A Multi-Criteria Analysis Model for Investment Projects in Smart Cities
Abstract
:1. Multi-Criteria Economic Evaluation for Smart Urban Planning
2. The Smart City’s Core Components
- (1)
- Identification of multiple goals—financial, social, cultural, environmental—to be achieved through the execution of projects;
- (2)
- (3)
- attributing a performance indicator to each criterion.
3. Optimization Algorithms for Smart City Initiatives
- Linear programming problems, if the objective function and the functions defining the constraints are linear, and
- non-linear programming problems, if at least one of the problem functions is not linear.
- Of continuous optimization, if the x vector assumes values in Rn;
- of integer (or discrete) optimization, when the variables considered assume values in Zn;
- mixed, when the variables assume both integer and continuous value.
- Pure integer linear optimization, when x decision variables are bound to assume values in the Z+ set;
- binary or boolean optimization if, instead, the condition of entirety is more restrictive and it imposes that the variables assume only values 0 and 1, or else , with the meaning of chosen {1} and not chosen {0}.
4. A Multi-Criteria Economic Evaluation Model for Smart Cities
- -
- The available budget (param BUDGET);
- -
- the multi-criteria matrix (param INDICATORS_unit {PROJECTS, EVALUATION CRITERIA}); and
- -
- the vector of the investment costs for the n projects (param COST {PROJECTS}), are reported in the PARAMETERS section.
INDICATORS_unit[i, j] × x[i].
- -
- Build a model in parametric form through the .mod file;
- -
- write the data about the problem in a .dat file separated by the corresponding .mod file;
- -
- characterize the elements of the system as a set of objects (set);
- -
- define the value of unknowns, i.e., the projects to be selected (var x binary);
- -
- structure the objective function as a linear algebraic expression that maximizes investment capability to pursue the many goals associated with sustainable city planning.
5. Case Study
- financial implications;
- employment effects;
- reduction of air pollutants, also thanks to the use of renewable energy sources;
- implementation of new technologies for better utilization of the services for the city;
- urban equalization.
- the Internal Rate of Return (IRR);
- the number of new employees that the project produces (N° OF WORKERS);
- the lowest CO2 emissions in the atmosphere, in terms of thousands of tons per year (the numerical values are positive—i.e., detrimental for selection purposes—in the case of CO2 emissions, while they are negative where the project causes CO2 destruction, such as for urban recovery initiatives that create new green spaces);
- the amount of digital services information offered by the project for the fruition of the service (N° ICT);
- the geographic location of the operation. A numeric value in the Saaty ordinal scale is attributed to the indicator (IMPA) in growing measure as the project’s ability to generate new wealth in those districts with a higher level of degradation, which therefore require useful actions in pursuit of the highest urban standards found in other city areas.
- ampl: reset;
- ampl: model FILE.mod;
- ampl: data FILE.dat;
- ampl: option solver cplex;
- ampl: solve.
6. Conclusions
Author Contributions
Conflicts of Interest
References
- Glaeser, E.L.; Scheinkman, J.A.; Shleifer, A. Economic Growth in a Cross-Section of Cities. J. Monet. Econ. 1995, 36, 117–143. [Google Scholar] [CrossRef]
- Simon, C.J.; Nardinelli, C. Human Capital and the Rise of American Cities, 1900–1990. Reg. Sci. Urban Econ. 2002, 32, 59–96. [Google Scholar] [CrossRef]
- Glaeser, E.L.; Shapiro, J.M. Urban Growth in the 1990s: Is City Living Back? J. Reg. Sci. 2003, 43, 139–165. [Google Scholar] [CrossRef]
- Johnson, B. Cities, systems of innovation and economic development. Innov. Manag. Policy Pract. 2008, 10, 146–155. [Google Scholar] [CrossRef]
- Harrison, C.; Eckman, B.; Hamilton, R.; Hartswick, P.; Kalagnanam, J.; Paraszczak, J.; Williams, P. Foundations for smarter cities. IBM J. Res. Dev. 2010, 54, 1–16. [Google Scholar] [CrossRef]
- Batty, M.; Axhausen, K.; Fosca, G.; Pozdnoukhov, A.; Bazzani, A.; Wachowicz, M.; Ouzounis, G.; Portugali, Y. Smart cities of the future. Eur. Phys. J. Spec. Top. 2012, 214, 481–518. [Google Scholar] [CrossRef]
- Chourabi, H.; Nam, T.; Walker, S.; Gil-Garcia, J.R.; Mellouli, S.; Nahon, K.; Pardo, T.A.; Scholl, H.J. Understanding Smart Cities: An Integrative Framwork. In Proceedings of the 45th Hawaii International Conference on System Sciences, Maui, HI, USA, 4–7 January 2012; pp. 2289–2297. [Google Scholar] [CrossRef]
- Chan, E.H.W.; Yung, E.H.K. Is the development control legal framework conducive to a sustainable dense urban development in Hong Kong? Habitat Int. 2004, 28, 409–426. [Google Scholar] [CrossRef]
- De Mare, G.; Granata, M.F.; Nesticò, A. Weak and Strong Compensation for the Prioritization of Public Investments: Multidimensional Analysis for Pools. Sustainability 2015, 7, 16022–16038. [Google Scholar] [CrossRef] [Green Version]
- Odendaal, N. Information and communication technology and local governance: Understanding the difference between cities in developed and emerging economies. Comput. Environ. Urban Syst. 2003, 27, 585–607. [Google Scholar] [CrossRef]
- Tewdwr-Jones, M.; Allmendinger, P. Territory, Identity and Spatial Planning. Spatial Governance in a Fragmented Nation; Routledge: London, UK; New York, NY, USA, 2006. [Google Scholar]
- Barbier, E.B. The Concept of Sustainable Economic Development. Environ. Conserv. 1987, 14, 101–110. [Google Scholar] [CrossRef]
- Nesticò, A.; Galante, M. An estimate model for the equalisation of real estate tax: A case study. Int. J. Bus. Intell. Data Min. 2015, 10, 19–32. [Google Scholar] [CrossRef]
- Nesticò, A.; Pipolo, O. A protocol for sustainable building interventions: Financial analysis and environmental effects. Int. J. Bus. Intell. Data Min. 2015, 10, 199–212. [Google Scholar] [CrossRef]
- Fusco Girard, L.; Nijkamp, P. Le Valutazioni Integrate per lo Sviluppo Sostenibile Della città e del Territorio; FrancoAngeli: Milano, Italy, 1997. [Google Scholar]
- Bencardino, M.; Nesticò, A. Demographic Changes and Real Estate Values. A Quantitative Model for Analyzing the Urban-Rural Linkages. Sustainability 2017, 9, 536. [Google Scholar] [CrossRef]
- Dirks, S.; Keeling, M. A Vision of Smarter Cities. How Cities Can Lead the Way into a Prosperous and Sustainable Future; IBM: Somers, NY, USA, 2009. [Google Scholar]
- Kanter, R.M.; Litow, S.L. Informed and Interconnected: A Manifesto for Smarter Cities. Available online: https://hbswk.hbs.edu/item/informed-and-interconnected-a-manifesto-for-smarter-cities (accessed on 23 July 2009).
- Nam, T.; Pardo, T.A. Conceptualizing Smart City with Dimensions of Technology, People, and Institutions. In Proceedings of the 12th Annual International Conference on Digital Government Research (DG.O 2011), College Park, MD, USA, 12–15 June 2011. [Google Scholar]
- Caragliu, A.; Del Bo, C.; Nijkamp, P. Smart cities in Europe. In Proceedings of the 3rd Central European Conference in Regional Science (CERS), Košice, Slovak Reublic, 7–9 October 2009; pp. 45–59. [Google Scholar]
- Yovanof, G.S.; Hazapis, G.N. An architectural framework and enabling wireless technologies for digital cities and intelligent urban environments. Wirel. Pers. Commun. 2009, 49, 445–463. [Google Scholar] [CrossRef]
- Available online: https://www.fastcompany.com/3038818/the-smartest-cities-in-the-world-2015-methodology (accessed on 4 April 2018).
- Centre of Regional Science, Vienna University of Technology. Smart Cities. Ranking of European Medium-Sized Cities; Final Report; Vienna University of Technology: Vienna, Austria, 2007. [Google Scholar]
- Lim, C.S.; Mohamed, M.Z. Criteria of project success: An explanatory re-examination. Int. J. Proj. Manag. 1999, 17, 243–248. [Google Scholar] [CrossRef]
- Ika, L.A. Project success as a topic in project management journals. Int. J. Proj. Manag. 2009, 40, 6–19. [Google Scholar] [CrossRef]
- 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]
- Shapiro, J.M. Smart Cities: Quality of Life, Productivity, and the Growth Effects of Human Capital. Rev. Econ. Stat. 2006, 88, 324–335. [Google Scholar] [CrossRef]
- Lazaroiu, G.C.; Roscia, M. Definition methodology for the smart cities model. Energy 2012, 47, 326–332. [Google Scholar] [CrossRef]
- De Mare, G.; Nesticò, A.; Macchiaroli, M. Significant appraisal issues in value estimate of quarries for the public expropriation. Valori e Valutazioni 2017, 18, 17–23. [Google Scholar]
- Nesticò, A.; De Mare, G.; Sica, F. An Optimization Algorithm for the Selection of Investment Projects in Smart Cities. In Proceedings of the 15th International Conference on Environmental Science and Technology (CEST 2017), Rhodes, Greece, 31 August–2 September 2017. [Google Scholar]
- Korte, B.; Vygen, J. Optimisation Combinatoire. Théorie et Algorithmes; Springer: Paris, France, 2010. [Google Scholar]
- Ventura, P. Alcuni contributi alla separazione primale e duale per problemi di programmazione lineare intera. In Bollettino dell’Unione Matematica Italiana; Serie 8, 6-A; La Matematica nella Società e nella Cultura, Fasc. 2; CNR: Roma, Italy, 2003; pp. 335–338. [Google Scholar]
- Vercellis, C. Ottimizzazione. Teoria, Metodi, Applicazioni; McGraw-Hill: Milano, Italy, 2008. [Google Scholar]
- Thuesen, G.J.; Fabrycky, W.J. Economia per Ingegneri; Il Mulino: Bologna, Italy, 1994. [Google Scholar]
- Bruglieri, M.; Cordone, R.; Liberti, L.; Iuliano, C. Manuale essenziale di AMPL; Dipartimento di Elettronica e Informazione; Politecnico di Milano: Milan, Italy, 2010. [Google Scholar]
SMART CITY | ||
---|---|---|
Technological Factors | Institutional Factors | Human Factors |
Digital City | Smart Community | Creative City |
Intelligent City | Smart Growth | Learning City |
Ubiquitous City | Humane City | |
Wired City | Knowledge City | |
Hybrid City | ||
Information City |
Projects Portfolio Selection Problem |
---|
Sets |
set PROJECTS ; set PROJECTS_TYPE 1; set PROJECTS_TYPE 2; ⋮ |
set PROJECTS_TYPE k; set EVALUATION CRITERIA; |
Parameters |
param BUDGET; |
param INDICATORS_unit {PROJECTS, EVALUATION CRITERIA}; |
param COST {PROJECTS}; |
Variables |
var x {i in PROJECTS} binary; |
Objective Function |
maximize (or minimize) objective: sum {i in PROJECTS, j in INDICATORS} INDICATORS_unit[i, j] × x[i]; |
Constraints |
s.t. (subject to) constraints_0: sum {i in PROJECTS} COST [i] × x[i] ≤ BUDGET; s.t. (subject to) constraints_1: sum {j in PROJECTS_TYPE 1} y [f] ≥ 1; ⋮ |
s.t. (subject to) constraints_m: sum {h in PROJECTS_TYPE k} l [h] ≥ 1; |
Smart Sectors | Projects | IRR (%) | N° of Workers | CO2 (Thousands of Tons per Year) | N° of ICT | IMPA | COST (Thousands of €) | |
---|---|---|---|---|---|---|---|---|
SMART ENVIRONMENTAL ENERGY | 1 | URBAN ENERGY CONSUMPTION MONITORING SYSTEM | 6.70 | 2 | −1 | 3 | 7 | 1000 |
2 | ALTERNATIVE ENERGIES FOR SCHOOL BUILDINGS | 8.10 | 3 | −3 | 6 | 5 | 4300 | |
3 | USE OF PHOTOVOLTAIC PANELS | 4.08 | 1 | −5 | 1 | 3 | 3800 | |
4 | NEW TREATMENT PLANT | 5.14 | 12 | 1 | 0 | 1 | 5000 | |
5 | GEOTHERMAL SYSTEM FOR PUBLIC BUILDINGS | 6.05 | 4 | −3 | 2 | 5 | 4850 | |
6 | EFFICIENCY OF CITY’S ELECTRONIC GRID | 10.20 | 1 | −2 | 2 | 3 | 3000 | |
7 | NEW METHANE GAS PLANT | 8.30 | 5 | −2 | 2 | 3 | 3150 | |
8 | ALTERNATIVE ENERGY SYSTEMS FOR RESIDENTIAL CONSTRUCTION | 9.10 | 6 | −3 | 1 | 3 | 7125 | |
9 | RECLAMATION OF CONTAMINATED SOILS | 6.20 | 3 | −1 | 0 | 9 | 4560 | |
10 | THERMOMETRIC SURVEYING FOR HISTORICAL BUILDINGS | 4.50 | 5 | 0 | 2 | 3 | 4120 | |
SMART LIVING LIFE & HEALTH | 11 | URBAN GARDENS | 7.55 | 10 | −3 | 2 | 5 | 2230 |
12 | AIR QUALITY MONITORING SYSTEMS | 5.10 | 2 | 0 | 1 | 5 | 2000 | |
13 | SENSOR NETWORKS FOR ENVIRONMENTAL EMERGENCIES | 6.25 | 3 | −1 | 4 | 3 | 5210 | |
14 | ENVIRONMENTALLY SUSTAINABLE URBAN RENEWAL | 9.30 | 1 | −4 | 4 | 7 | 5748 | |
15 | ALTERNATIVE TOURISM ACTIONS | 8.00 | 12 | 0 | 5 | 1 | 1300 | |
16 | DIGITAL ENHANCEMENT OF CULTURAL HERITAGE | 11.20 | 4 | 0 | 5 | 3 | 1838 | |
17 | STRUCTURES FOR EDUCATIONAL SCHOOL CANTEEN | 5.35 | 10 | −1 | 1 | 5 | 5370 | |
18 | INTEGRATED AGRO-ECOLOGICAL SYSTEMS | 7.33 | 15 | −2 | 1 | 7 | 2200 | |
19 | CULTURAL INFORMATION CENTRE | 8.00 | 12 | 3 | 5 | 3 | 2850 | |
20 | POLE FOR THE HEALTH PREVENTION | 5.40 | 16 | 0 | 4 | 3 | 2110 | |
21 | SUPPORT SERVICES FOR DISABLED PEOPLE | 6.00 | 15 | 0 | 1 | 5 | 3700 | |
22 | INTERVENTIONS AGAINST EARLY SCHOOL-LEAVING | 4.50 | 4 | 0 | 2 | 5 | 2300 | |
23 | NEW ARCHAEOLOGICAL PARK | 7.60 | 3 | 0 | 3 | 3 | 3560 | |
SMART MOBILITY ALTERNATIVE SYSTEMS | 24 | ALTERNATIVE MOBILITY INITIATIVES | 9.50 | 6 | −3 | 2 | 3 | 2160 |
25 | BIKE-SHARING SYSTEMS | 6.50 | 3 | −4 | 2 | 3 | 1617 | |
26 | ACTIONS FOR ELECTRICAL MOBILITY | 6.60 | 6 | −5 | 3 | 3 | 5895 | |
27 | IMPROVEMENT OF COMMODITIES DISTRIBUTION | 6.75 | 1 | −1 | 1 | 5 | 9200 | |
28 | MOBILITY MANAGEMENT SERVICES | 10.20 | 4 | −1 | 4 | 1 | 8000 | |
29 | INFO-MOBILITY INTEGRATED PLATFORMS | 5.26 | 2 | −1 | 6 | 3 | 7116 | |
30 | ASSISTED MOBILITY SERVICES | 8.50 | 8 | 3 | 3 | 3 | 2500 | |
31 | ROAD MAINTENANCE | 5.40 | 8 | 0 | 1 | 5 | 1600 | |
SMART PEOPLE INCLUSION | 32 | SUPPORT SERVICES FOR THE ELDERLY | 8.10 | 22 | 0 | 3 | 9 | 8120 |
33 | CONSTRUCTION OF SOCIAL APARTMENT BUILDINGS | 7.20 | 2 | 1 | 2 | 7 | 7800 | |
34 | OPEN-DATA TOOLS FOR INTEGRATED PLANNING | 9.45 | 5 | 0 | 4 | 3 | 1110 | |
35 | CREATION OF SOCIAL ENTERPRISES | 5.20 | 16 | 1 | 1 | 5 | 4860 | |
36 | NEW CULTURAL CENTER | 10.20 | 8 | 0 | 4 | 5 | 6750 | |
37 | FACILITY FOR EMIGRANTS | 6.80 | 18 | 2 | 0 | 7 | 5110 | |
38 | CITY ORATORY | 4.60 | 1 | 0 | 1 | 7 | 3256 | |
39 | YOUTH HOSTEL | 10.70 | 8 | 3 | 2 | 5 | 4560 | |
40 | URBAN CIVIC NETWORKS | 7.40 | 4 | 0 | 4 | 3 | 1230 |
.Dat File | ||||||
set PROJECTS: = 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40; | ||||||
set INDICATORS: = IRR N.W. CO2 ICT IMPA; | ||||||
param INDICATORS_unit: = | param COST: = | |||||
IRR | N.W. | CO2 | ICT | IMPA | ||
1 | 0.6 | 0.09 | −0.33 | 0.5 | 0.78 | 1000 |
2 | 0.72 | 0.14 | −1 | 1 | 0.56 | 4300 |
3 | 0.36 | 0.05 | −1.67 | 0.17 | 0.33 | 3800 |
4 | 0.46 | 0.55 | 0.33 | 0 | 0.11 | 5000 |
5 | 0.54 | 0.18 | −1 | 0.33 | 0.56 | 4850 |
6 | 0.91 | 0.05 | −0.67 | 0.33 | 0.33 | 3000 |
7 | 0.74 | 0.23 | −0.67 | 0.33 | 0.33 | 3150 |
8 | 0.81 | 0.27 | −1 | 0.17 | 0.33 | 7125 |
9 | 0.55 | 0.14 | −0.33 | 0 | 1 | 4560 |
10 | 0.4 | 0.23 | 0 | 0.33 | 0.33 | 4120 |
11 | 0.67 | 0.45 | −1 | 0.33 | 0.56 | 2230 |
12 | 0.46 | 0.09 | 0 | 0.17 | 0.56 | 2000 |
13 | 0.56 | 0.14 | −0.33 | 0.67 | 0.33 | 5210 |
14 | 0.83 | 0.05 | −1.33 | 0.67 | 0.78 | 5748 |
15 | 0.71 | 0.55 | 0 | 0.83 | 0.11 | 1300 |
16 | 1 | 0.18 | 0 | 0.83 | 0.33 | 1838 |
17 | 0.48 | 0.45 | −0.33 | 0.17 | 0.56 | 5370 |
18 | 0.65 | 0.68 | −0.67 | 0.17 | 0.78 | 2200 |
19 | 0.71 | 0.55 | 1 | 0.83 | 0.33 | 2850 |
20 | 0.48 | 0.73 | 0 | 0.67 | 0.33 | 2110 |
21 | 0.54 | 0.68 | 0 | 0.17 | 0.56 | 3700 |
22 | 0.4 | 0.18 | 0 | 0.33 | 0.56 | 2300 |
23 | 0.68 | 0.14 | 0 | 0.5 | 0.33 | 3560 |
24 | 0.85 | 0.27 | −1 | 0.33 | 0.33 | 19,500 |
25 | 0.58 | 0.14 | −1.33 | 0.33 | 0.33 | 11,560 |
26 | 0.59 | 0.27 | −1.67 | 0.5 | 0.33 | 6600 |
27 | 0.6 | 0.05 | −0.33 | 0.17 | 0.56 | 6750 |
28 | 0.91 | 0.18 | −0.33 | 0.67 | 0.11 | 16,200 |
29 | 0.47 | 0.09 | −0.33 | 1 | 0.33 | 5260 |
30 | 0.76 | 0.36 | 1 | 0.5 | 0.33 | 2500 |
31 | 0.48 | 0.36 | 0 | 0.17 | 0.56 | 1600 |
32 | 0.72 | 1 | 0 | 0.5 | 1 | 8125 |
33 | 0.64 | 0.09 | 0.33 | 0.33 | 0.78 | 7800 |
34 | 0.84 | 0.23 | 0 | 0.67 | 0.33 | 1100 |
35 | 0.46 | 0.73 | 0.33 | 0.17 | 0.56 | 4860 |
36 | 0.91 | 0.36 | 0 | 0.67 | 0.56 | 6750 |
37 | 0.61 | 0.82 | 0.67 | 0 | 0.78 | 5110 |
38 | 0.41 | 0.05 | 0 | 0.17 | 0.78 | 3256 |
39 | 0.96 | 0.36 | 1 | 0.33 | 0.56 | 4560 |
40 | 0.66 | 0.18 | 0 | 0.67 | 0.33; | 1230; |
param BUDGET: = 33,500; |
Combination of Projects | Objective Function | Costs (in Thousands of €) | |
---|---|---|---|
1 | 1-11-16-18-19-20-21-22-23-30-31-34-35-40 | 27.98 | 33,088 |
2 | 1-11-15-16-18-19-21-22-23-30-31-34-35-40 | 27.97 | 32,270 |
3 | 1-7-11-15-16-18-20-22-30-31-34-37-39-40 | 27.96 | 32,238 |
4 | 1-15-16-19-20-22-23-30-31-32-34-39 | 27.95 | 32,853 |
5 | 1-6-11-12-15-16-18-20-23-30-31-34-38-39-40 | 27.94 | 33,494 |
6 | 1-11-15-16-18-19-20-21-22-23-30-31-34-40 | 27.93 | 29,528 |
7 | 1-11-15-16-18-19-20-21-22-23-29-30-34-40 | 27.92 | 33,188 |
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Nesticò, A.; De Mare, G. A Multi-Criteria Analysis Model for Investment Projects in Smart Cities. Environments 2018, 5, 50. https://doi.org/10.3390/environments5040050
Nesticò A, De Mare G. A Multi-Criteria Analysis Model for Investment Projects in Smart Cities. Environments. 2018; 5(4):50. https://doi.org/10.3390/environments5040050
Chicago/Turabian StyleNesticò, Antonio, and Gianluigi De Mare. 2018. "A Multi-Criteria Analysis Model for Investment Projects in Smart Cities" Environments 5, no. 4: 50. https://doi.org/10.3390/environments5040050