Real Estate Market Dynamics in the City of Naples: an Integration of a Multi-Criteria Decision Analysis and Geographical Information System

sustainability

Article Real Estate Market Dynamics in the City of Naples: An Integration of a Multi-Criteria Decision Analysis and Geographical Information System

Pasquale De Toro * , Francesca Nocca *, Andrea Renna * and Luigi Sepe *

Department of Architecture, University of Naples Federico II, via Toledo 402, I-80134 Naples, Italy * Correspondence: [email protected] (P.D.T.); [email protected] (F.N.); [email protected] (A.R.); [email protected] (L.S.)

Received: 18 December 2019; Accepted: 5 February 2020; Published: 7 February 2020

Abstract: Urban development and regeneration projects produce multidimensional impacts on the city, on its environmental, economic, and social systems. An aspect that can be considerably affected by urban dynamics is linked to the real estate market. So, analysing real estate dynamics is useful to support decision-makers in the elaboration of urban regeneration plans and projects, and thus orient their choices. Focusing attention on the city of Naples (Italy), the purpose of this paper is to analyse in detail the real estate dynamics in this city through the integration of a Multi-Criteria Decision Analysis (MCDA) method and Geographical Information System (GIS). This integration allowed us to map and analyse the territory, linking a specific issue (the real estate dynamics) to the territory itself, and to analyse it according to specific criteria. This aims for a better understanding and interpretation of real estate dynamics, representing a useful tool for orienting and supporting urban planning strategies.

Keywords: urban regeneration; urban dynamics; real estate prices; ArcGIS; QGIS; geoTOPSIS

1. Introduction Cities are as living organisms, and thus they have their own dynamics, transforming over time to adapt to the ever-changing context, new community needs, and new paradigms [1]. Today, in particular, in this period of growing unsustainability (that is characterized by growing urbanization, social inequalities, and ecological and economic crisis), international organizations (i.e., United Nations) are calling for new urbanization strategies in order to achieve sustainable development of cities and human settlements, making them more “inclusive, safe, resilient and sustainable” (goal 11 of the 2030 Agenda for Sustainable Development) [2,3]. Urban transformation and regeneration produce multidimensional impacts on the city, on its environmental, economic, and social systems. An aspect that can be considerably affected by urban dynamics is linked to the real estate market. Furthermore, social, cultural, environmental, and economic factors affect demand and supply of real estate. There is a very close relationship between the dynamics of urban development and the real estate market, and so analysing real estate dynamics is useful for decision-makers in the elaboration of urban regeneration plans and projects, and thus orient their choices [4]. In Europe, since the late 1990s, a growing increase in real estate values has occurred. It has been interrupted since 2008, following the American housing bubble. In 2014, the European Central Bank (ECB)’s liquidity supply made the access to credit for businesses and consumers easier, and thus they regained confidence. This, together with the convenient transaction costs on the market, led to 18.6% increase in transactions in 2016. Prices reached stability in 2017. Since the second half of the 1990s, the Italian real estate market, in particular, has had a positive trend. The reason is linked to the low

Sustainability 2020, 12, 1211; doi:10.3390/su12031211 www.mdpi.com/journal/sustainability Sustainability 2020, 12, 1211 2 of 24 level of interest rates on mortgages, following the introduction of the single currency, generating a greater propensity to borrowing and consequently a growing demand for housing; the volatility that has affected the financial markets should be also considered in this framework [5]. The combination of all these events has led to an increase in sale volumes, with a peak in 2006 (with almost 845 thousand transactions) and an increase in values until 2007, when the Italian real estate market reversed its trend due to the real estate bubble of the American subprime. The downward trend of the real estate cycle began in fact in the second half of 2007, when for the first time, property prices reported a contraction. In the last ten years, property prices in big cities have fallen by over 40% [6,7]. However, the percentage of decrease in real estate values of some major Italian cities such as Florence ( 28.3%), Milan ( 26.3%), Palermo ( 39.3%), Rome ( 35.8%), and Verona − − − − ( 36.0%) has recorded a lower decrease than the national average [8,9]. The greatest decrease in − property values, almost uniform in the different areas of the city, has been recorded in Genoa ( 53.3%). − Naples, instead, is at the third place in the ranking ( 47.0%) after Genoa and Bari during the decade − 2009–2018 [10]. Despite of the above described negative situation in Italy, there are some cases of urban transformation and regeneration projects positively affecting the real estate market values. Milan (+3.8%) and Turin (+2.4%) represent the two cases of greater increase. Milan is becoming more and more attractive, attentive to ecological and energy needs, and also capable of accepting new challenges regarding important and international events (i.e., the World Exposition Milan 2015, Expo). The city of Turin, on the other hand, is the one that has most successfully exploited the European funds to “rethink and reshape” the spaces of a territory historically linked to big industries (related to car production—FIAT—and its satellite activities). Focusing attention on the of the city of Naples (Italy), the aim of this paper is to analyse in detail the real estate dynamics in this city and propose an integrated evaluation approach for a better understanding and interpretation of urban dynamics, and thus to orient and activate future appropriate planning policies. This work can be useful for decision makers to understand what happened in the city of Naples in a synoptic way and with a high level of definition, such as that of census sections. It can represent a framework that allows linking the real estate dynamics with other information collected for the same sections for the census. After the literature review (Section2) and the introduction of the case study of the city of Naples (Section3), the methodological process is explained, identifying four main steps and integrating a Multi-Criteria Decision Analysis (MCDA) and Geographical Information System (GIS) for the analysis of the real estate dynamic in Naples, both for housing and commercial properties (Section4). The results are analysed, showing through many maps the outcome of the different elaborations and studies implemented (Sections5–7).

2. Literature Review Evaluation processes play a key role in decision-making processes related to urban regeneration, in the implementation of urban projects and plans, and in orienting development strategies. In particular, here the attention is focused on understanding and evaluating real estate dynamics. The evaluation of real estate assets is important for supporting and orienting urban strategies and choices to make cities more competitive [11,12]. The real estate price represents a useful indicator to evaluate urban performances, and many studies highlight the relationships between the real estate values and urban regeneration [13–16]. Geographical Information System (GIS) is a widely used tool for representing the status quo of an area and planning the future scenarios of urban regeneration. This tool can support and facilitate decision-making processes, both for urban planners and for the other actors involved in the process. Many studies use GIS as a basic tool for mapping and analysing the distribution of various issues in different fields [17–20]. Territorial statistical analyses are possible to be carried out by GIS linking a given issue to the territory. The use of statistical techniques for the analysis of spatial autocorrelation Sustainability 2020, 12, 1211 3 of 24 has led to important results in different research fields, ranging from natural to social and economic sciences. Different types of geostatistical techniques are used in practice. These allow us to determine groupings according to specific criteria in a given study area. For example, the Hot Spot (Gi* de Getis-Ord) analysis [21] is used for determining spatial clusters, referred to as high values (hot spots) or low values (cold spots), and the cluster and outlier (Anselin local Moran’s I) analysis [22] is used for identifying concentrations of values and spatial outliers [23]. These techniques are used in relevant researches from 1980s for studies on finding synthetic, local, and geostatistical indicators [23]. Sánchez-Martín et al. [23], for example, use the hotspot analysis (based on Gi* de Getis-Ord) and the cluster and outlier analysis (based on Anselin local Moran’s I) to analyze the accommodation distribution patterns in ExtremAdura (Spain). Las Casas et Al. [24] use geostatistical techniques for the analysis of the migration flows in Italy. Curto and Fregonara [25] start from data organized in GIS to monitor and analyse real estate market in a social perspective, applying the methodology in the city of Turin (Italy). In some cases, GIS tool is integrated with other tools in order to achieve more complete and detailed results. For example, it is integrated with 3D data visualization to produce a visual representation of data and information and give more depth of the field [19]. Furthermore, the integration between GIS and MCDA is a useful tool for supporting urban planners and, in general, decision makers, both in ex-ante and ex-post evaluation and monitoring [26]. The Multi-Criteria Decision Analysis (MCDA) methods are “useful tool developed to support the decision makers in their unique and personal decision process. MCDA methods provide stepping-stones and techniques for finding a compromise solution. They have the distinction of placing the decision maker at the centre of the process. They are not automatable methods that lead to the same solution for every decision maker, but they incorporate subjective information” ([24], p. 2). The MCDA allows assessing alternative projects on the basis of several criteria to be considered simultaneously in a complex situation, including different actors/stakeholders and points of view [27,28]. They are used in different fields from management, to social science, to economics, etc. [27,29,30]. It is widely used, as it can contribute to solve any problem in which a significant decision needs to be made [27]. There are different multicriteria methods that have been developed [27,31] (about 100 to date, [29]) and tested in different sectors to support decision-making processes [32]. Guarini et al. [29], in their study about the selection of multi-criteria decision analysis methods for real estate/land management processes, identify (based on the analyses of Guitoni et al. [33] and Ishizaka and Nemery [27]) the following methods as the most frequent used: ELimination Et Choix Traduisant la REalitè (ELECTRE) [34]; Multi-attribute utility theory (MAUT) [35]; Analytic Network Process (ANP) [36]; Measuring Attractiveness by a Categorical Based Evaluation (MACBETH) [37]; Analytic Hierarchy Process (AHP) [38]; Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) [39]; Preference Ranking Organization Method for Enrichment Evaluations (PROMETHEE) [40]. These MCDA methods are used in a wide range of decision making processes, and in the last decade there are several experiences highlighting the increased interest in the use of MCDA using structured and comprehensive databases in urban planning and real estate sector and land management [29]. Bottero et al. [41], for example, uses the PROMETHEE method to support decisions in urban planning and regeneration processes, comparing different scenarios of the City of Collegno (Italy). The use of MCDA-GIS integration has increased significantly over the last twenty years, demonstrating its usefulness in several fields (e.g., urban planning, ecological areas) [42–44]. The MCDA allow understanding of a complex issue and, at the same time, the GIS tool makes the results clearer and easier to read for policy makers and less expert people, allowing also the elaboration of statistical analyses. There are different levels of integration of these two tools: Indirect, built-in, and complete integration [26]. The complete integration is the only one allowing the use of the same database, interface, and access simultaneously [26,45]. As Boggia et al. highlight [26], Sustainability 2020, 12, 1211 4 of 24 applications in strategic sustainable planning are still rare [46–48]. Malcezewski underlines, in his literature reviews about MCDA and GIS from 1991 to 2006 [45,49], this lack of MCDA included in GISSustainability [50]. He 2019 underlines, 11, x FOR PEER that REVIEW only a few papers describe a complete integration between these4 of two27 tools, above all due to the scarce amount of MCDA software implemented in GIS [50], thus considering thetools, two above software all indue independent to the scarce phases amount of the research.of MCDA Furthermore, software implemented other reasons in are GIS both [50], related thus to theconsidering unfamiliarity the two (often) software of GIS in experts independent with decision-making phases of the research. processes Furthermore, and to the lackother of reasons open source are methodsboth related available to the [50 unfamiliarity]. (often) of GIS experts with decision-making processes and to the lackBoggia of open et source al. [26 me],thods for example, available use [50]. MCDA-GIS integration as an approach for sustainability assessmentBoggia thatet al. represents [26], for example, a complex use issue,MCDA-GIS including integration different as an dimensions approach for (economic, sustainability social, environmentalassessment that dimensions). represents Sobriea complex and Pirlotissue, [ 50incl] integrateuding different GIS and dimensio ELECTREns TRI (economic, for analysing social, the problemenvironmental to determine dimensions). policies Sobrie to prevent and Pirlot further [50] damages integrate inGIS a degradedand ELECTRE landscape TRI for in analysing Burkina the Faso (Africa).problem Omidipoor to determine et policies al. [18] useto prevent a GIS-based further decision damages support in a degraded system forlandscape facilitating in Burkina participatory Faso urban(Africa). renewal Omidipoor process. et Masseial. [18] [use51] a integrate GIS-based MCDA decision in GIS support framework system for for environmental facilitating participatory evaluations. Deurban Toro renewal and Iodice process. [52] carryMassei out [51] a multi-criteria integrate MCDA evaluation in GIS using framework the geoTOPSIS for environmental algorithm for evaluations. De Toro and Iodice [52] carry out a multi-criteria evaluation using the geoTOPSIS applying the concept of ecosystem health to the Metropolitan Area of Naples, classifying the territory algorithm for applying the concept of ecosystem health to the Metropolitan Area of Naples, according to its urban health. classifying the territory according to its urban health. GIS tool and the MCDA-GIS integration are here used to understand the real estate dynamics of the GIS tool and the MCDA-GIS integration are here used to understand the real estate dynamics of city of Naples, with a particular focus on the neighbourhood in which urban projects have been planned the city of Naples, with a particular focus on the neighbourhood in which urban projects have been or implemented in the last ten years. There are many works dealing with this issue, demonstrating, planned or implemented in the last ten years. There are many works dealing with this issue, through case studies, the correlation between these two phenomena [13–15,53]. This topic has been demonstrating, through case studies, the correlation between these two phenomena [13–15,53]. This recently addressed during the conference “Urban regeneration and real estate market” [16], highlighting topic has been recently addressed during the conference “Urban regeneration and real estate thatmarket” urban [16], regeneration highlighting projects that urban can aff ectregeneration the real estate projects market can fromaffect dithefferent real pointsestate market of view from (legal, economic,different points urban). of Consideringview (legal, economic, that many urban). factors Co affnsideringect the real that estate many sector factors (i.e., affect location the real attributes, estate servicessector (i.e., availability, location accessibility,attributes, services urban availabilit quality), itsy, accessibility, evaluation is urban important quality), for addressingits evaluation urban is strategiesimportant [12 for,54 addressing]. urban strategies [12,54]. 3. The Case Study: The City of Naples, Italy 3. The Case Study: The City of Naples, Italy ThisThis work work focusesfocuses on the the real real estate estate dynamics dynamics in inthe the city city of Naples, of Naples, a municipality a municipality of almost of almost one onemillion million inhabitants, inhabitants, part part of the of metropolitan the metropolitan port portcity of city Naples, of Naples, in the in South the Southof Italy of (Figure Italy (Figure 1). The1 ). Thecity city calls calls the thehomonymous homonymous gulf gulfthat thatextends extends from from the Sorrento the Sorrento peninsula peninsula to the to volcanic the volcanic area of area the of thePhlegraean Phlegraean fields. fields. It is It rich is rich in valuable in valuable cultural cultural and andnature nature heritage, heritage, and its and historic its historic centre centre was on was the on theUNESCO UNESCO World World Heritage Heritage List List since since 1995. 1995.

FigureFigure 1. 1.The The citycity ofof Naples,Naples, Italy. (Source: Auth Authors’ors’ elaboration elaboration based based on on google google map). map).

TheThe economic economic and and social social framework framework of of Italy, Italy, in in which which the the case case study study is is located, located, is is characterized characterized by persistentby persistent uncertainties uncertainties about about economic economic development development and structural and structural problems problems aﬀecting affecting the country’s the country’s growth potential and medium and long-term sustainability conditions. In an international scenario of generalized slowdown in 2018, the Italian economy decelerated sharply compared to 2017, experiencing a nearly stagnant trend during the year, with signs of decline in the second half of

Sustainability 2020, 12, 1211 5 of 24 growth potential and medium and long-term sustainability conditions. In an international scenario of generalized slowdown in 2018, the Italian economy decelerated sharply compared to 2017, experiencing a nearly stagnant trend during the year, with signs of decline in the second half of the year. The slight recovery recorded in the first part of 2019 is associated with a further expansion of the production and employment base [55]. Third largest municipality in Italy by population, Naples, is, with Florence, Rome, Venice, and Milan, one of the top Italian “destinations”. With 3,700,000 visitors in 2018, the city has come out from the severe tourist depression of past decades (due for example to the image damage caused by the media, the Irpinia earthquake of 1980, and the waste crisis) [56]. Unlike other Italian cities such as Rome and Milan (to which it is comparable in terms of population), the City of Naples has a lower average income, of about 20,000 euros [57]. Moreover, in Naples, employment rate is lower than in Rome, and the differences between districts are much more marked. With reference to the real estate market, Naples is the city in southern Italy that is growing most in terms of real estate sales. The Neapolitan market was the only one, in fact, to recover following the decline in real estate transactions began with the economic crisis, which in the South of Italy led to halving sales. At the end of 2018, the real estate market of Naples returned almost to the values of the pre-crisis period, with a growth of 10.5% of transactions compared to the previous year. As the study by Scenari Immobiliari (Independent Institute of Studies and Research) points out, in the next decade the city will have to implement the initiatives started more than ten years ago and which have been blocked in progress due to lack of funds or other types of difficulties [58]. The city will have to increase its supply of social housing, which are at the moment inadequate and far from the standards of other European cities, so as to face the phenomenon of illegality and respond to the hardships of the population. As underlined in the Metropolitan Strategic Plan of the Metropolitan City of Naples [59], in order to compete with other cities, Naples will have to carry out strategic actions related to different issues such as encouraging sustainable mobility, improving accessibility, and valorising cultural and natural heritage. Furthermore, a widespread energy redevelopment of its building stock, which is largely obsolete, is required. In the coming years, in fact, as highlighted by Scenari Immobiliari, the real estate market will tend to “downgrade” the value of buildings without sustainability requirements and to “reward” buildings of new generation, or low energy impact [58]. Moreover, the success of the short tourist lease (Naples is the first city in Southern Italy and the fourth in Italy) shows how demand has changed, and that there is space for new economies.

4. Material and Methods The methodological process of this work is divided in four main steps (Figure2):

- First step: During this phase, data about market prices of housing and commercial properties have been acquired. Furthermore, the cartography (based on census sections) by Italian National Institute of Statistics (ISTAT) [60] has been acquired to georefer data, and a database has been elaborated. - Second step: This phase refers to the georeferencing of all data by means of a Geographical Information System (GIS). - Third step: During this phase, diﬀerent geostatistical analyses have been developed (showed and developed in §§ 4.1; 4.2; 4.3). Furthermore, a Multi-Criteria Decision Analysis (MCDA) method has been carried out by means a plugin of QGIS. - Fourth step: Analysis and discussion of results. Sustainability 2020, 12, 1211 6 of 24 Sustainability 2019, 11, x FOR PEER REVIEW 6 of 27

Figure 2. Methodological process. Figure 2. Methodological process. The change in market prices of housing and commercial properties has been analysed in relation to theThe 2009–2018 change periodin market (after prices the 2008 of crisis).housing In particular,and commercial four years properties have been has selected been analysed so that the in variationsrelation to are the more 2009–2018 evident: period 2009, (after 2012, 2015,the 2008 2018. crisis A time). In intervalparticular, of 3 four years years has been have chosen, been selected otherwise so itthat would the havevariations been diareffi cultmore to appreciateevident: 2009, thevariations 2012, 2015, which, 2018. considering A time interval also the of intermediate 3 years has years,been wouldchosen, have otherwise been less it would significant, have andbeen considering difficult to alsoappreciate the amount the variations of data to which, be considered. considering also the intermediateThe data have years, been would deduced have from been the less O ffisignificcial Listant, of and the considering Naples Real also Estate the Exchangeamount of [data61–64 to]. Thebe considered. 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Itthe is alsolocal set real up estate to carry market, out research through activities the implementation aimed at observing of specific the realinitiatives estate market,that facilitate developing and make real estatefaster investmentand guaranteed initiatives the meeting and urban between regeneration; supply and it also demand carries outin both training, the purchase verification, and andsale control of real activitiesestate. It inis thealso sector. set up Every to carry six months,out research it draws activities up the aimed Official at Price observing List, a toolthe forreal operators estate market, in the sectordeveloping that shows real estate the prices investment per square initiatives metre of and properties, urban relatingregeneration; to municipalities, it also carries neighbourhoods, out training, areasverification, of the city,and andcontrol the activities province in of the Naples. sector. It Every contains six months, actual buying it draws and up selling the Official real estate Price dataList, provideda tool for by operators sales agents. in the It issector available that onlineshows andthe inprices printed per edition square starting metre of from properties, the first half relating of 2007. to Themunicipalities, data of the Oneighbfficialourhoods, Price List areareas not of georeferenced. the city, and So, the the prov firstince step of after Naples. data retrievalIt contains was actual their georeferencing.buying and selling To this real end, estate the data cartographic provided base by dividedsales agents. into census It is available sections byonline the Italianand in National printed Instituteedition starting of Statistics from (ISTAT) the first was half used. of 2007. According The data to ISTAT, of the NaplesOfficial is Price divided Listin are 5.216 not censusgeoreferenced. sections. So, theThe first real step estate after data data available retrieval have was been their classified georeferencing. by the Naples To Realthis Estateend, the Exchange cartographic (2009–2018) base individed Unitary into Market census Values sections (in Italian:by the VMU).Italian National They are Institute expressed of per Statistics square (ISTAT) meter (€ /wassqm) used. and, concerningAccording to housing ISTAT, properties, Naples is theydivided refer in to 5.216 “standard census properties”: sections. Flat for residential use, moderately renovated,The real located estate on data an intermediate available have floor, been with classified a floor area by ofthe 100 Naples square Real meters, Estate not Exchange furnished. (2009– With regard2018) in to Unitary commercial Market properties, Values shops(in Italian: on the VMU). ground They floor are and expressed with an area per ofsquare approximately meter (€/sqm) 50 square and, metersconcerning are considered. housing properties, These values they by therefer Naples to “s Realtandard Estate properties”: Exchange have Flat been for deduced residential from use, the transactionmoderately pricesrenovated, that actually located occurred,on an intermediate and are the floor, average with of a thefloor minimum area of 100 and square maximum meters, values. not Unbalancedfurnished. With or atypical regard situations to commercial havebeen properties, excluded shops from on the the pricing. ground In fact,floor those and valueswith an referring area of toapproximately properties of 50 particular square valuemeters or are degradation considered. (or Th thatese in values any case by havethe Naples non-ordinary Real Estate characteristics) Exchange have notbeen been deduced considered from for the developing transaction the prices database. that actually In addition, occurred, the prices and considered are the average refer to of “free the properties”,minimum and that maximum is to be understood values. Unbala as havingnced or no atypical legal constraints. situations Furthermore,have been excluded they are from related the topricing. individual In fact, housing those values units andreferring not to to real properties estate complexes. of particular The value processed or degradation data are referred(or that in to any the Unitarycase have Market non-ordinary Values (VMU) characteristics) of both residential have not andbeen commercial considered properties for developing for each the census database. section In (5.216addition, census the prices sections) considered in reference refer to to the “free four properti years consideredes”, that is (forto be a totalunderstood of 41.728 as processedhaving no data).legal Theconstraints. 5.216 census Furthermore, sections include they are the followingrelated to 10 individual districts: housing units and not to real estate complexes. The processed data are referred to the Unitary Market Values (VMU) of both residential

Sustainability 2020, 12, 1211 7 of 24

– district no. 1, including San Ferdinando, Chiaia, Posillipo neighbourhoods (432 census sections); – district no. 2, including Porto, Pendino, Montecalvario, San Giuseppe, Avvocata, Mercato neighbourhoods (1.025 census sections); – district no. 3, including Stella and San Carlo all’Arena neighbourhoods (454 census sections); – district no. 4, including San Lorenzo, Vicaria, Poggiorele neighbourhoods (632 census sections); – district no. 5, including Vomero and Arenella neighbourhoods (416 census sections); – district no. 6, including San Giovanni a Teduccio, Barra, Ponticelli neighbourhoods (654 census sections); – district no. 7, including Miano, Secondigliano, San Pietro a Patierno neighbourhoods (428 census sections); – district no. 8, including Piscinola, Chiaiano, Scampia neighbourhoods (375 census sections); – district no. 9, including Soccavo and Pianura neighbourhoods (357 census sections); – district no. 10, including Fuorigrotta and Bagnoli neighbourhoods (443census sections). The database of house and commercial properties’ prices has been then georeferenced by means the GIS tool, producing a total of 8 maps (4 about house prices and 4 about commercial properties’ prices) referring to 4 years (2009, 2012, 2015, 2018), showing the price trend during the period considered. So, a merge between the ISTAT cartography and the data coming from the Naples Real Estate Exchange has been carried out. The georeferencing of data is essentially a way to link the various phenomena to the territory (in our case, with reference to the change in market prices). After mapping these price trends, diﬀerent analyses and elaborations have been conducted by means of the GIS tool [65,66].

4.1. Cluster and Outlier Analysis (COA) The first analysis elaborated is the Cluster and Outlier Analysis (COA) in the ArcGIS framework for identifying concentrations of values and spatial outliers. In fact, it has been conducted in order to identify similarities of behavior between data spatially close to each other. This uses the Anselin Local Moran Statistics I to determine the relationships among data [67]. This is calculated by the “Local Moran Index” [22] that highlights areas where high values or low values are grouped in “clusters”, and areas in which there are values that are very different from those surrounding (“outlier”). The Moran Index is defined as the measure of the spatial autocorrelation which, in turn, can be defined as a territorial cluster of similar parameter values [68]. Its values range from 1 to 1. A positive − value of the Moran Index indicates that the area considered (in our case the census sections) has neighboring areas with similar values (either high or low), and therefore there are clusters. If the value of the index is instead negative, it means that there is a spatial proximity of dissimilar values (spatial heterogeneity), and in this case they are “outlier”, that is, an anomalous value that is distant from the other values taken into consideration. The zero value instead indicates perfect spatial randomness [69,70]. More generally, there is positive spatial autocorrelation if the intensity of a phenomenon in an area is similar to the intensity of the phenomenon in contiguous areas, while there is a negative autocorrelation in the case in which two contiguous zones have different intensities. By means of ArcGIS, this statistical analysis has been geoprocessed, returning maps as the result. This analysis is defined according to the following Formula (1) about the Local Moran’s I statitistc of spatial association [71]: n xi X X Ii = − wi,j xj X (1) S2 − i j=1,j,i where:

– xi is an attribute for feature i; – X is the mean of the corresponding attribute; Sustainability 2020, 12, 1211 8 of 24

– wi,j is the spatial weight between feature i and j; and

Pn 2 j=1,j,i xj X S2 = − (2) i n 1 − with n equating to the number of feature.

4.2. Hot Spot Analysis (HSA) After the aforementioned analysis, another elaboration has been carried out. The Hot Spot Analysis (HSA) has been conducted (by means of ArcGIS software) using the Getis–Ord Gi* statistic [21] for determining if spatial clusters are referring to high values (hot spots) or low values (cold spots). A hotspot is “an area that has higher concentration of events compared to the expected number given a random distribution of events” [72]. The HSA is a spatial analysis and mapping technique whose results are a z-score and a p-value that indicate where high or low value clusters are spatially. It can be positive (if values are higher than the global average), negative (if values are lower than the global average), or equal to zero (if values are the same as the global values). Additionally, the results of this analysis have been reported in the maps produced by ArcGIS software. The Getis-Ord local statistic is given by the following Formula (3) [73]: P P n w x X n w j=1 i,j j − j=1 i,j Gi = r (3) P P 2 n n w2 n w j=1 i,j− j=1 i,j S n 1 − where:

– xi is the attribute value for feature j; – wi,j is the spatial weight between feature I and j; – n is equal to the total number of features; and (4,5)

Pn j=1 xj X = (4) n s Pn 2 j=1 xj 2 S = X (5) n −

After that, an analysis of the percentage variation of the house and commercial property prices (euro/sqm) has been investigated in reference to the years 2009–2018. The results of this elaboration have been two maps (house and commercial property maps) showing percentage variation considering nine classes.

4.3. The Integration of MCDA and GIS: the Implementation of the TOPSIS Method The last analysis was to understand which census sections, in the period considered, have had the best/worst performance. To this end, a Multi-Criteria Decision Analysis (MCDA) method has been carried out, that is the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) method [39,74–76]. In particular, the “geoTOPSIS” algorithm (whose functioning is based on the TOPSIS method) included in an open source QGIS plugin, named “Vector MCDA”, which has been used [77]. The plugin uses diﬀerent MCDA algorithms to implement multi-criteria analysis in a GIS framework. This TOPSIS method is based on the ideal point approach, that is based on the idea that the preferable choice has to have the shortest geometric distance (in Euclidean space) from the ideal point Sustainability 2020, 12, 1211 9 of 24

(positive solution) and the longest geometric distance from the anti-ideal point (negative solution). The method returns a hierarchy of preferences with respect to close/distance to the ideal point. The GeoTOPSIS returns a map (in QGIS that we have transformed into an ArcGIS map for a clearer reading of the results) that shows the geographical arrangement of the performances of the census sections, that is, which census sections have maintained higher values (best performance) or lower values (worst performance) during the whole time interval considered. The criteria of this case study are the market values of house and commercial properties related to the four years considered. No diﬀerent weights were assigned to the criteria of this case study. This elaboration allows understanding of how each census section is placed in relation to the “ideal value” (the maximum value) and the “anti-ideal value” (the minimum value). In this case, the minimum value is zero-value because it is the lowest one that can be used as market value.

5. Results Working with georeferenced data in an environment that provides rapid spatial visualizations allows for almost immediately obtaining very interesting representations. The maps resulting from the georeferencing of data referred to market values of housing and commercial properties (deduced from the Official List of the Naples Real Estate Exchange) show how the market values are changed in the 2009–2018 period (Figures3 and4). The values have been organized into six classes: 0, 1–1500 €/sqm, 1501–3000 €/sqm, 3001–5000 €/sqm, 5001–7000 €/sqm, 7001–9000 €/sqm. The 0 value refers to the public spaces and assets for which there is no market. The six classes come from the Jenks Natural Breaks Classification System [78] and a subsequent manual adjustment to obtain more defined classes. The map with the highest values was the starting point for elaborating the classes in order to always get the same range of values for all the four years considered. A similar procedure was adopted to determine the six classes of commercial property prices: 0, 1–2500 €/sqm, 2501–5000 €/sqm, 5001–8000 €/sqm, 8001–12,000 €/sqm, 12,001–17,000 €/sqm. As the resulting maps show (Figures3 and4), during the analysed period, a decrease in the house prices actually occurred, consistent with what is highlighted in paragraph 1. For example, the dark brown colour (corresponding to the class of values 7001–9000 €/sqm) that characterized the area of Posillipo and the historic centre of the city has “become lighter” (5001–7000 €/sqm) over the four years, thus highlighting a decrease in property prices. The area of Via Partenope (pedestrian seafront) is excluded from this decreasing trend, registering, in 2015, prices in the highest class (7001–9000 €/sqm) (Figure3). In some neighbourhoods, a somewhat different phenomenon is instead linked to the commercial properties market, where the dynamics show that they are not strictly related to the residential ones (Figure4). For example, analysing the area of the Vomero neighbourhood, it is possible to note that the prices of commercial properties have maintained high values. The same is valid again for the area of Via Partenope. It can be pointed out that prices have remained high over the years in pedestrian areas. The first analysis, the Cluster and Outlier Analysis (COA), allows us to understand if the variation of real estate prices (decreased in the recent years) refers to the entire city or not, that is, understanding if it is a phenomenon distributed in an uneven manner or if there are some clusterizations. To this end, the function used by the ArcGIS software has returned maps that allow a clear reading of the results. Indeed, there are areas that are clustered, but it is significant how the shape and size of these areas have changed over time (Figures5 and6). For example, the Ponticelli-San Giovanni a Teduccio area in the years 2009, 2012, 2015 has been characterized by quite homogeneous values and, instead, in the last year analysed (2018), the phenomenon has been more varied. Most likely, this variation is due to some significant urban redevelopment interventions that have been implemented recently. Suffice it to consider that the Apple Developer Academy has been established in this neighbourhood; this inevitably has defined new mechanisms. Sustainability 2020, 12, 1211 10 of 24 Sustainability 2019, 11, x FOR PEER REVIEW 10 of 27

(a) Year 2009 (b) Year 2012

(c) Year 2015 (d) Year 2018 Sustainability 2019, 11, x FOR PEER REVIEW 11 of 27 Figure 3. 3. HouseHouse prices prices (€/sqm). (€/sqm).

(a) Year 2009 (b) Year 2012

FigureFigure 4. Commercial property property prices prices (€/sqm). (€/sqm).

The first analysis, the Cluster and Outlier Analysis (COA), allows us to understand if the variation of real estate prices (decreased in the recent years) refers to the entire city or not, that is, understanding if it is a phenomenon distributed in an uneven manner or if there are some clusterizations. To this end, the function used by the ArcGIS software has returned maps that allow a clear reading of the results. Indeed, there are areas that are clustered, but it is significant how the shape and size of these areas have changed over time (Figures 5 and 6). For example, the Ponticelli-San Giovanni a Teduccio area in the years 2009, 2012, 2015 has been characterized by quite homogeneous values and, instead, in the last year analysed (2018), the phenomenon has been more varied. Most likely, this variation is due to some significant urban redevelopment interventions that have been implemented recently. Suffice it to consider that the Apple Developer Academy has been established in this neighbourhood; this inevitably has defined new mechanisms. The results also show that in the neighbourhoods of Vomero and Posillipo, and in the historic centre, there is a quite homogeneous clustering. These considerations are also very similar with regard to commercial properties.

Sustainability 2020, 12, 1211 11 of 24 Sustainability 2019, 11, x FOR PEER REVIEW 12 of 27

(a) Year 2009 (b) Year 2012

(c) Year 2015 (d) Year 2018 Sustainability 2019, 11, x FOR PEER REVIEW 13 of 27 FigureFigure 5.5. Cluster and and outlier outlier analysis—housing analysis—housing market. market.

(a) Year 2009 (b) Year 2012

FigureFigure 6. 6.Cluster Cluster and outlier outlier analysis—c analysis—commercialommercial property property market. market.

After that, in order to understand if these clusters are referring to high or low values, the second elaboration has been carried out (Hot Spot Analysis using the Getis–Ord Gi* statistic). The maps (Figure 7) relating to the residential market resulting from the aforementioned analysis show that (albeit with some minor changes to the shape) the ancient centre, and the Vomero and Posillipo neighbourhoods are clustered for high values. On the other hand, the entire peripheral area is grouped together for low values. As the maps show, there is a “buffer zone” that changes slightly over the years and represents a “hinge” between the two clusters (hot and cold spots). This dynamic is a bit richer for commercial properties (Figure 8). Probably, this is due to the fact that the commercial market is more dynamic than the residential one. So, there are more sales data, thus making the dynamics more clearly pointed out than in the residential real estate market (which does not have a strong dynamic like the commercial one).

Sustainability 2020, 12, 1211 12 of 24

The results also show that in the neighbourhoods of Vomero and Posillipo, and in the historic centre, there is a quite homogeneous clustering. These considerations are also very similar with regard to commercial properties. After that, in order to understand if these clusters are referring to high or low values, the second elaboration has been carried out (Hot Spot Analysis using the Getis–Ord Gi* statistic). The maps (Figure7) relating to the residential market resulting from the aforementioned analysis show that (albeit with some minor changes to the shape) the ancient centre, and the Vomero and Posillipo neighbourhoods are clustered for high values. On the other hand, the entire peripheral area is grouped together for low values. As the maps show, there is a “buﬀer zone” that changes slightly Sustainabilityover the years 2019, 11 and, x FOR represents PEER REVIEW a “hinge” between the two clusters (hot and cold spots). 14 of 27

(a) Year 2009 (b) Year 2012

FigureFigure 7. 7. HotspotHotspot analysis—housing analysis—housing market. market.

This dynamic is a bit richer for commercial properties (Figure8). Probably, this is due to the fact that the commercial market is more dynamic than the residential one. So, there are more sales data, thus making the dynamics more clearly pointed out than in the residential real estate market (which does not have a strong dynamic like the commercial one).

Sustainability 2020, 12, 1211 13 of 24 Sustainability 2019, 11, x FOR PEER REVIEW 15 of 27

(a) Year 2009 (b) Year 2012

FigureFigure 8. 8.HotspotHotspot analysis—commercial analysis—commercial property property market. market.

ThenThen the the maps maps related related to to the the percentage percentage variat variationion of of the the house house and and commercial commercial property property prices prices (euro/sqm)(euro/sqm) have have been been analysed analysed in in reference reference to to th thee period period 2009–2018 2009–2018 (Figures (Figures 99 and and 10).10). The The results results show that there are few areas in which the crisis has not been felt (which therefore have no negative or showSustainability that there 2019 ,are 11, xfew FOR areas PEER inREVIEW which the crisis has not been felt (which therefore have no negative 16 of 27 orpositive positive variations) variations) and and that that therefore therefore this crisisthis cris in realis in estate real estate market market has aﬀ ectedhas affected almostthe almost entire the city. entire city. It is possible to note, for example, that the area of San Giovanni a Teduccio (where the Apple Developer Academy has been located) has good results, more in the commercial than in the residential market. Probably this difference is due both to the fact that the students mainly make use of commercial services (and thus there was a trade revival) and the fact that the students do not buy the house to stay, but either they are commuters or they rent the house (and this analysis is only on sales data and not related to rents). The same phenomenon also occurred in the ancient centre. Further analyses would be needed to analyse the different causes (such as the localization of numerous B & B) of the results.

Figure 9. Percentage variation (2009–2018)—housing market. Figure 9. Percentage variation (2009–2018)—housing market.

Figure 10. Percentage variation (2009–2018)—commercial property market.

By means of the last analysis (geoTOPSIS functioning based on the TOPSIS method), the overall performance of the census sections has been investigated, that is, which census particles have maintained higher values (best performance) or lower values (worst performance) during the whole time interval considered. The resulting map in QGIS framework has been transferred in ArcGIS framework to be clearly analysable (Figures 11 and 12). Even through this analysis, the residential market shows a high performance in the areas of the historic centre, Vomero, and Posillipo neighbourhoods (high values). All the more peripheral areas, on the other hand, have had a medium-low performance that worsens moving away from the city centre. The white spaces in the maps represent the 0 value and correspond to the public spaces and assets (i.e., airport, railway station). In the resulting map of the commercial property market, it is pointed out that the areas with low performance decrease, probably due to some phenomena already highlighted in the previous analyses (such as the case of Apple).

Sustainability 2019, 11, x FOR PEER REVIEW 16 of 27

Sustainability 2020, 12, 1211 Figure 9. Percentage variation (2009–2018)—housing market. 14 of 24

Figure 10. Percentage variation (2009–2018)—commercial property market. Figure 10. Percentage variation (2009–2018)—commercial property market. It is possible to note, for example, that the area of San Giovanni a Teduccio (where the Apple DeveloperBy means Academy of the haslast been analysis located) (geoTOPSIS has good functi results,oning more based in the on commercial the TOPSIS than method), in the the residential overall market.performance Probably of the this census diﬀerence sections is due bothhas been to the investigated, fact that the students that is, mainly which make census use particles of commercial have servicesmaintained (and higher thus there values was (best a trade performance) revival) and or thelower fact values that the (worst students performance) do not buy during the house the towhole stay, buttime either interval they considered. are commuters The orresulting they rent map the in house QGIS (and framework this analysis has isbeen only transferred on sales data in andArcGIS not relatedframework to rents). to be Theclearly same analysable phenomenon (Figures also 11 occurred and 12). in the ancient centre. Further analyses would be neededEven through to analyse this the analysis, diﬀerent the causes residential (such asmarket the localization shows a high of numerous performance B & in B) the of theareas results. of the historicBy meanscentre, ofVomero, the last and analysis Posillipo (geoTOPSIS neighbourhoods functioning (high based values). on the All TOPSIS the more method), peripheral the overall areas, performanceon the other ofhand, the census have had sections a medium-low has been investigated, performance that that is, which worsens census moving particles away have from maintained the city highercentre. valuesThe white (best spaces performance) in the maps or lower represent values the (worst 0 value performance) and correspond during to the the whole public time spaces interval and considered.assets (i.e., airport, The resulting railway map station). in QGIS In frameworkthe resulting has map been of transferredthe commercial in ArcGIS property framework market, to it beis Sustainability 2019, 11, x FOR PEER REVIEW 17 of 27 clearlypointed analysable out that (Figuresthe areas 11 with and 12low). performance decrease, probably due to some phenomena already highlighted in the previous analyses (such as the case of Apple).

Figure 11. geoTOPSIS (2009–2018)—housing market. Figure 11. geoTOPSIS (2009–2018)—housing market.

Figure 12. geoTOPSIS (2009–2018)—commercial property market.

6. Real Estate Values and Urban Projects in Seven Selected Neighbourhoods Starting from the previous analyses, seven neighbourhoods of the city of Naples have been selected and examined. The selected neighbourhoods are those in which significant urban regeneration interventions have been implemented (or planned) over the period of time considered, and positive variation percentage has been recorded despite the general negative context of the real estate market in the city (−47% during the decade 2009–2018). They are the following (Figure 13): 1. Vicaria–San Lorenzo–Pendino–Mercato–Porto (historic centre); 2. San Carlo all’Arena; 3. Vomero; 4. San Ferdinando; 5. Chiaiano; 6. Poggioreale; 7. San Giovanni a Teduccio.

Sustainability 2019, 11, x FOR PEER REVIEW 17 of 27

Sustainability 2020, 12, 1211 Figure 11. geoTOPSIS (2009–2018)—housing market. 15 of 24

Figure 12. geoTOPSIS (2009–2018)—commercial property market. Figure 12. geoTOPSIS (2009–2018)—commercial property market. Even through this analysis, the residential market shows a high performance in the areas of the historic6. Real Estate centre, Values Vomero, and and Urban Posillipo Projects neighbourhoods in Seven Selected (high Neighbourhoods values). All the more peripheral areas, on the other hand, have had a medium-low performance that worsens moving away from the city Starting from the previous analyses, seven neighbourhoods of the city of Naples have been centre. The white spaces in the maps represent the 0 value and correspond to the public spaces and selected and examined. The selected neighbourhoods are those in which significant urban assets (i.e., airport, railway station). In the resulting map of the commercial property market, it is regeneration interventions have been implemented (or planned) over the period of time considered, pointed out that the areas with low performance decrease, probably due to some phenomena already and positive variation percentage has been recorded despite the general negative context of the real highlighted in the previous analyses (such as the case of Apple). estate market in the city (−47% during the decade 2009–2018). 6. RealThey Estate are the Values following and Urban (Figure Projects 13): in Seven Selected Neighbourhoods 1. Vicaria–San Lorenzo–Pendino–Mercato–Porto (historic centre); Starting from the previous analyses, seven neighbourhoods of the city of Naples have been 2. San Carlo all’Arena; selected and examined. The selected neighbourhoods are those in which signiﬁcant urban regeneration 3. Vomero; interventions have been implemented (or planned) over the period of time considered, and positive 4. San Ferdinando; variation percentage has been recorded despite the general negative context of the real estate market in 5. Chiaiano; the city ( 47% during the decade 2009–2018). 6. Poggioreale;− They are the following (Figure 13): 7. San Giovanni a Teduccio. 1. Vicaria–San Lorenzo–Pendino–Mercato–Porto (historic centre); 2. San Carlo all’Arena; 3. Vomero; 4. San Ferdinando; 5. Chiaiano; 6. Poggioreale; 7. San Giovanni a Teduccio.

Sustainability 2019, 11, x FOR PEER REVIEWFigure 13. Seven areas analysed. 19 of 27 Figure 13. Seven areas analysed.

We considered the trend of the values of each area and put them in relation to the trend of the entire city of Naples. The aim is to observe the trend in the values of these neighbourhoods where interventions of urban regeneration have been implemented compared to the general trend of the city. The historic centre has been analysed in its entirety as the main interventions concern both the port area and the “Mercato” area (Figure 14). The neighbourhoods included in this area fall within the limits of the Great Project “Historical Centre of Naples, enhancement of the UNESCO site”. The main objective of this project is to redevelop the area, not only limited to the recovery of the built environment (by monofunctional interventions). While aiming at the conservation of the heritage, it acts on the urban, building, environmental, and social fabric, developing first of all the reorganization and the redesign of the land and infrastructure, and intervening on the space between the buildings, on the roadways, on the public space, linking togetherFigureFigure the di 14.14.fferent TheThe historic components centre of of in Naples. Naples. a single system. The analysed interventions concern the redevelopment of Porta Capuana through the recovery of theThe GloriaThe neighbourhoods San and Carlo S. Anna all’Arena towers included neighbourhood and in part this of area the fallisAragonese one within of the the walls neighbourhoods limits carried of the out Great together of ProjectNaples with “Historicalthat the hasurban Centreredevelopmentsuffered of Naples, the most of enhancement the from area, the the fall of restylingin the prices UNESCO ofin the site”. post-crisisgardens The mainof decade, Castel objective withCapuano, ofa thisloss the projectof aboutredevelopment is 800 to redevelop €/sqm of thePiazza(about area, Mercato not25% only compared (for limited which, to to the theto averagedate, recovery only value of the the in paving built2009) environment (Figureshas been 3 removed),and (by 4). monofunctional Analysing and the the recovery trend interventions). of and this the Whilere-functionalisationarea, aiming it emerges at the that conservation of the the average Girolamini of thevalue heritage, ofcomplex the itne actsighbourhood (aimed on the urban,at hasincreasing building,never been the environmental, abovesupply the of average spaces and social of for fabric,educational,the city developing of training,Naples first in and ofthe all receptionlast the ten reorganization years. activities). Nevertheless, and the the redesign San Carlo of the all’Arena land and neighbourhood infrastructure, has and interveningsomeIn additionpositive on the sections.to space these between actions,Probably, thealready they buildings, are carried related on out the to or roadways, the in progress,recent on restyling thethere public are of alsoPiazza space, the linkingCarlo works III, togetherrelating the theto re-openingthe diff introductionerent components in 2016 of theof in PiazzaLimited a single Poderico, Traffic system. Zone and (LTZ)the redevelopment in 2012, which ofhas several contributed streets to within limit vehicle the trafficneighbourhoodThe and analysed encourage through interventions the repavingpedestrianisation concern and improvement the redevelopment of the area, of lighting having of Porta (Figure positive Capuana 15). impacts In throughaddition, on thethe in the recoveryproperties’ Ponti of thepricesRossi Gloria of area, this and area.about S. Anna Finally, 200 towers new the homes construction and part were of thebuilt of the Aragonese in Università 2012 within walls and carriedthe Garibaldi former out togethermetroindustrial stations with complex thehas urban givenof “Visconti ceramics”. These redevelopment works can have affected the properties’ prices in the area. redevelopmentgreater usability of to the the area, 4 districts, the restyling encouraging of the an gardens increase of in Castel value Capuano, of the buildings. the redevelopment Analysing the of Piazzatrend of Mercato values (for(Figures which, 3 and to date, 4), it only emerges the paving that, outside has been a removed),peak in 2012, and the the trend recovery of this and area the re-functionalisationfollows the entire city. of the Girolamini complex (aimed at increasing the supply of spaces for educational, training, and reception activities). In addition to these actions, already carried out or in progress, there are also the works relating to the introduction of the Limited Traffic Zone (LTZ) in 2012, which has contributed to limit vehicle traffic and encourage the pedestrianisation of the area, having positive impacts on the properties’ prices of this area. Finally, the construction of the Università and Garibaldi metro stations has given greater usability to the 4 districts, encouraging an increase in value of the buildings. Analysing the trend of values (Figures3 and4), it emerges that, outside a peak in 2012, the trend of this area follows the entire city.

Figure 15. The San Carlo all’Arena neighbourhood.

The trend in real estate values in the Vomero neighbourhood (Figure 16), on the other hand, has always been significantly higher than that of the city, despite a decline in 2012 (Figures 3 and 4). In addition to the existence of five rail connections (two metro lines and three funicular lines), the Villa Floridiana (important “green lung” of the neighbourhood) and the Certosa of San Martino, is added the partial pedestrianisation of Via Luca Giordano in 2010 that connects with the already pedestrian Via Scarlatti, characterizing the neighbourhood by two main central arteries dedicated to trade, socialization, and leisure. Even the ancient “borgo Antignano” has been placed at the centre of a functional reorganization of the neighbourhood: A new lighting system has been designed and has been pedestrianised, allowing an area (that has always been used only as a neighbourhood market) to enjoy a renewed mix of functions that has contributed to the increase in real estate values.

Sustainability 2019, 11, x FOR PEER REVIEW 19 of 27

Sustainability 2020, 12, 1211 17 of 24 Figure 14. The historic centre of Naples. The San Carlo all’Arena neighbourhood is one of the neighbourhoods of Naples that has suﬀered The San Carlo all’Arena neighbourhood is one of the neighbourhoods of Naples that has the most from the fall in prices in the post-crisis decade, with a loss of about 800 €/sqm (about 25% suffered the most from the fall in prices in the post-crisis decade, with a loss of about 800 €/sqm compared to the average value in 2009) (Figures3 and4). Analysing the trend of this area, it emerges (about 25% compared to the average value in 2009) (Figures 3 and 4). Analysing the trend of this that the average value of the neighbourhood has never been above the average of the city of Naples in area, it emerges that the average value of the neighbourhood has never been above the average of the last ten years. Nevertheless, the San Carlo all’Arena neighbourhood has some positive sections. the city of Naples in the last ten years. Nevertheless, the San Carlo all’Arena neighbourhood has Probably,some positive they are sections. related Probably, to the recent they restyling are related of Piazza to the Carlorecent III, restyling the re-opening of Piazza in Carlo 2016 ofIII,Piazza the Poderico,re-opening and in the 2016 redevelopment of Piazza Poderico, of several and streets the within redevelopment the neighbourhood of several through streets repavingwithin the and improvementneighbourhood of lighting through (Figure repaving 15 ).and In improvement addition, in the of lighting Ponti Rossi (Figure area, 15). about In addition, 200 new in homes the Ponti were builtRossi in 2012area, within about the200 former new homes industrial were complex built in of 2012 “Visconti within ceramics”. the former These industrial redevelopment complex works of can“Visconti have aﬀ ectedceramics”. the properties’ These redevelopment prices in the works area. can have affected the properties’ prices in the area.

Sustainability 2019, 11, x FOR PEER REVIEW 20 of 27

Traffic congestion and lack of parking spaces are among the main problems affecting the Vomero neighbourhood. The Municipality has partly tried to solve these problems by the implementation of two projects in Via Rossini and Via Andrea da Salerno (near Piazza Quattro Giornate), providing about 150 new underground car parks with the consequent reorganization of the areas close to the interventions. Finally, in the re-organization of public spaces of the neighbourhood there is alsoFigureFigure Piazza 15. 15. Muzzi,The The SanSan a Carlosquare all’Arena located neighbourhood. neighbourhood.in the adjacent Arenella neighbourhood, where the building of an underground parking lot has given new life to the square. So, in this neighbourhoodTheThe trend trend in in characterized real real estateestate values values by the in in thepresence the Vomero Vomero of neighbourhood po neighbourhoodsitive census (Figure sections, (Figure 16), many on16 ),the oninterventions other the hand, other has hand,of hasurbanalways always redevelopment been been significantly signiﬁcantly have higher been higher thanimplemented than that that of the of in thecithety, city, perioddespite despite of a reference.decline a decline in 2012 in 2012(Figures (Figures 3 and3 4).and 4). In addition to the existence of five rail connections (two metro lines and three funicular lines), the Villa Floridiana (important “green lung” of the neighbourhood) and the Certosa of San Martino, is added the partial pedestrianisation of Via Luca Giordano in 2010 that connects with the already pedestrian Via Scarlatti, characterizing the neighbourhood by two main central arteries dedicated to trade, socialization, and leisure. Even the ancient “borgo Antignano” has been placed at the centre of a functional reorganization of the neighbourhood: A new lighting system has been designed and has been pedestrianised, allowing an area (that has always been used only as a neighbourhood market) to enjoy a renewed mix of functions that has contributed to the increase in real estate values.

FigureFigure 16.16. The Vomero neighborhood.

InEven addition the toSan the Ferdinando existence of neighbourhood ﬁve rail connections (Figur (twoe 17), metro rich linesin cultur andal three and funicular recreational lines), theattractions, Villa Floridiana has recorded (important real “greenestate lung”values ofhigh theer neighbourhood) than the average and of the the Certosa city over of Santhe Martino,years, is addedresisting the the partial crisis pedestrianisation that has hit the of city Via Lucain the Giordano period considered in 2010 that (Figures connects 3 withand the4). alreadyThis pedestrianneighbourhood, Via Scarlatti, despite characterizing having recorded the a neighbourhood 20% drop in real by estate two values main centralover the arteries decade, dedicated has some to trade,positive socialization, sections. andThe leisure.part of the Even neighbourhood the ancient “borgo showing Antignano” the most hassignificant been placed increase at the is “borgo” centre of a functionalSanta Lucia reorganization in which the of works the neighbourhood: for the redevelopm A newent of lighting Mount systemEchia (thanks has been to the designed funds of and the has “Pact for Naples”, an investment programme aimed at regenerating the territory and strengthening urban transport systems over a period of no more than seven years) are underway, and in which the next Chiaia station of the metro line 6 is expected to be opened. Positive census sections are near the pedestrianisation of Via Toledo and Via Verdi, Municipio metro station (building in 2015), with the consequent restyling of Piazza Municipio.

Figure 17. The San Ferdinando neighbourhood.

Sustainability 2019, 11, x FOR PEER REVIEW 20 of 27

Sustainability 2020, 12, 1211 18 of 24 been pedestrianised, allowing an area (that has always been used only as a neighbourhood market) to enjoy a renewed mix of functions that has contributed to the increase in real estate values. Traffic congestion and lack of parking spaces are among the main problems affecting the Vomero neighbourhood. The Municipality has partly tried to solve these problems by the implementation of two projects in Via Rossini and Via Andrea da Salerno (near Piazza Quattro Giornate), providing about 150 new underground car parks with the consequent reorganization of the areas close to the interventions. Finally, in the re-organization of public spaces of the neighbourhood there is also Piazza Muzzi, a square located in the adjacent Arenella neighbourhood, where the building of an underground parking lot has given new life to the square. So, in this neighbourhood characterized by the presence of positive census sections, many interventionsFigure 16. The ofVomero urban neighborhood. redevelopment have been implemented in the period of reference. EvenEven the the San San Ferdinando Ferdinando neighbourhood neighbourhood (Figure (Figur 17),e rich 17), in rich cultural in cultur and recreationalal and recreational attractions, attractions, has recorded real estate values higher than the average of the city over the years, has recorded real estate values higher than the average of the city over the years, resisting the crisis resisting the crisis that has hit the city in the period considered (Figures 3 and 4). This that has hit the city in the period considered (Figures3 and4). This neighbourhood, despite having neighbourhood, despite having recorded a 20% drop in real estate values over the decade, has some recorded a 20% drop in real estate values over the decade, has some positive sections. The part of the positive sections. The part of the neighbourhood showing the most significant increase is “borgo” neighbourhood showing the most significant increase is “borgo” Santa Lucia in which the works for the Santa Lucia in which the works for the redevelopment of Mount Echia (thanks to the funds of the redevelopment“Pact for Naples”, of Mount an investment Echia (thanks programme to the funds aimed of theat regenerating “Pact for Naples”, the territory an investment and strengthening programme aimedurban at transport regenerating systems the over territory a period and of strengthening no more than seven urban years) transport are underway, systems over and ain periodwhich the of no morenext than Chiaia seven station years) of the are metro underway, line 6 is andexpected in which to be theopened. next Positive Chiaia stationcensus sections of the metro are near line the 6 is expectedpedestrianisation to be opened. of Via Positive Toledo censusand Via sections Verdi, Municipio are near the metro pedestrianisation station (building of in Via 2015), Toledo with and the Via Verdi,consequent Municipio restyling metro of station Piazza (building Municipio. in 2015), with the consequent restyling of Piazza Municipio.

FigureFigure 17. 17. TheThe SanSan Ferdinando neighbourhood. neighbourhood.

The real estate trend in the Chiaiano neighbourhood (Figure 18) has not been aﬀected by excessive falls but, however, in the period considered, it has never been above or at least in line with the city average values (Figures3 and4). Despite of the presence of considerable positive census sections, the projects taking place in the last ten years are not such as, in our opinion, to justify such increases from a strictly urban point of view. Over the years, about 30 new houses (for the re-buildings after the earthquake) have been constructed in this neighbourhood. Moreover, it is at the centre of the “Parco delle Colline” project (by which a new opening was made in via dei Guantai ad Orsolona to support the Camaldoli Urban Park), including the “Selva di Chaiano” which, despite its “rethinking” as a “green lung”, is still in disastrous condition. In addition, since 2014, the project “A bridge over the walls” (“Un ponte oltre i muri”) has started, and an open-air art gallery has been realized. It has been planned through the Murales technique on the approximately 7000 sqm of the concrete wall of the Chiaiano metro station. Sustainability 2019, 11, x FOR PEER REVIEW 21 of 27

The real estate trend in the Chiaiano neighbourhood (Figure 18) has not been affected by excessive falls but, however, in the period considered, it has never been above or at least in line with the city average values (Figures 3 and 4). Despite of the presence of considerable positive census sections, the projects taking place in the last ten years are not such as, in our opinion, to justify such increases from a strictly urban point of view. Over the years, about 30 new houses (for the re-buildings after the earthquake) have been constructed in this neighbourhood. Moreover, it is at the centre of the “Parco delle Colline” project (by which a new opening was made in via dei Guantai ad Orsolona to support the Camaldoli Urban Park), including the “Selva di Chaiano” which, despite its “rethinking” as a “green lung”, is still in disastrous condition. In addition, since 2014, the project “A bridge over the walls” (“Un ponte oltre i muri”) has started, and an open-air art gallery has been Sustainabilityrealized.2020 It has, 12 ,been 1211 planned through the Murales technique on the approximately 7000 sqm of19 the of 24 concrete wall of the Chiaiano metro station.

FigureFigure 18.18. TheThe Chiaiano neighbourhood. neighbourhood.

TheThe Poggioreale Poggioreale neighbourhood neighbourhood hashas critical values values that that have have suffered suﬀered a adrop drop of ofabout about 20% 20% comparedcompared to to 2009, 2009, with with a a contraction contraction in in values values closeclose to 600 € // sqmsqm (Figure (Figures 3 3and and 4).4). DespiteDespite few few positive positive census census sections, sections, thethe PoggiorealePoggioreale neighbourhood neighbourhood shows shows critical critical situations situations (Figure(Figure 19 ).19). It It has has beenbeen signiﬁcantlysignificantly penalizedpenalized by by bureaucratic bureaucratic slowdowns slowdowns because because the the Urban Urban RegenerationRegeneration Plan Plan (URP) (URP) has has been been blocked. blocked. This This Plan Plan dates dates back back toto aa programmeprogramme agreementagreement signedsigned in 1994in among1994 among the Municipality, the Municipality, the Region, the Region, and theand Ministrythe Ministry of Public of Public Works. Works. It provided, It provided, within within the S. Alfonsothe S. neighbourhood,Alfonso neighbourhood, for theconstruction for the construction of equipment of equipment (such as (such a business as a business incubator incubator and a and nursery a school),nursery the school), redevelopment the redevelopment and re-organization and re-organizat of theion road of system, the road and system, the recovery and the ofrecovery the building of the of building of the former “Milk Plant”. theSustainability former “Milk 2019, 11 Plant”., x FOR PEER REVIEW 22 of 27 To date, the project has not been started (the first tender was not successful because of irregularities in the conclusion of the contract that led to a very long dispute), and today, many years later, the economic conditions that made that design possible at the time have evidently changed. Therefore, the current Urban Regeneration Plan is the subject of a series of redistribution of equipment. They maintain the same standards, but they are distributed over a different size. The only equipment to have been sacrificed is the large underground car park; however, parking areas will be ensured at ground level. At the moment, the Plan is being remodelled by the Region, and only after this phase it will be possible to proceed to a new tender. The implementation of the projects provided in Urban Regeneration Plan could contribute to a rise in market prices in this neighbourhood, which, to date, are still falling.

FigureFigure 19.19. TheThe Poggioreale neighbourhood. neighbourhood. ToFinally, date, the the project San Giovanni has not beena Teduccio started neighbourh (the first tenderood (Figure was not 20) successful shows, from because a residential of irregularities point inof the view, conclusion a negative of trend the contractbelow the that average led toof Naples a very (Figures long dispute), 3 and 4). and Instead, today, from many a commercial years later, thepoint economic of view, conditions it shows thatsigns made of recovery that design since possiblethe establishment at the time of haveApple evidently Developer changed. Academy and theTherefore, new pole of the the current University Urban of Naples Regeneration Federico PlanII. Probably, is the subject since these of a changes series of occurred redistribution in 2016, of equipment.they have Theynot yet maintain had repercussions the same standards, on the residential but they arereal distributed estate market, over which, a different compared size. Theto the only equipmentcommercial to haveone, is been affected sacrificed more slowly is the largeby the underground effects of urban car changes. park; however, parking areas will be ensured at ground level. At the moment, the Plan is being remodelled by the Region, and only after this phase it will be possible to proceed to a new tender. The implementation of the projects provided in Urban Regeneration Plan could contribute to a rise in market prices in this neighbourhood, which, to date, are still falling.

Figure 20. The San Giovanni a Teduccio neighbourhood.

7. Conclusions As showed in the previous paragraphs, the implemented projects have been quite one-off and heterogeneous (there have been no comprehensive urban strategies) in the period analysed. In the neighbourhoods where urban regeneration projects have been implemented (the seven selected neighbourhoods), even if they are punctual projects, real estate values have remained at least stable (if not increased). The best performances have been recorded where regeneration projects have included a mix of actions, from redevelopment, to accessibility, to the enhancement of infrastructures, to the valorization of cultural heritage. The integrated evaluation approach proposed in this study aims to provide support for a better understanding and interpretation of urban dynamics, and to orient and activate, consequently, the appropriate planning policies, implementing actions, and projects that are more appropriate to the “vocation” of each area. Sometimes urban regeneration projects and the consequent increase in real estate values can have negative effects, such as the phenomenon of gentrification: Prices rise too much and therefore sales transactions (or rents) decrease, and a “touch and go” tourism develops

Sustainability 2019, 11, x FOR PEER REVIEW 22 of 27

Sustainability 2020, 12, 1211 20 of 24 Figure 19. The Poggioreale neighbourhood.

Finally,Finally, the the San San Giovanni Giovanni a Teduccioa Teduccio neighbourhood neighbourhood (Figure (Figure 20 20)) shows, shows, fromfrom aa residentialresidential point of view,of view, a negative a negative trend trend below below the average the average of Naples of Naples (Figures (Figures3 and 34 and). Instead, 4). Instead, from from a commercial a commercial point of view,point of it showsview, it signs shows of signs recovery of recovery since the since establishment the establishment of Apple of DeveloperApple Developer Academy Academy and the and new polethe of new the pole University of the University of Naples of Federico Naples II.Federico Probably, II. Probably, since these since changes these occurredchanges occurred in 2016, in they 2016, have notthey yet have had repercussionsnot yet had repercussions on the residential on the realresidential estate market,real estate which, market, compared which, compared to the commercial to the one,commercial is aﬀected one, more is affected slowly bymore the slowly eﬀects by of the urban effects changes. of urban changes.

FigureFigure 20. 20.The The SanSan GiovanniGiovanni a Teduccio neighbourhood. neighbourhood.

7. Conclusions7. Conclusions AsAs showed showed in in the the previous previous paragraphs, paragraphs, thethe implementedimplemented projects projects have have been been quite quite one-off one-o andff and heterogeneousheterogeneous (there (there have have been been no no comprehensive comprehensive urban strategies) in in the the period period analysed. analysed. In Inthe the neighbourhoodsneighbourhoods where where urban urban regenerationregeneration projectsprojects have been been implemented implemented (the (the seven seven selected selected neighbourhoods),neighbourhoods), even even if theyif they are are punctual punctual projects, projects, real real estate estate values values have have remained remained atat leastleast stablestable (if not(if increased). not increased). The best The performances best performances have beenhaverecorded been recorded where regenerationwhere regeneration projects projects have included have a mixincluded of actions, a mix from of redevelopment,actions, from toredevelopment, accessibility, toto the accessibility, enhancement to ofthe infrastructures, enhancement toof the valorizationinfrastructures, of cultural to the heritage.valorization of cultural heritage. TheThe integrated integrated evaluation evaluation approach approach proposedproposed in this study study aims aims to to provide provide support support for for a better a better understandingunderstanding and and interpretationinterpretation of of urban urban dynamics dynamics,, and and to orient to orient and andactivate, activate, consequently, consequently, the theappropriate appropriate planning planning policies, policies, impl implementingementing actions, actions, and and projects projects that that are are more more appropriate appropriate to tothe the “vocation”“vocation” of of each each area. area. Sometimes Sometimesurban urban regenerationregeneration projects projects and and the the consequent consequent increase increase in inreal real estateestate values values can can have have negative negative eff ects,effects, such such as theas the phenomenon phenomenon of gentrification: of gentrification: Prices Prices rise rise too muchtoo andmuch therefore and therefore sales transactions sales transactions (or rents) decrease,(or rents) anddecrease, a “touch and and a “touch go” tourism and go” develops tourism [79 develops]. In order to prevent that, urban development processes increase economic attractiveness, but cause negative impacts on other dimensions (for example, by changing the social composition of neighbourhoods), and social and cultural components must be taken into account in regeneration strategies and policies (i.e., through bottom-up approaches). Revitalizing a poor or degraded neighbourhood economically, without also considering social impacts (and therefore the phenomenon of gentrification, for example), only “moves” the problem of poverty to another area of the city. To this end, the MCDA methods are a useful tool for evaluating alternative projects considering different criteria and including various actors/stakeholders and points of view. In this study, the integration of a Multi-Criteria Decision Analysis (MCDA) and Geographical Information System (GIS) allowed us to map and analyse the territory, linking a specific issue (the real estate dynamics) to the territory itself, and to analyse it according to specific criteria. In particular, here the use of geoTOPSIS allows classifying and discretizing urban areas in order to understand which ones have maintained the best or worst performance during the period considered. This can support decision makers in a clearer and more detailed reading of the territory in order to identify the areas in which to plan new interventions. Sustainability 2020, 12, 1211 21 of 24

Furthermore, the analysis at a high level of deﬁnition, such as that of census sections, can be useful for future steps of the research, representing a base for elaborating analysis linking the real estate dynamics with other information collected for the same sections for the census. This integrated approach can support the governance of cities and the development of strategies for enhancing the comprehensive territorial productivity.

Author Contributions: Conceptualization, P.D.T.; methodology, P.D.T., F.N.; data curation, A.R., L.S.; formal analyses, P.D.T., F.N.; writing—original draft writing, F.N.; writing—review and editing, F.N. All authors have read and agree to the published version of the manuscript. Funding: This research was founded by the Ministry of Education, University and Research (MIUR) under the Research Project of Relevant National Interest (PRIN) program (Project title: “Metropolitan cities: territorial economic strategies, financial constraints and circular regeneration”). Conflicts of Interest: The authors declare no conflict of interest.

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