Association Rule Mining for Occupational Wellbeing During COVID
摘要
Businesses have started to take an active role in promoting occupational wellbeing and boosting workplace performance. One of the primary challenges of this is the identification of the factors that contribute to workplace wellbeing and performance, either implicitly or explicitly, before targeting those areas. This paper applies association rule mining algorithms to employee wellbeing data that was collected from 157 participants, during the period of January to August of 2020 (before and during the COVID-19 lockdown), with an aim to find useful patterns that could help identify potential unknown factors that influence wellbeing and performance. The rules extracted through the experimentation have been analysed by occupational psychologists and physiologists who confirmed the effectiveness of the proposed approach in boosting workplace wellbeing and performance.