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Advisor(s)
Abstract(s)
Weather change plays an important role in work-related accidents,
it impairs people’s cognitive abilities, increasing the risk of injuries
and accidents. Furthermore, weather conditions can cause an increase or
decrease in daily sales in the retail sector by influencing individual behaviors.
The increase in transactions, in turn, leads employees to fatigue and
overload, which can also increase the risk of injuries and accidents. This
work aims to conduct a case study in a company in the retail sector to
verify whether the transactions records in stores and the weather conditions
of each district in mainland Portugal impact the occurrence of work
accidents, as well as to perform predictive analysis of the occurrence or
non-occurrence of work accidents in each district using these data and
comparing different machine learning techniques. The correlation analysis
of the occurrence or non-occurrence of work accidents with weather
conditions and some transactions pointed out the nonexistence of correlation
between the data. Evaluating the precision and the confusion
matrix of the predictive models, the study indicates a predisposition of
the models to predict the non-occurrence of work accidents to the detriment
of the ability to predict the occurrence of work accidents.
Description
Keywords
Predictive Analysis Correlation Analysis Weather Conditions Transactions Records
Pedagogical Context
Citation
Borges, Lucas D.; Sena, Inês; Marcelino, Vitor; Silva, Felipe G.; Fernandes, Florbela P.; Pacheco, Maria F.; Vaz, Clara B.; Lima, José; Pereira, Ana I. (2024). Effect of Weather Conditions and Transactions Records on Work Accidents in the Retail Sector – A Case Study. In 3rd International Conference on Optimization, Learning Algorithms and Applications (OL2A 2023). Cham: Springer Nature, Vol. 1, p. 34–48. ISBN 978-3-031-53024-1.
Publisher
Springer Nature
