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9 - Fuzzy-Set Analysis of Network Data as Mixed Method

Personal Networks and the Transition from School to Work

Published online by Cambridge University Press:  05 July 2014

By
Betina Hollstein  and
Claudius Wagemann
Edited by
Silvia Domínguez  and
Betina Hollstein
Betina Hollstein
Affiliation:
Universität Bremen
Claudius Wagemann
Affiliation:
Goethe University
Silvia Domínguez
Affiliation:
Northeastern University, Boston
Betina Hollstein
Affiliation:
Universität Bremen
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Summary

Introduction

Entering the labor market marks a decisive juncture in setting the course for a young adult’s career and future life. In the face of increasing youth unemployment and rapidly shifting labor markets, the question of the determinants of successful or unsuccessful transitions into gainful employment deserves particular attention. In this chapter, we analyze the conditions that affect these school-to-work transitions. To do so, we focus on the particularly vulnerable group of youth with less education, who face higher risks in this phase of life. We ask under which conditions do these youth, after a failed search for an apprenticeship, actually succeed in finding work? We investigate both individual characteristics (such search behaviors) and the network aspects – functional aspects (cognitive, instrumental, and emotional support of network members), structural aspects (like network size and composition), and attributes of network members, such as occupational status of parents.

The database consists of qualitative longitudinal data collected by the Collaborative Research Center (CRC) 333 “Perspectives on the Development of Work” based at the Ludwig Maximilians University of Munich. We conducted a secondary analysis of these data using fuzzy set analysis, a particular form of Qualitative Comparative Analysis (QCA; Ragin 2000, 2008). In this chapter, we demonstrate how and under what conditions fuzzy set QCA can be employed to conduct research into social networks. We consider QCA a mixed method as it integrates thick descriptions, a common feature of qualitative methods, with data reduction, which is characteristic of quantitative methods. It is especially suited for the analysis of medium-sized samples as it specifically allows us to model both complex solutions and equivalent terms of solutions for combinations of factors. As we will demonstrate, the application of fuzzy set analysis facilitates systematic case comparisons and supports the construction of typologies that strongly build on the individual cases. Methodologically, our study is considered a “conversion design” (Tashakkori and Teddlie 2009), in which qualitative data are transformed into numeric data. The various network aspects are described as individual characteristics and then used to explain individual behavior.

Type
Chapter
Information
Mixed Methods Social Networks Research
Design and Applications
 , pp. 237 - 268
Publisher: Cambridge University Press
Print publication year: 2014

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