As a group of five students, we conducted a survey about reasons for students to chose their college. The survey was conducted on the SurveyMonkey.com, and got responds from students in 16 different colleges in the United State.

1. +
COLLEGE-STUDENT SURVEY –
Stephanie Levonne
PHASEYan
II
Fei
Yukihiro Tsuya
Zhiyong Yang
My (Roxy) Dinh

2. AGENDA
1. Important Attributes & Survey
2. Dummy variables & Regression model
3. Part-worths of the attributes
4. +
Relative importance of an attribute
5. Expected utility of each college choice
6. Expected market shares
7. Conclusion + Q&A

3. + IMPORTANT ATTRIBUTES:
 PRICE
 SIZE
 10K
 Large
 25K
 Medium
 50K
 Small
 RANK
 Top
25
 Others
 LOCATION
 City
 Suburban

4. +
SURVEY

5. +
REGRESSION MODEL
Utility = 8.107 – 1.172*Tuition 25K – 2.508*Tuition 50K –
2.065*Rank(others) - .463*Size(medium) - .379*Size(small) .649*Location(Suburban)

6. +
Part-Worth Utilities of the
Attributes
Part-worths
for Rank
0
-0.5
Top 25
Others
-1
-1.5
-2
-2.5
Part-worths
for Size
0
-0.1
-0.2
-0.3
-0.4
-0.5
Series
1

7. +
Part-Worths for Rank
Part-worths for Rank
0
Top 25
-0.5
-1
-1.5
-2
-2.5
Others

8. 0
10,000
25,000
-0.5
-1
-1.5
-2
-2.5
Part-worths for Price
-3
+
Part-Worths for Price
50,000

9. +
Part-Worths for Size
Part-worths for Size
0
Large
Medium
Small
-0.05
-0.1
-0.15
-0.2
-0.25
-0.3
-0.35
-0.4
-0.45
-0.5
Series1

10. Part-worths for Location
0
City
Suburb
-0.1
-0.2
-0.3
-0.4
-0.5
-0.6
-0.7
+
Part-Worths for Location

11. Relative Importance
of Each Attribute
RI for Tuition
RI for Rank
RI for Size
RI for Location
44.11%
36.33%
8.14%
11.42%
+
Highest
Lowest

12. + Expected utility of each college choice:
Ten different combinations

13. +
Expected utility of each college choice:
Lowest
Highest

14. +
Market shares of 10 combinations

Formula:

15. +
Market Shares of 10 Combinations

16. 
MS(U1) = Exp(U1)/[Exp(U1)+Exp(U2)+Exp(U3)+Exp(U4)+Exp(U5)+Exp(U6)+Exp(U7)+Exp(U8)+Exp(U9)+Exp(U10)] =
23.453/4892.438 = 0.479%

MS(U2) = Exp(U2)/[Exp(U1)+Exp(U2)+Exp(U3)+Exp(U4)+Exp(U5)+Exp(U6)+Exp(U7)+Exp(U8)+Exp(U9)+Exp(U10)] =
141.175/4892.438 = 2.885%

MS(U3) = Exp(U3)/[Exp(U1)+Exp(U2)+Exp(U3)+Exp(U4)+Exp(U5)+Exp(U6)+Exp(U7)+Exp(U8)+Exp(U9)+Exp(U10)] =
365.602/4892.438 = 7.473%

MS(U4) = Exp(U4)/[Exp(U1)+Exp(U2)+Exp(U3)+Exp(U4)+Exp(U5)+Exp(U6)+Exp(U7)+Exp(U8)+Exp(U9)+Exp(U10)] =
646.776/4892.438 = 13.220%

MS(U5) = Exp(U5)/[Exp(U1)+Exp(U2)+Exp(U3)+Exp(U4)+Exp(U5)+Exp(U6)+Exp(U7)+Exp(U8)+Exp(U9)+Exp(U10)] =
130.321/4892.438 = 2.664%

MS(U6) = Exp(U6)/[Exp(U1)+Exp(U2)+Exp(U3)+Exp(U4)+Exp(U5)+Exp(U6)+Exp(U7)+Exp(U8)+Exp(U9)+Exp(U10)] =
319.862/4892.438 = 6.538%

MS(U7) = Exp(U7)/[Exp(U1)+Exp(U2)+Exp(U3)+Exp(U4)+Exp(U5)+Exp(U6)+Exp(U7)+Exp(U8)+Exp(U9)+Exp(U10)] =
68.102/4892.438 = 1.392%

MS(U8) = Exp(U8)/[Exp(U1)+Exp(U2)+Exp(U3)+Exp(U4)+Exp(U5)+Exp(U6)+Exp(U7)+Exp(U8)+Exp(U9)+Exp(U10)] =
17.904/4892.438 = 0.366%
Lowest: Combination 8 (50k, others, large, suburban)

MS(U9) = Exp(U9)/[Exp(U1)+Exp(U2)+Exp(U3)+Exp(U4)+Exp(U5)+Exp(U6)+Exp(U7)+Exp(U8)+Exp(U9)+Exp(U10)] =
1091.164/4892.438 = 22.303%

MS(U10) = Exp(U10)/[Exp(U1)+Exp(U2)+Exp(U3)+Exp(U4)+Exp(U5)+Exp(U6)+Exp(U7)+Exp(U8)+Exp(U9)+Exp(U10)] =
2088.079/4892.438 = 42.680%
Highest: Combination 10 (10k, Top 25, medium, city)

17. +
Conclusion (from our sample)

Students wants to attend a large-sized college located in the urban area
which is ranked in the Top 25 and only costs 10k for tuition => it is difficult
to reach this ideal combination, so universities should pay attention to more
important attributes.

Tuition is the most important attribute (44.11%), while size is the least
important factor that affects a college student’s decision (8.14%)

Hence, universities should give financial incentives e.g.
scholarship, financial aids, on-campus jobs to attract the target audience:
potential college students and parents

Ranking is the second most important factor, so the admission office
should focus a lot on PR and students’ feedbacks in order to improve
ranking

18. +
THANKS FOR YOUR
ATTENTION 
Questions?