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

Evaluation of sustainable development and utilization-oriented renewable energy systems based on CRITIC-SWARA-CODAS method using interval valued picture fuzzy sets

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.

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.

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.

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

The aim of this study is to determine the human capital performance of Latin American Countries and Türkiye using the CRITIC (Criteria Importance Through Intercriteria Correlation) and ARAS (Additive Ratio Assessment) techniques. In the analysis, CRITIC-based ARAS method has been used. This method is a combination two methods. The CRITIC method has provided the objective weights of the criteria, and human capital performances and ranking of the countries are obtained by ARAS method. In order to evaluate the human capital stock of the countries the following criteria are utilized: the infant mortality rate (per 1,000 live births), unemployment rate (percentage of the total labor force), average life expectancy at birth, total (years), labor force participation rate (percentage of the total population aged 15-64), current health expenditure (percentage of GDP), internet users (percentage of the total population), and population aged 15-64 (percentage of the total population). The analysis covers the years of 2019, 2020 and 2021. According to the CRITIC method results, the infant mortality rate has been the least significant criterion for every year under study, whereas the unemployment rate is the most significant. The ARAS method suggests that in every year examined, Cuba has done the best in terms of human capital. Chile and Uruguay rank second and third, respectively, after Cuba. Throughout the years under study, Guinea has performed the worst, followed by Haiti. Venezuela in 2021 and Honduras in 2019 and 2020 rank third-worst. Among the 22 nations, Türkiye ranks 15th in 2019, 12th in 2020, and 13th in 2021.

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 financial risk evaluation is critically vital for enterprises to identify the potential financial risks, provide decision basis for financial risk management, and prevent and reduce risk losses. In the case of considering financial risk assessment, the basic problems that arise are related to strong fuzziness, ambiguity and inaccuracy. q-rung orthopair fuzzy set (q-ROFS), portrayed by the degrees of membership and non-membership, is a more resultful tool to seize fuzziness. In this article, the novel q-rung orthopair fuzzy score function is given for dealing the comparison problem. Later, the and operations are explored and their interesting properties are discussed. Then, the objective weights are calculated by CRITIC (Criteria Importance Through Inter-criteria Correlation). Moreover, we present combined weights that reflects both subjective preference and objective preference. In addition, the q-rung orthopair fuzzy MCDM (multi-criteria decision making) algorithm based on CoCoSo (Combined Compromise Solution) is presented. Finally, the feasibility of algorithm is stated by a financial risk evaluation example with corresponding sensitivity analysis. The salient features of the proposed algorithm are that they have no counter-intuitive case and have a stronger capacity in differentiating the best alternative.

Third-party logistics (3PL) is becoming more and more popular because of globalization, e-commerce development, and increasing customer demand. More and more companies are trying to move away from their own account transportation to third-party accounts. One reason for using 3PLs is that the company can focus more on its core activities, while the 3PL service provider can provide distribution activities in a more professional way, save costs and time, and increase the level of customer satisfaction. An emerging issue for companies in the logistics industry is how they can decide on the 3PL evaluation and selection process for outsourcing activities. For the first time, the entropy and the criteria importance through intercriteria correlation (CRITIC) methods were coupled in order to obtain hybrid criteria weights that are of huge importance to decide on the 3PL provider evaluation and selection process. The obtained criteria weights were further utilized within the additive ratio assessment (ARAS) method to rank the alternatives from the best to the worst. The introduced hybrid–ARAS approach can be highly beneficial, since combining two methods gives more robust solutions on one hand, while on the other hand eliminating subjectivity. Comparative and sensitivity analyses showed the high reliability of the proposed hybrid–ARAS method. A hypothetical case study is presented to illustrate the potentials and applicability of the hybrid–ARAS method. The results showed that 3PL-2 was the best possible solution for our case.

Enhancing risk factor evaluation for infectious diseases using decision-making approach based on linear programming

Measurement of road safety situation by CRITIC-TODIM-NMF: A lesson system of legislation and regulation for the United States

Purpose: This study aims to evaluate and identify the most suitable logistics service providers within the framework of Logistics 4.0, shaped by digital transformation and Industry 4.0 technologies. Logistics 4.0 seeks to optimize logistics processes using innovative technologies such as smart systems and big data analytics. In this context, selecting the right service provider is of strategic importance for businesses. This study intends to assist companies in making accurate decisions in this complex process. Method: The CRITIC (Criteria Importance Through Intercriteria Correlation) based WASPAS (Weighted Aggregated Sum Product Assessment) method was employed. The CRITIC method was used to determine the objective weights of the criteria, while the WASPAS method utilized these weights to calculate the overall performance scores of the alternatives. Findings: The results of the study reveal the key criteria that businesses should consider when selecting Logistics 4.0 service providers and identifying the top-performing service providers. Originality: This study highlights the advantages and effectiveness of using the combined CRITIC and WASPAS methods in the selection of service providers in the logistics sector. Additionally, it contributes to the literature on the selection of Logistics 4.0 service providers.

Choosing sites for solar photovoltaic (PV) power plants in developing countries like India is a crucial task while considering multiple conflicting factors and sub-factors simultaneously. Multi-criteria decision-making (MCDM) is an optimisation method that provides a framework for handling such situations in an intuitionistic fuzzy environment. The complexity and uncertainty associated with the site selection model are dealt with professionally. The Criteria Importance Through Intercriteria Correlation (CRITIC) method is applied to determine the relative importance of the criteria, identifying airflow speed as the most influential factor, followed by humidity ratio, level of dust haze, availability of labour and resources, and ecological effects. This shows that airflow speed plays an important role in the power plant’s efficiency and performance. The Vlse Kriterijumska Optimizacija I Kompromisno Rešenje (VIKOR) method is then used to prioritise the alternatives as potential locations for setting up a solar PV power plant in India. A new de-i-fuzzification method based on the relative difference between two real numbers is also proposed. Sensitivity analyses and comparative studies are conducted to assess the robustness and effectiveness of the framework. Overall, the results demonstrate that the proposed framework is useful and effective for optimising site selection for solar power plants in India.

Transportation of petroleum-based products is a complex and hazardous logistics process. Selecting the appropriate transportation vehicles for this process is crucial for ensuring safety and efficiency. Therefore, prioritizing selection criteria and choosing the most suitable fuel tanker is essential in reducing potential risks and improving overall fleet operations. Given the many types of tankers available for petroleum product transportation, decision-makers should employ a multi-criteria decision-making (MCDM) approach to identify the best option for their specific needs. This study introduces a novel MCDM approach that combines the Weighted Aggregated Sum Product Assessment (WASPAS) and the Criteria Importance through Intercriteria Correlation (CRITIC) in a Fermatean fuzzy (FF) environment, addressing five main criteria and evaluating five fuel tanker alternatives. Using this approach, the research identified and prioritized key criteria for selecting an appropriate tanker model by providing insights into 24 sub-criteria. The results reveal that tanker price emerges as the most important sub-criterion, leading us to determine the M3 tanker model as the most suitable fuel tanker after carefully evaluating all 24 different sub-criteria. The findings can significantly assist petroleum firms in making informed decisions when choosing fuel tankers by considering various technical, operational, comfort, environmental, and economic factors. The results can also be used to inform policy on fuel distribution.