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Cited by 434

The DOI matches its Crossref record; 68 of the 68 references it cites were found in a registry or an index.

Early identification of international executive potential.

Spreitzer, Gretchen M., McCall, Morgan W., Mahoney, Joan D.·1997·Journal of Applied Psychology

Abstract

This research extends the traditional approach to the early identification of executives by introducing the notion of ability to learn from experience. Drawing on the literature, the researchers created a reliable measurement tool named Prospector for rating the potential of aspiring international executives in terms of both end-state competencies and the ability to learn from experience. The 14 dimensions derived from the Prospector instrument are Sensitive to Cultural Differences, Business Knowledge, Courage, Brings Out the Best in People, Integrity, Insightful, Committed, Takes Risks, Seeks Feedback, Uses Feedback, Is Culturally Adventurous, Seeks Learning Opportunities, Open to Criticism, and Flexibility. The research also began to assess the validity of the Prospector dimensions in terms of current performance, executive potential, on-the-job learning, and international criteria on 838 lower, middle-, and senior-level managers from 6 international firms and 21 countries. The findings suggest that Prospector may have promise for use in the early identification of international executives.

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Metadata

Authors
Spreitzer, G. M., McCall, M. W., & Mahoney, J. D.
Venue
Journal of Applied Psychology
Published
1997-02
Volume
82
Issue
1
Pages
6-29
ISSN
  • 0021-9010 (ISSN-L)
  • 1939-1854
OpenAlex
W1990016617
Cited by
434
References
68
FWCI
33.58
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Early identification of international executive potential. https://app.cochat.ai/papers/10.1037/0021-9010.82.1.6
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Spreitzer, G. M., McCall, M. W., & Mahoney, J. D. (1997). Early identification of international executive potential. Journal of Applied Psychology. https://doi.org/10.1037/0021-9010.82.1.6

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.