First Post: A Specific Situation (1/9)

 A Case undergrad is trying to decide whether to wait for the green link shuttle or to walk to the quad from NRV in the morning. Some information to consider are the average travel times for the two options. The green link has a high variability between 7 and 30 minutes when including the wait at the stop, and walking takes a more consistent 20 minutes. The shuttle is also less consistent than walking because about 20% of the time, the bus will either take a break or turn to the Maltz parking lot the stop before it picks people up from north side, or the bus will be too full to pick up more people. There are many other factors to consider when making this decision, some of which are the weather, tardiness, and willingness to walk. For example, if its raining and I am tired, I am willing to wait for the green link even if it will take 30 minutes. However, If I have exactly 20 minutes until my class starts and have energy to walk, I will not take the shuttle that might make me late over a method that I know will make me exactly on time. Making this decision is risk assessment; Am I willing to take the potentially frustratingly long wait if it means a comfortable ride and a possibly faster travel time? I make this decision every morning when leaving home, weighing what the result would be if I chose either mode of transport for the conditions of that morning. Sometimes when I decide to walk, I will note where the Green link is on its route when I start walking. If the shuttle reaches my final stop before I do, I make a mental note to aid in my future decisions. When I measure the green link against my walking speed, I am doing an evaluation that aids in future decisions, but is not a decision in itself.

The green link decision is based on a set of factors that change constantly and unpredictably. A decision cannot be made until all the factors are considered at that moment, and any small change in the factors could be a tipping point towards one decision and another. In this sense, the shuttle decision is a chaotic nonlinear system. One aspect the shuttle example reveals is that these tipping points are very personal, and vary depending on who is deciding. Someone's own tipping points can only be determined experimentally, by observing the decision being made over and over again. I could make a research project to determine how individual preferences influence the decision. I would first numerically model a system for my own decision patterns. It would require me to derive an equation that involves some of the most important factors in quantitative form, and finding constants for those factors that puts the result over or under a certain critical value. I could then tell certain people to fill out a form every morning for the determining factors and whether they took the bus. I could then do a statistical process to determine the constants for each factor that matches their decisions. I could then numerically compare the tipping points for the shuttle decision for different people.