## 6 Discussion  
The focus of this study was to optimize future planning of airport terminal facilities based on traffic demand forecasts and the dominant share of airline business models. A case study was conducted at Pula Airport that provided all necessary historical data on passenger traffic demand and shares of airline business models for the period from 2009 to 2019. An analysis of the data on passenger traffic demand and shares of airline business models was conducted, and the results showed that in the period from 2009 to 2019, Pula Airport had a visible trend of change in the shares of airline business models from full-service carriers (FSC) to low-cost carriers (LCC). Based on historical data, forecasts of passenger traffic demand (plus, additionally, the number of aircraft operations) and the shares of airline business models were made using the forecasting tools of Python and MS Excel. The expected number of passengers and expected shares of airline business models were obtained, i.e., the dominant airline business model--LCC--was identified at Pula Airport. According to the obtained results, Pula Airport can expect the rise of low-cost airline flights, i.e., the share of the LCC airline business model. Results show that in the future period of 7 years, a rise is expected to go from 61% in the first year up to 70% in the last forecasted year. Results of the forecasted number of passengers (i.e., traffic demand) show that Pula Airport can also expect a rise in passenger traffic, going from 863,116 passengers in the first year of forecasting up to 1,100,747 passengers in the last year of forecasting. If an expected dominant share of the airline business models (in the case of Pula Airport, the LCC model) is obtained, it is possible to apply it to the expected number of passengers in the same year. Hence, the calculations are made for each year of the forecasting period, i.e., in the first year of the forecasting period, the expected total passenger traffic is 863,116 passengers, while the expected dominant share of airline business models is LCC with the share of 61%. Applying that share to expected total passenger traffic of 863,116 passengers, it can be calculated that 61% of 863,116 passengers, i.e., 526,500 passengers will use the services of low-cost carriers (LCCs). Analogously, in the last year of the forecasting period, the expected total passenger traffic is 1,100,747 passengers, while the expected dominant share of airline business models is LCC with the share of 70%. Applying that share to the expected total passenger traffic of 1,100,747 passengers, it can be calculated that 70% of 1,100,747 passengers, i.e., 770,522 passengers, will use the services of low-cost carriers (LCCs). In accordance with the obtained forecasts of traffic demand and the shares of airline business models, it is possible to plan the airport terminal facilities of Pula Airport and thus optimize the capacity and level of service of the passenger terminal. The IATA Airport Development Reference Manual--ADRM--was applied in this research, as it is the main document for the development of airport terminal facilities and the optimization of level of service (LOS). IATA created it for dimensioning space and facilities, determining the processing time of passengers and baggage by segments in the traffic flow, and calculating airport capacity. These IATA standards can be compared to standard capacity measures. The capacity of a passenger terminal is not uniquely determined; it depends on the desired level of service (LOS), i.e., what is the acceptable level of the number of passengers per unit of space and the acceptable waiting time of passengers in line for a particular airport. Each airport determines this individually. For example, for 100 m\({}^{2}\), the capacity is 50 passengers, i.e., 2 m\({}^{2}\) per passenger, but if 1 m\({}^{2}\) per passenger is acceptable, the capacity will be 100 passengers. Therefore, it is primarily a matter of the preferences of the airport management.