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Rise and Fall of People Express Airlines

People Express Airlines [1] operated from 1981 to 1987 in the Unites States. It grew to industry prominence in a period of only five years. But this dramatic growth was followed by a dramatic decline. The People Express example can be used to understand the pitfalls of fast growth strategy, using a dynamic resource-based view as proposed by John Morecroft [2].

Model of the Airline

The airline industry is modeled using tangible and intangible resources. While resources such as number of planes and staff size are tangible, service quality and airlines’ reputation are intangible.
(Press Shift + Enter to evaluate.)
In[]:=
CloudImport["https://www.wolframcloud.com/obj/7435a644-6ec7-4a8d-9989-46c1206ad3cc","MO"];
Load the People Express model developed by Guido Wolf Reichert:
In[]:=
CloudImport["https://www.wolframcloud.com/obj/f0487bd9-f100-4a5d-8f23-6edb250c05fd","MO"];
Load Modelica Standard Library 3.2.3
In[]:=
WSMLink`Library`LoadMSL["3.2.3"];
Check the model diagram:
In[]:=
SystemModel["PeopleExpress.BaseRun",{"Diagram",ImageSize->Large}]
Out[]=
People Express Boeing 747 at London Gatwick in June 1983.
Background image copyright © 1983 Eduart Marmet; licensed CC BY-SA 3.0.
If you want to modify the model, open it in Wolfram System Modeler by evaluating the following code (to be able to do this, you will need to download the notebook to your desktop and install Wolfram System Modeler):
In[]:=
SystemModeler["PeopleExpress.BaseRun","Modeling"]
This stylized interpretation of People Express consists of three subsystems: fleet, staff and passengers. These subsystems are modeled using the system dynamics metaphor of stack and flow.
Check the model diagram of a fleet subsystem:

Check the Simulation Results

Simulate the model and check the effect of parameters on the revenue passenger miles (RPM) and service quality:
(Press Shift + Enter to evaluate.)
In[]:=
[◼]
SystemModelManipulate
["PeopleExpress.BaseRun"]
Snapshot of the dashboard:
A revenue passenger mile (RPM) is a transportation industry metric that shows the number of miles traveled by paying passengers and is typically an airline traffic statistic [3].

Effect of Fleet Growth Rate on Service Quality

Modify the dashboard to limit your analysis on the effect of a fast growth rate of fleet size:
(Press Shift + Enter to evaluate.)
In[]:=
[◼]
SystemModelManipulate
["PeopleExpress.BaseRun",​​{"Plots",{"Fleet Size","Total Staff","Service Quality",​​"Revenue Passenger Miles (RPM)"},ControlTypeSetterBar},​​{{"growth",70,"Growth Rate"},10,100}​​]
Snapshot of the dashboard:
Consider a growth rate of 70%. As the fleet size increases (see Fleet Size), the number of staff (see Total Staff) also increases. But the increase in staff, mostly comprising inexperienced staff, did not translate into an increase in service quality (see Service Quality for the initial three years).
Service quality decreases and reaches a tipping point (between 1983 and 1984), after which the revenue from passengers (see Revenue Passenger Miles (RPM)) also begins to decrease and fails to bounce back.

References

[1] People Express Airlines (1980s)​
​https://en.wikipedia.org/wiki/People_Express_Airlines_(1980s)
[2] The Rise and Fall of People Express: A Dynamic Resource-Based View​
​https://proceedings.systemdynamics.org/1997/morecroft5.htm
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