Building smarter digital content: a CRITIC – DEMATEL framework for leveraging large language model optimization in marketing

With the growing of environmental issues, manufacturing companies are compelled to improve their performance to reduce resource consumption and environmental pollution. Accordingly, company's performance should be measured according to the green manufacturing indicators. The importance of the indicators must be determined properly aligned with the company's goals and profiles. This study aims to determine the weight of green manufacturing indicators which becomes the critical input for green performance evaluation. Different weighting methods including entropy and CRiteria Importance Through Inter-criteria Correlation (CRITIC), are integrated using Decision-Making Trial and Evaluation Laboratory (DEA) to determine the final weight. A case study of the Indonesian manufacturing company is presented to illustrate the application of the proposed method. The result indicates that process technology, compliance of environmental quality standards, and operational standards are considered critical in green manufacturing.

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.

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.

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

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

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

Decision making trial and evaluation laboratory (DEMATEL) is considered as an effective method for the identification of cause-effect chain components of a complex system. It deals with evaluating interdependent relationships among factors and finding the critical ones through a visual structural model. Over the recent decade, a large number of studies have been done on the application of DEMATEL and many different variants have been put forward in the literature. The objective of this study is to review systematically the methodologies and applications of the DEMATEL technique. We reviewed a total of 346 papers published from 2006 to 2016 in the international journals. According to the approaches used, these publications are grouped into five categories: classical DEMATEL, fuzzy DEMATEL, grey DEMATEL, analytical network process- (ANP-) DEMATEL, and other DEMATEL. All papers with respect to each category are summarized and analyzed, pointing out their implementing procedures, real applications, and crucial findings. This systematic and comprehensive review holds valuable insights for researchers and practitioners into using the DEMATEL in terms of indicating current research trends and potential directions for further research.

Purpose: This study evaluates the ecological footprint of Artificial Intelligence (AI)-driven healthcare solutions using Grey Relational Analysis (GRA), focusing on energy consumption, carbon emissions, electronic waste (e-waste), and natural resource depletion.Study design/methodology/approach: A multi-criteria decision-making approach integrating the Fuzzy Best Worst Method (FBWM) and the Decision-Making Trial and Evaluation Laboratory (DEMATEL) was employed to assess and prioritize the key environmental factors.Sample and data: Data for FBWM and DEMATEL were systematically collected from a panel of experts. These professionals, with extensive experience in the field, provided critical input on the relative importance of criteria and their interdependencies.Results: The findings highlight that electronic waste, natural resource depletion, and energy consumption are the most significant environmental concerns. At the same time, inefficiencies in AI training and carbon footprint emerge as key causal factors. Addressing these upstream drivers can significantly reduce AI’s overall environmental burden in healthcare.Originality/value: This research provides valuable insights for policymakers and healthcare institutions advocating sustainable AI adoption strategies that balance technological advancement with ecological responsibility.Research limitations/implications: AI development in healthcare requires a shift towards energy-efficient computing, optimized AI training methodologies, and responsible e-waste management. Healthcare institutions, policymakers, and AI developers must collaborate to ensure that medical AI innovations are both technologically transformative and environmentally responsible. Adopting green AI practices—such as hardware recycling, federated learning, and energy-efficient model deployment—is crucial to achieving long-term sustainability in AI-powered healthcare.

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

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.

The power transformer is one of the most critical facilities in the power system, and its running status directly impacts the power system's security. It is essential to research the risk priority evaluation of the power transformer parts. Failure mode and effects analysis (FMEA) is a methodology for analyzing the potential failure modes (FMs) within a system in various industrial devices. This study puts forward a hybrid FMEA framework integrating novel hesitant fuzzy aggregation tools and CRITIC (Criteria Importance Through Inter-criteria Correlation) method. In this framework, the hesitant fuzzy sets (HFSs) are used to depict the uncertainty in risk evaluation. Then, an improved HFWA (hesitant fuzzy weighted averaging) operator is adopted to fuse risk evaluation for FMEA experts. This aggregation manner can consider different lengths of HFSs and the support degrees among the FMEA experts. Next, the novel HFWGA (hesitant fuzzy weighted geometric averaging) operator with CRITIC weights is developed to determine the risk priority of each FM. This method can satisfy the multiplicative characteristic of the RPN (risk priority number) method of the conventional FMEA model and reflect the correlations between risk indicators. Finally, a real example of the risk priority evaluation of power transformer parts is given to show the applicability and feasibility of the proposed hybrid FMEA framework. Comparison and sensitivity studies are also offered to verify the effectiveness of the improved risk assessment approach.

Investigation of flow behaviour in the nozzle of a Pelton wheel: Effects and analysis of influencing parameters

Parametric optimization and sensitivity analysis of the integrated Taguchi-CRITIC-EDAS method to enhance the surface quality and tensile test behavior of 3D printed PLA and ABS parts.