Ph.D. Theses
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Browsing Ph.D. Theses by Author "Mardikyan, Sona Kunuzyan."
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Item A 360° customer lifetime value prediction method using machine learning for multi category e-commerce companies(Thesis (Ph.D.) - Bogazici University. Institute for Graduate Studies in the Social Sciences, 2023., 2023) Yılmaz, Gülşah.; Badur, Bertan Yılmaz.; Mardikyan, Sona Kunuzyan.The Customer Lifetime Value (CLV) prediction methods that are used by e-commerce companies are mainly focusing on a specific group of customers with multiple transaction data and therefore remain unable to value the one-time purchasers. As a result, the management of these companies is incapable of valuing all customers and the overall company. Thus, each type of user needs a different way to predict CLV. In this thesis, we intend to develop a novel 360° holistic technique for the prediction and use of CLV models in the marketing management of multi-category e-commerce companies to enhance their strategic decision-making. The research compared the proposed framework which was constructed with several outputs (CLV, DPC, and TAS) with other ML models to evaluate the new variables created based on relationship marketing theory (RMT) and to demonstrate the best model which is more appropriate for multi category e-commerce companies' usage. To make this result useful, we created customer clusters that enable management to separate end-users according to the three outputs. Finally, Shapley values obtained using explainable artificial intelligence (XAI) are then utilized to understand the DNN's findings. The results showed that using XAI shows which factors are more crucial to the results. Overall, the proposed model helps marketing management teams in planning their operations efficiently by differentially allocating their resources to specific types of customers based on their profitability which provides more strategic decision-making.Item The anatomy of an online social community network(Thesis (Ph.D.)-Bogazici University. Institute for Graduate Studies in the Social Sciences, 2018., 2018.) Akar, Ezgi.; Mardikyan, Sona Kunuzyan.The emergence of Web 2.0 has revolutionized the ways of communication on the Internet and has allowed people to form their virtual worlds involving online communities and social networks. People have started to generate their contents, share them, and communicate with each other in these communities and networks. In parallel to the generation of huge amount of contents in these platforms, these communities and networks have become valuable data sources for businesses. It is the fact that analysis of user content in online communities and social networks allows businesses to enhance their business value and achieve their goals. In this sense, to create and manage these communities successfully, managers need to understand how to motivate community members and keep them frequently involved. Therefore, this study employs social network analysis to map and understand the network structure of an online community and to detect sub-communities in it. Additionally, it explores and identifies user roles in an online community and proposes a research model that investigates members’ usage intentions of the community. The research model also analyzes the moderating effect of these investigated user roles on members’ usage intentions of the community. In this manner, this study combines various theories for a better understanding of what roles exist in online communities, what roles members prefer to adopt, what usage intentions members have by presenting a four-phase methodology. Additional to theoretical implications, the study also guides managers to develop motivational strategies to keep their members continually satisfied in online communities.