Business Administration

This course offers a study of human resources and management. Topics include: managing employees for competitive advantage; work design and workforce planning; managing employee competences; managing employee attitudes and behaviors.

This course provides an understanding of key issues and applied methodologies relating to management accounting frameworks used by managers when faced with making financial decisions in the context of the business environment. The focus is on information for cost management, budgetary control, and short and longer term financial decision making. It examines the blend of financial analysis and managerial judgment required to make sound decisions. In particular there is an emphasis on issues in overhead cost recovery; contribution costing and CVP analysis; costing issues in the context of a competitive environment, including activity based costing (ABC); relevant costs for decision making; core investment appraisal techniques (ARR, Payback, NPV and IRR); budgetary control, variance analysis, and standard costing.

This course presents a practical approach (based on Excel examples) to understand the principles of management science and to apply them to business decision problems. Developing models of practical decision-making problems and solving them using Excel Solver, one learns how important and useful the scientific decision making process based on management science is for solving problems in real-world business applications. Focusing on management science modeling skills, this course covers linear programming, simplex method, sensitivity analysis, transportation models, integer programming, and others (if time permitted). Students learn the fundamental knowledge and analytical skills in management science. Management science (also called Operations research) combines the three broad disciplines of Mathematics, Computer Science, and Business Applications. This course aims to develop the ideas of developing, analyzing, and validating mathematical models for decision problems, and their systematic solution. The course involves modeling and mathematical analysis.