When analyzing Kansai International Airport there were several key themes that could be identified. Certain drivers promoted domestic as well as international passenger movement throughout Osaka Kansai International. Based on available data it was possible to forecast both international and domestic movements for passengers. The analysis and resulting economic models portrayed significant changes that will take place over a course of thirty years. In this analysis key inputs were selected for analysis. Further, interpretation of key models and systems helped produce individualized outcomes.

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There are several key dimensions to international air traffic at Osaka Kansai International Airport. There has been a significant pike in the number of flights that are taking place on an international level. Some of the commercial flights to Asia as well as those to Taiwan and South Korea have helped build momentum for international travel. The highest record numbers were seen last year for several months. There were similar aircraft movements over the years as passengers have risen considerably from around the world. Based on the current trends it is project that traffic will increase in future years as well.

The patterns of domestic travelers are significantly unique at Osaka Kansai International. Because of the record number of passengers from other countries passing through, more attention needs to be drawn to the outbound routes. This would also add to a collection of route options that include medium distance travels. Such implementation may improve access to domestic flights for passengers in the country.

In the upcoming forty years there are several themes that can be predicted with regards to air traffic. According to current growth, there will be more flights offered at international levels over the years. There will be a higher quality of experience that becomes notable around the world as other travelers seek the airport as an intermediary or final destination. This will be a continual phenomenon based on the current standards of operation.

With more routes and flights offered in proximal areas it would be possible to get better results for domestic travel as well as international.

There are several ways that this analysis has resulted in contemporary results. Utilizing the existing data and resources, a logistic regression was used to illustrate much of the growth patterns in Kansai air traffic. The results for air traffic at both international and national levels demonstrate an s curve, somewhat characteristic of logistic regression graphs. With recent growth in international tourism it is clear that there is a significant mount of potential for improvement in multiple categories and areas.

Upon interpreting the results of the economic model it is clear that there are some notable upcoming trends. Socioeconomic factors are of significant importance due to the impact that the airport has on the entire region. It is a significant economic driver in its vicinity and the changes in its business affect thousands of people on a regular basis. Suzuki, Pak and Kim (1989) have identified the importance of these factors when utilizing the OURS model. This econometric model evaluated more than one hundred and twenty areas as well as the sectors in which industry has been divided. Overall the population is affected as is the land based on certain dynamics and groups. Making forecasts for each zone plays a big part in the way that planning for the future can take place.

Overall there were multiple sets of data used in this case study. Air passengers as well as changes by registered carriers contributed greatly throughout the nation of Japan. The arrival of tourists could be stratified based on origin countries and varied significantly from the travel practices of Japanese residents. Air traffic data was also utilized in order to come to conclusions about key themes and methods in this process. Ultimately, the drivers of international versus national usage of air passenger planes are significantly different. It is possible to forecast changes based on economic models; however unknown factors and variables could influence these predictions over time.