The Staff Ride: An Approach to Qualitative Data Generation and Analysis

Wendy S. Becker, Shippensburg University, and Michael J. Burke, Tulane University, published “The Staff Ride: An Approach to Qualitative Data Generation and Analysis” on November 9th, 2011 in Organizational Research Methods OnlineFirst Section. To view the other OnlineFirst articles, please click here.

The abstract:

The authors present and illustrate the research staff ride—the re-creation of a historical event for the purpose of understanding organizational phenomena through observation, reflection, and discussion. Staff rides make unique contributions to research through the independent analysis of events outside organizations by content experts who collectively and concurrently reflect on retrospective data while experiencing context. Staff rides involve the examination of ordered sequences of contextually bound events and, thus, promote participants’ understanding of the dependence between past and future observations. In this article, the authors elaborate on the types of data, data collection procedures, and data analyses for research staff rides. Importantly, they discuss potential strengths and challenges associated with staff rides in qualitative research, along with ways to address these challenges.

To learn more about Organizational Research Methods, please follow this link.

Are you interested in receiving email alerts whenever a new issue or article becomes available online? Then click here.

Bookmark and Share

[polldaddy rating=”4667602″]
0 0 votes
Article Rating

Business & Management INK

Business and Management INK puts the spotlight on research published in our more than 100 management and business journals. We feature an inside view of the research that’s being published in top-tier SAGE journals by the authors themselves.

Subscribe
Notify of
guest

This site uses Akismet to reduce spam. Learn how your comment data is processed.

0 Comments
Inline Feedbacks
View all comments
0
Would love your thoughts, please comment.x
()
x