The Operational Impact of Organizational Communities of Practice: A Bayesian Approach to Analyzing Organizational Change
Organizations are increasingly making use of communities of practice (CoPs) as a way of leveraging the dispersed knowledge and expertise of their employees. One important way in which CoPs are predicted to benefit organizations is by facilitating the transfer of best practices. In this study, we exa...
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curtin-20.500.11937-112682017-09-13T14:55:04Z The Operational Impact of Organizational Communities of Practice: A Bayesian Approach to Analyzing Organizational Change Cordery, John Cripps, E. Gibson, C. Soo, C. Kirkman, B. Mathieu, J. Organizations are increasingly making use of communities of practice (CoPs) as a way of leveraging the dispersed knowledge and expertise of their employees. One important way in which CoPs are predicted to benefit organizations is by facilitating the transfer of best practices. In this study, we examined the impact of the introduction of global CoPs on changes made to operational procedures in three refineries operated by a multinational company over a period of more than 5 years. We used a Bayesian change point detection model to assess the probability that changes in the rate of adoption of new and revised operational procedures occurred following the introduction of CoPs. The results confirmed our predictions, providing support for the idea that CoPs benefit organizations by contributing to the development of better operational routines and demonstrating the utility of Bayesian techniques for assessing the impact of complex organizational change 2015 Journal Article http://hdl.handle.net/20.500.11937/11268 10.1177/0149206314545087 restricted |
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Digital Repository |
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Local University |
institution |
Curtin University Malaysia |
building |
Curtin Institutional Repository |
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Online Access |
description |
Organizations are increasingly making use of communities of practice (CoPs) as a way of leveraging the dispersed knowledge and expertise of their employees. One important way in which CoPs are predicted to benefit organizations is by facilitating the transfer of best practices. In this study, we examined the impact of the introduction of global CoPs on changes made to operational procedures in three refineries operated by a multinational company over a period of more than 5 years. We used a Bayesian change point detection model to assess the probability that changes in the rate of adoption of new and revised operational procedures occurred following the introduction of CoPs. The results confirmed our predictions, providing support for the idea that CoPs benefit organizations by contributing to the development of better operational routines and demonstrating the utility of Bayesian techniques for assessing the impact of complex organizational change |
format |
Journal Article |
author |
Cordery, John Cripps, E. Gibson, C. Soo, C. Kirkman, B. Mathieu, J. |
spellingShingle |
Cordery, John Cripps, E. Gibson, C. Soo, C. Kirkman, B. Mathieu, J. The Operational Impact of Organizational Communities of Practice: A Bayesian Approach to Analyzing Organizational Change |
author_facet |
Cordery, John Cripps, E. Gibson, C. Soo, C. Kirkman, B. Mathieu, J. |
author_sort |
Cordery, John |
title |
The Operational Impact of Organizational Communities of Practice: A Bayesian Approach to Analyzing Organizational Change |
title_short |
The Operational Impact of Organizational Communities of Practice: A Bayesian Approach to Analyzing Organizational Change |
title_full |
The Operational Impact of Organizational Communities of Practice: A Bayesian Approach to Analyzing Organizational Change |
title_fullStr |
The Operational Impact of Organizational Communities of Practice: A Bayesian Approach to Analyzing Organizational Change |
title_full_unstemmed |
The Operational Impact of Organizational Communities of Practice: A Bayesian Approach to Analyzing Organizational Change |
title_sort |
operational impact of organizational communities of practice: a bayesian approach to analyzing organizational change |
publishDate |
2015 |
url |
http://hdl.handle.net/20.500.11937/11268 |
first_indexed |
2018-09-06T18:50:33Z |
last_indexed |
2018-09-06T18:50:33Z |
_version_ |
1610885190937214976 |