Sustainability assessment of start-ups with the ESG Starter and the GHG & Impact Estimator
Notice bibliographique
Résumé
The background paper explains the methodology of the developed tools ESG Starter and GHG & IMPACT Estimator, which can be used to assess the sustainability of start-ups. Background: Sustainability assessment of start-ups Assessing the ecological and social impact of start-ups is associated with a high degree of uncertainty and considerable effort. As a result, sustainability-oriented aspects are often not given sufficient consideration in investment decisions. As a result, promising start-ups with high sustainability potential and social benefits are often not ecognized enough and do not receive sufficient financial support (Fichter et al., 2024), while capital may flow into less sustainable or less impactful companies or not into young innovative companies at all. This misallocation of capital means that start-ups with high sustainability potential often face greater challenges in further developing and scaling their ideas and thus realizing their impact potential due to insufficient appreciation of their positive externalities. A directionally sound sustainability assessment makes it possible to better channel capital towards social goals and innovation policy „missions“ (BMBF, 2023) and to increase the chances that innovative solutions for overcoming ecological and social challenges will successfully establish themselves on the market. Special considerations when evaluating start-ups Start-ups are in the initial phases of company and business development. Their products, services and business models are usually still in their infancy and will change considerably in the future due to their innovative nature and the need to find the right „market fit“. As a result, the impact on sustainability can often only be estimated on the basis of assumptions and plausible scenarios. Especially in the early phases, start-ups lack established value chains and historical data that can prove their performance and effects (outcomes and impacts). Compared to large companies or established SMEs, startups also have significantly fewer resources and capacities to deal intensively with sustainability issues and their evaluation. Against this backdrop, there are three key peculiarities when assessing the sustainability impact of start-ups: Firstly, the focus of the assessment cannot usually be on the impacts of a start-up that have already occurred and are measurable, but rather on the sustainabilitypotential - i.e. the future contributions to ecological, social and economic sustainability. Secondly, it is only practicable to integrate and evaluate sustainability aspects at an early stage if this is possible for both the start-up itself and external takeholders (e.g. investors, start-up funding programs) with reasonable effort and provides information relevant to decision-making. Thirdly, an approach is suitable for evaluating a startup if it can be applied flexibly in different phases, sectors and situations (DIN SPEC 90051-1 consortium, 2020).
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Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,004 | 0,007 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,002 |
| Bibliométrie | 0,006 | 0,005 |
| Études des sciences et des technologies | 0,000 | 0,001 |
| Communication savante | 0,002 | 0,002 |
| Science ouverte | 0,001 | 0,002 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,010 | 0,003 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».