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ÖgeThe effects of loyalty programs on customer loyalty in automotive industry(Graduate School, 2023-06-23)The fundamental concepts of customer satisfaction, brand loyalty, and brand association serve as the cornerstones of the companies' marketing strategies. To ensure to have those concepts in their businesses, companies need to place the customer into the center, and implement their marketing strategy with considering these cornerstones effectively. Understanding and assessing the demands, actions, and qualities of the customer is the first step for putting customer into the focus. By gathering, examining, and utilizing the behavioral and characteristic data, brands can enhance their performance. One of the important strategies to implement customer data management within the operations, is customer loyalty program. With loyalty programs, the companies can increase their sales revenues and utilization or purchasing of the products and services. Various businesses such as airlines, retailers and banks develop loyalty programs in order to keep the customer loyal to their brands. One of the key players in the market, automotive companies, also integrate loyalty programs within their strategy. However, there is not sufficient amount of research in the literature that mentions the usage of car brand loyalty programs and clearly demonstrates the impacts of loyalty programs on customer loyalty by taking customer satisfaction into account. In this dissertation, the impacts of the car brand loyalty programs on customer loyalty were assessed with a survey and previous literature-based research. There were a total of 331 people answered the survey. To fully comprehend the impact of loyalty programs on customer satisfaction, the three main benefits of the programs -utilitarian, symbolic, and hedonic-were initially grouped. After doing so, the relation between customer satisfaction and customer loyalty were examined to figure out the main goal of the study. The studies of the data revealed a favorable relationship between customer satisfaction and the utilitarian, symbolic, and hedonistic advantages of the loyalty program. Additionally, the study demonstrated that customer loyalty grows as customer satisfaction does. The additional variables (gender, age, education level, income group, job, owned car brand, car ownership period and service visit frequency of the customers) were also tested to observe whether they have an impact of the research model. The results showed that customer loyalty differs according to the car ownership period and job of the customer. Besides these, there was not any other significant difference amongst the variables. During the research, the reasons for not participating in a car brand loyalty program and the preferences of non-members for loyalty program features were also discovered. Lack of information, a lack of perceived need for a loyalty program, the absence of any existing loyalty programs, and the absence of any appealing offers that attract customers are the most frequent excuses given for not enrolling in a loyalty program. Additionally, non-member clients prefer to sign up for a loyalty program that allows for easy registration, benefits for regular use, and point collection.
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ÖgeSustainable purchasing criteria importance rank determination with fuzzy cognitive mapping and max diff analysis(Graduate School, 2023-08-23)Sustainability has emerged as a paramount concern in contemporary business and supply chain management, necessitating the adoption of sustainable practices throughout the procurement process. Sustainable purchasing involves integrating environmental, social, and economic considerations into procurement decisions, with the aim of minimizing negative impacts on the environment and society while maximizing value for the organization and its stakeholders. The development and implementation of sustainable purchasing criteria are crucial for guiding procurement decisions and promoting sustainability within supply chains. These criteria encompass various factors, including but not limited to energy efficiency, waste reduction, fair labor practices, supplier diversity, and the use of environmentally friendly materials. By incorporating these criteria, organizations can prioritize sustainability goals and contribute to broader sustainable development objectives. Determining the importance ranks of sustainable purchasing criteria is essential for effective decision-making and resource allocation. Several methods, such as the Analytic Hierarchy Process (AHP), the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS), can be employed to assess the relative significance of different criteria. Ranking sustainable purchasing criteria allows organizations to identify priority areas and make informed procurement decisions that align with their sustainability objectives. Moreover, it facilitates the implementation of sustainability initiatives, enabling organizations to reduce their ecological footprint and foster responsible business practices. In this paper, sustainable purchasing criteria will be examined under three main headings: economic, environmental and social. There are seven criteria under these main headings. Sustainable purchasing criteria will be ranked according to their importance with Fuzzy Cognitive Mapping (FCM) and Max Diff Analysis methods. With this study, it is aimed to determine the importance levels of sustainable purchasing criteria, obtained by the participation of surveys of expert buyers in Turkey, by FCM and Max-Diff Analysis. A web-based survey was conducted to start these analyses. The data was obtained through the survey. It was desired to obtain meaningful quantitative information with the help of qualitative data and analyzes obtained by the questionnaire. With the Fuzzy Cognitive Mapping method, the criteria under each subheading were ranked according to their importance. It was requested from the participants to enter the effect of each criterion on the other criteria with the help of matrices, and with the help of iteration with the activation matrix, the importance levels of the criteria were determined according to the effect relations with each other. In Max Diff analysis, on the other hand, the participants were asked to choose the sustainable purchasing criteria as the least effective - the most effective in groups among themselves, and the importance levels of these criteria were determined accordingly. According to analyses, importance ranks are given below: For economic criteria, in both analyses, E2 – Quality of Service/Products is the most important criteria among other economic criteria, E1 – Competitive Price follows it. Rank results are very parallel. For environmental criteria, in both analyses, EN1 – Environmental Management System Compliance is the most important criteria among other environmental criteria. In Max Diff analysis, EN2 – Production Input Management Competency Level comes second where in Fuzzy Cognitive Mapping, EN3 – Recycling Management Competency Level follows EN1. For Social Criteria, in Max Diff Analysis, S3 – Product/Service Responsibility Level is the most important and S5 – Compliance with Ethical Issues is the second most important criteria. In Fuzzy Cognitive Mapping, S5 – Compliance with Ethical Issues is the most important where S2 – Human Rights Compliance Level is the second important criteria. In the future, all large, medium and small sized companies will need to adapt to sustainable purchasing criteria. And with this study, in the period when the concept of sustainability gains importance in the future, it is tried to determine how the importance levels of purchasing criteria are relative to each other.
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ÖgeGlobal goals, local voices: A multinational comparative sentiment and topic analysis of public transportation in the context of SDGs(Graduate School, 2024-05-28)In the contemporary world, public transportation emerges as a fundamental component of societal infrastructure and becomes a critical driver of economic growth, environmental sustainability, and social equity. The increasing demand for public transportation, population growth, and urbanization underscores the need for a comprehensive understanding of public sentiment toward these services. Such insights are crucial for governments to align service offerings with public expectations and optimize resource allocation. This thesis delves into the exploration and analysis of public opinion on public transportation in five culturally and geographically diverse countries, using data collected from Twitter. By applying advanced techniques in natural language processing, specifically sentiment analysis and topic modeling, the study aims to examine public perception, identifying areas of satisfaction and dissatisfaction. This analysis not only promises to offer valuable insights for enhancing transportation services but also aims to contribute to the broader discourse on sustainable development, aligning with the United Nations' Sustainable Development Goals. The use of social media data in this research underscores the potential of digital platforms as rich sources of public opinion, offering a novel approach through which urban planning and policy-making can be informed and enriched. This thesis builds upon key theories and models of sentiment analysis, topic modeling, and public transportation research. A significant research gap identified is the application of NLP techniques, to understand public opinions on public transportation systems. The thesis aims to bridge this gap by analyzing public sentiment and issues related to public transportation, thereby contributing to the understanding of public perception and its alignment with the Sustainable Development Goals. This approach challenges the current scope of sentiment analysis and topic modeling applications by extending them into the domain of public transportation. The study employs a mixed-methods approach, combining quantitative data analysis with qualitative insights. It focuses on sentiment analysis and topic modeling of tweets to determine public opinions about public transportation in the UK, USA, India, South Africa, and Australia. Data collection involved gathering 406,005 tweets via the Twitter API from January 1, 2021, to March 31, 2023, focusing on the terms 'public transportation' and 'public transport.' These tweets, characterized by their dates, user locations, and text content, underwent preprocessing, including cleaning and normalization steps like removing URLs, emojis, and stop words and applying stemming and lemmatization. The study then utilized the RoBERTa language model for sentiment analysis and Latent Dirichlet Allocation for topic modeling. The outcome of this analysis was then paired with relevant Sustainable Development Goals (SDG) targets to assess progress and perceptions in five different countries towards sustainable public transportation. The key findings reveal significant public concerns about transportation costs, infrastructure quality, safety, and service quality across the studied nations: the UK, USA, India, South Africa, and Australia. Notably, in the UK and Australia, mandatory use of masks during the COVID-19 pandemic received mixed reactions, indicating varying public perceptions of health safety measures in public transport. The study also uncovered specific challenges like women's safety in public transport in India and South Africa, highlighting the need for targeted interventions. Furthermore, the adoption of electric buses in India reflects a significant shift towards sustainable transportation. These findings have profound implications for policymakers and stakeholders in the transportation sector. They underscore the need for inclusive, equitable, and sustainable transportation policies that address public concerns and align with Sustainable Development Goals, particularly in ensuring safety, affordability, and accessibility in public transportation. The thesis offers pivotal insights into public perceptions of public transportation, uncovering the diverse impacts of geographic, cultural, and policy factors. Key findings reveal significant regional variations in sentiment and priorities, with safety, infrastructure, and costs emerging as universal concerns. The study's novel approach in pairing public sentiment with specific Sustainable Development Goals highlights the role of public transportation in achieving broader societal objectives, including gender equality, education, and public health. This work significantly contributes to the literature by providing a comprehensive, data-driven understanding of public transportation issues across various contexts, enhancing our grasp of how different factors play in shaping public opinion. The research lays the groundwork for future explorations into a broader, multi-lingual analysis of public transportation, extending to other service sectors and evolving user behaviors.
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ÖgeA simulation-based staff scheduling analysis for call centersin cargo industry(Graduate School, 2024-06-07)Call center staff scheduling problems have been studied frequently on a regular basis for many years. Call centers generally conduct their business on customers by delivering service. Problems occur especially when the density of queues is high, causing long waiting times. In terms of customer satisfaction, this outcome is undesirable. One of the reasons that causes this outcome is the inefficient personnel/job scheduling. In call centers, most of the time, the demand of service is inhomogeneous. Therefore, the incoming number of calls varies depending on the time interval of the day, in which the firm operates. The aim of this thesis is to understand appropriately how a call center operates and generate effective and efficient solutions by employing simulation. The raw data regarding the call center operations were first acquired which contained several important aspects that are beneficial to capture the behavior of the system and propose a better alternative to it. Gathered raw data had incoming call dates and several other statistical records that were kept. Firstly, this data was analyzed using MATLAB. Subsequent calculations on Matlab made it possible to put the resulting data that illustrate different aspects of the queue to the ARENA simulation program as inputs. To achieve effective and efficient scheduling, the incoming calls were categorized based on different time intervals by taking the density of calls into account across a day for 27 days. Afterward, input analysis was conducted on the ARENA Input Analyzer tool to get the best-fit distributions that were necessary in order to create a successful simulation analysis. After processes were clearly defined and mapped on ARENA, several simulation parameters were calculated and considered before conducting the analysis, one of which stands for huge importance in terms of reliability and accuracy of the outcomes, which was determining the appropriate number of replications. The results showed that there was insufficient number of employees working at that time. Additionally, employee scheduling was not conducted in an efficient way. These were the main reasons why bottlenecks occurred in the first place. In order to reinforce the solutions, a scenario analysis was conducted. Additional three scenarios were included in the simulation program and all of the scenarios were compared against each other in terms of KPIs. Finally, results showed that the simulation conducted appeared to be appropriate, and represented the overall system successfully. The scenario analysis illustrated thatrelaxing the bottleneck could be achieved when effective and efficient job scheduling is conducted. Moreover, the outcomes also indicated that customer satisfaction could be achieved by improving the existing system according to the simulation results presented. In the first section, an entry to the call center staff scheduling problem has been made. In section 2, a literature study was conducted in order to see the span and spread of techniques employed to solve the problem. A comprehensive study was conducted to see the blindspots in literature. These studies were heavily analyzed, and the outcomes were clearly illustrated. It was deducted from these studies that the use of simulation would be appropriate, specifically, discrete-event simulation. In Section 3, the methodology is proposed. After determining which technique to employ in order to solve the problem, related academic books were analyzed to come up with a fine approach to the problem. In Section 4, after creating the framework to follow, the simulation application was conducted. Firstly, the raw data was pre-processed and analyzed in Matlab, the descriptive statistics were presented, and the results were given to the ARENA simulation program to conduct input analysis. Input analysis included conducting data analysis, and determining best-fit distributions. Data analysis and finding best-fit distributions are crucially important because the ultimate aim when conducting a simulation analysis is to create an artificial system that perfectly reflects the original one. Because the raw data acquired showed seasonality and, therefore needed to be more carefully analyzed. Best-fit distributions were found for the five main data categories which were call durations, interarrival times, waiting time for missed calls, assignment time to the queue, and connection waiting time from the queue to the operator. The application chapter also included creating a process flow chart. After the system is conceptualized and input analysis is conducted, the process flow chart, which also reflects the actual simulation model that needs to be built, was drawn. Subsequently, the ARENA model was created. In the ARENA model, along with several other aspects, one main parameter was to define the minimum necessary number of replications. In order to do that, some statistical calculations and comparisons were made, and the minimum necessary number of replications was found. Finally, output and scenario analysis were conducted to better capture the the effects of changes made in order to improve the overall system. Important KPIs were collected and run for four scenarios. It seemed that waiting time in queues was caused by the insufficient number of employees working without an appropriate schedule. Additionally, this caused the problem of long waiting times in queues, in other words, bottlenecks, which also decreased the customer satisfaction level. Scenario analysis pointed out the existing system and proposed better alternatives in the subsequent scenarios in terms of KPIs. According to the results of the scenario analysis, the firm needs to hire more personnel and schedule those effectively and efficiently, as illustrated in this thesis to improve the overall call center operations. All the necessary figures and tables regarding the simulation application were given in Section 4. Additionally, in Section 5, the results of this thesis were presented and suggestions for future studies were given.
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Ögeİkinci ve üçüncü dereceden stokastik baskınlık testlerinin karşılaştırılması: Borsa İstanbul'da bir uygulama(Lisansüstü Eğitim Enstitüsü, 2022-06-16)Bir insanın satın alma gücü temelde sahip olduğu sermayeye bağlıdır. Sermaye ise ülkelerin sunduğu itibari paralar, değerli metaller, hisse senetleri, mevduat ve gayrimenkul gibi birçok farklı araçtan oluşabilmektedir. Kişinin sermayesinin gerçek değeri sahip olduğu yatırım aracına göre azalıp artabilmektedir. Bu durum yatırım ne şekilde yapılmalıdır sorusunu ortaya çıkarmıştır. Bu soruya geçmişten günümüze sunulan cevaplardan başlıca kabul edileni yatırım aracının sadece getirisine değil, sahip olduğu riske de dikkat edilmesi ve getiri ve riski beraberce en çoklayacak şekilde yatırım kararı verilmesidir. Bu kapsamda ilk yaklaşım riski azaltmak adına tek bir yatırım aracı seçmek yerine mümkün olduğunca fazla yatırım aracına sermayeyi dağıtmaktır. Bu kapsamda beklenen getiriye ulaşmak için geçmiş getirilerin ortalamasından ve riski belirlemek için bu getirilerin standart sapmasından yararlanılan ortalama - varyans optimizasyonu kullanılarak en uygun portföye ulaşılmaya çalışılmıştır. Bununla beraber bazı yatırım araçlarının genel olarak bir diğerinden daha iyi sonuç verdiği bir durumda, bir diğer deyişle baskıladığı durumda, diğer yatırım aracının kullanılmasının yanlış olduğu yaklaşımıyla stokastik baskınlık testi ortaya atılmıştır. Stokastik baskınlık testi portföyün dağılımının nasıl olacağını değil hangi yatırım araçlarının olması ve olmaması gerektiğini göstermektedir. Getiri, risk gibi odaklandığı alana göre farklı derecelerde yapılabilmektedir. Bu çalışmada 12.03.2021 ve 11.03.2022 tarih aralığında ayrı ayrı ikinci ve üçüncü dereceden stokastik baskınlık testleri; BIST 30, BIST Katılım 30, BIST Teknoloji, BIST Gıda, İçecek ve BIST Kimya, Petrol, Plastik olmak üzere beş farklı Borsa İstanbul endeksine uygulanmıştır. Stokastik baskınlık testlerinin verdiği sonuçlara göre kullanılacak hisseler seçilerek bu hisselere ortalama – varyans portföy optimizasyonu uygulanmış ve risk minimizasyonu, Sharpe oranı maksimizasyonu ve eşit ağırlıklandırma dikkate alınarak etkin portföyler oluşturulmuştur. Oluşturulan bu portföyler 14.03.2022 ve 26.05.2022 tarih aralığında test edilmiştir. Test sonucundan farklı endekslerin de kullanılması sayesinde birçok soruya cevap verilebilmiştir. Bunlardan ilki bir bütün olarak stokastik baskınlık testini kullanmanın verimli olup olmadığıdır. Bu alanda yapılan incelemede sonuçlar izlenilen endekslere göre farklı çıkmaktadır. Bu durum endekslerin dayandıkları temellerin birbirinden farklı olması ve izlenilen piyasanın stabil bir yapıda olmamasına bağlanmıştır. Risk açısından incelendiğindeyse oluşturulan etkin portföylerin riski daha yüksek çıkmıştır. Bu durum sahip oldukları hisse çeşitliliğinin daha az olmasının getirdiği bir sonuçtur. Bir diğer incelenen konu ise portföy optimizasyonunda kullanılan ağırlıklandırma yöntemlerinin karşılaştırılmasıdır. Bir önceki konuya benzer şekilde ve aynı sebeplerde getiri açısından incelenen endeksten endekse farklı sonuçlar çıkmıştır. En yüksek riske sahip olan yöntem ise sharpe oranı maksimizasyonu çıkmıştır. Diğer iki yöntemden eşit ağırlıklandırma, ele alınan bütün hisseleri portföye katarken, risk minimizasyonu yöntemi de neredeyse bütün hisseleri portföye katmaktadır. Sharpe oranı maksimizasyonunda bu durum geçerli olmadığı için riskte olumsuz ayrıştığı değerlendirilmiştir. Çalışmanın incelediği asıl konu olan ikinci ve üçüncü dereceden stokastik baskınlık testlerinin sonuçlarının birbirleriyle karşılaştırılmasındaysa net olarak her iki testin de birbirlerine karşı daha üstün olmadıkları sonucuna varılmıştır.