March 2, 2018
March is the season for daffodils, St. Patrick’s Day, and spring break, for those among us who get spring break. With that in mind, this month on the blog we’re taking a look at whether spring break seems to have had an effect on air travel from Champaign County between 2003 and 2016.
What are our assumptions?
The best first step in any data analysis is to establish what it is we’re asking, and what our assumptions and limitations are. We’ve already stated our question above: Does the data show spring break travel having an effect on plane travel from Champaign County? If so, what is that effect?
For the purposes of this post, we’re limiting plane travel from Champaign County to enplanements at Willard Airport. Due to a lack of available, close-grained data, we are not looking at bus or train travel – but keep an eye out for those topics as possible future posts.
The data we looked at is monthly, so we identified March of each year in our study period (2003-2016) as our spring break points of interest. Since the data is not available broken down into enplanements per week, we have to look at the entire month.
Table: Willard Airport Enplanements by Month: 2003-2016Download table data for Willard Airport Enplanements by Month: 2003-2016.
Do we see upticks in enplanements in March? What about other events in the academic calendar? What other trends do we see?
To answer the first question: sometimes, and depending on what we call “upticks.” In each year in the study period, March has a greater number of enplanements than February – in that way, it’s always a consistent increase.
However, March is not a consistent high point in the year for enplanements. In seven of the 14 years in the study period (2003, 2006, 2009, 2010, 2011, 2014, and 2016), March was one of the top three months for Willard enplanements, but in three years (2004, 2012, and 2013) it was one of the bottom three months. In the other four years, the March figure was neither among the highest nor the lowest monthly enplanements. So it has been more likely for March of each year to have relatively high enplanements compared to the other months of that year, but this hasn’t happened across the board.
We can also look at other key academic calendar event months: the start of the fall semester (August), the end of the fall semester (December), the start of the spring semester (January), and the end of the spring semester (May).
There’s a distinct pattern of winter traveling lulls. For 10 of the 14 years, December is one of the bottom three enplanement months. January is among the bottom three enplanement months six times. In contrast, May and August are never among the bottom three enplanement months in any year in the study period. Both are high-travel months: May is in the top three enplanement months seven times, and August makes the top three eight times. But just because those patterns exist does not mean that they’re wholly or even partly explainable by academic travel.
The data establishes that March is somewhat more likely to have relatively high enplanements for each year, that December and January tend to have relatively low enplanement numbers, and that May and August have relatively high enplanement numbers. However, the data does not establish that the academic calendar events that occur in each of these months actually cause these high or low numbers. We may see some correlation, but, based on only the data we’re looking at, we cannot conclude causation.
The enplanement data also shows a drop-off in travelers out of Willard Airport in recent years. Clearly there are month-to-month increases and decreases, but average annual enplanement in the 2011-2016 period is significantly lower than in the 2003-2010 period.
Where does this analysis fall short?
This analysis is by no means complete or perfect. One thing to keep in mind is that academic travel to conferences and symposia is done year-round, and so many of these events are held each year that it’s impossible to analyze their effect in a simple analysis of month-by-month traffic.
Furthermore, this analysis only looks at Willard Airport, and we cannot assume that all travelers from Champaign County are choosing Willard as their departure airport. For various logistical reasons associated with individual trips, travelers at all times of year and traveling for any reason may choose different airports, meaning that their travel behaviors would not appear at all in an analysis of Willard traffic.
As we noted earlier, this analysis only covers air travel, and we posit that a significant amount of spring break travel is done by train, bus, or automobile.
Also, enplanement data only covers travelers boarding planes at Willard; no data is included in this analysis on arrivals in Champaign County. Just for measuring spring break travel, departures are more immediately relevant than arrivals, but it would be helpful in order to gain a more complete picture of travel patterns.
Finally, there is no breakdown of enplanements by reason of travel, to separate academic travel from all other travel – the logistical demands and confidentiality concerns of comprehensively collecting that data, then aggregating, cleaning, and publishing it, can be fairly described as prohibitive.
How might we expand this analysis?
To make a full study of academic travel in Champaign County and East Central Illinois, without assuming either omniscience or unlimited time and funds to collect and process traveler surveys, we can propose a couple steps for study expansion.
- Determine the scope of the expanded study: are we looking at all academic travel for any reason (e.g., including conferences and similar trips), or at recreational travel by travelers affiliated with colleges and universities?
- Explore options for getting data on other modes of travel, such as trains and buses.
- Select other, similarly sized airports, both with and without a local university, as points of comparison.
What kind of questions could this type of study answer for planning?
One area where the whole subject of air (and bus and train) travel behaviors can intersect with planning is in transportation planning. Trips that occur by the modes listed above generally include a first-mile/last-mile segment: travelers must get from their initial point of departure to the airport, train station, or bus station in order to begin the larger part of their trip. At the other end of the trip, they must get from the airport, train station, or bus station to whatever their actual final destination is. If there is a pattern of many trips from a single area (e.g., campus) to the common destination (e.g., an airport, train station, or bus station) occurring over at relatively short period of time, there may be demand for a program or service.