Search Results (68)

Process Failure Mode and Effects Analysis (PFMEA) is the standard technique for proactive risk assessment in automotive assembly lines. To support differentiated criterion weighting, hesitancy-aware linguistic evaluation and rank stability validation, this paper proposes a symmetric extension of PFMEA that integrates Proportional Intuitionistic Fuzzy Sets (PIFSs) with the Analytic Hierarchy Process (AHP) and the Evaluation Based on Distance from Average Solution method (PIF-EDAS). PIFSs introduce a proportional balance between membership μ, non-membership ν and hesitancy π that is mathematically symmetric under linguistic-pair interchange and that preserves a constant hesitancy budget (π = 1/(1 + $k_1$ + $k_2$)) across the nine-point linguistic scale. The framework is applied to an automotive Original Equipment Manufacturer (OEM) assembly line in Türkiye, on an inventory of twelve failure modes spanning torque, fastening, welding, panel alignment, harness, sealant, paint, ECU, trim, electrical connector, part variant and tightening sequence operations. Consistency of the PIF-AHP pairwise comparisons is confirmed (CR = 0.0017 ≪ 0.1), yielding criterion weights $w_S$ = 0.598, $w_O$ = 0.245 and $w_D$ = 0.156. Comparative cross-method analysis against PIF-TOPSIS, PIF-VIKOR and a classical-style ordinal RPN benchmark indicates strong cross-method agreement: Spearman rank correlations range from 0.865 to 0.972, and Wrong Torque Application remains the unanimous top-priority failure across all four methods. Five sensitivity scenarios (proposed weights, equal weights, and severity-, occurrence- and detection-dominant) confirm that FM1 (Wrong Torque) remains the top-priority failure and FM9 (Damaged Interior Trim) remains the lowest-priority failure across all five scenarios; the composition of the upper-priority set is criterion-sensitive, with FM10 rising under equal-weight, occurrence- and detection-dominant scenarios and FM8 rising under the severity-dominant scenario. The proposed framework incorporates differentiated criterion weights, expert hesitancy and rank stability validation within a symmetric PIFS-based MCDM structure. The contribution of this study is therefore three-fold: (i) a symmetric PIFS formulation that enforces mirror symmetry under linguistic-pair interchange and a constant hesitation budget on the nine-point scale; (ii) a case-based assessment of twelve automotive PFMEA failure modes; and (iii) a transparent rank stability protocol for symmetric MCDM benchmarking. The framework integrates directly with existing FMEA workflows and scales linearly in computational complexity with the number of failure modes. Full article

Inbound tourism has become an important indicator of destination openness, service capacity, cultural communication, and sustainable governance. However, existing evaluations often separate visitor experience, destination competitiveness, and sustainability, making it difficult to diagnose how service quality supports long-term competitiveness. This study develops a sustainability-oriented framework for evaluating inbound tourism service quality in 10 representative Chinese cities. Nineteen indicators are organized into four dimensions: basic service provision, cultural and experiential perception, safety and emergency response, and sustainable and resilient development. A TIFN-AHP-TOPSIS model is used to integrate official statistics, public tourism information, online-review evidence, and expert judgments while retaining uncertainty and hesitation in qualitative assessments. The results show that Shanghai, Beijing, and Hangzhou form the leading tier; Shenzhen, Chengdu, Guangzhou, Sanya, and Xiamen form the balanced tier; and Xi’an and Chongqing form the potential tier. Robustness checks based on risk-preference adjustment, entropy-weighted TOPSIS, grey relational TOPSIS, and perception-indicator perturbation confirm the stability of the tier classification. The findings suggest that inbound tourism competitiveness depends not only on transport access and reception capacity but also on cultural interpretation, digital convenience, safety governance, ecological quality, and resilience. The framework provides a diagnostic tool for improving sustainable destination competitiveness. Full article

The rapid adoption of artificial intelligence (AI) in healthcare is reshaping service delivery and enabling more personalized, data-driven care. However, cross-country differences in AI implementation and perceived strategic importance remain insufficiently understood. This study proposes a dual-dimensional framework to assess AI maturity across 50 countries in the WHO European Region, distinguishing between actual AI applications and perceived opportunities. Using data from the WHO 2024–2025 Artificial Intelligence for Health survey, the AI Applications Index (AIA) is constructed using an intuitionistic fuzzy TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) method that accounts for uncertainty in implementation. In parallel, the AI Opportunities Index (AIO) is developed using a belief-structure TOPSIS approach to capture perceptions of AI’s strategic relevance. To better understand underlying patterns, Multiple Correspondence Analysis and Ward hierarchical clustering are applied to identify latent structures, homogeneous groups, and transitional development pathways. An Index of Alignment (IA) is introduced to measure coherence between AI applications and perceived opportunity. Countries are grouped into four development trajectories based on the mean values of the AI Applications and AI Opportunities indexes: AI leaders, implementation-driven systems, opportunity-driven systems, and lagging systems. These results are further compared with Ward clustering, revealing hybrid and transitional profiles not fully captured by aggregate classifications. The findings indicate that AI maturity is shaped not only by implementation levels but also by the alignment between technological capacity and strategic perception. The results highlight the multi-speed and institutionally differentiated nature of AI transformation in European healthcare systems. Full article

The recycling of power batteries is a key measure for improving the new energy industry chain and achieving green circular economy goals. However, the process of evaluating and selecting recycling schemes is influenced by multiple complex factors and often involves a significant amount of ambiguous and uncertain decision-making information. As an important extension of intuitionistic fuzzy sets, picture fuzzy sets characterize fuzzy information through three distinct dimensions: membership, neutrality, and non-membership. This three-dimensional structure offers unique advantages in addressing uncertain and ambiguous decision-making problems, where traditional fuzzy sets may lose valuable information. Drawing on the Bray–Curtis distance measure, this paper proposes a novel picture fuzzy distance measure that captures differences across all three dimensions more comprehensively. By combining the weighted form of the proposed picture fuzzy distance measure with the classical TOPSIS method, a new multi-attribute decision-making model is established under the picture fuzzy framework. The effectiveness and feasibility of the proposed method are demonstrated through a case study on the recycling of power batteries for electric vehicles. A sensitivity analysis of relevant parameters is conducted, confirming the stability of the model against variations in parameter settings. Comparative results indicate that the proposed novel picture fuzzy distance measure exhibits superior robustness compared to existing similar distance measures. Furthermore, the constructed decision-making model can provide reliable and practical support for uncertain multi-attribute decision-making problems in real-world applications. Full article

Digital transformation is reshaping societies by promoting the adoption of advanced technologies. Moreover, the digitization of public services has become an important focus for governments. In this paper, digital government performance indicators are analyzed to improve the efficiency of digitizing public services. Based on this awareness, the seven main criteria and twenty-one sub-criteria are determined. Then, a fuzzy decision-making framework is proposed to evaluate digital government performance across 165 countries as alternatives. To the best of our knowledge, limited studies have investigated an integrated clustering-based fuzzy decision-making framework for evaluating digital government performance. The intuitionistic trapezoidal fuzzy number-based analytical hierarchy process (ITFNAHP), a part of the introduced framework, is developed to find the weights of the main criteria and sub-criteria. Digital technologies, innovation, and the economy are the most significant criteria for digital government operations. The k-means clustering method is then employed to group the alternatives. The four clusters are obtained from the clustering technique. Next, the technique of order preference similarity to ideal solution (TOPSIS) is introduced to rank the digital governments of each cluster. Switzerland, Rwanda, North Macedonia, and Eswatini are the top choices among others in each cluster, respectively. Additionally, a sensitivity analysis is conducted considering the ten different situations. In addition, the managerial and policy implications are discussed, including the achievement of Sustainable Development Goals (SDGs). Full article

Amid the accelerating waves of global digitalization and the deepening interplay of cultural diversity, urban creative spaces have become pivotal arenas for the digital creative industry—yet a systematic, cross-culturally robust tool for assessing their sustainability remains conspicuously absent. Here, we address this gap by constructing a multi-dimensional evaluation framework derived from a systematic literature review, comprising five primary dimensions—AIGC technology integration, cultural heritage preservation, the economic benefits of the digital cultural industry, ecological synergy and social inclusiveness, and governance and policy support—along with 20 secondary indicators. To enhance methodological rigor, we integrate the Intuitionistic Fuzzy Analytic Hierarchy Process (IFAHP) to determine indicator weights while mitigating the subjective biases inherent in traditional approaches and employ the TOPSIS method to quantitatively assess and rank the creative spaces of five representative cities: London, Shanghai, Los Angeles, Tokyo, and Berlin. Our findings reveal that London leads in comprehensive sustainability, followed closely by Shanghai, with sensitivity analysis confirming the high robustness of the rankings. The originality of this work lies in reconceptualizing AIGC not as a conventional digital instrument but as a core transformative driver embedded within the evaluation architecture, while the application of IFAHP substantially enhances the scientific validity and methodological reliability of the assessment. This research provides an operational diagnostic tool and actionable optimization pathways for advancing the sustainability of urban creative spaces worldwide, offering practical implications for fostering cultural innovation, bridging the digital divide, promoting social inclusiveness, and informing evidence-based urban governance policies. Full article

With the rapid development of intensive marine aquaculture, water quality has become a key factor affecting both economic benefits and ecological safety in marine aquaculture. In the process of actual water quality evaluation, due to the great uncertainty and ambiguity of evaluation indicators, experts find it difficult to evaluate in real number form and are more inclined to use linguistic variables to evaluate indicators, which poses challenges for the construction of water quality evaluation models. An intuitionistic fuzzy set (IFS) is an effective tool for dealing with uncertainty and fuzziness in complex problems. Based on a detailed analysis of existing distance measures for IFS, this study proposes a new distance measure that not only considers membership and non-membership information, but also constructs an allocation function for membership and non-membership, introducing hesitation information into distance metrics. We proposed the definitions and proved the properties. The comparative experiments show that the new distance measure can overcome the shortcomings of existing distance measures. Furthermore, based on the newly proposed distance measure, the IFS TOPSIS method is improved in multi-attribute decision-making applications. Finally, a practical application of marine aquaculture water quality evaluation is used. The results illustrate that when $\alpha$ = 1 the closeness declines from 0.741 to 0.432, when =2 the closeness declines from 0.662 to 0.46, and when =6 the closeness declines from 0.566 to 0.82. The convenience and effectiveness of the new method is demonstrated. Full article

This research assessed management strategies for overtourism in Zadar County. Overtourism has become apparent in both city and seaside destinations, affecting residents’ quality of life. This study defines overtourism as a challenge for urban management, emphasizing that exploring strategies to address overtourism also influences the management of sustainability and quality of life in urban areas. Here, a methodological framework was created with five strategies, each evaluated against seven criteria. The evaluation was carried out by the directors of the county’s tourist boards. Since these strategies have not yet been implemented, the directors had to rate them with some uncertainty, as they lacked complete information about the criteria and potential effects. To handle this uncertainty, the intuitionistic fuzzy set (IFS) approach was used. Additionally, the SiWeC method determined the importance of the criteria, and the TOPSIS method ranked the strategies. Results, based on ratings from 12 directors, indicated that Digital Support and Environmental Sustainability are the most important criteria. Strategy C, which aims to redirect tourists to lesser-known locations within the county, performed best, maintaining visitor numbers while helping preserve the region’s natural resources. This research has shown that strategies for managing overtourism help reduce the pressure tourists place on urban environments, thereby improving the quality of life and sustainable development of these environments. Full article

Selecting a sustainable healthcare waste treatment method is a complex multi-criteria problem influenced by environmental, economic, social and technological factors. This study addresses key gaps in the literature by proposing an intuitionistic fuzzy AHP–TOPSIS framework that explicitly models cognitive uncertainty and expert hesitation, while demonstrating its application through a real-world case study in Adana, Türkiye. In contrast to prior studies utilizing fewer criteria, our framework evaluates four treatment alternatives—incineration, steam sterilization, microwave, and landfill—across 17 comprehensive criteria that directly integrate circular economy principles such as resource recovery and energy efficiency. The results indicate that steam sterilization is the most sustainable option, demonstrating superior performance across environmental, economic, social, and technological dimensions. A 15-scenario sensitivity analysis ensures ranking resilience across varying decision contexts. Furthermore, a systematic comparative analysis highlights the methodological advantages of the proposed framework in terms of analytical granularity and robustness compared to existing models. The study also offers step-by-step operational guidance, creating a transparent and policy-responsive decision-support tool for healthcare waste management authorities to advance sustainable practices. Full article

Aiming at the problem that existing intuitionistic fuzzy entropy measures fail to fully balance the interaction between intuition (determined by hesitation degree) and fuzziness (characterized by the difference between membership degree and non-membership degree), this paper proposes the concept of isentropic arc, reveals the mutual offset effect of the two in entropy composition, and provides a new theoretical perspective for the planar analysis of entropy measures. Further research finds that there are maximum and minimum entropy points in the intuitionistic fuzzy entropy plane. Based on this, two different types of isentropic arcs can be constructed. Combining this feature with the core logic of approaching the ideal solution, this paper constructs a new intuitionistic fuzzy entropy measure formula based on the TOPSIS method. This formula can characterize the synergistic influence of intuition and fuzziness at the same time, meets all the constraints of the axiomatic definition, and is more suitable for the needs of actual decision-making scenarios. Comparative analysis of numerical examples shows that the proposed new entropy measure has significantly better discrimination than existing methods for six groups of samples with a high hesitation degree and high fuzziness, and the entropy value ranking is consistent with the ranking of the uncertainty information contained in the samples. Finally, the weight decision-making model based on this entropy measure is applied to the evaluation of coal mine emergency rescue capability, verifying its practical value in solving complex uncertainty problems. Full article

In a dynamic and uncertain environment, maintaining a high level of business process (BP) reliability represents a key long-term objective for organizations. The manufacturing process, as the most critical business process in manufacturing enterprises, is emphasized due to its potential to cause significant disruptions across other BPs if it fails. This paper proposes a two-stage model. In the first stage, failures leading to lean waste are evaluated and ranked using the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) combined with interval-valued intuitionistic fuzzy numbers (IVIFNs), referred to as IF-TOPSIS. The model is grounded in the Failure Mode and Effect Analysis (FMEA) framework. In the second stage, a modified fuzzy logic system with IVIFN-based rules is applied to determine the risk level of the manufacturing process. This approach is based on the property of symmetry in the decision-making process, ensuring that criteria are treated in a balanced manner and inference rules are applied consistently. A case study based on real-life data demonstrates that the obtained results identify measures that can enhance business strategy and reduce failure rates. Thus, the model is validated and shown to contribute to lean waste reduction. It can be concluded that the proposed methodology provides clear and practical guidance to enterprise management, as well as to all sectors and individuals involved in ensuring a reliable manufacturing process, for defining failure priorities and implementing preventive measures. Full article

The specificity of the business of agro-food companies is that their products have little or no impact on the environment. However, environmental pollution of these products is caused by the use of packaging. Therefore, it is necessary to apply the principles of the circular economy in the business of companies. Applying green packaging that has little or no impact on the environment helps in preserving the environment. Companies usually purchase packaging from suppliers and therefore, it is necessary to choose the right supplier from which to purchase green packaging to support the implementation of the circular economy. The aim of this research is to select a green packaging supplier for company X in order to influence the development of a circular economy in the company’s business. Based on this, the following research question is considered in this paper: how can the selection of a green packaging supplier influence the implementation of a circular economy at company X? The research covers ten criteria used in this selection, with which eight suppliers were observed. Because every decision-making process in the economy is characterized by risk and insecurity that affects the uncertainty in decision-making, an intuitionistic fuzzy set (IFS) was used. Determining the importance of weights was performed directly based on the ratings of the decision-maker (DM) and the steps of the SiWeC (Simple Weight Calculation) method, as well as using the Entropy method. The compromise results of these methods showed that the most important criteria for assessing the life cycle of packaging are transparency and ethics in business. The ranking of suppliers was carried out using the TOPSIS (Technique for Order of Preference by Similarity to Ideal Solution) method and its results showed that supplier 5 is the first choice for establishing long-term cooperation in the procurement of green packaging. Full article

Trapezoidal-valued intuitionistic fuzzy numbers (TrVIFNs) are the real generalizations of intuitionistic fuzzy numbers, interval-valued intuitionistic fuzzy numbers, and triangular intuitionistic fuzzy numbers, which effectively model real-life problems that consist of imprecise and incomplete data. This study incorporates the Aczel-Alsina aggregation operators (which consist of parameter-based flexibility) for solving any group of decision-making problems modeled in a trapezoidal-valued intuitionistic fuzzy (TrVIF) environment. In this study, we first define new operations on TrVIFNs based on the Aczel-Alsina operations. Secondly, we introduce new trapezoidal-valued intuitionistic fuzzy aggregation operators, such as the TrVIF Aczel-Alsina weighted averaging operator, the TrVIF Aczel-Alsina ordered weighted averaging operator, and the TrVIF Aczel-Alsina hybrid averaging operator, and we discuss their fundamental mathematical properties by examining various theorems. This study also includes a new algorithm named ‘three-stage multi-criteria group decision-making’, where we obtain the criteria weights using the newly proposed TrVIF-MEREC method. Additionally, we introduce a new modified algorithm called TrVIF-WASPAS to solve the multi-criteria decision-making (MCDM) problem in the trapezoidal-valued intuitionistic fuzzy environment. Then, we apply this proposed method to solve a model case study problem involving location selection for a wind power plant project. Then, we discuss the proposed algorithm’s sensitivity analysis by changing the criteria weights concerning different parameter values. Finally, we compare our proposed methods with various existing methods, like some subclasses of TrVIFNs such as IVIFWA, IVIFWG, IVIFEWA, and IVIFEWG, and also with some MCGDM methods of TrVIFNs, such as the Dombi aggregation operator-based method in TrVIFNs and the TrVIF-Topsis method-based MCGDM, to show the efficacy of our proposed algorithm. This study has many advantages, as it consists of a total ordering principle in ranking alternatives in the newly proposed TrVIF-MCGDM techniques and TrVIF-WASPAS MCDM techniques for the first time in the literature. Full article

The theoretical reliability of complex equipment often significantly deviates from real-world performance due to the inherent influence of diverse environmental and operational factors, making scientific reliability evaluation particularly challenging. This study proposes a multi-attribute group decision-making (MAGDM) evaluation framework based on a strict intuitionistic fuzzy distance and an improved TOPSIS approach. First, an improved strict intuitionistic fuzzy distance measure (ISIFDisM) is rigorously developed to overcome the limitations of existing methods, exhibiting high robustness, monotonicity, and discriminability. Second, building upon ISIFDisM, a systematic MAGDM evaluation model is constructed, comprising three key steps: (1) data acquisition through structured questionnaire surveys; (2) attribute weights determined using the entropy weight method; and (3) alternative ranking through normalized priority coefficients derived from intuitionistic fuzzy distance calculations. Third, the proposed framework is applied to a practical case study focused on reliability assessment of ship equipment, enabling effective ranking of various marine engines. Finally, through static comparative analyses and dynamic scenario simulations, the feasibility, robustness, and methodological superiority of the proposed framework are thoroughly validated. Full article

For interval-valued intuitionistic fuzzy sets featuring complementary symmetry in evaluation relations, this paper proposes a novel, complete fuzzy multi-attribute group decision-making (MAGDM) method that optimizes both expert weights and attribute weights. First, an optimization model is constructed to determine expert weights by minimizing the cumulative difference between individual evaluations and the overall consistent evaluations derived from all experts. Second, based on the Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS), the improved closeness index for evaluating each alternative is obtained. Finally, leveraging entropy theory, a concise and interpretable optimization model is established to determine the attribute weight. This weight is then incorporated into the closeness index to enable the ranking of alternatives. Integrating these features, the complete fuzzy MAGDM algorithm is formulated, effectively combining the strengths of subjective and objective weighting approaches. To conclude, the feasibility and effectiveness of the proposed method are thoroughly verified and compared through detailed examination of two real-world cases. Full article