Kredi kartı işlemleri için üye işyeri hizmet ücreti optimizasyonu

This thesis aims to enhance the current pricing policies set to optimize customer retention by proposing enhanced methodologies, focusing on finding efficient algorithms that apply to large-scale businesses. Customer retention studies have a vital effect on companies since they affect the generated revenue and market share. This study mainly investigates pricing factors and their relationship with customer churn. The aim is to find commission rates that will be used to charge merchants when making transactions with Point of Sale (POS) devices. An important aspect to remember is the price sensitivity of those merchants as there happens to be a negative relationship between their retention, and pricing policies. We designed a nonlinear mathematical model to solve this problem. However, solving nonlinear models for large-scale problems is not effective when computational power and current solving techniques are considered. As an approach to solving this phenomenon, we discretized the nonlinear form of the model and proposed an alternative integer programming model. By doing so, solvers used to optimize the integer programming models were able to solve higher scales of the problem when compared with global nonlinear solvers. However, it is observed that IP solvers fail to solve the proposed mathematical model after a certain size. To solve this dimensionality problem, stratification techniques are used to divide the problem and optimize subparts of the whole problem separately while limitations and the objective of the problem are considered.