Syllabus

Title
0617 Business Intelligence in Supply Chains 1 (BI 1)
Instructors
ao.Univ.Prof. Dr. Alexander Prosser
Contact details
Type
PI
Weekly hours
2
Language of instruction
Englisch
Registration
09/27/24 to 09/27/24
Registration via LPIS
Notes to the course
Dates
Day Date Time Room
Saturday 11/30/24 09:00 AM - 05:00 PM LC.-1.038
Thursday 01/23/25 02:00 PM - 06:00 PM LC.-1.038
Friday 01/24/25 02:00 PM - 06:00 PM LC.-1.038
Wednesday 01/29/25 09:00 AM - 05:00 PM LC.-1.038
Contents

Implementation of CO2 (generally, greenhouse gas GHG) accounting conformant to IFRS S2.

Learning outcomes

Students will understand the concept of carbon footprint reporting and the underlying data management requirements. They will understand current and already planned future requirements. This knowledge will come in useful in future positions managing national or transnational supply chains.

Students will learn how to research specific details in these requirements for a given supply chain and how to implement them in a system specifically designed to handle footprint management and reporting. The example case used will be based on the “umbrella” case study used in SCO 3.

Students will learn how to implement their supply chain and to map it to CO2 equivalents in a specific tool and how to derive the necessary reports to meet the auditing requirements.

Students will also learn to leverage relative financial and CO2 advantages in alternative sources depending on the CO2 reporting requirements of their market.

Attendance requirements

According to the examination regulation full attendance is intended for a PI.

Teaching/learning method(s)

Students have to research specific requirements in the applicable legal base of the supply chain to implement their supply chain in a specific tool and to map the GHG requirements to that model and also to make optimal decisions based on the requirements of the target market.

Assessment

Assessment will be based on the case study to be implemented.

 

Grading scale:

(1) Excellent: 90% - 100%

(2) Good: 80% - <90%

(3) Satisfactory: 70% - <80%

(4) Sufficient: 60% - <70%

(5) Fail: <60%

 

Prerequisites for participation and waiting lists

 

Readings

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Recommended previous knowledge and skills

Availability of lecturer(s)

Last edited: 2024-06-28



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