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Defining Who You Are By What You're Not: Organizational Disidentification and The National Rifle Association

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  • Kimberly D. Elsbach

    (Graduate School of Management, University of California, Davis, California 95616)

  • C. B. Bhattacharya

    (School of Management, Boston University, 595 Commonwealth Avenue, Boston, Massachusetts 01915)

Abstract

Through two exploratory studies, we develop and test an introductory framework of “organizational disidentification.” Our first study explores the concept of organizational disidentification through a qualitative investigation of cognitive relationships with the National Rifle Association (NRA). Findings suggest that organizational disidentification is a self-perception based on: (1) a cognitive separation between one's identity and the organization's identity, and (2) a negative relational categorization of oneself and the organization (e.g., categorizations such as “rivals” or “enemies”). Organizational disidentification appears to be motivated by individuals' desires to both affirm positive distinctiveness and avoid negative distinctiveness by distancing themselves from incongruent values and negative stereotypes attributed to an organization. Our findings also suggest that organizational disidentification can lead individuals to take action (either volunteer work or voicing their opinion) as a result of their perceived separation from the organization's identity. Results of our second study”a large-scale survey of public attitudes about the NRA”provide support for this framework.

Suggested Citation

  • Kimberly D. Elsbach & C. B. Bhattacharya, 2001. "Defining Who You Are By What You're Not: Organizational Disidentification and The National Rifle Association," Organization Science, INFORMS, vol. 12(4), pages 393-413, August.
  • Handle: RePEc:inm:ororsc:v:12:y:2001:i:4:p:393-413
    DOI: 10.1287/orsc.12.4.393.10638
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    References listed on IDEAS

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    1. K. Jöreskog, 1971. "Statistical analysis of sets of congeneric tests," Psychometrika, Springer;The Psychometric Society, vol. 36(2), pages 109-133, June.
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