Combining co-citation clustering and text-based analysis to reveal the main development paths of smart cities

Mora, Luca; Deakin, Mark; Reid, Alasdair

doi:10.1016/j.techfore.2018.07.019

Cited by 147 publications

(110 citation statements)

References 97 publications

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“…But the two datasets are not the same. Mora, Deakin & Reid (2018) displays five central clusters also found by co-word analysis, but several more distinct minor Appendix 1: Retrieval Profile in Web of Science:…”

Section: Research Question Threementioning

confidence: 77%

“…Median age analyses were not done by Su, Lyu, Yang et al (2015) nor by Mora, Bolici & Deakin (2017) and Mora, Deakin & Reid (2018). Our analyses of median age of references and citations demonstrate a great variation 1990-1999.…”

mentioning

confidence: 77%

“…Due to less involved frequencies of the WoS Categories in this map, and thus less possible edges, the connections between and within clusters are less strong compared to the map, Figure 7, see Appendix 2 for category frequencies. Mora, Deakin & Reid (2018 , Table 3) perform co-citation and co-word analyses. The latter is comparable with our categorical analysis.…”

Section: Research Question Threementioning

confidence: 99%

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Smart city research 1990–2016

Ingwersen

Serrano-López

2018

Scientometrics

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The methodology is partly based on the 'issue management' approach by Lancaster & Lee (1985) partly on common publication and citation analysis of the set of source documents (n=4,725), the set of their references (n=27,099) and the set of publications (n=7,863) citing the source documents. Median age analyses are included for the sets of references and citations to the source documents. DIVAlike diagrams (Database Information Visualization and Analysis system) are used to demonstrate the distribution of source documents over document types, time and volume of citations obtained. Social Network Analysis (SNA) is applied to topic modeling of the top-100 central WoS Categories of 'smart city(ies)' research and to the set of references. Findings show that the first mention of the concept 'smart city(ies)' in publication titles takes place in 1999. The research area demonstrates a strong multidisciplinary nature and an exponential growth of research publications (in WoS) 2008-2016 dominated by China, Italy, USA, Spain and England. The same five countries are also among the most citing and cited countries. Aside from a constantly strong ICT (Information and Communication Technology) and Electrical/Electronic Engineering presence 'sustainability' elements (Energy, Transport, Environment) are also vital, in particular during the first and third analysis period. The references from the source documents have more distinct topical clusters than the source documents. Artificial Intelligence (AI) appears as a novel field among the source documents 2008-2016, but disappears from the top-25 list in the citing documents. Instead Economics, Water Resources and Meteorology & Atmospheric Sciences move into the list. Proceedings papers, as in many other engineering and technology based research fields, are the dominant document type (70 %) but have small citation impact (0.6 c/p), thus decreasing the overall impact of the area to 3.6 c/p. Journal articles are the most cited type with 76 % of all citations received (impact 2008-2016: 7.5 c/p). Most citations to journal articles derive from journal articles themselves (76 %).

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Section: Research Question Threementioning

confidence: 77%

mentioning

confidence: 77%

Section: Research Question Threementioning

confidence: 99%

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Smart city research 1990–2016

Ingwersen

Serrano-López

2018

Scientometrics

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“…ICT is mentioned as the main driver for the growth of smart cities (Mora et al, 2019a). Smart cities focus on applying ICTs through embedding sensors and sensor networks in railways, bridges, tunnels, roads, buildings, water systems, dams, oil and gas pipelines and other objects (Su, Li, and Fu 2011).…”

Section: Enabling Icts As Prerequisites For a Smart Citymentioning

confidence: 99%

“…This definition is a typical example of a technocratic conception of the smart city (Söderström, Paasche, and Klauser 2014): a technology-led vision on the development of smart cities based on a technology push (Angelidou 2015). Mora, Deakin, and Reid (2019a) relates this vision to the corporate development path: 'urban areas become smart when they are equipped with a platform of digital solutions provided by ICT consultancies' (ibid., 64). According Mora, Deakin, and Reid (2019b) ICT companies suggest that in their technology-led vision the introduction of ICT solutions is the only factor to be considered when discussing smart city development.…”

Section: Enabling Icts As Prerequisites For a Smart Citymentioning

confidence: 99%

Smart city technologies and figures of technical mediation

Voordijk

Dorrestijn

2019

Urban Research & Practice

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With ICTs increasingly influencing the built environment, it becomes ever more important to analyse the impact of smart city technologies on citizens' behaviour. To explore this impact, the philosophy of technical mediation is used. This philosophy implies that our way of living is always, to some degree, constituted and transformed by technologies. This study's objective is to assess the applicability of Dorrestijn's model of human-technology relationships when exploring the impact of smart city technologies on citizen's behaviour. Based on Dorrestijn's model of figures of technical mediation, an argumentative literature review is conducted and mediating effects of smart city technologies categorized.

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Research trends in the application of big data in smart cities—A literature review

2023

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In this study, we review articles published in academic journals. in the last 5 years at the intersection of big data and the smart city context. Based on a dataset of 192 articles, we use content analysis to identify recent trends and future research directions. The most influential research areas identified include using big data analytics, electric vehicle integration, and citizen‐centric big data, while the most recent research area that emerged is green space. Our results highlight how big data can influence eight different dimensions of smart cities, with smart mobility attracting the most attention from researchers in the application of big data in smart cities. In contrast, smart people and smart economy are the least explored dimensions from this perspective.

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Combining co-citation clustering and text-based analysis to reveal the main development paths of smart cities

Cited by 147 publications

References 97 publications

Smart city research 1990–2016

Smart city research 1990–2016

Smart city technologies and figures of technical mediation

Research trends in the application of big data in smart cities—A literature review

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