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Machine learning for predicting sense of place among hybrid workers: A SHAP-based analysis of key factors

; ; ;

In
Wellbeing, space and society 9, Seiten/Artikel-Nr.:100328

ImpressumAmsterdam : Elsevier

Umfang[1]-16

ISSN2666-5581

Online
DOI: 10.1016/j.wss.2025.100328

DOI: 10.18154/RWTH-2025-10477
URL: https://publications.rwth-aachen.de/record/1023071/files/1023071.pdf

Einrichtungen

  1. Institut und Lehrstuhl für Arbeits-, Sozial- und Umweltmedizin (922110 ; 922120)

Projekte

  1. OAPKF - Open-Access-Publikation mit Unterstützung der RWTH Aachen University (021000-OAPKF) (021000-OAPKF)

Thematische Einordnung (Klassifikation)
DDC: 300

OpenAccess:
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Dokumenttyp
Journal Article

Format
online

Sprache
English

Anmerkung
Peer reviewed article

Externe Identnummern
SCOPUS: SCOPUS:2-s2.0-105022888405
WOS Core Collection: WOS:001630271600001

Interne Identnummern
RWTH-2025-10477
Datensatz-ID: 1023071

Beteiligte Länder
Germany

Lizenzstatus der Zeitschrift

 GO

Medline ; Creative Commons Attribution-NonCommercial CC BY-NC 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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The record appears in these collections:
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Publication server / Open Access
Faculty of Medicine (Fac.10)
Public records
521001\-2
Publication Charges
Publications database
TypAmountVATCurrencyShareStatusCost centre
Other100.007.00EUR6.56 %(DEAL)021000-922110
APC1424.0099.68EUR93.44 %(DEAL)021000-922110
Sum1524.00106.68EUR   
Total1630.68     
 Record created 2025-12-08, last modified 2025-12-11
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