A New Model for Stock Management in Order to Rationalize Costs: ABC-FUCOM-Interval Rough CoCoSo Model

Naeini A., Mosayebi A., Mohajerani N.

Karabašević D., Popović G., Stanujkić D., Maksimović M., Sava C.

Yazdani M., Zarate P., Kazimieras Zavadskas E., Turskis Z.

PurposeThe purpose of this paper is to discuss the advantage of a combinatory methodology presented in this study. The paper suggests that the comparison with results of previously developed methods is in high agreement.Design/methodology/approachThis paper introduces a combined compromise decision-making algorithm with the aid of some aggregation strategies. The authors have considered a distance measure, which originates from grey relational coefficient and targets to enhance the flexibility of the results. Hence, the weight of the alternatives is placed in the decision-making process with three equations. In the final stage, an aggregated multiplication rule is employed to release the ranking of the alternatives and end the decision process.FindingsThe authors described a real case of choosing logistics and transportation companies in France from a supply chain project. Some comparisons such as sensitivity analysis approach and comparing to other studies and methods provided to validate the performance of the proposed algorithm.Originality/valueThe algorithm has a unique structure among MCDM methods which is presented for the first time in this paper.

Hanafi R., Mardin F., Asmal S., Setiawan I., Wijaya S.

Abstract SSM is a large training unit, which focuses on selling the spare parts for the vehicle. Their current problems were the unwell-organized warehouse layout and the lack of distance of the shelves causing the warehouseman facing the difficultness in terms of inventorying the goods management. The overstocked supply usually occurs at the end of the year because of oversupply. This study used the ABC classification method for the rearrangement of their facility layout based on the demand. As a result, brake pad, outer tire, and engine oil, which were classified in A group (fast-moving), must be relocated closer to the access gate. By this arrangement, it could minimize the movement of the personnel up to 133,318.55 m annually. Moreover, using the Economic Order Quantity (EOQ) method, the order period, safety stock, and Re-Order Point (ROP) could be optimized, and the total supply would minimize cost.

Stević Ž., Durmić E., Gajić M., Pamučar D., Puška A.

Sustainability in a supply chain is a demand on the one hand and a challenge on the other. It is necessary to balance between these dimensions in order to fulfill the purpose of the supply chain. Therefore, in the first phase—i.e., in procurement—it is necessary to take into account its sustainability. In this paper, a sustainable supplier was selected respecting all three aspects of sustainability. The evaluation was carried out on the basis of a total of 21 criteria arranged into two levels and three groups. A new Interval Rough SAW (simple additive weighting) method, which represents a contribution to the treatment of problems belonging to the multi-criteria decision-making (MCDM), was developed. The integration of interval rough numbers with the SAW method was completed. In addition, the full consistency method (FUCOM) was applied to determine the weights of the criteria. The integrated FUCOM-Interval Rough SAW model enables treatment of multi-criteria problems while reducing subjectivity to the lowest possible level and eliminating uncertainties and ambiguities. The results obtained were determined throughout a sensitivity analysis consisting of a change in the weight of the criteria and the influence of dynamic matrices on the change in ranks. In addition, Spearman’s rank correlation coefficient (SCC) was calculated to confirm the stability of the previously obtained results.

Puška A., Stojanović I., Maksimović A.

Durmić E.

Božanić D., Tešić D., Kočić J.

Fazlollahtabar H., Smailbašić A., Stević Ž.

Pamučar D., Sremac S., Stević Ž., Ćirović G., Tomić D.

Successfully organizing the transport of hazardous materials and handling them correctly is a very important logistical task that affects both the overall flow of transport and the environment. Safety advisors for the transport of hazardous materials have a very important role to play in the proper and safe development of the transport flow for these materials; their task is primarily to use their knowledge and effort to prevent potential accidents from happening. In this research, a total of 21 safety advisors for the transport of hazardous materials in Serbia are assessed using a new model that integrates Linguistic Neutrosophic Numbers (LNN) and the WASPAS (Weighted Aggregated Sum Product Assessment) method. In this way, two important contributions are made, namely a completely new methodology for assessing the work of advisors and the new LNN WASPAS model, which enriches the field of multi-criteria decision making. The advisors are assessed by seven experts on the basis of nine criteria. After performing a sensitivity analysis on the results, validation of the model is carried out. The results obtained by the LNN WASPAS model are validated by comparing them with the results obtained by LNN extensions of the TOPSIS (Technique for Order Performance by Similarity to Ideal Solution), LNN CODAS (COmbinative Distance-based ASsessment), LNN VIKOR (Multi-criteria Optimization and Compromise Solution) and LNN MABAC (Multi-Attributive Border Approximation area Comparison) models. The LNN CODAS, LNN VIKOR and LNN MABAC are also further developed in this study, which is an additional contribution made by the paper. After the sensitivity analysis, the SCC (Spearman Correlation Coefficient) is calculated which confirms the stability of the previously obtained results.

Pamucar D., Chatterjee K., Zavadskas E.K.

Third-party logistics (3PL) has involved a significant response among researchers and practitioners in the recent decade. In the global competitive scenario, multinational companies (MNCs) not only improve quality of service and increase efficiency, but also decrease costs by means of 3PL. However, the assessment and selection of 3PL is a very critical decision, comprising intricacy due to the existence of various imprecisely based criteria. Also, uncertainty is an unavoidable part of the information in the decision-making process and its importance in the selection process is relatively high and needs to be carefully considered. Consequently, incomplete and inadequate data or information may occur among other various selection criteria, which can be termed as a multi-criteria decision-making (MCDM) problem. Interval rough numbers are very flexible to model this type of uncertainty occurring in MCDM problems. Thus this paper presents a new integrated interval rough number (IRN) approach based on the Best Worst Method (BWM) and Weighted Aggregated Sum Product Assessment (WASPAS) method along Multi-Attributive Border Approximation area Comparison (MABAC) to evaluate 3PL providers. The hybrid IRN-BWM based methodology is used for computing the priority weights of criteria while IRN-WASPAS and IRN-MABAC are employed to achieve the final ranking of 3PL providers. A computational study is performed to illustrate the proposed approaches along with a sensitivity analysis on different sets of criteria weight coefficient values to validate the stability of the suggested methodology. Consequently, a comparative analysis of the obtained ranking results with their crisp and fuzzy counterparts is also conducted for checking the reliability of the proposed approach. The results display stability in ranking of alternative results and prove the feasibility of the proposed approach to handle MCDM problems with IRNs.

Emeç Ş., Akkaya G.

Purpose The purpose of this paper is to develop a stochastic multi-criteria decision-making approach to solute the warehouse location problem in the stochastic environment which contains uncertain condition. Design/methodology/approach In developed approach, the weight of criteria was calculated by using the stochastic analytic hierarchy process (SAHP) method. Alternative ranking was made and evaluated by fuzzy VIKOR (VlseKriterijumska Optimizacija I Kompromisno Resenje). Findings This study dealt with warehouse location selection problem of a supermarket that has sellers in many regions in Turkey and selected proper warehouse. Originality/value This study combined SAHP and fuzzy VIKOR methods as a solution approach for warehouse location selection problems.

Stojčić M., Pamučar D., Mahmutagić E., Stević Ž.

Queuing systems (QS) represent everyday life in all business and economic systems. On the one hand, and there is a tendency for their time and cost optimization, but on the other hand, they have not been sufficiently explored. This especially applies to logistics systems, where a large number of transportation and storage units appear. Therefore, the aim of this paper is to develop an ANFIS (Adaptive neuro-fuzzy inference system) model in a warehouse system with two servers for defining QS optimization parameters. The research was conducted in a company for the manufacturing of brown paper located in the territory of Bosnia and Herzegovina, which represents a significant share of the total export production of the country. In this paper, the optimization criterion is the time spent in the system, which is important both from the aspect of all customers of the system, and from that of the owner of the company. The time criterion directly affects the efficiency of the system, but also the overall costs that this system causes. The developed ANFIS model was compared with a mathematical model through a sensitivity analysis. The mathematical model showed outstanding results, which justifies its development and application.

Pamučar D., Stević Ž., Sremac S.

In this paper, a new multi-criteria problem solving method—the Full Consistency Method (FUCOM)—is proposed. The model implies the definition of two groups of constraints that need to satisfy the optimal values of weight coefficients. The first group of constraints is the condition that the relations of the weight coefficients of criteria should be equal to the comparative priorities of the criteria. The second group of constraints is defined on the basis of the conditions of mathematical transitivity. After defining the constraints and solving the model, in addition to optimal weight values, a deviation from full consistency (DFC) is obtained. The degree of DFC is the deviation value of the obtained weight coefficients from the estimated comparative priorities of the criteria. In addition, DFC is also the reliability confirmation of the obtained weights of criteria. In order to illustrate the proposed model and evaluate its performance, FUCOM was tested on several numerical examples from the literature. The model validation was performed by comparing it with the other subjective models (the Best Worst Method (BWM) and Analytic Hierarchy Process (AHP)), based on the pairwise comparisons of the criteria and the validation of the results by using DFC. The results show that FUCOM provides better results than the BWM and AHP methods, when the relation between consistency and the required number of the comparisons of the criteria are taken into consideration. The main advantages of FUCOM in relation to the existing multi-criteria decision-making (MCDM) methods are as follows: (1) a significantly smaller number of pairwise comparisons (only n − 1), (2) a consistent pairwise comparison of criteria, and (3) the calculation of the reliable values of criteria weight coefficients, which contribute to rational judgment.

Ciavarella M., Carbone G., Vinogradov V.

Kassapoglou has recently proposed a model for fatigue of composite materials which seems to suggest that the fatigue SN curve can be fully predicted on the basis of the statistical distribution of static strengths. The original abstract writes expressions for the cycles to failure as a function of R ratio are derived. These expressions do not require any curve fitting and do not involve any experimentally determined parameters. The fatigue predictions do not require any fatigue tests for calibration". These surprisingly ambitious claims and attractive results deserve careful scrutiny. We contend that the result, which originates from the reliability theory where exponential distributions is sometimes used to model distribution of failures when age (or wearout) has no influence on the probability of failure, does not conform to a fatigue testing with the resulting SN curve distribution. Despite Kassapoglou's attempt to use a wearout law which seems to confirm this result even with wearout, we contend that a proper statistical treatment of the fatigue process should not make wear-out constants disappear, and hence the SN curves would depend on them, and not just on scatter of static data. These concerns explain the large discrepancies found by 3 independent studies which have tried to apply Kassapoglou's model to composite fatigue data.

Pei H., Wang Z., Cao J., Chen Y., Bai Z.

Na Z., Stević Ž., Subotić M., Kumar Das D., Kou G., Moslem S.

This paper introduces a novel Integrated Interval Rough Pivot Pairwise Relative Criteria Importance Assessment (IRN PIPRECIA) model combined with Interval Rough Combined Compromise Solution (IRN CoCoSo), marking a significant advancement in sustainable traffic flow management for commercial vehicles. This innovative merger is a first in literature, methodologically enhancing the evaluation of road sections based on critical parameters including passenger car equivalent (PCE) 85%, AADT, road conditions, and accident data. Our model systematically fills the research gap in holistic traffic performance analysis, providing a unique tool for prioritizing road safety and efficiency. The key scientific contribution is the model's ability to integrate causal and consequential traffic factors into a single framework, offering a novel multi-criteria decision-making (MCDM) approach. Results, validated through various verification models, show the integrated model's effectiveness in real-world scenarios, confirming its robustness and stability. With strong engineering application potential, our work supports urban planners and traffic managers in making informed, sustainable decisions. The model extends beyond traditional traffic analysis, promising a shift towards more adaptive, data-driven infrastructure management. Future research will aim to refine the criteria basis and explore real-time decision-making through advanced MCDM applications.

Nişel R., Nişel S.

In today'sCountry ranking rapidly evolving world, innovationInnovation plays a crucial role in a country’s economic well-being. This research presents a new approach to assessing and ranking nations based on their innovationInnovation capabilities. Using a wide range of indicators from the OECD guidelines, the study examines various aspects of innovationInnovation, such as research and development (R&D), collaborationR&D Collaboration, and the economic impact of innovative efforts. The study uses the LOPCOW methodLopcow method to carefully weigh these indicators and the COCOSO methodCocoso method to systematically classify countries. This comprehensive analysis highlights global innovationInnovation competencies. Our results reveal clear patterns in global innovationInnovation. We see that traditionally innovative countries continue to be ahead. In addition, the methodology used covers specific criteria that involve not only the development of new technologies, but also the improvement of the production process and innovationsInnovation in services and policies. It ensures comprehensive coverage and represents national innovationInnovation capabilities in multiple dimensions. Therefore, the presented research validates the efficiency of the integrated LOPCOW-COCOSO methodCocoso method in sorting countries according to the level of innovationInnovation and provides useful insights for policymakers, industry leaders, and researchers.

Rong Y., Yu L., Liu Y., Simic V., Pamucar D., Garg H.

Srivastava R.R., Singh P.K.

Exploding population, industrialization, and an increase in water pollution has led to acute shrinkage in freshwater availability. Numerous countries have started exploring municipal wastewater as a new potential source of water to bring a paradigm shift from linearity to obtaining circularity in human water cycle management. This study aims to develop a decision support system for integrated water and wastewater management (DSS_IWWM), targeted towards reuse-focused selection of appropriate wastewater treatment technology, and localized planning around STPs in terms of reclaimed water demand identification, estimation, allocation, and sustainable pricing. The developed DSS_IWWM comprises of a repository of fourteen reuse purposes, reuse quality criteria, and 25 wastewater treatment technologies (WWTTs) in 360 combinations. It is sensitive to local resource scenarios and applies a socioeconomic and technology-focused methodology for addressing the interests of the community and investing agencies and viably. To validate the application of the DSS_IWWM, it is first tested with data from three cities in the state of Uttar Pradesh (India)—Lucknow, Prayagraj, and Agra—and then extended to nine more Indian cities with varying influent quality characteristics, resource inputs, existing STP technologies, and same target quality and decision criteria prioritization, to present a comparison of appropriate WWTTs and associated average prices obtained in different scenarios. It is concluded that influent quality, existing technology, and target quality criteria play significant role in selection of appropriate WWTTs. The traditional technologies such as UASB and ASP are required to be augmented and supplemented with high-performing WWTTs, such as BIOFOR-F with (C + F + RSF) and SBT + WP to obtain desired effluent quality. High-performing advanced oxidation process (AOP)-based systems such as A2O, SBR, and BIOFOR-F require WWTTs with relatively lower average costs (such as SBT and OP). The developed DSS_IWWM may prove to be very useful and beneficial for policymakers, government officials, engineers, and scientific community as it will facilitate rational decision-making for efficient investment planning in reuse focused wastewater treatment towards achieving circular economy in sustainable water resource management.

Brito J.R., Galo N.R.

As empresas estão vivenciando um momento de constante competitividade, o que acarreta desafios para se destacarem no mercado e obter resultados financeiros satisfatórios. Em meio a alta concorrência, uma questão essencial é realizar a gestão de estoques de forma eficiente, por possibilitar obter vantagens competitivas e impactar diretamente na rentabilidade da empresa. Para o alcance de uma gestão eficiente, torna-se necessário o uso de ferramentas e métodos de auxílio. Com isso, este artigo possui o objetivo de apresentar a ferramenta curva ABC e analisar suas contribuições, como forma de auxiliar os gestores na tomada de decisão. Para tanto, foi realizada uma modelagem quantitativa empírica em uma empresa que atua no segmento de tecnologia Telecom localizada em Goiânia-GO, onde foi realizada a classificação ABC para o estoque não operacional e, em um segundo momento aplicação do método TOPSIS em seus respectivos componentes da lista oriundo da classificação com objetivo de mapear oportunidades que não são possíveis apenas com a classificação ABC, houve sucesso na aplicação de ambos os métodos, onde a organização consegue realizar a gestão do estoque e de compras de forma estratégica, evitando excesso de produtos em estoques.

Bouraima M.B., Saha A., Stević Ž., Antucheviciene J., Qiu Y., Marton P.

The selection and prioritization of appropriate actions to improve the performance of the railway sector pose a common challenge for policymakers and transport planners. This challenge is further complicated by factors such as political power shifts, policy changes, and socio-economic and environmental impacts, introducing various uncertainties. To address this issue, a novel multi-criteria decision-making framework was developed in this study. The framework introduces the weighted geometric Dombi Maclaurin Symmetric Mean operator within an intuitionistic fuzzy environment, enabling the identification of the most appropriate action from nine different alternatives to enhance the performance of railway sector. Moreover, the study makes an additional contribution by combining this approach with an interval rough PIvot Pairwise RElative Criteria Importance Assessment to determine the weight coefficients of the criteria. To assess the robustness of the proposed methodology, sensitivity analysis and a comparative study were conducted. The findings of the study indicate that “enhancing the governance of the transport sector” emerged as the most appropriate action to improve the performance of the railway sector.

Yadav R.S., Kaya S.K., Pant A., Tiwari A.

Purpose Artificial intelligence (AI)-based human capital management (HCM) software solutions represent a potentially effective way to leverage and streamline a bank’s human resources. However, despite the attractiveness of AI-based HCM solutions to improve banks’ effectiveness, to the best of the authors’ knowledge, there are no current studies that identify critical success factors (CSFs) for adopting AI-based HCM in the banking sector. This study aims to fill this gap by investigating CSFs for adopting AI-based HCM software solutions in the banking sector. Design/methodology/approach Full consistency method methodology and technology–organization–environment, economic and human framework are used for categorizing and ranking CSFs. Findings The study identifies the technological and environmental dimensions as the most and least important dimensions for AI-based HCM adoption in banks. Among specific CSFs, compatible technology facilities, sufficient privacy and security and relative advantages of technology over competing technologies were identified as the most important. Implementation of AI-based HCM solutions requires significant outlays of resources, both human and financial, for banks. Originality/value The study provides bank administrators a set of objective parameters and criterion to evaluate the feasibility of adopting a particular AI-based HCM solution in banks.

Yildirim E., Cam V., Balki F., Sarp S.

AbstractStock management is very important for the companies to supply necessary demand for the products they sell, to pricing the products and to the aspect of storage cost. In stock management, the products to be sold to the customer are procured by ordering from the vendors. The orders given to the vendors are determined by estimating the sales quantities of the products. When estimating sales, if we order in large quantities, the storage and expiration dates of the products may exceed, or if we order less than demand, the customer cannot find the product in the store. With the Covid-19 pandemic entering our lives, there have been some changes in our habits. One of these changes is the change in shopping habits of people due to the isolation period. By managing this change in terms of stock management on the store side, it ensures that people can reach the products they demand in these difficult times and that companies do not create extra costs by making more stock than necessary. We made a sales forecast on 5-lt sunflower oil which is a basic food product using the data of a grocery chain with machine learning methods and developed models to use these forecasts in stock management. Our data is multivariate and contains both quantitative and qualitative features. In our study, we used the supervised learning method and the XGBoost, LGBMRegressor and Ridge models used in many machine learning projects. As a result of our studies, an improvement of approximately 25% has emerged with the features we added specifically for the pandemic.

Masmali I., Hassan R., Shuaib U., Razaq A., Razzaque A., Alhamzi G.

Symmetrical and asymmetrical information plays a critical role in resolving many issues. The implications of symmetry and asymmetry in interval-valued picture fuzzy decision-making, lie in their ability to represent and manage complex data. Decision makers approach the problem of information asymmetry through various methods. Integrating symmetric and asymmetric data in the context of a specific physical phenomenon poses significant challenges. To address these challenges, interval-valued picture fuzzy (IVPF) sets have emerged as an effective tool for managing complex data. In decision-making processes, it is essential to consider the complementary and conflicting nature of the analyzed data. This article aims to refine the shortcomings of the existing score function for Multiple Criteria Decision-Making (MCDM) problems in an IVPF environment, and present an improved score function. The IVPF sets are leveraged to propose IVPF weighted arithmetic operators, IVPF ordered weighted arithmetic operators, IVPF weighted geometric operators, and IVPF ordered weighted geometric operators, which are analyzed in terms of their key features. To demonstrate the effectiveness of the proposed score function and newly defined operators, a case study involving the selection of the best food item for manufacturing, is conducted. Additionally, a comparative analysis is established to investigate the significance of the newly defined techniques in solving decision-making problems under IVPF knowledge.

Pamucar D., Gokasar I., Ebadi Torkayesh A., Deveci M., Martínez L., Wu Q.

The Integration of Unmanned Aerial Vehicles (UAVs) into transportation systems has numerous benefits, ranging from the ability to record real-time data to having high mobility and broad vision. Because of the increasing levels of congestion in the cities, many of the transportation system tasks, such as traffic management and data collection, have become complicated to handle. The implementation of UAVs in transportation systems is a feasible solution to overcoming these problems. Therefore, UAVs have become a point of interest for many transportation system authorities. This study aims to introduce an integrated Fuzzy Level Based Weight Assessment (LBWA) in a stratification environment (SF-LBWA) and Fuzzy Rough Hamacher Combined Compromise Solution (CoCoSo) model to resolve the prioritization of Unmanned Aerial Vehicles in transportation system problems. The decision framework for such a problem is defined by establishing the relevant alternatives and criteria according to the specialized literature. Hence, a case study illustrates the formulation and solution of the problem. This study will indicate the most suitable alternative for the problem and provide guidance as authorities look for ways to integrate UAVs and transportation systems.

Prakash Garg C., Görçün Ö.F., Kundu P., Küçükönder H.

In recent years, there have been dramatic changes in manufacturing systems in many industries depending on technological developments. Robotics is one of the essential components of these changes. Today, the usage of robotics in manufacturing processes has become widespread in almost all industries. Also, it has become a very strong desire ever-increasing for even small and medium-sized enterprises at present. Almost all the previous studies emphasized that industrial robot selection is a highly complex decision-making problem as there are many conflicting factors and criteria. Besides, different and advanced specifications of these robotics added by robotic manufacturers have caused to increase the complexities much more. Hence, decision-makers encounter more complicated decision-making problems affected by many uncertainties. Because of that, an integrated fuzzy group MCDM framework can help overcome many ambiguities proposed in the current paper. The proposed fuzzy integrated model consists of the fuzzy SWARA (F-SWARA’B) and the fuzzy CoCoSo (F-CoCoSo'B), which are extended with the help of the Bonferroni function. The model selected the appropriate industrial robotics used in the automotive industry by considering 15 criteria and ten alternatives. According to the result of the study, the three most significant criteria have been determined: Working Accuracy, Reaching Distance, and Performance; and the most suitable option is the A8. The obtained results were validated with the help of a comprehensive sensitivity analysis consisting of different 150 scenarios. The results are also compared with some existing techniques. The sensitivity analysis results approve the validity and applicability of the proposed model.

ARMAN K., KUNDAKCI N.

Bulut teknolojisinin işletmeler üzerindeki etkisi kanıtlandığından beri dünya çapında her geçen gün daha fazla işletme bu teknolojiye yönelmekte ve yatırım yapmaktadır. Bulut teknolojisi ile işletmeler, fiziksel sınırları ortadan kaldırarak yüksek güvenlik hizmeti ile verileri için yüksek depolama alanı kazanırken daha hızlı veri paylaşımı ile önemli maliyet tasarrufu sağlamaktadır. İşletmeler için bulut hizmet sağlayıcısı seçimi önemli bir karardır. İşletmelerin bulut hizmet sağlayıcıları için çeşitli endişeleri mevcut olabilmektedir ve işletmelerin en uygun bulut hizmet sağlayıcısının seçimi için birbiri ile çelişen bir dizi kriteri göz önünde bulundurması gerekir. Bu problemin çözümünde Çok Kriterli Karar Verme (ÇKKV) yöntemleri kullanılabilir. Bu çalışmanın amacı bir işletme için en uygun bulut hizmet sağlayıcısının seçimidir. Bu çalışmada, kriter ağırlıkları FUCOM (Full Consistency Method) ile belirlendikten sonra WEDBA (Weighted Euclidean Distance Based Approximation) yöntemi ile en uygun bulut hizmeti sağlayıcısı öneri olarak sunulmaktadır. Çalışmadan elde edilen sonuçlar, bulut hizmet sağlayıcısı seçiminde kriterlerin önem seviyelerine göre sırasıyla güvenlik, aylık maliyet, hafıza kapasitesi, sürdürülebilirlik, dosya paylaşım kapasitesi ve ek ücretsiz depolama alanı şeklinde olduğunu göstermektedir. İşletmelere sunulan paketler açısından ise en uygun bulut hizmet sağlayıcısı Google Drive olarak belirlenmiştir.

Gou C.

This paper proposes a multiattribute group decision-making (MAGDM) based on the CoCoSo method under the intuitionistic fuzzy sets (IFSs) environment for quality evaluation of innovation and entrepreneurship education (IEE) in vocational colleges. First of all, this paper extends the CoCoSo to the IFSs environment. Second, a new MAGDM model for quality evaluation of IEE in vocational colleges based on the CoCoSo algorithm is built. In this algorithm, the attribute weight is derived by subjective weight and objective weight, and the objective weights are defined by using the CRITIC method. At the end of this given study, some comparisons are given to verify the decision effectiveness of the algorithm.

Tavana M., Shaabani A., Di Caprio D., Bonyani A.

• A systematic and efficient approach to select the best eco-friendly packaging is proposed. • Asymmetric Interval Type-2 Trapezoidal Fuzzy Sets (IT2TFSs) are used to model ambiguous and uncertain data. • Best Worst Method (BWM) and Combined Compromise Solution (CoCoSo) are integrated in an asymmetric IT2TFS setting. • A new consistency ratio is defined for IT2TFS-BWM to check the reliability of IT2TFS comparisons. • A real case study is presented to show the applicability and capability of IT2TFS-BWM-CoCoSo. Increasing consumer goods and products has inspired environmental activists and policymakers to demand eco-friendly packaging from retailers and manufacturers. At the same time, consumer attitudes about sustainable packaging have changed significantly. In response to these changing consumer sentiments, the packaging value chain is changing, and businesses are seeking to use environmentally friendly packaging for their products. However, choosing the best packaging is a significant challenge for decision-makers (DMs) who must consider many uncontrollable and unpredictable environmental factors. This study aims to design a new methodology for assessing engineering and ecological challenges and proposing a practical approach for selecting the best eco-friendly packaging alternative. We propose a novel model that integrates the Best-Worst Method (BWM) and Combined Compromise Solution (CoCoSo) within an asymmetric Interval Type-2 Trapezoidal Fuzzy Set (IT2TFS) setting. The new IT2TFS-BWM-CoCoSo method consists of two phases: determining the optimal weights of the evaluation criteria and ranking the alternatives. The asymmetric IT2TFS is used in both phases to interpret DMs’ fuzzy preferences. A new consistency ratio (CR) is defined to assess the consistency level of DMs’ preference comparisons expressed by asymmetric IT2TFSs. The asymmetric features add flexibility to DMs’ evaluations without weakening their accuracy. The proposed methodology is applied to a real-life case study of a US-based company that produces and ships handmade crystals. Recycled cardboard and paper, biodegradable packaging peanuts, and eco-friendly plastic and recycled plastics are found to be the best eco-friendly packaging alternatives. The case study results demonstrate the applicability and efficacy of the proposed method and its flexibility in solving sustainable packaging selection problems of companies with similar characteristics. At the same time, the technical features of the proposed framework open the way to a wide range of applications for sustainable consumption and production.