Search Results (42)

In recent years, multi-criteria group decision-making (MCGDM) methods have attracted widespread attention in the academic community. However, most existing MCGDM approaches suffer from limitations in decision-makers’ expressive capacity and the loss of uncertain information. To address these issues, this study proposes a novel multi-criteria group decision-making (MCGDM) framework. First, we developed an evaluation information representation method called the hybrid probabilistic information set (HPIS), which allows DMs to fully express their opinions based on individual cognition using the most suitable form of representation. Second, the criteria importance through inter-criteria correlation (CRITIC) and the combined compromise solution (CoCoSo) methods are extended into the cloud model environment, ensuring that the rich uncertainty information is fully preserved and transmitted throughout the entire evaluation process. Finally, we apply the proposed MCGDM framework to a practical case study evaluating urban flood resilience within an urban agglomeration, to identify its vulnerable components. The results indicate that Baoding, Zhangjiakou, and Chengde are identified as the most vulnerable cities, necessitating immediate and targeted measures to bolster their flood defense capabilities. At the same time, decision-makers can select both qualitative and quantitative comments simultaneously and carry uncertainty information throughout the entire calculation process. Furthermore, the sensitivity and comparative analyses demonstrate the robustness and practical utility of the proposed method under the tested scenarios. Full article

The life insurance sector plays a critical role in the financial stability of countries due to its long-term liability structure and strong interaction with the financial system. The aim of this study is to evaluate the performance of the life insurance sector in the EU and EEA countries using a multi-criteria decision-making (MCDM) approach. Eight performance criteria reflecting financial stability, profitability, growth, and risk were used in the study. Criterion weights were determined using the Modified Preference Selection Index (MPSI) method, an objective method free from subjective judgments, and the performance ranking of the countries was obtained using the Combined Compromise Solution (CoCoSo) method. The data used in the analysis were obtained from the insurance statistics database published by the European Insurance and Occupational Pensions Authority (EIOPA). The findings show that ROE is the most important indicator, and that Cyprus, Hungary, and Iceland exhibit a significant positive difference in the life insurance sector compared to other countries. This study provides a unique contribution to the limited literature on comparative analyses at the country level by examining the performance of the life insurance sector in EU and EEA countries using an objective weighting and integrated ranking approach. The study results reveal important findings for a comparative assessment of life insurance markets from the perspective of regulatory bodies, policymakers, and industry stakeholders. Based on cross-sectional data for 2024, the findings should be interpreted as a framework providing a country-level risk-sensitive performance comparison under varying conditions. Full article

Sustainable competitiveness has increasingly become an important policy objective for OECD countries, as economic performance is expected to be balanced with environmental protection, social well-being, and effective governance structures. The aim of this study is to evaluate and compare the sustainable competitiveness performance of OECD countries from a holistic perspective. In the analysis, six criteria reflecting the main dimensions of global sustainable competitiveness were considered. Criterion weights were calculated using the CRITIC (Criteria Importance Through Intercriteria Correlation) method, an objective weighting technique that does not rely on subjective judgments. These weights were then integrated with the CoCoSo (Combined Compromise Solution) method to rank the sustainable competitiveness performance of countries. In the final stage, a clustering analysis was applied to group OECD countries exhibiting similar sustainability characteristics. The findings indicate that natural capital emerges as the most influential dimension within the evaluation framework. According to the ranking results, Finland, Sweden, Lithuania, Denmark, and Estonia are positioned among the countries with the highest sustainable competitiveness performance. The results reveal noticeable differences across OECD countries, demonstrating that environmental, social, economic, and governance-related dimensions affect country performance in distinct ways. A direct comparison with the 2025 Global Sustainable Competitiveness Index shows a strong but not perfect association between the two rankings (Spearman’s ρ = 0.977), indicating structural consistency alongside meaningful mid-ranking shifts. Furthermore, the clustering results enable the identification of country groups sharing relatively similar sustainability profiles. Overall, the study contributes methodologically to the sustainable competitiveness literature by integrating objective weighting, multi-criteria decision-making, and clustering analysis within a unified analytical framework, while also offering insights for comparative policy evaluation. Full article

Rapid progress in sustainable and intelligent transportation has intensified interest in smart airport initiatives, driven by the need to support environmentally responsible and technology-enabled aviation development. As complex sociotechnical subsystems of smart aviation, smart airports integrate advanced digital, operational, and organizational technologies to enhance efficiency, resilience, and passenger experience. With increasing emphasis on such transformations, multiple strategic development plans have emerged, each with distinct priorities and implementation pathways, which necessitates a rigorous and transparent evaluation mechanism to support informed decision-making under uncertainty. This study proposes an integrated spherical fuzzy multi-criteria decision-making (MCDM) framework for assessing and ranking smart airport development plans. Subjective expert judgments are modeled using spherical fuzzy sets, allowing for the simultaneous consideration of positive, neutral, and negative membership degrees to better capture linguistic and ambiguous information. Expert importance is determined through a hybrid weighting scheme that combines a social trust network model with an entropy-based objective measure, thereby reflecting both relational credibility and informational contribution. Criterion weights are computed through an integrated approach that merges criteria importance through the inter-criteria correlation (CRITIC) method with the stepwise weight assessment ratio analysis (SWARA) method, balancing data-driven structure and expert strategic preferences. The weighted evaluations are aggregated using a spherical fuzzy extension of the combined compromise solution (CoCoSo) method to obtain the final rankings. A case study involving smart airport development planning in China is conducted to illustrate the applicability of the proposed approach. Sensitivity, ablation, and comparative analyses demonstrate that the framework yields stable, discriminative, and interpretable rankings. The results confirm that the proposed method provides a reliable and practical decision support tool for smart airport development and can be adapted to other smart transportation planning contexts. Full article

Regions with insufficient resilience in their agriculture industry can usually be exposed to threats of unstable supply of food and agricultural products. Therefore, agricultural resilience is important for regional development and welfare. To support the development of agricultural resilience, proper policies and incentives need to be implemented. To achieve this, the first step is to appropriately evaluate the regional agricultural resilience levels. In this study, a novel agricultural resilience evaluation method was developed based on hybrid weighting approaches and dynamic CoCoSo (i.e., Combined Compromise Solution). The method can capture the temporal change in resilience levels, integrate richer information, and provide more robust output. To confirm its effectiveness, the method was applied to the evaluation of regional agricultural resilience in 21 cities of Sichuan province in China across five years. Over a recent five-year period, the annual average levels of agricultural resilience in Sichuan have increased, although this trend became less significant in more recent years. Also, the resilience levels among cities are diverse, and some cities have experienced significant changes of resilience across years. When considering temporal effects integrating five years, Liangshanzhou city ranks the first and Bazhong city ranks the last in terms of their resilience levels, but such results can depend on CoCoSo parameters and time weight parameters, with the latter having more significant influence. This study can contribute to the existing literature by providing new methodological tools for agricultural resilience research and regional management studies. Also, this study can help identify cities with different agricultural resilience levels and dynamics, informing practitioners’ new perspectives for agricultural policy evaluation as well as business strategy planning. Full article

Traditional multi-criteria decision-making (MCDM) methods face problems in sustainable product design evaluation, including weak semantic expression, single weight modeling, and insufficient ranking robustness. To address these issues, this paper proposes an evaluation framework based on Trapezoidal Intuitionistic Fuzzy (TrIF), named TrIF-DEC, which integrates Decision-Making Trial and Evaluation Laboratory (DEMATEL), Entropy, and Combined Compromise Solution (CoCoSo). Firstly, design criteria across four dimensions—social, economic, technological, and environmental—are identified based on sustainability considerations. Then, TrIF is used to capture the fuzziness and hesitation in expert judgments. The DEMATEL and Entropy methods are combined to extract causal relationships between criteria and quantify data variation, enabling the collaborative weighting of subjective and objective factors. Finally, multi-strategy integrated ranking is performed through TrIF-CoCoSo to enhance decision stability. An empirical case study on nursing bed design demonstrates the effectiveness of the proposed framework. Results demonstrate that TrIF-DEC can systematically integrate uncertainty information with multidimensional sustainability goals, providing reliable support for complex product design evaluation. Full article

The assessment of company performance requires a holistic approach, encompassing both financial and non-financial metrics. Accordingly, we develop a comprehensive airline performance evaluation model utilizing the Balanced Scorecard (BSC)-based multi-criteria decision-making (MCDM) framework. Based on contingency theory, we use 30 Key Performance Indicators (KPIs) derived from the literature and develop a novel performance model by combining the BSC framework with the Method based on the Removal Effects of Criteria (MEREC) for KPI weighting and the Combined Compromise Solution (CoCoSo) for ranking. The focus on Turkish Airlines, serving as a comparative benchmark, over the period 2020–2023 reveals that while financial KPIs hold the greatest weight, non-financial KPIs have the most significant impact on performance. The lowest performance is recorded in 2020, most probably attributable to the COVID-19 pandemic, followed by a remarkable recovery in 2021. We offer a methodological contribution for managers, decision-makers, and scholars—an objective, data-driven tool to assess airline performance. Furthermore, we furnish policymakers with tangible data for more effective industrial incentives and convenient regulatory strategies. In contrast to most of the literature emphasizing financial indicators and subjective weighting approaches that might yield biased rankings, we suggest a novel integrated performance evaluation model tailored for the airline industry. Full article

Macroeconomic indicators are essential measures that reflect the overall economic wellbeing of a region or country and have a significant impact on investment decisions. The data on macroeconomic indicators for Turkish development regions facilitate a comparison of macroeconomic performance between these regions. This kind of analysis can help enhance the development levels of the regions while ensuring resources are used efficiently. This study compares the macroeconomic performance of Turkish development regions between 2019 and 2022 using a hybrid multi-criteria analysis method. A total of 26 regions were evaluated based on seven criteria: GDP, GDP per capita, employment rate, number of enterprises, export, unemployment rate, and import. The criteria were weighted using the Step-Wise Weight Assessment Ratio Analysis (SWARA) method and ranked using the Combined Compromise Solution (CoCoSo) method. This study addresses a gap in the literature by analyzing the macroeconomic performance of Turkish regions, aiming to reduce economic disparities. The results showed that the Istanbul region had the best performance over the 4-year period, while Eastern Anatolia experienced a consistently declining performance, ranking last. Some regions had fluctuating performances, while others maintained steady outcomes. This study advances research by offering a more reliable and comprehensive analysis, thereby contributing to the improvement of future studies on regional economic development. Full article

Despite manufacturing firms recognizing the potential benefits of polymer-based smart materials (PBSM) in additive manufacturing (AM), their large-scale integration remains limited. As manufacturing firms strive toward net-zero emissions (NZE) and sustainable manufacturing, integrating PBSM into AM could be pivotal for manufacturing firms striving to achieve NZE and more sustainable production. In this regard, this study uses a mixed-method approach: a systematic literature review (SLR) to address the current trends and critical challenges associated with the “development, processing, and scalability” of PBSM adoption for AM. Further, the study analyzes 100 responses from Indian manufacturing firms, employing exploratory factor analysis (EFA) to develop a framework. This framework is further validated by determining the priority order of challenges using the Combined Compromise Solution (CoCoSo) through a case study. The outcome highlights that end-of-life management and lack of standardization are the most critical challenges for manufacturing firms, restricting the adoption of PBSM for AM. This research provides valuable insights for industry professionals and academia, guiding a strategic roadmap toward net-zero manufacturing. With this transformation, industries can align with global net-zero targets and contribute to India’s net-zero economy (NZE) goal by 2070. Full article

Assessing the urban green transportation development level (UGTDL) is of great significance for addressing traffic issues in megacities and promoting urban sustainable development. An evaluation framework for the UGTDL is proposed based on Multi-Criteria Decision Analysis (MCDA) methods. Firstly, from both macro and micro perspectives, a comprehensive evaluation indicator system is constructed, covering multiple dimensions such as traffic spatial organization efficiency, green travel, new energy vehicle development, traffic safety, and the traffic environment. Secondly, to address the uncertainties and fuzziness in the evaluation process, the Probability Language Term Set (PLTS) is introduced to represent expert evaluation information, thereby reducing the information loss. Thirdly, the improved Step-wise Weight Assessment Ratio Analysis (SWARA) method is employed to calculate the weights of the indicators, improving the computational efficiency. Finally, the extended Combined Compromise Solution (CoCoSo) method is used to calculate the UGTDL, avoiding the compensatory issues in the traditional decision-making methods. The proposed approach is applied to assess the UGTDL in Guangzhou from 2020 to 2023. The results show that the UGTDL scores for Guangzhou from 2020 to 2023 are 1.6367, 2.2325, 2.1141, and 1.8575, respectively. Sensitivity analysis verifies the effectiveness and stability of the approach. Further obstacle analysis shows that the promotion of new energy vehicles (NEVs) has led to a marginal decrease in the utility of Guangzhou’s UGTDL. In the future, Guangzhou should take further measures to improve the traffic space organization efficiency and traffic safety. Full article

Emergency medical services (EMSs) are critical to reducing fatalities and improving patient outcomes in emergencies such as traffic accidents, where response time is a decisive factor. This study proposes a comprehensive and systematic approach to designing and optimizing EMS systems tailored for urban traffic accidents. By integrating Geographic Information Systems (GISs), hypercube queuing models, Economic Value Added (EVA) calculations, and multi-criteria decision-making (MCDM) techniques, we developed a model that balances service efficiency, financial sustainability, and equitable access to emergency care. The hypercube queuing model was applied to estimate key performance metrics, such as response time, coverage, and the GINI index for equity, under varying numbers of ambulances and demand scenarios. In addition, EVA was calculated for different configurations of leased and owned ambulances, offering a financial perspective to assess the viability of public–private partnerships (PPPs) in EMSs. Using the fuzzy Analytic Hierarchy Process (AHP) and CoCoSo (Combined Compromise Solution) methods, this study identified the optimal number of ambulances required to minimize response time, maximize coverage, and ensure financial sustainability. The proposed approach has been applied to a real case in Colombia. Furthermore, integrating leased ambulances offers a financially viable solution with positive EVA values that guarantee the long-term sustainability of the public–private partnership. This paper advances the literature by providing a practical framework for optimizing EMS systems, particularly in developing countries where financial constraints and resource limitations represent significant challenges. The proposed methodology improves service efficiency and economic sustainability and ensures equity in access to life-saving care. Full article

More and more investments are being made in energy conversion projects from renewable energy sources (RESs), and a large number of investors are entering this sector. The focus of this study is the decision-making by the investor BD Green Energy in the Brčko District of Bosnia and Herzegovina. In order to choose the RES system that would realize this investment in the most efficient way, expert decision-making based on the fuzzy–rough approach and the Bonferroni mean operator was used. Determining the importance of the criteria was conducted using the fuzzy–rough SiWeC (simple weight calculation) method. The results of this method showed that all used criteria have similar importance for the investor. RES system selection was conducted using the fuzzy–rough CoCoSo (combined compromise solution) method. The results of this method showed that investing in photovoltaic (PV) energy is the best for the investor. This research provided guidance on how investors should make investment decisions in RES systems with incomplete information and uncertainty in the decision-making process. Full article

International economic trade plays a crucial role in global merchandise supply chains; as such, the development of industries is critical to enhance the expansion and growth of marine transportation services. In Vietnam, commercial activities are rapidly expanding, and there is a strong foundation for developing seaport enterprises. This research aims to evaluate and rank the business performance of seaport enterprises in Vietnam by analyzing the ratio of various variables in the financial statements from 2019 to 2023 via an integration of the Criteria Importance Through Intercriteria Correlation (CRITIC) and Combined Compromise Solution (COCOSO) methods. First, the weight of each variable will be determined by the CRITIC method. Second, the efficiency and rank of each alternative will be identified by the COCOSO method. These empirical results revealed the business performance and position of each seaport enterprise based on the efficiency scores, providing valuable insights into their financial operations. Additionally, the findings described a comprehensive overview of maritime transport and recommended actionable solutions to improve the business performance of seaport enterprises in the future. Full article

The United Nations’ sustainable development goals have highlighted the significance of improving supply chain sustainability and ensuring the proper distribution of orders. This study proposes a novel framework involving Z-number, game theory, an indifference threshold-based attribute ratio analysis (ITARA), and a combined compromise solution method (CoCoSo) to evaluate the sustainability of suppliers and order allocations. To better reflect the decision makers’ current choices for the sustainability of assessed suppliers and order allocations and enhance the comprehensiveness of decision-making, the importance parameter of the supplier is obtained through game theory objectively for transforming supplier performance into order allocation performance. The Z-numbers are involved in ITARA (so-called ZITARA) and CoCoSo (so-called ZCoCoSo) to overcome the issue of information uncertainty in the process of expert evaluation. ZITARA and ZCoCoSo are used to determine the objective weights of criteria and to rank the evaluated order allocations, respectively. A case study of a China company is then presented to demonstrate the usefulness of the proposed framework and to inform their decision-making process regarding which suppliers the orders should be assigned to. Full article

In terms of both economy and sustainability, rural areas can greatly benefit from adopting E-commerce. The Chinese government is currently devoting significant efforts to developing agricultural E-commerce. However, one of the most significant problems is the lack of effective tools for evaluating regional potentials in this regard, possibly leading to inappropriate policymaking, investment allocation, and regional planning. To address this issue, this study proposes a novel and effective method for evaluating regional potentials for agricultural E-commerce development, integrating the method based on the removal effects of criteria (MEREC), Heronian mean operator, and combined compromise solution (CoCoSo) method. The method’s effectiveness is then tested and confirmed in the Chinese city of Yibin through an evaluation of its ten regions. The results suggest that such a method is robust, objective, and able to consider indicator interactions effectively. By applying this method, regional agricultural E-commerce development potentials can be thoroughly evaluated and ranked. This study contributes to the literature by providing new analytical techniques for agricultural studies, as well as by supporting political and investment decision-making for governments and E-commerce practitioners in the agriculture sector. Full article