Analyzing the labor market and salary determinants for big data talent based on job advertisements in China

Yingjie Lu, Hong Tuo, Haoyi Fan and Haiying Yuan

PLOS ONE, 2025, vol. 20, issue 2, 1-22

Abstract: The demand for big data talent is rapidly increasing with the growth of the big data industry. However, there has been limited research on what employers seek in recruiting big data talent. This paper aims to apply labor market segmentation theories to the big data labor market and develop a theoretical framework to analyze the distribution of big data talent in different labor market segments. Furthermore, we develop a salary determination model to explain wage differentials. An empirical analysis is conducted using online job advertisements from a Chinese recruitment website to investigate the labor market for big data talent in China. Our findings show that there are significant differences in the demand for big data talent across different types of cities and industries. Different types of enterprises have different requirements for individual characteristics and offer various levels of big data job positions. Furthermore, our results reveal that individual, job-related and organizational characteristics are all significant predictors of salaries. These findings can provide particularly useful insights for organizations and managers in the big data industry.

Date: 2025
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Persistent link: https://EconPapers.repec.org/RePEc:plo:pone00:0317189

DOI: 10.1371/journal.pone.0317189

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