With the introduction of competition into the Airline Empires demand equation, the demand curve shifts noticeably. As shown in Figure 2, the entire graph shifts to the left since there is more capacity available at the same demand. This results in a much lower fare required to achieve profitable load factors; The same drop in yield the major airlines are complaining of

Figure 2 - Example load factor distribution for a route with competition

While this system was revolutionary to online airline management simulations, it does have some major drawbacks. Firstly, by taking an average of the cities yearly enplanements to calculate demand, accurate demand between airports is impossible. Most specifically, a player inaugurating a flight between two extremely close, yet large cities, will develop a respectable profit. For example, New York?s LaGuardia and JFK airports will have a very high load factor since both of these airports generate a large number of enplanements, but very few, if any, passengers are actually flying between these two airports. The same situation results when operating a flight between to distant cities. Hong Kong generates a very large number of enplanements every year, and South Bend, IN develops enough to be included in the game, however there are actually very few passengers who fly that route. The SBN-HKG route in the current Airline Empires system would have a comparable number of passengers as the SBN-ATL route, which in reality, has many more enplanements.

Another problem with the current demand equation is the handling of connecting passengers. Currently, when a hub is designated by a player, all routes through that city are affected by a percentage of passengers entering the city. For each passenger that flies into or out of the city, they are added to the total city value for that airline at half of the fare. For instance, if you have two full 100-seat routes between your hub in Atlanta and Birmingham and Charlotte, the passenger base for each city would increase by 100 passengers (100 for each flight divided by two). By adding the total number of passengers who fly into the city to the cities yearly enplanements, an increase in load factor will result, as is found in the industry. Since each connecting passenger takes two flights for every one ticket they purchased, their ticket revenue is divided by two. While this does add incentive for players to develop a hub-and-spoke system, it falls far short of simulating the true revenues generated in an accurate connecting environment. It is from this inaccuracy that the next generation of revenue management simulations will be derived.

The premise behind most airline revenue management systems is to maximize revenue by catering to the high yield business passenger, yet minimizing unused capacity by offering otherwise unsold seats at a discount. Revenue management systems are among the most complex computer systems in the world, and attempting to simulate both the market and the reaction of one of these systems is a comparably complex task. It is no wonder then that an accurate simulation of actual airline revenue generation does not currently exist.