Multicriteria Approach to Sustainable Transport Evaluation under Incomplete Knowledge: Electric Bikes Case Study

Compromise Multi-Criteria Selection of E-Scooters for the Vehicle Sharing System in Poland

In Poland, there is a high ratio of private transport and unfavorable patterns of daily commuting. These patterns can be changed by introducing comfortable and eco-friendly vehicles, such as e-scooters and e-bikes. At the same time, the development of the e-micromobility-based vehicle sharing services market is developing. The aim of the article is to analyze selected e-scooters available on the Polish market and to identify the most useful vehicles from two opposing perspectives, i.e., the potential customer and owner of the vehicle sharing system. The PROSA GDSS (PROMETHEE for Sustainability Assessment—Group Decision Support System) method and the graphical representation of GAIA (Geometrical Analysis for Interactive Assistance) were used to search for a compromise and balance between the needs of the indicated stakeholders. The results of the methods used were compared with the results of the PROMETHEE GDSS method, which does not take into account the balance between the stakeholders and allows for a strong compensation of the assessments of decision makers. The conducted research allowed indicating the optimal e-scooter to meet the needs of both decision makers, and it is the JEEP 2xe Urban Camou. Both the sensitivity analysis and the solution obtained with the use of the PROMETHEE GDSS method confirmed that it is the optimal alternative, the least sensitive to changes in criteria weights and changes in the decision makers’ compensation coefficients.

How Should We Measure? A Review of Circular Cities Indicators

As the world continues to urbanize, it is necessary to identify and implement new urban development models and strategies in order to meet the challenges of sustainable development. As cities continue to face challenges in becoming fully circular, the need to establish a framework to measure the circular economy in urban areas grows. Many definitions for circular cities have been developed and addressed in recent years, as have numerous indicators. To make the transition to a circular city, we must integrate the findings and develop a general definition and measurement framework. This article aims at outlining a framework for circular cities indicators based on their key characteristics, as well providing directions for fostering circularity at the city level. To accomplish this goal, we conducted a systematic review and analyzed key papers published in the field of circular economy to determine how circular cities are measured. Choosing the right indicators to use for developing, monitoring, and evaluating circular cities is a difficult task for urban policymakers, managers, and planners. This highlights the significance of standardized frameworks for urban indicators. As a result, the authors propose a framework and highlight some key points about circular cities and smart urban metabolism.

Evaluating the Environmental Impact of Using Cargo Bikes in Cities: A Comprehensive Review of Existing Approaches

The impact of the use of cargo bicycles for delivery processes on the environment is undeniably positive: it leads to the reduction of pollutants, noise, and vibrations caused by traditional vehicles; decreases traffic jams; causes more effective use of public space; and others. But how should such an effect be measured? What tools should be used to justify the necessity for change to more sustainable means of transport? How can we improve the state of the environment considering the interests of logistics service providers? There is a large amount of scientific literature dedicated to this problem: by using different modeling approaches, authors attempt to address the issue of sustainable transport. This paper conducts a literature review in the field of green cargo deliveries, investigates the benefits and drawbacks of integrating cargo bikes in urban logistics schemes, and examines methodologies and techniques for evaluating the impact of using cargo bicycles on the environment. By providing an opportunity to get acquainted with the situation in the sphere of green deliveries, the authors aim to encourage a breakthrough in the field of sustainable transport that may be achieved by using cargo bikes in modern cities. We review the existing approaches and tools for modeling transport emissions and state the significant positive environmental consequences.

Methodical Aspects of MCDM Based E-Commerce Recommender System

The aim of this paper is to present the use of an innovative approach based on MCDM methods as the main component of a consumer Decision Support System (DSS) by recommending the most suitable products among a given set of alternatives. This system provides a reliable recommendation to the consumer in the form of a compromise ranking constructed from the five MCDM methods: the hybrid approach TOPSIS-COMET, COCOSO, EDAS, MAIRCA, and MABAC. Each of the methods used contributes significantly to the final compromise ranking built with the Copeland strategy. Chosen MCDM methods were combined with the objective CRITIC weighting method, and their performance was presented on the illustrative example of choosing the most suitable mobile phone. A sensitivity analysis involving the rw and WS correlation coefficients was performed to determine the match between the compromise ranking of the candidates and the rankings provided by each MCDM method. Sensitivity analysis demonstrated that all investigated compromise candidate rankings show high convergence with the rankings provided by the particular MCDM methods. Thus, the performed study proved that the proposed approach shows high potential to be successfully used as a central component of DSS for recommending the most suitable product. Such DSS could be a universal and future-proof solution for e-commerce sites and websites, providing advanced product comparison capabilities in delivering a recommendation to the user as a final ranking of alternatives.

Exploring Intention to Use Shared Electric Bicycles by the Extended Theory of Planned Behavior

In China, shared electric bicycles are developing rapidly, and are widely used by residents. Understanding the factors that affect residents’ intention to use shared electric bicycles is important for implementing a policy of developing sustainable transportation. A sample of 751 respondents has been collected in a small-sized Chinese city to analyze residents’ intention to use shared electric bicycles, using an extended theory of planned behavior model. The findings reveal that the research model can well explain residents’ intention to use shared electric bicycles. Attitude, subjective norm, and perceived behavioral control have direct positive effects on the intention to use shared electric bicycles. Among them, the subjective norm has the greatest impact on the intention to use shared electric bicycles. Environmental concern and policy support have indirect positive effects on the intention to use shared electric bicycles through the partial mediation of attitude and subjective norm. Based on the above analysis, some measures are proposed to guide the development of shared electric bicycles.

Identification of Relevant Criteria Set in the MCDA Process—Wind Farm Location Case Study

The paper undertakes the problem of proper structuring of multi-criteria decision support models. To achieve that, a methodological framework is proposed. The authors’ framework is the basis for the relevance analysis of individual criteria in any considered decision model. The formal foundations of the authors’ approach provide a reference set of Multi-Criteria Decision Analysis (MCDA) methods (TOPSIS, VIKOR, COMET) along with their similarity coefficients (Spearman correlation coefficients and WS coefficient). In the empirical research, a practical MCDA-based wind farm location problem was studied. Reference rankings of the decision variants were obtained, followed by a set of rankings in which particular criteria were excluded. This was the basis for testing the similarity of the obtained solutions sets, as well as for recommendations in terms of both indicating the high significance and the possible elimination of individual criteria in the original model. When carrying out the analyzes, both the positions in the final rankings, as well as the corresponding values of utility functions of the decision variants were studied. As a result of the detailed analysis of the obtained results, recommendations were presented in the field of reference criteria set for the considered decision problem, thus demonstrating the practical usefulness of the authors’ proposed approach. It should be pointed out that the presented study of criteria relevance is an important factor for objectification of the multi-criteria decision support processes.

Evaluation of the Italian transport infrastructures: A technical and economic efficiency analysis

•The deregulation process played a key role in terms of airport efficiency.•The technical efficiency of 32 Italian airports has been evaluated•The methodological approach has been twofold: DEA and Tobit model•The main results show that efficiency is independent of an airport's size.•The findings highlight the decisive role of public shareholders in small airports.

Identification of Players Ranking in E-Sport

Human activity is moving steadily to virtual reality. More and more, people from all over the world are keen on growing fascination with e-sport. In practice, e-sport is a type of sport in which players compete using computer games. The competitions in games, like FIFA, Dota2, the League of Legends, and Counter-Strike, are prestigious tournaments with a global reach and a budget of millions of dollars. On the other hand, reliable player ranking is a critical issue in both classic and e-sport. For example, the “Golden Ball” is the most valuable prize for an individual football player in the whole football history. Moreover, the entire players’ world wants to know who the best player is. The position of each player in the ranking depends on the assessment of his skills and predispositions. In this paper, we studied identification of players evaluation and ranking obtained using the multiple-criteria decision-making based method called Characteristic Objects METhod (COMET) on the example of the popular game Counter-Strike: Global Offensive (CS: GO). We present a range of advantages of the player evaluation model created using the COMET method and, therefore, prove the practicality of using multi-criteria decision analysis (MCDA) methods to build multi-criteria assessment models in emerging areas of eSports. Thus, we provide a methodical and practical background for building a decision support system engine for the evaluation of players in several eSports.

Efficiency of Methods for Determining the Relevance of Criteria in Sustainable Transport Problems: A Comparative Case Study

Problems related to sustainable urban transport have gained in importance with the rapid growth of urban agglomerations. There is, therefore, a need to support decision-making processes in this area, a trend that is visible in the literature. Many methods have already been presented as a useful decision-making tool in this field. However, it is still a significant challenge to properly determine the relevance of the criteria because it is one of the most critical points of many presented techniques to solve decision problems. In this work, we propose two new approaches to determining the relevance of particular decision criteria effectively in sustainable transport problems. For this purpose, we examine a study case for the evaluation of electric bikes evaluated against eight criteria, which have been taken from earlier work. We calculate the relevance of each criterion using four different approaches and then evaluate their effectiveness using a reference ranking and popular multi-criteria decision analysis methods. The results are compared with each other by using similarity coefficients. Finally, we summarize the results obtained and set out further methods of development.

A New Approach to Identifying a Multi-Criteria Decision Model Based on Stochastic Optimization Techniques

Many scientific papers are devoted to solving multi-criteria problems. Researchers solve these problems, usually using methods that find discrete solutions and with the collaboration of domain experts. In both symmetrical and asymmetrical problems, the challenge is when new decision-making variants emerge. Unfortunately, discreet identification of preferences makes it impossible to determine the preferences for new alternatives. In this work, we propose a new approach to identifying a multi-criteria decision model to address this challenge. Our proposal is based on stochastic optimization techniques and the characteristic objects method (COMET). An extensive work comparing the use of hill-climbing, simulated annealing, and particle swarm optimization algorithms are presented in this paper. The paper also contains preliminary studies on initial conditions. Finally, our approach has been demonstrated using a simple numerical example.

Are MCDA Methods Benchmarkable? A Comparative Study of TOPSIS, VIKOR, COPRAS, and PROMETHEE II Methods

Multi-Criteria Decision-Analysis (MCDA) methods are successfully applied in different fields and disciplines. However, in many studies, the problem of selecting the proper methods and parameters for the decision problems is raised. The paper undertakes an attempt to benchmark selected Multi-Criteria Decision Analysis (MCDA) methods. To achieve that, a set of feasible MCDA methods was identified. Based on reference literature guidelines, a simulation experiment was planned. The formal foundations of the authors’ approach provide a reference set of MCDA methods ( Technique for Order Preference by Similarity to Ideal Solution (TOPSIS), VlseKriterijumska Optimizacija I Kompromisno Resenje (VIKOR), Complex Proportional Assessment (COPRAS), and PROMETHEE II: Preference Ranking Organization Method for Enrichment of Evaluations) along with their similarity coefficients (Spearman correlation coefficients and WS coefficient). This allowed the generation of a set of models differentiated by the number of attributes and decision variants, as well as similarity research for the obtained rankings sets. As the authors aim to build a complex benchmarking model, additional dimensions were taken into account during the simulation experiments. The aspects of the performed analysis and benchmarking methods include various weighing methods (results obtained using entropy and standard deviation methods) and varied techniques of normalization of MCDA model input data. Comparative analyses showed the detailed influence of values of particular parameters on the final form and a similarity of the final rankings obtained by different MCDA methods.

Multi-Objective Approach for Optimization of City Logistics Considering Energy Efficiency

Urban population increase results in more supply chain operations in these areas, which leads to increased energy consumption and environmental pollution. City logistics represents a strategy of efficient freight transportation and material handling to fulfill customer and business demands. Within the frame of this paper, the authors describe an optimization model of a multi-echelon collection and distribution system, focusing on downtown areas and energy efficiency, sustainability, and emission reduction. After a systematic literature review, this paper introduces a mathematical model of collection and distribution problems, including package delivery, municipal waste collection, home delivery services, and supply of supermarkets and offices. The object of the optimization model is twofold: firstly, to design the optimal structure of the multi-echelon collection and distribution system, including layout planning and the determination of required transportation resources, like e-cars, e-bikes, and the use of public transportation; and secondly, to optimize the operation strategy of the multi-echelon supply chain, including resource allocation and scheduling problems. Next, a heuristic approach is described, whose performance is validated with common benchmark functions, such as metaheuristic evaluation. The scenario analysis demonstrates the application of the described model and shows the optimal layout, resource allocation, and operation strategy focusing on energy efficiency.

Strategic Planning Based on Sustainability for Urban Transportation: An Application to Decision-Making

Public transportation is one of the main goals of a developing city. This topic includes not only administrators, but also city residents and the environment, with economic, environmental, and social factors. This paper presents a multicriteria decision-making process for prioritizing alternative public transportation projects in Kırıkkale, considering the urban type of a developing city. It outlines three planned projects for improvement: “electric municipality bus”, “light rail system”, and the “modernization of existing vehicles and network optimization”. In this study, we use the analytic hierarchy process and fuzzy technique for order preference by similarity to ideal situation (TOPSIS) application to prioritize transportation projects using economic, social, transportation, and environmental sub-criteria. The aim of this study is to select the most suitable project, based on sustainability, for more urban livability in Kırıkkale city. In the strategic decision-making process, the weights of each sustainability criteria have been determined using analytic hierarchy process (AHP). The fuzzy TOPSIS method has been applied for ranking the proposed alternative projects for Kırıkkale. Finally, the analytic decision process results are compared, and the electric municipality bus is selected as the best project alternative. The results of this study can not only offer a solution for current needs related to urban planning, but also ensure as a more transparent decision-making process for developing sustainability in developing cities in the near future.

Resilience and Vulnerability of Public Transportation Fare Systems: The Case of the City of Rio De Janeiro, Brazil

Resilience is the ability of a system to adapt, persist, and transform as a reaction to threats, which may be external or internal to the system, while vulnerability is the state of being susceptible to harm from exposure to stresses associated with environmental and social change and from the inability to adapt. Based on a study of the threats that can affect urban mobility, we identified a gap regarding the analysis of the levels of resilience and vulnerability in the face of subsidy threats that can severely affect developing countries. This article measures the level of resilience and vulnerability due to the absence of public transport fare subsidies. For this purpose, we developed an approach based on fuzzy logic and applied it in 33 administrative regions (ARs) of the city of Rio de Janeiro, Brazil. We obtained four matrices of the levels of vulnerability and resilience of each of the regions as an origin and destination. The results show that areas nearest to the downtown region and those with high-capacity transportation available (commuter train and/or subway, systems with many transfer points) are more resilient, while a high level of vulnerability is associated with low income, negative socioeconomic indicators, and the predominance of road transportation to reach jobs. The contribution of this paper is the method applied to analyse the levels of vulnerability and resilience of public transport, which includes a threat that can cause a rupture that impacts routines and job accessibility in a region.

The Effects of a First-Time Experience on the Evaluation of Battery Electric Vehicles by Potential Consumers

In some countries, such as Norway, there is significant growth in the proportion of battery electric vehicles (BEVs) among new registrations. This is not the case in Germany, where less than 1% of all newly registered vehicles are electric cars. This disparity raises the questions of whether the performance factors of current BEVs (e.g., driving range) are able to compete with petrol-powered cars and how they are perceived by potential customers. Using marketing methods, car manufacturers can influence attitudes towards products and increase purchase intentions. Most prior studies used experiments in different settings to find out the perceived value of BEVs among potential customers, taking into account a longer perspective. There are no prior studies on the influence of short test drives on the value perception of BEVs. The main objective of this article was to explore and assess the effects of a first-time experience on the evaluation of BEVs by potential consumers in the German market (around the city of Münster, in the North Rhine-Westphalia region). We utilized the concept of a sensory marketing approach in the form of a short (10–15 min) test drive experiment. The results showed that perceptions, in terms of acquisition costs and acceleration/driving pleasure in particular, are developing positively. Other increasing values are maintenance and energy costs, engine/battery reliability, range in km, and driving comfort. In addition, the perception of all other performance factors has developed positively. Also, willingness to buy a BEV increased after the short test drive. The experiment shows that short test drives with BEVs are a suitable means to support the widespread promotion of electric cars.