Exploring the smart city agenda using knowledge networks – The emergence of a new global city landscape

Keywords: smart city, science mapping, knowledge network, global smart city knowledge space, global city network, city rankings

Abstract

In the era of digital transformation, cities increasingly adopt technology-based smart city (SC) agendas. However, implementation depends heavily on locally available scientific knowledge that is simultaneously embedded in global networks. To explore this paradoxical tension, this study provides a nuanced, globalscale analysis of the nexus between academic SC knowledge production and urban economic status. We used Web of Science (WoS) publication metadata (keywords and affiliations) across two distinct periods: 2010–2017 and 2018–2022. First, we employed network analysis (keyword-based thematic networks) to reveal academic SC knowledge segments. Then, we used affiliation data of publications for mapping SC knowledge hubs by scientific output globally. Finally, we derived SC knowledge ranking from collaboration data, adopting the Globalization and World Cities (GaWC) ranking methodology. We used the GaWC economic-related ranking for capturing economic status, based on the international corporate advanced producer services-related firms’ data in 2016 and 2020. Our findings confirm that academic SC knowledge is highly interdisciplinary with a strong technological focus. While an increasing number of cities accumulate SC knowledge production, it becomes concentrated within a small subset of hubs. In addition, emerging economies such as China, India, South Korea, and Brazil as newly prominent regional hubs, are strengthening their position in the global knowledge landscape. Comparing SC knowledge ranking with GaWC ranking, focusing on change in time, our analysis reveals four distinct urban trajectories: dynamic cities of economic and SC knowledge importance; SC knowledge accumulators; economic weight gainers; and potential laggards. Although European cities dominate the top 100 in the rankings, a dynamic shift appears: European cities are mostly sliding into the economic weight gainer or potential laggard categories, while Asian (especially Chinese) cities dominate the dynamic category. These trajectories signal an emerging global urban paradigm where local SC knowledge increasingly complements traditional economic dimensions, particularly in less prominent cities.

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Published
2026-09-30
How to Cite
VidaZ. V., & BorsiB. (2026). Exploring the smart city agenda using knowledge networks – The emergence of a new global city landscape. Hungarian Geographical Bulletin, 75(3), 327-355. https://doi.org/10.15201/hungeobull.75.3.4
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Articles