scholarly journals Data-Driven Smart Sustainable Cities of the Future: An Evidence Synthesis Approach to a Comprehensive State-of-the-Art Literature Review

2021 ◽  
pp. 100047
Author(s):  
Simon Elias Bibri
2021 ◽  
Vol 4 (1) ◽  
Author(s):  
Simon Elias Bibri

AbstractIn recent years, it has become increasingly feasible to achieve important improvements of sustainability by integrating sustainable urbanism with smart urbanism thanks to the proven role and synergic potential of data-driven technologies. Indeed, the processes and practices of both of these approaches to urban planning and development are becoming highly responsive to a form of data-driven urbanism, giving rise to a new phenomenon known as “data-driven smart sustainable urbanism.” Underlying this emerging approach is the idea of combining and integrating the strengths of sustainable cities and smart cities and harnessing the synergies of their strategies and solutions in ways that enable sustainable cities to optimize, enhance, and maintain their performance on the basis of the innovative data-driven technologies offered by smart cities. These strengths and synergies can be clearly demonstrated by combining the advantages of sustainable urbanism and smart urbanism. To enable such combination, major institutional transformations are required in terms of enhanced and new practices and competences. Based on case study research, this paper identifies, distills, and enumerates the key benefits, potentials, and opportunities of sustainable cities and smart cities with respect to the three dimensions of sustainability, as well as the key institutional transformations needed to support the balancing of these dimensions and to enable the introduction of data-driven technology and the adoption of applied data-driven solutions in city operational management and development planning. This paper is an integral part of a futures study that aims to analyze, investigate, and develop a novel model for data-driven smart sustainable cities of the future. I argue that the emerging data-driven technologies for sustainability as innovative niches are reconfiguring the socio-technical landscape of institutions, as well as providing insights to policymakers into pathways for strengthening existing institutionalized practices and competences and developing and establishing new ones. This is necessary for balancing and advancing the goals of sustainability and thus achieving a desirable future.


2021 ◽  
Vol 9 (1) ◽  
Author(s):  
Simon Elias Bibri

AbstractAs materializations of trends toward developing and implementing urban socio-technical and enviro-economic experiments for transition, eco-cities have recently received strong government and institutional support in many countries around the world due to their ability to function as an innovative strategic niche where to test and introduce various  reforms. There are many models of the eco-city based mainly on either following the principles of urban ecology or combining the strategies of sustainable cities and the solutions of smart cities. The most prominent among these models are sustainable integrated districts and data-driven smart eco-cities. The latter model represents the unprecedented transformative changes the eco-city is currently undergoing in light of the recent paradigm shift in science and technology brought on by big data science and analytics.  This is motivated by the growing need to tackle the problematicity surrounding eco-cities in terms of their planning, development, and governance approaches and practices. Employing a combination of both best-evidence synthesis and narrative approaches, this paper provides a comprehensive state-of-the-art and thematic literature review on sustainable integrated districts and data-driven smart eco-cities. The latter new area is a significant gap in and of itself that this paper seeks to fill together with to what extent the integration of eco-urbanism and smart urbanism is addressed in the era of big data, what driving factors are behind it, and what forms and directions it takes. This study reveals that eco-city district developments are increasingly embracing compact city strategies and becoming a common expansion route for growing cities to achieve urban ecology or urban sustainability. It also shows that the new eco-city projects are increasingly capitalizing on data-driven smart technologies to implement environmental, economic, and social reforms. This is being accomplished by combining the strengths of eco-cities and smart cities and harnessing the synergies of their strategies and solutions in ways that enable eco-cities to improve their performance with respect to sustainability as to its tripartite composition. This in turn means that big data technologies will change eco-urbanism in fundamental and irreversible ways in terms of how eco-cities will be monitored, understood, analyzed, planned, designed, and governed. However, smart urbanism poses significant risks and drawbacks that need to be addressed and overcome in order to achieve the desired outcomes of ecological sustainability in its broader sense. One of the key critical questions raised in this regard pertains to the very potentiality of the technocratic governance of data-driven smart eco-cities and the associated negative implications and hidden pitfalls. In addition, by shedding light on the increasing adoption and uptake of big data technologies in eco-urbanism, this study seeks to assist policymakers and planners in assessing the pros and cons of smart urbanism when effectuating ecologically sustainable urban transformations in the era of big data, as well as to stimulate prospective research and further critical debates on this topic.


foresight ◽  
2019 ◽  
Vol 21 (4) ◽  
pp. 482-496 ◽  
Author(s):  
Eldar Sedaghatparast

Purpose This paper aims to depict an extensive and cohesive picture of future banking’s dimensions and components. Design/methodology/approach A two-step qualitative approach has been applied. First, an extensive scanning has been carried out to identify megatrends and best practices. Second, applying meta-synthesis analysis, more than 186 up-to-date references were strategically scanned to elicit dimensions and components of future banking. Findings This research has had twofold findings. The direct and explicit results were the main dimensions of banking in the future: information technology, employees, customers, diversified services, organizational structures and farsightedness. The implicit findings were also remarkable: many entities are thinking about future of banking, mostly in financial technology dimension; the departure from traditional banking has recently been accelerated; and more works need to be done to have a comprehensive map of banking in the future. Research limitations/implications As the research methodology was based upon a literature review, it lacks covering some hidden or less flashing dimensions such as future business models, merging between banks and other financial or technological firms in advance, the evolution of organizational structures, etc., which would be captured by applying other methods such as expert Delphi panels. Practical implications Planners in the banking industry can benefit from the direct findings. They may extend the results, customize and prioritize the components to provide a competitive business model in the future market of banking. Originality/value The novelty of this paper lies in a cohesive representation of future banking dimensions and components, which is created by a systematic methodology and broad literature review.


2021 ◽  
Vol 9 (1) ◽  
Author(s):  
Simon Elias Bibri

AbstractThe increased pressure on cities has led to a stronger need to build sustainable cities that can last. Planning sustainable cities of the future, educated by the lessons of the past and anticipating the challenges of the future, entails articulating a multi-scalar vision that, by further interplaying with major societal trends and paradigm shifts in science and technology, produce new opportunities towards reaching the goals of sustainability. Enabled by big data science and analytics, the ongoing transformative processes within sustainable cities are motivated by the need to address and overcome the challenges hampering progress towards sustainability. This means that sustainable cities should be understood, analyzed, planned, designed, and managed in new and innovative ways in order to improve and advance their contribution to sustainability. Therefore, sustainable cities are increasingly embracing and leveraging what smart cities have to offer in terms of data-driven technologies and applied solutions so as to optimize, enhance, and maintain their performance and thus achieve the desired outcomes of sustainability—under what has been termed “data-driven smart sustainable cities.” Based on a case study analysis, this paper develops an applied theoretical framework for strategic sustainable urban development planning. This entails identifying and integrating the underlying components of data-driven smart sustainable cities of the future in terms of the dimensions, strategies, and solutions of the leading global paradigms of sustainable urbanism and smart urbanism. The novelty of the proposed framework lies in combining compact urban design strategies, eco-city design strategies and technology solutions; data-driven smart city technologies, competences, and solutions for sustainability; and environmentally data-driven smart sustainable city solutions and strategies. These combined have great potential to improve and advance the contribution of sustainable cities to the goals of sustainability through harnessing its synergistic effects and balancing the integration of its dimensions. The main contribution of this work lies in providing new insights into guiding the development of various types of strategic planning processes of transformative change towards sustainability, as well as to stimulate and inspire future research endeavors in this direction. This study informs policymakers and planners about the opportunity of attaining important advances in sustainability by integrating the established models of sustainable urbanism and the emerging models of smart urbanism thanks to the proven role and untapped potential of data-driven technologies in catalyzing sustainable development and thus boosting sustainability benefits.


2021 ◽  
Vol 1 (1) ◽  
Author(s):  
Simon Elias Bibri

AbstractSustainable cities are quintessential complex systems—dynamically changing environments and developed through a multitude of individual and collective decisions from the bottom up to the top down. As such, they are full of contestations, conflicts, and contingencies that are not easily captured, steered, and predicted respectively. In short, they are characterized by wicked problems. Therefore, they are increasingly embracing and leveraging what smart cities have to offer as to big data technologies and their novel applications in a bid to effectively tackle the complexities they inherently embody and to monitor, evaluate, and improve their performance with respect to sustainability—under what has been termed “data-driven smart sustainable cities.” This paper analyzes and discusses the enabling role and innovative potential of urban computing and intelligence in the strategic, short-term, and joined-up planning of data-driven smart sustainable cities of the future. Further, it devises an innovative framework for urban intelligence and planning functions as an advanced form of decision support. This study expands on prior work done to develop a novel model for data-driven smart sustainable cities of the future. I argue that the fast-flowing torrent of urban data, coupled with its analytical power, is of crucial importance to the effective planning and efficient design of this integrated model of urbanism. This is enabled by the kind of data-driven and model-driven decision support systems associated with urban computing and intelligence. The novelty of the proposed framework lies in its essential technological and scientific components and the way in which these are coordinated and integrated given their clear synergies to enable urban intelligence and planning functions. These utilize, integrate, and harness complexity science, urban complexity theories, sustainability science, urban sustainability theories, urban science, data science, and data-intensive science in order to fashion powerful new forms of simulation models and optimization methods. These in turn generate optimal designs and solutions that improve sustainability, efficiency, resilience, equity, and life quality. This study contributes to understanding and highlighting the value of big data in regard to the planning and design of sustainable cities of the future.


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