Affiliation:
1. Information Systems and Analytics Department Leavey School of Business Santa Clara University Santa Clara California USA
2. Department of Supply Chain Management The Eli Broad Graduate School of Management Michigan State University East Lansing Michigan USA
3. Department of Electrical and Computer Engineering Michigan State University East Lansing Michigan USA
4. Department of Supply Chain Management Raymond J. Harbert College of Business Auburn University Auburn Alabama USA
Abstract
AbstractThe United Nations Sustainable Development Goals have recently emphasized the importance of diversity inclusion. Motivated by this goal, we examine the impact of employing individuals with disabilities in apparel manufacturing cells on overall team productivity (PD). We formulate a series of deterministic and stochastic PD maximization assignment problems to study the impact of disability inclusion on a production line. We extend the baseline PD maximization formulation to study a multi‐objective problem that simultaneously maximizes PD, disability diversity (DD), and language diversity (LD). Each analysis is performed across two different garments drawn from a real‐world setting. The models are tested using archival time study data collected in partnership with an apparel manufacturing firm where more than 75% of the billed work hours are from individuals with significant disabilities. The following insights emerge from the analyses. First, the PD of teams that have individuals across multiple, different types of disabilities is higher than the PD of teams with employees who share a single, specific type of disability. Second, teams that employ both individuals with and without disabilities perform slightly better than teams that consist of only individuals with disabilities. In some instances, contrary to intuition, teams of only individuals with disabilities even have higher PD than teams of only individuals with no disabilities. Finally, our results from the multi‐objective problem that simultaneously maximizes PD, DD, and LD suggest that PD is not generally sensitive to increases in DD. However, PD is sensitive at extreme levels of DD and LD. Limitations and possible future extensions of the study are discussed.
Subject
Management of Technology and Innovation,Industrial and Manufacturing Engineering,Management Science and Operations Research
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