I'm curious about the "blank" areas in island nations like the NZ example above
A red square not catched by any airport is simply omitted. (a blank area with no red/green square is an unpopulated area and omitted)
Then on to some considerations / thoughts of the system ..Item 1
As previously posted we now already have the airports tied to the squares, and that is fully dynamic how they react.
One thing to do there is to test/code the airport vs. square "score". In other words, if many airports share a square we need to distribute the pax from these squares to the airports. This is something that's highly debatable, since studies on this matter give different data.
Generally speaking the passengers would prefer the nearest
airport, however studies show that while they do this they still actually prefer the alternative larger
airport that would be farther away compared to a small airport nearby (given that all other variables remain the same), since they think that larger airport has better services and better chances of re-routing etc. in case of problems (however they also think that larger airport is more prone to delays). (ref. a study made in University of Leeds for example)
So there's no clear method for this, and just a matter of choosing some combination.
If we use a simple method it would be simply a function of distance, airport size and the number of routes perhaps. However one main issue here is that this doesn't take into account the destinations at all. Example: if we have square X from which 100 people wish to travel to square/airport Y, and square X is catched by two airports (A & B) which both are identical in terms of the "score" (for the sake of example). This means that how it would work, in the current plans, is that airport-to-airports demands A-Y and B-Y will be the same (50 pax; since the square related score for departing pax from square X is the same for both). But the problem is that if only route A-Y exists and is flown, then naturally all 100 passengers would move to A-Y and leave the B-Y demand as zero since there's no other option. All logical so far ..
Technically this poses a challenge since the square to square demand figures cannot be stored (too many). So perhaps, as discussed, one approach could be that first we calculate the baseline airport to airport values where each "airport vs. square score" is calculated purely on distance & airport size. Let's say 65% emphasis on distance and 35% of airport size class (50% traffic class / 50% infra class) .. (though these numbers can be debated). This is the initial setting also when a game starts. Naturally if a square is catched only by 1 airport, then it would catch the entire population regardless of the distance to that airport since people don't have any other choice (and this is mainly in remote areas where there aren't too many airports).
And when game starts and routes start to appear, the system would then take into account the actual
service and routes by players to shift this demand to make the people "smart". However this is a slow process and is not able to react immediately. If for example my airline flying B-Y will close down the route (while another airline is flying A-Y at the same time) it would take up to a game month for the people to move to the A-Y route instead. In an ideal system each individual passenger would be "smart" and switch right away but it's not possible. Another thing that needs to be measured here are the prices (etc.) of the available flights; and again the issue is the slow reaction (think of the B-Y airline dumping prices and gaining all the demand, and then raising them through the roof and he'd still have the whole demand available before the system is able to update the data). Item 2
So far we already know how many passengers will depart
from each square in total (based solely on data of each square and country - no relation to airports in this part yet at all). A major thing to be worked on next are the destinations. So we need to know where the guys wish to fly from that square, and this is one of the most important parts here.
Most of the data needed for this on country and square level is collected now, and this will be transformed into actual values.
One big change is that the Y/C/F class thing will be gone and it will be replaced with passenger types who have different purposes of travel
. The main division is still three classes; leisure, business and VFR (visiting friends & relatives), with the addition of cargo (separate stuff). The three classes are roughly ~30% each, but there are huge differences in this for each country and airport, so again no reference material or study can fully give a proper baseline for this. Generally speaking though in rich countries the leisure level is higher and in poor countries it's more business-oriented flying. The VFR is then highly represented on routes where countries share close links, such as France and Algeria for example (immigrants..) - we already have a good database of these country relationships (but could be expanded even further).
Each of these pax types will have different preferences then. A leisure traveller cares just about the price and business traveller just about the schedule, if we exaggerate quite much. If we'd wish it to be even better each group could be divided into sub-groups (such as urgent business, non-urgent business etc.), but I think that's too complicated already. And according to the pax preferences you can then sell different products to them (seat quality etc).
So step 1 is to finalize the pax type calculation for each square; what kind of people depart from that location.
After this is done, the destinations need to be figured out. And naturally each pax type will have a different preference. Usually most leisure travel happens within own continent, about 80% of international tourists are from the same region (region=e.g. Europe) (ref: UNWTO Tourism Barometer)
, while business/VFR may be more of a mix of short/longhaul more. Though the proportion of longhaul leisure flights does increase once we go more into the future.
Each country will be given a countrywide values for industrial, business and tourism activity. The first two are most likely combinations of existing data (GDP related) since it's been impossible to find any suitable sources for that, and the tourism activity data has been just gathered (however it only takes into account international overnight tourist stays). All this data is then counted (just in the process of working with this) and on top of that is added the country-level data on the squares (that has been collected together). These combined values, added with some distance based data & info on country relations, will then give a single 'desirability score' for each square, for each passenger type separately.
..and that should be how we arrive to figures on where the people wish to go from each square. One possible problem spot is domestic air travel, especially in the small island nations.
Once all that is known this is then moved to airport level and it should be quite close to completion. Easier said than done though.