Ugly Duckling No More: Pasts and Futures of Organizational Learning Research
Anne S. Miner and
Stephen J. Mezias
Additional contact information
Anne S. Miner: School of Business, University of Wisconsin-Madison, 975 University Avenue, Madison, Wisconsin 53716-1323
Stephen J. Mezias: Leonard N. Stern School of Business, New York University, 44 West 4th Street, New York, New York 10012-1126
Organization Science, 1996, vol. 7, issue 1, 88-99
Abstract:
This article addresses theoretical and research frontiers for learning research, a second theme of Professor Argyris essay---the lead article in the “Crossroads” section. We outline three key theoretical questions for further work. We call for more systematic empirical learning research, suggesting that the paucity of such research may have resulted less from defensiveness than from the demanding requirements of doing crisp, systematic learning research. The need for scholarly empirical work is enhanced, we believe, by the growing popularity of organizational learning models among practitioners. Concurring with Professor Argyris' broad concern with enhancing research fruitfulness, we suggest ways to supplement traditional organizational research methods. In particular, we argue that it makes sense to cast wider nets for models of learning and adaptation, to sustain qualitative investigation, to use simulation techniques, and to maintain stronger---and perhaps even experimental---linkages between applied and theoretical research.
Date: 1996
References: Add references at CitEc
Citations: View citations in EconPapers (54)
Downloads: (external link)
http://dx.doi.org/10.1287/orsc.7.1.88 (application/pdf)
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:inm:ororsc:v:7:y:1996:i:1:p:88-99
Access Statistics for this article
More articles in Organization Science from INFORMS Contact information at EDIRC.
Bibliographic data for series maintained by Chris Asher ().