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Institutional Repository [SANDBOX]
Technical University of Crete
Technical University of Crete
EN
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| URI: | http://purl.tuc.gr/dl/dias/15D30118-3257-4BC9-9D4F-12A4B5E5C939 | ||
| Year | 2024 | ||
| Type of Item | Diploma Work | ||
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| Bibliographic Citation | Maria Piagkou, "Analysis of employee loyalty using Logistic Regression and fsQCA", Diploma Work, School of Production Engineering and Management, Technical University of Crete, Chania, Greece, 2024 https://doi.org/10.26233/heallink.tuc.99156 | ||
| Appears in Collections |
The purpose of this thesis is to analyze the impact of a set of criteria on employee loyalty using qualitative comparative analysis and fuzzy sets/QCA, along with logistic regression. The fs/QCA method is based on the theory of fuzzy sets and Boolean algebra to identify whether specific factors or combinations thereof are present or absent when a particular phenomenon occurs or not. In other words, it identifies causal conditions or combinations capable of leading to a high outcome and any necessary conditions for the presence of the result. Additionally, logistic regression is used in this study. This method is applied when the variable we want to predict is binary. Specifically, it is useful for predictions regarding the identification of potential factors influencing the presence or absence of the variable. In this case, we examine the variable of employee loyalty (remaining or not in the workplace) and the significance of the criteria related to it. The goal is to obtain logical results that effectively reflect employee loyalty and the criteria that affect it. The data used are sourced from the Kununu website, focusing on employee reviews regarding work experience within a large supermarket chain.
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