Navigating the Green Transition During the Pandemic Equitably: A New Perspective on Technological Resilience Among Boston Neighborhoods Facing the Shock

Cities, public authorities, and private organizations respond to climate change with various green policies and strategies to enhance community resilience. However, these community-level transition processes are complex and require deliberate and collective planning. Under this context, the purpose of this study is to understand the energy actions taken at the local level, as well as to analyze the differences between the neighborhoods’ green energy transitions in terms of their socio-economic aspects, using a big data perspective. The paper is addressing the following question: what was the role that the pandemic played in accelerating or slowing Boston’s green investments, and to what extent do different racial and socioeconomic groups invest in green technologies during this period? The study aims to answer these research questions using the City of Boston as a case study to reveal different neighborhoods’ paths in achieving the transformation of city ecosystems towards green neutrality. Next, the theoretical framework builds the linkages among the city’s measures, climate actions proposed by the City of Boston, and their associated contexts and outcomes in shaping new policy and planning models for higher ‘green’ performance. Following the understanding of the actions, the neighborhoods’ socio-economic and building permit data were assessed to understand whether economic disparities exacerbated during the pandemic have affected neighborhoods’ performance in green transition. This method is applied in a comparative study of its 23 neighborhoods, using a dataset provided by Boston Area Research Initiative (BARI). Intriguingly, the paper’s findings show that racial differences within the city have no significant impact on tech-related expenditures. There is a clear negative correlation between poverty rate and investment, which indicates the reverse relationship between these socio-economic factors. The study concludes that city authorities will need to address the challenges of each community achieving green transition with more targeted programs based on its needs

Networking analysis in the urban context: Novel instrument for managing the urban transition

Nowadays, the insurgence of shocks in every dimension of life is questioning the effect of globalization on the urbanization process. The exposition to risks, related to the impact of continuous environmental and economic shocks, seems, in turn, increasingly connected to high urbanization processes. Among a variety of specific vulnerability factors that can influence the life of the population in each settlement, two sources of them seem to be generalized: Higher levels of income inequality spread in urban areas, the concentration of knowledge complexity in large cities. Traditional urbanization theory has become hard to interpret these changes on a global scale, and “innovation” is a core concept to explain the new differences in the urbanization dynamics. The paper aims to combine urban and innovation policy towards the post-Europe 2020 Strategy, as a scientific advance in urban and regional studies within innovation policy design. It is argued that this combination is a crucial need due to the pivotal role that the city is acquiring in managing adaptation to shocks and in designing new approaches in line with the Just Transition mechanism introduced by the European Union. The paper argues that in light of a completely new scenario of development, especially after the pandemic, due to the necessity to make a transition towards sustainability, the traditional approach of analyzing the context to drive the political choices of transition need to change. Data analytics is acquiring importance in the decision making that required to be faster due to the continuous and unpredictable shocks are facing us. The technological progress, the engine of development is crucial in driving cities and territories towards a transition to a post-carbon economy. Since the city transition is not formal top-down management, the network modeling of this structure and the complexity of the component would be an exciting approach. Network analysis, both as a tool to measure the change and as a new framework for urban management, could play an essential role for policymakers to develop a responsive dashboard that benefits from local data to generate place sensitive materials for decisions. The urban system is consistently facing turbulence which leads politicians to convert them to a path to analysis, this point of translating the routine tensions into the challenges following a pattern of emergence and remedies to a cure are resilience building. Defining urban resilience in city level is double-sided sward however it grasps the prosperity of the innovation tightly, but would stem educational shields for fresh ideas required incubators to grow. The expected result is to explain how applying the networking analysis at the urban level can change the perspective of urban planning, create an Ex-ante mechanism based on network modeling for policymakers to foresight trajectories based on their decision could depict an utterly novel approach in urban management tools

Spatializing Social Networking Analysis to Capture Local Innovation Flows towards Inclusive Transition

The location of the local network of firms impacts, positively or negatively, their economic performance. The interactions between different sectors in a territory are still not easily observable. We test the complexity of the economic structure at a local level, given the availability of data at a very granular scale. This could greatly assist in observing sectors or/and locations that play a dominant role in the regional economy. Thus, in order to interpret the economic structure of a territory, we used cluster-based analysis. The analysis helps in evaluating the interconnections among sectors that constitute a cluster. A novel method of describing the territorial economic structure is presented by applying Social Network Analysis (SNA) within cluster-based analysis to characterize the importance of both location and economic interconnections. In this study, we focus on the industrial agglomerations in Calabria, Italy, to underpin the potential of the region’s industries by using social networking analysis metrics. This research put forward new interpretations of SNA metrics that describe regional economic compositions. Our findings reveal that territorial social networks are a potential instrument for understanding interactions in regional systems and economic clusters and might help in highlighting local industrial potentials. We believe that this study’s results could be considered as the initial steps for a pioneer data-driven place-based structural analysis model