Employee turnover of small and micro enterprises in China: Present situations, impacts and determinants

HUANG Yuhong1 Yi Daichun1 JIE Mengyin1

(1.China Household Finance Survey and Research Center, Southwestern University of Finance and Economics (SWUFE))

【Abstract】Based on the data of China Micro and Small Enterprise Survey (CMES), this paper introduced the management situation and present condition of the employee turnover in small and micro enterprises in China. It also analyzed the relationship between employee turnover and the management of small and micro enterprises as well as the main factors that influence employee turnover in small and micro enterprises. From data analysis, we found that an optimal level of employee turnover rate exists. Either overly low or overly high employee turnover was not conductive to the enterprise development. Secondly, a large number of small and micro enterprises did not have any employee turnover, demonstrating that the employees were of poor quality, complacency, and career stagnation. However, due to the lack of competitive compensation package as well as employee cultivation and incentive system, there would be relatively high talent risks in the enterprises with overly high employee turnover.

【Keywords】 small and micro enterprises; employee turnover; enterprise operation;


【Funds】 Supported by the key project of National Social Science Fund of China (14ZDB134)

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(Translated by MO Yingqi)


    [1]. (1) The data are from the website of National Business Research Institute (NBRI): https://www.nbrii.com/employee- survey- white- papers/survey-research-yields-data-on-employee-turnover/. [^Back]

    [2]. (2) Small and micro enterprises include legal entities and individual households of small and micro enterprises that meet the standards. This paper only studies legal entities of small and micro enterprise. [^Back]

    [3]. (3) CMES only asked the enterprises newly established in 2015 a few simple questions. Due to the lack of relevant information, these enterprises were excluded in this paper. Secondly, considering that sampling error existed at the preliminary stage of collecting the samples of small and micro enterprises, and that there was inconsistency of the answers from the respondents on enterprise assets, business income and employee scale in formal investigation and in the sampling stage, this paper further screened out enterprises not conform with sizing standards based on the Standard Requirements of Small and Medium-sized Enterprises. [^Back]

    [4]. (4) The number of new employees recruited from June 2014 to the survey time was asked on the CMES questionnaire. [^Back]

    [5]. (5) Since the employee turnover rate varies significantly among different industries, the excluded enterprises may be limited to a certain industry. To avoid this problem, this paper compared the industrial distribution of rejected samples and retained samples. Thereafter, we did not find existing problem that the rejected samples were obviously limited to a certain industry. Taking the manufacturing industry as an example, of the rejected samples, 29.6% were manufacturing industry, while of the retained samples, the percentage was 29.7%. [^Back]

    [6]. (6) The intuitive way to validate the inverted U-shaped influence of employee turnover on enterprise operation is to set the resignation rate and the quadratic term. However, the statistics employed by this paper show that 50.4% of small and micro enterprises did not have employee resignation, resulting to the deviated distribution of the data, demonstrating that a large number of enterprises have zero turnover rate. Another approach is to take the enterprises with resignation rate as samples only, which however, will lead to few research samples. If we subdivide the employees into regular and non-regular staff, or enterprises into small ones and micro-enterprises, there will be fewer samples. [^Back]

    [7]. (7) Taking the simple linear regression as an example, y=β1x12x1x2+ε, where x1 represents “whether to resign,” x2 means “resignation rate” and x1x2 is the cross term of “whether to resign” and “resignation rate.” After taking the derivative of y to x1, we can get β12x2. To calculate the optimal resignation rate, we need to make the formula equal to 0. Then x2=−β12. Although the marginal effect of linear model differs by(∂P(y=1|x))(/ ∂(xβ))from that of the Logit model, compared to the marginal effect of x1 and x2, in fact it is equal to the ratio of coefficient of linear model since the molecular and denominator include the number of terms simultaneously. [^Back]


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This Article


CN: 11-1235/F

Vol , No. 12, Pages 77-89

December 2016


Article Outline


  • 1 Introduction
  • 2 Data source and definition of employee turnover
  • 3 Status quo of operation and employee turnover of small and micro enterprises
  • 4 Data description and empirical model: employee turnover and corporate profits
  • 5 Factors that affect employee turnover
  • 6 Conclusions and policy recommendations
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