, Kathryn J
Eljiz, Kathy
Dadich, Ann
Fitzgerald, Janna-Anneke
Sloan, Terry
Griffith University Author(s)
Year published
2015
Metadata
Show full item recordAbstract
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 ...
View more >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.
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View more >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.
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Journal Title
Journal of Health Organization and Management
Volume
29
Issue
2
Subject
Biomedical and clinical sciences
Commerce, management, tourism and services
Business systems in context not elsewhere classified