1 Introduction
2 Sustainable Tourism Composite Indicators: A Review
2.1 The Role of International Institutions
2.2 Sustainable Tourism Composite Indicators in the Literature
Authors | Concept of sustainable tourism indicator | Investigation area | Economic (elementary indicators) | Environmental (elementary indicators) | Social (elementary indicators) | Other dimensions (elementary indicators) | Statistical Methodology | Advantages and disadvantages |
---|---|---|---|---|---|---|---|---|
Asmelash and Kumar (2019) | Four dimensions of Sustainable Tourism Development: (1) Socio-cultural sustainability (2) Environmental sustainability (3) Economic sustainability (4) Institutional Sustainability Each dimension is a set of further sub-dimensions | Tigrai Regional State (Ethiopia) | 11 elementary indicators structured in 3 sub-dimensions: Employment quality (4) Economic viability (3) Local prosperity (4) | 12 elementary indicators ordered into 4 sub-dimensions: Physical integrity (3) Biological diversity (3) Resources efficiency (3) Environmental purity (3) | 12 elementary indicators organised into 5 sub-dimensions: Social equity (3) Visitor fulfillment (4) Local control (4) Community wellbeing (4) Cultural richness (3) | Institutional dimension It is composed of 18 elementary indicators, which in turn are structured in 4 sub-dimensions: Local-oriented control policy (3) Political participation (3) Local policy planning (3) Political support (3) | Three-round Delphi Method to finalize the evaluation of the potential indicators Exploratory Factor Analysis (EFA) and Structual Equation Modelling (SEM) were performed to uncover the underlying structure of the relatively large set of sustainability indicators | Advantages: Broad-based involvement of stakeholders in indicator development The use of EEA’s DPSIR comprehensive framework The inclusion of the institutional sustainability Disadvantages: Sustainable indicators are strictly dependend on the specific local destination, which makes it hard to be set at the regional and national level Elementary indicators based on the participatory approach are too limited to the given tourist sites The use of a convenient sampling method in the pilot study makes it hard to infer the analysis, which would have been much more adequate with probability sampling techniques |
Blancas et al. (2010a) | Net Goal Programming Synthetic Indicator (GPSIN) Three dimensions of Sustainable Tourism Development: (1) Socio-cultural sustainability (2) Environmental sustainability (3) Economic sustainability Each dimension shows a hierarchical structure | 14 coastal countries of Andalusia (Spain) | 34 elementary indicators organised into 8 key aspects: Economic benefits for tourism for the local population and destination (11) Sustaining tourist satisfaction (3) Development control (1) Tourist offers providing a variety of experiences (6) Seasonality (3) Tourism employement (2) Transport related to tourism (6) Competitiveness of the destination (2) | 32 elementary indicators organised into 8 key aspects: Protection of the natural resources (2) Management of scarce natural resources (5) Waste management and treatment (9) Atmospheric pollution (3) Management of the visual impact of infrastructure (4) Use intensity (4) Environmental management (1) Specific aspects of environmental tourism sustainability (4) | 28 elementary indicators organised into 6 key aspects: Social-cultural effects of tourist activity (7) Conservation of cultural heritage (3) Destination safety (2) Control for the effects of tourist development on the population (9) Social-carrying capacity (2) Effects of tourist activity on the host population’s well-being (5) | − | GPSIN is based on the goal programming method (from Operation Research) under which the destination is compared, for each indicator, to a priori aspiration level (given by a panel of experts according to the opinion-based approach) GPSIN is the weighted sum of two components, which synthesise the strenghtness and weakness of each destination | Advantages: The composite indicator building avoids previous normalisation The compensation in GPSI.N depends on two parameters, λ and γ, which are relative weights of strengths and weaknesses, respectively GPSI.N is open-ended measure to the goals of sustainable tourism Two phases of data aggregation: the first one produces a synthetic indicator for each dimension; the last provides a final rank to analyse its stability Disadvantages: Subjectivity of expert panel to define the a priori aspiration level and weights of each indicator The adaptability of indicators to goal programming may have some conflicts between areas with different tourism targets |
Blancas et al. (2010b) | Three dimensions of Sustainable Tourism Development: (1) Social (2) Environmental (3) Economic The dimensions do not show any structure inside (for a total of 32 elementary indicators) | 32 coastal areas in Spain (Spain) | 8 elementary indicators | 16 elementary indicators | 8 elementary indicators | − | The key
factors in the indicators system are relevance, data availability, spatial scope and feasibility of performing comparative Data-centric approach based on two-stage aggregation methodology by PCA and a distance to a reference point (DPC) | Advantages: Specificity on local site (coastal tourism) Objective weights by DPC Disadvantages: A not full comprehensive system of indicators A low communicative and interpretability of results |
Blancas et al., (2016) | Vectorial Dynamic Composite Indicator (VDCI) An innovative composite indicator, which is a Vector with a Static (SC) and Dynamic Component (DC) VDCI is structured in three dimensions: (1)Social(2) Economic (3) Environmental | 29 European countries | 36 elementary indicators organised into 8 key aspects: Economic benefits of tourism for the host community and destination (10) Sustaining tourist satisfaction (2) Development control (1) Tourist offers: providing a variety of experiences (5) Seasonality (3) Tourism employement (7) Tourism-related transport (7) Destination competitiveness (1) | 20 elementary indicators organised in 10 key aspects: Protection of the natural ecosystem (1) Energy management (3) Water management (1) Wastewater management (2) Management of solid urban waste (4) Atmospheric pollution (3) Management of the visual impact of facilities and infrastructure (3) Intensity of tourist use (1) Public administrations’ expenditure on environmental protection (1) Use of resources (1) | 29 elementary indicators organised into 6 key aspects: Socio-cultural effects of tourist activity (4) Safety of destination (5) Conservation of cultural heritage (2) Effects on national population structure (6) Social carrying capacity (2) Effects on level of well-being in the local population (10) | − | VDCI is applied in the Static Component (SC) to evaluate the destination level in relation to other competiting destinations, in order to reach a common aspiration level The Dynamic Component (DC) allows the analysis in the reference period of the progress−regress of each destination respect to the own aspiration level | Advantages: Comparative analysis between destinations, and over-time analysis for each destination Adaptability to other tourism destinations by incorporating new specific indicators Direct analysis of the strengths and weaknesses of each destination respect to the three dimensions Disadvantages: Need to define a set of shared goals for each destination to evaluate the dynamic component ranking, as well as a common reference value for the static component ranking |
Blancas et al. (2018) Lozano-Oyola et al., (2019a) | Differential Dynamic Index (DDI) with a Static (SC) and Dynamic Component (DC) DDI modified the previous VDCI (Blancas et al., 2016) to obtain differentiated vectorial sustainability evaluations for each type of territory using multiple benchmarks DDI is composed of the same three dimensions of VDCI with baseline aspects Lozano-Oyola (2019a) used the analytic information provided by the DDI’s two components for the creation of a System of Sustainable Tags to link the evaluation of the indicator with the planning and management decisions of the destinations | Coastal destinations of Andalusian (Spain) | 24 elementary indicators structured into 8 baseline aspects: Economic benefit of tourism for the host community and destination (6) Sustaining tourist satisfaction (2) Development control (1) Tourism facilities on offer-provision of a variety of experiences (7) Seasonability of tourism activity (3) Tourism employment (2) Tourism-related impact transport (2) Destination competitiveness (1) | 20 elementary indicators structured into 9 baseline aspects: Protection of the natural ecosystem (2) Energy management (2) Water management (1) Wastewater management (2) Management of solid urban waste (5) Atmospheric pollution (3) Management of the visual impact of facilities and infrastructure (3) Intensity of tourist use (1) Environmental management (1) | 21 elementary indicators structured into 6 baseline aspects: Socio-cultural effects of tourism on host community (4) Local public safety (2) Conservation of cultural heritage (3) Effect on local population structure (6) Social carrying capacity of the destination (2) Effects on level of well-being in the local population (4) | − | A comprehensive set of 65 elementary indicators Weighting system based on a panel of 57 experts (Budget Allocation Process) with three weighting levels A cluster analysis to form homogeneous groups of municipalities | Advantages: Different aspiration levels according to each territory’s characteristics Using the Sustainable Tourism Evaluation Diagram to evaluate both the current situation of each destination and its progress or regress over time Disadvantages: It would require other relative dynamic measures that enable the quantitative grading of the destination’s evaluation according to the evolution shown by a reference territory |
Castellani and Sala (2010) | Sustainable Performance Index (SPI) SPI summerises 20 elementary indicators concerning economic, social, cultural and environmental aspects without any over structure | Alpi Lepontine Mountains Community -union of 13 municipalities (Italy) | Economy and labour (6) | Environment (5) | Population (3) Housing (1) | Tourism (2) Services (3) | A comprehensive set of 20 elementary indicators is inspired by European projects (DIAMONT, MARS) The framework includes subjective information by local stakeholders to promote local sustainable development (following the European Charter methodology) The weighting of each elementary indicator is obtained by objective and subjective values | Advantages: Linkage to local policy targets Repeatability and comparability of procedure among mountain protected areas Disadvantages: The subjectivity of carrying capacity’s threshold The strong dependence on the local situation, which makes it hard to be set at the regional and national
level |
Lozano-Oyolaet al. (2019b) | Three dimensions of Sustainable Tourism: Social (1) Economic (2) Environmental Each dimension mostly includes objective indicators (for a total of 49 elementary indicators), without showing any structure inside | 36 Andalusian Urban Destinations (Spain) | 20 elementary indicators | 15 elementary indicators | 14 elementary indicators | − | Weighting system based on expert panel (Budget Allocation Process) with three levels: dimensional, factorial and quantification Non-compensatory aggregation procedure based on multicriteria decision-making ideas and on the construction of a mixed-integer linear programming model | Advantages: It allows obtaining a complete pre-order of alternatives Disadvantages: Computational cost required for determining the ranking |
Pérez et al. (2013) | DEAPC index (Data Envelopment Analyis after distance-Principal Component) Three dimensions of Sustainable Tourism Development: (1)Social dimension related to people and tourist development (2) Economic dimension related to tourism management, and material and financial resources (3)Patrimonial dimension related to natural and cultural environment Each dimension includes both subjective and objective indicators (for a total of 39 elementary indicators), without showing any structure inside | 15 Cuban nature-based tourism destinations (Cuba) | 14 elementary indicators | Some indicators of tourism environmental sustainability are included in the patrimonial dimension | 11 elementary indicators | Patrimonial dimension which is composed of 14 elementary indicators | A two-stage methodology (Data Envelopment Analysis after distance-Principal Component – DEAPC): (1)Distance-Principal Component (DPC), which combines Principal Component Analysis (PCA) with the distance to a reference point (dimensional composite indicators) (2)Benefit-of-the-Doubt approach (BoD) for the global synthetic indicator | Advantages: Mixture of objective (obtained from statistical sources) and subjective (reflecting the perceptions of all agents involved in tourism development) indicators The use of the concept of sustainable tourism development proposed by WTO (2004) The combination of the more objective statistical methods with efficiency methods The possibility to be applied to other destinations by changing some elementary indicators Disadvantages: The presence of the hybrid patrimonial dimension, which includes both cultural aspects and more strictly environmental aspects that could be form a separate dimension Indicators are strictly dependend on the specific local destination, which makes it hard to be set at the regional and national level |
Pulido Fernández and Sánchez Rivero (2009) | Sustainable Tourism Index (STI) The global STI method summerises 14 elementary indicators by the Spanish System of Environmental Indicators of Tourism, refusing the hypothesis that all indicators are equally important | 17 Spanish autonomous regions (Spain) | \ | \ | \ | \ | The STI method uses a rubust weighting system based on factor loadings A comparison of STI method with other two aggregation methods, which gained worldwide acceptance: Tourism competitiveness monitor of the World Travel and Tourism Council (WTTC) Environmental Sustainability Index (ESI) of the World Economic Forum (WEF) The comparison is based on composite correlations among the indicators built with the three methodologies using the Spanish system of 14 environmental tourism indicators (SSETI) | Advantages: Consistency of weighting system The use of EEA’s DPSIR comprehensive framework Disadvantages: Four partial indexes of sustainability corresponding to each component of the DPSIR model The paucity of data makes it hard to extend the theoretical framework to different tourist destinations, compromising their comparability |
Torres-Delgado and Palomeque, (2018) | Index of Tourist Sustainability (ISOST) Three dimensions of Tourism Sustainability: (1)Socio-cultural dimension (2) Economic dimension (3) Environmental dimension From an initial list of 26 elementary indicators – taken from the indicator system at the local level developed by Torres-Delgado and Lόpez Palomeque (2014) – to a final list of 12 indicators | 20 tourist municipalities in Catalonia (Spain) | 3 elementary indicators: Seasonality of tourism offer Presence of second homes Public investment in tourism | 6 elementary indicators: Energy consumption Water consumption Waste generation Land use distribution Environmentally certified tourism establishments Environmental criteria applied to tourism planning | 3 elementary indicators: Tourist population Diversification of tourist attractions and resources Tourism products accessible to disabled | OECD (2008) methodology: z-score method Equal weight system Linear aggregation at both levels (elementary indicators and sub-indexes) | Advantages: The use of EEA’s DPSIR comprehensive framework: within each dimension of tourism sustainability, the elementary indicators are declined with respect to each component of the DPSIR model The high level of territorial detail (tourist municipalities) allows sustainable tourism policies to be most effective Disadvantages: Linear aggregation could imply compensability, i.e., poor performance in some elementary indicators can be compensated by high values of other indicators |
3 Material and Methods
3.1 Developing the Theoretical Framework and Selecting Elementary Indicators
Pillar | Sub-Pillar | Ind. # | Indicator | Description | Source |
---|---|---|---|---|---|
Economic value (D1.1) | ind.01 | GDP generated by tourism | Share of GDP generated by tourism out of total regional GDP | Istat | |
ind.02 | Labour productivity in the tourism sector | Value added by the tourism sector per work unit in the sector – thousands of euro chained together | Istat | ||
ind.03 | Tourism intensity | Share of tourists out of inhabitants | Ispra | ||
ind.04 | Summer seasonality of tourism | Days of presence (Italian and foreign) in the complex of accommodation facilities in the non-summer months per inhabitant | Istat | ||
ind.05 | Employment in the tourism sector | Percentage of employees in the tourism sector | Istat | ||
ind.06 | Female employment in tourism | Percentage of female employees in the tourism sector | Istat | ||
ind.07 | At-risk-of-poverty persons | Percentage of at-risk-of-poverty persons with an equivalent income to or below 60% of the median equivalised income in the regional resident population | Istat-BES | ||
Sustainability of tourism enterprise (D1.2) | ind.08 | Tourism companies | No. of tourism companies (in 1 K); Istat survey on the Capacity and occupancy of tourist accommodation establishments | Istat | |
ind.09 | Accommodation establishments | No. of accommodation establishment (hotels, camping, B&B, …); Istat survey on the Capacity and occupancy of tourist accommodation establishments | Istat | ||
ind.10 | ISO 14001 certification | No. of ISO 14001 certified production sites | Ispra | ||
ind.11 | EMAS registration | No. of EMAS (Eco-Management and Audit Scheme) registered sites | Ispra | ||
ind.12 | Ecolabel license | No. of EU Ecolabel licences between services and products | Ispra | ||
International appeal (D1.3) | International tourism demand (D1.3.1) | ind.13 | Tourist stay of foreigners | No. of foreign overnight stays | Bank of Italy |
ind.14 | Quota of foreign tourism on domestic tourism | Ratio of no. of foreign arrivals to Italian arrivals | Eurostat | ||
ind.15 | Foreign tourism expenditure | Total foreign tourism expenditure (in mln. euro) | Bank of Italy | ||
ind.16 | Foreign tourists revisiting a place | No. of foreign tourists revisiting a place | Bank of Italy | ||
International tourism satisfaction (D1.3.2) | ind.17 | Courtesy of the host population for foreign tourism | Rating on 5-points Likert scale of the courtesy of the host population for foreign tourists | Bank of Italy | |
ind.18 | Cooking for foreign tourism | Rating on 5-points Likert scale of local cooking for foreign tourists | Bank of Italy | ||
ind.19 | Environment for foreign tourism | Rating on 5-points Likert scale of the quality of the environment visited by foreign tourists | Bankof Italy | ||
ind.20 | Value of visited cities for foreign tourism | Overall rating on 5-points Likert scale of the cities visited by foreign tourists | Bank of Italy | ||
Tourism demand (D1.4) | ind.21 | Tourism arrivals | No. of tourist arrivals (Italian and foreign) | Istat | |
ind.22 | Tourism presence in accommodation establishments | No. of
presence of tourists (Italian and foreign) in accommodation facilities | Istat | ||
ind.23 | Tourist stay | Average tourist stay | Istat | ||
ind.24 | Ratio of tourist presence to resident population | Ratio of tourist visits to regional resident population | Istat | ||
ind.25 | Museum visitors | No. of visitors to museums and similar institutions (in 100 K) | Istat | ||
ind.26 | Cultural heritage visitors | No. of visitors to antiques and art institutes (thousands) | Istat | ||
Cultural heritage organisations (D1.5) | ind.27 | UNESCO world heritage | UNESCO world heritage in each Italian region | Unesco | |
ind.28 | UNESCO world heritage nomination | UNESCO world heritage nomination | Unesco | ||
ind.29 | Archaeological heritage | No. of archaeological sites; Istat survey on museums and similar institutions | Istat | ||
ind.30 | Museum heritage | No. of museums and art galleries; Survey on museums and similar institutions | Istat | ||
ind.31 | Monumental sites | No. of monumental sites; Survey on museums and similar institutions | Istat | ||
ind.32 | Degree of promotion of cultural offer of state institutes | Ratio of paying visitors to non-paying visitors of the state institutions of antiques and art with admission fee (%); Survey on museums and similar institutions | Istat | ||
ind.33 | Cultural events | No. of theatrical and musical shows | Istat-SIAE | ||
ind.34 | Expenditure for cultural events | Spending at the box office for theatrical and musical events | Istat-SIAE |
Pillar | Sub-Pillar | Ind. # | Indicator | Description | Source |
---|---|---|---|---|---|
Energy and water consumption (D2.1) | ind.35 | Energy consumption by inhabitants | Per capita energy consumption in KWh (elaborated by Istat on Terna Spa data) | Istat | |
ind.36 | Energy consumptio by tourism sector | Energy consumption by tourism enterprises (hotels, camping, restaurants,…) in mln KWh; Istat on Terna Spa data | Istat | ||
ind.37 | Water consumption by inhabitants | Per capita water consumption (m.3) | Istat | ||
ind.38 | Air pollution | No. of days the particulate threshold value is exceeded 50 ml/PM10 | Istat-Ispra | ||
ind.39 | Greenhouse gas (GHG) emissions by tourism industry | Share of CO2 (tonnes) by tourism industry out of total CO2, related to the land use and excluding emissions by maritime traffic | Istat | ||
Sustainable energy and water management (D2.2) | ind.40 | Energy consumption by renewable sources | Electricity from renewable sources (wind, biomass, solar heat, hydroelectric) as a percentage of gross internal consumption of electricity (GWh); Istat on Terna Spa data | Istat | |
ind.41 | Renewable energy produced as a percentage of the total | Ratio of energy from renewable sources (excluding transport sector) to total final energy consumption; Istat on Terna Spa data | Istat-ASVIS | ||
ind.42 | Population served by water purification | Percentage of population actually served by urban waste water treatment plants with secondary and tertiary treatment over the total population of the region | Istat-ASVIS | ||
ind.43 | Water distribution efficiency | Percentage of the volume of water supplied to users compared to that fed into the water system | Istat-ASVIS | ||
Waste management
(D2.3) | ind.44 | Waste produced by tourism sector | Amount of urban waste attributable to tourism per capita (elaborated by ISPRA on Istat data) | Istat-Ispra | |
ind.45 | Rate of landfill waste to the total waste | Urban waste going to landfill as a percentage of the total urban waste collected | Istat-ASVIS | ||
ind.46 | Urban waste collected separately | Tons of urban waste collected separately out of the total urban waste collected | Istat-ASVIS | ||
ind.47 | Recycled rate | Ratio of the quantities of urban waste prepared for re-use or recycled to the total quantities produced | Istat-ASVIS | ||
ind.48 | Per capita separate waste | Quantity of urban waste collected separately per capita (kg/inhabitant) | Ispra | ||
ind.49 | Rate of organic waste | Organic fraction treated in composting plants out of total urban organic waste (%) | Istat-Ispra | ||
Environmental value (D2.4) | Quality of the environment (D2.4.1) | ind.50 | Blue Flag beach certification | No. of Blue flag beach or certified municipalities | FEE* |
ind.51 | Favourable habitat conservation | Percentage of habitats with favourable conservation status | Istat | ||
ind.52 | Quality of bathing coasts | Percentage of the length of the bathing coasts on the total length of the coasts | Istat-Ispra | ||
Promotion of natural heritage (D2.4.2) | ind.53 | Sites of Community Importance (SCI) | Area of sites of community importance on the regional territory (%) | Istat-BES | |
ind.54 | Special Protection Area (SPA) | Percentage of official protected natural areas on the total territory | Istat-BES | ||
ind.55 | Rete Natura 2000 | Area of the Rete Natura 2000 (sites of community importance) on the regional area (%) | Istat-BES |
Pillar | Sub-Pillar | Ind. # | Indicator | Description | Source |
---|---|---|---|---|---|
Security (D3.1) | ind.56 | Thefts and robberies suffered by tourists | No. of thefts and robberies potentially suffered by tourists | Istat | |
ind.57 | Percentage of crimes suffered by tourists to the total crimes | Ratio of no. of thefts and robberies suffered by tourists to the total crimes reported to law enforcement agencies | Istat | ||
ind.58 | Petty crime index | Petty crime in the provinces of the regional capitals on the resident population | Istat | ||
ind.59 | Road accident rate | Road accident rate per houndred inhabitants | Istat | ||
ind.60 | Severe injury rate from road accident | Rate of serious injury in road traffic accident by region per 100 K inhabitants (hospital discharge data) | Istat | ||
ind.61 | Occupational accident rate in the tourism sector | Accident rate in the tourism sector by number of employees | Istat-Inail | ||
Health (D3.2) | ind.62 | Mortality rate | Standardised mortality rate for major causes of death in 30–69 years per 100 K inhabitants | Istat | |
ind.63 | Hospitals | No. of hospitals and treatment centers per 100 K inhabitants | Istat | ||
ind.64 | Family health care expenditure | Health expenditure per capita (including spending for all privately and publicly funded family health care services and products) | Istat; HFA-Italy (Health for All) | ||
Mobility (D3.3) | ind.65 | Local Public Transport (LPT) capacity | Median value of places-km of LPT (bus, tramway, underground, funiculars) per thousand inhabitants | Istat | |
ind.66 | Rail transport utilisation index | Percentage of workers, schoolchildren and students aged 3 and over who regularly use the train to go to work, kindergarten or school | Istat | ||
ind.77 | Spreading of urban transport | Urban public transport networks in the provincial capital municipalities for 100 square kilometres of municipal territory | Istat | ||
ind.68 | Degree of satisfaction with regional rail transport | Average number of people who declare themselves satisfied with the seven different characteristics of the surveyed service (frequency of journeys, punctuality, possibility of finding a seat, cleaning of cars, convenience of the timetables, cost of ticket, information on the service) on the total number of users of the service | Istat | ||
ind.69 | Cycle path density | Median value of the density of km of cycle paths over 100 km.2 of the province’s surface | Istat-UrBES | ||
Gender balance (D3.4) | ind.70 | Work-life balance for women in the tourism industry | Employment rate of women in the tourism sector (aged 25–49) with pre-school children to women (aged 25–49) without children | Istat | |
ind.71 | Temporary employment rate for women in the tourism sector | Ratio of no. of female workers (dependent, self-employed, temporary) out of the total employees in the tourism sector (average annual values) | Istat | ||
ind.72 | Female unemployment rate | Total women jobseekers in the female workforce (> 15 years old) | Istat | ||
ind.73 | Long-term female unemployment rate | Women looking for long-term work (> 12 months) out of total women seeking work | Istat | ||
ind.74 | NEET female rate | Percentage of young women (aged 20–34) neither in employment nor in education and training | Istat | ||
ind.75 | Political participation of women | Percentage of female regional councillors elected | Istat-Asvis |
3.2 Data Treatment, Multivariate Analysis and Normalisation
3.3 Weighting and Aggregation
4 Results and Discussion
4.1 The Conceptual Structure of the SusTour-Index
4.2 Measuring the Dimensionality of the SusTour-Index
Pillar | Cronbach’s alpha | Eigen value (\(\lambda_{i}\)) | Cumulative variance | |
---|---|---|---|---|
D1 | Economic sub-index | |||
D1.1 | Economic value | 0.9378 | 5.086 | 0.8059 |
D1.2 | Sustainability of tourism enterprise | 0.8229 | 5.4663 | 0.6192 |
D1.3 | International appeal | 0.8541 | 4.0408 | 0.5879 |
2.0387 | 0.8845 | |||
D1.4 | Tourism demand | 0.7456 | 2.9055 | 0.7148 |
D1.5 | Cultural heritage | 0.8812 | 4.3637 | 0.7353 |
D2 | Environmental sub-index | |||
D2.1 | Energy and water consumption | 0.8648 | 3.1617 | 0.9605 |
D2.2 | Sustainable energy and water management | – | – | – |
D2.3 | Waste management | 0.7293 | 2.3033 | 0.6803 |
D2.4 | Environmental value | 0.5864 | 1.8312 | 0.446 |
1.6619 | 0.854 | |||
D3 | Social sub-index | |||
D3.1 | Security | 0.916 | 4.1757 | 0.7635 |
D3.2 | Health | – | – | – |
D3.3 | Mobility | 0.7695 | 2.2493 | 0.7922 |
D3.4 | Gender balance | 0.8627 | 3.3907 | 0.8743 |
4.3 Weighting and Aggregating: The Multi-modelling Approach
First set of 14 models (M1–M14) | Second set of 9 models (M15–M23) | ||||||||
---|---|---|---|---|---|---|---|---|---|
Model | I level (Indicators) | II level (Pillars) | Model | I level (Indicators) | II level (Pillars) | ||||
Weight | Aggregation of indicators | Weight | Aggregation of pillars | Weight | Aggregation of indicators | Weight | Aggregation of pillars | ||
M1 | EW | Linear | EW | Linear | M15 | EW | Linear | PCA | Linear |
M2 | EW | Linear | EW | Geometric | M16 | EW | Geometric | PCA | Linear |
M3 | EW | Linear | EW | MP | M17 | EW | MP | PCA | Linear |
M4 | EW | Linear | EW | Wroclaw | M18 | PCA | Linear | EW | Linear |
M5 | EW | Linear | EW | Borda | M19 | PCA | Linear | EW | Geometric |
M6 | EW | Geometric | EW | Linear | M20 | PCA | Linear | EW | MP |
M7 | EW | Geometric | EW | Geometric | M21 | PCA | Linear | EW | Wroclaw |
M8 | EW | Geometric | EW | MP | M22 | PCA | Linear | EW | Borda |
M9 | EW | Geometric | EW | Wroclaw | M23 | PCA | Linear | PCA | Linear |
M10 | EW | Geometric | EW | Borda | |||||
M11 | EW | MP | EW | Linear | |||||
M12 | EW | MP | EW | Geometric | |||||
M13 | EW | MP | EW | Wroclaw | |||||
M14 | EW | MP | EW | Borda |