A linear programming-based optimization model to address skilled labor shortages through strategic investments in the construction industry

The construction industry is facing several challenges, including skilled labor shortage and reduced productivity. This dissertation reviews the literature to examine the challenges facing the construction industry, with primary focus on the impact of skilled labor shortages. Based on the review of the literature, we identify three key factors to address the skilled labor shortages and its impact on productivity, which are: 1. Education, 2. Apprenticeship; and 3. Financial Incentive. A mathematical modeling framework using a Linear Programming approach is developed to minimize the total investment in education, apprenticeship, and financial incentive to reduce the impacts of skilled labor shortages and boost the productivity. Simulation-based data as well data from a survey questionnaire are used to perform various case study examples and sensitivity analysis to test and validate the developed mathematical model. The results indicate that apprenticeship and financial incentives play a significant role in reducing short term labor shortages. Education on the other hand, plays a significant role in reducing the labor shortage in the long run. A more robust analysis using additional data can be performed in the future works.