Search

Bilgisayar teknolojilerindeki hızlı gelişmeler, bilgi iletişim teknolojileri (BİT) kavramını ortaya çıkarmıştır. Devletler bilgi iletişim teknolojilerine yönelik altyapılarını iyileştirmek ve geliştirmek için adımlar atmaktadırlar. Bu bağlamda, ülkelerin BİT düzeylerini değerlendirmek kritik bir konudur. Bu motivasyonla hazırlanan çalışmada, G7 ülkelerinin BİT performansı BİT istihdam, BİT yatırım, BİT katma değer, BİT mal ihracı, internet erişimi ile evden bilgisayara erişim kriterlerine göre analiz edilmektedir. Önce, bu kriterlerin göreli ağırlıkları hem MEREC hem de CRITIC objektif ağırlıklandırma yöntemleri ile hesaplanmakta ve birleştirilmiş bir önem düzeyi belirlenmektedir. Daha sonra ise ülkelerin BİT performans düzeylerini belirlemek için CoCoSo yöntemi kullanılmaktadır. Elde edilen sonuçlar, BİT malları ihracı (0,3137) ile internet erişiminin (0,1581), G7 ülkelerinin BİT düzeylerinin gelişimi açısından en önemli kriterler olduğunu ortaya koymaktadır. Ayrıca bulgulara göre ABD (6,0238) ve İngiltere (3,4215), BİT gelişim düzeyi açısından en iyi ülkelerdir. Buna karşın İtalya ve Kanada ise son sıralarda yer almaktadırlar.

Abstract Crypto assets have become increasingly popular in recent years due to their many advantages, such as low transaction costs and investment opportunities. The performance of crypto exchanges is an essential factor in developing crypto assets. Therefore, it is necessary to take adequate measures regarding the reliability, speed, user-friendliness, regulation, and supervision of crypto exchanges. However, each measure to be taken creates extra costs for businesses. Studies are needed to determine the factors that most affect the performance of crypto exchanges. This study develops an integrated framework, i.e., fuzzy best–worst method with the Heronian function—the fuzzy measurement of alternatives and ranking according to compromise solution with the Heronian function (FBWM’H–FMARCOS’H), to evaluate cryptocurrency exchanges. In this framework, the fuzzy best–worst method (FBWM) is used to decide the criteria’s importance, fuzzy measurement of alternatives and ranking according to compromise solution (FMARCOS) is used to prioritize the alternatives, and the Heronian function is used to aggregate the results. Integrating a modified FBWM and FMARCOS with Heronian functions is particularly appealing for group decision-making under vagueness. Through case studies, some well-known cryptocurrency exchanges operating in Türkiye are assessed based on seven critical factors in the cryptocurrency exchange evaluation process. The main contribution of this study is generating new priority strategies to increase the performance of crypto exchanges with a novel decision-making methodology. “Perception of security,” “reputation,” and “commission rate” are found as the foremost factors in choosing an appropriate cryptocurrency exchange for investment. Further, the best score is achieved by Coinbase, followed by Binance. The solidity and flexibility of the methodology are also supported by sensitivity and comparative analyses. The findings may pave the way for investors to take appropriate actions without incurring high costs.

Abstract The risk profiles of investors play an important role in the success of derivative products investments. It is also necessary to determine the appropriate investor profile according to the conditions of a country. This protects investors from major losses. Therefore, there is a strong need for a new study that analyzes the risk profiles of derivative products in emerging economies. This study aims to identify the most appropriate investor risk profile for derivative instruments in emerging economies. It constructs a novel decision-making model. In this model, the facial action coding system, quantum theory, spherical fuzzy sets, and multi-stepwise weight assessment ratio analysis (M-SWARA) methodology are integrated to minimize uncertainty in this process. First, three main participants of derivatives for financial technology investors are evaluated using the quantum spherical fuzzy M-SWARA technique. After that, seven emerging economies are ranked based on this performance using quantum spherical fuzzy technique for order of preference by similarity to ideal solution. The main contribution is that an appropriate investor profile is identified for financial derivative investments in emerging economies. One of the important originalities of this study is the development of a new technique called M-SWARA by making some improvements to the classical stepwise weight assessment ratio analysis method. It is concluded that hedging is the most appropriate purpose for making investments in derivative products in emerging economies. It is also identified that China has the greatest performance among the seven emerging economies regarding the appropriate purpose for making derivative investments. For the effective management of this problem in these countries, it is recommended to prevent the speculative use of derivative products with legal regulations.

The superiority of BWM over other weighting methods for obtaining the weight values of the attributes is that it achieves high-confidence results with a reasonable number of pairwise comparisons. Although the best-worst method (BWM) is a well-known multi-criteria decision-making (MCDM) method that has been successfully utilized in almost all scientific areas to solve challenging real-life problems, no research has comprehensively examined the state-of-the-art in this regard. The present study depicts a detailed overview of publications concerned with BWM during the period 2015–2022. Based on the information obtained from the Scopus database, this work presents a big picture of current research on BWM. In other words, this paper analyzes the existing literature about BWM and identifies thematic contexts, application areas, emerging trends, and remaining research gaps to shed light on future research agendas aligning with those gaps. Further, the most recent BWM research is analyzed in the top ten scientific areas, from engineering to materials science. “Engineering”, “computer science”, and “business, management, and accounting” are the hottest fields of BWM research. China is the most active country regarding “engineering” and “computer science”, whereas India is the leader in “business, management, and accounting”. The study also reveals that there are still many research gaps in BWM research. The big picture taken in this study will not only showcase the current situation of BWM research but will also positively impact the direction and quality of new research.

Abstract A large number of materials and various criteria fashion material selection problems as complex multi-criteria decision-making (MCDM) problems. This paper proposes a new decision-making method called the simple ranking process (SRP) to solve complex material selection problems. The accuracy of the criteria weights has a direct impact on the outcomes of the new method. In contrast to current MCDM methods, the normalization step has been eliminated from the SRP method as a potential source of producing incorrect results. The application of the method is appropriate for situations with high levels of complexity in material selection because it only considers the ranks of alternatives in each criterion. The first scenario of vital-immaterial mediocre method (VIMM) is used as a tool to derive criteria weights based on expert assessment. The result of SRP is compared with a number of MCDM methods. In order to evaluate the findings of analytical comparison, a novel statistical measure known as compromise decision index (CDI) is proposed in this paper. CDI revealed that the MCDM methods’ outputs for solving the material selection could not be theoretically proven and requires to be evaluated through practice. As a result, the dependency analysis-an additional innovative statistical measure is introduced to demonstrate the reliability of MCDM methods by assessing its dependency on criteria weights. The findings demonstrated that SRP is extremely reliant on criteria weights and its reliability rises with the number of criteria, making it a perfect tool for solving challenging MCDM problems.

This study aimed to examine the economic contribution and financial performance of the real sector in Turkey. Using the real sector company accounts published by the Central Bank of the Republic of Turkey (CBRT), seventeen sectors were analysed with the CRITIC-based MAIRCA method. The economic contribution was evaluated with sub-indicators to economic growth, employment, and entrepreneurship; financial performance was evaluated with liquidity, financial structure, turnover and profitability indicators. The findings revealed that manufacturing sector provided the highest contribution to total economy and in all sub-indicators. While the sectors with the lowest contribution in the sub-indicators differed, it was determined that the sub-sector with the lowest total contribution was real estate activities sector. In terms of total financial performance and liquidity, financial structure, and profitability sub-indicators, human health and social work activities, and according to turnover ratios energy supply sector have the highest performance. The study revealed that the sectors with an increased contribution to the economy and those with high financial performance differentiate. Lastly, it has been seen that sectors with high economic contribution exhibit weak financial performance. The findings were checked by sensitivity analysis and proposed method produces consistent results against weight changes and the model is reliable.

Economic freedom indicators create a beneficial and suitable guide and a crucial reference for investors, policymakers, lenders, and market researchers worldwide. In light of these indicators, the economic freedom performances of countries can be determined. The Heritage Foundation annually releases a ranked list of the country based on their performance in terms of fourteen economic freedom criteria with equal weights through a simple aggregation approach. According to an average-based aggregator, equal weight of economic freedom criteria and calculating rank of countries cannot be a completely reliable approach. Thus, this work establishes a composite index system in the form of a decision support system that employs the method based on the removal effects of criteria (MEREC) and the double normalization-based multi-aggregation (DNMA) to specify the economic freedom levels of the OPEC countries. MEREC obtains the importance weights of indicators without the interference of any stakeholder or decision-makers. Afterward, DNMA, as a novel ranking multi-criteria method, is applied to sort countries based on their performance against all economic freedom criteria. This is the first attempt in the literature to calculate the index of economic freedom utilizing an integrated multi-criteria decision support model. Whereas “investment freedom” is the most significant indicator of economic freedom, the UAE is in the best position in terms of economic freedom among OPEC countries. A fourphased sensitivity control is also performed so as to verify the robustness and usefulness of the developed decision tool.

Sürdürülebilir tedarik zinciri yönetimi, ekonomik performans, ekolojik koruma ve sosyal konuları kapsamasından dolayı hem araştırmacılardan hem de firmalardan büyük ilgi görmektedir. Bir tedarik zincirinin sürdürülebilirlik performansını artırmak için zincirin üyeleri, tedarikçilerini kendi stratejilerine göre dikkatle seçmelidir. Bu nedenle sürdürülebilirliğin üç boyutu (ekonomi, çevresel ve sosyal) bağlamında sürdürülebilir tedarikçi seçimini gerçekleştirmek için etkili bir karar aracına ihtiyaç duyulur. Bu çalışma, tedarikçilerin sürdürülebilirlik performansını değerlendirmek için çok kriterli bütünleşik bir karar aracı önermektedir. Önerilen model, FUCOM ve MAIRCA yöntemlerini 3 sürdürülebilirlik boyutu, 12 alt kriter ve 5 sürdürülebilir tedarikçiyi göz önünde bulunduracak şekilde entegre etmektedir. Ayrıca, önerilen modelin uygulanabilirliğini göstermek için bir otomobil yedek parça firmasında bir çalışma gerçekleştirilmiştir. Bulgulara göre her bir boyut için en önemli alt kriterler ürün fiyatı, bilgilendirme ve çevre yönetim sistemi olarak bulunmuştur. Sonuç olarak, FUCOM-MAIRCA modeli sürdürülebilir tedarik zinciri yönetiminde uygun tedarikçileri değerlendirmek ve seçmek için uygulanabilir. Ayrıca model, pazarlama, yönetim ve finans gibi diğer işletme alanlarında da uygulama potansiyeline sahiptir.

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.

Integrating green approaches and digital marketing strategies for Information and Communication Technologies (ICTs), which reduce environmental risks to desired levels by eliminating emissions and pollution, is considered one of the most promising solutions for logistics companies. The study strives to bring a practical and applicable solution to the decision problem involving the selection of indicators for green approaches and digital marketing strategies for ICTs in the logistics sector. An integrated Fermatean Fuzzy Step-wise Weight Assessment Ratio Analysis (FF–SWARA) and Fermatean Fuzzy Complex Proportional Assessment (FF–COPRAS) methodology is applied to evaluate green approaches and digital marketing strategies. Concerning the findings, the foremost criterion is “data management,” whereas the best strategy is “programmatic advertising.” To the best of the authors’ knowledge, there is no other study that both offers a strategy selection for the logistics industry and considers environmental protection, sustainability, digital transformation, energy costs, and social and economic factors. The study is a part of ongoing research on productivity, sustainability, the environment, digitization, recycling and estimating levels of waste reduction, as well as business practices, competitiveness and ensuring employee satisfaction and resource efficiency. Also, it investigates the similarities and dissimilarities in the green approach practices of business in logistics and determines the extent to which these practices could be reflected. It is expected to ensure a roadmap for green approach practices and to support sustainable and ecological awareness efforts for ICTs in the logistics sector. Logistics companies can select an integrated digital strategy based on green informatics that suits them using the decision model employed in this study, which can handle uncertainties effectively. In this regard, the study’s findings, which focus on reaching customers and the most precise target audience in digital applications for businesses, are critical for developing strategy, plan and process.

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.

This study aims to help managers develop a proper strategy and policy for their company’s future. After the global COVID-19 pandemic, developed countries decided to change their production and relocate and re-industrialize. The U.S.’s big electronics and automobile companies are not an exception to this rule. The lithium batteries are the main instrument of mobile phone and electric vehicles. The leading lithium battery supplier for the U.S mobile phone companies is China. Argentina, Bolivia, and Chile (in South America) have some of the largest lithium mines in the world; these countries are known as the lithium triangle. Among the 86 million tonnes of lithium resources worldwide, 49.9 million tonnes exist in this area. The researchers in this study surveyed the best country for constructing a battery for companies in the U.S. Because of the growth of electric vehicles and their use of the lithium battery, the world is facing astronomical prices for lithium. To emphasize this issue and help managers create good policy, this study combined multiple methods. The improved suitability-feasibility-acceptability (SFA) strategy is integrated with the Bayesian best-worst method (BBWM) and measurement of alternatives and rankings according to compromise solution (MARCOS) multicriteria methods to determine the best destination. For comparison, based on the SFA strategy, seven criteria are introduced: commercially viable reserves, national minimum wage, corporate income tax, accessibility to mining companies, accessibility to the waterway, population, and political stability index. The Bayesian BWM analysis reveals that the foremost factor is corporate income tax, whereas MARCOS’s findings indicate that Chile is the best country to construct the lithium battery industry. To verify the proposed approach, a comparison analysis also is performed.

Maddi güçlükler, engelli bireye sahip ailelerin standart bir yaşam sürmelerini zorlaştırmaktadır. Bu çalışmada, temel tüketim grupları göz önünde bulundurularak engelli bireye sahip ailelerin, engelli bireye sahip olmayan aileler gibi hayatlarını sürdürebilmeleri için gerekli finansal desteği tahmin etmek üzere bir model geliştirilmiştir. Çalışmanın amacı, ana tüketim gruplarını göz önünde bulundurarak engelli bireye sahip ailelerin diğer ailelerle aynı yaşam standartlarına sahip olmaları için gereken finansal desteğin belirlenmesidir. Analizlerde, Türkiye İstatistik Kurumu (TÜİK) tarafından hazırlanan Hanehalkı Bütçe Anketi (HBA) verileri kullanılmıştır. Analizlere 101.504 hane dahil edilmiştir. Modelin geliştirilmesi sırasında AHP yöntemi kullanılmıştır. Ayrıca önerilen modelin kararlılığını göstermek için bir duyarlılık analizi yapılmıştır. Önerilen model, farklı sayıda bireye sahip aileleri de dikkate almaktadır.

Nowadays, cities are developing differently according to their needs, limitations and certain strategic plans. Moreover, conurbation areas will be more common in so many countries like Chile when there are two or more cities developing one next to another, leaning on each other. In this atmosphere, typical residents live in a region or a neighborhood based on certain criteria, so they know how and where they are going to live. From another point of view, a newcomer is usually faced with a city full of contrasts which make things completely and surprisingly complicated. In order to illustrate this, a real case was selected based on the research field, qualitative and quantitative (real) data. The Coquimbo-La Serena conurbation and it’s regions as “Comuna (in Chile)” is a really suitable case to show the complexity of the study. In order to face the challenge, a new hybrid Multiple-Attribute Decision-Making (MADM) method is introduced based on the Best-Worst Method (BWM) and Multi-Attributive Ideal-Real Comparative Analysis (MAIRCA). The five best different neighborhoods as Comunas of the conurbation were analyzed based on the two main scenarios: having a private car or using only public transportation. To obtain more reliable results, a sensitivity analysis was made so as to determine the behavior of the proposed model against weight changes. Besides, the final results were compared with the other MADM methods, for example: Multi-Attributive Border Approximation Area Comparison (MABAC), VIsekriterijumsko KOmpromisno Rangiranje (VIKOR) and COmbinative Distance-based ASsessment (CODAS).

Predicting stock market (SM) trends is an issue of great interest among researchers, investors and traders since the successful prediction of SMs’ direction may promise various benefits. Because of the fairly nonlinear nature of the historical data, accurate estimation of the SM direction is a rather challenging issue. The aim of this study is to present a novel machine learning (ML) model to forecast the movement of the Borsa Istanbul (BIST) 100 index. Modeling was performed by multilayer perceptron–genetic algorithms (MLP–GA) and multilayer perceptron–particle swarm optimization (MLP–PSO) in two scenarios considering Tanh (x) and the default Gaussian function as the output function. The historical financial time series data utilized in this research is from 1996 to 2020, consisting of nine technical indicators. Results are assessed using Root Mean Square Error (RMSE), Mean Absolute Percentage Error (MAPE) and correlation coefficient values to compare the accuracy and performance of the developed models. Based on the results, the involvement of the Tanh (x) as the output function, improved the accuracy of models compared with the default Gaussian function, significantly. MLP–PSO with population size 125, followed by MLP–GA with population size 50, provided higher accuracy for testing, reporting RMSE of 0.732583 and 0.733063, MAPE of 28.16%, 29.09% and correlation coefficient of 0.694 and 0.695, respectively. According to the results, using the hybrid ML method could successfully improve the prediction accuracy.

Corporate governance applications and firms’ ability level in putting these applications taken into considerations have started to be influential in making investment decisions. In addition to financial performances of the firms, corporate governance application levels also getting important day by day. The objective of this study is to determine inefficiency reasons of the firms constituting the Corporate Governance Index of Turkey. To this end, in the first stage of the study, annual data of the 21 companies trading on Borsa Istanbul (BIST) XKURY have been analyzed with Data Envelopment Analysis (DEA). In the second stage, the Malmquist Total Factor Productivity (MTFP) Index of the firms has been calculated. According to the results, none of the index firms in the financial sector was able to show full operational efficiency between 2010 and 2013. Additionally, the findings indicate that the firms were not managed efficiently, operated in unfitting scales and could have produced products with less input. Moreover, this study has revealed that one fourth of the firms experienced technological decline.

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’ 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’ 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.

Mobile banking (M-banking) which integrates software, hardware, and human is a new platform for banks. Determining the performance of M-banking services helps bank practitioners identify better policy to improve their positions. The aim of this study is to develop an integrated model for evaluating M-banking services by two methods, namely the Fuzzy Analytic Hierarchy Process (FAHP) with an extent analysis approach and ARAS (Additive Ratio ASsessment). In this study, the priority weights obtained through the FAHP are combined with the ARAS method to as­sess and rank the M-banking services. Moreover, in order to verify the applicability of this proposed model, a case study in Turkey is offered. The findings indicate that facilitating conditions play the most determining role in the adoption of the M-banking, followed by self-efficacy, privacy risk, and security risk. Consequently, the proposed model helps to overcome difficulties in M-banking service evaluation process and increases the efficiency of the M-banking service activities. Besides, the case study validates that the proposed model is an effective and efficient decision making tool for the evaluation of M-banking services under fuzzy environments. First published online: 23 Apr 2017

In the global competitive environment, companies not only improve the quality of service and increase the efficiency, they also decrease the cost by means of third-party logistics (3PLs). 3PLs, therefore, is an important strategy for companies desiring to gain a competitive advantage and 3PLs provider selection plays a critical role for the success of outsourcing. Nevertheless, the level of uncer­tainty in the selection process is relatively high and need to be carefully considered. Hence, in order to select a proper 3PLs provider, integration of the Fuzzy AHP and Evaluation based on Distance from Average Solution (EDAS) has offered a novel integrated model, in which Fuzzy AHP is used for calculating priority weights of each criteria and EDAS is employed to achieve the final ranking of 3PLs providers. Besides, in order to demonstrate the applicability of the proposed model, it is validated by a case study. Cost together with quality, and professionalism are found to be the most important factors for 3PLs provider selection. Consequently, the advantage of this model is that it is simple to apprehend and easy to apply. The use of the proposed model leads to the selection of suitable alternative successfully in other selection problems. First published online: 23 Apr 2017

Aktarma problemi genellikle ulaştırma problemiyle karıştırılabilmektedir. Ulaştırma problemi ürünlerin, sadece tedarik noktalarından talep noktalarına doğrudan iletilmesine izin verirken, aktarma problemi ürünlerin gerek tedarik noktalarının gerekse talep noktalarının kendi içinde iletilmesini sağlar. Aktarma problemlerinin amacı, kapasiteli arz noktaları kullanılarak talep noktalarının isteklerini karşılamak için en iyi yolu bulmaya çalışmaktır. En iyi yolu bulmaya çalışırken, ürünleri taşımadan kaynaklanan değişken maliyetler de dikkate alınmaktadır. Çalışmanın amacı, işbirlikçi oyun teorisi yaklaşımıyla aktarma probleminin çözümüne yönelik bir yaklaşım sunmaktır. Problemin çözümünde Shapley değerinden yararlanılmıştır. Çalışmada gerçekleştirilen uygulamada iki tedarikçi, bir dağıtım merkezi ve iki müşterinin yer aldığı lojistik bir ağ yapısı ele alınmıştır. Uygulamada aynı zamanda işbirlikçi olmayan (non-cooperative), seçimli işbirlikçi (selected cooperative) ve tam işbirliği (cooperative) ortamda üç oyunculu bir yapı vardır. Çalışma, gerçek hayatta tedarik zinciri stratejisine göre karar vericinin nasıl doğru bir pozisyon alması gerektiği konusunda yol gösterici olabilecek niteliğe sahiptir. Ayrıca çalışmada, geleneksel ağ çözümü ile üç oyunculu ve tam işbirliği olan bir ortamda Shapley değerinin hassaslığı ve etkin bir çözüm önerdiği ortaya konulmuştur.

The aim of this study is to determine the preferences of university students when buying mobile phone line GSM operators (Turkcell, Vodafone, Avea) with the analytic hierarchy process method. Students compared each decision criterion and GSM operators on the base of each criterion using analytic hierarchy process importance level scale. Weighted score of decision criteria were calculated according to the students’ evaluation. The rank of the preferred GSM operators is determined first according to each criterion and then to all criteria as a whole. Ranking for preference of GSM operators as decision criteria is as follows: Based on calling charge criteria Vodafone-Avea-Turkcell; based on calling area criteria Turkcell-Vodafone-Avea; based on family’s GSM operator subscription criteria Turkcell-Vodafone-Avea; based on service quality criteria Turkcell-Vodafone-Avea; based on subscription charge criteria Vodafone-Avea-Turkcell; When these five criterion evaluated as a whole ranking of GSM operators is Turkcell-Vodafone-Avea.

The quality of websites can directly influence bank's effectiveness. Therefore, the effective evaluation of the quality of bank websites is a point of concern for customers, owners, and researchers. The primary goal of the study is to propose a hybrid model of AHP and COPRAS-G methods for evaluating the website quality of banks. Furthermore, this study sheds light on understanding weights of evaluation criteria related to quality of bank websites. In this study, the weights of the evaluation criteria are computed by AHP method. Next, COPRAS-G is used to assess the quality levels of the websites and to rank them. A case study of evaluating the quality of bank websites of seventeen banks in Turkey is used to demonstrate the applicability and the effectiveness of this model. Empirical findings show that banks in Turkey utilize the Internet to its full potential to improve their websites. Furthermore, Garanti Bankasi has the best overall performance, followed by TEB, and Ziraat Bankasi. Additionally, the top-five evaluation criteria in order of importance are relevance, richness, understandability, navigability, and response time. Overall, the results show that this model provides a comprehensive and systematic approach that quantitatively measures a website's quality. First published online: 08 May 2014