Abstract
The health, safety, and well-being of employees, service providers, and customers are important priorities for retail companies. Based on this principle, an intelligent system that contributes to the reduction of accidents at work will be developed, monitoring risk control, preventing work-related illnesses, promoting a culture of zero accidents, and seeking to ensure the health of employees, customers, and stakeholders. In order to achieve such goals, it is necessary to determine the local and global variables (internal and external) that feed the system. This study comprises the first strategy applied to collect the local variables involved in the problem. To obtain this, a data analysis study in a retail store was performed. Data analysis procedures were performed namely clustering analysis with algorithm k-means, correlation procedures, like Pearson coefficient and matrix of correlation, and relationship analysis with parallel coordinate graphs. From the preliminary results, it is possible to indicate a set of local variables that have influence in the occupational behavior and accidents at work.
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This work has also been supported by FCT - Fundação para a Ciência e Tecnologia within the Project Scope UIDB/05757/2020 and project iSafety Norte 2020 n. 072598.
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Sena, I.P., Fernandes, F.P., Pacheco, M.F., Pires, A.A.C., Maia, J.P., Pereira, A.I. (2021). Occupational Behaviour Study in the Retail Sector. In: Pereira, A.I., et al. Optimization, Learning Algorithms and Applications. OL2A 2021. Communications in Computer and Information Science, vol 1488. Springer, Cham. https://doi.org/10.1007/978-3-030-91885-9_45
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DOI: https://doi.org/10.1007/978-3-030-91885-9_45
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