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Revealing drivers of green technology adoption through explainable Artificial Intelligence

; ; ; ; ;

In
Advances in applied energy 20, Seiten/Artikel-Nr.:100242

Impressum[Amsterdam] : Elsevier ScienceDirect

Umfang[1]-13

ISSN2666-7924

Online
DOI: 10.18154/RWTH-2025-10864
DOI: 10.1016/j.adapen.2025.100242

URL: https://publications.rwth-aachen.de/record/1023939/files/1023939.pdf

Einrichtungen

  1. Lehrstuhl für Computational Network Science (125230 ; 125210)
  2. Lehr- und Forschungsgebiet Ökonomie der Nachhaltigkeit (817220)


Thematische Einordnung (Klassifikation)
DDC: 333.7

OpenAccess:
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Dokumenttyp
Journal Article

Format
online, print

Sprache
English

Anmerkung
Peer reviewed article

Externe Identnummern
SCOPUS: SCOPUS:2-s2.0-105017043809
WOS Core Collection: WOS:001584755400001
OpenAlex: W4414419737

Interne Identnummern
RWTH-2025-10864
Datensatz-ID: 1023939

Beteiligte Länder
Germany

Lizenzstatus der Zeitschrift

 GO

Creative Commons Attribution CC BY 4.0 ; DOAJ ; OpenAccess ; Article Processing Charges ; Clarivate Analytics Master Journal List ; DOAJ Seal ; Emerging Sources Citation Index ; Fees ; SCOPUS ; Web of Science Core Collection
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817230
125230
 Record created 2025-12-17, last modified 2026-09-14
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