Public Initiatives of Settlement Transformation: A Theoretical-Methodological Approach to Selecting Tools of Multi-Criteria Decision Analysis
Abstract
:1. Introduction and Aims of the Work
- ELimination Et Choix Traduisant la REalitè (ELECTRE) [22];
- Multi-attribute utility theory (MAUT) [23];
- Analytic Network Process (ANP) [24];
- Measuring Attractiveness by a Categorical Based Evaluation (MACBETH) [25];
- Analytic Hierarchy Process (AHP) [26];
- Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) [27];
- Preference Ranking Organization Method for Enrichment Evaluations (PROMETHEE) [28].
- -
- no method (hereinafter ‘tool’) can be considered perfect or applied to every type of problem [13];
- -
- the range of available procedures offers different operating opportunities, but also poses the risk of using tools not suited to the decision-making problem at hand [20];
- -
- an axiomatic analysis of decision-making procedures has yet to be carried out [13].
2. Multi-Criteria Decision Analysis (MCDA): Structure, Endogenous Variables, Exogenous Variables
2.1. Framework
2.2. Exogenous Variables
2.2.1. The Number of Evaluation Elements
2.2.2. Typology of Indicators
2.2.3. Stakeholders to be Included in the Decision Process
2.2.4. Typology of the Expected Solution
2.2.5. Technical Support from a Decision Aid Specialist during the Implementation of the Procedure
2.3. Endogenous Variables
2.3.1. Type of Decision-Making Problem
- Description problem: the need to identify the main distinctive features for a group of alternatives;
- Sorting problem: definition of homogeneous groups of alternatives by characteristics;
- Ranking choice problem: ranking of alternatives, from best to worst.
2.3.2. Solution Approach
- Full aggregation approach: “A score is evaluated for each criterion and these are then synthesized into a global score. This approach assumes compensable scores, i.e., a bad score for one criterion is compensated for by a good score on another” [13]. These scores are expressed considering the performance set of the alternatives according to the criteria and sub-criteria selected for the implementation of the analysis. The scores allow to each alternative to be comparable with each other;
- Outranking approach: “A bad score may not be compensated for by a better score. The order of the option may be partial because the notion of incomparability is allowed. Two options may have the same score, but their behavior may be different and therefore incomparable” [13]. The allocation of the full or partial score to the alternatives is based on the consideration of the performance set, based on the criteria and sub-criteria selected for the implementation of the analysis. The incomparability is defined by alternative performance sets equally valid but differently qualified because they are based on different sets of criteria;
- Goal, aspiration or reference level approach: “This approach defines a goal on each criterion, and then identifies the closest options to the ideal goal or reference level” [13]. The options (alternatives) are evaluated through the aggregate collection (vector sum) of the performance in relation to the different criteria that allows to define the distances (vector) of alternatives from the objective assumed.
2.3.3. Input Level
2.3.4. Implementation Procedure
- Preference thresholds, indifference thresholds, veto thresholds [51]: for obtaining a merit ranking of alternatives. Rank is constructed through the expression of pairwise preference degree when comparing the performance of n alternatives. For the expression of preference level, evaluation requires to consider the preference and indifference thresholds. On the basis of this thresholds positive, negative and net unicriterion and global flows are constructed taking into account the weights attributed to each criterion. If an action is negatively performing according to a single criterion, it may also be included a veto threshold that definitively excludes that option from the final ranking;
- Utility function [21]: to express the measure of desirability or preference of each alternative respect the other. Different criteria are considered in the function; for each criteria, the marginal utility is determined representing the partial contribution that each criteria brings to the overall utility assessment [13]. Global utility is expressed by Global Utility Scores (generally expressed in values between 0 and 1) commonly calculated by the additive method or with a weighted sum, based on the weighted importance (weight) for each criterion, or a simple addition;
- Pairwise comparisons on rational scale [26,52]: through the construction of evaluation matrices. The comparison between the elements included in the evaluation matrices, structured according to a hierarchical system of Criteria, Sub-criteria and Alternatives, is performed by simultaneously comparing two elements at a time with respect to the hierarchically superior element on the basis of a rational numerical scale (Saaty Fundamental Scale);
- Pairwise comparisons on rational scale with interdependencies [24]: through the construction of evaluation matrices called Supermatrix. Comparison of the elements included in the Supermatrix, organized into clusters of Criteria, Sub-Criteria and Alternatives, is performed by simultaneously comparing two elements at a time taking into account any interdependencies between them: (1) inner dependency in cluster criteria; (2) inner dependence in the alternative cluster; (3) outer dependency (correlation between two different clusters). Based on the influences (also called nodes) between elements or clusters, the Supermatrix is filled considering the influence of each node on each other is expressed on a rational scale (Saaty Fundamental Scale). In case there is no interdependence between the compared elements, the zero value is inserted into Supermatrix;
- Pairwise comparisons on interval scale [25,53]: through the construction of evaluation matrices also called matrices of judgments. The comparison between the elements of the evaluation (alternatives and criteria) is implemented by the pairwise comparison based on a semantic qualitative scale (traditionally translated into quantitative values from 1 to 7). Values are generally included in the matrix of judgments where the relative attractiveness of the criteria and alternatives is expressed also by the consideration of weight (attributed to each criterion);
- Ideal option and anti-ideal option [13,27,54,55,56]: expressing, for each alternative, the shortest distance to the ideal (virtual) solution and the longest distance from the anti-ideal solution, taking into account the performance of alternatives referred to each criterion and to the weight of each criterion. The distance is expressed by calculating a distributive normalization and an ideal normalization of recorded performances.
2.3.5. Output Typology (Ordering of Alternatives)
- Partial and complete ordering obtained by expressing pairwise preference degrees and scores. This ordering is based on the simultaneous consideration of the positive and negative global performance flows evaluated for each alternative or on the sole consideration of the net flows that make it possible to understand whether the considered alternatives obtain a higher rank, a minor rank or if two or more alternatives are incomparable or equally valid;
- Partial and complete ordering obtained by expressing pairwise outranking degrees. Preferred degrees can lead to a partial rank (if two or more alternatives are incomparable) or total rank (if the incomparability hypothesis is not allowed) of alternatives traditionally through the expression of degrees of concordance and discordance according to the criteria considered;
- Full ordering obtained by considering the scores assigned to alternatives in several ways (pairwise comparisons with or without interdependencies, utility functions, pairwise comparisons on interval scale). These scores are complex and general (they do not accept hypotheses of incomparability between two alternatives) and generally allow the ordering of alternatives from the best to the worst;
- Full order with score closest to the aim assumed. This is based on the calculation of the proximity coefficient for each alternative traditionally expressed in values between 0 and 1 where value 1 expresses the closest proximity to the aim.
2.3.6. Decision Problem Solution
- n categories of alternatives of equal score but different behavior. The hypothesis of incomparability between two alternatives is admitted and the solution to the decision-making problem is based on the consideration of several alternatives at the same time valid to make the choice;
- Alternative with the higher global score: it does not admit the incomparability hypothesis between two alternatives and the decision-making solution is based on choosing the alternative that gets the highest score;
- Alternative with the closest score to the ideal solution: it does not admit the hypothesis of incomparability between two alternatives and the solution to the decision problem is based on choosing the alternative that gets the closest score to the ideal normalization of the recorded performances for alternatives considered.
2.4. Transposition of the Properties of MCDA Tools into a Binary Mathematical System
3. The Procedure for Selecting Tools of Multi-Criteria Decision Analysis
3.1. Overview
- Weighting of variables (optional action);
- Determination of the framework of expected properties: identification (presence/absence) of the qualifications needed by the different variables to address the decision-making problem at hand;
- Calculation of the overall index of suitability: based on a comparison of the properties of the MCDA tools (Table 3) with their expected properties, an overall index can be obtained for the suitability of each tool to the evaluation problem addressed;
- Identification of the tool best suited to resolving the decision-making problem: ranking of the MCDA tools with respect to the overall suitability indicators obtained.
3.2. Weighting of Variables (Optional Action)
- -
- simple if all stakeholders are considered of equal importance;
- -
- weighted if the stakeholders are considered of different importance [64].
3.3. Determination of the Framework of Expected Properties
3.4. Calculation of the Overall Index of Suitability
- SRW(Vn; Qn): suitability results (partial coherence results) weighted;
- SR(Vn; Qn): suitability results (partial coherence results);
- W(Vn): weighting judgement expressed on Vn variable (between 0 and 1).
- IS(Tn): index of overall suitability (overall coherence index);
- SR(Vn; Qn): suitability results (partial coherence results);
- NVn: number of variables considered.
- ISW(Tn): index of overall suitability (overall coherence index) weighted;
- SRW(Vn; Qn): suitability results (partial coherence results) weighted;
- NVn: number of variables considered.
3.5. Ranking and Selection of MCDA Tools
4. Case Study and Results
4.1. Procedure Application for Selecting the MCDA Instrument to Evaluate Design Proposals in the Call for Tenders for a New Office Building of the Chamber of Deputies in Rome
4.2. Definition of Expected Properties
4.3. Calculation of Synthetic Coherence Indicator
4.4. MCDA Tools Ordering and Choice of the Tool to be Used (Results)
5. Conclusions
Author Contributions
Conflicts of Interest
References
- Marakas, G.M. Decision Support Systems in the 21st Century; Prentice Hall: Upper Saddle River, NJ, USA, 2003; Volume 134. [Google Scholar]
- Klapka, J.; Piňos, P. Decision support system for multicriterial R&D and information systems projects selection. Eur. J. Oper. Res. 2002, 140, 434–446. [Google Scholar]
- Belton, V.; Stewart, T. Multiple Criteria Decision Analysis—An Integrated Approach; Kluwer Accademic Press: Boston, MA, USA, 2002. [Google Scholar]
- Figueira, J.; Greco, S.; Ehrgott, M. Multiple Criteria Decision Analysis—State of the Art Survay; Springer: New York, NY, USA, 2005. [Google Scholar]
- Huang Ivy, B.; Keisler, J.; Linkov, I. Multi-criteria decision analysis in environmental sciences: Ten years of application and trends. Sci. Total Environ. 2011, 409, 3578–3594. [Google Scholar] [CrossRef] [PubMed]
- Chung, E.S.; Lee, K.S. Prioritization of water management for sustainability using hydrologic simulation model and multicriteria decision making techniques. J. Environ. Manag. 2009, 90, 1502–1511. [Google Scholar] [CrossRef] [PubMed]
- Liu, D.F.; Stewarr, T. Object-oriented decision support system modelling for multicriteria decision making in natural resource management. Comput. Oper. Res. 2004, 31, 985–999. [Google Scholar] [CrossRef]
- Qin, X.S.; Huang, G.H.; Chakma, A.; Nie, X.H.; Lin, Q.G. A MCDM-based expert system for climate change impact assessment and adaption planning—A case study for the Georgia Basin, Canada. Expert Syst. Appl. 2008, 34, 2164–2179. [Google Scholar] [CrossRef]
- Guarini, M.R.; D’Addabbo, N.; Morano, P.; Tajani, F. Multi-Criteria Analysis in Compound Decision Processes: The AHP and the Architectural Competition for the Chamber of Deputies in Rome (Italy). Buildings 2017, 7, 38. [Google Scholar] [CrossRef]
- Guarini, M.R.; Chiovitti, A.; Battisti, F.; Morano, P. An Integrated Approach for the Assessment of Urban Transformation Proposals in Historic and Consolidated Tissues. ICCSA 2017. Lect. Notes Comput. Sci. 2017, 10406, 562–574. [Google Scholar]
- Guarini, M.R.; Locurcio, M.; Battisti, F. GIS-Based Multi-criteria Decision Analysis for the “Highway in the Sky”. ICCSA 2015. Lect. Notes Comput. Sci. 2015, 9157, 146–161. [Google Scholar]
- Haimes Yacov, Y. On the Universality and contributions of Multiple Criteria Decision Making: A systems-based Approach. J. Multi-Criteria Decis. Anal. 2011, 18, 91–99. [Google Scholar] [CrossRef]
- Ishizaka, A.; Nemery, P. Multi-Criteria Decision Analisys, Methods and Software; Wiley and Sons Ltd.: Chichester, UK, 2013. [Google Scholar]
- Roy, B. Méthodologie Multicritére d’Aide à la Décision; Economica: Paris, France, 1985. [Google Scholar]
- Guitoni, A.; Martel, J.M. Tentative guidelines to help choosing an appropriate MCDA method. Eur. J. Oper. Res. 1998, 109, 501–521. [Google Scholar] [CrossRef]
- Vincke, P. L’aide Multicritère à la Décision; Université de Bruxelles: Bruxelles, Belgium, 1989. [Google Scholar]
- Colson, G.; De Bruyn, C. Models and Methods in Multiple Objectives Decision Making, Models and Methods in Multiple Criteria Decision Making; Pergamon Press: Oxford, UK, 1989. [Google Scholar]
- Fishburn, P.C. A survey of multiattribute/multicriterion evaluation theories. In Multiple Criterion Problem Solving; Zionts, S., Ed.; Springer: Heidelberg, Germany, 1978; pp. 181–224. [Google Scholar]
- Guitouni, A.; Martel, J.M.; Vincke, P.; North, P.B. A Framework to Choose a Discrete Multicriterion Aggregation Procedure. 1998. Available online: https://pdfs.semanticscholar.org/27d5/9c846657268bc840c4df8df98e85de66c562.pdf (accessed on 28 July 2017).
- Roy, B.; Bouyssou, D. Aide Multicritère à la Décision: Methodes et Cas; Economica: Paris, France, 1993. [Google Scholar]
- Keeney, R.L.; Raiffa, H. Decisions with Multiple Objectives: Preferences and Value Trade-Offs; Cambridge University Press: Cambridge, UK, 1993. [Google Scholar]
- Roy, B. Classement et choix en presence de points de vue multiples: La méthode ELECTRE. Revue Francaise d’Informatique et de Recherche Opérationnelle 1968, 8, 57–75. [Google Scholar] [CrossRef]
- Dyer, J.S. MAUT—Multiattribute utility theory. In Multiple Criteria Decision Analysis: State of the Art Surveys; Springer: New York, NY, USA, 2005; pp. 265–292. [Google Scholar]
- Saaty, T.L. Analytic network process. In Encyclopedia of Operations Research and Management Science; Springer: New York, NY, USA, 2001; pp. 28–35. [Google Scholar]
- Bana e Costa, C.; Vansnick, J.C. MACBETH: An interactive path to-wards the construction of cardinal value functions. Oper. Res. 1994, 1, 387–500. [Google Scholar] [CrossRef]
- Saaty, T. A scaling Method for priorities in herarchical structures. Math. Psychol. 1977, 15, 234–281. [Google Scholar] [CrossRef]
- Hwang, C.L.; Yoon, K. Multiple Attribute Decision Making: Methods and Applications; Springer: Heidelberg, Germany; New York, NY, USA, 1981. [Google Scholar]
- Brans, J.P.; Vincke, P. Note—A Preference Ranking Organisation Method: The PROMETHEE Method for Multiple Criteria Decision-Making. Manag. Sci. 1985, 31, 647–656. [Google Scholar] [CrossRef]
- European Commission. Evaluation Methods for the European Union’s External Assistance. Evaluation Tool. 2006. Available online: http://ec.europa.eu/europeaid/sites/devco/files/evaluation-methods-guidance-vol4_en.pdf (accessed on 28 July 2017).
- Seixedo, C.; Tereso, A. A Multicriteria Decision Aid Software Application for selecting MCDA Software using AHP. In Proceedings of the 2nd International Conference on Engineering Optimization, Lisbon, Portugal, 6–9 September 2010; Available online: http://hdl.handle.net/1822/19355 (accessed on 5 October 2017).
- Battisti, F.; Guarini, M.R. Public interest evaluation in negotiated public-private partnership. Int. J. Multi-Criteria Decis. Mak. 2017, 7, 54–89. [Google Scholar] [CrossRef]
- Campbell, J.D.; Jardine, A.K.; McGlynn, J. (Eds.) Asset Management Excellence: Optimizing Equipment Life-Cycle Decisions; CRC Press: Boca Raton, FL, USA, 2016. [Google Scholar]
- Guarini, M.R.; Battisti, F. Evaluation and Management of Land-Development Processes Based on the Public-Private. Adv. Mater. Res. 2014, 869–870, 154–161. [Google Scholar] [CrossRef]
- Bouyssou, D. Some remarks on the notion of compensation in MCDA. Eur. J. Oper. Res. 1986, 26, 150–160. [Google Scholar] [CrossRef]
- Bouyssou, D. Building criteria: A prerequisite for MCDA. Read. Mult. Criteria Decis. Aid 1990, 58–80. [Google Scholar] [CrossRef]
- Roy, B.; Vanderpooten, D. The European school of MCDA: Emergence, basic features and current works. J. Multi-Criteria Decis. Anal. 1996, 5, 22–38. [Google Scholar] [CrossRef]
- Belton, V.; Pictet, J. A framework for group decision using a MCDA model: Sharing, aggregating or comparing individual information? J. Decis. Syst. 1997, 6, 283–303. [Google Scholar] [CrossRef]
- Akaa, O.U.; Abu, A.; Giovinazzi, S. Balancing stakeholder views for decision-making in steel structural fire design. In Proceedings of the International Conference on Performance-based and Life-cycle Structural Engineering, School of Civil Engineering, Brisbane, Australia, 9–11 December 2015; pp. 983–992. [Google Scholar]
- Lahdelma, R.; Salminen, P.; Hokkanen, J. Using Multicriteria Methods in Environmental Planning and Management. Environ. Manag. 2000, 26, 595–605. [Google Scholar] [CrossRef] [PubMed]
- Li, Y.; Thomas, M.A. A Multiple Criteria Decision Analysis (MCDA) Software selection Framework. In Proceedings of the 47th Hawaii International Conference on System Science (HICSS), Waikoloa, HI, USA, 6–9 January 2014; pp. 1084–1094. [Google Scholar]
- Kaspar, R.; Ossadnik, W. Evaluation of AHP software from a management accounting perspective. J. Model. Manag. 2013, 8, 305–319. [Google Scholar]
- Make It Rational AHP Software. Available online: http://makeitrational.com/analytic-hierarchy-process/ahp-software (accessed on 5 October 2017).
- Expert Choice. Available online: http://www.expertchoice.com (accessed on 5 October 2017).
- Super Decisions CDS. Available online: https://superdecisions.com (accessed on 5 October 2017).
- Right Choice. Ventana Systems UK. Available online: http://www.ventanasystems.co.uk/services/software/rightchoice/ (accessed on 5 October 2017).
- M-MACBETH Software. Available online: http://www.m-macbeth.com (accessed on 5 October 2017).
- Smart Picker Pro: The Desktop Application. Available online: http://www.smart-picker.com/products (accessed on 5 October 2017).
- Electre III-IV Software. Available online: http://www.lamsade.dauphine.fr/spip.php?rubrique64&lang=fr (accessed on 5 October 2017).
- Triptych: TOPSIS. Available online: http://www.stat-design.com/Software/TOPSIS.html (accessed on 5 October 2017).
- Salet, W.G.; Thornley, A.; Kreukels, A. (Eds.) Metropolitan Governance and Spatial Planning: Comparative Case Studies of European City-Regions; Taylor & Francis: Oxford, UK, 2003. [Google Scholar]
- Bouyssou, D.; Perny, P. Ranking methods for valued preference relations: A characterization of a method based on leaving and entering flows. Eur. J. Oper. Res. 1992, 61, 186–194. [Google Scholar] [CrossRef]
- Saaty, T. The Analytic Hierarchy Process; Mcgraw Hill: New York, NY, USA, 1980. [Google Scholar]
- Bana e Costa, C.; Vansnick, J. On the mathematical foundations of MACBETH. In Multiple Criteria Decision Analysis: State of the Art Surveys; Springer: New York, NY, USA, 2005; pp. 409–442. [Google Scholar]
- Lai, Y.J.; Hwang, C.L. Fuzzy multiple objective decision making. In Fuzzy Multiple Objective Decision Making; Springer: Berlin/Heidelberg, Germany, 1994; Volume 404, pp. 139–262. [Google Scholar]
- Hwang, C.L.; Paidy, S.R.; Yoon, K.; Masud, A.S.M. Mathematical programming with multiple objectives: A tutorial. Comput. Oper. Res. 1980, 7, 5–31. [Google Scholar] [CrossRef]
- Behzadian, M.; Otaghsara, S.K.; Yazdani, M.; Ignatius, J. A state-of the-art survey of TOPSIS applications. Expert Syst. Appl. 2012, 39, 13051–13069. [Google Scholar] [CrossRef]
- Baudry, G.; Macharis, C.; Vallée, T. Range-based Multi-Actor Multi-Criteria Analysis: A combined method of Multi-Actor Multi-Criteria Analysis and Monte Carlo simulation to support participatory decision making under uncertainty. Eur. J. Oper. Res. 2018, 264, 257–269. [Google Scholar] [CrossRef]
- Ascough, J.C., II; Maier, H.R.; Ravalico, J.K.; Strudley, M.W. Future research challenges for incorporation of uncertainty in environmental and ecological decision-making. Ecol. Model, The Importance of Uncertainty and Sensitivity Analysis in Process-based Models of Carbon and Nitrogen Cycling in Terrestrial Ecosystems with Particular Emphasis on Forest Ecosystems. In A Workshop Organized by the International Society for Ecological Modelling (ISEM), Proceedings of the Third Biennal Meeting of the International Environmental Modelling and Software Society (IEMSS), Burlington, VT, USA, 9–13 August 2006; Ecological Modelling Elsevier: Amsterdam, The Netherlands, 2008; Volume 219, pp. 383–399. [Google Scholar] [CrossRef]
- Salo, A.; Hämäläinen, R.P. Multicriteria Decision Analysis in Group Decision Processes. In Handbook of Group Decision and Negotiation, Advances in Group Decision and Negotiation; Kilgour, D.M., Eden, C., Eds.; Springer Science & Business Media: Dordrecht, The Netherlands, 2010; pp. 269–283. [Google Scholar]
- Wang, J.-J.; Jing, Y.-Y.; Zhang, C.-F.; Zhao, J.-H. Review on multi-criteria decision analysis aid in sustainable energy decision-making. Renew. Sustain. Energy Rev. 2009, 13, 2263–2278. [Google Scholar] [CrossRef]
- Saaty, T.L.; Vargas, L.G. Models, Methods, Concepts & Applications of the Analytic Hierarchy Process; Springer Science & Business Media: Dordrecht, The Netherlands, 2012; Volume 175. [Google Scholar]
- Ribeiro, F.; Ferreira, P.; Araújo, M. Evaluating future scenarios for the power generation sector using a Multi-Criteria Decision Analysis (MCDA) tool: The Portuguese case. Energy 2013, 52, 126–136. [Google Scholar] [CrossRef] [Green Version]
- Dulmin, R.; Mininno, V. Supplier selection using a multi-criteria decision aid method. J. Purch. Supply Manag. 2003, 9, 177–187. [Google Scholar] [CrossRef]
- Guarini, M.R.; Battisti, F. Benchmarking Multi-criteria Evaluation: A Proposed Method for the Definition of Benchmarks in Negotiation Public-Private Partnerships. ICCSA 2014. Lect. Notes Comput. Sci. 2014, 8581, 208–223. [Google Scholar]
- Saaty, T.L.; De Paola, P. Rethinking design and urban planning for the cities of the future. Buildings 2017, 7, 76. [Google Scholar] [CrossRef]
- Morano, P.; Tajani, F. The break-even analysis applied to urban renewal investments: A model to evaluate the share of social housing financially sustainable for private investors. Habitat Int. 2017, 59, 10–20. [Google Scholar] [CrossRef]
- Guarini, M.R.; Buccarini, C.; Battisti, F. Technical and Economic Evaluation of a Building Recovery by Public-Private Partnership in Rome (Italy). Green Energy and Technology. In Appraisal: From Theory to Practice; Stanghellini, S., Morano, P., Bottero, M., Oppio, A., Eds.; Springer: Berlin, Germany, 2017; pp. 101–115. [Google Scholar]
- Nesticò, A.; Sica, F. The sustainability of urban renewal projects: A model for economic multi-criteria analysis. J. Prop. Invest. Financ. 2017, 35, 397–409. [Google Scholar] [CrossRef]
Phases of the Building Process | Valuable Question | Decision-Making Problems | Decision Making Problems | |
---|---|---|---|---|
Normative References (Italy) | - Presidential Decree 380/2001 ss.mm.ii, - Legislative Decree 50/2016 ss.mm.ii | Legislative Decree 50/2016 ss.mm.ii | - Law Decree 351/2001 ss.mm.ii; - Law Decree 112/2008 ss.sm.ii; - Legislative Decree 42/2004 ss.mm.ii; - Law Decree 85/2010 ss.mm.ii | Presidential Decree 380/2001 ss.mm.ii |
Programming | Preliminary needs studies | Priority of needs identification | - Settlement development; - Redevelopment, recovery, reuse, urban regeneration; - Development of discarded areas/buildings; - Decision support in project management; - Valuation of public buildings (Legislative Decree 351/2001, Article 3-bis of Legislative Decree 112/2008, Article 58 of the Italian Civil Code) - Valorization of Cultural Heritage (Law Decree. 85/2010, Articles 5-7 ss.mm.ii.) - Valorization of landscape-environmental assets (Law Decree 85/2010, Articles 5-7 ss.mm.ii.) | - Restoration and conservation interventions (Art.3 (c); - Renovation of buildings (Article 3 (d); - New construction works (art.3, letter e1-e7); - Urban planning interventions (art.3, letter f) |
Designers and advisors selection | Identification of subjects to be included in Lyfe Cycle Management | |||
Economic technical feasibility project | Design solution that identifies the best relationship between cost and benefit for the community, in relation to the specific needs to be met and performance to be provided (Legislative Decree 50/2016, Article 23, paragraph 5) | |||
Design | ||||
Definitive project | Best design solution in accordance with the requirements, criteria, constraints, addresses and indications set by the contracting authority and, where applicable, the feasibility project (Legislative Decree 50/2016, Article 23, paragraph 7) | |||
Executive project | Best design solution in terms of form, type, quality, size and price and in relation to the solution proposed in the maintenance plan of the work and its parts in relation to the life cycle (Legislative Decree 50/2016, art. 23, co 8) | |||
Work Execution | Relocation of work | Finding the best deal (based on the most economically advantageous bid criterion) | ||
Management during Exercise | Service delivery | Identify the most advantageous management solution and/or the most suitable operator in accordance with the objectives | ||
Ordinary and extraordinary maintenance (D.P.R.380/2001, Article 3, par. 1, letter a, b) | Definition of the ordinary and extraordinary maintenance solution in relation to the modalities and times for the interventions |
Number of Evaluation Elements | Typology of Indicators | Expected Solution | Technical Support of a Decision Aid Specialist | Stakeholders to Be Included in the Decision Process | Tool |
---|---|---|---|---|---|
Limited number of criteria and sub-criteria and a small number of alternatives | - Quantitative; - Qualitative; - Mixed | Definition of n alternatives valid in relation to objectives | - Yes; - No | - Participatory process not activated; - Participatory process activated with a limited and specialized number of stakeholder; - Participatory process activated with a significant number of stakeholder preferably organized in categories | ELECTRE |
Limited number of criteria and sub-criteria and a large number of alternatives | A better overall alternative definition for the purpose; The ideal alternative definition closest to the lens | MAUT | |||
Large number of criteria and sub-criteria and a small number of alternatives | AHP; ANP | ||||
Large number of criteria and sub-criteria and a large number of alternatives | MACBETH; PROMETHEE; TOPSIS |
Type of Decision-Making Problems | Solution Approach | Implementation Procedure | Input Level | Output Typology | Decision Problem Solution | Tool |
---|---|---|---|---|---|---|
Sorting/Description | Outranking approach | Preference thresholds, indifference thresholds, veto thresholds | Medium | Partial ordering obtained by expressing pairwise preferences degrees | n categories of alternatives of equal score but different behaviour | ELECTRE |
Ranking/Choice | Full aggregation approach | Utility function | High | Full ordering obtained by considering the scores | Alternative with the higher global score | MAUT |
Pairwise comparison on rational scale and interdependencies | High | Full ordering obtained by considering the scores | Alternative with the higher global score | ANP | ||
Pairwise comparison on interval scale | High | Full ordering obtained by considering the scores | Alternative with the higher global score | MACBETH | ||
Pairwise comparison on rational scale | Low | Full ordering obtained by considering the scores | Alternative with the higher global score | AHP | ||
Goal, aspiration or reference level approach | Ideal option and anti-ideal option | Low | Full ordering with score closest to the aim assumed | Alternative with the closest score to the ideal solution | TOPSIS | |
Outranking approach | Preference thresholds, indifference thresholds, veto thresholds | Medium | Partial ordering obtained by expressing pairwise preferences degrees | n categories of alternatives of equal score but different behaviour | ELECTRE | |
Total ordering obtained by expressing pairwise preferences degrees | Alternative with the higher global score | |||||
Preference thresholds, indifference thresholds | Medium | Partial ordering obtained by expressing pairwise preferences degrees | n categories of alternatives of equal score but different behaviour | PROMETHEE | ||
Partial ordering obtained by expressing pairwise preferences degrees | Alternative with the higher global score |
Score to Be Assigned | Parameters for the Input Level Definition and Calculation | |||
---|---|---|---|---|
Data and Parameter Quantity (i) | Definition Time (ii) | Skills and Level of Knowledge of the Decision Problem (iii) | Use of Other Integrated Tecniques (iv) | |
1 | High | Long | High | Necessary |
0.5 | Medium | Medium | Medium | Advised |
0 | Low | Short | Low | Unnecessary |
Type of Variables | Variables | Qualification of Variables | Properties of MCDA Tool in Binary System | ||||||
---|---|---|---|---|---|---|---|---|---|
ELECTRE | MAUT | ANP | MACBETH | AHP | TOPSIS | PROMETHEE | |||
Exogenous | Number of evaluation elements | Limited number of criteria and sub-criteria and a small number of alternatives | 1 | 0 | 0 | 0 | 0 | 0 | 0 |
Limited number of criteria and sub-criteria and a large number of alternatives | 0 | 1 | 0 | 0 | 0 | 0 | 0 | ||
Large number of criteria and sub-criteria and a small number of alternatives | 0 | 0 | 1 | 0 | 1 | 0 | 0 | ||
Large number of criteria and sub-criteria and a large number of alternatives | 0 | 0 | 0 | 1 | 0 | 1 | 1 | ||
Typology of indicators | Quantitative | 1 | 1 | 1 | 1 | 1 | 1 | 1 | |
Qualitative | 1 | 0 | 1 | 1 | 1 | 1 | 1 | ||
Mixed | 1 | 0 | 1 | 1 | 1 | 1 | 1 | ||
Stakeholders to be included in the decision process | Participatory process not activated | 1 | 1 | 1 | 1 | 1 | 1 | 1 | |
Participatory process activated with a limited and specialized number of stakeholder | 1 | 1 | 1 | 1 | 1 | 1 | 1 | ||
Participatory process activated with a significant number of stakeholder preferably organized in categories | 1 | 1 | 1 | 1 | 1 | 1 | 1 | ||
Expected solution | A better overall alternative definition for the purpose | 1 | 0 | 0 | 0 | 0 | 0 | 0 | |
The ideal alternative definition closest to the lens | 0 | 0 | 0 | 0 | 0 | 1 | 0 | ||
A better overall alternative definition for the purpose | 0 | 1 | 1 | 1 | 1 | 0 | 1 | ||
The ideal alternative definition closest to the lens | 0 | 0 | 0 | 0 | 0 | 1 | 0 | ||
Technical support of a Decision Aid Specialist | Yes (advisable) | 1 | 1 | 1 | 1 | 0 | 0 | 0 | |
No (not necessary) | 0 | 0 | 0 | 0 | 1 | 1 | 1 | ||
Endogenous | Type of decision-making problems | Sorting | 1 | 0 | 0 | 0 | 0 | 0 | 0 |
Description | 1 | 0 | 0 | 0 | 0 | 0 | 0 | ||
Ranking/Choice | 1 | 1 | 1 | 1 | 1 | 1 | 1 | ||
Solution approach | Outranking approach | 1 | 0 | 0 | 0 | 0 | 0 | 1 | |
Full aggregation approach | 0 | 1 | 1 | 1 | 1 | 0 | 0 | ||
Goal, aspiration or reference level approach | 0 | 0 | 0 | 0 | 0 | 1 | 0 | ||
Implementation procedure | Preference thresholds, indifference thresholds, veto thresholds | 1 | 0 | 0 | 0 | 0 | 0 | 0 | |
Preference thresholds, indifference thresholds | 0 | 0 | 0 | 0 | 0 | 0 | 1 | ||
Utility function | 0 | 1 | 0 | 0 | 0 | 0 | 0 | ||
Pairwise comparison on rational scale and interdependencies | 0 | 0 | 1 | 0 | 0 | 0 | 0 | ||
Pairwise comparison on interval scale | 0 | 0 | 0 | 1 | 0 | 0 | 0 | ||
Pairwise comparison on rational scale | 0 | 0 | 0 | 0 | 1 | 0 | 0 | ||
Ideal option and anti-ideal option | 0 | 0 | 0 | 0 | 0 | 1 | 0 | ||
Input level | High | 0 | 1 | 1 | 1 | 1 | 0 | 0 | |
Medium | 1 | 0 | 0 | 0 | 0 | 0 | 1 | ||
Low | 0 | 0 | 0 | 0 | 0 | 1 | 0 | ||
Output typology | Partial ordering obtained by expressing pairwise preferences degrees | 1 | 0 | 0 | 0 | 0 | 0 | 1 | |
Total ordering obtained by expressing pairwise preferences degrees | 1 | 0 | 0 | 0 | 0 | 0 | 1 | ||
Full ordering obtained by considering the scores | 0 | 1 | 1 | 1 | 1 | 0 | 0 | ||
Full ordering with score closest to the aim assumed | 0 | 0 | 0 | 0 | 0 | 1 | 0 | ||
Decision problem solution | n categories of alternatives of equal score but different behaviour | 1 | 0 | 0 | 0 | 0 | 0 | 1 | |
Alternative with the higher global score | 0 | 1 | 1 | 1 | 1 | 0 | 0 | ||
Alternative with the closest score to the ideal solution | 0 | 0 | 0 | 0 | 0 | 1 | 0 |
Type of Variables | Weight | Variables | Qualification of Variables | Expected Properties in Relation to Decision-Making Problem |
---|---|---|---|---|
Exogenous | 0 ≤ W ≤ 1 | Number of evaluation elements | Limited number of criteria and sub-criteria and a small number of alternatives | Request = 1; Not request = 0 |
Limited number of criteria and sub-criteria and a large number of alternatives | Request = 1; Not request = 0 | |||
Large number of criteria and sub-criteria and a small number of alternatives | Request = 1; Not request = 0 | |||
Large number of criteria and sub-criteria and a large number of alternatives | Request = 1; Not request = 0 | |||
0 ≤ W ≤ 1 | Typology of indicators | Quantitative | Request = 1; Not request = 0 | |
Qualitative | Request = 1; Not request = 0 | |||
Mixed | Request = 1; Not request = 0 | |||
0 ≤ W ≤ 1 | Stakeholders to be included in the decision process | Participatory process not activated | Request = 1; Not request = 0 | |
Participatory process activated with a limited and specialized number of stakeholder | Request = 1; Not request = 0 | |||
Participatory process activated with a significant number of stakeholder preferably organized in categories | Request = 1; Not request = 0 | |||
0 ≤ W ≤ 1 | Expected solution | Definition of n alternatives valid in relation to objectives | Request = 1; Not request = 0 | |
A better overall alternative definition for the purpose | Request = 1; Not request = 0 | |||
The ideal alternative definition closest to the lens | Request = 1; Not request = 0 | |||
0 ≤ W ≤ 1 | Technical support of a Decision Aid Specialist | Yes (advisable) | Request = 1; Not request = 0 | |
No (not necessary) | Request = 1; Not request = 0 | |||
Endogenous | 0 ≤ W ≤ 1 | Type of decision-making problems | Sorting | Request = 1; Not request = 0 |
Description | Request = 1; Not request = 0 | |||
Ranking/Choice | Request = 1; Not request = 0 | |||
0 ≤ W ≤ 1 | Solution approach | Outranking approach | Request = 1; Not request = 0 | |
Full aggregation approach | Request = 1; Not request = 0 | |||
Goal, aspiration or reference level approach | Request = 1; Not request = 0 | |||
0 ≤ W ≤ 1 | Implementation procedure | Preference thresholds, indifference thresholds, veto thresholds | Request = 1; Not request = 0 | |
Preference thresholds, indifference thresholds | Request = 1; Not request = 0 | |||
Utility function | Request = 1; Not request = 0 | |||
Pairwise comparison on rational scale and interdependencies | Request = 1; Not request = 0 | |||
Pairwise comparison on interval scale | Request = 1; Not request = 0 | |||
Pairwise comparison on rational scale | Request = 1; Not request = 0 | |||
Ideal option and anti-ideal option | Request = 1; Not request = 0 | |||
0 ≤ W ≤ 1 | Input level | High | Request = 1; Not request = 0 | |
Medium | Request = 1; Not request = 0 | |||
Low | Request = 1; Not request = 0 | |||
0 ≤ W ≤ 1 | Output typology | Partial ordering obtained by expressing pairwise preferences degrees | Request = 1; Not request = 0 | |
Total ordering obtained by expressing pairwise preferences degrees | Request = 1; Not request = 0 | |||
Full ordering obtained by considering the scores | Request = 1; Not request = 0 | |||
Full ordering with score closest to the aim assumed | Request = 1; Not request = 0 | |||
0 ≤ W ≤ 1 | Decision problem solution | n categories of alternatives of equal score but different behaviour | Request = 1; Not request = 0 | |
Alternative with the higher global score | Request = 1; Not request = 0 | |||
Alternative with the closest score to the ideal solution | Request = 1; Not request = 0 |
Goal | General Objectives | Criteria | Sub-Criteria | Indicators | |
---|---|---|---|---|---|
The urban void solution by the inclusion of new functions | Architectural and Urban quality | Urban fabric filling in relashionship with the historical development process | Alignement of the new building to the urban fabrics before demolition (Rilievo IGM 1873) | Qualitative | - Total; - Partial; - Absent |
Presence of inner courts (covered or uncovered) following the tradition of the historical urban fabric | Qualitative | - Presemt; - Absent | |||
Organic relashionship between buildings and urban spaces | Connection between design spaces, urban spaces and parliamentary functions close to the design area | Qualitative | - Very high; - High; - Meidum; - Low; - Very low | ||
Mixed use providing by concentration of commercial functions on Matrix route in order to restore its functional and morphological continuity | Qualitative | - Total; - Partial; - Absent | |||
Easy access to non parliamentary functions on matrix route (Via di Campo Marzio) | Qualitative | - Total; - Partial; - Absent | |||
Technical and functional quality | Flexibility and integrability of inner and outer spaces from functional and distributive point of view | Minimizing of unmovable structures to reduce the impact on the dinamic and alternative use of spaces | Qualitative | - Very high; - High; - Meidum; - Low; - Very low | |
Minimizing of tecnical and structural elements to reduce the impact on the dynamic and alternative use of spaces | Qualitative | - Total; - Partial; - Absent | |||
Economic and finalncial aspects | Spending Control | Cost reduction | Quantitative | % on base amount established for call for tenders | |
Cost sustainability connected with energy saving | Quantitative | €/year | |||
Maintenance costs por year | Quantitative | €/year | |||
Economic Convinience | Environmental costs | Quantitative | € | ||
Costs Benefits ratio | Quantitative | Net Present Value (€) |
Type of Variables | Variables | Qualification of Variables | Expected Properties to Decision Making Problem | Related to: |
---|---|---|---|---|
Exogenous | Number of evaluation elements | Limited number of criteria and sub-criteria and a small number of alternatives | 0 | - |
Limited number of criteria and sub-criteria and a large number of alternatives | 0 | - | ||
Large number of criteria and sub-criteria and a small number of alternatives | 0 | - | ||
Large number of criteria and sub-criteria and a large number of alternatives | 1 | Criteria, Sub-Criteria and Indicators of Evaluation; Considering a significant participation in the call | ||
Typology of indicators | Quantitative | 0 | - | |
Qualitative | 0 | - | ||
Mixed | 1 | Criteria, Sub-Criteria and Indicators of Evaluation | ||
Stakeholders to be included in the decision process | P.P. not activated | 0 | ||
P.P. activated with a limited and specialized number of stakeholder | 0 | |||
P.P. activated with a significant number of stakeholder preferably organized in categories | 1 | Need to activate a participatory process with a significant number of categories of stakeholders | ||
Expected solution | Definition of n alternatives valid in relation to objectives | 0 | - | |
A better overall alternative definition for the purpose | 1 | Need to select the best design proposal | ||
The ideal alternative definition closest to the lens | 0 | - | ||
Technical support of a Decision Aid Specialist | Yes (advisable) | 1 | Need to speed up decision making | |
No (not necessary) | 0 | - | ||
Endogenous | Type of decision making problems | Sorting | 0 | - |
Description | 0 | - | ||
Ranking/Choice | 1 | Need to form a ranking among the design proposals | ||
Solution approach | Outranking approach | 0 | - | |
Full aggregation approach | 1 | Necessity of project proposals in relation to all achievements | ||
Goal, aspiration or reference level approach | 1 | |||
Implementation procedure | Preference thresholds, indifference thresholds, veto thresholds | 0 | - | |
Preference thresholds, indifference thresholds | 1 | Need to check the performance of project proposals in relation to thresholds | ||
Utility function | 0 | - | ||
Pairwise comparison on rational scale and interdependencies | 0 | - | ||
Pairwise comparison on interval scale | 0 | - | ||
Pairwise comparison on rational scale | 0 | - | ||
Ideal option and anti-ideal option | 1 | Need to check the performance of project proposals in relation to thresholds | ||
Input level | High | 1 | Calculation Table 4: amount of data and parameters: high; Times for the definition: medium; Skills and degree of knowledge of the decision-making problem: high; Use of integrated techniques: not necessary | |
Medium | 0 | - | ||
Low | 0 | - | ||
Output typology | Partial ordering obtained by expressing pairwise preferences degrees | 0 | - | |
Total ordering obtained by expressing pairwise preferences degrees | 0 | - | ||
Full ordering obtained by considering the scores | 1 | Need to measure the performance of project proposals | ||
Full ordering with score closest to the aim assumed | 1 | |||
Decision problem solution | n categories of alternatives of equal score but different behaviour | 0 | - | |
Alternative with the higher global score | 1 | Need to identify the project proposal with the best performance in relation to the goals | ||
Alternative with the closest score to the ideal solution | 1 |
Type of Variables | Variables | Qualification of Variables | Consistency in Relation to the MCDA Tools in Relation to the Expected Qualification | ||||||
---|---|---|---|---|---|---|---|---|---|
ELECTRE | MAUT | ANP | MACBETH | AHP | TOPSIS | PROMETHEE | |||
Exogenous | Number of evaluation elements | Limited number of criteria and sub-criteria and a small number of alternatives | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
Limited number of criteria and sub-criteria and a large number of alternatives | 0 | 0 | 0 | 0 | 0 | 0 | 0 | ||
Large number of criteria and sub-criteria and a small number of alternatives | 0 | 0 | 0 | 0 | 0 | 0 | 0 | ||
Large number of criteria and sub-criteria and a large number of alternatives | 0 | 0 | 0 | 1 | 0 | 1 | 1 | ||
Typology of indicators | Quantitative | 0 | 0 | 0 | 0 | 0 | 0 | 0 | |
Qualitative | 0 | 0 | 0 | 0 | 0 | 0 | 0 | ||
Mixed | 1 | 0 | 1 | 1 | 1 | 1 | 1 | ||
Stakeholders to be included in the decision process | P.P. not activated | 0 | 0 | 0 | 0 | 0 | 0 | 0 | |
P.P. activated with a limited and specialized number of stakeholder | 0 | 0 | 0 | 0 | 0 | 0 | 0 | ||
P.P. activated with a significant number of stakeholder preferably organized in categories | 1 | 1 | 1 | 1 | 1 | 1 | 1 | ||
Expected solution | A better overall alternative definition for the purpose; The ideal alternative definition closest to the lens | 0 | 0 | 0 | 0 | 0 | 0 | 0 | |
A better overall alternative definition for the purpose | 0 | 1 | 1 | 1 | 1 | 0 | 1 | ||
The ideal alternative definition closest to the lens | 0 | 0 | 0 | 0 | 0 | 0 | 0 | ||
Technical support of a Decision Aid Specialist | Yes (advisable) | 1 | 1 | 1 | 1 | 0 | 0 | 0 | |
No (not necessary) | 0 | 0 | 0 | 0 | 0 | 0 | 0 | ||
Endogenous | Type of decision making problems | Sorting | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
Description | 0 | 0 | 0 | 0 | 0 | 0 | 0 | ||
Ranking/Choice | 1 | 1 | 1 | 1 | 1 | 1 | 1 | ||
Solution approach | Outranking approach | 0 | 0 | 0 | 0 | 0 | 0 | 0 | |
Full aggregation approach | 0 | 1 | 1 | 1 | 1 | 0 | 0 | ||
Goal, aspiration or reference level approach | 0 | 0 | 0 | 0 | 0 | 1 | 0 | ||
Implementation procedure | Preference thresholds, indifference thresholds, veto thresholds | 0 | 0 | 0 | 0 | 0 | 0 | 0 | |
Preference thresholds, indifference thresholds | 0 | 0 | 0 | 0 | 0 | 0 | 1 | ||
Utility function | 0 | 0 | 0 | 0 | 0 | 0 | 0 | ||
Pairwise comparison on rational scale and interdependencies | 0 | 0 | 0 | 0 | 0 | 0 | 0 | ||
Pairwise comparison on interval scale | 0 | 0 | 0 | 0 | 0 | 0 | 0 | ||
Pairwise comparison on rational scale | 0 | 0 | 0 | 0 | 0 | 0 | 0 | ||
Ideal option and anti-ideal option | 0 | 0 | 0 | 0 | 0 | 1 | 0 | ||
Input level | High | 0 | 1 | 1 | 1 | 1 | 0 | 0 | |
Medium | 0 | 0 | 0 | 0 | 0 | 0 | 0 | ||
Low | 0 | 0 | 0 | 0 | 0 | 0 | 0 | ||
Output typology | Partial ordering obtained by expressing pairwise preferences degrees | 0 | 0 | 0 | 0 | 0 | 0 | 0 | |
Total ordering obtained by expressing pairwise preferences degrees | 0 | 0 | 0 | 0 | 0 | 0 | 0 | ||
Full ordering obtained by considering the scores | 0 | 1 | 1 | 1 | 1 | 0 | 0 | ||
Full ordering with score closest to the aim assumed | 0 | 0 | 0 | 0 | 0 | 1 | 0 | ||
Decision problem solution | n categories of alternatives of equal score but different behaviour | 0 | 0 | 0 | 0 | 0 | 0 | 0 | |
Alternative with the higher global score | 0 | 1 | 1 | 1 | 1 | 0 | 0 | ||
Alternative with the closest score to the ideal solution | 0 | 0 | 0 | 0 | 0 | 1 | 0 | ||
Overall suitability index (IS) | 0.36 | 0.73 | 0.82 | 0.91 | 0.73 | 0.73 | 0.55 |
MCDA Tool | Overall Suitability Index (IS) | Ranking |
---|---|---|
MACBETH | 0.91 | 1 |
ANP | 0.82 | 2 |
MAUT | 0.73 | 3 |
AHP | 0.73 | 3 |
TOPSIS | 0.73 | 3 |
PROMETHEE | 0.55 | 6 |
ELECTRE | 0.36 | 7 |
© 2017 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
Share and Cite
Guarini, M.R.; Battisti, F.; Chiovitti, A. Public Initiatives of Settlement Transformation: A Theoretical-Methodological Approach to Selecting Tools of Multi-Criteria Decision Analysis. Buildings 2018, 8, 1. https://doi.org/10.3390/buildings8010001
Guarini MR, Battisti F, Chiovitti A. Public Initiatives of Settlement Transformation: A Theoretical-Methodological Approach to Selecting Tools of Multi-Criteria Decision Analysis. Buildings. 2018; 8(1):1. https://doi.org/10.3390/buildings8010001
Chicago/Turabian StyleGuarini, Maria Rosaria, Fabrizio Battisti, and Anthea Chiovitti. 2018. "Public Initiatives of Settlement Transformation: A Theoretical-Methodological Approach to Selecting Tools of Multi-Criteria Decision Analysis" Buildings 8, no. 1: 1. https://doi.org/10.3390/buildings8010001