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Multicriteria Evaluation of Urban Regeneration Processes: An Application of PROMETHEE Method in Northern Italy.

1. Introduction

In recent years many European cities have implemented relevant renewal programmes for enhancing physical, environmental, social, and economic long-term development of old industrial sites or areas under decline. Integrated regeneration processes represent the main concern in many experiences. Physical transformations are embedded within social, environmental, and economic as well as institutional aspects [1]. How to achieve a balance among interrelated and often conflictual goals in order to improve the quality of urban systems is still an open challenge. On one side the need of replacing top-down strategies with collaborative models, based on needs, expectations, and values shared by all the parties involved, is widely acknowledged as one of the driver of success [2-4]. On the other one, local oppositions often arise against both public and private works, thus causing interruptions and delays to development processes [5].

Territorial and urban regeneration programmes specifically point out the need of developing new combinations between analytical tools and participatory approaches, in order to strengthen the choices' legitimacy and to address the wealth of contradictory visions, and preferences of the different actors to a shared vision according to a multilevel governance perspective. A critical review of the notion of reuse over time has revealed an emerging attention to the quality issue that does not only depend on development and design tools focused on environmental targets, but also on the managerial approach of local authorities in structuring multiform partnerships [6].

Under these circumstances, evaluation plays a crucial role since it allows to codefine and rank alternative projects with respect to both technical elements, which are based on empirical observations, and non-technical elements, which are based on social visions, preferences, and feelings [7].

In this context, a very useful support is provided by Multiple Criteria Decision Analysis (MCDA) techniques, which are used to make a comparative assessment of alternative projects or heterogeneous measures [8, 9]. These methods allow several criteria to be taken into account simultaneously in a complex situation and they are designed to help decisionmakers (DMs) to integrate the different options, which reflect the opinions of the involved actors, in a prospective or retrospective framework. Participation of decision-makers in the process is a central part of the approach.

Aware of the advantages and disadvantages of the many available MCDA techniques, this paper aims at testing the PROMETHEE (Preference Ranking Organisation Method for Enrichment Evaluations), as an outranking method [10] to support decisions in urban planning and regeneration processes. Given the lack of robust assumptions on the decision maker preferences, the PROMETHEE can be effectively integrated with participatory methods in order to get enough information to understand whether one alternative is at least as good as another.

In particular, the paper refers to the assessment of different urban regeneration scenarios for the city of Collegno (Italy). Differently from Bottero et al. [11], who modeled urban resilience dynamics in Collegno by using Fuzzy Cognitive Maps, and complementing Bottero et al. [12] who combined Stakeholder Analysis and Stated Preference Methods to assess the social value of urban regeneration scenarios in Collegno and their related willingness to pay, we combine the PROMETHEE approach with SWOT Analysis and Stakeholder Analysis, to rank six urban regeneration alternatives and identify the solution that outranks the others, thus providing decision-makers with useful tools in making welfare-maximizing urban planning decisions. We thus aim to contribute framing a multimethodological evaluation process which can be transferred, once validated, in other decision contexts [13].

The remainder of the paper is organized as follows. Section 2 provides a methodological background and a brief literature review; Section 3 illustrates the application of PROMETHEE in the evaluation of urban renewal projects in the city of Collegno (Italy); in Section 4 results are discussed and conclusions are drawn.

2. Methodological Background

The PROMETHEE method is one of the most recent Multicriteria Decision Analysis (MCDA) methods which was firstly proposed by Brans in the early Eighties [10] and subsequently extended by Brans and Vincke [14], Brans et al. [15], Brans and Mareschal [16], and Brans and Mareschal [17]. Usually a multicriteria problem is an ill-posed mathematical problem as it does not find a solution which optimizes all of the criteria simultaneously. As other multicriteria methods, the PROMETHEE requires additional information to overcome the poorness of dominance relation on Preference (P) and Indifference (I), thus enriching the dominance graph [18]. The PROMETHEE is an outranking method for ranking a finite set of alternative actions when multiple criteria, which are often conflicting, and multiple decision-makers are involved [8]. PROMETHEE uses partial aggregation and by a pairwise comparison of alternative actions, it allows to verify whether under specific conditions one action outranks or not the others. The PROMETHEE methods are a family of outranking methods [19]: PROMETHEE I (partial ranking); PROMETHEE II (complete ranking); PROMETHEE III (ranking based on intervals); PROMETHEE IV (continuous case); PROMETHEE V (including segmentation constraints); and PROMETHEE VI (evaluating the degree of hardness of a multicriteria decision problem with respect to the weights given to the criteria, i.e., for human brain representation). In addition, in 2004 Figueira et al. [20] proposed two extensions of the PROMETHEE, namely PROMETHEE TRI to solve sorting problems, and PROMETHEE CLUSTER for nominal classification.

In this paper we implement PROMETHEE II in order to rank alternatives according to different criteria which have to be maximized or minimized. Once the decision group was constituted, we proceeded according to the following subsequent steps.

Step 1 (construction of an evaluation matrix). A double entry table for the selected criteria and alternatives has been compiled by using cardinal (quantitative) and ordinal (qualitative) data. This matrix accounts for deviations of evaluations on pairwise comparisons of two alternatives, a and b, on each criterion.

Step 2 (identification of the preference function Pj(a, b) for each criterion j). The preference function is used to determine how much alternative a is preferred to alternative b and it translates the difference in evaluations of the two alternatives into a preference degree. These preferences are represented in a numerical scale ranging between 0 and 1. The value "1" represents a strong preference of alternative a over b, whereas "0" represents the indifferent preference value between the two alternatives. Six types of preference functions have been proposed by the developers of the PROMETHEE methodology: Usual criterion, Quasi criterion (U-shape), Criterion with linear preference (V-shape), Level criterion, Linear criterion, and Gaussian criterion [15, 21].

Step 3 (calculation of the overall preference index [PI](a,b)). The overall preference index [PI](a, b) represents the intensity of preference of a over b and it is calculated as follows (1):

[PI]n(a,b) = [k.summation over (j=1)] [w.sub.j] [p.sub.j] (a,b) (1)

where [pi] (a, b) is the overall preference intensity of a over b with respect to all of the K criteria, [w.sub.j] is the weight of criterion I, and [p.sub.j](a,b) is the preference function of a over b with respect to criterion j. Clearly [PI](a,b) ~0 implies a weak global preference of a over b, whereas [PI](a,b) ~ 1 implies a strong global preference of a over b.

Step 4 (calculation of the outranking flows, i.e., positive flow [[PHI].sup.+](a) and negative flow [[PHI].sup.-1] (a)). In PROMETHEE method two flow measures can be determined for each alternative. There are a positive flow (it expresses how alternative a is outranking all the others)

[[PHI].sup.+] (a) = 1/n - 1 [summation over (b[member of]A)] [PI] (a,b) (2)

and negative flow (it expresses how alternative a is outranked by all the others)

[[PHI].sup.-] (a) = 1/n - 1 [summation over (b[member of]A)] [PI] (b,a) (3)

Step 5 (comparison of the outranking flows to define the alternatives complete ranking). In detail, PROMETHEE II, here implemented, provides a complete ranking of the alternatives by calculating the net flow (4):

[PHI](A) = [[PHI].sup.+] (a) - [[PHI].sup.-] (a). (4)

The higher the net flow, the better the alternative. When PROMETHEE II is considered, no incomparability remains, as all the alternatives are comparable on all the criteria. It is worth noting that the net flow provides a complete ranking and thus can be compared with a utility function.

In the past decade, a growing interest arose in identifying solutions which reflect reality as much as possible by modeling it in a clear and understandable way by both analysts and decision-makers. Conceptually, PROMETHEE is a rather simple ranking method compared with other methods for multicriteria analysis [15] and the number of its applications to real world decision problems increased significantly [22]. The applications of PROMETHEE methods are varied and cover as major fields environmental management, water management, business and financial management, logistics and transportation, and energy management [22]. There are several applications as well in social sciences starting from seminal works by D'Avignon and Mareschal [23] and Urli and Beaudry [24] on hospital services and allocation of funds to development programs, respectively. Nonetheless, PROMETHEE applications in urban and territorial planning are quite recent. Mavrotas et al. [25] adopted PROMETHEE for comparatively evaluating control strategies to reduce air pollution in Tessaloniki and base their procedure on active involvement of local and central authorities; Anton et al. [26] applied PROMETHEE for the management and disposal of solid wastes in an Andine area; Juan et al. [27] used the PROMETHEE method combined with fuzzy set theory to determine the priority of 13 urban renewal projects in Taipei City, whereas Roozbahani et al. [28] combined PROMETHEE with Precedence Order in the Criteria (POC) to urban water supply management in Melbourne to assess operation rules in single or group decision-making contexts. More recently Cilona and Granata [29] implemented the PROMETHEE approach to support prioritization of subprojects in complex renewal projects at neighborhood scale; Esmaelian et al. [30] implemented PROMETHEE IV and GIS to identify most vulnerable urban areas to earthquakes and they prove its efficacy in electing the most suitable locations for the construction of emergency service stations; Polat et al. [31] proposed an integrated approach which combines the Analytic Hierarchy Process (AHP) and the PROMETHEE method to support construction companies to select urban renewal projects to invest in; Bottero et al. [32] used PROMETHEE methods to analyze different urban regeneration scenarios in Gran Canaria island; Cerreta and Daldanise [33] proposed PROMETHEE to support urban regeneration by a learning and negotiation process; Dirutigliano et al. [34] applied PROMETHEE as a support tool for promoting energy retrofitting of urban districts in Torino; Mendonca Silva et al. [35] used PROMETHEE method to solve an urban planning conflict in Recife; Wagner [36] adopted PROMETHEE to assist the decision-making process in spatial urban planning, whereas Tscheikner-Gratl et al. [37 ] compared PROMETHEE to other four multicriteria decision aiding/making methods (i.e., ELECTRE, AHP, WSM, and TOPSIS) in rehabilitation planning of urban water networks.

3. Application

The case study considered in the present paper is related to the urban regeneration program of the city of Collegno, located in the metropolitan area of Torino (Northern Italy). The program, promoted by the Municipal Administration, aims at finding answers to the economic and social needs of the city and to provide a coherent development strategy to a territory afflicted by an unregulated development and by the presence of many abandoned areas.

The objectives of the program are mainly related to the regeneration of the city as "Collegno Social Town". The creation of a nice and livable place and the elimination of physical and environmental limits are the key elements of the development strategy. The area of the Fermi metro station, including the site of Campo Volo, represents a crucial portion of the territory under investigation.

3.1. Structuring of the Decision Problem. The first step for the evaluation refers to the structuring of the decision problem, i.e. identifying the possible alternative strategies for the urban regeneration program and defining the criteria to be included in the model. For this purpose, an integrated framework has been proposed in the present application that aims at setting the problem and highlighting its key elements. More precisely, two different analyses have been performed, namely, the SWOT Analysis and the Stakeholders Analysis.

In detail,

(i) the SWOT (Strengths, Weaknesses, Opportunities, and Threats) Analysis is a technique used to define strategies, in those context which are characterized by complexity and uncertainty, such as urban regeneration. The analysis was used for a critical interpretation of the case under investigation and for supporting the definition of the goal of the transformation and the construction of the alternative projects;

(ii) the Stakeholders Analysis allows to define who are the actors of the process under investigation. As stated by Yang (2013), in the context of urban transformation real-world problems, only if stakeholders' interests are identified, it is possible to sufficiently empower them in the decision-making process. Moreover, the analysis permits to define which resources and objectives the actors are able to bring into play, showing possible conflicts. Finally, by means of Stakeholders Analysis the complexity of the decisional process can be represented, suggesting the evaluation criteria to be considered for the comparison of the alternative strategies (Figure 1).

3.2. Alternative Transformation Projects. In this experimentation, we have implemented an integrated approach to evaluate six different alternatives related to the development of the urban regeneration program of the city of Collegno.

In detail, starting from the alternatives analyzed by Bottero et al. [11,12], we have selected six alternative projects, which we consider the most relevant according to the SWOT and Stakeholders Analyses. These alternatives can be described as follows (Figure 2):

(1) Cultural district: this strategy is based on the creation of new cultural services for the area, including a new public library and residences for university students.

(2) Smart City: the goal of this strategy consists in providing a new identity to the area based on the concept of smart city.

(3) Start up: this project focuses on the creation of innovative business activities in the area.

(4) City and craft: this strategy is based on the valorization of the small economic activities in the area and on the creation of a new urban park in the Northern part of the area.

(5) Sharing city: the objective of this project is mainly related to the valorization of the public spaces in the area, with special attention to innovative shared solution for living and working.

(6) Green infrastructure: the main intent of this strategy is to improve the livability of the territory, with particular attention to the creation of new green infrastructures, such as pedestrian and bicycle paths.

3.3. Definition and Evaluation of the Criteria. In accordance with the results of the two aforementioned analyses, we identified the most important drivers of the transformation that can be summarized in Table 1. In particular, SWOT and Stakeholders Analysis allowed breaking down the complexity of the problem and identifying general aspects that characterize the transformation to be defined, namely, environmental, economic, social, regeneration, mobility, and services factors. These aspects have been then further investigated in order to obtain a set of measurable attributes for the evaluation of the alternatives.

The subsequent step consists in assessing the performance of the alternatives from the point of view of the evaluation criteria and in assigning a preference function with related thresholds of the criteria (q, p) (Table 2).

3.4. Weights Determination. For the development of the PROMETHEE II method, different decision scenarios have been taken into account. The different scenarios reflect the point of view of different actors who can face the problem under investigation. For this purpose, in the application of the methodology personal interviews with experts in different fields and local decision-makers were developed. In particular, 5 experts have been considered for the evaluation, whose expertise was in urban design, economic evaluation, history of architecture, landscape architecture, and sociology. According to the revised Simos procedure [38], the interviews were carried out through the set of cards methodology that allows for setting the criteria weights and determining their priority, according to actors' preferences. The weight values obtained by different experts are shown on the axes of radar charts displayed in Figure 3. As it is possible to see, all the actors agreed in considering the regeneration aspects as the most important ones. On the contrary, the criteria related to parking spaces and new commercial developments are not important according to all the actors involved in the evaluation.

3.5. Results. The ranking of alternative options was derived by implementing the decision support software Visual PROMETHEE 1.4 [39].

Figure 4 shows the final ranking of the alternative strategies with reference to the sets of weights resulting from the interviews to different actors involved. By direct inspection of Figure 4, it emerges that the ranking is preserved in all the cases and for all the strategies. The "Sharing city" alternative is confirmed as the best performing strategy for the successful implementation of the urban transformation/regeneration process. According to our results, the "Green infrastructures" alternative is worth of consideration too, as it is placed as second in the actors' ranking.

To complement the discussion of our results, we consider worth of mentioning the novelty of our approach to the evaluation of complex urban transformation processes and their long-term effects.

Decision problems in urban planning, and specifically those which are concerned with the design and implementation of urban transformation/regeneration process, are often ill-structured problems, as they involve multiple actors and stakeholders, often conflicting objectives and views and are characterized by significant uncertainty over potential outcomes of alternative design options and planning actions. In this context the valuation of alternative scenarios is a complex process, where various aspects need to be accounted for simultaneously. These aspects comprise both technical and non-technical issues and characteristics. The formers build on empirical observations, whereas the latters are usually based on social visions, preferences and feelings [13].

In this paper we adopted a mixed-method research approach to address the issue of urban planning and projects evaluation. In detail, in accordance with Creswell et al. [40], we developed a multiphase mixed-method that allows for considering the subsequent phases of projects formulation and implementation, and thus considering as inputs for the next analysis the results/outputs of the previous one. We combined different methods for the design and selection of alternative urban regeneration projects and strategies, and structured a multiphase decision aiding process meant to support strategic planning. To structure the decision problem we implemented a SWOT Analysis and a Stakeholder Analysis. Problem structuring is in fact a fundamental phase in any decision problem, which involves multiple actors and perspectives, and conflicting stakes to be conciliated, but it becomes of greater importance when alternatives are not a priori designed in detail as in this case [41-45]. We firstly carried out a SWOT Analysis, which provided an in-depth knowledge of the problem and context under investigation, and of the correlation between endogenous and exogenous factors. In this phase, data and information were collected, the objectives were identified and potential alternative scenarios were defined at a preliminary stage. We then performed a Stakeholder Analysis, informed by the SWOT Analysis, through which we identified the actors involved in the problem, and their values and objectives. Stakeholder Analysis allowed to identify conflicting interests at an early stage of the process and develop a strategic view of the human and institutional framework, the relationships among different actors and their concerns. In fact it plays a key role in strategic planning and urban regeneration processes. The above-mentioned analyses informed the last phase of the mixed-method approach (e.g., criteria express actors' objectives and needs), in which PROMETHEE method was implemented to assess the alternative scenarios under investigation, obtain a list of priorities, and identify the best performing urban regeneration strategy. Table 3 provides an insight in our multiphase decision aiding process, synthetizes strengths and limitations of SWOT Analysis, Stakeholder Analysis and PROMETHEE method respectively, and illustrates main results obtained from their implementation in the city of Collegno case study.

4. Discussion and Conclusions

Multicriteria Analysis is nowadays widely implemented in decision and valuation processes, and specifically in urban planning. Urban planning and urban regeneration processes are multidimensional concepts and involve socioeconomic, environmental, technical, and ethical perspectives, which are strongly interconnected and cannot be addressed by referring exclusively to economic issues: urban renewal projects are often faced by many challenges, such as destruction of existing social networks, expulsion of vulnerable groups, and adverse impacts on the living environment.

Therefore, in urban planning, due to intrinsic complexities and to the high number of stakeholders and actors involved in the decision process, multicriteria techniques and methodologies can be efficiently implemented to identify efficient solutions, which accounts for decision-makers and actors preferences, as well as for public choice policy objectives [46]. To some extent, urban planning is meant to respond to challenges, improve communication between government or public administrations and stakeholders, allocate budgets according to a list of priorities, and favor long and mid-term investments. In addition, to be effective and successful, urban planning requires a commitment by the government to achieve strategic goals, a common understanding on prioritization of actions, and the involvement of the society and the private sector that collaborate to develop and implement strategic plans.

This paper shows how the PROMETHEE II method can be usefully implemented in decision problems related to urban planning and development projects; namely, in this paper the PROMETHEE method is used to determine the projects' priority. In detail, we evaluated different regeneration scenarios for the city of Collegno according to a set of qualitative and quantitative criteria, which account for social, environmental, mobility and economic key factors. As the dominance relation is poor on preference and indifference, incomparability holds for most of pairwise comparisons and additional information is needed to make a decision. By outranking relations, the PROMETHEE method provides realistic enrichments of the dominance relation despite incomparability relations are not completely eliminated. In this respect, the integration of SWOT Analysis and Stakeholder Analysis increased the information useful for ranking the scenarios, thus confirming the importance of supporting cross-sector approaches in sustainable regeneration projects.

The scenarios under investigation were evaluated according to experts judgments, local stakeholders and decisionmakers' preferences, values and objectives.

According to the results of PROMETHEE II, scenario 5 the "Sharing city project" is the most desirable and comprising alternative to implement, whereas scenario 6 the "Green Infrastructure" is ranked as second, except for the judgments expressed by the expert in landscape architecture. Our results show that the other alternatives cannot be listed in the same descending order of their net flows for each expert. As multiactor analysis shows, the "Sharing City" alternative encompasses the preferences of the entire group of five experts involved in the decision process. The results obtained from the Visual PROMETHEE software highlight the usefulness of multicriteria outranking methods in spatial decision-making problems. Multiactors analysis was indeed useful in clarifying the most appropriate project, by taking into account the point of views of different actors.

The comprehensive and integrated approach proposed in this paper accounts for key factors in urban renewal, provides a useful tool to assess renewal projects from the standpoint of urban competitiveness and sustainability, and may have interesting policy implications by providing policy makers with useful guidelines for investments to be undertaken. Successful implementation of urban renewal is de facto a crucial driver in promoting sustainable urban development and improving urban competitiveness and attractiveness. In this respect the PROMETHEE method can be useful in assisting decision-makers in selecting urban renewal programs and projects in a more objective and realistic way.

Data Availability

The data used to support the findings of this study are available from the corresponding author upon request.

Conflicts of Interest

The authors declare that there are no conflicts of interest regarding the publication of this paper.


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Marta Bottero, (1) Chiara D'Alpaos, (2) and Alessandra Oppio (3)

(1) Department of Regional and Urban Studies and Planning, Politecnico di Torino, Italy

(2) Department of Civil, Environmental and Architectural Engineering, University of Padova, Italy

(3) Department of Architecture and Urban Studies, Politecnico di Milano, Italy

Correspondence should be addressed to Marta Bottero;

Received 23 April 2018; Revised 7 September 2018; Accepted 11 October 2018; Published 14 November 2018

Academic Editor: Mhand Hifi

Caption: Figure 1: Stakeholders mapping for the case under investigation.

Caption: Figure 2: Alternative strategies considered in the evaluation model [Figure 2 is reproduced from Bottero et al. [11]].

Caption: Figure 3: Sets of weights resulting from the different actors.

Caption: Figure 4: Ranking comparison for the different actors.
Table 1: Evaluation criteria for the PROMETHEE model
[Table 1 is reproduced from Bottero et al. [11]].

Criteria                         Description

[C.sub.1] Public/private         Ratio between public and private
spaces                           surfaces

[C.sub.2] Co-working spaces      Surface of the structures for
                                 workshop, meeting, training courses

[C.sub.3] Co-housing             Number of residents in new co-
inhabitants                      housing buildings

[C.sub.4] Permeable surface/     Ratio between permeable areas and
territorial surface              overall territorial surface of the

[C.sub.5] Urban gardens          Total area used for community and
                                 private urban gardens

[C.sub.6] Waste production       Amount of waste produced in a year
                                 by the activities of the program

[C.sub.7] Residential areas      Surface for residential functions

[C.sub.8] Retail areas           Surfaces for commercial functions

[C.sub.9] Sport and leisure      Surfaces for sport and cultural
areas                            activities

[C.sub.10] Mixite index          Index that describes the functional
                                 mix of the area

[C.sub.11] Slow mobility         Surface of the pedestrian tracks
                                 and bicycle lanes

[C.sub.12] New public parking    Number of new public parking lots

[C.sub.13] Car sharing/bike      Number of car and bike sharing
sharing                          points

[C.sub.14] Total Economic        Estimate of the social benefits
Value                            delivered by the program

[C.sub.15] Investment cost       Total cost of the program

[C.sub.16] New jobs              Number of new jobs created

[C.sub.17] Regeneration          Regenerated surface

[C.sub.18] Via De Amicis         Qualitative index showing the level
regeneration                     of the regeneration of Via De

[C.sub.19] Territorial index     Ratio between the maximum buildable
                                 volume and the territorial surface

Table 2: Input matrix for the PROMETHREE evaluation.

                         Ratio between    Surface of        No. of
                          public and          the        residents in
                            private       structures        new co-
                           services      for workshop,      housing
                                           meeting,        buildings

CULTURAL DISTRICT            4,31            20425            398
SMART CITY                   3,25            24260            150
START UP                     1,33            49880            255
CITY AND CRAFTS              8,35            11328            421
SHARING CITY                 2,76            5108            2513
GREEN INFRASTRUCTURE         4,20            3300            1036

                         Ratio between    Total area       Amount of
                           permeable       used for          waste
                           areas and     community and   produced in a
                            overall      private urban    year by the
                          territorial       gardens      activities of
                          surface of                      the program
                          the program

CULTURAL DISTRICT            0,69            8.527         1.350.845
SMART CITY                   0,39            2.130         2.332.234
START UP                     0,58           25.569         2.692.663
CITY AND CRAFTS              0,52           66.894         1.817.205
SHARING CITY                 0,53           23.118         3.014.301
GREEN INFRASTRUCTURE         0,71           12.888         1.631.941

                          Surface for     Surface for     Surface for
                          residential     commercial       sport and
                         function (SLP     functions       cultural
                            in m2)        (SLP in m2)     activities
                                                          (SLP in m,)

CULTURAL DISTRICT           70.880          28.031          48.150
SMART CITY                  117.736         59.169          81.796
START UP                    82.330          95.000          26.960
CITY AND CRAFTS             164.925         84.248          21.458
SHARING CITY                538.018         40.192          114.725
GREEN INFRASTRUCTURE        75.252          25.515          37.920

                         Mixite index

CULTURAL DISTRICT            0,71
SMART CITY                   0,46
START UP                       1
CITY AND CRAFTS              0,30
SHARING CITY                 0,30

                          Surface of      No. of new      No. of car
                              the        parking lots      and bike
                          pedestrian                        sharing
                          tracks and                        points
                         bicycle lanes

CULTURAL DISTRICT           68.326           1.385             7
SMART CITY                  171.609          2.567            12
START UP                    16.000           2.100             2
CITY AND CRAFTS             132.541          1.137             3
SHARING CITY                624.933          1.689            14
GREEN INFRASTRUCTURE        251.831          1.394            19

                         Estimate the    Total cost of    No. of new
                            social        the program    jobs created
                           benefits        ([euro])
                         delivered by
                          the program
                         (VETin [euro])

CULTURAL DISTRICT          2.550.746      233.336.184        1.010
SMART CITY                  537.692      279.468.,021        1.545
START UP                   3.500.000      100.000.000         300
CITY AND CRAFTS            7.471.328      183.948.594         736
SHARING CITY               7.707.778      494.055.026        3.229
GREEN INFRASTRUCTURE        531.155       231.527.860         768

                          Regenerated     Qualitative    Ratio between
                            surface      Index for the    the maximum
                         (Regenerated    regeneration      buildable
                           SLP/Total       of Via De      volume and
                             SLP)           Amicis            the
CULTURAL DISTRICT             0,2              3             0,38
SMART CITY                   0,12              5             0,16
START UP                     0,51              4             0,23
CITY AND CRAFTS              0,36              4             0,52
SHARING CITY                 0,06              5             0,40
GREEN INFRASTRUCTURE         0,20              5             0,13

Table 3: Strengths and limitations of the proposed evaluation methods
and relative results from the city of Collegno case study.

Evaluation     Strengths and Limitations    Results from the city of
method                                      Collegno case study

SWOT           + Improvement of overall     The SWOT Analysis allowed
Analysis       understanding of the         the definition of the
               decision problem general     guidelines for the design
               framework                    and implementation of the
                                            general masterplan as well
               + Provision of a             as the identification of
               systematic approach to       the transformation process
               analyse and decompose        layout. It played a key
               complex problems             role in supporting experts
                                            and planners in the
               + Identification of          identification of
               correlation between          alternative scenarios for
               internal factors,            urban transformation/
               strengths and weaknesses     regeneration.
               and external factors,
               opportunities and threats

               + Ease of use and
               understanding of results

               -Open nature and
               unstructured method

               -Preliminary level of

               -Tendency to overemphasize

               -Lack of prioritisation of
               factors (no requirement
               for their classification
               and evaluation)

               -Risk of

               -Risk of over-
               subjectivity in the
               generation of factors

Stakeholders   + Improvement in             The Stakeholders Analysis
Analysis       stakeholders management      provided the
               and mobilization of their    identification of relevant
               support in achieving a       actors in the
               goal                         transformation and
                                            relative values and
               + Identification of          perspectives. These actors
               purpose and time-            are mostly private
               dimension of interest        investors and developers,
                                            who have financial
               + Identification of time-    resources available for
               frame and resource           undertaking investments
               availability                 and carry out the urban
                                            regeneration process. The
               + Provision of               Municipality of Collegno
               comprehensive analysis       and the social groups
               meant to produce new         involved in the process
               knowledge about policy-      proved to be relevant
               making processes             actors as well.

               + Prediction or
               encouragement of
               stakeholder alliances

               -Need for great reliance
               on quantitative approaches
               to data collection

               -Need for iterative
               processes in data
               collection and analysis

               -Inappropriateness of
               feedback of results when
               stakeholders may influence
               or control analysis

               -Uncertainty over validity
               and reliability of results

               -Potential biases
               generated by analysts who
               become implicitly
               stakeholders who bring to
               the analysis their own
               values, perspectives and
               problem understanding

PROMETHEE      + Ease of use                The analysis performed by
Approach                                    implementing the PROMETHEE
               + Provision of a complete    method allowed the
               ranking                      comparisons of urban
                                            transformation alternative
               + Accuracy of results        options and the
                                            identification of the best
               + Adoption of the            performing solution for
               concordance non-             the regeneration process.
               discordance principle in     The results show that the
               the definition of the        considered sets of weights
               overall preference index     converge in ranking the
                                            "Sharing city" alternative
               + Limited total              as the most preferred
               compensation between pros    option, and the "Green
               and cons                     infrastructure"
                                            alternative as the second
               + No assumption on the       best option.
               requirement of criteria to
               be proportionate

               + Avoidance of the
               commensurability problem

               -Non triviality in
               preference structuring in

               -Assignment of weights
               that does not build on a
               clear method

               -No information on the
               cost-effectiveness or
               profitability of
               alternatives (are they

               -Assignment of values that
               does not build on a clear

               -Difficulties in selecting
               the generalized criterion
               functions and the
               associated thresholds for
               each criterion

               -Computational limitations
               with respect to the number
               of decision alternatives
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Article Details
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Title Annotation:Research Article
Author:Bottero, Marta; D'Alpaos, Chiara; Oppio, Alessandra
Publication:Advances in Operations Research
Article Type:Report
Geographic Code:4EUIT
Date:Jan 1, 2018
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