Open Access

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.

Clinical Research is expanding into an international and more regulated environment, specifically its quality management. Pharmaceuticals and Research Organizations are investing significant amounts of money as well as the regulatory agencies. The U.S. Food and Drug Administration (FDA) and the European Medicines Agency (EMA) are improving and developing regulations and meetings to standardize globally these practices. Therefore this Thesis integrates and extends the FDA and EMA recommendation of implementing “Risk based quality management” in Clinical Research protocol execution with a multisource point of view and the proposal of adding a Risk Management Report as an output, which will work also as an input for future protocols implementation. Diverse articles and regulations related with Quality Management and Clinical Research Processes were reviewed to work as a base for the analysis of this thesis. Risk Based Quality Management is the actual trend and newly implemented process to improve quality in clinical research. The goal of this Thesis is to combine the different actual factors, methods and regulations in order to expand Risk Based Quality Management and reach a better degree in quality and standardization. The question therefore is whether this redesigned Risk Based Quality Management process can really be incorporated with the actual practices, and if it is possible to adopt it in Clinical Research.

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.

In the last 30 years academics were exploring the field of ethical consumption and identified an attitude - behavior gap in the decision making process. Since then diverse studies have been implemented to understand ethical consumers' attitudes, motives and behavior. Parallel to the academic research being developed, there had been an increasing interest from the consumer side in behaving and consuming more ethically. Particularly, consumers have inclined their ethical purchases towards fair trade products. The present exploratory research implemented a quantitative metaphoric method called Zaltman Elicitation Metaphoric Technique (ZMET) to further contribute in the literature of ethical and fair trade consumption. The ZMET in-depth interviews were carried out with 10 German fair trade food consumers during the months of February and March in 2015. The results revealed a connection between participants' feelings, emotions, personal values and fair trade food consumption; likewise the research identified an association of fair trade to sustainability.