Hallbarhetslankade lan - vagen till en mer hallbar fastighetsbransch : En studie om tillampningen av hallbarhetslankade lan och dess effekter hos svenska fastighetsbolag
Bibliographic record
Abstract
The construction and real estate sector accounts for a significant part of Sweden's total greenhouse gas emissions. Swedish real estate companies play a leading role in the climate transition and represent more than half of the Swedish market for green corporate bonds. International initiatives such as the UN's Agenda 2030, the Paris Agreement, and the EU's Green Taxonomy Regulation promote sustainable development and the identification of sustainable investments. The taxonomy regulation directs investments towards sustainability, which, along with growing global demand, impacts the market for sustainability linked loans. The thesis aims to investigate the motives and driving forces behind Swedish property companies and banks' participation in sustainability linked loans, their application and impact on their sustainability work, and potential challenges and future prospects for these loans in Sweden. This thesis is based on a qualitative research method and includes seven interviews with respondents from two different stakeholder groups; lenders (banks) and borrowers (property companies). A literature study has been prepared to provide insight into sustainability linked loans and the market's characteristics. The collected empirical material has then been analyzed based on Corporate Social Responsibility (CSR) and Signaling theory. The conclusions are based on the study's empirical data and discussion. The conclusions drawn are that sustainability linked loans play a significant role in Swedish real estate companies' sustainability work by offering financial incentives, strengthening the companies' strategies, and increasing transparency. Banks and property companies see advantages in the form of better conditions and a stronger link between sustainability efforts and financial benefits. Challenges for the future include transparency and the risk of greenwashing. The implementation of the EU's CSRD and ESRS is expected to address these challenges. Despite this, sustainability linked loans are expected to continue to grow and be demanded by more industries.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.006 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.009 | 0.005 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.010 | 0.002 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".