Edited by Timothy Clark, Mike Wright and David J. Ketchen Jr.
Chapter 15: When being normal is not enough: a few thoughts about data, analyses, and (the storm of) re-analyses
Good research is hard to do. Getting accepted for publication is harder still. So, when the editors of this book asked us to contribute a short chapter, we turned to Pooh and asked, “What should we write about?” Pooh mumbled something about honey, ice cream and being the perfect weight for a bear a foot taller than he was, and then sort of wandered off to worry about more important issues in the world of bears. This left us with only a few other personalities in our own heads with which to brainstorm ideas. After talking amongst (all of) ourselves, we decided to extol the virtues of not being entirely normal when it comes to data and analyses. A number of years ago, we published a meta-analysis (Stewart and Roth, 2001) on the relationship between entrepreneurial status and risk propensity (Pooh was not interested in that either). In short, we found that individuals who were entrepreneurs were more likely to have higher levels of risk propensity than were managers, a difference magnified if the entrepreneurs were growth-oriented. We were not terribly surprised when two researchers asked for our data (Eeyore did predict doom and gloom … ), but we were surprised when a rather “spirited” attack on our original meta-analysis appeared in the Journal of Applied Psychology (Miner and Raju, 2004). It was at this point that we were very glad that we were not entirely normal.
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