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Complex Pythagorean fuzzy set (CPFS) is a massive influential principle for managing ambiguity and inconsistent information in genuine life dilemmas. To determine the relationship among any number of attributes, the Hamy mean (HM) operators based on interaction operational laws are very dominant and massive flexible to manage awkward and problematic information. This study aims to combine the complex Pythagorean fuzzy (CPF) information with interaction HM operators to initiate the CPF interaction HM (CPFIHM) operator, CPF interaction weighted HM (CPFIWHM) operator, CPF interaction dual HM (CPFIDHM) operator, CPF interaction weighted dual HM (CPFIWDHM) operator and their powerful properties. Additionally, a decision-making strategy for determining the security threats in the computer is elaborated under the interaction of HM operators based on the CPF setting. Numerous examples are illustrated with the help of presented operators to determine the consistency and flexibility of the investigated operators. Finally, with the help of sensitivity analysis, advantages, and geometrical representation, the supremacy, and efficiency of the presented works are also elaborated.

The striking theory of ELECTRE III approach, being a marvelous strategy to deal with pseudo criterion, prevails over the traditional variants of ELECTRE method and other decision-making approaches for veracious decision-making. The noticeable efficiency and broader space of complex Pythagorean fuzzy model make it more significant and dominant for modeling two dimensional imprecise knowledge. The remarkable contribution of this study is to present a high aptitude variant of ELECTRE method by taking the advantage of the flexible structure of complex Pythagorean fuzzy sets closely following the outranking principles of ELECTRE III method. The proposed complex Pythagorean fuzzy ELECTRE III method is accredited to employ the theory of ELECTRE III technique to excellently deal with pseudo criterion as well as the two dimensional imprecise data for authentic decision-making. The proposed methodology uses three different threshold values, including preference, indifference and veto threshold values, to check the preference relation between alternatives. The presented strategy is applied to a case study for material selection to get the befitting decision. The comparative study with Pythagorean fuzzy ELECTRE III method is also included in this article to verify its decision-making aptitude.

Modelling the reliability information in decision making process is an important issue to inclusively reflect the thoughts of decision makers. The Evaluation Based on Distance from Average Solution (EDAS) and Analytic Hierarchy Process (AHP) are frequently used MCDM methods, yet their fuzzy extensions in the literature are incapable of representing the reliability of experts’ fuzzy preferences, which may have important effects on the results. The first goal of this study is to extend the EDAS method by using Z-fuzzy numbers to reinforce its representation ability of fuzzy linguistic expressions. The second goal is to propose a decision making methodology for the solution of fuzzy MCDM problems by using Z-fuzzy AHP method for determining the criteria weights and Z-fuzzy EDAS method for the selection of the best alternative. The contribution of the study is to present an MCDM based decision support tool for the managers under vague and imprecise data, which also considers the reliability of these data. The applicability of the proposed model is presented with an application to wind energy investment problem aiming at the selection of the best wind turbine. Finally, the effectiveness and competitiveness of the proposed methodology is demonstrated by making a comparative analysis with the Z-fuzzy TOPSIS method. The results show that the proposed methodology can not only represent experts’ evaluation information extensively, but also reveal a logical and consistent sequence related to wind turbine alternatives using reliability information.

Innovations in technology emerged with digitalization affect all sectors, including supply chain and logistics. The term “digital supply chain” has arisen as a relatively new concept in the manufacturing and service sectors. Organizations planning to utilize the benefits of digitalization, especially in the supply chain area, have uncertainties on how to adapt digitalization, which criteria they will evaluate, what kind of strategies should be developed, and which should be given more importance. Multi-criteria decision making (MCDM) approaches can be addressed to determine the best strategy under various criteria in digital transformation. Because of the need to capture this uncertainty, fermatean fuzzy sets (FFSs) have been preferred in the study to widen the definition domain of uncertainty parameters. Interval-valued fermatean fuzzy sets (IVFFSs) are one of the most often used fuzzy set extensions to cope with uncertainty. Therefore, a new interval-valued fermatean fuzzy analytic hierarchy process (IVFF-AHP) method has been developed. After determining the main criteria and sub-criteria, the IVFF-AHP method has been used for calculating the criteria weights and ranking the alternatives. By determining the most important strategy and criteria, the study provides a comprehensive framework of digital transformation in the supply chain.

Risk assessment takes place depending on the expertise and subjective linguistic assessments of experts. Expert judgements are collected via a questionnaire or an interview including qualitative data. Pessimistic or optimistic status of experts can affect their perceptions on risk. Furthermore, expert judgments are affected by questions’ structure based on whether it is a positive type question (e.g., ‘What is the occurrence probability of the accident?) or a negative type question (e.g., ‘What is the non-occurrence probability of the accident?). All of these cases create uncertainties in the risk assessment process. For this reason, there are various studies using fuzzy risk analysis models to address these uncertainties in risk assessment. However, there is not any risk assessment tool that considers the uncertainties caused by the factors mentioned above, simultaneously. Therefore, in this paper, we introduce the concept of decomposed fuzzy sets (DFS) to model human thoughts and perceptions in a more realistic and detailed way through optimistic and pessimistic membership functions. We present the basic operations on decomposed fuzzy sets and their properties. To demonstrate the utility of the proposed method, the method is applied to operational risk analysis in business processes. The data used in the application are collected from the managerial board of a construction company. The application results and advantages of the proposed method are presented together with a comparative analysis.

Present worth (PW) analysis is an important technique in engineering economics for investment analysis. The values of PW analysis parameters such as interest rate, first cost, salvage value and annual cash flow are generally estimated including some degree of uncertainty. In order to capture the vagueness in these parameters, fuzzy sets are often used in the literature. In this study, we introduce interval-valued intuitionistic fuzzy PW analysis and circular intuitionistic fuzzy PW analysis in order to handle the impreciseness in the estimation of PW analysis parameters. Circular intuitionistic fuzzy sets are the latest extension of intuitionistic fuzzy sets defining the uncertainty of membership and non-membership degrees through a circle whose radius is r. Thus, we develop new fuzzy extensions of PW analysis including the uncertainty of membership functions. The methods are given step by step and an application for water treatment device purchasing at a local municipality is illustrated in order to show their applicability. In addition, a multi-parameter sensitivity analysis is given. Finally, discussions and suggestions for future research are given in conclusion section.

In Quality function deployment (QFD) approach, customers tend to express their needs in linguistic terms rather than exact numerical values and these needs generally contain vague and imprecise information. To overcome this challenge and to use the method more effectively for complex customer-oriented design problems, this paper introduces a novel intuitionistic Z-fuzzy QFD method based on Chebyshev’s inequality (CI) and applies it for a new product design. CI provides the assignment of a more objective reliability function. The reliability value is based on the maximum probability obtained from CI. Then, the expected values of lower and upper bounds of interval-valued intuitionistic fuzzy (IVIF) numbers are determined. A competitive analysis among our firm and competitor firms and an integrative analysis for the different functions of QFD is presented. The proposed Z-fuzzy QFD method is applied to the design and development of a hand sanitizer for struggling with COVID-19.

Milk-run is a delivery method allowing to move small quantities of a large number of different items with predictable lead times from various suppliers to a customer. The main goal is to minimize the transportation cost by minimizing the travel distance and by maximizing vehicle capacities. The effects of uncertainties in arrival times of vehicles and loading times of shipments should also be considered in modeling the milk-run problems. In this paper, a multi-objective linear programming model, an ordinary fuzzy multi-objective linear programming model and an intuitionistic fuzzy multi-objective linear programming model are proposed for the milk-run modeling under time window constraints. The proposed approaches are applied on the real-life data of Borusan Logistics which is one of the largest logistics firms in Turkey and the results are presented.

Linguistic terms are quite suitable to make evaluations in multiple criteria decision making problems since humans prefer them rather than sharp evaluations. When linguistic evaluations are used in the decision matrix instead of exact numerical values, fuzzy set theory can capture the vagueness in the linguistic evaluations. Ordinary fuzzy sets have been extended to many new types of fuzzy sets such as intuitionistic fuzzy sets, neutrosophic sets, spherical fuzzy sets and picture fuzzy sets. Spherical fuzzy sets are an extension of picture fuzzy sets whose squared sum of their parameters is at most equal to one. This paper develops a novel spherical fuzzy CRiteria Importance Through Intercriteria Correlation (CRITIC) method and applies it for prioritizing supplier selection criteria. Supplier selection is one of the most critical aspects of any organization since any mistake in this process may cause poor supplier performance and inefficiencies in the business processes. Supplier selection is a multi-criteria decision making problem involving several conflicting criteria and alternatives. A numerical illustration of the proposed method is also given for this problem.

Both national and international encouragements for research and development (R&D) projects have been growing worldwide. Since R&D projects include various uncertainties related to time, technology, finance, and knowledge, risk management studies are highly significant for the success of these projects. In risk management, all of the potential actions that might have negative impacts on the processes or outputs of a project should be determined, and if it is possible, their negative impacts should be reduced before the project starts. In this study, after risks in R&D projects are determined, the alternative projects are prioritized with respect to these risks by using an approach based on interval-valued intuitionistic fuzzy AHP and fuzzy information axiom. Interval-valued Intuitionistic Fuzzy Analytic Hierarchy Process (IVIF AHP) is used to determine the importance degrees of the determined risk factors while fuzzy information axiom is used to evaluate R&D projects considering these risk factors. It is revealed that the most important risk is “Abnormal changes in cost” while the least important one is “Deficiencies in contract articles”.

The REGIME method is an easy to understand techniques which is based on pairwise comparisons and which can use qualitative data for decision making problems. The steps of the technique are simple and can be easily adopted to complex decision problems. Classical REGIME techniques use crisp numbers to evaluate qualitative evaluations. In this paper we propose Pythagorean Fuzzy REGIME (PF-REGIME) techniques which integrates Pythagorean Fuzzy Sets with REGIME technique. The proposed PF-REGIME is applied to waste disposal site selection problem. The decision model is constructed for three alternatives and five criteria in order to demonstrate the performance of the proposed PF-REGIME method.

Process capability analysis (PCA) is a tool for measuring a process’s ability to meet specification limits (SLs), which the customers define. Process capability indices (PCIs) are used for establishing a relationship between SLs and the considered process’s ability to meet these limits as an index. PCA compares the output of a process with the SLs through these capability indices. If the customers’ needs contain vague or imprecise terms, the classical methods are inadequate to solve the problem. In such cases, the information can be processed by the fuzzy set theory. Recently, ordinary fuzzy sets have been extended to several new types of fuzzy sets such as intuitionistic fuzzy sets, Pythagorean fuzzy sets, picture fuzzy sets, and spherical fuzzy sets. In this paper, a new extension of intuitionistic fuzzy sets, which is called penthagorean fuzzy sets, is proposed, and penthagorean fuzzy PCIs are developed. The design of production processes for COVID-19 has gained tremendous importance today. Surgical mask production and design have been chosen as the application area of the penthagorean fuzzy PCIs developed in this paper. PCA of the two machines used in surgical mask production has been handled under the penthagorean fuzzy environment.

Companies started to determine their strategies based on intelligent data analysis due to stagey enhance data production. Literature reviews show that the number of resources where demand estimation, location analysis, and decision-making technique applied together with the machine learning method is low in all sectors and almost none in the shopping mall domain. Within this study’s scope, a new hybrid fuzzy prediction method has been developed that will estimate the customer numbers for shopping malls. This new methodology is applied to predict the number of visitors of three shopping malls on the Anatolian side of Istanbul. The forecasting study for corresponding shopping malls is made by using the daily signaling data from indoor base stations of large-scale technology and telecommunications services provider and the features to be used in machine learning models is determined by fuzzy multi criteria decision making method. Output revealed by the application of the fuzzy multi criteria decision making method enables the prioritization of features.

A circular intuitionistic fuzzy set (CIFS) recently introduced by Atanassov as a new extension of intuitionistic fuzzy sets is represented by a circle whose radius is r and whose center is composed of membership and non-membership degrees. The idea is similar to type-2 fuzzy sets, which are based on the fuzziness of membership functions with a third dimension. CIFSs help us define membership functions more flexibly, taking into account the vagueness in membership and non-membership degrees. In this study, TOPSIS, which is a multi-criteria decision-making (MCDM) method, is developed under circular intuitionistic fuzzy environment. The proposed CIF-TOPSIS method is applied to determine the most appropriate pandemic hospital location selection problem. Then, a sensitivity analysis based on criteria weights and the weight of the decision maker’s optimistic and pessimistic attitudes are conducted to check the robustness of the decisions given by the proposed approach. A comparative analysis with the single-valued intuitionistic fuzzy TOPSIS, Pythagorean fuzzy TOPSIS, picture fuzzy TOPSIS methods is also performed to verify the developed approach and to demonstrate its effectiveness.

Autonomous vehicles are one of the emergent advances of the new technology era that has the prospective to redesign transportation structures. Understanding and measuring the limitations of adopting autonomous vehicles and selecting the best autonomous vehicle based on different aspects is crucial for enhancing the adoption process. Defining the criteria and the appropriate evaluation methodology is very important for selecting the best autonomous vehicles. However, this selection process is a human judgment-based process where both benefit and cost criteria with imprecise linguistic assessments should be considered. The KEmeny Median Indicator Ranks Accordance (KEMIRA) method is a method that enables ranking the benefit and cost criteria independently. In this paper, a new KEMIRA method based on hesitant fuzzy linguistic term sets is defined. Hesitant Fuzzy Linguistic Term Sets (HFLTS) are newly utilized to represent the hesitancy of the decision-makers. The proposed new KEMIRA is approach the first study that defines the alternative scores and weights of the criteria via HFLTS. The computational steps of the new model are applied to autonomous vehicle selection. A real application is employed to show the applicability of the new KEMIRA method.

Models of Fuzzy Multi-Criteria Decision Analysis (FMCDA) are based, as a rule, on different approaches to fuzzy extension of source MCDA methods. For this, simplified models are used to approximate the functions of fuzzy variables with propagation of parametric fuzzy numbers (FNs) through all calculations. In this paper, authors suggest a novel approach to fuzzy extension of MCDA methods, for PROMETHEE-I/II, through development of fuzzy PROMETHEE-I/II (FPOMETHEE-I/II) models of different complexity: in addition to simplified models, the standard fuzzy arithmetic (SFA), and transformation methods (TMs) are implemented for assessing functions of FNs corresponding to these models. For ranking of alternatives, two defuzzification based, and one pairwise comparison ranking methods are implemented within the developed models. Special attention is paid to analysis of the overestimation problem, which can occur when using SFA in the presence of dependent variables in corresponding expressions, and to “proper fuzzy extensions” of PROMETHEE-I/II (i.e., results of all functions of FNs within the model are in accordance with the extension principle) based on TMs and, for some models, on the SFA. One of the key goals of this contribution is comparison of the distinctions in ranking alternatives by different FPROMETHEE-II models. It is demonstrated by evaluating a large number of scenarios based on Monte Carlo simulation that the probability of distinction in ranking alternatives by “proper” and “approximated” FPROMETHEE-II models may be considered as significant for ranking multicriteria problems. Another goal of this paper is analysis of the correctness of FPROMETHEE-I/II models with respect to the basic MCDA axiom related to ranking of dominated and dominating alternatives. Authors demonstrate that the basic axiom can be violated, in the general case, by all developed FPROMETHEE-I/II models and suggest an approach to fix this problem.

When a decision maker is not sure in assigning a value for a pairwise comparison, he/she should assign a fuzzy value such as ‘between 3 and 4’ or ‘around 5’. These expressions can be represented by fuzzy numbers, which make the use of fuzzy AHP methods possible. Each new fuzzy set extension has caused new fuzzy AHP method to be developed by researchers. INFUS conferences is a scientific arena that the researchers can present their new fuzzy AHP extensions and benefit the discussions during the sessions. This paper summarizes the latest fuzzy AHP/ANP extensions developed in the recent years at INFUS conferences.

This research article is devoted to present a decision-making approach pertaining the excellent tendencies of traditional TOPSIS method under the broader environment of complex spherical fuzzy sets (CSFSs). TOPSIS method is regarded as one of the authentic decision-making strategies that follows the scheme to point out the alternative acquiring favorable distances from the ideal solutions. On the other hand, the pre-eminent feature of the CSFS includes the tendency to handle both aspects of two-dimensional information involved in the satisfaction, abstinence and dissatisfaction nature of human decisions. This study aims to expand the number of multiple criteria group decision-making (MCGDM) techniques by presenting a strategy, named complex spherical fuzzy TOPSIS (CSF-TOPSIS) method that cumulates the novel features of complex spherical fuzzy sets with the potential of TOPSIS method. In proposed method, we merge the independent decisions of all experts about the capabilities of alternatives and priorities of criteria using the CSFWA operator. We rank the alternatives in an ascending order of revised closeness index, evaluated by deploying normalized Euclidean distance. We establish the proposed CSF-TOPSIS method by an explanatory numerical example for the selection of best water supply strategy for Nohoor village in Iran. Further, we conduct the comparative study with spherical fuzzy TOPSIS method and complex spherical fuzzy VIKOR method to explicate the adequacy of the proposed strategy and consistency of the results.

The purpose of this study is to develop an extension of CODAS method using picture fuzzy sets. In this respect, a new methodology is introduced to figure out how picture fuzzy numbers can be applied to CODAS method. COmbinative Distance-based Assessment (CODAS) is a new MCDM method proposed by Ghorabaee et al. Picture fuzzy sets (PFSs) are a new extension of ordinary fuzzy sets for representing human’s judgments having possibility more than two answers such as yes, no, refusal and neutral. Compared with other studies, the proposed method integrates multi-criteria decision analysis with picture fuzzy uncertainty based on Euclidean and Taxicab distances and negative ideal solution. ERP system selection problem is handled as the application area of the developed method, picture fuzzy CODAS. Results indicate that the new proposed method finds meaningful rankings through picture fuzzy sets. Comparative analyzes show that the presented method gives successful and robust results for the solutions of MCDM problems under fuzziness.

The membership function of a general type-2 fuzzy set is three-dimensional in order to incorporate its vagueness through the third dimension. Similarly, Circular intuitionistic fuzzy sets (CIFSs) have been recently introduced by Atanassov (2020) as a new extension of intuitionistic fuzzy sets, which are represented by a circle representing the vagueness of the membership function. CIFSs allow decision-makers to express their judgments including this vagueness. In this study, the TOPSIS method, which is one of the most used multi-criteria decision-making methods is extended to its CIF version. The proposed CIF-TOPSIS methodology is applied to the supplier selection problem. Then, a sensitivity analysis based on criteria weights is conducted to check the robustness of the proposed approach. A comparative analysis with single-valued intuitionistic fuzzy TOPSIS method is also performed to verify the developed approach and to demonstrate its effectiveness

Spherical fuzzy sets are the latest extension of the ordinary fuzzy sets. The main characteristic of the spherical fuzzy sets is satisfying the condition that the squared sum of the membership, nonmembership, and hesitancy degrees must be at least zero and at most one. In this research, by extending the classical linear assignment method to bi-objective linear assignment and integrating it with cosine similarity measure, we presented a novel beneficial method for solving multiple criteria group decision-making problems in the spherical fuzzy environment. A new concept for weighting the criteria, which is composed of positive and negative impacts (weights), is introduced. The proposed bi-objective model tries to maximize positive impacts and minimize the negative impacts simultaneously. In order to solve the bi-objective linear assignment model, [Formula: see text]-constraint method is applied. Therefore, a trade-off solution is formed between maximizing positive impacts and minimizing negative impacts. The applicability and validity of the proposed method are shown through an insurance options selection problem. To test the reliability and validity of the proposed method, comparative and sensitivity analysis are performed.

Sustainable energy selection has been a very popular problem among the researchers and various models including deterministic, probabilistic and fuzzy approaches have been developed for the solution of this problem. Fuzzy approaches to sustainable energy selection problems have been often handled in the literature. Aggregation operators for multi-expert decision making problems are an alternative solution technique for multi criteria decision making problems. Since neutrosophic and intuitionistic fuzzy aggregation operators are comparable extensions of ordinary fuzzy sets, they have been employed to aggregate multi-expert judgments. An illustrative energy selection problem is presented, solved by two approaches, and results are compared. The same linguistic data have been used for the comparison purpose.

This study presents a multi-experts multiple criteria decision making approach for quantitatively evaluating social sustainable development factors. The proposed model which integrates Z-fuzzy numbers and fuzzy AHP enables to weight and rank social sustainable development factors, which may give guidance to many sustainable development researches. In addition to the first usage of the Z-fuzzy numbers for the weighting decision of social sustainable development factors, another contribution of the study is presenting the Z-fuzzy numbers integrated AHP method with multi-experts which can be useful in many problems and applications containing uncertainty. The most important advantage of the Z-fuzzy numbers integrated AHP method is that it allows the degree of confidence of decision makers to be included to the calculations. An application of the proposed approach is also presented for prioritizing the social sustainable development factors based on the experts’ evaluations together with a sensitivity analysis.

Location-Based Systems enable novel business models that can locate a person and send an action or message to him/her. One of the most commonly adopted location-based business models is location-based advertisements. Companies can send customized messages to target customers by using location-based ads. The model is promising since the conversion rate of the customers is high. On the other side, since the customers can be targeted based on their locations and interests, the price of the advertisement should be modeled a dynamic pricing model. In this study, we propose a dynamic pricing model for location-based ads by using the Spherical Fuzzy AHP method.

Pythagorean fuzzy sets (PFS) are an extension of intuitionistic fuzzy sets introduced by Atanassov [1]. PFSs have the advantage of providing larger domains for assigning membership and non-membership degrees satisfying that their squared sum is at most equal to one. PFS have been often used in modeling the problems under vagueness and impreciseness in order to better define the problems together with the hesitancy of decision makers. Different human emotions and behaviors can be modeled in humanoid robots (HR) by fuzzy sets. In this paper, facial expressions of a humanoid robot are modeled depending on the degrees of the emotions. Larger degree of emotion causes a stronger indicator of the facial mimic.

Effective utilization of renewable energy sources is an essential component of countries’ sustainable development strategies. A thorough evaluation of renewable energy alternatives is required to assure maximum exploitation of resources. The evaluation of renewable energy sources is a complicated problem since many criteria, even some of them are conflicting, must be taken into account simultaneously. Pythagorean fuzzy sets are better able to reflect uncertainty and vagueness in an assessment process by providing a greater domain for decision makers to describe their opinions. Therefore, this study aims at prioritizing renewable energy alternatives by employing interval-valued Pythagorean fuzzy WASPAS method. The obtained results are compared to the results of intuitionistic type-2 fuzzy WASPAS, interval-valued intuitionistic fuzzy WASPAS and crisp WASPAS methods. Biomass is selected to be the best renewable energy alternative for Central Anatolia Region of Turkey.

The catastrophes due to widespread outbreaks create a long-standing distraction and have an accelerating transmission The uncontrolled outbreaks cause not only health-related problems but also supply chain related problems The outbreak caused by the coronavirus (COVID-19) shows how vulnerable the Healthcare systems and the supporting systems such as supply chains of the countries to such type of disasters Keeping high levels of inventory, especially for healthcare products, can be beneficial to overcome such shortage problems Nevertheless, keeping a high level of inventory can be costly, and the durability of the products creates a limit The decision-makers have to carefully decide the inventory levels by considering many factors such as the criticality of the product and the easiness of producing the product In this study, we try to develop a decision model for defining the inventory levels in Healthcare systems by considering multiple scenarios such as outbreaks A novel spherical regret based multi-criteria decision-making approach is developed and used for evaluating the total regret of not keeping stock of the healthcare equipment [ABSTRACT FROM AUTHOR] Copyright of Journal of Intelligent & Fuzzy Systems is the property of IOS Press and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission However, users may print, download, or email articles for individual use This abstract may be abridged No warranty is given about the accuracy of the copy Users should refer to the original published version of the material for the full abstract (Copyright applies to all Abstracts )

Limanlar, geçmiş çağlardan bu yana bulunduğu şehirlerin ekonomik gelişiminde çok önemli işlevler üstlenmiş ticari ve sosyal ünitelerdir. Bir liman şehri olan İstanbul’un ticari ve beşeri hayatında denizyolu ulaştırmasının dolayısıyla limancılığın ayrı bir yeri vardır. Tarihsel süreçte, -sırasıyla- Roma, Bizans ve Osmanlı İmparatorluğu gibi büyük medeniyetlere başkentlik yapan İstanbul, coğrafi ve stratejik konumu nedeniyle dünya ticaretinde her zaman önemli merkezlerden biri olmuştur. Asya ile Avrupa’yı birbirine bağlayan, Akdeniz-Ege-Karadeniz aksında kritik ve alternatifsiz bir geçiş olan doğal bir boğaza sahip olan İstanbul; tarih boyunca doğal bir liman olma işlevini sürdürmüştür. İstanbul’un çok yönlü hinterlandı ve dağıtım özelliği, hem Karadeniz Havzası hem de Ege/Akdeniz Havzası’na açılan bir liman şehri olmasını sağlamıştır. Bu çalışmada İstanbul il sınırları içerisinde günümüzde faaliyet gösteren ticaret ve yolcu limanları fonksiyonlarına göre sınıflandırılmış, İstanbul ve Marmara alt bölge limanları, ulaşım ve ticaret coğrafyası açısından değerlendirilerek, İstanbul bölgesi kaynaklı ithalat ve ihracat verileri incelenmiştir. Diğer taraftan, bölgenin ticaret yolları perspektifinde limanların sektörel gelişimleri için önerilerde bulunulmuştur

PurposeThe companies are struggling to collect invoices due to the decrease in the economic growth. This global trend does not only affect undeveloped countries, but it also has a strong impact on the developed countries. Improving the debt collection process become a significant element to maintain financial stability. The institutions that are specialized on collecting payments, debt collection agencies and their call centers, with their expertise in the field can improve the payment process. Yet, managing evaluating the performance of debt collection agencies is a very hard process that involves uncertainty and imprecision. Performance measurement (PM) is a combination of numerically expressed characteristics which give insight about the success or degree of accomplishment of an activity. PM can be handled in various levels such as individual, team, department or company. The aim of this study is to present a systematic and objective PM method for call centers.Design/methodology/approachIn this study, first an exploratory approach is used to understand the call center measurement problem. Several meetings are done with the representatives of both call center firms and the parent firms that outsource debt collection process. Simultaneously, a broad literature review is conducted. An iterative approach is selected to reach deeper knowledge on the process. New meetings are planned and scope of the literature review has changed based on this iterative approach. After these steps, the problem has been considered as the multi-criteria decision-making problem since more than one criteria should be considered for evaluating the performances of call centers. The result of the literature review and the meetings with experts show that defining the weights for the criteria is very crucial for evaluating the performances accurately. Collecting human judgment for defining the weights of call center criteria necessitates dealing with vagueness and uncertainty. The intuitionistic fuzzy sets excellent tools for representing uncertainty. Interval valued intuitionistic fuzzy sets can easily represent the human judgments. Thus, in this study, an intuitionistic fuzzy multi-criteria decision making approach is used to design the proposed methodology. Incomplete interval-valued intuitionistic preference relations are used to determine the weights of the indicators aggregating linguistic evaluations of the decision makers.FindingsThe proposed approach provides an objective calculation of performance measurement. In order to provide objectivity, indicator performance functions are proposed for the first time in this study. Nine different functions and related parameters are defined to objectively measure indicator performances.Originality/valueThe paper proposes an objective and easy-to-modify approach for call-center PM, which can be used by call center managers. It presents a new fuzzy multi-criteria decision-making (MCDM) method for call center performance evaluation, which can consider the multi-experts' judgments under vagueness and impreciseness, which may be conflicting and incomplete interval-valued intuitionistic fuzzy preference relations. Also nine new functions are defined for indicator performance.