Motivation and Emotion

, Volume 18, Issue 2, pp 129–166

Trust and commitment in the United States and Japan

  • Toshio Yamagishi
  • Midori Yamagishi
Article

DOI: 10.1007/BF02249397

Cite this article as:
Yamagishi, T. & Yamagishi, M. Motiv Emot (1994) 18: 129. doi:10.1007/BF02249397

Abstract

A distinction is proposed betweentrust as a cognitive bias in the evaluation of incomplete information about the (potential) interaction partner andassurance as a perception of the incentive structure that leads the interaction partner to act cooperatively. It is hypothesized that trust in this sense helps people to move out of mutually committed relations where the partner's cooperation is assured. Although commitment formation is a rather standard solution to the problems caused by social uncertainty, commitment becomes a liability rather than an asset as opportunity costs increase. Facing increasing opportunity costs, trust provides a springboard in the attempt to break psychological inertia that has been mobilized to maintain committed relations. In conjunction with an assumption that networks of mutually committed relations play a more prominent role in Japanese society than in American society, this hypothesis has been applied to predict a set of cross-national differences between the United States and Japan in the levels of trust and related factors. The results of a cross-national questionnaire survey (with 1,136 Japanese and 501 American respondents) support most of the predictions, and indicate that, in comparison to Japanese respondents, American respondents are more trusting of other people in general, consider reputation more important, and consider themselves more honest and fair. In contrast, Japanese respondents see more utility in dealing with others through personal relations.

Copyright information

© Plenum Publishing Corporation 1994

Authors and Affiliations

  • Toshio Yamagishi
    • 1
  • Midori Yamagishi
    • 2
  1. 1.Hokkaido UniversitySapporoJapan
  2. 2.Osaka International UniversityOsakaJapan

Personalised recommendations