Input-Output Modeling for Smart City Development

Noori, Negar; Jong, Martin de; Janssen, Marijn; Schraven, Daan; Hoppe, Thomas

doi:10.1080/10630732.2020.1794728

Cited by 35 publications

(17 citation statements)

References 64 publications

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“…This conceptualization utilizes the Input-Process-Output-Impact approach [80]. As the key 'input', we have the city and its indigenous assets.…”

Section: Smart and Sustainable Cities: An Urban Focus To Achieve Sustainabilitymentioning

confidence: 99%

“…In other words, technology will only lead to sustainability if its adequateness is thoroughly scrutinized via community engagement, and its implementation is carried out via a sound policy and government monitoring [79]. This conceptualization utilizes the Input-Process-Output-Impact approach [80]. As the key 'input', we have the city and its indigenous assets.…”

Section: Smart and Sustainable Cities: An Urban Focus To Achieve Sustainabilitymentioning

confidence: 99%

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The Sustainability of Artificial Intelligence: An Urbanistic Viewpoint from the Lens of Smart and Sustainable Cities

2020

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The popularity and application of artificial intelligence (AI) are increasing rapidly all around the world—where, in simple terms, AI is a technology which mimics the behaviors commonly associated with human intelligence. Today, various AI applications are being used in areas ranging from marketing to banking and finance, from agriculture to healthcare and security, from space exploration to robotics and transport, and from chatbots to artificial creativity and manufacturing. More recently, AI applications have also started to become an integral part of many urban services. Urban artificial intelligences manage the transport systems of cities, run restaurants and shops where every day urbanity is expressed, repair urban infrastructure, and govern multiple urban domains such as traffic, air quality monitoring, garbage collection, and energy. In the age of uncertainty and complexity that is upon us, the increasing adoption of AI is expected to continue, and so its impact on the sustainability of our cities. This viewpoint explores and questions the sustainability of AI from the lens of smart and sustainable cities, and generates insights into emerging urban artificial intelligences and the potential symbiosis between AI and a smart and sustainable urbanism. In terms of methodology, this viewpoint deploys a thorough review of the current status of AI and smart and sustainable cities literature, research, developments, trends, and applications. In so doing, it contributes to existing academic debates in the fields of smart and sustainable cities and AI. In addition, by shedding light on the uptake of AI in cities, the viewpoint seeks to help urban policymakers, planners, and citizens make informed decisions about a sustainable adoption of AI.

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“…This conceptualization utilizes the Input-Process-Output-Impact approach [80]. As the key 'input', we have the city and its indigenous assets.…”

Section: Smart and Sustainable Cities: An Urban Focus To Achieve Sustainabilitymentioning

confidence: 99%

Section: Smart and Sustainable Cities: An Urban Focus To Achieve Sustainabilitymentioning

confidence: 99%

The Sustainability of Artificial Intelligence: An Urbanistic Viewpoint from the Lens of Smart and Sustainable Cities

2020

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“…Pevcin (2019) observes that research funding has driven the numbers and direction of publications on smart cities. The utilization of the smart city concept can also be attributed to the so-called technology push [84].…”

Section: Discussionmentioning

confidence: 99%

Evidence-Based Public Policy Decision-Making in Smart Cities: Does Extant Theory Support Achievement of City Sustainability Objectives?

et al. 2021

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Evidence-based decision making is promoted as offering efficiency and effectiveness; however, its uptake has faced barriers such as underdeveloped supporting culture, limited access to evidence, and evidence that is not fully relevant. Smart city conceptualizations offer economic and environmental sustainability and better quality of life through evidence-based policy decision-making. We wondered whether smart city theory and practice has advanced the knowledge of evidence-based decision-making. We searched major databases for literature containing a mention of smart cities, decision-making, and policy. We identified relevant literature from a range of disciplines and supplemented these by following backwards and forwards citations. Evidence-based decision-making was found mostly in literature regarding the theory and practice of smart city operations, and, to lesser extents, the articles regarding policy decisions and tactical decisions. Better decision-making which supported the achievement of city sustainability objectives was reported in some articles; however, we found significant obstacles to the further achievement of city objectives in the areas of underachievement in collaborative decision-making, privileging of big data evidence, and artificial intelligence agents as decision-makers. We assembled a definition of smart city decision-making and developed an agenda of research which will support city governments, theorists, and practitioners in better achieving sustainability through improved decision-making.

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“…Blockchain will -logically-so -not solve government corruption on its own and requires other contextual considerations for a transition to less corrupt governments. Following these assumptions, an outline of the elements to be included in the diffusion model is created by critically evaluating the Theory of Change (ToC) [3] and the Input-Output (IO) model [25]. A ToC describes "how and why an intervention is assumed to lead to a desired end-result" [22].…”

Section: Data Collection and Methodologymentioning

confidence: 99%

A Smart Governance diffusion model for blockchain as an anti-corruption tool in Smart Cities

Parenti

Noori

Janssen

2022

SCS

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Government corruption in Latin America prevents the region’s sustainable development and constitutes a failure of current systems. Governments have started to leverage new technologies to increase transparency and promote integrity within their processes. Among these, blockchain technology has gained traction as a promising tool for Smart Governance due to its unique properties in terms of immutability, trust, coordination, security, and transparency. The use of blockchain within Smart City initiatives is complicated by a lack of diffusion models. This paper develops a diffusion model for blockchain technology after analyzing three case studies and conducting a survey of thirty blockchain start-up leads across Latin America. The final model, named Smart Governance BT diffusion model, conceptualizes the diffusion of blockchain as a gradual process including inputs, a dynamic throughput, and outputs. Relevant for academics and government representatives alike, the model aims at improving the conceptual understanding of technology diffusion in Smart Cities and highlights the potential of blockchain as a mitigator of vulnerabilities to corruption. As initial conditions matter for its successful adoption and diffusion, it is recommended for Latin American governments to (1) redesign and digitalize their processes and legislation, (2) conduct a thorough cost-benefit analysis for specific use cases, and (3) reduce inefficiencies in areas with relatively medium to low levels of historical corruption in a first instance. The model can be tested and refined in future research and can be applied to any Smart City initiative requiring conceptualization.

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Input-Output Modeling for Smart City Development

Cited by 35 publications

References 64 publications

The Sustainability of Artificial Intelligence: An Urbanistic Viewpoint from the Lens of Smart and Sustainable Cities

The Sustainability of Artificial Intelligence: An Urbanistic Viewpoint from the Lens of Smart and Sustainable Cities

Evidence-Based Public Policy Decision-Making in Smart Cities: Does Extant Theory Support Achievement of City Sustainability Objectives?

A Smart Governance diffusion model for blockchain as an anti-corruption tool in Smart Cities

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