Measuring Road Transport Sustainability Using MCDM-Based Entropy Objective Weighting Method
TL;DR: In this paper , the integrated entropy-CoCoSo approach for evaluating the sustainability of road transportation systems is introduced, and the framework process is proposed to define the weight of the decision criteria based on the real data.
Abstract: Road haulage solutions are incredibly adaptable, having the capacity to link domestically and internationally. Road transportation offers a greener, more efficient, and safer future through sophisticated technology. Symmetry and asymmetry exist widely in industrial applications, and logistics and supply chains are no exception. The multi-criteria decision-making (MCDM) model is considered as a complexity tool to balance the symmetry between goals and conflicting criteria. This study can assist stakeholders in understanding the current state of transportation networks and planning future sustainability measures through the MCDM approach. The main purpose of this paper is to evaluate and compare the sustainable development of existing road transportation systems to determine whether any of them can be effectively developed in the Organization for Economic Cooperation and Development (OECD) countries. The integrated entropy–CoCoSo approach for evaluating the sustainability of road transportation systems is introduced, and the framework process is proposed. The entropy method defines the weight of the decision criteria based on the real data. The advantage of the entropy method is that it reduces the subjective impact of decision-makers and increases objectivity. The CoCoSo method is applied for ranking the road transportation sustainability performance of OECD countries. Our findings revealed the top three countries’ sustainability performance: Japan, Germany, and France. These are countries with developed infrastructure and transportation services. Iceland, the United States, and Latvia were in the last rank among countries. This approach helps governments, decision-makers, or policyholders review current operation, benchmark the performance of other countries and devise new strategies for road transportation development to achieves better results.
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TL;DR: In this paper , a stepwise weight assessment ratio analysis (SWARA) method, the 2-tuple linguistic representation method, and the combined compromise solution (CoCoSo) were applied to solve the problem of supplier selection.
Abstract: The development of artificial intelligence and the recent COVID-19 pandemic as well as the emergence of other diseases has led to dramatic changes in the overall supply chain development. The choice of a suitable supplier will be the key to ensuring sustainable development of the company and the normal operation of the overall supply chain. However, the evaluation data of the supplier selection contains both qualitative and quantitative data simultaneously. In addition, the evaluation information provided by experts often includes some incomplete and hesitant information. These reasons lead to the complexity of supplier selection. Traditional supplier selection calculation methods ignore the objective weight considerations and thus lead to biased assessment results. The main goal of this study is to overcome the limitations of conventional supplier selection methods, fully consider the subjective and objective weights of the evaluation criteria and deal with incomplete information for providing more correct supplier ranking results. A stepwise weight assessment ratio analysis (SWARA) method, the 2-tuple linguistic representation method, and the combined compromise solution (CoCoSo) were applied in this study to solve the problem of supplier selection. To verify the rationality and correctness of the proposed method, the third-party logistics supplier selection was used as the illustrated example in the numerical validation section. The simulation results confirm that the proposed method can effectively deal with supplier selection with unclear information and can provide more reasonable supplier ranking results.
3 citations
TL;DR: In this article , a hybrid of the Fermatean fuzzy set and entropy method was used to prioritize product failure items risk, which can fully consider cognitive information provided by experts to provide more accurate risk ranking results of failure items.
Abstract: Risk evaluation is an important part of the product design and product manufacturing process; it entails the pursuit of the highest product quality and preventing failure under the constraints of limited resources. The failure mode and effects analysis approach is one of the most widely applied risk evaluation tools that uses the product of the three risk elements of product failure items, severity, occurrence probability, and detection probability, to calculate the risk priority number, the priority of failure risk. However, the typical failure mode and effects analysis method ignores the consideration of objective weights, which may lead to incorrect evaluation results. Moreover, the method of expressing information about product failure provided by experts also directly affects the results of risk assessment. To comprehensively assess the risk of product failure, in this study, the hybrid of the Fermatean fuzzy set and entropy method was used to prioritize product failure items risk. This study used a service failure mode and effects analysis numerical example of self-service electric vehicles to illustrate and test the correctness of the proposed new hybrid Fermatean fuzzy set and entropy method. The mathematical operation results were also compared with the listing of different calculation methods. The test results prove that the proposed new hybrid Fermatean fuzzy set and entropy method can fully consider the cognitive information provided by experts to provide more accurate risk ranking results of failure items.
2 citations
TL;DR: Zhang et al. as mentioned in this paper established a new comprehensive evaluation system, which selected 21 indicators from the natural and humanistic aspects, and put forward zoning optimization suggestions for the livable quality in Aksu prefecture.
Abstract: With the proposal of the United Nations Sustainable Development Goals (SDGs), how to effectively improve the quality of human settlements has become a hot spot. Governments and scholars around the world pay attention to reasonable improvement of livability, which is conducive to improving the happiness level of residents and is closely related to human well-being. Due to the lack of rural statistical data in Xinjiang, this study established a new comprehensive evaluation system, which selected 21 indicators from the natural and humanistic aspects. The results show that the overall ecological security of Aksu prefecture is good, and Kuche city has the best humanistic livability performance. In terms of the livable quality of towns, Kuche Urban Area performs best. The towns with excellent and good livable quality are concentrated, but their spatial connections are weak. Based on the analysis and survey results, we put forward zoning optimization suggestions for the livable quality in Aksu prefecture. The results of this study would provide directional guidance for the improvement of livable quality in Aksu prefecture. At the same time, we expect that it can provide a methodological supplement for the relevant evaluation in other similar regions.
2 citations
TL;DR: In this paper , a framework for the sustainability assessment of road transport in EU countries and to evaluate the countries' achievements in the last decade is presented, based on TOPSIS.
Abstract: One quarter of global energy consumption goes towards meeting transport needs. In Europe, the share of energy for transport is much higher and accounts for about a third. Therefore, it is very important to monitor the sustainable development and progress of the sector. This paper seeks to develop a framework for the sustainability assessment of road transport in EU countries and to evaluate the countries’ achievements in the last decade. The research adheres to the provision that the developed framework should be easily applied in future studies. Therefore, significant attention is paid to the selection of indicators and their availability, as well as the selection of the research instrument itself. The multi-criteria decision-making (MCDM) technique TOPSIS has been applied for calculations and countries’ ranking, in order to compare countries’ achievements in the last decade (2010–2020). The last ten years’ analysis allows us to identify the direction of individual countries in developing road transport.
1 citations
TL;DR: The authors used Landsat and Google Earth data from 1999 to 2018 to estimate the interactions among roads stock, urban size and corresponding population changes in Akure, a mid-sized capital city in Nigeria, with substantial federal road connectivity.
Abstract: The unprecedented increase in population and urbanization dynamics, particularly without the requisite road infrastructure on the African continent, necessitates a more contextual understanding of the interaction between urban expansion and transportation in its cities. The study used Landsat and Google Earth, two readily available data in a resource-constrained context, and population data from 1999 to 2018 to estimate the interactions among roads stock, urban size and corresponding population changes in Akure, a mid-sized capital city in Nigeria, with substantial federal road connectivity. The results suggest strong positive relationships among all the variables of interest. At α = 10%, an increase in road stock causes a significant ( p = 0.064) increase in population. The study reveals a heavier road density as the city expanded, slightly reduced from the core, with an increased stock of roads toward the periphery. These findings could significantly inform how cities evolve and can guide urban and transportation planners on complementary road infrastructure for growing cities. The study recommends that, irrespective of the political dispensation, the government could increase connective and motorable road stock toward the periphery each fiscal year, with promises of sustainability and resilience in the urban system despite the ever-increasing population.
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TL;DR: This final installment of the paper considers the case where the signals or the messages or both are continuously variable, in contrast with the discrete nature assumed until now.
Abstract: In this final installment of the paper we consider the case where the signals or the messages or both are continuously variable, in contrast with the discrete nature assumed until now. To a considerable extent the continuous case can be obtained through a limiting process from the discrete case by dividing the continuum of messages and signals into a large but finite number of small regions and calculating the various parameters involved on a discrete basis. As the size of the regions is decreased these parameters in general approach as limits the proper values for the continuous case. There are, however, a few new effects that appear and also a general change of emphasis in the direction of specialization of the general results to particular cases.
65,425 citations
TL;DR: In this article, the authors reviewed the corresponding methods in different stages of multi-criteria decision-making for sustainable energy, i.e., criteria selection, criteria weighting, evaluation, and final aggregation.
Abstract: Multi-criteria decision analysis (MCDA) methods have become increasingly popular in decision-making for sustainable energy because of the multi-dimensionality of the sustainability goal and the complexity of socio-economic and biophysical systems. This article reviewed the corresponding methods in different stages of multi-criteria decision-making for sustainable energy, i.e., criteria selection, criteria weighting, evaluation, and final aggregation. The criteria of energy supply systems are summarized from technical, economic, environmental and social aspects. The weighting methods of criteria are classified into three categories: subjective weighting, objective weighting and combination weighting methods. Several methods based on weighted sum, priority setting, outranking, fuzzy set methodology and their combinations are employed for energy decision-making. It is observed that the investment cost locates the first place in all evaluation criteria and CO2 emission follows closely because of more focuses on environment protection, equal criteria weights are still the most popular weighting method, analytical hierarchy process is the most popular comprehensive MCDA method, and the aggregation methods are helpful to get the rational result in sustainable energy decision-making.
1,868 citations
TL;DR: A method for the determination of objective weights which is based on the quantification of two fundamental notions of MCDM: the contrast intensity and the conflicting character of the evaluation criteria is proposed.
Abstract: The association of weights in multiple criteria problems is a critical stage of the whole decision making process. In some decision situations the extraction of subjective preferences is either difficult or undesirable. This paper proposes a method for the determination of objective weights which is based on the quantification of two fundamental notions of MCDM: the contrast intensity and the conflicting character of the evaluation criteria. The latter notion is of great importance in interfirm comparisons because the financial indices used are often highly correlated. The method developed is applied to a sample of industrial firms. The results are compared to those obtained by other sets of objective weights and show this method ensures a better compromise of the criteria examined.
1,288 citations
TL;DR: In this paper, an extensive review in the sphere of sustainable energy has been performed by utilizing multiple criteria decision making (MCDM) technique and future prospects in this area are discussed.
Abstract: In the current era of sustainable development, energy planning has become complex due to the involvement of multiple benchmarks like technical, social, economic and environmental. This in turn puts major constraints for decision makers to optimize energy alternatives independently and discretely especially in case of rural communities. In addition, topographical limitations concerning renewable energy systems which are mostly distributed in nature, the energy planning becomes more complicated. In such cases, decision analysis plays a vital role for designing such systems by considering various criteria and objectives even at disintegrated levels of electrification. Multiple criteria decision making (MCDM) is a branch of operational research dealing with finding optimal results in complex scenarios including various indicators, conflicting objectives and criteria. This tool is becoming popular in the field of energy planning due to the flexibility it provides to the decision makers to take decisions while considering all the criteria and objectives simultaneously. This article develops an insight into various MCDM techniques, progress made by considering renewable energy applications over MCDM methods and future prospects in this area. An extensive review in the sphere of sustainable energy has been performed by utilizing MCDM technique.
983 citations
TL;DR: An effective approach based on the concept used by the technique for order preference by similarity to ideal solution (TOPSIS) is developed to rank competing companies in terms of their overall performance on multiple financial ratios to ensure that the evaluation result is not affected by the inter-dependency of criteria and inconsistency of subjective weights.
Abstract: Simultaneous consideration of multiple financial ratios is required to adequately evaluate and rank the relative performance of competing companies. This paper formulates the inter-company comparison process as a multi-criteria analysis model, and presents an effective approach by modifying TOPSIS for solving the problem. The modified TOPSIS approach can identify the relevance of the financial ratios to the evaluation result, and indicate the performance difference between companies on each financial ratio. To ensure that the evaluation result is not affected by the inter-dependence of the financial ratios, objective weights are used. As a result, the comparison process is conducted on a commonly accepted basis and is independent of subjective preferences of various stakeholders. An empirical study of a real case in China is conducted to illustrate how the approach is used for the inter-company comparison problem. The result shows that the approach can reflect the decision information emitted by the financial ratios used. The comparison of objective weighting methods suggests that, with the modified TOPSIS approach, the entropy measure compares favourably with other methods for the case study conducted. Scope and purpose The performance evaluation and ranking of modern enterprises is a complex process, in which multiple financial ratios are required to be considered simultaneously. The purpose of this paper is to apply the framework of multi-criteria analysis to the inter-company comparison problem. An effective approach based on the concept used by the technique for order preference by similarity to ideal solution (TOPSIS) is developed to rank competing companies in terms of their overall performance on multiple financial ratios. The approach modifies the TOPSIS method by using weighted Euclidean distances to ensure a meaningful interpretation of the evaluation result. The use of objective weights for financial ratios based on Shannon's entropy concept reflects the context-dependent concept of informational importance. This ensures that the evaluation result is not affected by the inter-dependency of criteria and inconsistency of subjective weights. This approach is particularly applicable for situations where reliable subjective weights cannot be obtained. With its simplicity in both concept and computation, the approach can readily be incorporated into a computer-based system.
857 citations