Relational or additional research. It brings a

March 24, 2019 Tourism

Relational database systems have changed the data landscape for businesses. No longer do organizations have to rely on past dated information, be concerned with inaccuracies in data sets, or the level of effort required to extract meaningful information from transactional data. Relational databases have enabled businesses to access multiple sets of information, in different ways, without time consuming manipulation of tables or additional research. It brings a level of sophistication to business analytics that permits more accurate insights into trends, allowing for better decision making.
As a NFP organization, international airports in Canada focus on generating economic prosperity in the region. While their influence over the airline industry is more passive than that of airlines, their strategies have impacts on the industry and the region. Understanding the passenger volumes and demographics that flow through the airport, enable strategies that differentiate and specialize on the unique factors that support the airport’s success.
By analyzing historical traffic growth against economic factors, an airport can develop air traffic forecasts that support its immediate strategic planning needs, as well as provide key inputs into the master plan. Air travel is a derived demand. Demand for air transportation between origin and destination markets is derived from the interaction of social and economic factors between these markets, shaped by carriers’ networks and available aircraft capacity. Generally, business/trade activity, tourism/visitor activity as well as visiting friends and relatives constitute the primary components of air travel at an airport. The level of aviation traffic at an airport is related to the general socio-economic conditions of the markets and regions it serves, therefore data related to these factors is key in understanding the market and predicting future trends.
Data sets include historical data on origin and destination passengers by sector and region, enplaned and deplaned passengers by sector and region, and historical data on aircraft movements by sector, region and type of operation. Economic factors such as gross domestic product, population, and fuel prices are also included. Analyzing these multiple sets of data provides more sophisticated information that can predict annual origin and destination passenger forecast, as well as annual enplaned and deplaned passengers, broken down into domestic or international passenger traffic. The output provides a forecast of traffic that feeds into the airport’s strategies. The information drives non-aeronautical strategies that cater to the unique demographic of the passenger, including concessions (restaurants, stores, and bars), or passenger services such as parking and ground transportation. Traffic volume and aircraft predictions determine terminal enhancements, or runway requirements, and informs the capital plan. Cargo strategies are developed by understanding the business and trade activity in the region.
Calgary and Edmonton International Airports compete for passenger traffic within the Alberta region. Differentiating their airports from one another has become a major component of their strategies. Building strong brand loyalty in their respective regions enables them to remain competitive in their industry, and work alongside each other. Understanding the socio-economic factors influencing passenger traffic at their airports enables them to focus on strategies that attract and serve their community.


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