Please follow directions or I will dispute!
Please respond to both students separately with a minimum of 100 words with references
page 1 Zachary response with references
page 2 Salvatore response with references
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?
There are many variables that can effect the elasticity of a users cost. Using the example of a single person flying air from their origin to destination comes with a variety of costs from the consumers standpoint. The individual flying has to balance the cost of the ticket, luggage, food, lodging, rental car services, etc. There are also costs that are associated with the airline industry. They are concerned with the payment of salaries to their employees, the cost fuel, and the cost associated with the upkeep of the air craft to name a few examples.
Considering the multitude of cost factors that effect the demand elasticity on this individuals travel it can be difficult but plausible to construct total traveling costs to this user. Every situation is different and the price elasticity can be effected by customer preference and company costs. For example, If the cost of fuel for the plane is higher than average or an airline has to transition to a different aircraft to carry passengers ticket prices and food prices on the plane can become more expensive. According to a recent study on price elasticity this rise in price has the ability to deter the consumer from purchasing that ticket and opt for a more affordable means (Gallo, 2015). The consumer can also determine elasticity by their preferences. For example, the extra price for a first class ticket or luxurious rental car is worth the cost for that particular consumer compared to fellow consumers.
Ultimately, if I were to create model to represent travel cost, the first objective would be to quantify the average of cost for travel through air while incorporating other variables such as higher priced airfare or overnight stay.
Good morning classmates,
When I see the word elasticity I think of what I learned in my engineering undergrad where we explored the modulus of elasticity of materials, essentially how far can you stretch a particular material under a force (F), and then return to their original shape when the force was removed. Basically we would calculate what the overall breaking strength of the material was, and without looking up a definition for elasticity of demand I would personally define it as the price limit that could be placed on any goods or service before consumers would no longer purchase the goods or service, or the breaking point at which the utility received from the goods or services are no longer worth the cost of those goods or services.
Through some research and reading, Ive found that Lorenzo Sabatelli (2016) provides a succinct definition of elasticity of demand through examining and calculating income and substitution effects (Sabatelli, 2016). Sabatelli (2016) explains that elasticity of demand is the aggregate economic measure of consumer response, or the demand response, to goods and services as a result of changes in price or income.
One of the most indicative examples of elasticity of demand is evidenced from air travel in todays COVID-19 environment. First, from the number of countries restricting travel and the general publics unwillingness to travel, the supply far outweighs the demand. Second, social distancing many airlines are implementing a 50% capacity social distancing policy to make travelers feel more comfortable or safe, which lowers the supply. Third, airline companies have cut the number of flights to various destinations daily, or wholly, thus decreasing supply. However, this affects the pricing that will be felt by the daily consumer if a typical passenger airliner carries 100 people (well assume there are no first/business class seats, just domestic flight with economy seating) from New York to Florida for $200 per person, the airline generates $20,000 before their operating expenses now implement COVID protocols which creates an available 50 seats any sane person would immediately conclude that the airline would charge $400 per person vice $200 to account for the 50% decrease in travelers to maintain generated revenue. However, with the limited number of people traveling, the airline may fill 30% of the 50% available, leaving us with 15 passengers of the original 100 passengers. It would not be in the airlines best interest to charge $1,300 per ticket to maintain operating revenue as the price point is no longer cost-effective for the convenience of travelling via air.
Elasticity of Demand Model:
In order to represent the full picture of costs associated with travelling from New York to Florida, well make the following expense assumptions:
Monthly car payment to include insurance premium
Tank of gas
Airline ticket: Class (comfort level), departure/arrival time, flight duration)
Airport/Terminal parking fees
Mileage/Wear-and-tear to personal vehicle
Travel time (traffic to the airport, aircraft delay/cancellation, time spent waiting in security, layovers)
Airport food/bar expenses
From the perspective of the individual, at least from my perspective the cost of the tank of gas, cost of the tolls and cost of the parking at the terminal would need to be cheaper than the cost of taxi from my house to the airport for me to decide to drive to the airport. The comfort level of the aircraft is not something I typically examine because the utility I receive from first class vice economy is not enough for me to spend the extra money (example of elasticity of demand through income elasticity). However, the flight duration and layovers are something I consider because my time is valuable to me and it is inconvenient for me to wait in the airport. When deciding if the layover for X number of hours is worth the difference in ticket cost, I also consider what my time will be spent doing in the airport more than likely having a beer or two and something to eat (I would estimate anywhere between $60-$100) so if the ticket differential is not greater than what I would intend on spending on food, I would opt for the non-stop or shortest duration possible.
From the perspective of the airline the elasticity of demand could be determined by several factors, many of which are unknowns. Why is the individual traveling and how much would they pay to travel? How much inconvenience will an individual assume for a lower price ticket and how much will an individual pay for convenience?
Since there are many unknowns from the perspective of the airline, elasticity of demand becomes hard to predict as the data required to make an accurate pricing forecast is not readily available. However, according to Sabatelli (2016), Contingency studies, e.g. studies of consumer willingness to pay, are often used to elicit the potential response of consumers, nevertheless they are not always financially or logistically feasible, or consistent (Sabatelli, 2016).
Measuring Elasticity of Demand:
One of the best examples of elasticity of demand that I can think of is through Singapores ride-sharing application, Grab. Like I discussed last week, private purchase of a vehicle in Singapore is astronomical so most of the general population uses mass transportation, but what if youre heading somewhere in a hurry or need to get somewhere thats a little off the beaten path? Not to worry, there are still plenty of commercially owned vehicles working for Grab that can get you where youve got to go. Sometimes, if its raining, or if its rush hour, the Grab application will automatically implement surge pricing, wherein a ride that would typically cost me $10 could now cost $15-$25 depending on the amount of users in my area currently looking for similar rides.
I use this as an example because it allows me to measure how important it is for me to leave at this specific time and if the price associated with it is worth it to me. Sometimes, I feel that I have no choice and will just pay the surge pricing and always feel the return of me being somewhere on time just is not worth the additional money.
In New York, surge pricing is not called surge pricing for the Long Island Railroad, its called peak and off-peak times. At the end of the day, the railroad charges a higher fare for those commuting during rush-hour periods. For me to travel from Penn Station in Manhattan to the Ronkonkoma train station where my vehicle is parked during peak hours, I would pay $19.75 vice paying $14.25 if travelling off-peak (Schedules & Fares, n.d.). The $5.50 difference is probably viewed by most commuting Americans an inconsequential amount of money to spend to get home a few hours earlier instead of waiting until off-peak hours return and the railroad is counting on that! If I commute to the city year-round, five days a week and only travelled peak hours on my way home, I would pay an additional $1,430 and wouldnt bat an eye.
During the high traffic hours, mass transportation using Americans will pay the additional fee because of the convenience of getting home earlier; however, if the tolls on the Throggs Neck Bridge and Whitestone Bridges out of Manhattan and onto Long Island instituted peak-pricing, many people would probably avoid travelling across the bridges in their private vehicles to avoid the additional fee, also a factor of convenience and control.
In my opinion, if an airline could use consumer purchase patterns to determine high volume purchasing times, they may also be able to institute a peak or surge price. It can already be seen that airlines implement higher prices around school vacations and holidays as many people are known to be taking family vacations or travelling for personal reasons. However, if airlines could determine the rush-hour travel for business travelers, the elasticity of demand would increase and higher, premium pricing could be charged as the expense to a company would be less scrutinized than the expense to an individual.
Sabatelli, L. (2016). Relationship between the Uncompensated Price Elasticity and the Income Elasticity of Demand under Conditions of Additive Preferences. PloS One, 11(3), e0151390. https://doi.org/10.1371/journal.pone.0151390
Schedules & Fares. (n.d.). Retrieved August 13, 2020, from http://lirr42.mta.info/fares.php