Abstract

Long-range demand planning and capacity management play an important role for policy makers and airline managers alike. Each makes decisions regarding allocating appropriate levels of funds to align capacity with forecasted demand. Decisions today can have long lasting effects. Reducing forecast errors for long-range range demand forecasting will improve resource allocation decision making. This research paper will focus on improving long-range demand planning and forecasting errors of passenger traffic in the U.S. domestic airline industry. This paper will look to build upon current forecasting models being used for U.S. domestic airline passenger traffic with the aim of improving forecast errors published by Federal Aviation Administration (FAA). Using historical data, this study will retroactively forecast U.S. domestic passenger traffic and then compare it to actual passenger traffic, then comparing forecast errors. Forecasting methods will be tested extensively in order to identify new trends and causal factors that will enhance forecast accuracy thus increasing the likelihood of better capacity management and funding decisions.

Notes

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Thesis Completion

2013

Semester

Spring

Advisor

Leon, Steven

Degree

Bachelor of Science in Business Administration (B.S.B.A.)

College

College of Business Administration

Degree Program

Finance

Subjects

Business Administration -- Dissertations, Academic;Dissertations, Academic -- Business Administration

Format

PDF

Identifier

CFH0004425

Language

English

Access Status

Open Access

Length of Campus-only Access

3 years

Document Type

Honors in the Major Thesis

Included in

Finance Commons

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