Respond of 100 or more words to following discussion separately on (There are several factors that affect transportation costs. I would like you all to explore costs that are associated with demand elasticity on a single user’s transportation cost. This user would be traveling via plane from their point of origin to their destination. Also how could one build a model to represent total traveling costs to this user)  Responses should be a minimum of 100 words and include direct questions.

1. Good evening all,
When exploring a single users transportation costs, I, like other posts Ive read, chose to look at my personal habits/choices on air travel. Air travel for me is either work related and funded by the government or personal and funded by me. Business travel is relatively a simple decision. I call the travel management agency we use and say I need to go from point A to point B. Outside of selecting departure and arrival times that are most beneficial to me, I really consider very little and therefore, there is little driving my demand outside of necessity.
My personal travel is typically leisure based and I consider the trip based on the package deal. Obviously, the price of an airline ticket is part of the equation, but the price of the amenities (hotel, food, rental vehicle, etc.) are also taken into the equation. Much of this is driven by the economy and, in my experience, when prices are lower across the board or I have more jingle in my pocket (i.e. my economic position has improved), I have more desire to travel. 
In the research I found, it appears that my decisions are pretty much in the norm. In a meta-study, 21 previous studies on the demand elasticity of air travel were compiled and found that price elasticity estimates suggest that tourist (personal travel) arrivals will fall 15 percent for every 10 percent rise in the cost of travel (Gillen et al. 2003).
I am no mathematical genius by any means, so any feed on my attempt at a model for total cost is much appreciated. But I would develop model that provides a composite score based on the sum of weighted factors and weighted products. Each factor (airline ticket price, lodging price, etc.) can be weighted equally or in order of importance and how well they meet your preferences. For example:
Factors (1-3 base on importance):      Cost Preference
Air fare cost(3)                                  9 = $100-200
Hotel cost(2)                                      6 = $201-400
Food cost(1)                                        3 = $401-600
                                                            0 = $600

So a proposed trip to Dallas: $300 airfare, $450 lodging, $180 food
Airfare (3)(6)=18
Hotel (2)(3)=6
Food (1)(9)=9
Composite score (18+6+9)/(3+2+1) = 33/6 = 5.5
One could add additional vacation cities or any other factors (rental vehicle, # of days, activities) to consider their overall importance in your decision making.  Compare the final scores of all options and make your decision.

2. Transportation elasticity seems to be difficult for transportation managers to project. Many factors are moving variables that can only best be estimated based off of future projections and past metrics. Transportation Demand Management (TDM) Encyclopedia identifies transit elasticity as the percentage change in transit ridership resulting from each 1% change in transit service, such as bus-miles or frequency (2018).

Some of the elasticities that can affect the demand for travel are price, route, time of travel, and, for this forum, the size or type of aircraft. For instance, the price is generally less to travel on those red eye flights that have a couple of connections because it is less desirable to get up in the middle of the night and get on a plane followed by rushing to connecting flights which generally leaves more open seats that the airline needs to fill. What makes projecting the demand elasticity most difficult is that the demand all depends on the consumers need and available funds. If the service costs more than what the customer can afford then the customer will find another way to travel or will stay home and the transportation manager has to plan based off previous data points to determine the right price to offer services and when it becomes appropriate to adjust the price and to what extent to keep those last minute customers purchasing to cover the cost of operation and come out ahead (Transportation Economics, 143-144).

To help with building a model for total traveling costs to this user we would need several data points. Things to consider for the individual users cost can go as in depth as if they are using a private auto and all the costs for their auto (i.e. insurance, maintenance, fuel, etc.), parking, baggage fees, if they are using the perks areas within the airport or paying for upgraded ticket for quicker boarding, any services that they are using on the aircraft, and travel and lodging once at the destination.

Transportation Economics, (ND). Transportation Economics. Accessed from https://engineering.purdue.edu/~ce561/classnotes/Chapter%205.pdf on 16 April 2020

3. Changes in demand can fluctuate based on a change in an attribute of a service or product provided.  When it comes to transportation costs, a single users preference or demand for a mode of transportation is largely dependent on their circumstances (lifestyle) and the trips price, utility maximization, route, time, safety, security, convenience, or comfort.  All these subjectivities make up service attributes that are accounted for in a basic demand function, which in linear form is y=b+mx (Sinha & Labi, 2007).

Since we are only concerned about a single user, a disaggregate approach is the most suitable method to building an individual choice model that helps determine the probability that an individual will choose a certain trips characteristics and attributes.  According to Sinha & Labi (2007), Depending on the number of travel alternatives and the statistical assumptions associated with the demand data, model types include logit, probit, and dogit models.

If the user is traveling by air from their point of origin to their destination, they are likely to face transportation costs such as trip fare, taxes, baggage fees, facility usage costs (WIFI on the airplane), delay and travel time costs.      We can calculate the individuals ATC with the fixed and variable costs that he or she is likely to face then estimate the users demand elasticity for different service attributes of their trip using a demand function or model.  We can also formulate the unit travel time.