Course content

The subject is compulsory in the first year of the study program INGLOG (Program subject 1 identity subject). It should help to provide a good understanding of basic business economics and data analysis. The course consists of a module in basic economics (3.5 credits), and a module in basic data analysis (4 credits). The academic content (see the section for learning outcomes) is adapted to logistics engineers' needs for knowledge and skills in business economics and data analysis. Several subjects further on in the study program build on this subject.

Learning outcome

The course conveys the following knowledge to the candidate

• General knowledge of business finance and investment analysis
• Specific knowledge of pricing under various market forms, financial accounting, accounting analysis of cost trends, investment analysis and transfer pricing
• Specific knowledge of performance measurement in value chains and logistics
• General knowledge of data types and data acquisition methods, both quantitative and qualitative
• Specific knowledge of business modelling, break-even analysis, sensitivity analysis, trend analysis, forecasting, data visualization and interpretation with examples from logistics
• Specific knowledge of computer systems for logistics, ERP systems
• General knowledge of the use of Big Data, Data Mining and Machine

LearningSkills: The candidate must be able to:

• Apply acquired knowledge in analyzes and discussions of basic business economic issues
• Carry out written business financial analyzes using relevant calculation methods and theory
• Assess the choice between different qualitative and quantitative data analysis methods and apply them
• Build simple models in Microsoft Excel, and use techniques to analyze and visualize data
• Carry out break-even analysis, Pareto analysis, trend analysis in a logistics context
• Solve other real problems in logistics with examples from inventory management (EOQ) and planning
• Recognize the structure of integrated logistics information systems (ERP)

Other important learning objectives: The candidate should be able to

• Understand the role of logistics in an overall corporate economic perspective
• Be able to apply data analysis in logistics and value chain management in general and in particular with a view to continued development in digitalisation
• Understand the role of digitalization, sustainability and ethics in business operations

Learning methods and activities

Lectures and assignments

Compulsory assignments

• Exercise

Specific conditions

Recommended previous knowledge

None.

Required previous knowledge

None.

Course materials

To be specified by the start of semester.