1. Database Management and Modeling
Final Project
CHENYE PAN, EN-CHIAO WEN
JIALIN ZHAO, WENQIAN WANG, XUETING SHEN
DECEMBER 7, 2015

2. AGENDA
Background
ObjecRves
Methodology
Findings
Conclusion

3. 1
BACKGROUND

4. SFO conducts a yearly comprehensive survey of
their guests to gauge saRsfacRon with their
faciliRes, services, and ameniRes.
Customer interviews held at all airport terminals
and boarding areas from May 11 through May 26,
2011
Data Source

5. 2
OBJECTIVES

6. • Understand and monitor passenger purchase
behavior and percepRon of SFO
• IdenRfy factors that have strong impact on in-terminal
purchase and SFO saRsfacRon
• Understand what different passenger groups expect
of SFO
• IdenRfy areas to improve
ObjecRves

7. 3
METHODOLOGY

8. This data set contains 3188 observaRons and 7 core
variables, including two dependent variables:
• Purchase in in-terminal retail stores
• Overall saRsfacRon
Other core variables are “Age”, “Gender”,
“Household Income”, “Times flown out from SFO”
and “Trip Purpose”.
Variables

9. Purchase
Cross-TabulaRon Analysis
Logit Regression
Sa+sfac+on
Index
Cross-TabulaRon Analysis
Logit Regression
Approach
This report’s main purpose is to analyze which passengers are
more likely to purchase in SFO and which have higher saRsfacRon
with SFO. StaRsRc measures and model are used.

10. 4
FINDINGS

11. Purchase
Age, Flying Times and Trip Purpose have
no significant associaRon with Purchase

12. • The Chi-Square staRsRcs is significant (p<0.05)
indicaRng an associaRon between Gender and
Purchase in retail stores such that the female
passengers are more likely to purchase in in-
terminal retail stores (40% versus 33%)
Measure of AssociaRon
Gender and Purchase
• Gender 0=male, gender 1=female
Purchase 0=no, purchase 1 =yes

13. • Odds raRo ≅1.3, indicaRng that females are 1.3
Rmes more likely than males to purchase
Measure of AssociaRon
Gender and Purchase
• Gender 0=male, gender 1=female
Purchase 0=no, purchase 1 =yes
Group 1
Group 2

14. • The Chi-Square staRsRcs is significant (p<0.05)
indicaRng an associaRon between Household
Income and Purchase in retail stores such that
the passengers with over 100K household income
are more likely to purchase in in-terminal retail
stores (40% versus 35%)
Measure of AssociaRon
HHI and Purchase
• HHI 0 =$100K and under, HHI 1=above $100K
Purchase 0 =no, purchase 1 =yes

15. • Odds raRo (OR) ≅1.25 means passengers with
HHI >100K are 1.25 Rmes more likely than
passengers with HHI ≤$100K to purchase.
Measure of AssociaRon
HHI and Purchase
• HHI 0=$100K and under, HHI 1=fabove $100K
Purchase 0=no, purchase 1 =yes
Group 1
Group 2

16. Gender Income
Logit
(Log of odds)
Odds of non-
purchase
Male (0) HHI ≤100K (0) 0.8028 e0.8028=
2.2318
Male (0) HHI >100K (1) 0.8028+(-0.2618)=0.5410 e0.5410
=1.7177
Female (1) HHI ≤100K (0) 0.8028+(-0.3101)=0.4927 e0.4927
=1.6367
Female (1) HHI >100K (1) 0.8028+(-0.3101)+(-0.2618)=0.2309 e
0.2309
=1.2597
!
Logit (purchase) = 0.8028 - 0.3101*Gender (Female) -
0.2618*HHI (>$100K)
• Female passengers whose HHI is
more than $100K are most likely to
purchase in the SFO retail stores
• Male passengers whose HHI ≤
$100K is least likely to purchase in
SFO retail stores
Logit Regression Model

17. SaRsfacRon
Age, Gender and Household Income have
no significant associaRon with Purchase

18. SaRsfacRon Score

19. Index

20. Measure of AssociaRon
• The Chi-Square staRsRcs is significant (p<0.05)
indicaRng an associaRon between Flying
Frequency and Overall SaRsfacRon such that the
passengers who have flown more than 6 Rmes
from SFO in the past 12 months are more likely to
have low saRsfacRon with SFO than those flown
1- 6 Rmes (31% versus 24%)
Flying Times and SaRsfacRon
• Times 0 =1-6 Rmes, Rmes 1 =more than 6 Rmes
saRsfacRon 0 =low, saRsfacRon 1 =high

21. Measure of AssociaRon
• Odds RaRo (OR) ≅0.7, indicaRng that Group 1
(those flying 6 Rmes and less) are 30% less likely
to have low saRsfacRon than Group 2 (those
flying more than 6 Rmes)
Group 1
Group 2
Flying Times and SaRsfacRon
• Times 0 =1-6 Rmes, Rmes 1 =more than 6 Rmes
saRsfacRon 0 =low, saRsfacRon 1 =high

22. Measure of AssociaRon
• The Chi-Square staRsRcs is significant (p<0.001)
indicaRng an associaRon between Trip Purpose and
Overall SaRsfacRon such that the passengers who
fly for business are more likely to have low
saRsfacRon with SFO than those who fly for non-
business (30% versus 22%)
Trip Purpose and SaRsfacRon
• purpose 0 =business, purpose 1 =non-business
saRsfacRon 0 =low, saRsfacRon 1 =high

23. Measure of AssociaRon
• Odds RaRo (OR) ≅1.5, indicaRng that Group 1
(those flying for business) are 1.5 Rmes more
likely to have low saRsfacRon than Group 2
(those flying for non-business)
Group 1
Group 2
Trip Purpose and SaRsfacRon
• purpose 0 =business, purpose 1 =non-business
saRsfacRon 0 =low, saRsfacRon 1 =high

24. Logit Regression Model
Purpose Times
Logit
(Log of odds)
odds of Low
Satisfaction
Business (0) ≤6 times (0) -0.8940 e-0.8940
=0.4090
Business (0) >6 times (1) -0.8940+ 0.2642=-0.6298 e-0.6298
=1.8772
Non-business (1) ≤6 times (0) -0.8940+(-0.3939)=-1.2879 e
-1.2879
=0.2758
Non-business (1) >6 times (1) -0.8940+0.2642+(-0.3939)=-1.0237 e
-1.0237
=0.3592
!
• Passengers who travels for
business and have flown out
from SFO for more than 6 Rmes
are least saRsfied with SFO.
• Passenger who travels for non-
business and have flown out
from SFO for 1- 6 Rmes are
most saRsfied with SFO.
Logit (low saRsfacRon) = -0.8940 - 0.3939*Purpose (non-
business) - 0.2618*Times (>6)

25. 5
CONCLUSION

26. • Female passengers and high-income passengers are more likely
to purchase in SFO
Ø SFO may provide more products and brands that cater to
high-income females
• Business passengers and passengers who have flown more than
6 Rmes out from SFO in the past 12 months are less saRsfied
with SFO
Ø Further research is needed to find out why business
passengers have low saRsfacRon and find a way to
improve the returning passengers’ saRsfacRon with SFO
Insights

27. Areas to Improve
• Artwork and exhibiRons
• Restaurants
• Retail shops and concessions
• InformaRon booths (lower level near baggage claim)
• InformaRon booths (upper level - departure area)
• Signs and direcRons on SFO airport roadways
• Airport parking faciliRes
• Long term parking lot shutle (bus ride)

28. THANK YOU!
&
GOOD LUCK WITH YOUR FINALS