Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
6.8
3.3
Journals
Sustainability
Special Issues
Smart Sustainable Cities in the Era of Big Data
sustainability-logo
Submit to Sustainability Review for Sustainability Propose a Special Issue

Journal Menu

► Journal Menu

Journal Browser

► Journal Browser
share announcement

Smart Sustainable Cities in the Era of Big Data

A special issue of Sustainability (ISSN 2071-1050). This special issue belongs to the section "Sustainable Urban and Rural Development".

Deadline for manuscript submissions: closed (25 November 2022) | Viewed by 19724

Special Issue Editor

Dr. Simon Elias Bibri

E-Mail Website
Guest Editor
Department of Computer and Information Science, Norwegian University of Science and Technology (NTNU), 7491 Trondheim, Norway
Interests: sustainable development goals; digital transformation for sustainability; urban planning and design; smart urban governance; big data science and analytics; the Internet of Things (IoT); urban computing and intelligence; urban artificial intelligence (AI); data-driven smart sustainable cities; sustainable cities; smart cities; integrated renewable energy and smart energy technologies; smart solutions for environmental sustainability; environmental innovations and sustainability transitions; science, technology, and innovation studies; circular economy and business model innovation for sustainability; technological and sectoral innovation systems; urban, regional, and environmental policy
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

This Special Issue focuses on data-driven smart sustainable cities. This is a new paradigm of urbanism that has recently materialized in the light of the big data revolution, or what has been termed as the fourth paradigm of science as enabled by big data science and analytics. This new area of science and technology (S&T) embodies an unprecedentedly transformative power—which is manifested not only in the form of revolutionizing science and transforming knowledge, but also in enhancing social practices, catalyzing major shifts, creating powerful discourses, and fostering societal transitions. Of particular relevance is instigating the massive changes in the way both sustainable cities and smart cities are studied, understood, planned, designed, controlled, managed, and governed in the face of the escalating urbanization trend. This relates to what has been dubbed data-driven smart sustainable urbanism, a new era wherein sustainable urbanism and smart urbanism processes and practices are becoming highly responsive to a form of data-driven urbanism. At the core of data-driven urbanism is a computational understanding of city systems and domains that reduces urban life to algorithmic and calculative procedures and thus transforms it into a haze of software instructions. This is informed by urban science—a field in which big data science and analytics is practiced, which is increasingly making both smart cities and sustainable cities more sustainable, resilient, efficient, equitable, and livable by rendering them more measurable, knowable, and tractable in terms of their operational functioning, planning, and development. The ultimate aim is to find more effective ways to improve, advance, and maintain the contribution of both smart cities and sustainable cities to the goals of sustainability.

Data-driven smart sustainable cities tend to take several forms in terms of combining the strengths of sustainable cities and smart cities and harnessing the synergy between their strategies and solutions based on how this combination and synergy can be conceptualized and operationalized. As a corollary of this, there is a host of unexplored opportunities to mitigate or overcome the extreme fragmentation of and the weak connection between sustainable cities and smart cities at the technical and policy levels thanks to the fast-flowing torrent of urban data. The vast deluge of contextual and actionable data being generated daily with its new and extensive sources hides the answers to the most challenging analytical questions, as well as the solutions to the most complex challenges pertaining to sustainability. It also provides raw ingredients to build tomorrow’s human engineered systems and plays a key role in understanding urban constituents as data agents. Indeed, numerous opportunities have recently been explored and could be realized in the ambit of data-driven smart sustainable cities.

This Special Issue of Sustainability aims to offer a platform for advancing sustainable cities and smart cities in terms of sustainability, and more importantly for integrating their strategies and solutions within the framework of smart sustainable cities based on data-driven technologies and solutions. The basic idea of data-driven smart sustainable cities as a holistic approach to urbanism is to explicitly bring together sustainable cities and smart cities as urban endeavors in order to build smart sustainable cities in ways that continuously assess, optimize, and enhance their performance with respect to the three dimensions of sustainability as well as their synergistic and balanced integration over the long run.

We encourage researchers, practitioners and scientists to submit original research articles, case studies, reviews, critical perspectives, and viewpoint articles on topics including but not limited to:

  • Smart cities and sustainability;
  • Data-driven urbanism and sustainable development;
  • Sustainable cities and smartness;
  • Urban sustainability and big data technology;
  • Data-driven smart solutions for environmental, economic, and/or social sustainability;
  • Data-driven smart solutions for resilient cities;
  • Environmental, economic, social, and institutional dimensions of smart sustainable cities;
  • Data-driven scientific urbanism for sustainability;
  • Practical examples and best practice insights in emerging data-driven smart sustainable urbanism;
  • IoT- and AI-enabled smart sustainable cities;
  • Socially responsible AI in smart cities and sustainable cities;
  • Data-driven smart urban planning and design;
  • Urban intelligence functions for sustainability;
  • Data-driven smart urban metabolism models;
  • Smart sustainable transport systems, energy systems, and waste systems;
  • Smart public safety and smart healthcare;
  • Opportunities for and challenges of promoting data-driven smart sustainable cities;
  • Physical, infrastructural, social, and institutional transformations needed for promoting data-driven smart sustainable cities.

Dr. Simon Elias Bibri
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Sustainability is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • data-driven smart sustainable cities
  • smart cities
  • sustainable cities
  • smart urbanism
  • data-driven urbanism
  • big data technologies
  • data-driven smart applications
  • urban analytics
  • computational urban science
  • urban intelligence
  • sustainability

Benefits of Publishing in a Special Issue

  • Ease of navigation: Grouping papers by topic helps scholars navigate broad scope journals more efficiently.
  • Greater discoverability: Special Issues support the reach and impact of scientific research. Articles in Special Issues are more discoverable and cited more frequently.
  • Expansion of research network: Special Issues facilitate connections among authors, fostering scientific collaborations.
  • External promotion: Articles in Special Issues are often promoted through the journal's social media, increasing their visibility.
  • e-Book format: Special Issues with more than 10 articles can be published as dedicated e-books, ensuring wide and rapid dissemination.

Further information on MDPI's Special Issue polices can be found here.

Published Papers (4 papers)

Download All Papers
Order results
Result details
Show export options expand_more Show export options expand_less
Select all
Export citation of selected articles as:

Research

23 pages, 3782 KiB  
Article
How to Promote a Smart City Effectively? An Evaluation Model and Efficiency Analysis of Smart Cities in China
by Yufei Fang and Zhiguang Shan
Sustainability 2022, 14(11), 6512; https://doi.org/10.3390/su14116512 - 26 May 2022
Cited by 12 | Viewed by 3391
Abstract
With the rapid development of smart cities, smart city evaluation is receiving an increasing amount of attention. However, the link between the evaluation results of smart cities and the decision making of urban construction roadmap is still relatively lacking. Therefore, it is necessary [...] Read more.
With the rapid development of smart cities, smart city evaluation is receiving an increasing amount of attention. However, the link between the evaluation results of smart cities and the decision making of urban construction roadmap is still relatively lacking. Therefore, it is necessary to quantitatively analyze the evaluation results, to support cities to formulate specific measures for effectively improving their smartness construction. The era of big data gives us the opportunity to evaluate and improve the development of smart cities with urban data. This paper proposes a Capability–Performance–Experience (CPE) evaluation model. An empirical study was conducted with 275 Chinese cities as samples. Principal component analysis and k-means clustering were adopted to classify cities according to their infrastructure readiness level. For each category, multi-linear regression and sensitivity analysis were adopted to analyze the impact of each input factors on each output factors. The results contribute to reasonably design or adjust strategies for smart cities based on their own development stages. Some policy implications are proposed to better prioritize investment in smart cities and to maximize the return on citizens’ experience. Full article
(This article belongs to the Special Issue Smart Sustainable Cities in the Era of Big Data)
►▼ Show Figures

Figure 1

29 pages, 5276 KiB  
Article
Emerging Trends and Knowledge Structures of Smart Urban Governance
by Zaheer Allam, Ayyoob Sharifi, Simon Elias Bibri and Didier Chabaud
Sustainability 2022, 14(9), 5275; https://doi.org/10.3390/su14095275 - 27 Apr 2022
Cited by 10 | Viewed by 7831
Abstract
The concept of smart cities peaked in 2015, bringing an increased influx of ‘smart’ devices in the form of the Internet of Things (IoT) and sensors in cities. As a result, interest in smart urban governance has become more prevalent in administrative, organisational, [...] Read more.
The concept of smart cities peaked in 2015, bringing an increased influx of ‘smart’ devices in the form of the Internet of Things (IoT) and sensors in cities. As a result, interest in smart urban governance has become more prevalent in administrative, organisational, and political circles. This is sustained by both local and global demands for an increased contribution to the goals of sustainability through urban governance processes in response to climate change urgencies. Cities generate up to 70% of global emissions, and in light of societal pressures for more inclusivity and democratic processes, the need for sound urban governance is merited. Further knowledge on the theme of smart urban governance is required to better understand the trends and knowledge structures and better assist policy design. Therefore, this study was undertaken to understand and map the evolution of the concept of smart urban governance through a bibliometric analysis and science mapping techniques using VOSviewer. In total, 1897 articles were retrieved from the Web of Science database over 5 decades, from 1968 to 2021, and divided into three subperiods, namely 1978 to 2015, 2016 to 2019, and 2020 to early 2022. Results indicate that the overall emerging themes across the three periods highlight the need for citizen participation in urban policies, especially in relation to smart cities, and for sustained innovation for e-participation, e-governance, and policy frameworks. The results of this study can aid both researchers exploring the concept of urban governance and policy makers rendering more inclusive urban policies, especially those hosting technological and digital domains. Full article
(This article belongs to the Special Issue Smart Sustainable Cities in the Era of Big Data)
►▼ Show Figures

Figure 1

20 pages, 1814 KiB  
Article
Smart City Governance Evaluation in the Era of Internet of Things: An Empirical Analysis of Jiangsu, China
by Wei-Ling Hsu, Miao Qiao, Haiying Xu, Chunmei Zhang, Hsin-Lung Liu and Yan-Chyuan Shiau
Sustainability 2021, 13(24), 13606; https://doi.org/10.3390/su132413606 - 9 Dec 2021
Cited by 10 | Viewed by 3640
Abstract
With the rapid development of smart cities all over the world, the evaluation of the smart city has become a new research hotspot in the academic circles. Nevertheless, there still exist a series of common problems in current smart city evaluation, including the [...] Read more.
With the rapid development of smart cities all over the world, the evaluation of the smart city has become a new research hotspot in the academic circles. Nevertheless, there still exist a series of common problems in current smart city evaluation, including the cognitive deprivation, lack of experience in planning, low coordination level, etc. Therefore, it is critical to establish a new hierarchy for smart city evaluation indicators, especially in the 5G era. Based on literature review, expert consensus, and the fuzzy analytic hierarchy process, this study developed an innovative smart city evaluation framework. In the framework, an index comprising three dimensions, i.e., smart economy, smart society, and smart environmental protection, as well as several attributes for these dimensions for smart city evaluation were established. Then, taking Jiangsu Province, the fastest-growing province in China, as the research area, the development level of smart city for the cities in Jiangsu was calculated. The results have verified the effectiveness of the framework, which can provide suggestions for sustainable urbanization, and help urban decision-makers to promote the efficient development of smart cities. Full article
(This article belongs to the Special Issue Smart Sustainable Cities in the Era of Big Data)
►▼ Show Figures

Graphical abstract

22 pages, 1042 KiB  
Article
Computational Valuation Model of Housing Price Using Pseudo Self Comparison Method
by Seungwoo Choi and Mun Yong Yi
Sustainability 2021, 13(20), 11489; https://doi.org/10.3390/su132011489 - 18 Oct 2021
Cited by 3 | Viewed by 2245
Abstract
Hedonic pricing method (HPM), which is commonly used for estimating real estate property values, considers the property’s internal and external characteristics for its valuation. Despite its popularity, however, the method lacks the mechanism that directly reflects the target property’s price fluctuation and the [...] Read more.
Hedonic pricing method (HPM), which is commonly used for estimating real estate property values, considers the property’s internal and external characteristics for its valuation. Despite its popularity, however, the method lacks the mechanism that directly reflects the target property’s price fluctuation and the real estate market’s volatility over time. To overcome these limitations, we propose Pseudo Self Comparison Method (PSCM), which reduces the real estate valuation problem to finding a pseudo self, which is defined as a housing property that can most closely approximate the characteristics of the target housing property, and adjusting its previous transaction price to be in sync with the real estate market change. The proposed PSCM is tested for two scenarios in which the volatility of the real estate market varies greatly, using the transaction data compiled from Seoul, the capital of South Korea, and its surrounding region, Gyeonggi. The study results show almost five times lower estimation errors when predicting housing transaction prices using the PSCM compared to the HPM in both scenarios and in both areas. The proposed method is particularly useful for mass valuation of apartments or densely located housing units. Full article
(This article belongs to the Special Issue Smart Sustainable Cities in the Era of Big Data)
►▼ Show Figures

Figure 1

Show export options expand_more Show export options expand_less
Select all
Export citation of selected articles as:
 
Displaying articles 1-4
Back to TopTop