Optimal matching analysis in career research: A review and some best-practice recommendations

Dlouhy, Katja

DOI: https://doi.org/10.5465/ambpp.2015.14674abstract
URL: https://journals.aom.org/doi/10.5465/ambpp.2015.14...
Additional URL: https://www.researchgate.net/publication/291368983...
Document Type: Conference or workshop publication
Year of publication: 2015
The title of a journal, publication series: Annual Meeting Proceedings / Academy of Management
Volume: 2015
Page range: 14674
Conference title: Academy of Management 2015 Annual Meeting
Location of the conference venue: Vancouver, Canada
Date of the conference: 07.-11.08.2015
Place of publication: Chicago, IL
Publishing house: Academy of Management
ISSN: 0065-0668 , 2151-6561
Publication language: English
Institution: Business School > ABWL, Personalmanagement u. Führung (Biemann 2013-)
Subject: 330 Economics
Abstract: Optimal matching is a method for the analysis of sequential data. It allows researchers to detect patterns in career sequences or in trajectories of vocational development. After giving a brief introduction to the method, we review the present literature on careers and vocational development to show where optimal matching analysis has already been employed. We then conduct Monte Carlo simulations of data with varying parameters for sequence length and sample size. Based on the results from these simulation studies, we recommend which properties data sets should have for an optimal matching analysis. We also provide guidelines on how to code sequences, discuss how to deal with missing values, and show which cost settings and clustering algorithms deliver the best results for data sets with specific properties.

Dieser Eintrag ist Teil der Universitätsbibliographie.

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