Decoding the Future of Sustainability: The European Union's Sustainable Finance Disclosure Regulation (SFDR) isn't just a mandate; it's a golden key unlocking a treasure trove of opportunities for businesses committed to sustainable supply chains. In this dynamic class, we'll crack the code on decarbonizing your operations, not just to achieve compliance, but to gain a vital edge in the rapidly evolving marketplace.

Beyond Boxes and Checklists: Forget the dry world of compliance checklists. We'll delve into the intricacies of the EU SFDR, understanding its implications for your specific industry and exploring innovative strategies for reducing your carbon footprint. From sourcing responsibly to optimizing logistics and engaging stakeholders, we'll equip you with the tools and knowledge to build a resilient, future-proof supply chain.

•Responsible Sourcing: Identifying high-impact nodes in your supply chain.
•Logistics Optimization: Moving from "just-in-time" to "just-as-green."
•Stakeholder Synergy: Engaging partners to build a resilient, future-proof ecosystem.

Competitive Advantage Awaits: By embracing sustainability as a core value, you'll not only mitigate climate risks but also unlock a wealth of benefits:
•Enhanced brand reputation and customer loyalty
•Reduced operational costs and improved efficiency
•Attracting and retaining top talent who value environmental responsibility
• Securing investment from eco-conscious financiers

This class is your gateway to becoming a sustainability champion within your
organization. Together, we'll navigate the exciting landscape of the EU SFDR, equipping you with the
knowledge and confidence to:

• Develop a winning decarbonization strategy
• Implement effective sustainability measures
• Track your progress and measure your impact
• Become a thought leader in the drive towards a greener future
• Unlock the carbon code, unleash your competitive advantage, and join the sustainability
revolution!

Class attendance is compulsory

Course will involve reading and active discussion on topics assigned to you each day.
Final case analysis has to be sketched out and submitted later. A new AI-Powered Workshop Exercise

• Exercise: The SFDR "Ghost Writer" & Gap Analyst
• In this hands-on lab, we will use Large Language Models (LLMs) to bridge the gap between
complex supply chain data and SFDR reporting requirements.
• The Objective: Use an LLM to transform raw supplier data into a compliant "Principal Adverse
Impact" (PAI) narrative.

The Workflow:
1. The Prompt Engineering Phase: Participants will be given a sample dataset of supplier carbon
emissions and energy mix. You will learn to draft a "System Prompt" that instructs the AI to act
as a Chief Sustainability Officer.
2. Scenario Analysis: Ask the AI to identify the top three "Regulatory Risks" within that dataset
according to SFDR Article 8 and 9 criteria.
3. The "Executive Summary" Sprint: Use the AI to synthesize technical data into a compelling,
jargon-free summary for board-level stakeholders.

We will specifically focus on how to use AI to detect "greenwashing" in supplier self-disclosures by crossreferencing
their claims against industry benchmarks.

Grading: TBA (Case analysis, presentation (group), written assignment (group)

SCM grading scale:

Percentage    Points         Grade
90 - 100        22.5 – 25     Excellent (1)
80 - <90       20 - <22.5    Good (2)
70 - <80       17.5 - <20    Satisfactory (3)
60 - <70       15 - <17.5    Passed (4)
< 60              <15             Failed (5)

Please log in with your WU account to use all functionalities of read!t. For off-campus access to our licensed electronic resources, remember to activate your VPN connection connection. In case you encounter any technical problems or have questions regarding read!t, please feel free to contact the library at readinglists@wu.ac.at.

Policy on Plagiarism & AI Usage:

Original Work: All submissions must be original. Using existing materials, websites, or a peer's work without proper citation is plagiarism.

AI Transparency: If you use an LLM (like ChatGPT or Gemini) to assist in your research or drafting, you must include an "AI Disclosure Statement" at the end of your work detailing which prompts were used.

Verification: We reserve the right to use detection tools and oral "viva" style follow-ups to verify the authorship of any work. Dishonesty will result in a failing grade.

Example AI Disclosure: "I used [AI Model Name] to generate the initial SWOT analysis for this supplier. I then manually edited the output to include specific SFDR Article 9 metrics and verified all data against the provided course case study."