Using Predictive Analytics For Corporate Shuttle Decisions - - PowerPoint PPT Presentation
Using Predictive Analytics For Corporate Shuttle Decisions Wednesday, November 18 | 3:00 p.m. 4:30 p.m. PRESENTED BY: Matthew D. Grunenwald, PhD Student, ERAU Roger A. Parker, PhD, AirMarkets, Inc. Bruce J. Holmes, D.E., AirMarkets, Inc.
PRESENTED BY: Matthew D. Grunenwald, PhD Student, ERAU Roger A. Parker, PhD, AirMarkets, Inc. Bruce J. Holmes, D.E., AirMarkets, Inc.
Wednesday, November 18 | 3:00 p.m. – 4:30 p.m.
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– Commercial airlines operate from congested hubs offering less direct options. – Companies are beholden to commercial schedules and availability. Companies operating corporate air shuttles control the locations and schedule with direct flights for their travel demand.
and centralization of operations to hub-and-spoke system (Dempsey & Goetz, 1992).
commercial airline service; 70 with major hubs (Cannon & Richey, 2012; Quilty, 2005; NBAA, 2015; Sheehan, 2003).
employee productivity time.
– Business jet and turboprop aircraft numbers rose from 7,081 in 1980 to 21,256 by 2013 (GAMA, 2014).
forecasts.
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hinges on the assumption of the estimated productive timesaving benefit as measured by the net savings of time with a labor cost factor applied.
base assumptions for analyzing options.
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heavy-equipment manufacturing, chemical and petroleum production, and medical transportation.
between $11B and $56B, and number of employees between 19,000 and 106,000.
revenues and employees.
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function.
– Measures the contribution of various factors of a specific travel itinerary against other itineraries serving the same market.
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Utility function enables making the optimal choice for travel between options
(ABM) represents consumer behaviors for all travelers in all origins and destination for all modes of travel around the world.
probabilities of demand, market-by-market, mode- by-mode, with schedules and revenues, based on consumer behaviors and preferences.
decisions by aircraft OEMs, fleet operators, airport authorities, and investors.
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– Increased utilization of corporate shuttles optimizes business travel by minimizing travel costs and travel times, and increasing flexibility where businesses travel non-stop.
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differently.
cost as important as those with moderate income.
depends on the size of the fare.
is different than an increase of $100 to a $1000 fare.
inversely related to the value of time.
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Value of Time Value of Money
Value of Time vs. Value of Money
Data represents choices of 5,000 passenger agents
with travel is the duration of the trip.
connections or other stops along the way.
(the shortest itinerary) in the market.
itinerary is still quite long.
business trip is $200 per hour.
– For high level executives, it can be more than $10,000/hr.
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specific flight diminishes.
important.
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trip.
than the penalty for being early.
ideal time where the actual departure is close enough to the ideal.
have any associated schedule delay
adjusted to accommodate the shuttle schedule
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The closer a particular itinerary is to the ideal departure/arrival time, the better.
– Scheduled service has an associated disutility if stops are required. – The penalty for direct connections – those between airplanes from the same airline – is less than for indirect connections, between different carriers.
amenities such as in-flight service, and noise levels.
– On commercial carriers, 1st class is always better than economy class. – For shuttle or charter services, cabin comfort is always better than 1st class, for no other reason than increased privacy.
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Air shuttles minimize disutility associated with non-direct flights and commercial cabins
especially when comparing alternatives.
– Since money is a part of the utility computation, and other factors (e. g. time) are as well, it is possible to compute the dollar value of a change in the other factors. – For example, if one travel alternative takes longer than another, the dollar value of the time difference can be calculated.
utility equal for both options.
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– Random utility models do not assume that everything is known about the total utility associated with each choice – there is a random term in the model. – Each available option is assigned a probability of being chosen.
that makes the probability of each option equal for a given passenger.
here to delve into the Science.
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Compensatory value = benefit in time, money and comfort using shuttle service.
employee travel needs using some form of corporate air shuttle.
corporate air shuttle operation.
agreements, fractional ownership, leasing options, full ownership of aircraft.
department.
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commercial air service.
calculated for every potential user of the shuttle. The total benefit is the sum of compensatory values (cost savings) for all potential users.
employees from Memphis to Tampa (2:00 flight), using nominal costs for the shuttle service and air fares (exact compensatory value dependent on type and number of aircraft used).
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Total compensatory value of $127,256/year
current capacity on executive aircraft for augmenting travel requirements on appropriate city pairs compared to scheduled airline service.
– Because this operation is already familiar with Federal aviation requirements flight
– Should they increase or replace current aircraft with more or larger aircraft that are more versatile in multiple roles, such as executive transport as well as corporate air shuttle operations.
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and calculated.
personnel with very high value of time, and the employees as in the first
shuttle service and air fares, expanding the availability of shuttle service.
compensatory value dependent on type and number of aircraft used.
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Total compensatory value of $54,221/year
by computing an optimal schedule given the travel needs of the corporate shuttle customers.
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modeling genetic algorithm techniques. These methods generate an optimized air travel configuration using specified aircraft, where the optimization function is the utility compensatory value.
Charlotte (1:40 flight), given current commercial air travel options and assuming 40 employees.
aircraft configuration as well as the optimum flight configuration. Additional compensatory value of $71,113/year.
value of time, considering
– Fare costs – Value of time – Cabin comforts – Number and types of stops
– New Entrants – Expanding Executive Asset Use – Optimization of current shuttle operations
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Agent-based modeling measures the compensatory value using corporate shuttles
further research is needed to apply the model to specific operations for greater accuracy.
under unique cost structures.
solutions apart from commercial operations.
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16 16 710 710 1120 1120 1 1
( , ) ( )ln ( ) [ ( ) ( )ln ] ( ) [ ( ) ( ) ( ) ( ) ( ) ( )] ( ) ( ) ( ) ( ) ( ) ( ) ( ) ( ) ( ) ( ( ) ( ))
f d bd base dc dc ic ic st st ec ec
V i j i f j i i d d j i X j i X j i X j d j i N j i N j i X j i X j G i t j
( ) ( ) ( ( ) ( ) 1) 1 ( ) ( ( ) ( )) ( ) ( ) ( ( ) ( ) 1) 1 ( ) ( ) ( )
E L
G E E G L L
i t j a t j i a i G i t j b a i t j i t j b i i t j b
The utility passenger i uses to evaluate itinerary option j is given by where the function G is the ideal schedule delay, defined as
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The coefficients (i)’s are random variables with empirical means and standard deviations derived from extensive passenger research (Parker, 2010).
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f i
d bd base
1 1
st st ec ec
dc dc ic ic
16 16 710 710 1120 1120
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G(t1)=G(t1 – )
Departure time of flight 1 = t1 Departure time of flight 2 = t2
Ideal departure time =
G(t2)=G(t2 – )
MORNING EVENING TIME OF DAY DISUTILITY
a b
The function G is the schedule delay disutility, which represents the disutility (negative utility) of not traveling when desired. It consists of an early and late disutility curve and an indifference window around the ideal.
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makes the utility equal for both options.
equivalent is simply
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'
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that i will choose j is given by:
value between option 1 and option 2 is given by where C(1) and C(2) are the non-fare utilities associated with each option.
35 ( , ) ( , ) 1
V i j n V i k k
1 (1) ( ) (2)
'( ) (1) (2)
f
C i C
e F i f f e
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Cannon, C. R. & Richey, F. D. (2012). Practical applications in business aviation management. Lanham, MD: Government Institutes. Dempsey, P. S. & Goetz, A. R. (1992). Airline deregulation and laissez-faire mythology. Westport, CT: Quorum Books. General Aviation Manufacturers Association (2014). 2014 general aviation statistical databook & 2015 industry outlook. Washington, D.C.: General Aviation Manufacturers Association. National Business Aviation Association. (2015). Business aviation fact book. National Business Aviation Association. Retrieved from https://www.nbaa.org/business-aviation/fact-book/ Parker, R. A. (2010), Virtual Markets: The Application of Agent-Based Modeling to Marketing Science, PhD Dissertation, Univ. of Technology Sydney. Quilty, S. (2005). History, the regulation of air transportation, airports, and the Federal Aviation
https://www.aaae.org/training_professional_development/professional_development/accre dited_airport_executive_program/program_study_materials/ACC%20Module1.pdf Sheehan, J. J. (2013). Business and Corporate Aviation Management. New York, NY: McGraw- Hill Education.
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