The complexity of urban systems is well-known, with cities representing intricate webs of social, economic, and environmental factors that shape their development over time. During periods of transition, such as those caused by economic or environmental shocks, these factors become even more pronounced, making it difficult to anticipate and respond to changes. To address this challenge, this research explores the use of resiliency as a lens for understanding the complex nature of urban contexts in the transition phase, with a particular focus on discovering hidden perspectives. The research is based on the TREnD project, which aims to address disparities in European regions and cities. To develop a conceptual framework for picturing a complex system (urban area) in transition, the research utilizes a mixed-method strategy. The first step is to identify the ongoing process of learning by doing, which the research refers to as resilience. Resilience is seen as an endogenous characteristic of the transition process, which is critical to understanding how urban systems respond to change. To assess the theoretical model, the research employs a range of quantitative methods. Big-data analysis is used to map the network of interconnectedness between cities and innovation drivers. Descriptive models are used to interpret the nature of the transition process, allowing the research to identify patterns and trends that might not be visible otherwise. Borrowing theories from biology, mathematics, and complex systems, the research emphasizes the importance of a long-term approach to structural change, rather than a one-size-fits-all method. The research also places special attention on technology as a unique approach to quantifying theories on a measurable ground during this effort. By analyzing technological advancements in different regions and cities, the research seeks to identify the factors that drive innovation and resilience. This focus on technology provides a novel perspective on urban systems, highlighting the importance of understanding how technology is integrated into the fabric of cities and regions. To test the theoretical model, the research applies suggested models in two case studies. The first case study focuses on Calabria, a European region with a long history of structural issues. The second case study focuses on Boston, one of the well-known innovative areas of the American continent. These case studies provide a detailed picture of how resilience and technological innovation operate in different urban contexts, highlighting the importance of place-based methods for measuring and understanding these concepts. The TREnD project serves as the principal rationale for the research, providing a rich source of data and insights into the complex nature of urban contexts. The research focuses on a place-based method for measuring technological resilience, which can be used by policymakers, communities, and scientific fellows to deal with this complex issue. To achieve these goals, the research introduces a series of algorithms, network mapping, distance heatmaps, and conceptual frameworks. By using these tools, the research aims to provide a more comprehensive understanding of the complex nature of urban systems, and to identify the factors that drive resilience and innovation
La complessità dei sistemi urbani è ben nota, con le città che rappresentano intricati intrecci di fattori sociali, economici ed ambientali che plasmano il loro sviluppo nel tempo. Durante i periodi di transizione, come quelli causati da shock economici o ambientali, questi fattori diventano ancora più evidenti, rendendo difficile anticipare e rispondere ai cambiamenti. Per affrontare questa sfida, questa ricerca esplora l'uso della resilienza come lente per comprendere la complessa natura dei contesti urbani nella fase di transizione, con particolare attenzione alla scoperta di prospettive nascoste. La ricerca si basa sul progetto TREnD, che mira a ridurre le disparità nelle regioni e città europee. Per sviluppare un quadro concettuale per rappresentare un sistema complesso (area urbana) in transizione, la ricerca utilizza una strategia mista. Il primo passo consiste nell'identificare il processo in corso di apprendimento attraverso l'azione, che la ricerca definisce resilienza. La resilienza è vista come una caratteristica endogena del processo di transizione, che è fondamentale per comprendere come i sistemi urbani rispondono ai cambiamenti. Per valutare il modello teorico, la ricerca utilizza una serie di metodi quantitativi. L'analisi di big data viene utilizzata per mappare la rete di interconnessione tra città e fattori di innovazione. I modelli descrittivi vengono utilizzati per interpretare la natura del processo di transizione, consentendo alla ricerca di identificare modelli e tendenze che potrebbero non essere visibili altrimenti. Attingendo a teorie provenienti dalla biologia, dalla matematica e dalla complessità dei sistemi, la ricerca enfatizza l'importanza di un approccio a lungo termine al cambiamento strutturale, anziché un metodo universale. La ricerca pone anche particolare attenzione alla tecnologia come approccio unico per quantificare le teorie su un terreno misurabile durante questo sforzo. Analizzando i progressi tecnologici in diverse regioni e città, la ricerca cerca di identificare i fattori che guidano l'innovazione e la resilienza. Questo focus sulla tecnologia fornisce una prospettiva innovativa sui sistemi urbani, evidenziando l'importanza di comprendere come la tecnologia sia integrata nella struttura delle città e delle regioni. Per testare il modello teorico, la ricerca applica i modelli suggeriti in due studi di caso. Il primo studio di caso si concentra sulla Calabria, una regione europea con una lunga storia di problemi strutturali. Il secondo studio di caso si concentra su Boston, una delle aree innovative più note del continente americano. Questi studi di caso forniscono un'immagine dettagliata di come la resilienza e l'innovazione tecnologica operino in contesti urbani diversi, evidenziando l'importanza dei metodi basati sul luogo per misurare e comprendere questi concetti. Il progetto TREnD serve come principale razionale del progetto, fornendo un quadro concettuale per la comprensione della resilienza urbana e dei fattori che la influenzano. La ricerca si concentra in particolare sul metodo basato sul luogo per misurare la resilienza tecnologica, fornendo ai policy maker, alle comunità e ai ricercatori scientifici un approccio innovativo per affrontare le sfide della transizione urbana. Utilizzando algoritmi, mappe di rete, heatmap di distanza e quadri concettuali, questa ricerca fornisce un'immagine dettagliata dei sistemi urbani in transizione, offrendo un quadro concettuale per comprendere come questi sistemi evolvono nel tempo
Managing urban transition. Place-sensitive approach towards technological resilience / Sohrabi, Poya. - (2023 Apr 17).
Managing urban transition. Place-sensitive approach towards technological resilience
Sohrabi, Poya
2023-04-17
Abstract
The complexity of urban systems is well-known, with cities representing intricate webs of social, economic, and environmental factors that shape their development over time. During periods of transition, such as those caused by economic or environmental shocks, these factors become even more pronounced, making it difficult to anticipate and respond to changes. To address this challenge, this research explores the use of resiliency as a lens for understanding the complex nature of urban contexts in the transition phase, with a particular focus on discovering hidden perspectives. The research is based on the TREnD project, which aims to address disparities in European regions and cities. To develop a conceptual framework for picturing a complex system (urban area) in transition, the research utilizes a mixed-method strategy. The first step is to identify the ongoing process of learning by doing, which the research refers to as resilience. Resilience is seen as an endogenous characteristic of the transition process, which is critical to understanding how urban systems respond to change. To assess the theoretical model, the research employs a range of quantitative methods. Big-data analysis is used to map the network of interconnectedness between cities and innovation drivers. Descriptive models are used to interpret the nature of the transition process, allowing the research to identify patterns and trends that might not be visible otherwise. Borrowing theories from biology, mathematics, and complex systems, the research emphasizes the importance of a long-term approach to structural change, rather than a one-size-fits-all method. The research also places special attention on technology as a unique approach to quantifying theories on a measurable ground during this effort. By analyzing technological advancements in different regions and cities, the research seeks to identify the factors that drive innovation and resilience. This focus on technology provides a novel perspective on urban systems, highlighting the importance of understanding how technology is integrated into the fabric of cities and regions. To test the theoretical model, the research applies suggested models in two case studies. The first case study focuses on Calabria, a European region with a long history of structural issues. The second case study focuses on Boston, one of the well-known innovative areas of the American continent. These case studies provide a detailed picture of how resilience and technological innovation operate in different urban contexts, highlighting the importance of place-based methods for measuring and understanding these concepts. The TREnD project serves as the principal rationale for the research, providing a rich source of data and insights into the complex nature of urban contexts. The research focuses on a place-based method for measuring technological resilience, which can be used by policymakers, communities, and scientific fellows to deal with this complex issue. To achieve these goals, the research introduces a series of algorithms, network mapping, distance heatmaps, and conceptual frameworks. By using these tools, the research aims to provide a more comprehensive understanding of the complex nature of urban systems, and to identify the factors that drive resilience and innovationFile | Dimensione | Formato | |
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