Evaluation of Level of Service at Airport Passenger Terminals: Individual Components and Overall Perspectives Anderson Correia Department of Civil Engineering University of Calgary- Canada
Jan 16, 2016
Evaluation of Level of Service at Airport Passenger Terminals:
Individual Components and Overall Perspectives
Anderson CorreiaDepartment of Civil Engineering
University of Calgary- Canada
Level of Service Definition
The term Level of Service expresses the quality of the experience which passengers perceive they encounter in the terminal. It addresses the wide range of factors that influence this experience.
Establishing level of service (LOS) measures is an area of interest for both airlines and airport operators.
LOS evaluations have been individually undertaken, without a standard methodology or reporting system (Humphreys and Francis, 2000).
The TRB - FAA study (TRB, 1987) recognized that the capacity of any airport passenger terminal component can not be evaluated without LOS definitions, but there is little agreement concerning these definitions.
Literature Review
Technique Employed Authors
Fuzzy set theory Park (1994); Ndoh and Ashford (1994); Teng(2000); Yen et. al (2001); Yeh and Kuo (2002).
Utility theoretic approach Omer and Khan (1998); Khan (1990); Siddiqui(1994).
Psychometrical scaling theory Muller (1987); Muller and Gosling (1991); Ndoh andAshford (1993).
Perception-response concept Mumayiz (1985); Mumayiz and Ashford (1986);Ashford (1986); Mumayz (1991); Park (1999).
Logit Models Yen (1995)
Deficiencies of Former Approaches
• No standard method.• Insufficient passenger input.• LOS developed arbitrarily.• Oversimplifications.• Focus on departing passengers.• Focus on North-American and European airports.• No airport wide LOS standards.
Research Objectives
• Development of LOS standards for individual components and for the airport terminal as a whole according to passenger perceptions and movement types.
• Complete analysis of departing passengers.• Partial analysis of arriving passengers.• Use of revealed preference data type.• Multi-attribute analysis.
Techniques Employed in This Research
• Psychometric Scaling Technique: to transform qualitative data into quantitative data.
• Regression Analysis: (1) to correlate passenger ratings of LOS and characteristics of facilities; and (2) to obtain the degree of importance of different components in the overall LOS.
Theoretical FrameworkSuccessive Categories Method (Psychometric Scaling Technique)
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LOS
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LOS
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:is category belowor at quality
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if category belowor at rated be willj Stimulus
Probability distribution function of the quantitative LOS ratings
Probability distribution function of the category boundaries
cat. 1 category 2 cat. 3 cat. 4
Quantitative continuum scale
UB1 UB
2 LOSj
UB3
Data Collection
• Rio de Janeiro International: June. 11-15. 2003
• Sao Paulo International: June. 16-22. 2003
May. 10-16. 2004
• Sao Paulo Domestic: June. 23-29. 2003
• Calgary International:
Jan. 19-23. 2004
Surveys Content
Nominal data: gender, purpose of trip (business/tourism), type of flight (international/domestic), number of checked-in bags, and party size.
User responses of LOS (divided into five categories:
1-poor, 2-regular, 3- fair, 4-good, 5-excellent).
Stimulus data: waiting time, processing time, availability of space, walking distance, total time, etc.
Results Provided
LOS standards for individual components– Curbside– Check-in counter– Security Screening– Departure Lounge– Baggage Claim
Results Provided (cont.)
• Overall LOS Measures– Walking Distance– Total Time– Orientation
• Overall LOS evaluation as a function of individual components.
1. Waiting Time at the Check-in(Sao Paulo/Guarulhos International Airport)
Group Range (min) Value (min) #
1 WT = 0 0.00 16 1.64
2 WT = 1 1.00 09 1.57
3 WT = 2 2.00 05 1.97
4 WT = 3 3.00 13 1.52
5 WT = 4 4.00 06 0.84
6 WT = 5 5.00 05 0.89
7 5 < WT 10 7.93 14 1.20
8 10 < WT 15 13.43 14 0.71
9 15 < WT 25 20.40 15 0.62
10 25 < WT 35 33.36 11 (0.52)
11 35 < WT 55 49.14 07 (1.49)
12 55 < WT 75 68.75 04 (2.63)
Total: 119
Plot of the Data and Regression Line(Check-in/Sao Paulo)
Waiting Time at the Check-inSão Paulo
-3.0
-2.0
-1.0
0.0
1.0
2.0
0 10 20 30 40 50 60 70
Waiting Time (min)
LO
S R
atin
gs
Observed
Predicted
Causal Relationships (Check-in/Sao Paulo)
LOS = 1.597 - 0.06 (WT)
R2 = 0.97
F = 262.30
Chi-Square = 13.476
(compared with 33.429 at 5% significance level)
Proposed LOS Standards(Check-in/Sao Paulo)
LOS WAITING TIME (min)
A < 1
B 1 - 17
C 17 - 34
D 34 - 58
E > 58
2. Processing Time at the Baggage Claim – Calgary Airport
Processing Time at the Baggage ClaimCalgary International Airport
-0.5
0.0
0.5
1.0
1.5
2.0
0 5 10 15 20
Processing Time (min)
LO
S R
atin
gs
Observed
Predicted
LOS Processing Time at Baggage Claim (min)
A < 1
B 1 - 14
C 14 - 20
D 20 - 26
E > 26
= 1.88 - 0.11 (PT) (t = 5.686) (t = - 4.053)R2 = 0.80F = 16.426Chi-Square = 12.631 Chi-Squarecritic = 18.307 (5% signif. - 10 d.f.)
LOSaryCa lg
3. Overall Terminal Evaluation (Departing Passengers - Sao Paulo/Guarulhos Intl. Airport)
Sec. Dep. Walking
Curb Check-in Screen. Lounge Distance Orientation Concessions
Curbside 1.0
Check-in 0.2 1.0
Security Screening 0.4 0.2 1.0
Lounge 0.3 0.2 0.3 1.0
Walking Distance 0.3 0.2 0.3 0.2 1.0
Orientation 0.3 0.4 0.3 0.3 0.4 1.0
Concessions 0.4 0.3 0.2 0.2 0.1 0.4 1.0
Composite Equation (Sao Paulo/Guarulhos International Airport)
LOS(overall) =
w0 + w1 LOS(curb) +w2 LOS(check-in) + w3 LOS(sec. sc.) + w4 LOS(lounge) +
w5 LOS(walking dist.) + w6 LOS(orientation) + w7 LOS(concessions)
Where
LOS(overall) = overall terminal LOS ratings
LOS(curb), LOS(check-in), LOS(sec. screen.), LOS(lounge), LOS(walk. dist.),
LOS(orientation), and LOS(concessions) = LOS ratings for each individual components
w0 = intercept
w1, w2, w3, w4, w5, w6, and w7 = parameters of the equation.
Parameters - Final Results (Sao Paulo/Guarulhos International Airport)
Component Parameters Standard Error t Stat P-valueIntercept 0.841 0.327 2.575 0.011Curbside 0.246 0.065 3.809 0.000Check-in 0.144 0.069 2.094 0.039Lounge 0.151 0.057 2.643 0.009Orientation 0.229 0.063 3.656 0.001Purpose 0.214 0.094 2.291 0.024R2 = 0.470F = 19.538Observations: 116
Composite Equation - Final Model (Sao Paulo/Guarulhos International Airport)
LOS(overall) = 0.841 + 0.246 LOS(curb) +0.144 LOS(check-in) +
+ 0.151 LOS(lounge) + 0.229 LOS(orientation) + 0.214 (purpose)
Main Contributions
• Provision of a comprehensive method to evaluate airport LOS according to passenger perceptions.
• Development of overall LOS measures.• Analysis of the impact of each individual
component in the overall LOS.• Validation of the technique with 400 interviewed
and observed passengers in two countries.• Practical to use: provision of A-E LOS ranges.
Conclusions
• All statistical analyses provide satisfactory goodnes-of-fit test results.
• Application of the theoretical framework provide reasonable and applied standards.
• The methodology can be applied to any airport.
• Data collection is complex, but feasible.
Future Research
• Application of the proposed methodology to various airports nationwide to obtain a comprehensive LOS evaluation.
• Verification of the impact of socio-economic variables in the perceived LOS.
• LOS of connecting passengers.