Abstract
Increasingly, market-based job search institutions, such as employment agencies and ethnic media, are playing a more important role than migrant networks for low-skilled Chinese immigrants searching for jobs. We argue that two major factors are driving this trend: the diversification of Chinese immigrants’ provinces of origin, and the spatial diffusion of businesses in the United States owned by Chinese immigrants. We also identify some new niche jobs for Chinese immigrants and assess the extent to which this development is driven by China’s growing prosperity. We use data from multiple sources, including a survey of employment agencies in Manhattan’s Chinatown, job advertisements in Chinese-language newspapers, and information on Chinese immigrant hometown associations in the United States.
- © 2018 Russell Sage Foundation. Liang, Zai, and Bo Zhou. 2018. “The Rise of Market-Based Job Search Institutions and Job Niches for Low-Skilled Chinese Immigrants.” RSF: The Russell Sage Foundation Journal of the Social Sciences 4(1): 78–95. DOI: 10.7758/RSF.2018.4.1.05. The portion of the study using data from a survey of employment agencies in New York City’s Chinatown was supported by the Russell Sage Foundation (88-10-06), whose support is gratefully acknowledged. The 2004 Survey of Chinese Immigrants was supported by the National Institutes of Health (NIH) (R01 HD39720-0) and the Ford Foundation (1025-1056). We thank Jian Cao for assistance with historical data from Chinese newspapers and Feinuo Sun for gathering critical data on Chinese immigrant hometown associations in the United States. The authors also thank three anonymous reviewers and editors for very constructive comments and suggestions. Direct correspondence to: Zai Liang at zliang{at}albany.edu, Department of Sociology, State University of New York at Albany, Albany, NY 12222; and Bo Zhou at bzhou3{at}albany.edu.
Open Access Policy: RSF: The Russell Sage Foundation Journal of the Social Sciences is an open access journal. This article is published under a Creative Commons Attribution-NonCommercial-NoDerivs 3.0 Unported License.