Parametric modeling for airline startup and progress

Airline industry requires large capital, has small profit margins and easily affected from economic and political crisis. Multiple airlines bankrupted and some of stranded airlines acquired by others in the last decade. Improper planning of inputs according to expected outputs is one of the main reasons for the realized bankruptcies. There are various computing methods and constraints arising from aviation regulations. Airline managements make planning decisions using these methods and constraints. But airline transportation is a dynamic industry, there are multiple interactions exist and it is hard to make correct strategic decisions using traditional production planning methods only. There are a lot of airlines performing same business and makes similar decisions that turn out operation results saved in databases. Past inputs and acquired outputs of particular airline group collected as data. Decision support system established by analyzing these data using parametric methods including data fitting and regression analysis. The operation data of thirty large world airlines were analyzed using parametric methods for eleven year period (2002-2012). Obtained stable functions used in model prepared for decision support system can be useful for airline startup and progress. Generated model can be used as a benchmarking, correction and verifying tool under general industry trends with traditional personnel and fleet planning methods for airline startup and progress. Key Words: Airline, for airline startup and progress, parametric modeling, data fitting, regression analysis, fleet and personnel planning