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Exploring Knowledge Transfer Opportunities between the Railway and Automotive Industries: A Systematic Literature Review

Cheng, Shiqing (2023) Exploring Knowledge Transfer Opportunities between the Railway and Automotive Industries: A Systematic Literature Review. Masterarbeit, Hochschule Harz.

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Kurzfassung

As two significant transportation sectors, the railway and automotive industries face similar challenges, including increased traffic demands, surging energy costs, and the pressing need to address sustainability and environmental concerns. It is urgent for these industries to seek proactive knowledge transfer opportunities to boost their competitiveness and effectively tackle these multifaceted challenges. However, there is a lack of articles that directly investigate knowledge transfer opportunities between these two sectors. This study employs a Systematic Literature Review (SLR) in four comprehensive databases (IEEExplore, Scopus, ScienceDirect, Web of Science) and delves into online resources provided by relevant stakeholders to explore knowledge transfer opportunities between the two sectors with a focus on infrastructure maintenance and data-sharing. Through the SLR, this research summarizes the current state of digitalization within the railway and automotive industries, presents practices related to data-sharing and infrastructure maintenance in both sectors, and points out potential opportunities for knowledge transfer, including preparing the infrastructure for smart mobility, implementing predictive maintenance for autonomous driving infrastructure, popularizing V2X communication in the railway industry, and empowering the data-sharing with Blockchain in the railway industry, which serve as a springboard for further exploration of smart and sustainable mobility solutions.

elib-URL des Eintrags:https://elib.dlr.de/200797/
Dokumentart:Hochschulschrift (Masterarbeit)
Titel:Exploring Knowledge Transfer Opportunities between the Railway and Automotive Industries: A Systematic Literature Review
Autoren:
AutorenInstitution oder E-Mail-AdresseAutoren-ORCID-iDORCID Put Code
Cheng, ShiqingHochschule HarzNICHT SPEZIFIZIERTNICHT SPEZIFIZIERT
Datum:2023
Referierte Publikation:Nein
Open Access:Nein
Gold Open Access:Nein
In SCOPUS:Nein
In ISI Web of Science:Nein
Seitenanzahl:98
Status:veröffentlicht
Stichwörter:Railway Automotive Digitalization Automation Innovation Transfer
Institution:Hochschule Harz
Abteilung:Fachbereich Automatisierung und Informatik
HGF - Forschungsbereich:Luftfahrt, Raumfahrt und Verkehr
HGF - Programm:Verkehr
HGF - Programmthema:Schienenverkehr
DLR - Schwerpunkt:Verkehr
DLR - Forschungsgebiet:V SC Schienenverkehr
DLR - Teilgebiet (Projekt, Vorhaben):V - TraCo - Train Control and Management, V - KoKoVI - Koordinierter kooperativer Verkehr mit verteilter, lernender Intelligenz
Standort: Braunschweig
Institute & Einrichtungen:Institut für Verkehrssystemtechnik
Institut für Verkehrssystemtechnik > Informationsgewinnung und Modellierung, BS
Hinterlegt von: Groos, Jörn Christoffer
Hinterlegt am:11 Dez 2023 12:52
Letzte Änderung:11 Dez 2023 12:52

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