Sustainable Development Goal "Goal 1: No Poverty" ile 'a göz atma
  • Öge
    A study on understanding potential users' intention to use micro-mobility vehicles: E-scooter systems in İstanbul
    (Graduate School, 2024-07-25) Kaplan, Semanur ; Alppay, Ekrem Cem ; 502201928 ; Industrial Design
    The word 'Technology' is defined by the Turkish Language Association (TDK); It is defined as all the tools and related information that people have developed to control and change their material environment. When we examine it in this context, we can consider every product designed and made available to people as a technology. Acceptance of these new products by individuals and understanding their usage intentions will ensure both the development of technology and the success of the products. Understanding whether a product will be accepted by potential users and predicting users' future usage intentions with a user-centered design approach is very important in terms of creating more successful and profitable products in the market. UTAUT2 model created to understand users' motivations for using the product; It is examined in the context of performance expectancy, effort expectancy, social influence, facilitating conditions, hedonic motivation, price value, perceived risk, habit, behavioural intention and usage behaviours. With this approach, it is aimed to reveal potential users' intentions to use the product in the future and their reasons for choosing or not choosing the product. Considering the main aim of manufacturers to deliver their products to as many users as possible, it is very important to understand the target audience's perception of the products and their usage intentions in order to produce products that have an important place in the market. In this context, the mission of industrial designers is; The task of designing products acceptable to target users is added. Within the scope of this research, a literature review was conducted on technology acceptance models, urban transportation and shared micro-mobility systems. Urban transportation and product service systems are examined in the context of shared micro-mobility vehicles. Shared micro-mobility systems offer innovative solutions that transform urban transportation, making it more sustainable, accessible and economical. It will have an important place in urban transportation in the future with its features such as reducing traffic congestion, being environmentally friendly, providing accessibility to other public transportation networks, being economical and being healthier because it encourages physical activity. In this context, within the scope of this thesis, a research was conducted on potential users using the 'Unified theory of acceptance and use of technology (UATUT2)' in order to analyze the factors affecting the technology acceptance of shared micro-mobility vehicles in urban transportation. Data collection stages are as follows; It consists of semi-structured interviews, field stud and surveys. The research results were evaluated together with the findings. Based on the findings obtained within the scope of the research, a comprehensive insight was obtained about the intentions of potential users to use shared micro-mobility systems in the future and development suggestions were presented for industrial designers to develop e-scooters.
  • Öge
    An evaluation of the art songs for soprano voice by Turkish composers of the Early Republican period in a vocal technique perspective
    (Graduate School, 2024-01-15) Yağcıoğlu, Alin ; Öztürk Özgen, Yelda ; 409072011 ; Music
    The presence of Western art song in Turkey can be traced back to the Ottoman State before the establishment of the Turkish Republic in 1923. There was an intense attempt to integrate the genres and norms of Western classical music into the musical culture of the country after the establishment of the republic. This era includes the period when Atatürk's principles were set and applied in all fields and marks a profound time in music revolution. One of the aims of this revolution was to raise composers so that they would produce works in the form of Western classical music blending with the cultural and folkloric characteristics of the country. Since there was very limited opportunity to receive music education in the 1920s, the Ministry of Education organized auditions to choose talented students and give them scholarship so that they could study at European conservatories. Consequently, many musicians were given governmental scholarships to study in European music schools. On their return, they started composing for the purpose of forming the national repertory of works in different forms of Western classical music. Besides grand forms such as symphonies, concertos, operas and oratorios, small-scale works were also composed. Turkish art song, which had its structural basis on the Western art song, is one of these small-scale musical forms. These composers most of whom were given grants to study music abroad arranged Turkish folk songs for voice and piano; besides, they composed art songs in Turkish based on the poems of contemporary poets of their time as well. Among several poets whose works were used as lyrics of these art songs, Faruk Nafız Çamlıbel, Ahmet Haşim, Cahit Külebi, Melih Cevdet Anday, Orhan Veli Kanık, Necip Fazıl Kısakürek and Necdet Evliyagil come to the fore as the outstanding poets in the history of Turkish literature. Besides Ahmed Adnan Saygun, Cemal Reşid Rey and Necil Kazım Akses, who are considered as belonging to the Turkish Five, Ahmed Samim Bilgen, Faik Canselen, and Ferit Hilmi Atrek also composed Turkish art songs. As all other voice registers, soprano register has certain features which may hinder or enhance the quality of singing in vocal compositions, depending on the treatment of the vocal line and vowel/consonant properties of the lyrics. In this study, the art songs of early republican Turkish composers are analyzed in terms of vocal performability for the first time in order to invite composers to consider vocal features of the soprano register in addition to informing singers with this voice range for a more aware interpretation. Regarding this analysis, musical excerpts from the songs are categorised as either vocally friendly or vocally challenging. It is hoped that these findings will shed light on composing for the soprano voice and the works of early republican Turkish composers will find a solid place both in recital repertoire and the curricula of the music institutions in Turkey.
  • Öge
    Electrocatalytic performance of interconnected self-standing tin nanowire network produced by AAO template method for electrochemical CO2 reduction
    (Wiley, 2023) Er, Dilan ; Avcı, Burçak ; Ürgen, Mustafa ; orcid.org/0009-0008-2120-2994 ; orcid.org/0000-0003-3549-0049 ; Metalurji ve Malzeme Mühendisliği
    In this study, we used a specially designed aluminum anodic oxide (AAO) template technique to produce interconnected self-standing tin nanowire electrocatalysts having a high surface-to-volume ratio for CO2 reduction toward formate. These electrodes consisted of interconnected tin nanowires with 150 nm diameter and 7 μm length supported on 70–100 μm thick tin film. As prepared electrodes produced 6 times higher formate than the flat tin sheets, yet Faradaic efficiencies (FE%) were unsatisfactory. The main reason for low FE% is determined as the etching of native oxide on tin nanowires during hot alkali treatment to remove AAO and remnant aluminum. Porous anodic oxidation in 1 M NaOH solution was realized to recover tin oxides on the surface. Anodized tin nanowire electrocatalysts produced higher formate than anodized tin sheets, reaching FEformate% of ~87 at −1 V vs. RHE cathodic reduction potential. Moreover, while anodic oxide on flat tin flaked off the surface in 1 h, these electrodes preserved their integrity and formate production ability even after 12 h.
  • Öge
    Enhancing UCAV operations with AI-driven point cloud semantic segmentation for precision gimbal targeting in defense industry
    (Graduate School, 2024-12-20) Bozkurt, Salih ; Duran, Zaide ; 501182617 ; Geomatics Engineering
    The widespread integration of technological advancements has fundamentally transformed the field of artificial intelligence, significantly enhancing the reliability of AI model outputs. This progress has led to the widespread use of artificial intelligence in various sectors, including automotive, robotics, healthcare, space technologies, and defense industries. Particularly in the field of aerial combat, target identification and engagement operations still heavily rely on human operator intervention. Within the scope of this thesis, the aim is to automate the complex and error-prone laser designation process using 3D point clouds and deep learning algorithms. The primary dataset for the study consists of 3D point clouds obtained by processing gimbal images of the Bayraktar AKINCI Unmanned Combat Aerial Vehicle (UCAV) using photogrammetric methods. For initial evaluations and parameter optimizations, the DublinCity 3D LiDAR point cloud data was used. The DublinCity dataset was created using Airborne LiDAR methodology in the capital city of Ireland, Dublin, in 2015. This dataset is hierarchically organized into 13 classes, including buildings, vegetation, ground, and undefined, divided into four main categories. Within these main categories, there are subcategories such as windows, doors, trees, and others. For this study, we used the PointNet++ and RandLA-Net algorithms, two widely recognized approaches for point cloud segmentation. Both algorithms are designed to process point clouds directly and deliver segmentation results. However, a key difference lies in their handling of data: while RandLA-Net can incorporate both geometric and color information, PointNet++ traditionally relies only on geometric features. To address this limitation, we modified the PointNet++ algorithm to utilize color attributes, allowing for a more comprehensive analysis. This enhancement represents a significant contribution of our research. By comparing the improved PointNet++ with RandLA-Net, we observed noticeable differences in their performance, particularly in how they handle datasets with combined geometric and color information. In tests conducted using only geometric features in the RandLA-Net algorithm, an accuracy rate of approximately 94% was achieved. When color information for points was also provided to the algorithm, the accuracy rate significantly increased to approximately 97%. In tests conducted with the PointNet++ algorithm, an accuracy rate of 94% was observed when only geometric features were used. However, the accuracy rate increased significantly to approximately 96% when the PointNet++ algorithm was enriched with color information. The results of this research highlight two main contributions. Primarily, combining point clouds produced from different sources with AI-driven decision-making processes provides substantial benefits for the defense industry in aerial combat activities, such as target identification, monitoring, and neutralization. Secondly, modifying the PointNet++ algorithm, which originally relied exclusively on geometric data, to include color information has greatly enhanced the accuracy of learning and decision-making in 3D point cloud processing tasks. This research seeks to offer a dependable and effective approach to reduce human involvement in laser designation procedures, especially by utilizing data gathered from the Bayraktar AKINCI UCAV. Upcoming research will aim to enhance precision by incorporating higher resolution point cloud data and examining different deep learning algorithms. Furthermore, analyzing data gathered from advanced RADAR systems and enhanced photogrammetric point clouds will be a key emphasis for upcoming studies. Additionally, this thesis features an extensive preprocessing stage, enhancing the DublinCity dataset and photogrammetrically produced Bayraktar AKINCI UCAV information by organizing them into separate categories. The intricate framework of the DublinCity dataset, consisting of 13 categories, provided a varied basis for assessing segmentation algorithms. In this process, distinguishing highly specific classes (e.g., windows, doors) created a chance to examine the connection between detail level and algorithm precision. This part of the research highlights the difficulties and constraints associated with handling high resolution, intricate data. Apart from defense applications, laser, RADAR, and gimbal systems offer numerous potential uses. The techniques and strategies created in this research can be readily modified for use in other fields. For instance, in disaster management, these systems could be employed for automatic debris identification and directing rescue teams during natural disasters like earthquakes or floods. In urban design and infrastructure management, these technologies can greatly enhance procedures such as 3D city visualization and automated extraction of building inventories. In agriculture and forestry, they might be used to improve soil productivity, identify damaging structures, and track plant health. Likewise, in the preservation of cultural heritage, these systems can aid in 3D mapping of archaeological locations, identifying relics, and comprehensive documentation of historical items. In summary, this thesis illustrates the successful use of deep learning algorithms in automating laser targeting processes for aerial combat applications involving UAVs within the defense sector. These studies not only improve the effectiveness of current technologies but also establish a base for creating autonomous systems. The findings of this research possess significant theoretical and practical implications. Upcoming developments in this area seek to integrate more intricate datasets, including those from radar technologies, and evaluate different algorithms to foster additional innovation.
  • Öge
    Highly sensitive OFET based room temperature operated gas sensors using a thieno[3,2-b]thiophene extended phthalocyanine semiconductor
    (Royal Society of Chemistry, 2024) İşçi, Recep ; Yavuz, Özgür ; Faraji, Sheida ; Gunturkun, Dilara ; Eroğlu, Mehmet ; Majewski, Leszek A. ; Yılmaz, İsmail ; Öztürk, Turan ; https://orcid.org/0000-0003-3086-4478 ; https://orcid.org/0000-0002-0660-7474 ; https://orcid.org/0000-0001-6544-1286 ; https://orcid.org/0000-0002-5046-7456 ; https://orcid.org/0000-0003-3777-5320 ; Kimya Bölümü
    Over the past decades, organic field-effect transistor (OFET) gas sensors have maintained a rapid development. However, the majority of OFET gas sensors show insufficient detection capability towards oxidizing and hazardous gases such as nitrogen dioxide (NO2) and sulfide dioxide (SO2). In this report, a sustainable approach toward the fabrication of OFET gas sensors, consisting of a thieno[3,2-b]thiophene (TT) and phthalocyanine (Pc) based electron rich structure (TT-Pc) for the detection of both nitrogen dioxide (NO2) and sulfide dioxide (SO2) is disclosed for the first time. Khaya gum (KG), a natural, biodegradable biopolymer is used as the gate dielectric in these OFET-based sensors. Thin film properties and surface morphology of TT-Pc were investigated by UV-Vis, SEM, AFM and contact angle measurements, which indicated a uniform and smooth film formation. The UV-Vis properties were supported by computational chemistry, performed using density functional theory (DFT) for optimizing geometry and absorption of TT-Pc models. Sensitive and selective responses of 90% and 60% were obtained from TT-Pc OFET-based sensors upon exposure to 20 ppm of NO2 and SO2, respectively, under ambient conditions. One of the lowest limits of detection of ∼165 ppb was achieved for both NO2 and SO2 using a solution-processed TT-Pc sensor with a natural, biodegradable dielectric biopolymer. The sensors showed excellent long-term environmental and operational stability with only a 7% reduction of the sensor's initial response (%) upon exposure to NO2 and SO2 over nine months of operation in air.
  • Öge
    Impacts of Syrians under temporary protection on local development in Türkiye
    (Graduate School, 2024-07-05) Aka, Anıl Deniz ; Yılmaz Kayaoğlu, Ayşegül ; 412211003 ; Economics
    Migration has become a major concern for policymakers and researchers since the 2000s, as the number of migrants has been steadily increasing, impacting people in socio-economic ways. The consequences and effects of migration are not limited to the migrants themselves; they also affect those who remain in the migrants' home areas and the residents of more developed countries where the migrants resettle. In the last decade, Turkey has been significantly affected by forced migration, particularly due to its support for Syrians displaced by the Civil War. This research explores how Turkey's local development has been influenced by these refugees. To do so, this study employs a causal identification strategy comparing Development Index scores in provinces hosting higher share of refugees with other provinces before and after 2012, when Syrian refugee influx towards Turkey has started. As local development levels of provinces in both within and across regions of Turkey are distinct from each other, we used alternative ways to construct our counterfactual group of provinces. Therefore, in addition to staggered synthetic difference-in-differences we also used difference-in-differences and synthetic control method to check the robustness of our findings. To analyze the effects and data, the Synthetic Difference in Differences method is employed. The purpose of this study is to demonstrate how local development, proxied by human development and gender development, is affected by migration. Additionally, this work implicitly examines the impact of migration on other socio-economic parameters, such as GDP per capita and life expectancy, which are included in the calculation of Human Development Index (HDI). The study also compares other indexes, including the Gender Inequality Index (GII), the Gender Development Index (GDI), and the Inequality-adjusted Human Development Index (IHDI), which measure gender and general inequality points. The results indicate that migrants have positively contributed to the local development, proxied by indices of GDI, GII, and HDI, except for the IHDI. These findings suggest that migrants have had a socio-economic contribution to Turkey between 2009 and 2018. Although Turkey's situation is unique due to the rapid increase in migrants and its provinces' diverse geographical and social characteristics, this thesis can contribute to the literature on whether refugees positively affect local development in destination countries.
  • Öge
    Inspection of microwave self-healing efficiency in carbon nanotube reinforced polymer composites for aerospace applications
    (Wiley, 2024) Irez, Alaeddin Burak ; orcid.org/0000-0001-7316-7694 ; Makina Mühendisliği
    The aerospace industry is evolving very rapidly every day, and due to the low operational and maintenance costs, unmanned aerial vehicles (UAVs) are utilized for many duties, including imaging, patrol, surveillance, and delivery. Flying platforms prioritize effective load-carrying capacity and light weight. To achieve this, lightweight materials with sufficient strength are utilized, and design optimizations are implemented. This study investigates material development for a UAV propeller, taking into account the possible consequences of a bird strike or hard landing such as micro damage occurrence. In this study, a twin-screw extruder was used to produce hybrid composites by blending a thermoplastic, polyamide-6 (PA6) with olefin block copolymers (OBC) and carbon nanotubes (CNT). After manufacturing test specimens by injection molding, tensile and Charpy impact tests were performed. OBC increased the elongation capacity and impact resistance of the PA6 through maleic anhydride (MAH) grafting while reducing the tensile strength. CNT incorporation compensated for this drop, but it rendered the composites more brittle. More importantly, due to the CNT's microwave (MW) absorption capacity, the hybrid composites have gained self-healing properties. Extended MW exposure time and high MW powers may cause localized burning of the material, resulting in a decrease in its self-healing efficiency. Following the failure of the examined composites, SEM microscopy revealed various toughening mechanisms in the composites. The use of a modified Halpin-Tsai model to estimate the elastic characteristics of CNT-reinforced composites revealed promising results, with minimal discrepancies when compared to experimental data. Highlights CNTs were found efficient for the self-healing behavior which is critical for improving the lifetime and planning maintenance for UAV propellers. CNT content, MW power & exposure time all impact the self-healing efficiency. Extended MW exposure time and high MW powers can cause localized burning of the material, resulting in a decrease in its self-healing efficiency. CNTs created bridge effects, ultimately leading to an enhancement in the strength of the composites. The use of a modified Halpin-Tsai model yielded good accuracy with experimental data.
  • Öge
    Machine learning assisted force field development for nucleic acids
    (Graduate School, 2024-06-14) Demir İniş, Gözde ; Tekin, Adem ; 702172002 ; Computational Science and Engineering
    Molecular dynamics and mechanics simulations have long been used as an effective tool in the investigation of biomolecular systems. These simulations are founded upon force fields (FF), which are empirically parametrized sets of equations. These sets of equations allow us to associate the configurations of interacting atoms and molecules in the simulated system with their energies. To perform this association, FFs use classical physics to derive the forces governing the dynamics of these systems rather than quantum mechanical (QM) calculations, which are computationally quite time-consuming and costly for large systems. By this means, they may assist us in gaining deeper insights into many systems, from small drug-like compounds to proteins, nucleic acid bases, and even viruses. Another area of use of FFs is crystal structure prediction (CSP). Although Density Functional Theory (DFT) can be used as an objective function in global optimization approaches for CSP, it is not feasible considering its computational demand. In this regard, using FFs as objective functions is a reasonable approach in terms of both cost and performance. Through this approach, the individual FFs generated in our research group and the well-known GAFF potential have been integrated into the in-house developed program (FFCASP), which has the capacity to perform both two-dimensional (2-D) and three-dimensional (3-D) CSP, and several studies have been carried out in which highly successful results have been obtained for various systems. There are numerous FFs in the literature, and each has its own strengths and weaknesses. Even the most popular of these FFs have been found to fall short of accurately describing some particular interactions. These interactions (such as base pairing, $\pi-\pi$ stacking, and hydrogen bonding) are non-covalent interactions and are of great importance for proteins and nucleic acids (deoxyribonucleic acid (DNA) and ribonucleic acid (RNA)), since they are the stabilizing factors of these complexes. Among these complexes, DNA can be considered the most significant biological molecule, as it contains the genetic information of all known living beings. A profound understanding of the interactions between DNA bases and solid surfaces is vital for an array of possible applications in the fields of biophysics, medicine, materials science, and nanotechnology. Biocompatible materials, biosensors, drug delivery systems, and organic semiconductors can be listed at the top of the application's list. Within the scope of this thesis study, in order to fill the aforementioned gap in the literature, a force field, namely NICE-FF (Non-empirical, Intermolecular, Consistent, and Extensible FF), with higher accuracy and relatively low computational cost, has been generated specifically for the DNA bases. In this respect, an automated framework has been developed to produce well-polished computational grids, carry out ab-initio calculations, perform FF parametrization, and even expand the existing set of parameters. With this genuine parametrization approach, which is analogous to machine learning (ML) techniques, we were able to fit the calculated SCS-MI-MP2 interaction energies (IEs) to the Buffered 14–7 potential function. The first set of parameters has been obtained using the generated data sets of all ten DNA base combinations. Afterwards, the NICE-FF parameter set was integrated into the FFCASP, and the performance of the FF was tested by performing CSPs on a series of organic molecules. First, CSP tests are conducted on four DNA bases and two other molecules (namely, hypoxanthine and uracil) that contain only the same atom types as the DNA bases. Once we were satisfied with the validity of our parameter set, we introduced two more molecules (pyrazinamide and 9-methylhypoxanthine), mostly consisting of DNA base atom types, along with a few other new ones, to broaden the range of NICE-FF. Following the determination of the new atom type parameters, we proceeded to perform CSP for these two compounds. Additionally, we performed CSP on our independent test case, theophylline, which contains the newly parametrized atom types, in order to validate the reliability of our extended parameter set. For all of these test cases mentioned above, a total of over one hundred thousand predictions were made. It has been revealed that they yielded quite successful results, and we were able to locate almost all the known experimental CSs of the considered molecules. Finally, with the help of CrystalCMP software, we quantitatively compared the molecular packing of all the above-mentioned NICE-FF-predicted crystals and their corresponding experimental structures. The low $RMSD_{20}$ values obtained for almost all test cases indicated that the molecular packing quality of the reproduced structures is quite high. Other than these tests, we performed benchmarking on the renowned S22 data set against the five popular FFs and high-level ab-initio IEs to evaluate the performance of NICE-FF. The results revealed that NICE-FF outperforms the widely recognized FFs by providing the most compatible IEs with the reference method (CCSD(T)). Polymorph studies that we conducted using our new FF showed that even with this limited parameter set, quite promising results can be obtained. Moreover, it is evident that NICE-FF has the potential to easily cover new organic molecules. By pursuing this direction, it is possible to develop a more generalized version of NICE-FF, which can cover a wider range of possible atom types of organic molecules. In this ongoing polymorph study, CSPs were carried out for four DNA bases (when $Z =$ 2, 4, and 8), and subsequent DFT calculations were completed for the selected promising structures. The lattice energies have been calculated in order to make it easier to compare the structures with varying $Z$. The last study reported in the thesis is independent from the subject of FFs. In this study, machine learning techniques were employed to predict the band gap and formation energy of dual-cation organic-inorganic hybrid perovskites.
  • Öge
    Sanal gerçeklik alışveriş deneyiminin teknoloji kabulüaçısından incelenmesi
    (Lisansüstü Eğitim Enstitüsü, 2024-07-08) Özcan, Mehmet Zafer ; Alppay, Ekrem Cem ; 502211916 ; Endüstriyel Tasarım
    Günümüzde teknolojik gelişmelerle birlikte, Sanal Gerçeklik (SG) teknolojisi ve uygulamaları her geçen gün daha erişilebilir hale gelmektedir. Meta başta olmak üzere, farklı sektörlerden büyük şirketler, bu trendin gerisinde kalmamak için kendi uygulamalarını, oyunlarını ve sistemlerini geliştirmeye ve yatırım yapmaya başlamıştır. Son zamanlarda, Apple'ın Apple Vision Pro ile bu teknoloji yarışına iddialı bir giriş yapması, Sanal Gerçeklik ve kardeş teknolojileri Artırılmış Gerçeklik (AG) ve Karma Gerçekliğin (KG) gelecekte telefon ve bilgisayarların yerine geçip geçmeyeceği tartışmalarını beraberinde getirmiştir. Bu süreçte, Nike ve Waikiki gibi giyim markaları, ürünlerini Sanal ve Artırılmış Gerçeklik teknolojileri kullanarak sundukları konsept mağazalar geliştirmiştir. Bugün, bu tür sanal mağazaları bulmak zor olsa da teknolojinin gelişim hızı, yakın gelecekte hayatın farklı alanlarında karşılaşacağımız teknolojilerden biri olacağını göstermektedir. Gelecekte, sanal mağazaları ziyaret edebileceğimiz ve ürünlerin sanal versiyonlarını deneyimleyebileceğimiz medya ortamlarının oluşması beklenmektedir. Ürünlerin SG demoları, bunların gerçek hayattaki versiyonlarını ifade edebilecek ürünler bu yolla fiziksel olarak, denenmeden müşteri üzerindeki tatminine bağlı olarak satılabilecektir. Bu gelişmeler yakın gelecekte farklı sektörleri de SG teknolojisini kullanmaya yönlendirecektir. Bu sebeplerden dolayı günümüzde sanal pazarlarda interaktif alışveriş yapılırken SG teknolojisinin kullanıcı tatminine ve kararına etkisinin araştırılması önemli ve güncel bir konu haline gelmiştir. Bu araştırmada; Sanal Gerçeklik teknolojisinin yakın gelecekte çevrimiçi alışveriş deneyimini nasıl etkileyeceğini ve buna bağlı olarak kullanıcılar tarafından teknoloji kabulünün incelenmesi amaçlanmıştır. Elde edilen veriler istatistiksel olarak değerlendirilmiş, nitel veriler ise içerik analizi yöntemi ile analiz edilmiştir. SG teknolojisinin, teknoloji kabulü çevrim içi alışveriş süreci temel alınarak irdelenmesi sonucunda çevrim içi alışveriş sürecinde kullanılabilirliğini arttırmaya yönelik dikkat edilmesi gereken hususlar ve potansiyel iyileştirme yöntemleri hakkında çıkarımlarda bulunulmuştur. Bu tez çalışmasında, Sanal Gerçeklikte uygulanabilecek potansiyel sanal mağaza türleri üç ana başlığa ayrılarak incelenmiştir. Bu başlıklar sırasıyla (1) Sanal pencereler yardımı ile çevrim içi alışveriş, (2) Fiziksel Mağaza Düzenine Sahip SG Mağazaları ve (3) Sanal Ürün Raflarına Hızlı Erişim'dir. Çalışmanın devamında mağazaların gelecekte nasıl performans göstereceği ve kullanıcılar tarafından ne oranda benimseneceği ile ilgili fikir sahibi olmak üzere gelecekteki çalışmalara yol gösterecek kapsamda bir Kullanıcı Deneyim Testi hazırlanmıştır. Bu Deneyim Testi, (1) Sanal Gerçeklik Deneyimi (katılımcıların sanal gerçeklik ile tanışması ve çevrim içi alışverişi deneyimleyerek bir fikir sahibi olmasını sağlar) (2) Yarı Yapılandırılmış Görüşme (katılımcıların ilk görüşlerinin ve deneyimlediklerini ve düşüncelerini toplamayı amaçlar), (3) Kullanıcı Deneyim Anketi (kapalı uçlu sorular ile kullanıcıların senaryoyu nasıl değerlendirdiklerini tespit etmeyi amaçlar), (4) Teknoloji Kabul Anketi (TKKBM-2) (katılımcıların bu teknolojiyi gelecekte kullanmayı planlayıp planlamadıklarını anlamayı amaçlar) ve son olarak da (5) Simülasyon Rahatsızlık Anketi (SRA) (katılımcıların deneyler sırasında yaşadıkları rahatsızlıkları tespit etmeyi amaçlar) çalışmalarını içermektedir. Yapılan literatür araştırmaları sonucunda ortaya konan 3 potansiyel sanal mağaza türünden "Sanal pencereler yardımı ile çevrim içi alışveriş" yöntemi seçilmiş ve detaylı olarak incelenmiştir. Deneysel çalışmaya katılan katılımcılar 20-29 yaş arası ve SG deneyimi olmayan ya da en fazla 1 saat deneyimlemiş kişiler arasından seçilmiştir. Katılımcılara yukarıda bahsedilen deneyimler ve anketler uygulanmıştır. Yarı-yapılandırılmış görüşmeler ve açık uçlu soruların analizi, mevcut internet sitelerine sanal ekranlar aracılığıyla erişmenin, çevrim içi alışveriş deneyimi için yeterli olmadığı sonucunu ortaya koymuştur. Ayrıca katılımcılar, sanal gerçeklik teknolojisinin sunduğu imkanlardan yararlanan ve özellikle sanal gerçeklik için tasarlanmış platformları kullanmayı mevcut internet sitelerine tercih edeceklerini de ifade etmişlerdir.
  • Öge
    The effect of investor sentiment on non-ferrous metals contracts at LME and optimizing a metals commodity portfolio
    (Graduate School, 2024-07-03) Açıkgöz, Ekin ; Taş, Oktay ; 403211010 ; Management
    The history of the financial markets is full of occurrences contradicting the assumptions of the traditional theories. Recent studies on Behavioral Finance argue that some of these observed financial phenomena can be explained by the probability that some of the traders at markets are not fully rational. These studies argue that the heuristics, biases, and sentiments affect the decisions of investors, who possess scarce cognitive resources and limited information. Behavioral finance is an approach that arose as an alternative approach to the criticized aspects of the traditional theories. Behavioral Finance discusses that non-financial drives influence the investors and can explain their investment preferences. Many empirical literatures discuss the effect of investor sentiment in finance. As investor sentiment is an influencer in the price formation of assets, it should be used to model the prices, returns, and volatility in the market. As studies on behavioral finance accumulate, empirical evidence on the influence of investor sentiment on the dynamics of the market increases. This study aims to assess the effect of sentiment in commodity markets. In the commodities markets, the participants are a mix of both investors and direct purchasers of the commodity itself, for its industrial use. The changing nature of the commodity markets can be observed through the increasing interest of financial investors, especially in the futures market, who do not have any physical exposure to the commodities in question. The literature argues that cointegration is one important concept in empirical behavioral finance. The study argues that investor sentiment is contagious among various markets and the conveyors of the sentiments are the financial investors, who diversify their portfolio with multiple asset classes traded in different markets, including commodities. Because of their significant role in industrial manufacturing, non-ferrous metals are an important area of concern for economic activity worldwide. The studies on the price patterns of industrial metals should also focus on the behavior of investors in both physical and derivatives markets. This study argues the existence of interconnectedness of the London Metal Exchange (LME) metals by other global financial markets through the way of investor sentiment. As for the sentiment measure, this study chooses an indirect approach to use a market proxy and assumes the Chicago Board Options Exchange's Volatility Index (VIX), which is a recognized measure of volatility and investor sentiment. As the literature states that the most successful and practical model for multivariate modeling is the Vector Autoregression (VAR) this study employs VAR as the analyzing methodology. Harry Markowitz introduced an analytical construct of a connection between the investment's return and the risk, which is called the Mean Variance Portfolio optimization. In this methodology, either the risk should be minimum for a specified return or the return should be maximum for an accepted value of risk. Portfolio diversification reduces the exposure of investors to the individual risk of the assets. It is all about deciding on the best possible portfolio diversification strategy. In time, many sophisticated estimation techniques were developed, in hopes of providing a better way than the Mean Variance Portfolio optimization method. However, it still remains as the milestone of the Modern Portfolio Theory. The study employs Mean Variance Portfolio optimization methodology to create a metal commodity portfolio from the assets traded at the LME. The biggest disadvantage of a regular Mean Variance Portfolio is actually a long-position-only (long-only) portfolio, which ignores a whole bunch of securities with negative expected returns. Investors overcome this disadvantage by the method of short selling. With short selling, investors are able to borrow and sell an asset without actually having its ownership. Investors, who short sell, earn their profits when the prices decline. Therefore, the study reconstructs the metal commodity portfolio by allowing short selling. This way, the study increases the flexibility of its portfolio and it benefits from the losing assets as well as the increasing assets. A portfolio with short positions results in a better performance if compared to a portfolio with long positions only. The first aim of this study is to investigate the idea that the investor fear gauge is universal for all exchanges and markets, and after blossoming in one driver market, such as the equity market, it will have effects on all other markets in degrees, such as the commodity markets. One of the other aims of this study is to emphasize the signifcance of non-ferrous industrial metals for the global financial markets by validating that the metals market is not independent of the developments of other markets with different kinds of assets classes, on the contrary, they express interrelationships among each other in various ways. The final aim of this study is to use the LME non-ferrous metals to create an optimum portfolio of metals commodity by using the Markowitz's optimization methodology, withouth and with short selling. The study gathers data for Nickel, Tin, Aluminum, Copper, Lead, and Zinc, which are the six non-ferrous metals of the LME. The study employs the VAR methodology to analyze the cointegration between industrial metals market prices and VIX. Test results verify a long-run relationship among the prices of non-ferrous metals and the fear factor in the global financial markets. Furthermore, the study constructs three different metals commodity portfolios: i) Portfolio 1 – Equal Weight Portfolio: To calculate the return series from the prices of each non-ferrous metal series, logarithmic expression is used. The results show positive returns for Copper, Lead and Tin, whereas they show negative returns for Aluminum, Nickel and Zinc for the defined period. As each of six assets are given equal weight, the resulting expected return for this portfolio is negative due to the losing assets. ii) Portfolio 2 – Optimized Mean Variance Portfolio: This is a metals commodity portfolio constructed by using the optimization methodology. The study calculates the covariance matrix for metal series. The highest covariance is among Nickel and Tin and the lowest covariance is among Copper and Lead. Moreover, all the relationships between the two metals are positive, which indicates that all metals tend to behave in the same direction with other metals. Then the study uses the Sharpe Ratio to approximate the market portfolio. It employs standard deviation as a measurement of total risk. The portfolio which maximizes the Sharpe Ratio is the optimum portfolio among the six non-ferrous metals. It can be observed that the highest weight in the optimum portfolio belongs to Lead. Copper and Tin also enter into the equation due to their positive expected return; however, the optimum portfolio does not include any Aluminum, Nickel and Zinc. The expected return is slightly lower than the individual asset with highest daily return. But it is higher than the portfolio with equal weights. The standard deviation is lower than both the portfolio with equal weight and the weighted average of the individual standard deviations of the metals, due to the fact that there are covariances among all two sets of assets. iii) Portfolio 3 – Long-Short Portfolio: Finally, the study constructs a second portfolio with short selling. This time the portfolio has long positions for Copper, Lead and Tin, whereas it has short positions for Aluminum, Nickel and Zinc. The study shows that the highest long position in the optimum portfolio belongs to Copper and it is limited with the threshold value. Whereas the biggest short position belongs to Zinc and it is also limited with the threshold value. All industrial metals enter into the equation. The resulting long-short portfolio has a larger number of assets, which results in a more diverse structure than the long-only portfolio, a daily return, which is significantly higher than both the portfolio with long positions only and any/each one of the individual assets, a portfolio variance, which is significantly lower than both the long-only portfolio and any/each one of the individual assets, and a higher Sharpe Ratio than the portfolio with long positions only, which indicates a higher portfolio performance. The study employs the London Metal Exchange Metals Index (LMEX) as the market benchmark and compares all three portfolios with LMEX in the same period. Although LMEX has a negative expected return due to the losing three metals out of six, it still has a better expected return than the equal weight portfolio. However, both optimized Mean Variance Portfolio and the long-short portfolio perform much better than the market index. When the study compares the three portfolios among each other, it utilizes Sharpe Ratio (SR) and Treynor Ratio (TR). a) SR of Portfolio 2 is higher than Portfolio 1. SR of Portfolio 3 is significantly larger than Portfolio 2. This indicates that Portfolio 2 performs better than Portfolio 1 and Portfolio 3 is the best performing among the three. b) TR is negative for Portfolio 1, which indicates a worse performance than the market benchmark. By assessing TR, the study concludes that Portfolio 2 outperforms Portfolio 1. However, the TR is negative for Portfolio 3, which is not very surprising since Portfolio 3 transforms negative performing assets into positive. It is an expected outcome as the benchmark return is negative, it leads to a negative Treynor ratio, especially as the portfolio's return is positive but the covariance between the portfolio and the benchmark index is also negative.
  • Öge
    The effect of social transfers on income inequality and poverty in Türkiye
    (Springer, 2024) Selim, Raziye ; Küçükçifçi , Suat ; 0000-0002-0277-1752 ; İşletme Mühendisliği
    This paper examines the effects of social transfers on inequality and poverty in Türkiye. We use Income and Living Conditions Survey that is conducted by TurkStat each year from 2006 to 2018. The social transfers include in cash and in-kind transfers from government to households. The standard budget incidence approach is used in the analysis. The redistribution impact of social transfers is measured using Gini coefficient and Suits coefficient and relative poverty rate. The equivalence scale adjustments are used for inequality and poverty estimations, and it is accepted as relative poverty approach. Pension income is the main factor that influences on reducing inequality and poverty. The inequality-reducing effect of pension income increased over time from 2005 to 2017. We also apply logistic regression analysis for 2018 SILC Survey. According to the logistic regression analysis, social transfers have the effect of reducing the probability of being poor in Türkiye.
  • Öge
    The impact of education reform on women's crime exposure in Türkiye
    (Graduate School, 2025-02-07) Vatansever, Ceyda ; Aygün Hızıroğlu, Aysun ; 412211023 ; Economics
    This study examines the effects of an educational reform on middle school completion, exposure to crime, and perceptions of security and trust in security forces. Using data from the Turkish Statistical Institute's Life Satisfaction Survey (2018-2022), the analysis focuses on female individuals born within a 72-month bandwidth around the January 1987 cutoff. This study applies a regression discontinuity design and Two Stage Least Squares (2SLS) to assess the impact of the reform, while also considering the inclusion and exclusion of the COVID-19 years to account for any pandemic related irregularities. The decision to exclude the COVID-19 years (2020 and 2021) from the analysis was made due to the potential disruption in data patterns during the pandemic, which may have affected the stability of our outcomes. Such disruptions could include changes in response behavior or alterations in the broader socio-economic context, making it difficult to isolate the true effects of the reform during those years. The exclusion ensures that the results more accurately reflect the reform's impact rather than any pandemic-related anomalies. The findings reveal that the education reform led to significant increases in middle school completion rates. We also find suggestive evidence of reductions in exposure to crime, although this result is not statistically significant. Additionally, the reform improved individuals' perceptions of personal security, particularly in terms of feeling safe at home while alone. Trust in security forces also increased, with women showing improved satisfaction with police forces and a higher perception of timely responses to security issues. However, some variables, such as the feeling of safety when walking alone at night, did not change significantly. Considering the reduction in the number of observations due to the exclusion of the COVID-19 years, we observed minor changes in the magnitude of the results, while the standard errors increased in the regressions when 2020 and 2021 were excluded. The decrease in the number of data points, resulting from the exclusion of the COVID 19 years, likely contributed to these changes. While the sizes of the coefficients remained largely unchanged, the statistical significance of some variables weakened with the reduced sample size. Despite this, the overall findings remained consistent. These results enhance our understanding of how educational reforms can influence not only academic outcomes but also broader societal dimensions, such as public confidence in institutions.
  • Öge
    The social dimension of sustainability: A case study on indoor environmental quality in Türkiye
    (Graduate School, 2024-07-12) Amini, Darya ; Kayalıca, Mehmet Özgür ; 403211007 ; Managment
    I conducted a study focusing on social sustainability, which is a crucial feature in today's environment. Extensive literature study revealed that the environmental and economic aspects of sustainability have been extensively studied, whereas the social aspect, especially in the context of Türkiye, has not been given equal emphasis. The lack of research in this area prompted me to investigate the social aspect, particularly concentrating on the efficiency and contentment of employees, which is crucial for organizations. The goal of my analysis was to discover the primary element that impacts employee productivity in the context of sustainability, specifically emphasizing green buildings. To accomplish this, I sought advice from experts in sustainability, architecture, and management. The experts received a paired questionnaire to rate ten sustainability parameters, including Energy Efficiency, Water Conservation and Management, Indoor Environmental Quality (IEQ), Waste Management and Recycling, Life Cycle Assessment, Long-term Impact, and others. After applying the Analytic Hierarchy Process (AHP) to the data, it was found that Indoor Environmental Quality (IEQ) was identified as the most significant factor impacting employee productivity in office environments. Acknowledging the crucial importance of Indoor Environmental Quality (IEQ), I advanced to the subsequent stage of my research, which focused on evaluating employee contentment with IEQ in their work environments. I chose three different buildings to compare their compliance with green building standards: the Energy Institute of Istanbul Technical University, a non-certified conventional building; the Istanbul Technical University Graduate School Building, which is Platinum LEED certified and features smart systems such as smart lighting and elevators; and the NEF Building, a LEED-certified green building with limited smart systems. During this portion of the investigation, I arranged multiple in-person meetings with individuals who work in these buildings. I delivered a detailed questionnaire with around 40 questions during these exchanges. The questions were created to investigate many elements of Indoor Environmental Quality (IEQ), such as air quality, temperature, lighting, acoustics, and views. I aimed to gain a comprehensive grasp of how employees viewed the Indoor Environmental Quality (IEQ) in their individual office settings. The questionnaire results were analyzed using the MANOVA methodology in SPSS software. This statistical method facilitated a detailed analysis of the data to detect any notable variations in employee satisfaction with IEQ among the three building types. The results showed that there were no significant differences in employee satisfaction with Indoor Environmental Quality (IEQ) among the three buildings. Employees indicated similar levels of satisfaction with their indoor settings, regardless of the different green certification levels and advanced smart systems present. The surprising result indicated that the investments in obtaining green certifications and implementing smart technologies may not be leading to improved employee satisfaction with Indoor Environmental Quality (IEQ). This discovery has significant consequences for the construction sector, legislators, and other parties engaged in the planning and development of environmentally friendly buildings. The statement emphasizes a significant flaw in existing sustainable construction methods: the importance of prioritizing and adequately managing Indoor Environmental Quality (IEQ) variables that have a direct influence on staff well-being and efficiency. The environmental advantages of green buildings are widely recognized, but the social aspect, especially employee satisfaction and productivity, needs more focus and incorporation into the design and construction procedures. My analysis highlights the importance of adopting a comprehensive approach to green construction requirements. It promotes a balance between environmental sustainability and the social factors that enhance the well-being and productivity of building inhabitants. By prioritizing Indoor Environmental Quality (IEQ), stakeholders may guarantee that green buildings achieve not just environmental objectives but also establish healthy, comfortable, and productive settings for employees. Ultimately, green buildings are a crucial advancement in sustainability, but this research emphasizes the necessity of taking social concerns, including Indoor Environmental Quality (IEQ), into account during their design and execution. It is important for policymakers, construction businesses, and other relevant industries to consider these findings and make employee wellness a top priority in their sustainability initiatives. This method will improve the efficiency of green buildings and support the broader objective of sustainable development, including environmental, economic, and social aspects.
  • Öge
    The worst forms of child labor in Türkiye: Assessing progress using 2012 and 2019 child labor surveys
    (Graduate School, 2024-07-04) Bozkurt, Buse ; Yılmaz Kayaoğlu, Ayşegül ; 412211006 ; Economics
    Child labor in Türkiye is a significant socioeconomic problem with enduring negative effects in the short- and long-term. Child labor entails engaging children in tasks that deprive them of their rightful childhood experiences, hinder their access to education, and pose detrimental effects on their mental, physical, social, and moral well-being. It encompasses situations where children are often compelled to work in roles unsuitable for their age group. During the mid-19th century Industrial Revolution, child labor became increasingly apparent as children were attracted to industrial settings. The relationship between the Industrial Revolution and child labor is a noteworthy historical phenomenon that underscores the exploitation of children in the early stages of industrialization. As industrialization swept across Europe and later other parts of the world, it brought about profound changes in economic and social structures. Factories emerged as centers of production, powered by new technologies and machinery. During this period, the demand for labor in factories and mines soared, leading to a significant influx of workers, including children, into urban industrial centers. Child labor became increasingly prevalent as employers sought to maximize profits by employing cheap and easily exploitable labor. Children were viewed as particularly desirable workers due to their small size, nimble fingers, and ability to perform tasks that required dexterity. Young children, as young as five or six years old, were frequently hired in factories, mills, and mines, often enduring extended shifts in unsafe environments. They were subjected to grueling labor, exposed to dangerous machinery, and deprived of basic rights and protections. Their wages were meager, and they often faced physical abuse and neglect. The exploitation of child labor during the Industrial Revolution was fueled by several factors. Poverty was rampant among working-class families, pushing households for sending children to work in order to bolster household income. Additionally, the rapid pace of industrialization and urbanization disrupted traditional family structures and social norms, leading to the breakdown of traditional forms of child-rearing and supervision. Moreover, the lack of effective labor regulations and enforcement mechanisms allowed employers to exploit child labor with impunity. In many cases, children worked in conditions that were detrimental to their health, development, and well-being, without access to education or opportunities for social mobility. The plight of child laborers during the Industrial Revolution sparked widespread social reform movements and calls for legislative action to protect children's rights. Over time, concerted efforts were made to enact laws and regulations with the goal of restricting child labor, enhancing conditions of work and expanding access to education. While the relationship between the Industrial Revolution and child labor is rooted in historical context, its legacy continues to resonate today. Child labor is also related to situations where families face economic hardship or poverty. When families struggle to meet their basic needs, they might view children as a way to add to the family's earnings. In many cases, children are sent to work out of necessity rather than choice, as their earnings may be crucial for the family's survival. Factors such as lack of access to education, social protection, and adequate employment opportunities can exacerbate the likelihood of child labor. Deprived of adequate educational opportunities, children may not have the opportunity to develop essential skills and knowledge that would enable them to secure better-paying jobs in the future. Additionally, the lack of efficient social safety nets exposes families to economic instability, heightening the probability of turning to child labor as a means of dealing with hardships. In some instances, cultural norms and societal attitudes may also contribute to the perpetuation of child labor. In communities where child labor is normalized or where children's contributions to household income are undervalued, families may be more inclined to engage their children in work from a young age. Additionally, globalization and the expansion of informal economies can create conditions conducive to child labor. In industries like agriculture, manufacturing, and household labor, where informal employment is common, and labor regulations are frequently ignored, children could be especially susceptible to exploitation and mistreatment. Overall, child labor is a complex phenomenon influenced by a myriad of economic, social, cultural, and institutional factors. Combating child labor necessitates a comprehensive strategy that addresses its underlying drivers, such as poverty, limited access to education, insufficient social safeguards, and lax enforcement of labor regulations. By tackling these fundamental issues, communities can establish environments that shield children from exploitation and enable them to flourish and realize their capabilities. On the other hand, the problem of the worst forms of child labor, which is aimed to be eliminated, is also an issue of great importance and requires urgent intervention. The term "worst forms of child labor" denotes the most severe and harmful instances of child exploitation, as outlined by the International Labour Organization (ILO) Convention No. 182 on the Worst Forms of Child Labour. These encompass various types of work that pose significant risks to the health, safety, and overall well-being of children. Examples include hazardous labor, where children are exposed to physical dangers such as operating dangerous machinery or working in unsafe environments like mines or construction sites. Forced labor is another form where children are coerced or deceived into work against their will, often through debt bondage or trafficking. Furthermore, children could fall victim to commercial sexual exploitation, experiencing prostitution, pornography, or other types of sexual abuse in exchange for financial profit. Child trafficking encompasses the recruitment, transportation, or harboring of children for the purpose of exploitation while involving children in illegal activities exposes them to dangers related to drug trafficking, smuggling, or armed conflict. These practices violate children's fundamental rights and are prohibited under international law. Tackling the worst forms of child labor requires a multifaceted approach, tackling underlying factors such as poverty, limited access to education, and inadequate legal protections. Strategies may include legislative reforms, awareness campaigns, social support initiatives, and targeted interventions to assist vulnerable children and families. By confronting the underlying causes and effects of child labor, societies can strive towards creating safer and more equitable environments for children to thrive. This study aims to delve into this multifaceted problem, presenting a comprehensive analysis with dual objectives. Firstly, it seeks to meticulously evaluate Türkiye's progress leading up to 2019, adhering to the objectives outlined in national development programs aimed at eliminating the worst forms of child labor by 2023. This evaluation serves as a critical benchmark, shedding light on the efficacy of existing policies and initiatives in combating child labor within the nation. Secondly, this study endeavors to empirically scrutinize the intricate web of factors that underpin the worst forms of child labor, employing a gender-disaggregated approach. By meticulously analyzing nationally representative survey data from 2012 and 2019, the research aims to discern nuanced patterns and dynamics that contribute to the prevalence of child labor, particularly focusing on gender differentials. Through this lens, the study seeks to unravel the underlying drivers of child labor and provide different insights for policymakers. In this study, the methodological approach involves analyzing data from the TUIK Child Labor Survey conducted in Türkiye in 2012 and 2019. The main emphasis is on the occurrence and factors influencing the worst forms of child labor in Türkiye. To achieve this, a logit model is employed to statistically analyze the relationship between various socio-economic factors and the likelihood of children engaging in hazardous labor, forced labor, or other forms of exploitative work. By using the logit model, the study aims to identify significant predictors of child labor and evaluate the effectiveness of Türkiye's efforts to combat this pressing issue. This methodological framework allows for a rigorous examination of the underlying factors contributing to the persistence of child labor. In essence, this study represents a pivotal stride towards comprehensively understanding the determinants of the worst forms of child labor in Türkiye, while concurrently evaluating the nation's progress in addressing this pressing issue. The empirical findings unearth critical revelations, underscoring the imperative need for Türkiye to fortify its child labor policies and craft more robust intervention strategies. Moreover, the findings illuminate the pervasive gender disparities inherent within the realm of child labor, highlighting the disproportionate vulnerabilities faced by boys, who frequently face exploitative work environments and extended work hours. Furthermore, the study discerns a strong correlation between educational attainment and the likelihood of children engaging in the worst forms of child labor, emphasizing the pivotal role of education as a deterrent. In summary, this research's findings emphasize the urgent need to tackle the underlying reasons for child labor and promote an environment where children can flourish without being exploited. Moving forward, concerted efforts must be directed towards bolstering educational infrastructure, mitigating gender disparities, enacting stringent measures, and fostering collaboration between government, civil society, and international organizations to eliminate child labor in every manifestation, thereby ensuring a brighter and more equitable future for Türkiye's youth.
  • Öge
    Yabancı portföy yatırımlarını etkileyen makroekonomik faktörler: Türkiye'de yabancı hisse senedi yatırımcıları üzerine inceleme
    (Lisansüstü Eğitim Enstitüsü, 2024-11-06) Kaynak, Adem ; Ekinci, Cumhur ; 403211001 ; İşletme
    Küreselleşmenin hızlandığı 1980'li yıllardan sonra dışa açık, yatırımların ve ticaretin uluslararası düzeyde hızlandığı bir döneme girilmiştir. Bununla birlikte gelişmekte olan ülkelere yabancı sermaye akışlarında artış gözlemlenmiştir. Yabancı sermaye akışlarını doğrudan yatırımlar ve portföy yatırımları olarak ikiye ayırmak mümkündür. Doğrudan yabancı yatırımlar daha uzun vadeli, şirket satın alımı, şirket birleşmeleri veya iştirak, tesis kurulması şeklinde olabilir. Bununla birlikte, yabancıların portföy yatırımları ise daha kısa vadeli olarak değerlendirilen başka bir ülkedeki hisse senedi, tahvil ya da diğer finansal enstrümanların satın alınması şeklinde gerçekleşir ve belirli bir sürede getiri elde edilmesi beklenir. Yabancı portföy yatırımların ülkeye gelmesini etkileyen faktörler literatürde uluslararası ölçekte piyasaları etkileyen itici faktörler ve ülkenin iç dinamikleriyle ilgili olan çekici faktörler bulunmaktadır. Portföy yatırımlarına örnek olarak gösterilebilecek yabancı yatırımcıların Borsa İstanbul'da hisse senedi yatırımlarında siyasi, jeopolitik ve ekonomik birçok faktör bulunmakla birlikte ekonomik göstergeler en önemli faktörler arasında yer almaktadır. Bu çalışmanın amacı, Türkiye'de 2011-2024 yılları arasında makroekonomik faktörlerdeki değişimin Borsa İstanbul'daki yabancı yatırımcı hareketleri üzerindeki etkilerini incelemek ve hangi faktörlerin yabancı yatırımcıları önemli ölçüde etkilediğini tespit etmektir. Belirlenen amaç kapsamında yapılacak analiz için, 2011-2024 arası aylık veriler kullanılmıştır. Çalışmanın bağımlı değişkeni, Borsa İstanbul'da yabancı yatırımcıların portföy büyüklüklerinin toplam portföy büyüklüğü içindeki payları olarak belirlenmiştir ve bu kapsamda kurumsal ve tüm yabancı yatırımcıların portföy payları olmak üzere iki farklı bağımlı değişken üzerinden (PFCOMB, PFINST) model çalışılmıştır. Çalışmada Borsa İstanbul ve yabancı yatırımcı portföy oranlarının ortak etkilendiği değişkenler olabileceği değerlendirilerek içsellik sorununu gidermek amacıyla 2SLS yöntemi kullanılmıştır. İçsel değişken olan RBIST, ilk olarak araç değişkenlerle birlikte test edilmiş ve sonrasında bu regresyonun sonucunda RBIST tahmin verileri ile ana bağımlı değişkenlerle regresyonlar çalıştırılmıştır. Çalışmanın sonuçlarına göre, Borsa İstanbul getirisi ve Türkiye 1 yıllık tahvil faizi yabancı yatırımcı portföy oranlarıyla anlamlı ve pozitif ilişkili, Türkiye CDS primiyle anlamlı ve negatif ilişkili olduğu görülmüştür. Borsa İstanbul endeks volatilitesi yabancı yatırımcıların portföy büyüklükleriyle pozitif ilişkili sonucu bulunmuş fakat bu sonuç istatistiksel olarak anlamlı sonuçlanmamıştır.