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2009 yılında piyasaya giriş yapan kripto paralar, âdemi merkeziyetçi bir yapıda mübadele işlevini yerine getiren sanal para birimleridir. Kripto paralar, blockchain teknolojisine bağlı olarak ticari işlemlere konu olması ve düşük transfer maliyeti ile hızlı işlemler gerçekleştirilmesi gibi niteliksel özelliklere sahiptir. Kripto paralar, bir yatırım aracı olarak son yıllarda büyük ilgi görmektedir. Bu çalışmanın temel amacı, yatırımcıların yatırım kararı vermesini kolaylaştıracak bir karar destek mekanizması sunmaktır. Bu amaçla Entropi-ARAS çok kriterli modeli kullanılarak finansal piyasalarda en yüksek işlem hacmine sahip ilk on kripto para değerlendirilmiştir. Öncelikle Entropi yöntemi kullanılarak yıllık ortalama getiri, işlem hacmi, toplam piyasa değeri, işlem gördüğü borsa sayısı, işlem gördüğü yıl sayısı, işlem hızı, en yüksek değerden değişim ve volatilite kriterinin ağırlıkları belirlenmiştir. Ardından ARAS yönteminde kullanılarak, kripto para alternatiflerinin performans sıralaması yapılmıştır. Çalışmanın bulgularına göre, işlem hacmi yatırım yaparken dikkate alınması gereken en önemli faktördür. Ayrıca, alternatif kripto paralar içinde ilk sırada Bitcoin, Tether ve Usd Coin yer alırken, Dogecoin son sırada yer almaktadır. Kripto paraların işlem hacmi ile performans sıralamalarının yüksek derecede pozitif korelasyona sahip olduğu sonucuna da ulaşılmıştır. Son olarak önerilen modelin sağlamlığı ve geçerliliği duyarlılık analiziyle de kontrol edilmiştir.

PurposeNowadays, companies have required new alternatives and strategies to handle environmental sustainability difficulties, primarily as ecological and social awareness has grown. In this context, the aim is to determine the green transportation indicators in companies with corporate identity and logistics activities at the international level in Giresun, Ordu, Gümüshane, Artvin, Rize, and Trabzon in the Eastern Black Sea Region in Turkey. At the same time, the study contributes to providing an effective and applicable solution to decision-making problems involving the assessment of green transportation indicators and smart network strategies in the logistics sector, which is a critical sector for countries. The purpose of this paper is to address these issues.Design/methodology/approachThis study aims to propose a model for the selection of smart network strategy and to determine the criteria weights used in green transportation indicators, and establish an ideal smart network strategy. In achieving the outlined goals of the study, the authors believe that the model proposed in the study will draw the focus to green logistics which will aid the environmental, economic and social efforts of businesses and governments through the provision of efficient use of scarce resources, which will, in turn, ensure that we leave a sustainable environment for future generations and businesses enjoy a competitive advantage. At the same time, different smart network strategies and green transportation indicators in companies show the success rate of social, economic and environmental indicators in green logistics practices. In addition to providing innovative, reliable and sustainable transportation systems, smart network strategies are critical for businesses to create cost advantages. Through the green transportation indicators and smart network strategies selection model outlined in this study, it is clear that the contribution will not only be limited to businesses, as the society and governments will also benefit from the important indicators on sustainability, as well as the protection of the environment and nature.FindingsAccording to the findings, “economic indicators” is the essential green transportation indicator in logistics companies with a corporate identity and worldwide transportation operations. Besides, the “mixed access model strategy” is the most appropriate smart network strategy in logistics firms with corporate identity and worldwide transportation activities. Currently, it is possible to assume that logistics organizations prefer to profit from all smart network strategies in terms of cost optimization and competitiveness rather than from just one. The study, on the other hand, which is a road map that will help sustainability practices in the logistics sector due to green transportation, also examines the similarities and differences of green transportation practices in companies in the relevant sector and to what extent they can be reflected. As a result, the study provides a practical road map for selecting green transport indicators and a smart network strategy process for the logistics industry.Originality/valueThis study examined logistics companies with a corporate identity and international transportation activities in provinces in the Eastern Black Sea Region such as Ordu, Giresun, Trabzon, Rize, Artvin and Gümüshane. Novel picture fuzzy level based weight assessment (PF-LBWA) and picture fuzzy combined compromise solution (PF-CoCoSo) methods are developed to solve the decision-making problem.

Innovation can be the greatest hope of overcoming economic challenges. This paper aims to evaluate countries concerning their innovation performances. We introduce an innovation performance evaluation methodology by considering objective factors and applying seven reliable MCDM methods: MEREC, CODAS, MABAC, MARCOS, CoCoSo, WASPAS, and MAIRCA. MEREC calculates the relative weights of indicators considered, while the other techniques decide the ranking order of G7 countries. The Borda rule is then employed to gain an aggregated ranking order. “Business sophistication” is the most critical indicator, whereas the US has the best position regarding the overall ranking. Sensitivity control is as well conducted.

İnternetin keşfedilmesiyle birlikte insanların yaşam tarzlarında ve alışkanlıklarında önemli ölçüde değişimler meydana gelmiştir. İnternetle birlikte işletmeler satışlarını internet üzerinden yapma eğilimine girmiş ve insanlar giderek daha fazla ihtiyacını internet üzerinden karşılamaya başlamışlardır. 2019 yılında ortaya çıkan Covid-19 ile internet tüketicilerin hayatında daha da önemli bir yere sahip olmaya başlamıştır. Tüketiciler hastalık korkusuyla ihtiyaçlarını sanal alışveriş platformları üzerinden gidermeye yönelmişlerdir. Bu çerçevede bu çalışmada beş ana kriter ve bunlara ilişkin yirmi üç alt kriter doğrultusunda sanal alışveriş platformlarının salgın dönemindeki performansları AHP ve MAIRCA bütünleşik modeliyle analiz edilmiştir. Bu bağlamda AHP yöntemiyle kriterlerin önem ağırlıkları tespit edilmiştir. MAIRCA yöntemi ise sanal alışveriş sitelerinin sıralanması amacıyla kullanılmıştır AHP sonuçları sırasıyla “uygun fiyat”, “karantina süreci” ve “enfekte olma korkusu” kriterlerinin sanal alışveriş platformlarının performanslarının en önemli belirleyicileri olduğunu göstermiştir. Ayrıca Trendyol, en başarılı alışveriş sitesi olarak belirlenmiştir. Bu çalışma sanal alışveriş platformları için salgın dönemindeki kendi performans değerlendirmelerinde kullanabilecekleri bir kılavuz niteliğinde olabilir.

This paper proposes a new multi-criteria group decision-making (MCGDM) method utilizing q-rung orthopair fuzzy (qROF) sets, improved power weighted operators and improved power weighted Maclaurin symmetric mean (MSM) operators. The power weighted averaging operator and power weighted Maclaurin symmetric mean (MSM) operator used in the existing MCGDM methods have the drawback of being unable to distinguish the priority order of alternatives in some scenarios, especially when one of the qROF numbers being considered has a non-belongingness grade of 0 or a belongingness grade of 1. To address this limitation of existing MCGDM methods, four operators, namely qROF improved power weighted averaging (qROFIPWA), qROF improved power weighted geometric (qROFIPWG), qROF improved power weighted averaging MSM (qROFIPWAMSM) and qROF improved power weighted geometric MSM (qROFIPWGMSM), are proposed in this paper. These operators mitigate the effects of erroneous assessment of information from some biased decision-makers, making the decision-making process more reliable. Following that, a group decision-making methodology is developed that is capable of generating a reasonable ranking order of alternatives when one of the qROF numbers considered has a non-belongingness grade of 0 or a belongingness grade of 1. To investigate the applicability of the proposed approach, a case study is also presented and a comparison-based investigation is used to demonstrate the superiority of the approach.

PurposeThis paper proposes a new multi-criteria decision-making method, called the vital-immaterial-mediocre method (VIMM), to determine the weight of multiple conflicting and subjective criteria in a decision-making problem.Design/methodology/approachThe novel method utilizes pairwise comparisons, vector-based procedures and a scoring approach to determine weights of criteria. The VIMM compares alternatives by the three crucial components, namely the vital, immaterial and mediocre criteria. The vital criterion has the largest effect on the final results, followed by the mediocre criterion and then the immaterial criterion, which is the least impactful on the prioritization of alternatives. VIMM is developed in two forms where the first scenario is designed to solve one-goal decision-making problems, while the second scenario embraces multiple goals.FindingsTo validate the method’s performance and applicability, VIMM is applied to a problem of sustainable supplier selection. Comparisons between VIMM, analytic hierarchy process (AHP) and best-worst method (BWM) reveal that VIMM significantly requires fewer comparisons. Moreover, VIMM works well with both fractional and integer numbers in its comparison procedures.Research limitations/implicationsAs an implication for research, we have added the development of the VIMM under fuzzy and grey environments as the direction for optimization of the method.Practical implicationsAs managerial implications, VIMM not only provides less complex process for the evaluation of the criteria in the managerial decision-making process, but it also generates consistent results, which make VIMM a reliable tool to apply to a large number of potential decision-making problems.Originality/valueAs a novel subjective weighting method, there exist five major values that VIMM brings over AHP and BWM methods: VIMM requires fewer comparisons compared with AHP and BWM; it is not sensitive to the number of criteria; as a goal-oriented method, it exclusively takes the decision-making goals into account; it keeps the validity and reliability of the Decision-Makers’ (DMs’) opinions and works well with integer and fractional numbers.

Renewable Energy Resources (RERs) are becoming increasingly significant for energy generation and will have vital for the future of humans, earth, and other living things. Due to the negative environmental impacts of fossil fuels, the authorities have taken RERs into account further. As a result, the present study extended a novel model using the Level Based Weight Assessment (LBWA) model based on in Interval Rough Number (IRN) extension of the Combinative Distance-Based Assessment (CODAS) method to cope with uncertain domain-based RER selection. A survey method using literature review and interview has been conducted to find and select appropriate perspectives and criteria; in this regard, the selected criteria were classified based on four groups, including socio-political, environmental, economic, and technical. Five sources of renewable energy, including solar energy, biomass energy, wind energy, hydropower energy, and geothermal energy, are evaluated in Turkey. The results of the extended IRN CODAS approach demonstrated that hydropower energy had the first rank among other sources, followed by solar energy, geothermal energy, biomass energy, and wind energy. In the application of the suggested model, the most suitable RER alternative is determined for Turkey. The results of this study showed the effectiveness, efficiency, and capability of the proposed methodology in the assessment of RERs.

PurposePharmaceutical supply chains (PSCs) need a well-operating and faultless logistics system to successfully store and distribute their medicines. Hospitals, health institutes, and pharmacies must maintain extra stock to respond requirements of the patients. Nevertheless, there is an inverse correlation between the level of medicine stock and logistics service level. The high stock level held by health institutions indicates that we have not sufficiently excellent logistics systems presently. As such, selecting appropriate logistics service providers (drug distributors) is crucial and strategic for PSCs. However, this is difficult for decision-makers, as highly complex situations and conflicting criteria influence such evaluation processes. So, a robust, applicable, and strong methodological frame is required to solve these decision-making problems.Design/methodology/approachTo achieve this challenging issue, the authors develop and apply an integrated entropy-WASPAS methodology with Fermatean fuzzy sets for the first time in the literature. The evaluation process takes place in two stages, as in traditional multi-criteria problems. In the first stage, the importance levels of the criteria are determined by the FF-entropy method. Afterwards, the FF-WASPAS approach ranks the alternatives.FindingsThe feasibility of the proposed model is also supported by a case study where six companies are evaluated comprehensively regarding ten criteria. Herewith, total warehouse capacity, number of refrigerated vehicles, and personnel are the top three criteria that significantly influence the evaluation of pharmaceutical distribution and warehousing companies. Further, a comprehensive sensitivity analysis proves the robustness and effectiveness of the proposed approach.Practical implicationsThe proposed multi-attribute decision model quantitatively aids managers in selecting logistics service providers considering imprecisions in the multi-criteria decision-making process.Originality/valueA new model has been developed to present a sound mathematical model for selecting logistics service providers consisting of Fermatean fuzzy entropy and WASPAS methods. The paper's main contribution is presenting a comprehensive and more robust model for the ex ante evaluation and ranking of providers.

PurposeThe present study aims to provide a practical and robust assessment technique for assessing countries' investability in global supply chains to practitioners. Thus, the proposed approach can help decision-makers evaluate and select appropriate countries in the expansion process of the global supply chains and reduce risks concerning country (market) selection.Design/methodology/approachThe present study proposes a novel decision-making approach, namely the REF-Sort technique. The proposed approach has many valuable contributions to the literature. First, it has an efficient basic algorithm and can be applied to solve highly complicated decision-making problems without requiring advanced mathematical knowledge. Besides, some characteristics differentiate REF-Sort apart from other techniques. REF-Sort employs the value or value range that reflects the most typical characteristic of the relevant class in assignment processes. The reference values in REF-Sort and center profiles are similar in this regard. On the other hand, class references can be defined as ranges in REF-Sort. Secondary values, called successors, can also be employed to assign a value to the appropriate class. REF-Sort can also determine the reference and successor values/ranges independently of the decision matrix. In addition, the proposed model is a maximally stable and consistent decision-making tool, as it is resistant to the rank reversal problem.FindingsThe current papers' findings indicate that countries have different features concerning investment. Hence, the current paper pointed out that only 22% of the 95 countries are investable, whereas 19% are risky. Thus, decision-makers should make detailed evaluations using robust, powerful, and practical decision-making tools to make more reasonable and logical decisions concerning country selection.Originality/valueThe current paper proposes a novel decision-making approach to evaluate. According to the authors' information, the proposed model has been applied to evaluate investable countries for the global supply chains for the first time.

Research background: International market selection is an essential issue for big companies that supply food products. Different types of decision factors and different characteristics of different international markets have brought up a complicated decision-making problem for food supply companies. In order to select the most suitable and profitable market, food supply companies have to consider several qualitative and quantitative factors, including social, political, economic, and ecological aspects. Purpose of the article: In order to overcome international market selection issues, the current study develops a novel integrated decision-making tool. Methods: A novel decision-making model of market analysis is developed as an extended model of Market Attractiveness and Business Attractiveness (MABA) analysis based on the Multiple Attribute Decision Making (MADM). To improve the MABA analysis model, we combine the EDAS method with MABA analysis to empower decision-makers in food supply companies to evaluate several international markets and select the most profitable market for their products. Findings & value added: In this study, we first identified the most important and frequently used decision factors for market analysis problems within MABA analysis under two categories: market attractiveness and business attractiveness. To show the proposed methodology's applicability and feasibility, we perform a case study for a food supply company in Iran that supplies products to Middle East and Asian countries. In order to investigate the reliability of the obtained results, we perform a sensitivity analysis concerning the importance of involved decision factors. The proposed decision-making tool results suggest that the model can be used as a reliable tool for market analysis problems. To sum up the long-term value of the study, we have developed a novel decision-making tool using MABA analysis and the EDAS method. No study integrates any MCDM methods with MABA analysis to the best of our knowledge. Integration of EDAS method with MABA analysis empowers decision-makers in market selection division to use more systematic methods for evaluating several markets.

Waste in fast-moving consumer goods (FMCGs) is a tremendous economic and ethical issue for retailers and the rest of society. Due to methodological weaknesses, previous studies are inadequate in prioritizing fundamental causes and drivers of retail food waste (RFW) in this context. This research explores the peculiar causes and drivers of RFW concerning different perishable FMCG categories. This research employs the fuzzy level-based weight assessment (F-LBWA) methodology to provide a robust and effective decision-making tool to retailers responsible for preventing waste in their stores. This research categorizes the causes and drivers into different product categories giving insight into the reasons and drivers that need more attention than others for each product category. The findings reveal that inappropriate buying/delivery is the most significant cause of waste for fruit and vegetables, dairy products, fresh meat, fish and seafood, and baked products, whereas improper storage is the most critical cause of waste for frozen food. The present work ensures practical implications for developing product category-specific waste management policies to improve retailers' efficiency, competitiveness, and profitability. For a developing country like Turkey, the applicable insights of this research can also serve all supply chain members and policymakers to prevent food waste through partnership.

Many managers and firm owners nowadays pay special attention to green supplier selection to gain competitive advantage all over the world. Consequently, this subject a critical and significant decision for firms. This study utilizes an extension to analytical hierarchy process (AHP) under interval type-2 fuzzy environment (IT2FAHP) model to better cope with ambiguity and vagueness for solving supplier selection problem considering green concepts. A real case application is also performed in a home appliance manufacturer to demonstrate the effectiveness and efficiency of the IT2FAHP model in the present paper. The findings indicate that the most important factors that are effective in selecting green suppliers are cleaner production, energy/material saving, green package, remanufacturing, and environmental management system. Further, a comparison and a sensitivity analysis are conducted to display the consistency and stability of the proposed model. The findings reveal that the IT2FAHP model is quite consistent with the models in literature and green product, cleaner production, green design, and green package have a significant positive effect on performances of green suppliers.

Sustainable transport in cities has been gaining a lot of attraction recently and a core focus of engineering management. Internet of Things (IoT) is seen as a widely accepted technology that promotes sustainability through the interconnection of diverse computing sources for solving environmental problems. Previous studies on IoT have discussed interesting factors toward its adoption, but selecting a suitable IoT service provider (IoTSP) is an open challenge due to a diverse set of factors in practice. Driven by the challenge, in this article, a generalized fuzzy-based decision model is put forward for IoTSP selection, which is the prime objective of the study. Initially, a strength, weakness, opportunity, threat (SWOT) analysis is adopted to identify the crucial challenges in IoT adoption. Later, the relative significance of these challenges is calculated by adopting the regret/rejoice approach. Due to uncertainty, certain rating information of IoTSPs is missing that are rationally imputed by proposing an analytical approach. Rating matrices from experts are transformed into opinion vectors, and a prioritization algorithm is developed with query vector for rational personalized ordering of IoTSPs. Data for the study are acquired via questionnaire, which is filled by experts. The efficacy of the developed model is exemplified by using a real case study of IoTSP selection for pollution management in Chennai. Concerning the findings, mobility, security, and connectivity are the most vital factors for IoTSP selection. Results show that the proposed model is a viable tool for IoTSP selection and it is robust, unique, and stable compared to its counterparts.

The COVID-19 pandemic has created unexpected demand for air cargo in terms of rapid mobility of critical basic needs. Air cargo carriers aim to maximize their profits by taking advantage of the current demand and using their limited capacity in the right place. At this point, some of the qualifications of the airports in the places where demand plays a crucial role in this decision of the carriers. Thus, evaluating the factors considered in the airport selection for air cargo carriers during the COVID-19 period is curious. This study proposes a triangular fuzzy Dombi-Bonferroni best-worst method (BWM) framework with vast flexibility to establish the priority preferences of factors considered in selecting airports. The fuzzy BWM model becomes a superior decision support system by combining the Bonferroni mean operator's ability to consider interrelationships between attributes and the flexibility of the Dombi operator. In this sense, we highlight eighteen criteria based on five airport aspects: location, physical features, performance, costs, and reputation. Findings reveal that the foremost aspects are location and costs, whereas the most crucial factors are airport charges and handling charges. The study suggests that airports should follow a low-price policy for airport-related charges without compromising their sustainability to have a share of the increasing number of air cargo flights, especially during the COVID-19 period, when airline passenger flights are decreased. The study is crucial in deciding the strategy and policy of air cargo carriers and airports during the pandemic period.

All over the world, the COVID-19 outbreak seriously affects life, whereas numerous people have infected and passed away. To control the spread of it and to protect people, appreciable vaccine development efforts continue with increasing momentum. Given that this pandemic will be in our lives for a long time, it is obvious that a reliable and useful framework is needed to choose among coronavirus vaccines. To this end, this paper proposes a new intuitionistic fuzzy extension of MAIRCA framework, named intuitionistic fuzzy MAIRCA (IF-MAIRCA) to assess coronavirus vaccines according to some evaluation criteria. Based on the group decision-making, the IF-MAIRCA framework both extracts the criteria weights and discovers the prioritization of the alternatives under uncertainty. In this work, as a case study, five coronavirus vaccines approved by the world's leading authorities are evaluated according to various criteria. The findings demonstrate that the most significant criteria considered in coronavirus vaccine selection are “duration of protection,” “effectiveness of the vaccine,” “success against the mutations,” and “logistics,” respectively, whereas the best coronavirus vaccine is AZD1222. Apart from this, the proposed model's robustness is verified with a three-phase sensitivity analysis.

Çalışmanın amacı, Türkiye'deki özel sermayeli bankaların kurumsal sürdürülebilirlik performanslarını analiz etmektir. Bu amaçla Entropi-ARAS bütünleşik modeli önerilmiştir. Önerilen modelinin etkinliğini kontrol etmek için ayrıca duyarlılık analizi yapılmıştır. Çalışmanın bulgularına göre özel sermayeli bankaların sürdürülebilirlik performanslarının belirlenmesinde en önemli boyut sosyal boyuttur. Kurumsal sürdürülebilirlik bakımından yüksek performans hedefine ulaşmak isteyen bankalar, öncelikle personel devir hızını düşürmeli, ardından doğrudan sera gazı tüketimini azaltmalıdırlar. Çalışma ayrıca, önerilen modelin bankaların kurumsal sürdürülebilirlik performanslarının belirlenmesinde yararlanılabilecek kullanışlı ve güçlü bir karar aracı olduğu ortaya koymuştur.

Blockchain technologies, which form the basis of Industry 4.0, paved the way for cryptocurrencies to emerge as technological innovation in the technology age. Recently, investors worldwide have been interested in cryptocurrencies with increasing acceleration due to high earning expectations though they have no backing and intrinsic value. As such, this paper seeks to identify the most proper cryptocurrencies from an investment standpoint in our technological era. Fifteen well-known cryptocurrencies with the highest market capitalization are evaluated as per sixteen factors. An intuitionistic fuzzy set-driven methodology incorporating Evaluation Based on Distance from Average Solution (EDAS), Multi-Attributive Ideal Real Comparative Analysis (MAIRCA, and Measurement of Alternatives and Ranking according to COmpromise Solution (MARCOS), which is the study’s prominent novelty, has been applied to provide a strong group decision vehicle for cryptocurrency selection. Notwithstanding, although the results obtained with the three approaches are highly consistent, investors would not like to doubt the instrument they will invest in. The Borda count is then applied to obtain a compromise for the rankings obtained from each approach. As per our findings, Ethereum, Tether, and Bitcoin are the most suitable cryptocurrencies, whereas reliable software, ease of inclusion in the wallet, and stability are the foremost factors to consider when investing in cryptocurrencies. The findings are further discussed in detail from a financial perspective. The proposed approach could be employed to select different investment instruments in future studies.

Not only the steadily growing demand for electricity generation but also the environmental concerns in recent years have led to the belief in the importance of renewable energy. Wind is one of the most important renewable energy sources utilized in electricity generation for a sustainable environment. This paper deals with performance assessment for existing onshore wind plants in terms of triple bottom line of sustainability and aims to propose a structural methodology. Furthermore, the proposed framework is essentially formed through two stages: the first stage is the determination of relative weights for sustainability factors through the best-worst method (BWM) and the second stage is a sustainability performance assessment of the available 42 wind plants in Izmir, Turkey. According to the findings, the environmental dimension is the most significant, followed by the economic and social dimensions. The results also reveal that distance to protected areas is the most important factor among others in terms of sustainability performance and that the wind plants throughout the north side of Izmir have a higher sustainability performance. To validate the robustness and reliability of the introduced framework, a sensitivity analysis is also conducted. The proposed framework could be employed successfully in other scientific applications.

The Best Worst Method (BWM) represents a powerful tool for multi-criteria decision-making and defining criteria weight coefficients. However, while solving real-world problems, there are specific multi-criteria problems where several criteria exert the same influence on decision-making. In such situations, the traditional postulates of the BWM imply the defining of one best criterion and one worst criterion from within a set of observed criteria. In this paper, an improvement of the traditional BWM that eliminates this problem is presented. The improved BWM (BWM-I) offers the possibility for decision-makers to express their preferences even in cases where there is more than one best and worst criterion. The development enables the following: (1) the BWM-I enables us to express experts&rsquo, preferences irrespective of the number of the best/worst criteria in a set of evaluation criteria, (2) the application of the BWM-I reduces the possibility of making a mistake while comparing pairs of criteria, which increases the reliability of the results, and (3) the BWM-I is characterized by its flexibility, which is expressed through the possibility of the realistic processing of experts&rsquo, preferences irrespective of the number of the criteria that have the same significance and the possibility of the transformation of the BWM-I into the traditional BWM (should there be a unique best/worst criterion). To present the applicability of the BWM-I, it was applied to defining the weight coefficients of the criteria in the field of renewable energy and their ranking.

The cash flow of a company is a key element for the firm value. The firm value of a company is depending largely on the ability to generate cash flows. In other words, a company’s firm value is calculated by using cash flows. Financial performance analysis helps companies in effective decision-making, planning, and auditing functions. Traditional ratio analysis uses the statement of financial position (balance sheet) and the profit and loss statement (income statement) to measure financial performance. However, the income statement of a company just shows the accounting profits. Depending on this, traditional ratios can sometimes be over or underestimated on measuring financial performances. To provide a better picture of a company’s financial strength and measure sensitive financial performance cash flow ratios were suggested instead of traditional ratios. Within this context, the aim of this study is to measure and compare the financial performance of Borsa İstanbul tourism companies with the use of cash flow based ratios. Ten tourism companies listed on BIST were evaluated by the Entropy-MAIRCA hybrid model. To achieve this, cash flow based eleven ratios were calculated within the indicators of liquidity, efficiency, profitability, and solvency (leverage). To calculate ratios a-year balance sheet, additionally, income statement and cash flow statement table gathered from Public Disclosure Platform. Findings of the Entropy method showed that the most important criteria were cash ratio, cash to sales, and cash to long term debts. According to the ranking results obtained by the MAIRCA method, the best tourism company is E. It was followed by G and D.

Temiz bir enerji kaynağı olan ve doğal dengeyi bozmayan rüzgâr enerjisi, günümüzün en önemli yenilenebilir enerji kaynaklarından birisidir. Bu çalışmada rüzgâr çiftlikleri için uygun yer tespitinde kullanılan faktörler, oldukça yeni bir sübjektif ağırlıklandırma yöntemi olan FUCOM (Full Consistency Method-Tam Tutarlılık Yöntemi) yöntemi kullanılarak analiz edilmiştir. FUCOM, doğrusal programlama temelli bir yöntemdir ve diğer ağırlıklandırma yöntemlerinden daha az ikili karşılaştırmaya ihtiyaç duyar. Çalışmadaki değerlendirme modeli, üç temel boyutu ve on iki faktörü dikkate almaktadır. Bulgular, bir rüzgâr çiftliği sahasının tercih edilmesinin büyük ölçüde rüzgâr potansiyeline ve yerleşim yerlerine olan uzaklığına bağlı olduğunu göstermiştir. Ayrıca önerilen yöntemin tutarlılığını ve kullanışlılığını göstermek için bir duyarlılık analizi yapılmıştır. Bu çalışmanın sonuçları rüzgâr enerjisine yönelik politika belirlemekte kullanılabilir.