A mathematical optimization approach to account for career development, job security, and job satisfaction in human resource planning in construction organizations

The construction industry as a major global employment market momentously contributes to the world's Gross Domestic Product (GDP). Human Resource (HR) planning is a key planning stage in construction projects which has traditionally involved identifying and recruiting the required skill resources as well as allocating the project tasks to individual employees and crews to maintain the maximum productivity. However, apart from these traditional objectives, the increasing importance of corporate social responsibility calls for HR planning to also account for social aspects including workers' future needs as well as employees retention and development. This requires developing workforce planning models that ensure construction workforce develops the skills and capabilities needed for the future while enjoying social benefits including career development opportunities and job satisfaction.Three major challenges of workforce management in construction industry including career development, job security, and job satisfaction are addressed in this thesis. The above social sustainability factors are mathematically incorporated in construction HR planning in order to strengthen the current workforce planning approach. The thesis starts by addressing the imbalance between employee and employer objectives which focus overly on corporate objectives such as maximizing productivity at the expense of workers' career development needs. A mathematical formulation is developed to enable managers to optimize the relationship between these interdependent corporate priorities which resulted in significant improvements in employees' career development opportunities. The thesis continues by proposing a HR sharing model to maximize the job tenure of employees, as a well-emphasized social objective in HR management, by sharing idle employees with required skills between several construction organizations. The model is designed to minimize the impact of trained workers loss and the associated productivity costs of participating organizations.In its last section, the focus of thesis is placed on maximizing employees job satisfaction through proposing a mathematical optimization model for job allocation in construction organization with the objective of maximizing an aggregate job satisfaction function consisting of salary and over-hour working factors. The thesis concludes by outlining the key findings and practical implications of this work in the conclusion chapter as well as providing directions for future works in this area.