Keywords

1 Introduction

During the last two years, cities around the world dealt with the impact and spread of the COVID-19 pandemic with unprecedented speed, due to our hyper-connected society (Aditi et al. 2020). There is growing evidence that anthropogenic impacts on ecological systems and the different challenges which the world faces: population growth; globalization; pandemic diffusions; climate change, and the consequent environmental degradation are now the main driver of planetary change needing more adaptability and innovation to promote health and well-being in cities.

The lesson learned from the COVID-19 pandemic is that people's health is connected and closely dependent on the planet’s health, and cities play an important role in this relationship (Capolongo et al. 2020). With the urban population set to increase over time, leading to a world population of 9.3 billion in 2050 (Chelleri 2012) the difficult undertaking of global sustainability rests largely on urbanization processes. Cities are defined as intricate systems consisting of social, ecological, and economic dimensions responsible for many of the trends considered unsustainable that push our planet beyond its ecological boundaries of development.

The present chapter aims to show how urbanization and the different challenges have modified the way people and communities live, work, and interact during the time and it is, therefore, even more, necessary than in the past, to adopt a multidisciplinary approach to the development of systemic operational skills that can address complex issues within cities through the use of Key Performance Indicators (KPI), and in this way, the problem exposed by the coronavirus pandemic is a perfect scenario for thinking cities in a more resilient and sustainable way.

Our understanding of cities has certainly changed, and this situation has inevitably turned out to be an unprecedented alarm bell that has highlighted the system's poor understanding of the risk’s nature and interdependencies between sectors, showing more attention in the implementation of NBSs within urban contexts in response to current problems.

Since its first applications, the NBSs approach has always wanted to be seen as a way of supporting human life and activities, addressing different societal challenges in terms of multiple benefits or ecosystem services. Given the complexity of cities, the need for a healthier environment is increasingly recognized as well as the importance of connecting urban space with natural areas. The sanitary crisis has offered an opportunity to re-think the relationship between cities and nature and the possibility of channeling the urban technological transition to counteract climate change, support biodiversity, reduce pollution, and improve the well-being of inhabitants.

Today we need to develop transdisciplinary methodologies using new tools for the development of integrated measures that adequately address different economic, social, environmental, and political aspects to promote health and well-being in cities. On these front scenarios and indicators stand as means to simplify and reduce the complexity of the real world to a potentially high but limited number of factors, analyzing and monitoring their interaction aimed at supporting the formulation of policies.

2 Methodology

The goal of this chapter is to propose a clear and simple methodology analysis that can be replicated in all urban contexts, through the creation of a specific set of indicators, to analyze the level of local sustainability, especially at the neighborhood scale. The use of indicators within the decision-making processes allows a better understanding of the data (Angelakoglou et al. 2019) and the possibility of evaluating the expected impacts to direct future policies for the redesign of post-pandemic cities (Moghadam and Lombardi 2018).

The proposed methodological framework is developed in two different phases: (Phase 1) Indicator selection and (Phase 2) Baseline scenario, with the aim of investigating the neighborhood scale, placing the city as a new generator of public health (Fig. 5.1).

Fig. 5.1
A chart of future development has 4 columns and 3 rows. The column headers are preselection, feedback, final selection, and baseline scenarios. The rows are goals, methods, and tools.

Methodological framework

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The proposed two phases allow the development of an appropriate vocabulary and lexicon aimed at analyzing the responsiveness of the territory, and in this case, the experiments were carried out for the Municipality of Turin, experimenting with the city of proximity as an urban planning pandemic response. Measuring, evaluating, and spatially visualizing the impact are the keys to the proposed evaluation process.

The proposed methodological framework intends to select and evaluate, from the set of final selected indicators, those that are defined as the Key Performance Indicators (KPI) (Genta et al. 2019), considered mandatory. To be as site-specific as possible, we started with the application of the experimentation to the neighborhood scale, especially for the City of Turin within the “Crocetta” neighborhood, the seat of the Polytechnic of Turin’s University, to become a pilot project to be adapted to the whole municipal area.

The different phases of the work are presented below:

2.1 Phase 1: Indicators Selection

The first phase of the work has the ultimate aim of measuring the level of sustainability and local proximity on the scale of the neighborhood by quantifying the phenomena that constitute it, thus producing the data necessary for the subsequent phase, the operational phase of quantifying the impacts. The proposed phase is structured in three different steps: Pre-selection, Feedback, and Final selection.

Steps will be detailed as follows:

2.1.1 Phase 1.1 Pre-selection

The objective of this phase is to pre-select the indicators that are more consistent with the final objective of the research to obtain the first set. The method was to read the indicators already consolidated over time, proposed within various projects and territorial databases, adapting them to the specifications of the Post Un-lock Project, modifying their descriptions and units of measurement. Starting from the consultation of the more than 700 indicators contained in the 10 sources used (Global Reference List of 100 Core Health Indicators; COVID-19 Dashboard Center; UN Habitat; ISTAT 2020; BES 2020; Italian Association of Epidemiology; ARPA; LEGAMBIENTE; CesbaMED; MOLOC), a careful selection was made, reaching the first selection of 29 pre-selected indicators. Particular attention to the choice of indicators was paid to the scale of analysis, to the availability of data, and finally to the relative possibility of calculation and relative measurement.

2.1.2 Phase 1.2 Feedbacks

From the earliest stages of this methodology, it was essential to identify the Stakeholders to be involved in the decision-making process to obtain expert opinions on the subject. Within this phase, the 29 pre-selected indicators in the first phase were submitted to the expert opinion of the Stakeholders within the present Post Un-lock project, to understand the indicators that, compared to the project, were more suitable. Their involvement in the decision-making process represented a very important step as it helped to know the existing data available, to determine the relevant objectives and to propose a final common strategic vision concerning the project (Genta et al. 2019).

The objective of this phase, through the compilation of a questionnaire in Google Modules, was that of the hierarchization of the post-COVID indicators by assigning them a score from 0 to 4 ((0 = not important at all, 1 = not important, 2 = on average important, 3 = important 4 = very important) to obtain a final list ordered by the value of importance in descending order. The feedbacks obtained were a total of 13, and the indicators as a result of the further changes made in the description and the unit of measurement went from 29 to 26 since 3 were identical. The interesting aspect that emerged from the hierarchization of the values obtained for each indicator is the perfect congruence with the topic under consideration. All 26 indicators turned out to be perfectly calculable indicators at the municipal level for the City of Turin, and in particular, among these 26, 15 indicators were specific to the neighborhood scale.

Since the ultimate goal of this work is to analyze the correlations existing between the urban environment and the proximity level of cities, especially at the neighborhood scale, the last phase of the selection of indicators was to ask oneself, among the 15 indicators on the scale of the neighborhood which were the Key Performance Indicators (KPI).

2.1.3 Phase 1.3 Final Selection

The tool used for the validation of the final set was the conduct of interviews with Stakeholders external to the Post Un-lock Project, asking them to evaluate the importance of the 15 indicators proposed at the neighborhood scale, defining them as “accepted”, “To be modified”, or “rejected”, giving reasons for their choices.

To conduct the interviews, some were carried out via video call, in particular to the local Stakeholders in the Turin context, which allowed the joint discussion of the results obtained and the votes assigned, and other votes were assigned through the compilation of an additional questionnaire, created on Google Modules to be distributed in a widespread manner. For this phase, the Stakeholders who provided their assessment were a total of 50, thus making the analysis as complete as possible and achieving the initial set of objectives.

The results obtained showed that all 15 indicators proposed on the neighborhood scale have been defined as “accepted”, thus resulting in the specific KPIs of the project (Table 5.1), confirming the attention paid in the previous phase of pre-selection of the indicators, and having proposed extremely specific and priority indicators.

Table 5.1 Key performance indicators (KPIs) at the neighborhood scale
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Although the choice of indicators always involves a subjective evaluation or, in any case, a link with the professional deformation of the discipline that a stakeholder represents, the selection process has shown that it has implemented a scientific and robust approach and, with the wide participation obtained, led to a balanced result inherent in the territorial context under study (Pignatelli 2020). Below is the list of the 15 validated KPIs:

2.2 Phase 2: A Baseline Scenario

The validation of the KPIs (Fig. 5.2) and the related calculation methodologies, units of measurement, and tools introduced the project to the next phase: the operational phase that is concerned their mapping and numerical quantification.

Fig. 5.2
3 charts present the final set of post-COVID indicators. 1. Municipal level has 26 optionals. 2. Neighborhood scale has 15 K P I's in a circle and 11 optionals outside. 3. Baseline scenario has 6 priority K P I's, 9 K P I's in a circle, and 11 optionals outside.

Presentation of the final set of post-COVID indicators

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The objective was to obtain the basic data and materials for the calculation of the selected post-COVID indicators, data that had to be updated, corrected, extensible to the entire municipal area georeferenced as much as possible.

The results obtained from the spatialization of the first 6 KPIs (Table 5.1) for which the relative technical data sheets containing the calculation procedures have been developed are shown below. The technical sheets produced for each selected KPI have been divided into Intent—explanation of the indicator and its specificity concerning the project; Evaluation method structured in Data requirements, Source of data, Evaluation method; and finally, the relative Results, maps showing the spatialized and calculated indicators.

The present indicators have been evaluated through spatial models and tools of the geographic information system (GIS) to map the results, and consequently, the method implements a new system based on multi-criteria indicators to support the decision-making process (Pignatelli 2020) and evaluate the neighborhood performance within the neighborhood.

This phase also concerned the application to the case study by experimenting with the methodology proposed within the “Crocetta” district of the Municipality of Turin. The choice of this district derives from the fact that it has been the seat of the Polytechnic of Turin since 1950 and from being a district in which there are important functions such as the Torino Porta Nuova railway station, the presence of three underground stations, and the Mauriziano Hospital, one of the main hospitals in the city.

3 Results

From the spatialization, evaluation, and analysis of the current state of the neighborhood, it has emerged that the “Crocetta” neighborhood represents one of the best-equipped neighborhoods in terms of services within its municipal area, in particular the small and large distribution, internal school services, and health services were analyzed. Indeed, from the analysis of their availability and proximity, it has emerged that all the residential buildings in the neighborhood are supplied at a walking distance of about 10/15 min (Balletto et al. 2020).

From the cross-reading between the availability of services and the number of transport modes present within it, the widespread distribution of bus stops, as well as other faster forms of transport such as underground and train, was demonstrated, allowing for a connection of the district with all parts of the city.

The presence of the Polytechnic of Turin plays a very important role for the district in promoting and encouraging its students to travel with sustainable mobility, since it can be seen that among the 13 Bike-sharing stations present for the entire district, 5 are close to the university as a means of travel most used by students who are attentive and sensitive to these issues, with 11 km of cycle paths available.

The neighborhood shows a scarce availability of internal urban green areas. Only 8% of the total area is covered by green areas (0.25 km2 out of 3.4 available), demonstrating the extensive waterproofing of the total area of the district (92%).

4 Conclusion and Future Developments

In this chapter, a proposed methodological framework has been proposed in order to investigate the correlations between the urban environment (Pirni et al. 2020) and the level of proximity of the cities for the Basic Scenario of the city of Turin at the neighborhood scale, providing objective results on which future actions can be based.

For what has been said, a city that promotes proximity in the urban context in balance is farsighted, capable of planning and building its future by adapting to the unpredictable emerging challenges, such as the recent health emergency, thus being able to sustain, regenerate and re-establish a new balance within the urban environment. An effective assessment of complexity, differentiated for each territorial system, is necessary to develop and implement successful strategies to achieve common objectives. For this reason, multi-criteria analysis tools, analysis of qualitative and quantitative indicators, and performance evaluations able to measure the effectiveness of actions before their implementation are becoming increasingly important (Genta et al. 2019).

Based on the analysis of the post-COVID indicators proposed in this study, in particular the evaluation of the Key Performance Indicators, it was possible to highlight the weak points and priority areas on which to act, experimenting with the theme of “experiencing proximity to the neighborhood scale” as an urban response to the pandemic.

Measuring, evaluating, and spatially visualizing the impact were the keys to the proposed evaluation process, and the methodology resulted:

Replicable: The proposed methodology allows it to be replicated in all urban contexts.

Adaptable: An adequate methodology has been provided to create one’s own set of indicators on which to base the analyses according to the topic being studied.

Accurate: The analyses were conducted at the neighborhood scale to be as accused as possible.

Specification: The proposed methodology allows to identify of the key indicators of the project (KPI).

The following are the main recommendations for future developments and implementations:

Evaluation and spatialization of the entire final set: This work experimented with the methodology proposed at the neighborhood level, developing the first 6 most priority KPIs one year after the start of the project. It is hoped that the methodology will then be applied to the entire municipal area by the Post Un-lock Project to obtain a general and broader picture of the situation.

Development of future scenarios: An extremely interesting aspect, which would further enrich this work, is the development of future scenarios. This would allow the comparison of urban assets before and after the modification, thus being able to compare the situations across different time-frames.

In this context, the methodology proposed in this study can provide the appropriate starting point for future research works based on the analysis of indicators and the use of multi-criteria spatial decision support systems, thus confirming the initial objectives set.