A Python package including an algorithm that considers employer, employee demographic and social factors, and employee preferences to determine the ideal proportion of home office work for efficiency and resource-saving.
Jupyter NotebookMIT
How Much Home Office is Ideal? A Multi-Perspective Algorithm (CHIWORK '23)
The COVID pandemic has made working from home necessary, and many employees want to continue doing so even after the pandemic. There are advantages and drawbacks to the home office trend from both employer and employee perspectives. Determining the ideal proportion of home office for each employee is important but there is a research gap in how to do so. This work presents an algorithm that considers multiple perspectives to determine the ideal proportion of home office, including the employer's view, demographic and social factors of the employee, and the employee's preferred proportion of home office. The algorithm combines findings from several studies and can identify discrepancies between these perspectives.
HOMPA - Overview
We consider three different perspectives to determine the ideal proportion of home office:
The employer's perspective, denoted as $P_{ER}$
Social factors, denoted as $P_{social}$
The preferred proportion of home office by employees, denoted as $P_{prefer}$
From the employer's perspective, we determine the maximum proportion of home office ($H_{max}$) based on the tasks executed and the ideal proportion of home office ($H_{opt}$), which also takes into account the proportion of interaction required for the particular tasks.
The factors of $P_{social}$ and $P_{prefer}$ are aggregated into $H_{social}$ and $H_{prefer}$ respectively.
We distinguish between an individual's and the company's total result for each perspective. Based on this, discrepancies between employers and employees and any need for discussion are identified.
