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ÖgeThe effects of the geopolitical risks on stocks: An assessment from finance, industry and it sectors in Turkey and BRİCS countries(Graduate School, 2023)At time present time, while risk factors are determinant of the financial markets, they are generally expressed as potential losses in the literature. Geopolitical risk, which is count as one of the risk factors, pay much attention with the increasing chaoses, economic tensions and threats in the world. Before, geopolitical risk is perceived posed by geopolitical location; in today it's including risks also derive from social, political, economic and geographical location. From the view of the recent studies, geopolitical risk is in the top of the five critical risks worldwide and preceded cyber risk. Caldara and Iacoviello have created the geopolitical risk index to make sense of geopolitical risks in 2018. They divided risks into 6 sub-categories such as war, threat, terror and tension. In accordance with their results, higher geopolitical risk causes decreasing on the real activity of the economies and capital movements shifted to developed economies.(Caldara& Iacoviello,2018) Caldara and Iacoviello have raised awareness about geopolitical risks with their work and touched upon the effects of major geopolitical events. Geopolitical risks and the effects of uncertainties arising from these risks awareness will provide insights to investors and policy makers. The leading geopolitical risks announced in 2022 are as follows; covid-19, the power of technology companies, increasing wars and tensions, permanent inflation after covid, disruptions in production and supply problems. Based on these conditions, the scope of this study was determined as finance, technology and industrial companies. In the industry, finance and information technology sectors, the effects of changes in geopolitical risk and changes in stock markets in BRICS and Turkey countries have been examined comparatively. The strategic importance of the BRICS countries, the evidence in the literature that they are among the rapidly developing countries, the first emergence of Covid in China and the countries where the variants are most frequently seen are countries such as Brazil and South Africa, at the same time, BRICS geographical location and consist of the 40% of the world population. These factors have motivated to explore the relationship of geopolitical risk impacts on specific sectors in the BRICS countries. In addition, Turkey was among the 2022 geopolitical risk lists announced by the Times magazines. Toda Yamamoto causality test was used in the analysis of the study. Although the Granger test is the first causality test to enter the literature, Toda Yamamoto, unlike the Granger test, includes the variables in the analysis at their own level. This ensures that information loss is avoided in the long run, and both-sided causality testing can be done thanks to Toda Yamamoto. Therefore, examining the relationship with Toda Yamamoto will be meaningful in this respect. The VAR model was used for the Toda Yamamoto test. Based on the conclusions drawn from the VAR model results, it proceeded with appropriate unit tests such as OLS. According to the results of the study, it was concluded that there is no direct sector-based causality in the BRICS countries. For example, the increase in the geopolitical risk index in the information technology sector in Russia affects the change in information technology share prices. This could be related to the Russia-Ukraine war and the technological constraints imposed on Russia worldwide. While there is no direct causality between the stock markets in the BRICS countries and the geopolitical risk index in the examined sectors, it has been concluded that there is a bilateral causality relationship in almost every sector in Turkey.
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ÖgeThe impact of incentives and subsidies on firms' innovation performance in Turkey(Graduate School, 2025-02-06)Countries' economic growth and global competitiveness are largely dependent on their innovation capabilities. Innovation adds dynamism to economies through the development of new products, processes, and services, playing a critical role in achieving sustainable development goals. Companies can quickly adapt to market conditions and become competitive internationally through innovation. In this process, government incentives encourage investment in R&D and innovation activities, accelerating technological progress and enhancing economic growth potential. Understanding the effects of government support on firm innovation performance allows policymakers to design efficient and effective support mechanisms. Governments use various policy tools to encourage innovation, including direct financial support, tax reductions, grants, and subsidies. These supports are vital, especially for SMEs with limited access to financial resources. There is ongoing debate in academic and political circles about whether government incentives actually enhance firms' innovation capacities. The effectiveness of incentives can vary depending on the industry, company size, and technology intensity. Therefore, a thorough analysis of the real effects of government supports is crucial for implementing these policies more accurately and effectively. The aim of this thesis is to comprehensively examine the impact of government incentives and subsidies on firm innovation performance in Turkey. The research seeks to provide a clear understanding of the effectiveness of these policies by evaluating the effects of various incentive mechanisms on firms' innovative outputs. The lack of a full understanding of the outcomes and performance of incentives and subsidies constitutes the main problem area of this study. In this context, the thesis aims to offer recommendations to policymakers for making incentive policies in Turkey more strategic and targeted. By providing valuable insights that will enable the more effective design and implementation of support mechanisms, this study aims to contribute to both academic research and policy development. In this study, a comprehensive literature review was conducted, covering the impact of innovation on economic progress, various forms of government incentives, and methods for measuring innovation performance. The historical developments related to the research topic were examined in detail, and existing academic studies on the factors influencing innovation performance were analyzed. The literature review revealed that innovation performance is shaped by multiple variables and highlighted the importance of understanding the complex nature of these interactions. This extensive review serves as a foundation for developing the theoretical and methodological framework of the thesis. Based on the literature review, a model suitable for the research topic and dataset was developed. In this model, the presence of innovation in firms was considered as the dependent variable. Frequently mentioned firm characteristics in the literature were selected as control variables, while government incentives and subsidies were identified as the main independent variable. The dataset used in the analysis comes from the World Bank Enterprise Survey (WBES), which covers more than 150 countries. These surveys provide insights into various aspects of the business environment, including access to finance, corruption, infrastructure, competition, and firm performance factors that are not typically found in financial reports. The developed model was evaluated using the Logit regression analysis technique in Python. Model fit and statistical significance were examined using diagnostic measures such as Pseudo R-squared, Log-Likelihood, LL-Null, and the LLR p-value. The results indicate that the independent variables have a statistically significant effect on the dependent variable. According to the findings, the most significant impact on innovation performance comes from the ratio of R&D expenditures to total revenue. The effect of firm size is minimal. Subsidies and export rates have been observed to positively influence the probability of innovation, aligning with the existing literature. The effect of firm age, although very low, is positive and thus considered statistically significant. In the Logit regression model, calculating the actual probability requires considering the simultaneous effects of all variables. Therefore, the survey data of firms were applied to the model using mean and median values to estimate the probability of innovation in Turkey over the years, based on whether firms received subsidies. The calculations indicate an increase in innovation probability between 2002 and 2005, followed by a continuous decline after 2005. While outliers elevated overall performance in all years, the median-based calculation for 2019 shows that the innovation probability remained at only 5% for non-subsidized firms and 19% for subsidized firms. To test the developed model, sample firms were selected from one of Turkey's leading conglomerates, and their annual data for the selected variables were used to calculate innovation probabilities. The obtained probabilities were then compared with the results derived from the mean and median values of firms across Turkey. The test confirmed that the model's results align with actual data. By testing this method, it was assessed that the model could be used to evaluate a company applying for subsidies, estimate its probability of innovation before receiving support, and determine its position relative to the national average. For international comparisons, the 48 countries surveyed in the most recent 2019 survey were ranked based on their Gross Domestic Expenditure on R&D (GERD) as a percentage of GDP. According to this ranking, six countries with a higher GERD/GDP ratio than Turkey and seven countries with a lower ratio were selected. The model was applied to these selected countries, and the effects and consistency of all variables were analyzed. The marginal effects of the variables were calculated and compared. Subsequently, the model was run using the mean and median values of surveyed firms in each country, and the average innovation performance was determined based on whether firms received subsidies. These results were then compared with the findings for Turkey. In this study, the performance results of firms from 13 selected countries were compared. According to these results, Turkey has the lowest probability of innovation in the absence of subsidies. While subsidies have a positive effect in Turkey, the innovation performance increases only to 19% when subsidies are provided, indicating a limited impact of financial support. The country with the strongest effect of subsidies is Slovenia. In all countries, the model is statistically significant, and the effect of subsidies is positive. Similar to Turkey, the most influential variable on innovation performance in the selected countries has been the proportion of R&D expenditures. The effect of the number of employees is close to zero in all countries. The effect of firm age is negative in five countries, indicating that as firms grow older, their innovation performance decreases in these countries. Overall, the impact of firm age on innovation is minimal across all countries. The effect of exports is positive in all countries except for three. Limitations; The World Bank conducts Enterprise Surveys in over 150 countries. However, surveys are not conducted in the same year for all countries. This creates limitations in accessing data for specific years, such as 2019, for countries like the USA, China, OECD averages, Japan, and Korea, which constrains the scope of the research. While the literature highlights regional differences, dividing the dataset by regions results in an insufficient number of incentivized firms for meaningful analysis. Since some questions were not asked every year, they lacked continuity, and certain variables mentioned in the literature could not be included in the model.
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ÖgeStartup evaluation criteria and startup selection model for corporate incubators(Graduate School, 2024-07-05)The main goal of this thesis is to develop a thorough evaluation system for choosing entrepreneurs to receive support from corporate incubators. A methodical approach is taken in the design of the research, which combines material from academic research with input from external sources to develop a specialized evaluation procedure with the assistance of industry expertise. An in-depth literature review was the first step in the methodology, during which keywords are utilized to locate research that is pertinent to the evaluation of startups. The results of the search are sorted according to the subjects, and then they are further narrowed by the examination of the titles and abstracts. The selection is narrowed down to a final set of 28 articles for the purpose of conducting in-depth reading and analysis as a result of this approach. Following the selection of articles, the process of data extraction and refining is carried out in order to extract a full set of criteria from the articles. The elimination of duplicates and criteria that are similar results in the compilation of a list of 65 separate criteria. Criteria that are excessively specific are grouped together, which ultimately results in the consolidation of 46 criteria into a more refined form. In order to determine which criteria are the most important, a frequency analysis is carried out, which ultimately leads to the establishment of a total of 38 critical criteria. This set of requirements are broken down into five distinct categories: the team, the market, the idea or product, the finances, and the strategy. For the purpose of obtaining the perspectives of specialists from the Turkish entrepreneurship ecosystem regarding the significance of each evaluation criterion, surveys are carried out with the assistance of experts. A survey that is conducted via Google Forms is devised, and information is gathered from professionals who have specialized experience in the evaluation of startups. After that, the data that was collected is examined in order to determine which criteria received low scores and then eliminate them, another intermediate step is added that is corporate expert interviews to refine the criteria and move the perspective from general to corporate, completing the collection of evaluation criteria. In the end, 29 distinct criteria had been listed within 5 groups. Fuzzy Analytic Hierarchy Process (Fuzzy AHP) is utilized as a multi-criteria decision making method in order to carry out the process of weighting the evaluating criteria. A selected group of experts from various corporations' entrepreneurship and innovation departments, conducted pairwise comparisons to determine the relative importance of each criterion. This stage ensures that the evaluation criteria are weighted appropriately, reflecting the nuanced perspectives of individuals who have extensive expertise in the field. Finally, the team criteria category had a weight value of 31\%, the market criteria category had a weight value of 25\%, the idea/product criteria category had a weight value of 21\%, the finance criteria category had a weight value of 8\%, and the strategy criteria category had a weight value of 15\%. In the selection and ranking stage of the model, the TOPSIS method is utilized to rank the startups based on the predetermined framework of evaluation criteria. At this stage, it is possible to determine which alternative is the most suitable by calculating the degree to which it is similar to both the positive and negative ideal solutions. In general, the thesis offers a thorough and expertly validated methodology for the evaluation of startups that is specifically suited to meet the startup selection requirements of corporate incubators and accelerators. Within the context of the evaluation process, the systematic approach maintains the integrity and relevance of the review process by taking into account the various elements that contribute to the success of startups. In the context of business incubation and acceleration, the framework provides a comprehensive and individualized solution for selecting entrepreneurs through combining the theoretical framework an the practical knowledge accumulated in the industry. In conclusion, this thesis makes a contribution to the startup evaluation topic within the entrepreneurship research field by offering a structured startup selection criteria framework that includes the methodological process of multi-method MCDM-based startup selection model. Incorporating a review of the relevant literature, data extraction and refinement, expert surveys, criterion weighting, and the implementation of the TOPSIS approach are all components of the methodology. In order to provide a comprehensive evaluation of startups, the evaluation framework that was developed takes into account a variety of criteria, including the team, the market, the idea or product, the finances, and the strategy categories. It is possible for corporate incubators and accelerators to make use of this framework in order to choose and support promising entrepreneurs in an efficient manner. As for the practical implications, these criteria set and selection model can serve as a guide for startups to use it as a self-assessment tool to point their weak spots in the eyes of incubators or investors etc. Also for the policy implications; in the national and industrial level, this study can shed light on the prioritized specialities among the startups in the field so that governmental entrepreneurship support mechanisms or entrepreneurship education curriculum can be improved.
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ÖgeSon adım teslimatta otonom drone kullanımının kullanıcı kabulü(Lisansüstü Eğitim Enstitüsü, 2024-07-22)Son yıllarda, covid-19 ile birlikte hızı artarak, son adım teslimat kavramının önemi artmıştır. Hızlı tüketim mallarının online kanallar vasıtasıyla talep edilmesinde bir artış gerçekleşmiştir.. Bu alandaki talebin artmasıyla birlikte yeni ihtiyaçlar oluşmuştur. Bu ihtiyaçlara cevap olabilecek son adım teslimat kanallarından birisi de drone ile teslimat olacağı söylenebilir. Son adım teslimat ürünün müşteriye ulaştırılması için son adım olarak nitelendirilebilir. Tedarik zinciri açısından bakılacak olursa, ham maddeden nihai ürünün oluşturulup tüketiciye ulaştırılması anlamına gelen tedarik zinciri halkalarının son halkası son adım teslimat olarak adlandırılır. Drone kelimesi bir takım pervaneler vasıtasıyla uçabilen, yatay veya dikey olarak hareket edebilen, araçları ifade etmektedir. Bu pervane sayıları üründen ürüne değişiklik göstermekte olup en az 3 adet olmaktadır. Otonom drone kavramı kendi kendine dışarıdan bir müdahale olmaksızın veya kısmi müdahale ile yatay ve dikey rotalar izlenerek uçarak varış noktasına ulaşabilen araçları ifade etmektedir. Lojistik süreçlerde, ürünün tüketiciye zamanında hasarsız olarak ulaştırılması müşteri açısından önemlidir. Bu süreçlerdeki gecikme müşterinin ürüne ve markaya dair aidiyet duygusunu azaltma potansiyeline sahiptir. Bu bağlamda, son adım teslimat hızının holistik perspektifte optimum seviyeye getirilmesi şirketler açısından önem arz etmektedir. Burada optimum seviyeyi yakalayabilmiş şirketler pazar payını koruyarak veya arttırarak rekabet avantajı sağlayacaklardır. Mevcut araştırmada tüketicilerin son adım teslimatta otonom drone kullanımını nasıl algıladıkları incelenmiştir. Araştırmada yeni teknolojilerin kabulünde sıklıkla kullanılan Teknoloji Kabul ve Kullanım Birleştirilmiş Modeli (UTAUT) kullanılmıştır. Araştırmada birden fazla değişken ve arasındaki ilişkinin incelenmesi nedeniyle Yapısal Eşitlik Modeli (YEM) kullanılmıştır.278 katılımcı sorulara yanıt vermiştir. Değişkenler 5'li Likert (5= Kesinlikle Katılıyorum; 1= Kesinlikle Katılmıyorum) ölçeğinde hazırlanmıştır. Analiz sürecinde ise Smart-PLS 4 paket programı kullanılmıştır. UTAUT modeliyle oluşturulan aracı değişkenlerin (Performans Beklentisi, Çaba Beklentisi, Sosyal Etki ve Kolaylaştırıcı Koşullar) aracılık ettiği bağımsız değişkenlerin (Kalite, Teslimat Güvenilirliği, Risk ve Güven), bağımlı değişken Davranışsal Niyet üzerindeki etkisi incelenmiştir. Çalışmanın sonuçlarına göre; H1, H2, H3, H4, H5, H6, H7, H8, H9, H11 hipotezleri desteklenmiş, H10 ve H12 hipotezleri ise desteklenmemiş olduğu sonucuna ulaşılmıştır. Böylece, Desteklenen hipotezler; kalitenin performans beklentisine etkisinin olduğu görülmüştür. Kullanıcıların cevaplarına göre, Teslimat güvenliğinin, performans beklentisine etkisi vardır. Kalitenin çaba beklentisine etkisi vardır. Teslimat güvenliğinin çaba beklentisi üzerinde etkisi vardır. Riskin sosyal etkiye etkisi bulunmaktadır. Ayrıca, güvenilirliğin sosyal etkiye etkisi vardır, riskin kolaylaştırıcı koşullara etkisi vardır, güvenilirliğin kolaylaştırıcı koşullara etkisi vardır, performans beklentisinin davranışsal niyete etkisi vardır, sosyal etkinin davranışsal niyete etkisi vardır, sonuçlarına da ulaşılmıştır. Desteklenmeyen hipotezlere bakıldığında ise; çaba beklentisinin davranışsal niyet üzerindeki etkisi ve kolaylaştırıcı koşulların davranışsal niyete etkisi anlamlı değildir. Elde edilen verilerin analizi sonucunda literatüre paralel sonuçlar elde edilmiştir. Söz konusu teknolojinin yaygınlaşmasıyla birlikte, yeni bilimsel çalışmalar yapılabilir. Bu çalışmanın bilime katkı sağlayacağı ve toplumun refah seviyesinin yükselmesine etki edeceği umut edilir.
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ÖgeAraştırma & geliştirme (Ar-Ge) yatırımlarının hisse fiyatları üzerine etkisi(Lisansüstü Eğitim Enstitüsü, 2024-07-18)Şirketlerin gerçekleştirmiş oldukları Araştırma ve Geliştirme (Ar-Ge) yatırımlarının hisse senedi fiyatları üzerindeki etkisine odaklanan çalışma, şirketlerin Ar-Ge harcamaları ile hisse senedi fiyatları arasındaki ilişkiyi inceleyecektir. Çalışmada, Ar-Ge harcamalarının şirketlerin hisse senedi fiyatları üzerindeki etkisini değerlendirmek için Borsa İstanbul'da işlem gören çeşitli sektörlerden ve iş alanlarından firmaların Ar-Ge yatırım ve hisse senedi verileri kullanılacaktır. Çalışmada farklı sektör ve iş alanlarından firmaların nicel verilerinin kullanılması, çalışma sonucunda elde edilecek bulguların güvenilirliğinin ve tutarlılığının artmasına olanak sağlayacak ve aynı zamanda farklı sektörlerdeki firmaların sektörel bazda Ar-Ge yatırımlarının hisse senedi fiyat performansı üzerindeki etkilerinin anlaşılmasına yardımcı olacaktır. Araştırma nicel bir bakış açısı ile gerçekleştirilecek olup yapılacak olan analizler panel veri analizi yöntemi kullanılarak gerçekleştirilecektir. Çalışmada Ar-Ge harcamalarının şirketlerin finansal performansı üzerindeki etkisi, hisse senedi değerlemelerindeki rolü, yatırımcı davranışları üzerindeki etkileri ve şirket imajı ve müşteri güveni üzerine etkisi gibi konulara odaklanılacaktır. Ayrıca, Ar-Ge harcamalarının hisse senedi fiyatları üzerindeki etkisinin sektörel farklılıkları da firmalar bazında detaylı bir şekilde incelenecektir. Veri analizi sürecinde, bulguların güvenilirliğini ve anlamlılığını değerlendirmek için panel veri analizi yöntemi kullanılacaktır. Elde edilen sonuçlar, literatürdeki mevcut bilginin derinleşmesine katkıda bulunacak ve Ar-Ge harcamalarının şirketlerin hisse senedi fiyatları üzerindeki etkisinin de daha ayrıntılı bir şekilde anlaşılmasına katkı sağlayacaktır. Bu çalışma, Ar-Ge harcamalarının firmaların hisse senedi fiyatları üzerindeki etkisinin derinlemesine bir analizini ortaya koymaya amaçlamaktadır. Literatürde mevcut olan sınırlı ve kısıtlı bilgiyi daha da derinleştirmek ve Ar-Ge harcamalarının hisse senedi fiyatları üzerindeki etkisini daha iyi anlamak için 2016-2023 yılları arasında Borsa İstanbul'da işlem gören farklı sektör ve iş alanlarından firmaların verileri kullanılacaktır. Yapılacak olan analizlerden elde edilecek bulgular, şirketlerin Ar-Ge stratejilerini şekillendirmede ve yatırımcıların yatırım kararı alma süreçlerine ışık tutma açısından da önemli bir rol oynayacaktır. Bu çalışma, Ar-Ge harcamalarının şirketlerin hisse senedi fiyatları üzerindeki etkisine dair daha derinlemesine ve detaylı bir çalışma geliştirmek isteyen araştırmacılar, iş dünyası profesyonelleri ve yatırımcılar için değerli bir kaynak olacaktır.