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Erschienen in: Social Network Analysis and Mining 1/2024

01.12.2024 | Original Article

Fostering UAM implementation: from bibliometric analysis to insightful knowledge on the demand

verfasst von: Faheem Ahmed Abbasi, Raymond Houé Ngouna, Muhammad Ali Memon, Mana Saleh Al Reshan, Adel Sulaiman, Asadullah Shaikh

Erschienen in: Social Network Analysis and Mining | Ausgabe 1/2024

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Abstract

In the current era, a new class of lightweight, silent, and all-electric aircraft that can take off and land vertically is about to transform mobility in major urban centers. Safer and quieter than helicopters, and operating in some cases without a pilot, they can supplement land mobility. Indeed, urban air mobility (UAM) has recently been a hot topic for debate and scientific research. However, it requires new types of service and technology and a novel business model. For a successful implementation, this paper provides the most insightful knowledge and actors, focusing on demand assessment through current research advancements in the area of urban air mobility. For that purpose, bibliometric analysis has been conducted, using a four-step methodology based on the search of the most frequently used keywords. The research work investigated the needs of the main stakeholders and illustrated how UAM can mitigate the pressure put on decision-makers regarding the mobility demand. The results show recent trends in scientific publications and citations, most cited articles, countries, and organizations that are more involved in this research subject, keyword co-co-occurrence analysis to identify and analyze current research areas and their associated barriers and challenges, using the VOSviewer software and WoS analytic feature.

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Metadaten
Titel
Fostering UAM implementation: from bibliometric analysis to insightful knowledge on the demand
verfasst von
Faheem Ahmed Abbasi
Raymond Houé Ngouna
Muhammad Ali Memon
Mana Saleh Al Reshan
Adel Sulaiman
Asadullah Shaikh
Publikationsdatum
01.12.2024
Verlag
Springer Vienna
Erschienen in
Social Network Analysis and Mining / Ausgabe 1/2024
Print ISSN: 1869-5450
Elektronische ISSN: 1869-5469
DOI
https://doi.org/10.1007/s13278-024-01210-3

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