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Interpersonal Commitment: The Hidden Power of Face-to-Face Diplomacy.

  • Published In: International Studies Review, 2024, v. 26, n. 2. P. 1 1 of 3

  • Database: Academic Search Ultimate 2 of 3

  • Authored By: Heimann, Gadi; Kampf, Zohar 3 of 3

Abstract

This article argues that interpersonal commitment is statespersons' most highly coveted aim, the greatest benefit that interpersonal relations can yield in diplomacy. Accordingly, statespersons employ a range of relational practices in encounters with counterparts, seeking to create and harness commitment that will advance professional aims. We argue that statespersons can follow one of two paths to generate commitment: (1) creating feelings of gratitude and providing help that makes a counterpart feel indebted; or (2) cultivating friendly relations. Both demand the successful implementation of relational practices. On the basis of thirty semistructured interviews with past and present senior Israeli statespersons and an analysis of fifteen autobiographies written by senior Israeli diplomats and political figures, we demonstrate to what extent statespersons acknowledge the importance of interpersonal commitment and its ramifications; identify the relational practices that statespersons employ to elicit commitment from a counterpart; and discuss the conditions that facilitate the emergence of such a commitment. We conclude by discussing the differences between thin and thick interpersonal commitments and underlining the importance of interpersonal relations in diplomacy. [ABSTRACT FROM AUTHOR]

Additional Information

  • Source:International Studies Review. 2024/06, Vol. 26, Issue 2, p1
  • Document Type:Article
  • Subject Area:Psychology
  • Publication Date:2024
  • ISSN:1521-9488
  • DOI:10.1093/isr/viae021
  • Accession Number:177947329
  • Copyright Statement:Copyright of International Studies Review is the property of Oxford University Press / USA and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

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