TIØ4295
Managerial Economics
Autumn
Trondheim
Norwegian
About this course
Content
The course covers fundamental topics in business economics, with a focus on the interrelationships between accounting, management control, finance, and strategy. Students are introduced to financial accounting and financial statement analysis, cost concepts and basic decision-making models, budgeting, investment analysis, and business valuation. The course also addresses how management control interacts with strategy, marketing, organization, and leadership. Emphasis is placed on practical applications, a holistic understanding of business economics, and the critical use of artificial intelligence as support in economic analysis and decision-making.
Learning outcomes
The course is designed as a K-course for engineering students who wish to include business economics in their degree programme. It primarily provides an introduction to fundamental methods and models in business economics.
The course aims to provide knowledge of:
- The role of firms in the economy and value creation from a societal perspective
Basic financial accounting
- accounting principles, accruals, valuation, depreciation, and deferred tax
- financial statement analysis and the use of key financial ratios
Management accounting and decision support
- cost concepts, full costing and contribution margin principles
- relevant costs, cost-volume-profit (CVP) analysis, and product mix decisions
Budgeting and planning
- income statements, cash flow budgets, and balance sheet budgets
- the relationship between budgeting, control, and goal achievement
Financial decisions
- interest rate calculations, investment analysis, and loan evaluation
- capital structure and financing
Business valuation
- fundamental valuation models
- applications in strategy and mergers and acquisitions (M&A)
Interaction between economics, strategy, and organization
- linkages between management control, strategy, marketing, organization, and leadership
Use of artificial intelligence in economic analysis
- opportunities and limitations of AI-based tools
- critical assessment of uncertainty, sources of error, and interpretation
Teaching methods
Lectures and mandatory exercises. Requirements will be announced at the beginning of the semester.