Unsupervised learning analysis of European working condition
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Date
2024-02
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Cogent Business & Management
Abstract
Workers require good working conditions to enhance their job performance, in this
study, we conducted a survey of European working conditions in 2022 and compared
the results with that of 2016 using an unsupervised learning approach for exploratory
data analysis and determining the relationships. Hence, the Principal Component
Analysis (PCA ) was adopted. The analyses were in two parts for both the 2016 and
2022 surveys. Following the PCA , the first part shows that European workers are mostly
characterized by cheerfulness and good spirits. The second part reveals that European
workers are best characterized by enthusiasm in their work. Test statistics showed that
the European working condition for the two periods does not differ significantly. The
working conditions in Europe have not been altered in the space of six years. This
study recommends that the working condition in Europe should be improved so that
employers would continue to give their best.
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Olumide S. Adesina, Adedayo F. Adedotun, Semiu A. Alayande, Emmanuel O. Efe-Imafidon, Tolulope F. Adesina, Hillary I. Okagbue & Oluwakemi O. Onayemi (2024) Unsupervised learning analysis of European working condition, Cogent Business & Management, 11:1, 2316644, DOI: 10.1080/23311975.2024.2316644