FUZZY DECISION MAKING METHOD BASED ON COCOSO WITH CRITIC FOR FINANCIAL RISK EVALUATION

To prevent the opportunities and challenges brought by unexpected economic situations, each enterprise must identify the sources of financial risk and establish an early warning mechanism for financial risk. In view of the shortcomings of traditional financial risk source identification, this paper adopts the CRITIC (Criteria Importance Through Inter-criteria Correlation) method to achieve objective weighting of indicators and calculate the enterprise risk value. MLP (Multilayer Perceptron) is used to quantitatively analyze the relationship between indicator data samples and risk values to establish a financial risk evaluation model. In this paper, macroeconomic risk indicators and business environmental risk indicators are used as the two main categories, and 12 indicators are selected as evaluation factors to apply the model to a wider range of corporate financial risk assessments. The results show that: this training model is more robust, with an error of only 8.86%. Among them, the loan interest rate (0.121) and total operating income (0.086) have a greater impact on corporate financial risks, and companies need to establish a complete financial risk early warning system based on the assessment results.

The financing cost of Supply Chain Management (S CM) is decreased by the emergence of supply chain finance. There is a deficiency in risk in terms of strategy and practice due to the growth of a diversified supply chain financial area. Numerous automated risk assessment frameworks are developed using deep learning and machine learning techniques in recent years to address these issues. Hence, industries are faced with the supply chain sustainability risk that is emerged from various resources. In existing research works, the field of supply chain finance is very limited due to the lack of integration. However, it does not address the small and medium sized enterprise which is used in the real time economy. The purpose of this survey is to conduct a literature review on estimating the financial risks associated with SCMs. This study includes various literature works considered for the financial risk evaluation, where the evaluation of deep learning techniques, performance analysis and their challenges while performing the financial risk evaluation are researched. However, the conventional techniques are presented with diverse challenges in estimating financial risks, and this review paper is highly useful for future research work. This research analyzes the estimation techniques, dataset utilized for evaluating the financial risks, implementation tools and performance metrics involved in the evaluation models. Moreover, various research gaps in the existing research works are explored which helps to show the enhanced performance of the supply chain financial risk evaluation model. Here, it explores various financial risk analyses which will be helpful for future research. Finally, the overall challenges and future works on the financial risk evaluation models are discussed to support future works.

The rare earth industry is a crucial strategic industry that is related to the national economy and national security. In the context of economic globalization, international competition is becoming increasingly fierce, and the rare earth industry is facing a more severe survival and development environment than ever before. Although China is the greatest world’s rare earth country in rare earth reserves, production, consumption and export volume, it is not a rare earth power. The rare earth industry has no right to speak in the international market. The comparative advantage is weakening and the security of rare earth industry appears. Therefore, studying the rare earth industry security has important theoretical and practical significance. When measuring the China’s rare earth industry security, the primary problem involves tremendous uncertainty. Neutrosophic soft set (NSS), depicted by the parameterized form of truth membership, falsity membership and indeterminacy membership, is a more serviceable pattern for capturing uncertainty. In this paper, five dimensions of rare earth industry security are identified and then prioritized against twelve different criteria relevant to structure, organization, layout, policy and ecological aspects of industry security. Then, the objective weight is computed by CRITIC (Criteria Importance Through Inter-criteria Correlation) method while the integrated weight is determined by concurrently revealing subjective weight and objective weight. Later, neutrosophic soft decision making method based CoCoSo (Combined Compromise Solution) is explored for settling the issue of low discrimination. Lastly, the feasibility and validity of the developed algorithm is verified by the issue of China’s rare earth industry security evaluation.

Purpose The study responds to address the practical problem faced by the digital marketers, content creators and digital business agencies on creating content, which is both human-readable and LLM-compatible. The present study identifies and analyses the key factors influencing content optimization for Large Language Models (LLMs) to develop a strategic framework for Large Language Model Optimization (LLMO) that aligns with modern search paradigms. Design/methodology/approach This research employs a two-phases multi-criteria decision-making (MCDM) approach combining CRITIC (Criteria Importance Through Intercriteria Correlation) to determine factor weights, and DEMATEL (Decision-Making Trial and Evaluation Laboratory) to map causal relationships. A panel of 15 experts across three countries (India, UAE and USA) rated the influence of five identified factors. Findings The study identifies five critical factors for LLMO: Retrieval Augmentation, Readability Enhancement, Content Quality Assurance, Filtering of Unsafe Content and User-Centric Content Design. Retrieval Augmentation and User-Centric Design emerged as key causal factors, while Readability and Content Quality acted as bridges or effects. Although factor weights were relatively balanced, the DEMATEL analysis revealed interdependencies highlighting the dynamic nature of LLMO. Practical implications The results provide actionable guidance to digital marketing experts and agencies, content strategists, marketing heads and developers to structure web content that is both human-readable and LLM-compatible. The study offers insights to organizations on how they can enhance their digital visibility and authority in AI-powered search ecosystems. Originality/value This study fills a critical gap by offering the first integrated CRITIC-DEMATEL framework for LLMO. It distinguishes LLMO from traditional SEO and offers a novel causal model to support the development of holistic, future-ready content strategies.

With the deepening of economic globalization, Chinas economy and the global economy are becoming increasingly interdependent and closely linked, resulting in a more complex environment for domestic enterprises and heightened financial risks. To enhance the risk resilience of enterprises, the research methods for assessing financial risks are becoming more diverse. Traditional financial risk analysis methods, such as the single-argument model, have certain limitations in the practical application of enterprise financial risk evaluation. These methods cannot overcome the restrictions of time, region, and industry, and their application value is not fully realized. To better assist enterprises in addressing the complexities of financial risks, fuzzy hierarchical analysis is applied to the traditional hierarchical analysis method under fuzzy optimization conditions. This method focuses on indices of measurable comparability, facilitating a more reasonable and objective financial risk evaluation of enterprises, especially when comparing different companies in the new energy vehicle industry and conducting a longitudinal comparison of Company A. Fuzzy hierarchical analysis integrates qualitative judgment with quantitative analysis, using triangular fuzzy numbers to generate a judgment matrix. The results are transformed into an objective fuzzy set, enabling the quantification and structuring of complex system indicators and improving the rationality and accuracy of the enterprises financial risk evaluation.

This study aims to improve the productivity and flexibility of the mushroom house to increase the production of straw mushrooms. Determining the design of technical specifications and material requirements of the mushroom house is a process that is quite important in determining the success or failure of increasing straw mushroom production. QFD (Quality Function Deployment) is used to obtain the best design based on the needs of the mushroom farmers. The needs of the mushroom farmers are then translated through QFD into technical specifications. MCDM (Multi Criteria Decision Making) is used to determine the material for the frame and blanket of the mushroom house according to the technical specifications of the QFD. CRITIC (Criteria Importance Through Intercriteria Correlation) is one of the methods of MCDM that performs an objective weighting of the criteria. A mushroom house was built based on the technical and material specifications obtained from QFD and CRITIC. Tests were carried out by comparing the productivity and flexibility between traditional mushroom houses and designed mushroom houses. The peroductivity of the mushroom house includes cleanliness, stability in temperature and humidity, the rate of growth of straw mushrooms in media. Flexibility includes the ability to assembled and disassembled, easily mobilize from one place to another.

Multi-criteria decision-based hybrid energy selection system using CRITIC weighted CODAS approach

A hybrid MCDM framework for assessing urban competitiveness: A case study of European cities

The problem of decision-making regarding the selection of the optimal composition of telecommunication network components is very urgent. The subject of the research in the article is a multi-criteria approach to the selection of telecommunication network components. This approach is related to the evaluation of possible options based on a set of indicators. The set of such indicators is determined by the specifics of a telecommunication network. One of the most dominant devices in telecommunication (mobile) systems is speech codecs. When choosing the appropriate codec configuration, there is a need to make a decision considering a set of contradicting criteria. The use of MCDM (Multiple Criteria Decision Making) methods when making decisions is a promising approach to solving such problems. The current article increases the efficiency of the multi-criteria approach to decision-making in the process of selecting telecommunication network components, in particular, a speech codec. The following methods were used: MARCOS (Measurement Alternatives and Ranking according to COmpromise Solution), entropy, CRITIC (Criteria Importance Through Inter-criteria Correlation) and BWM (Best–Worst method). The following results were obtained. Determining the weight of the criteria by which alternatives are evaluated is one of the key problems that arise when making multi-criteria decisions. Objective methods of entropy, CRITIC, and subjective BWM methods were used to find weighting factors of criteria. Different methods of determining the weights of the criteria give different values. The use of the combined BWM-CRITIC method is proposed, which balances the subjective opinions of experts and assessments made solely based on the decision matrix data. The values of the correlation coefficients showed a close relationship between the weights of the criteria determined by different methods. However, the strongest connection with other methods was shown by the combined BWM-CRITIC method. The MARCOS method was used to rank the alternatives and select the best alternative. A ranking of the set of speech codecs is obtained, which allows for determining the best alternative Conclusion. A comprehensive approach to the telecommunication network component selection is proposed, namely the multi-criteria BWM-CRITIC-MARCOS model, based on a combination of MCDM methods. The integration of methods into the proposed model provides a systematic approach to the assessment and selection of telecommunication network components.

Bu çalışmada Türk sigorta sektöründe hayat/emeklilik branşında faaliyette bulunan sigorta şirketlerinin performanslarının çok kriterli karar verme (ÇKKV) tekniklerinden CRITIC (CRiteria Importance Through Intercriteria Correlation) ve TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) yöntemleri kullanılarak ölçülmesi amaçlanmıştır. Bu kapsamda Türk sigorta sektöründe faaliyet gösteren 18 hayat sigorta şirketinin 2010 – 2020 yılları arasındaki verileri ele alınmıştır. Analiz kapsamında CRITIC – TOPSIS bütünleşik modeli için Kısa Vadeli Borçlar/ Toplam Aktifler, Dönem Net Karı/ Toplam Aktifler, Cari Varlıklar / Kısa Vadeli Borçlar, Faaliyet Giderleri / Toplam Varlıklar, Gerçekleşen Hasar / Kazanılmış Prim (Net), Toplam Özkaynaklar / Toplam Aktifler, Vergi Öncesi Kar /Alınan Primler (Brüt), Net Kar / Toplam Özsermaye, Alınan Primler (Net) / Alınan Primler (Brüt) ve Teknik Kar-Zarar / Alınan Primler kriterleri seçilmiştir. Çalışmada seçilen kriterlerin öncelik ağırlıkları CRITIC yöntemi ile tespit edildikten sonra TOPSIS yöntemi ile sigorta şirketleri performans bakımından sıralanmıştır. Çalışma sonucunda ele alınan yıllar itibarıyla hayat sigorta şirketlerinin performanslarının belirlenmesinde en önemli kriterin Kısa Vadeli Borçlar/Toplam Aktifler olduğu tespit edilmiştir. Çalışma sonucunda ele alınan yıllar itibarıyla hayat sigorta şirketlerinin performanslarının belirlenmesinde en önemli kriterin Kısa Vadeli Borçlar/Toplam Aktifler olduğu tespit edilmiştir. Ayrıca Halk Hayat ve Emeklilik A.Ş. ile Ziraat Hayat ve Emeklilik A.Ş.’nin ele alınan yıllarda performans sıralamasında ilk sıralarda yer aldığı BNP Paribas Cardif Hayat A.Ş.’nin analize dahil edilen tüm yıllarda performans sıralamasında son sıralarda olduğu tespit edilmiştir.

It is important to perform to find the most appropriate normalization procedure in MCDM methods. Normalization procedures proposed in the literature have tended to focus on cost and benefit type criteria. Some of the criteria discussed in MCDM problems may be required not to exceed a certain lower bound or upper bound, while others may be required to meet a certain target value. However, some criteria require target and boundary values-based normalizations, and these types of procedures receive much less attention despite their importance in many decision-making problems such as workers’ physical workload evaluation. Criteria affecting physical workload require target and boundary values-based normalizations because these normalization procedures best match the properties of human physiological capacities. In this context, this study proposes new normalization procedures based on target and boundary values. These new normalizations are applied in Criteria Importance through Inter-criteria Correlation (CRITIC), Preference Selection Index (PSI) to obtain criteria weights and Combined Compromise Solution (CoCoSo) method to prioritize workers for their physical workload levels. Additionally, a sensitivity analysis was performed to interpret the ranking differences for CRITIC-CoCoSo and PSI-CoCoSo integrations based on proposed normalization procedures.

Toward improved siting of wind–solar hybrid farms: A novel framework integrating multi-criteria decision making, machine learning–driven feature selection, and spatial clustering

The growth of medical tourism has contributed to the expansion of dental tourism. With the rise of tourism in Albania, dental tourism has similarly progressed. This research aims to evaluate the quality of dental tourism services in Tirana, applying fuzzy methods such as CRITIC (CRiteria Importance Through Intercriteria Correlation) and CoCoSo (Combined Compromise Solution). These two methods were integrated into a hybrid approach, as described in this paper. Seven experts evaluated dental practices using linguistic values. The CRITIC method results indicated that, among the ten criteria, the most significant was the variety of services. According to the CoCoSo method, Biodent Denti e Sorrisi, Diamond Dental, and Dental Med Austria practices demonstrated the highest quality in dental tourism services. As research results indicate, these clinics could serve as models for improving dental tourism in Albania through a focus on quality development.

An integrated AHP-CRITIC framework for scenario-driven comprehensive evaluation of PPRL technology

There has been a paradigm shift in the automobile industry due to e-mobility which reduces green-house gas emission and air pollution. In this context, selection of the most feasible automotive passenger vehicle is a complex decision-making problem due to the use of different power source, technology, specification and price. In this paper, five alternative vehicles based on fuel cell, hybrid electric, battery electric, plug in hybrid electric and compressed natural gas bi-fuel are evaluated using an integrated criteria importance through inter-criteria correlation (CRITIC) - Combined Compromise Solution (CoCoSo) method. CRITIC method is used to obtain the weights of the vehicle selection criteria, whereas, CoCoSo method is employed to rank the vehicles considering different technical and operational criteria such as greenhouse gas emission, fuel economy, vehicle range, accelerating time, annual fuel cost and vehicle base model cost. It is found that battery electric vehicle out performs all other considered alternatives. The validity of the results is verified by comparing with other well popular MCDM methods. Further, a sensitivity analysis is conducted by changing the criteria weights to establish the stability of the model.