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Classifying self-employed persons using segmentation criteria available in the Labour Force Survey (LFS) data

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Abstract This paper responds to the call of researchers, business practitioners, and policymakers to treat different kinds of entrepreneurs separately by the empirical implementation of Cieślik and Dvouletý (2019) segmentation… Click to show full abstract

Abstract This paper responds to the call of researchers, business practitioners, and policymakers to treat different kinds of entrepreneurs separately by the empirical implementation of Cieślik and Dvouletý (2019) segmentation criteria for classifying self-employed persons. The article shows how the segmentation variables (i.e. work engagement; skills and job classification; growth aspirations and economic dependency) might be used when working with the European Labour Force Survey (LFS) data set. The paper exploits the Czech sample of the ad-hoc module 2017 data set, and it shows differences between various types of entrepreneurs by using tools of applied statistical techniques (Chi-Square tests of association, Cramer’s V and t-tests). The article contributes to the community by showing how to use the segmentation variables in their own empirical research. The study encourages all researchers to explore the diversity of self-employment to advance the entrepreneurship field further forward. The article also includes several recommendations and directions for future research at the individual, regional, country or cross-country levels.

Keywords: self employed; employed persons; classifying self; segmentation criteria; segmentation; labour force

Journal Title: Journal of Business Venturing Insights
Year Published: 2020

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