Multi-criteria Evaluation Method Research Articles

Fuzzy RANCOM: A novel approach for modeling uncertainty in decision-making processes

Multi-Criteria Decision Analysis (MCDA) methods are essential for addressing real-world challenges in the dynamic field of decision support technology. As technology advances, the expanding variety of multi-criteria evaluation methods highlights the critical importance of method selection for reliable results. These methods can be applied to scenarios involving both precise data and uncertainties. Expert knowledge is relevant in navigating real-world decision problems, particularly in uncertain environments where judgment inaccuracies can create challenges. Determining criteria weights is a pivotal step, as it significantly influences final outcomes and provides a nuanced understanding of each factor's impact on the evaluation.This paper addresses the pressing need for methods that account for uncertainty and effectively reduce the impact of inaccuracies in expert judgment. To this end, we introduce the Fuzzy RANking COMparison (RANCOM) method, a novel fuzzy subjective weighting approach that extends the advantages of the original RANCOM method to manage uncertainty. Using Triangular Fuzzy Numbers (TFNs), the proposed extension maintains simplicity, rapid execution, and flexibility in establishing criteria relationships. Key contributions of this paper include the development of the Fuzzy RANCOM method and a comparative analysis with the Fuzzy Analytical Hierarchy Process (AHP) method. Through multiple simulations, the study examines the operational dynamics of these methods, offering a valuable tool for decision-makers, especially in contexts where expert judgments may be prone to inaccuracies. The development of the Fuzzy RANCOM method provides a robust solution, equipping decision-makers with an effective tool to determine criteria weights while minimizing the impact of potential judgment errors.

Rural Road Assessment Method for Sustainable Territorial Development

In Latin America, initiatives have been advocated for developing rural roads that facilitate optimal conditions free from dust, mud, and noise. The criteria for assessing public investment do not align with the requirements of rural infrastructure. Indeed, in rural areas, the territorial conditions such as openness to rural–urban markets, access to education and health, environmental protection, culture, and identity are more important than transportation times or traffic volume. Hence, a multicriteria evaluation method is proposed to prioritize the rural road improvements and maximize their contribution to sustainable territorial development. The roads with the highest sustainable contribution are optimized using a multi-objective decision-making analysis and prioritized based on a Manhattan distance. In addition, a fuzzy cognitive map analyzes the dynamic behavior of the optimal roads. Based on this proposal, a case study is applied where fifteen roads are selected from a sample of 101 in the Araucanía Region, Chile. For this, 16 evaluation criteria, 27 indicators, and sustainability’s social, environmental, technical, and economic dimensions are considered. The results detect reduced one-dimensional contributions despite identifying 15 optimal roads that collectively enhance sustainability. Two roads stand out for their long-term sustainability contribution, which are influenced by economic criteria of zonal productivity, tourism, and road maintenance. Thus, this method can help public agencies rank the roads that must be the subject of development projects.

Multi-criteria evaluation method for the selection of nature-based solutions for urban challenges

Multi-criteria evaluation method for the selection of nature-based solutions for urban challenges

Reducing Emissions in the Maritime Sector: Offshore Wind Energy as a Key Factor

The maritime environment is the setting for a variety of economic activities, such as offshore wind energy, aquaculture, salt extraction, and oil and gas platforms. While some of these activities have a long-term presence, others require decarbonization as they head towards their demise. In this context, the aim of this study is to develop a methodology to replace the electrical energy from offshore high-emission industrial processes with clean electricity generated by offshore wind energy. The proposal is structured in three phases: initiation, which involves the collection of quantitative, technical, and geospatial information of the study area; indicators, where the main indicators are calculated, and the best alternative is selected using multi-criteria evaluation methods; and finally, short-, medium-, and long-term scenarios are proposed. The methodology is evaluated in Spain, and the best alternative, which has a nominal power of 225 MW, is capable of avoiding up to 1.44 MtCO2 by 2050.

Where to plan shared streets: Development and application of a multicriteria spatial decision support tool

In response to the growing recognition of the vital role played by streets as public spaces in enhancing the vibrancy of urban life, various concepts aiming at creating greener and more inclusive streets have gained popularity in recent years, especially in North America. Shared streets are one example of such concepts that have attracted the attention of citizens and of urban and transportation planning professionals alike. This was the case in the city of Sherbrooke (Quebec, Canada) where, in response to numerous citizens’ requests, a need was identified to develop decision aid tools to help evaluate and rank street segments based on their potential to become shared streets. To achieve this, an action-research project was initiated in which we conducted a socio-technical process based on MACBETH, a multicriteria evaluation method. The project led to the development of a spatial decision support tool, operationally used today by the city professionals. This tool ensures a more informed and transparent decision-making process and supports shared streets planning policy. The methods developed are generalizable and can be adapted to other cities facing similar planning problems.

Enhancing smart city assessment: an advanced MCDM approach for urban performance evaluation

Urban centers in the 21st century face significant challenges impacting future urban living. The numerous indicators and inherent complexity involved in assessing urban performance in smart cities necessitate the application of multi-criteria evaluation methods, which are frequently associated with fuzziness and uncertainties. Thus, this study introduces an innovative decision support approach that integrates complex spherical fuzzy set to enhance decision-making for smart city evaluation. By incorporating a consensus measurement mechanism for judgments, the reliability of results is improved. The methodology assesses smart city performance by calculating a level index using criteria of resilience, sustainability, and urban livability, along with eighteen sub-criteria for comprehensive benchmarking. Results highlight pollution control, energy and environmental resources, community well-being, eco-friendly transport, and social cohesion as critical factors for smart city performance. Singapore demonstrates high-level performance due to its integration of advanced technologies and community-focused strategies. The evaluated results obtained via the developed approach offer valuable insights for urban planners aiming to promote sustainable, resilient, and livable urban development.

FINANCIAL PROVISION OF MARKETING ACTIVITIES OF MACHINE-BUILDING ENTERPRISES FOR STRENGTHENING COMPETITIVENESS IN THE CONTEXT OF A NEW REALITY

The purpose of this article is to develop a methodological approach to evaluating all possible options for the financial provision of the marketing activities of modern machine-building enterprises under conditions of full-scale war. Thus, the new conditions of reality are characteristic specifically of Ukrainian machine-building enterprises, which become the key object of the study. As a result, within this article, the optimal forms of financial provision, both external and internal, were chosen based on evaluation results, which will allow not only to "survive" in the current conditions for Ukrainian machine-building enterprises but also to strengthen their competitiveness in the face of new challenges and threats. The identification of the most optimal forms of financial provision and the conduct of evaluations were made possible through the implementation of expert analysis, using the Delphi method. The central place in the methodology of the article is occupied by the method of hierarchical multicriteria evaluation. Its thorough substantiation has better reflected the main results of the research. The developed methodological approach is distinguished by its convenience and practical value in the conditions of the new reality, that is wartime. Another feature is the consideration of not only internal resources but also external ones. Ultimately, the proper and secure application of the defined forms of internal and external financial provision of marketing activities to change their own competitiveness was also substantiated. This, in turn, allowed forming the correct trajectory for how to evaluate one’s own financial provision options for marketing activities and how to apply them to enhance one’s competitiveness. The practical significance of the obtained results lies in substantiating recommendations for establishing the optimal form of financial provision of marketing activities for machine-building enterprises.

Humans versus models: a comparative assessment of ecosystem services models and stakeholders’ perceptions

Mapping the production of Ecosystem Services (ES) is imperative for sustainable ecosystem management. Likewise, incorporating expert knowledge enhances ES research. Here, we calculate eight multi-temporal ES indicators for mainland Portugal using a spatial modelling approach. These indicators are then integrated into the novel ASEBIO index—Assessment of Ecosystem Services and Biodiversity—which depicts a combined ES potential based on CORINE Land Cover, using a multi-criteria evaluation method with weights defined by stakeholders through an Analytical Hierarchy Process (AHP). Outputs from the modelling show how ES have changed in Portugal in relation to land use changes, including trade-offs between 1990 and 2018. The composed ASEBIO index is compared against the stakeholders’ valuation of ES potential for the year 2018. The results reveal a significant mismatch between the ES potential perceived by stakeholders and the models, with stakeholder estimates being 32.8% higher on average. All the selected ES were overestimated by the stakeholders. Drought regulation and erosion prevention have the highest contrasts, while water purification, food production and recreation are the most closely aligned among both approaches. Providing the first national overview about the status of multiple ES over a 28 year-period, our findings highlight potential disparities between data-driven and stakeholder-based evaluations. Therefore, we suggest the need for integrative strategies that consider scientific models with expert knowledge for more effective ES assessments and land-use planning. This approach could help bridge the gap between data-driven models and human perspectives, resulting in more balanced and inclusive decision-making.

Successes and Failures of the Implementation of the Rural Development Programme 2014–2020 Measure “Agri-Environment and Climate” in Lithuania

The focus on environment and climate-friendly farming is increasingly important in the European Union (EU) Common Agricultural Policy (CAP). Activities of the Measure M10 “Agri-environment and Climate” of the Rural Development Programme (RDP) 2014–2020 were those policy instruments that pursued environmental and climate goals over large areas under agricultural activities, but their effectiveness is still being questioned. After evaluating implementation successes and failures of the activities of the Measure M10 “Agri-environment and Climate” of the Lithuanian RDP 2014–2020, we aim to contribute to policy instruments that are better designed, more effective, and more attractive for farmers to achieve environmental and climate goals. This research was conducted in several stages: (1) a thorough analysis of the Measure M10 and its implementation; (2) analysis of the Measure M10 activities’ contribution to the policy target areas; (3) multi-criteria evaluation of the activities; (4) survey of beneficiaries and discussions in the focus groups. The data available from the Ministry of Agriculture of the Republic of Lithuania, Agricultural Data Center, and National Paying Agency under Ministry of Agriculture of the Republic of Lithuania was used for the analysis. Analysis of the strategic documents and data on the implementation of Measure M10 was supplemented with results from studies focused on the environmental impact of the implementation of Measure M10 in Lithuania. Multi-criteria evaluation methods were used to arrange the activities of the Measure with respect to the selected indicators. The results from the survey of beneficiaries and discussions in the focus groups let us better clarify the motives, experiences, and preferences of farmers’ participation in the activities of Measure M10. The questionnaire was distributed to 2455 beneficiaries through the National Paying Agency and 342 answers were received back, i.e., 13.9%. Five discussions in focus groups, formed from farmers participating and not participating in the activities, representatives of implementing institutions, and employees of consulting and scientific institutions, were organized. The research has revealed areas for improvement in Measure M10, and suggestions for improvement were prepared to better achieve environmental and climate objectives.

Environmental Fragility in Commercial Forest Plantations Aiming at Sustainable Management

Objective: The objective of this study is to investigate the environmental fragility of two landscapes in which there is a predominance of commercial forest plantations, with the aim of analyzing this fragility through multicriterial evaluation, focusing on the planning of forest roads. Theoretical Framework: The theory of environmental fragility, multi-criteria evaluation methods, and principles of landscape management stand out, providing a solid basis for understanding the context of the investigation. These frameworks are crucial for analyzing the impact of forest roads on environmental variables such as water dynamics, sediment production, and soil erodibility. The integration of these theories allows for a comprehensive assessment of environmental fragility, essential for effective forest planning and road maintenance in forested areas Method: The methodology adopted involves a multi-criteria evaluation approach to assess environmental fragility in forest landscapes. Key criteria, including slope, distance from water bodies, soil erodibility, and topographic humidity, were integrated to create fragility maps. Data were collected through geographical and environmental analysis, processed with spatial analysis tools, and supplemented by principal component analysis to identify influential criteria. This approach enabled a detailed assessment of forest roads' environmental impact, supporting informed decisions in road planning and landscape management. Results and Discussion: The results revealed notable variations in environmental fragility. The analysis of forest roads highlighted their varying impact on environmental fragility. These results are framed within the context of environmental fragility and multi-criteria evaluation, emphasizing the role of criteria such as slope, proximity to water bodies, soil erodibility, and topographic humidity in assessing landscape degradation. The study underscores the need for careful forest road planning to mitigate environmental impacts and promotes the use of comprehensive evaluation methods in sustainable landscape management. Research Implications: The practical and theoretical implications of this research are discussed, providing insights into how the results can be applied or influence practices in the field of forest management and environmental conservation. These implications could encompass forest road planning, sustainable landscape management, and the development of environmental policies aimed at mitigating the impact of infrastructure on natural ecosystems.The study's findings emphasize the need for incorporating multi-criteria evaluation methods into forest planning processes to identify and mitigate areas of high environmental fragility. This approach can guide decision-makers in prioritizing areas for road maintenance, rehabilitation, or even rerouting to minimize ecological damage. Furthermore, the research underscores the importance of integrating environmental fragility assessments into broader forest management strategies, enhancing the sustainability of commercial forestry operations while preserving essential ecosystem services. Originality/Value: This study contributes to the literature by introducing an innovative application of multi-criteria evaluation in assessing environmental fragility within forest landscapes, specifically in the context of forest road planning. The research combines various environmental criteria into a comprehensive fragility map, offering a nuanced understanding of landscape vulnerability that is less commonly addressed in existing studies. Notably, this methodology focused on forest roads has not been previously explored in the literature, highlighting the unique contribution of this research to the field.The relevance and value of this research are evidenced by its potential to influence forest management practices, particularly in the sustainable planning and maintenance of forest roads.

Mapping Localization Preferences for Residential Buildings

In this study, we tried to gauge the trends of localization preferences for residential buildings among young adults. The pragmatic dimension of these studies is important in the process of real estate investment, where a location can be expressed using indicators and statistical data and then, using maps, indicate preferred areas for living in a small town. The aim of our research was to examine and visualize the preferences of young people for living locations in relation to access to services. We conducted an online survey using a Likert scale to determine which services and amenities are most important for young residents. Using multi-criteria evaluation (MCE) methods and their formulas, we calculated the attractiveness coefficient of the location of residential buildings, which we propose to call the RBLAF (Residential Building’s Localization Attractiveness Factor). The results of this research are maps: qualitative–quantitative with point symbols for the structure of services and quantitative isochromatics showing the preferences of potential future investors in real estate.

Screening of Characteristic Pollutants and Risk Pollutants in Different Media in the Yangtze River Basin Using Comprehensive Evaluation and Risk Quotient Methods

A variety of pollutants have frequently been detected in the Yangtze River Basin with the rapid economic development, the population increase, and the acceleration of urbanization, which threaten the aquatic ecosystem and human health. A multi-criteria comprehensive evaluation method was developed to identify the characteristic pollutants, and the risk quotient method was used to derive the risk pollutants in water and sediment samples in this article. A total of 155 pollutants from 11 categories were detected in the Yangtze River Basin according to the literature research. Then, the K-means method was used to analyze the cluster of pollutant comprehensive scores. All pollutants were graded based on their scores and recorded as Ⅰ-Ⅵ according to the number of cases in each cluster. A total of 43 pollutants with high scores of Ⅰ and Ⅱ were listed as the characteristic pollutants, which included 11 polycyclic aromatic hydrocarbons, 11 organochlorine pesticides, 10 polychlorinated biphenyls, eight dioxins, two heavy metals, and one phthalate ester. The top five median concentrations of contaminants in water and sediment samples were heavy metals, polycyclic aromatic hydrocarbons, phthalates esters, bisphenols, and pharmaceuticals and personal care products. According to the principle of risk maximization, the risk entropy value （RQ） was calculated based on the highest pollutant concentration. A total of 38 risky pollutants were screened in the water samples （RQ ≥ 0.1）. There were eight high-risk pollutants with RQ ≥ 1, which included benzo[a,h]-anthracene, anthracene, benzo[a]anthracene, pyrene, methoxychlor, aldrin, 2,4'-dichlorodiphenyl, and cadmium. There were 15 high-risk contaminants in the sediment, which included benzo[b]fluoranthene, anthracene, acenaphthene, fluoranthene, cadmium, lead, chromium, arsenic, selenium, dibutyl phthalate, dimethyl phthalate, diisobutyl phthalate, norfloxacin, perfluorobutyric acid, and bisphenol A. The risk pollutants contained emerging pollutants, which included ten pollutants in water samples and nine pollutants in sediments. Antibiotic pollutants accounted for the largest proportion of these emerging pollutants. The information provided in this article may be useful for the relevant departments to monitor the pollutants and propose management programs for the Yangtze River Basin. Additionally, it is of great significance for the ecological environmental protection and management of the Yangtze River Basin.

Construction and optimization of wilderness network connectivity to address landscape fragmentation in Zhejiang Province, China

Wilderness areas provide important ecosystem services for human being, and as crucial habitats for diverse species. Human activities have led to the fragmentation of wilderness landscapes, posing a significant challenge to biodiversity conservation. Identifying wilderness areas and assessing their network connectivity is fundamental for developing strategies to address this fragmentation. This study used Zhejiang Province, China, which is in the process of rapid urbanization as a case study. We identified the spatial distribution of wilderness by combing the index system and its weights of wilderness identification, using Boolean superposition analysis and the multi-criteria evaluation method, and tested the ecological sensitivity. Additionally, the connectivity of the wilderness network was assessed using the wilderness identification results in Zhejiang Province as ecological sources. The results indicate that: (1) 50% of Zhejiang Province still maintains relatively good wilderness integrity. (2) The wilderness network can cover 82% of highly fragmented habitats and currently unallocated potential natural reserves. (3) In areas not designated as nature reserves but experiencing frequent species movement as well as in identified wilderness regions, robust wilderness networks may play a crucial role in biodiversity conservation. The findings provide quantitative evidence for biodiversity-oriented wilderness network protection and landscape fragmentation management. The results also aid in selecting specific areas for rewilding and ecological restoration, thereby enhancing the overall robustness of the wilderness network.

Multicriteria Evaluation Framework for Industrial Heritage Adaptive Reuse: The Role of the ‘Intrinsic Value’

At the end of the 20th century, most industrial cities faced a massive phase of de-industrialisation, resulting in abandoned areas. However, these areas, rich in history and heritage, can represent significant resources for the regeneration of entire territories. Adaptive Reuse (AR) is one of the most appropriate strategies for the sustainable regeneration of brownfield sites: it gives new life to a ‘dead’ land, extending its use value so that it can continue to be enjoyed both by present and future generations. Decision-making processes concerning Industrial Heritage Adaptive Reuse (IHAR) cannot ignore the role that ‘intrinsic value’ plays in orienting development choices in such areas. Adopting participatory decision-making processes enables the inclusion of different values and interests of the stakeholders and, at the same time, increasing their awareness about the decision-making problem, thus reducing conflicts. This contribution intends to propose an evaluation framework to assess the multidimensional impacts of IHAR, considering the different values characterising them, and to support decision-making processes for the identification of the ‘preferable’ transformation scenario. This evaluation framework is applied, through the use of the TOPSIS multi-criteria evaluation method, in the case study of the ex-Italsider area in Bagnoli district (Naples, Italy), an industrial steel plant decommissioned in the early 1990s.

Assessment of Physical, Social, and Economic Vulnerability to Landslides Disaster in the Karangsambung Karangbolong National Geopark, Indonesia.

Abstract The Karangsambung-Karangbolong National Geopark (GNKK) is administratively located in Kebumen Regency, Central Java Province, Indonesia. The GNKK area has an area of 543,599 km2 which includes 12 sub-districts with 117 villages. The morphology of the GNKK area consists of hills, valleys, and plains to the coast. The morphology of hills and mountains is an area that is prone to landslides. Assessment of physical, social, and economic vulnerability needs to be carried out so that disaster risk analysis and mitigation can be carried out in the future. The aims of this study are 1. To determine the spatial distribution of physical, social, and economic vulnerabilities in the Karangsambung Karangbolong National Geopark Area, 2. To analyze the physical, social, and economic vulnerability to landslides in the Karangsambung Karangbolong National Geopark Area. Assessment of physical, social, and economic vulnerability using the Spatial Multi-Criteria Evaluation (SMCE) method. The results of the main study of the GNKK area have high, moderate, and low classes of physical, social, and economic vulnerability to landslides. However, most GNKK areas are classified as moderate. The community’s social conditions in each village significantly affect the areas prone to frequent landslides. The strategy for disaster mitigation by a landslide is increasing human resources for disaster knowledge with disaster mitigation training and using infrastructures such as installing landslide-prone signs and trigger lines.

The efficiency assessment of using hybrid neural networks for the detection of forged audio data in socially oriented systems

The subject of the research is the problem of detecting falsified data, in particular in audio format, in socially oriented systems. The goal of the work is to develop an effective model based on recurrent and convolutional neural networks for determining the fact of forgery of sound data, using MapReduce technology for parallelization. The article addresses the following tasks: determining the features of audio in socially-oriented systems, conducting an analysis of algorithms for processing audio information both in the form of text and in the form of a signal, forming a list of target architectures of neural networks and revealing the features of their implementation, conducting an experimental test of effectiveness selected approaches. The following methods used are – analytical and inductive method for determining the target set of neural network architectures; expert assessment for the formation of the most influential efficiency factors; experimental, multi-criteria evaluation and statistical methods of data augmentation to determine the most effective model. The following results were obtained: an audio data reprocessing algorithm was developed for the possibility of using recurrent and convolutional networks. Several approaches to data classification using augmentation based on vector autoregression and MapReduce parallelization technology have been implemented. It was determined that the most effective model for the multi-criteria selection problem is a combination of a bidirectional recurrent neural network with support for short- and long-term memory with several convolutional networks. The advantages of using MapReduce technology to optimize training time and data processing are shown, and a set of open questions for further research and applied implementation is defined. Conclusions: he application of an analytical and inductive approach followed by experimental verification made it possible to develop an effective (with an accuracy of more than 96%) a mechanism for detecting fabricated data both in the form of a signal and in text form. The obtained result makes it possible to assert the feasibility of implementing the proposed approach, and, accordingly, makes it possible to reduce the influence of such information in socially oriented systems, especially during crisis events.

Predicting urban tomorrow: CA-Markov modeling and district evolution

The global population is experiencing exponential growth, resulting in a substantial increase in urbanization and subsequent urban expansion. This uncontrolled expansion, often termed urban sprawl, poses significant challenges to sustainable urban development. Understanding the importance of this concern, obtaining precise information about changes in Land Use/Land Cover (LULC) becomes crucial. This research examines the transformative processes of LULC and urban expansion over a 20-year period in two distinct study areas. For this purpose, built-up areas are first analysed using satellite-derived land surface temperature data, revealing temperature increase over time attributed to urban expansion. To project future trends using CA-Markov model, the suitability maps for each LULC class aggregated through the Multi Criteria Evaluation (MCE) method. Subsequently, the CA-Markov simulates the LULC maps for 2017 and 2018 for each study area, with a focus on the year 2050. Model calibrated by comparing the simulated maps with the actual maps in both study areas, and the reliability is affirmed by high Kappa coefficients (> 80%). Consequently, the study predicts LULC maps for 2050, revealing that both areas will experience a continued increase in built-up areas, a decrease in forested areas, and a relative stability in agricultural zones over the next 33 years.

Integrating meteorological and geospatial data for forest fire risk assessment

Understanding the factors that cause fire is crucial for minimizing the fire risk. In this research, a comprehensive approach was adopted to recognize factors influencing forest fires. Golestan National Park (GNP) was considered as a representative area with a humid climate in this study. Initially, using the Multi-Criteria Evaluation Method, a fire risk map was created by analyzing natural and human factors, and vulnerable areas were identified. Then, the relationship between key elements such as meteorological conditions, Land Surface Temperature (LST), and precipitation, with the occurrence of fire in different years was investigated. CHIRPS and Landsat data were utilized to assess LST changes and precipitation. 23-year changes in fire occurrence areas in GNP were acquired using MODIS products. The results of the data analysis showed that the highest number of fires occurred in forest areas, and in the fire risk prediction map, the extremely high-risk class is completely consistent with the ground truth data. The assigned weights, derived from expert opinions, highlight the substantial significance of elevation, and distance from roads and settlements. Additionally, the effectiveness of the model in providing reliable forecasts for fire risks in GNP is highlighted by the ROC curve with an AUC value of 0.83. Forest fires within GNP exhibit a distinct seasonality, predominantly occurring from July to December. During the warmer months, by coinciding with summer excursions, human activities may contribute to the ignition of fires. In 2013 and 2014, rising fire incidents correlated with elevated temperatures, hinting at a potential connection. GNP fires showed an upward trend with higher monthly LST and a downward trend with increased annual precipitation. The results showed that there is a relationship between LST, precipitation, and the occurrence of fire in GNP. Approximately 176.15 ha of GNP's forest areas have been destroyed by fires over the last two decades. This research demonstrated that there is a dynamic interaction between environmental conditions and fire incidents. By considering these factors, managers and environmental planners can develop effective strategies for managing and preventing forest fire risks.

Towards a better psychological satisfaction: developing a mixed multi-criteria evaluation system to urban ‘Not in my back yard’ facilities siting

‘Not in My Back Yard (NIMBY)’ facilities are psychologically sensitive to urban and regional development. Multi-criteria evaluation (MCE) method has been widely used for the decision-making of optimum siting of urban NIMBY facilities which aim to improve residents’ psychological satisfaction. However, the evaluation of qualitative criteria in siting analysis remains under researched, such as the insufficient focus on urban and regional spatial development, social public opinion, and psychological factors. Thus, the effective improvement of MCE method through an interdisciplinary view can optimise the decision process and advance the factor assessment system of siting, which helps to supplement qualitative criteria evaluation. The specific improvement steps are as follows. The first step is to introduce the mixed MCE method to improve the qualitative criteria evaluation method by pre-processing qualitative criteria with min–max standardisation and normalization. This process transfers all negative factors to positive ones and transforms the F function to linear functions. The second step is to optimise the existing two-phase siting decision-making including the feasibility evaluation phase and the MCE phase. The third step is to propose a modular criteria system composed of urban and regional spatial planning, social psychological factors and the corresponding improvement strategy of this system from three perspectives of composition, measure, and weight. We argue that the improved method could be broadly applied to optimum siting decision of urban NIMBY facilities and enhance the psychological satisfaction of residents.

Evaluating Attractiveness of Newly Introduced Flights – Results of a Study for the Ostrava International Airport

Abstract The paper addresses the issue of evaluating the attractiveness of new airport connections, one of which is a global transfer hub and the other is a regional European international airport. The attractiveness of new connections expressed, for example, by predicting the demand for new flight routes has long been studied, mainly using gravity models. The aim of the presented paper is to check whether an approach based on gravity models could be replaced with other approaches, in this case by multi-criteria evaluation methods. Questions of substitution of approaches based on gravity models, compiled for demand prediction, are relevant in cases where there are not enough input data for existing gravity models. The absence of input data occurs especially in cases where either there is no historical data on the operation of flights, or historical data do not have current significance, e.g. the operation of the flight has been interrupted for a longer time. The results of a study carried out for Ostrava International Airport located in the Czech Republic, show that gravity models for which relevant data are not available can be fully replaced by multi-criteria evaluation methods.