An Organizational Learning Framework: From Intuition to Institution
Impact in
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- Journal
- Academy of Management Review
In The Last Decade
doi.org/10.5465/amr.1999.2202135 →Countries where authors are citing An Organizational Learning Framework: From Intuition to Institution
This map shows the geographic impact of An Organizational Learning Framework: From Intuition to Institution. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by An Organizational Learning Framework: From Intuition to Institution with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites An Organizational Learning Framework: From Intuition to Institution more than expected).
Fields of papers citing An Organizational Learning Framework: From Intuition to Institution
This network shows the impact of An Organizational Learning Framework: From Intuition to Institution. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the An Organizational Learning Framework: From Intuition to Institution.
About An Organizational Learning Framework: From Intuition to Institution
This paper, published in 1999, received 2.8k indexed citations . Written by Mary Crossan, Henry W. Lane and Roderick E. White covering the research area of Strategy and Management and Organizational Behavior and Human Resource Management. It is primarily cited by scholars working on Strategy and Management (1.6k citations), Organizational Behavior and Human Resource Management (972 citations), Communication (506 citations), Management of Technology and Innovation (453 citations) and Management Science and Operations Research (318 citations). Published in Academy of Management Review.
Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.
This paper is also available at doi.org/10.5465/amr.1999.2202135.