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      Sell-Offs and Firm Performance: A Matter of Experience?

      1 , 2 , 3
      Journal of Management
      SAGE Publications

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          Abstract

          Drawing on organizational learning theory, this article examines the moderating influences of different forms of internal and external sell-off experience on the relationship between firm sell-off activity and subsequent firm accounting performance. The results from a longitudinal analysis of sell-off activity by 293 European companies over a 15-year period (1995-2009) are consistent with basic predictions from learning theory, suggesting a positive moderating influence of a firm’s general sell-off experience. Yet, by distinguishing between multiple forms of learning (i.e., experiential, superstitious, interfirm, and vicarious learning), we further argue and find that the composition of a firm’s general sell-off experience is of substantial importance. Specifically, we find that learning benefits result from the repeated sale of related assets, whereas high levels of experience heterogeneity negatively affect the relationship between firm sell-off activity and subsequent firm performance. Furthermore, external sell-off experience by advisors and by industry peers is found to positively influence the divestiture–firm performance linkage. Collectively, these findings contribute to organizational learning theory and extend prior research on divestiture performance.

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                Author and article information

                Journal
                Journal of Management
                Journal of Management
                SAGE Publications
                0149-2063
                1557-1211
                May 2017
                October 03 2014
                May 2017
                : 43
                : 5
                : 1359-1387
                Affiliations
                [1 ]University of Mannheim
                [2 ]University of Erlangen-Nuremberg
                [3 ]University of Geneva
                Article
                10.1177/0149206314552452
                3564ce50-25cb-41ba-a173-f33c684687ce
                © 2017

                http://journals.sagepub.com/page/policies/text-and-data-mining-license

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