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Crowdlending is a growing business model that originated from the new crowdfunding phenomenon. It consists of funding companies’ loans through joining money from many investors in exchange for regular payments. One important key value in this model is the speed of the credit approval and the investment choice. The upcoming crowdlending platforms facilitate their growth through the automation of those processes. This study explores the creation of a credit-scoring model for an entrepreneurial platform, in order to fulfill the necessity of quickly determining the risk and the characteristics of loan applications for SME companies. This study will also analyze the pricing loan strategy based on the risk of the operations. Finally, the thesis suggests a of the loans and concludes with a series of improvement measures for the model.
Although the market share of a specific airline is very often a rough estimation, it is still of great importance for the airline top management. In order to make the right strategic decision, management should be aware of its current position and its competitors. This information is important to decide on the airline’s fleet assignment, revenue management and planning and scheduling. A variety of different models exists for market size and market share forecasting. Since no single model provides accuracy, airlines usually combine and compare the results of different approaches. Generally speaking, market share can be estimated using different starting parameters, such as flight frequency, fare, quality of service, number of airplane’s seats, time of departure, etc. The market share depends also on its competitors’ strategy and current economic situation. As it is almost impossible to take into consideration all these parameters in one model, different techniques very often provide different results, and it is the task of the airline network planners to calibrate and validate the model. In this Master Thesis I consider market share as a parameter whose value is between 0 and 1 and which is calculated as a ratio of passengers travelled by a specific airline to a total number of passengers travelled between a given pairs of cities. This Master Thesis presents two objectives. First, it gives an introduction to the history of the airline industry. It analyzes the main factors affecting the demand, gives and overview of the airline network management and presents the most popular models for market size and share forecasting. Second, it estimates the airlines’ market shares for a given set of city pairs for 2013 and 2014 and finds the formula which can be used for future network planning. The estimation is conducted using the Multinomial Logit (MNL) model.