Muhammet Enes Akpinar

One of the most critical decisions investors faces in capital markets is selecting the brokerage firm through which they will conduct their transactions. Especially for beginner investors, evaluating multiple criteria such as costs, service quality, and platform usability is of great importance. In this study, the Best-Worst Method (BWM) and the Measurement Alternatives and Ranking according to Compromise Solution (MARCOS) method, both of which are Multi-Criteria Decision-Making (MCDM) techniques, were employed to determine the most suitable brokerage firm for the new investor profile. Firstly, criteria were evaluated based on three different investor profiles, and criterion weights were determined using the BWM method. Subsequently, the performances of five brokerage firms were analyzed according to the established criteria set using the MARCOS method. According to the results of the analysis, Alternative One achieved the highest suitability coefficient (K₀) and was identified as the most appropriate brokerage firm for beginner investors. This study offers an original contribution to the literature by demonstrating how the combined use of the BWM and MARCOS methods can enhance decision-support processes in capital markets. Additionally, it proposes a systematic approach for facilitating the decision-making process for beginner investors.Keywords: Multi-Criteria Decision-Making, Capital Markets, MARCOS Method, BWM MethodJEL Classification: M10, D70, D81

Selecting the most suitable equipment for production is a complex decision-making problem due to the presence of multiple and often conflicting criteria. Decision makers must evaluate several alternatives and criteria simultaneously, which makes it difficult to identify the optimal choice. Although Many Multi-Criteria Decision-Making (MCDM) approaches have been proposed in the literature, most assume that the criterion values are precise and clearly define an assumption that rarely holds in real-world applications. To address this limitation, this study employs the fuzzy Choquet Integral method, which incorporates fuzzy logic to handle the uncertainty and subjectivity inherent in expert evaluations. Through this approach, decision makers can express their assessments using linguistic terms instead of precise numerical values, thereby reducing potential bias in subjective judgments. The proposed method was applied to a real-world industrial sewing machine selection problem in a textile company. Six alternative machines were evaluated across six criteria, using linguistic assessments provided by the production manager. The fuzzy Choquet Integral model was then used to aggregate these evaluations and determine the most suitable alternative. The results show that the proposed approach effectively models interaction among criteria and provides a realistic decision-support framework for equipment selection problems.

Purpose: This study aims to evaluate and identify the most suitable logistics service providers within the framework of Logistics 4.0, shaped by digital transformation and Industry 4.0 technologies. Logistics 4.0 seeks to optimize logistics processes using innovative technologies such as smart systems and big data analytics. In this context, selecting the right service provider is of strategic importance for businesses. This study intends to assist companies in making accurate decisions in this complex process. Method: The CRITIC (Criteria Importance Through Intercriteria Correlation) based WASPAS (Weighted Aggregated Sum Product Assessment) method was employed. The CRITIC method was used to determine the objective weights of the criteria, while the WASPAS method utilized these weights to calculate the overall performance scores of the alternatives. Findings: The results of the study reveal the key criteria that businesses should consider when selecting Logistics 4.0 service providers and identifying the top-performing service providers. Originality: This study highlights the advantages and effectiveness of using the combined CRITIC and WASPAS methods in the selection of service providers in the logistics sector. Additionally, it contributes to the literature on the selection of Logistics 4.0 service providers.

Underground dam site selection is the process of selecting locations for dams constructed for the storage and management of groundwater to ensure the sustainable use of water resources. Underground dams store groundwater by utilizing underground aquifers, enabling more efficient and effective utilization of water resources. Particularly, the importance of underground dams has been observed to increase with global warming. They play a crucial role in various aspects, especially during periods of drought, in meeting agricultural irrigation and drinking water needs, among others. The construction of underground dams requires the simultaneous consideration of numerous criteria, thus turning the construction process into a decision-making problem. This decision problem is referred to in the literature as a multi-criteria decision-making (MCDM) problem. In this study, the site selection problem for a underground dam to be established in the province of Izmir has been addressed. In the problem at hand, there are five different alternatives consisting of districts within the province of Izmir and ten different criteria. These criteria and alternatives were determined by experts. In the study, the weights of the criteria were determined using the MAIRCA method, and the EDAS method was used for the selection of alternative locations. As a result of the study, Kınık district was identified as the most suitable alternative among the selected districts.

The virus, which emerged in Wuhan, China, has taken the whole world under its influence in a short time. The World Health Organization declared this period as the "pandemic period", which means a global epidemic, due to the spread of the virus to the world in a short time. This period has undoubtedly been a period when many habits changed for everyone. Vacation habit is also one of the habits that change during this period. Especially in the summer months, people who spend their holidays in hotels had to be more sensitive in choosing the hotel due to the continuation of the pandemic period. While different criteria were considered in hotel selection before, the criterion of having a safe tourism certificate has become the most important criterion due to the pandemic. Businesses with this certificate can provide service without any problems as they take all precautions during the pandemic period. In this study, a hotel selection problem that takes into account the criteria of safe tourism certificate is discussed. In this study, a hotel selection problem that takes into account the safe tourism certification criteria is discussed. In the study, Stepwise Weight Assessment Ratio Analysis (SWARA) and fuzzy logic based The Complex Proportional Assessment (COPRAS) methods were used to solve the problem of choosing the most suitable hotel. As a result of the study, ten hotel alternatives were evaluated according to the criteria of safe tourism certificate during the pandemic period and the most suitable hotel was selected.

Machines are one of the most important production elements used by companies in the production phase. Sudden deterioration in machinery creates a process that can lead to a production halt and therefore a delay in orders. For this reason, enterprises decide to replace their old machines with newer technological machines. This replacement decision is not easy as it includes many criteria and there are many alternative machines on the market. From this point of view, in this study, a real-life application of a company's machinery purchase was made with fuzzy SWARA and fuzzy ARAS methods based on multi-criteria decision-making method. Criterion weights were determined by the fuzzy SWARA method. In the evaluation of alternative machines, the fuzzy ARAS method was taken into consideration. In the study, the criteria determined by the company manager and his team in line with the company needs were taken into consideration. Afterward, four machines were determined among the most suitable machines in the market and frequently used. Finally, calculations were made to find the machine that best meets the criteria required by the company among these machines. As a result of the calculations, the machine needed by the company was decided and the results were interpreted. Key Words: Machine Selection, Multi-Criteria Decision Making, Fuzzy SWARA, Fuzzy ARAS JEL Classification: M10, D70, D81

The changes in the industry have gone through many stages until today. These changes can be called a transition phase of industries that lasts for years. The process that started with the emergence of the Industry 1.0 concept first came to the concept of Industry 4.0. Recently, Industry 5.0 concepts are spoken around the world. Germany, where the concept of Industry 4.0 first emerged, is leading Industry 4.0 revolution. With the emergence of this concept, different topics such as smart factories, cybersecurity, simulation, 3D printers, and autonomous robots have come to the fore. These subheadings are undoubtedly very important topics for a factory. To fully implement the Industry 4.0 system, these subheadings must be applied and their sustainability must be ensured. In this study, the 3D printer selection process of a factory that wants to fully integrate its factory into a new revolution is discussed. This problem is called a multicriteria decision problem in terms of being very different criteria and alternatives. Decision-making trial and evaluation laboratory (DEMATEL) method was used to solve the problem, and the results were interpreted.

Increasing competition as a result of globalization forces companies to focus on the core activities they are specialized in and to use outsourcing in areas other than these core activities. Companies seek to outsource their logistics functions partially or completely since this is not in their main field of activity. Thus, companies are faced with the problem of choosing a Third Party Logistics (3PL) service provider that can contribute to their sustainable development and perfectly perform the logistics activities. In this study, the 3PL selection problem of a cable manufacturing company is discussed. The study aims to solve the business problem and to show the applicability of Multi-Criteria Decision-Making (MCDM) methods in the most appropriate 3PL selection problems. The 3PL selection was made in line with the criteria and alternatives determined by a team of decision-makers working in the relevant department of the company. First of all, the weight value of each criterion was determined by using the SWARA method based on the MCDM method. This method was chosen because it takes group decisions into account and is easy to implement. Afterward, calculations were made according to the criteria levels of each alternative service provider with the WASPAS method. In the study, 12 criteria were determined by the decision-makers. Besides, 5 different 3PL companies were taken into account. According to the results of the study, it was the third 3PL that met the criteria at the most appropriate level.

Amaç: Afetler insanlığın hiç beklenmedik zamanda karşılaşabileceği doğa olaylarıdır. Bu doğa olaylarının beklenmedik zamanda gerçekleşmesi beraberinde birçok felaketi getirebilmektedir. Hiç kuşkusuz afet sonrası en az zararla bu durumdan kurtulmanın yolu önceden tedbir alınmasıdır. Bir depremden sonra yapılacak işlemlerin belli olması en az can kaybı ile depremin sonlanmasına imkan tanıyabilir. Afet sonrası oluşturulacak geçici barınma bölgelerinin seçimi afetten sonra insanların barınma ve ihtiyaçlarının giderilmesi için en önemli adımlardan birisidir. Geçici barınma alanının seçimi çok farklı sayıda kritere bağlı olabilmektedir. Dolayısıyla alternatif geçici barınma alanı seçimi bir çok kriterli karar verme problemi olarak tanımlanabilir. Bu çalışmada amaç olası bir afet sonrası geçici barınma alanı seçimi üzerine bir uygulama yapmak ve en uygun alternatif konuma karar vermektir. Yöntem: Çalışmada problemin çözümü için çok kriterli karar verme yöntemi olan analitik hiyerarşi süreci kullanılmıştır. Bu yöntemde karar vericiler tarafından belirlenen kriterlerin ikili karşılaştırmaları yapılmaktadır. Ayrıca, her bir kriter ve alternatif arasında da kıyaslama yapılarak en uygun alternatif seçimine imkan tanımaktadır. Bu yöntem az bilgi ve karmaşık olmayan işlem aşamaları sebebiyle bu çalışmada kullanılmıştır. Bulgular: Çalışmada en uygun geçici barınma alanı seçimi yapılmıştır. Bu seçim işleminde altı farklı kriter dikkate alınmıştır (kamp boyutu, sağlık merkezlerine uzaklık, şehir merkezine uzaklık, altyapı, sosyal alanlara mesafe ve ulaşılabilirlik). Bu kriterleri karşılayan en uygun üç farklı konum belirlenmiştir. Bu belirlenen kriterlere göre en uygun üç konum analitik hiyerarşi süreci yöntemine göre değerlendirilmiştir. Elde edilen bulgulara göre barınma alanının boyutu kriterinin en yüksek ağırlığa sahip olduğu görülmüştür. Alternatif konumlar arasında yapılan değerlendirmelerde ise üçüncü alternatif konumun, geçici barınma alanı olarak en uygun yer olduğu görülmüştür. Özgünlük: Bu çalışmada bir afet sonrası geçici barınma alternatiflerinin değerlendirilmesi süreci ele alınmıştır. Ülkemizde afet sonrası müdahaleler için yetkili kurullar bulunmaktadır. Bu kurullar gerek illerde gerekse de ilçelerde ansızın yaşanan deprem ve sel gibi doğal afetlerde tedbirler almak için doğrudan sorumludurlar. Dolayısıyla bu çalışma sayesinde bu kurullar bilimsel açıdan alternatif konumlar belirleyerek olası bir afet durumunda insanların hayatlarının hızlı bir şekilde kurtarılmasını sağlayabileceklerdir. Diğer bir ifadeyle bu çalışma olası bir afet durumunda tüm illerde ve ilçelerde uygulanabilecek örnek bir çalışmadır.

Increasing environmental awareness in today's society and stricter environmental regulations have forced manufacturing firms to take necessary actions for the recovery of end-of-life (EOL) products through different options (e.g., recycling, remanufacturing,). Disassembly is regarded as a critical operation in EOL treatment of used products since all product recovery options require the disassembly of EOL products at certain levels. This critical operation is generally carried out by forming disassembly lines in product recovery facilities. Miscellaneous methodologies based on heuristics, metaheuristics and mathematical programming have been proposed for the balancing of disassembly lines. Majority of those methodologies assume that disassembly line parameters are deterministic by ignoring the fact that a disassembly line involves great deal of uncertainty mainly due to uncertain conditions of arriving EOL products. Considering this high level of uncertainty, simulation modeling can be an effective tool for the modeling of disassembly lines. In this study, a simulation-based disassembly line balancing methodology is proposed for the explicit consideration of stochastic parameters. First, simulation model of a disassembly line is constructed. Since the disassembly line balancing problem has a combinatorial nature, two commonly used metaheuristics (i.e., genetic algorithms (GAs) and simulated annealing (SA)) are integrated with the simulation model in order to balance the disassembly line. The disassembly sequence and task assignments proposed by GA are compared with the sequence and task assignments proposed by SA. This comparison indicates that GA outperforms SA in four of eight performance measures while both algorithms have the same value for line efficiency measure.