Chinese managers' career success networks: the impact of key tie characteristics on structure and interaction practices

Abstract

Structured personal interviews were conducted with 105 senior and mid-level Chinese male and female managers, in which each respondent provided information about their career success network (CSN) ties. Using this data, we tested hypotheses on: (1) the age composition of Chinese managers' CSNs; (2) the face-to-face interaction practices within Chinese managers' CSNs; and (3) the roles of tie sex composition and tie content (position-centred versus person-centred ties) in influencing the age composition of and interaction practices within Chinese managers' CSNs. The results demonstrated that both Chinese male and female managers, while generally preferring to form CSN ties with individuals who are older than themselves, are relatively more reluctant to include middle-aged or elder women in their CSN. The age of those included in the respondents' CSN was also influenced by tie content and whether the tie spans the organizational boundary. With respect to interaction practices within the CSN, tie content moderated the relationship between tie sex composition and interaction practice. Female managers' person-centred ties with men had significantly lower levels of interaction outside the workplace than person-centred ties composed of members of the same-sex. However, this difference was not exhibited in the case of position-centred ties. Interestingly, the reluctance to socialize with the opposite-sex exhibited by female managers did not appear to be shared by their male counterparts. The implications of these results for career success in China are discussed.

Keywords:

• age
• China
• interaction practices
• sex composition
• social networks

Acknowledgements

The two authors made equal contributions to this collaborative project. The School of Business at Queen's University in Canada provided financial support for the study. We are grateful to the participating individuals who gave so generously of their time. We also thank Christine Oliver for her valuable comments on our interview protocol and Janice Guo for her assistance in data collection and categorization.