End of life aircrafts recovery and green supply chain (a conceptual framework for addressing opportunities and challenges)
Notice bibliographique
Résumé
Purpose – This paper aims to address the different aspects of end-of-life (EOL) aircraft problems and their effects on original manufacturer’s supply chain. Aircraft manufacturers, in the greener aviation context, need to care about the footprint of planes at the EOL. Considering the challenges in EOL aircraft recovery, the reverse logistics and green supply chain solutions in the other industrial sections cannot be applied in the aerospace industry. A conceptual framework with four elements, supply chain competency, governance policy, relationship in supply chain and aerospace industry context, provides a basis for assessing the opportunities and challenges of the green supply chain in this industry. Design/methodology/approach – The basic research method utilized in this paper is the literature review. The literature review is a research methodology that includes examining books, journals, conference proceedings and dissertations for available information on the area of research. The research area regarding EOL aircraft is new. A substantial amount of literature exists in the field of end-of-life vehicle, but the main content of literature about the aircraft recycling can be obtained via relatively few literature, technical reports, news and industrial experts’ opinions. The literature is complete in some respects while inadequate in others. A considerable amount of information has been gathered through graduate student projects. The other information has been collected via contacts with professionals involved in an EOL aircraft recycling project. The basis for this methodological framework comes from a research process proposed by Mayring (2010) that emphasizes on four steps: material collection, descriptive analysis, category section and material evaluation. Findings – This paper addresses the opportunities and challenges of applying a green supply chain for aircraft manufacturers and analyzes the different aspects of aircraft at the EOL in the context of green supply chain. Research limitations/implications – This study enriches the literature by identifying EOL aircraft value chain analysis in the sustainable development context. It provides an introduction to a fresh research theme and sheds some light on green supply challenges in the aerospace industry. Practical implications – The proposed conceptual framework in this paper helps practitioners to realize the opportunities and challenges of aircraft manufacturers in applying long-term strategies with respect to EOL aircrafts. The proposed framework helps manufacturers to evaluate different perspectives of the EOL aircraft problem. Moreover, the current contribution of aircraft manufacturers into EOL projects is not in a systematic structure and performed through several managerial and professional meetings. The proposed framework in this study is a valuable tool to evaluate the different opportunities and challenges in an organized way. Originality/value – This work provides a valuable framework for future research related to green supply chains in the aerospace context. It also aids practitioners to realize the EOL aircraft problem in the context of the green supply chain, considering the opportunities and challenges.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
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 | 0,006 | 0,003 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,001 |
| Bibliométrie | 0,005 | 0,007 |
| Études des sciences et des technologies | 0,004 | 0,016 |
| Communication savante | 0,014 | 0,018 |
| Science ouverte | 0,002 | 0,007 |
| Intégrité de la recherche | 0,006 | 0,004 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,006 | 0,001 |
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 ».