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AI Written Works: Article Detail

When is Appreciative Inquiry Transformational? A Meta-Case Analysis
Author: Gervase Bushe , Aniq Khamisa

Academy of Management Conference Presentation 2004
Date: 01/01/2004


Annotation: Abstract
20 cases of the use of Appreciative Inquiry (AI) for changing social systems published before 2003 were examined to look for the presence or absence of transformational change and the utilization of 7 principles and practices culled from a review of the theoretical literature on AI.Though all cases began by collecting “stories of the positive”, followed the “4-D model” and adhered to 5 principles of AI articulated by Cooperrider & Whitney (2001), only 7 (35%) showed transformational outcomes.In 100% of cases with transformational outcomes, the appreciative inquiry resulted in new ideas and knowledge and a generative metaphor that transformed the accepted beliefs of system members.In none of the non transformational cases was new knowledge created and in one a generative metaphor emerged.Instead, non-transformational AI focused on changing existing organizational practices.In 83% of the transformational cases, the “destiny” or action phase of the appreciative inquiry was best characterized as “improvisational”.In contrast, 83% of the non transformational cases used more standard “implementation” approaches to the action phase in which attempts were made to implement centrally agreed upon targets and plans.The authors conclude that these two qualities of appreciative inquiry, a focus on changing how people think instead of what people do, and a focus on supporting self-organizing change processes that flow from new ideas rather than leading implementation of centrally or consensually agreed upon changes, appear to be key contributions of AI to the theory and practice of large systems change that merit further study and elaboration.

This paper is the only empirical assessment of AI published in a research journal and was the runner up for the Douglas McGregor memorial award in 2005.


Online Resources:
Article Online at Gervase Bushe's website

(submitted by aicommons@case.edu)

 
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