Hiring People With Disabilities: Work Assignment Models for Decision Support
Nowadays, the assimilation of workers with disabilities is recognized as both a challenge and an opportunity in terms of staff diversity and of corporate social responsibility of different organizations. In this context, achieving a fair and efficient task distribution is an essential aspect of guaranteeing the effective and full involvement of all the workers, independently from their cognitive and physical capacities. A task distribution model is a method for assigning and managing tasks within a work team, organization or group of persons, usually aiming to optimize productivity and efficiency. The main objective is to ensure that the correct tasks are assigned to the appropriate persons, taking into account their abilities, experience and current work charge. Task distribution models are particularly relevant when including people with disabilities, where they must be flexible and adaptable enough to guarantee the full integration of all the team members. In this work, we present a Mathematical Programming model for task distribution in the context of hiring people with disabilities. We discuss a practical case study at the Intendencia de Montevideo (IdeM - the municipality of the city of Montevideo), as part of a project for improving the integration of people with disabilities in its staff (currently the IdeM staff only includes about 1.5% of employees with disabilities; while applicable laws state that this percentage should raise to at least 4%). We present the results of applying the Mathematical Programming model, comparing the results against manual assignments. Different objective functions are also taken into account, as the various stakeholders also have specific goals that are important to take into account. The results show that mathematical programming models are an effective tool that can be used to support decision making and improve the integration of workers with disabilities in an organization.
Authors
- Héctor Cancela (ORCID: https://orcid.org/0000-0001-5015-0988)
- Michele Blasiak
- Julieta Oberti
- Jimena Strechia
- Patricia Quintana
Institutions
- Universidad de la República de Uruguay (UY)
Publication Details
- Published
- 2024-08-12
- DOI
- https://doi.org/10.1109/clei64178.2024.10700075
- Primary Topic
- Transportation and Mobility Innovations
- Type
- article
- Field-Weighted Citation Impact
- 0.00