What drives the relationship between digitalization and industrial energy demand? Exploring firm-level heterogeneity
Axenbeck, Janna
;
Berner, Anne
;
Kneib, Thomas
URN:
|
urn:nbn:de:bsz:180-madoc-637594
|
Dokumenttyp:
|
Arbeitspapier
|
Erscheinungsjahr:
|
2022
|
Titel einer Zeitschrift oder einer Reihe:
|
ZEW Discussion Papers
|
Band/Volume:
|
22-059
|
Ort der Veröffentlichung:
|
Mannheim
|
Sprache der Veröffentlichung:
|
Englisch
|
Einrichtung:
|
Sonstige Einrichtungen > ZEW - Leibniz-Zentrum für Europäische Wirtschaftsforschung
|
MADOC-Schriftenreihe:
|
Veröffentlichungen des ZEW (Leibniz-Zentrum für Europäische Wirtschaftsforschung) > ZEW Discussion Papers
|
Fachgebiet:
|
330 Wirtschaft
|
Fachklassifikation:
|
JEL:
C14 , D22 , L60 , O33 , Q40,
|
Freie Schlagwörter (Englisch):
|
digital technologies , energy use , manufacturing , machine learning
|
Abstract:
|
The ongoing digital transformation has raised hopes for ICT-based climate protection within manufacturing industries, such as dematerialized products and energy efficiency gains. However, ICT also consume energy as well as resources, and detrimental effects on the environment are increasingly gaining attention. Accordingly, it is unclear whether trade-offs or synergies between the use of digital technologies and energy savings exist. Our analysis sheds light on the most important drivers of the relationship between ICT and energy use in manufacturing. We apply flexible tree-based machine learning to a German administrative panel data set including more than 25,000 firms. The results indicate firm-level heterogeneity, but suggest that digital technologies relate more frequently to an increase in energy use. Multiple characteristics, such as energy prices and firms’ energy mix, explain differences in the effect.
|
| Das Dokument wird vom Publikationsserver der Universitätsbibliothek Mannheim bereitgestellt. |
Suche Autoren in
Sie haben einen Fehler gefunden? Teilen Sie uns Ihren Korrekturwunsch bitte hier mit: E-Mail
Actions (login required)
|
Eintrag anzeigen |
|
|