Effect of Education, Experience, and Media on USC Students’ Preferences for

Differentiation Strategies in New Businesses

Vincent Tsao

B.S. Business Cinematic Arts, 2014

University of Southern California

1

Literature Review

There is a wealth of research on the experience, personal qualities, and attributes of the

entrepreneur as factors that contribute to making a startup successful. This research has

determined that certain experiences, personal qualities, and attributes lead to increased

chances of success, with debate specifically on what exactly they are. For instance, a qualitative

study by LeBlanc (2013) gathered data from 16 interviews with entrepreneurs and found that

the knowledge, experience, access to information, and education of the founders allowed them

to better handle risk and start successful new businesses. Stronger risk management allowed

these entrepreneurs to make better decisions for their businesses after the initial decision to

enter the market.

A different set of key factors emerged in a study by Chatfield (2008), which found that

entrepreneurs’ initial entry decisions had little bearing on success, but rather post-startup

execution and luck were more important. This would suggest that initial entry is not the critical

period, but in reality, other research on business planning before new ventures reveals that

there are certain decisions in the initial entry that DO matter in the long-term (Chwolka 2012).

One of these is the competitive strategy that entrepreneurs choose. “A strategy, at its essence,

attempts to capture where the firm wants to go and how it plans to get there. When

entrepreneurship is introduced to strategy, the possibilities regarding where the firm can go,

how fast, and how it gets there are greatly enhanced” (Kuratko 2008). Especially in today’s

competitive landscape – one that is defined by continuous changes and intensely rivalrous

conditions - Kuratko argues that “through the effective application of entrepreneurship and

strategic leadership, new growth firms can adapt their behaviors and exploit such

opportunities” (2008).

There has been considerable research on the strategies that entrepreneurs should consider in

starting a business. Classical competitive strategy theory from Porter (1980) tells us that there

are three main strategies a firm, new or established, can pursue (Dess 1984):

1. cost leadership: winning market share by appealing to cost-conscious customers 2. differentiation: differentiating the products or services in ways that add to competitive

advantage 3. focus: choosing to compete in the mass market or in a defined, focused market segment

Experts would agree that the key message about the impact of strategy on new venture

performance is that “it all depends on the circumstances” (Sandberg 1988). But there has been

some research that suggests differentiating early from other players in the market (Sinha 2008)

or having “some type of unique selling proposition other than price that is not easily duplicated

2

by competitors” (Sandberg) is the most important and relevant strategic approach for new

ventures, though frequently at great cost and investment of time and money (Valipour 2012).

However, differentiation, according to Treacy and Wiersema (1993) can be further divided into

three sub-strategies: operational excellence (cost over choice), product leadership (superior

product), and customer intimacy (personalization and customization). But which strategy is the

‘best’ as perceived by a student entrepreneur? It is an important research question because

students are typically exposed to some of the best conditions they may ever experience as

aspiring entrepreneurs during their time in college. They enjoy expanding personal and

professional networks and access to mentors, educators, and resources. It is important to know

if students are thinking about strategy in entrepreneurship, a much less researched but vitally

important topic of entrepreneurship, in a certain way; and if so, what factors are shaping their

perspectives?

We know to some extent how new businesses are heavily affected by entrepreneurial

experience and personality when it comes to success and failure. Specifically, Kerrick (2008)

found that business students at the University of Louisville were more likely to have and pursue

entrepreneurial intentions when they were more risk-taking and creative. However, how would

the students’ experience affect which differentiation strategy they believe to be best? And how

does exposure to certain media affect their perceptions? Media defines “an image of what is

entrepreneurship and entrepreneurial phenomenon that media present to the mass people

may decide people’s attitude and affects people’s behavior” (Hang 2005) but there’s little

scientific research that identifies in what ways there is an impact. As college students, we are

beginning to really follow relevant media sources. Additionally, what’s the significance of

education and a formal learning structure? How strongly does each factor affect how student

entrepreneurs perceive the differentiation sub-strategies and whether one is more or less

effective than another? This study aims to test three factors (experience, media, and education)

specifically in the context of being a student at USC.

Overall, a literature review tells us that there are three recognized competitive strategies, and

that differentiation is the strategy perceived to be most important for new businesses. These

strategies, combined with other factors like an entrepreneur’s knowledge, education,

experience, and personality should provide key benchmarks for success. But for entrepreneurs,

do indicators like education and experience bias an individual to believe in the effectiveness of

one differentiation strategy over another? It’s a question that, if answered, could help student

entrepreneurs re-think the way that they approach starting new businesses and also help

educational institutions determine whether their curriculum is aligned with how students

interpret the effectiveness of differentiation strategies.

3

Methodology

A Qualtrics survey was distributed to USC students asking them to express, on a Likert scale, the

importance of the three differentiation sub-strategies: operational excellence, product

leadership, and customer intimacy. We also asked participants to rate the importance of the

sub-strategies on a sliding scale (assigning points out of 100) in order to compare the

importance of the sub-strategies relatively. Specifically, we took six key phrases that were

aligned with one of the three previously defined sub-strategies (two per strategy) and asked

respondents to rate the importance of each phrase to the success of a new business. We also

asked the same question replacing the key phrases with success factors and then with

challenges startups face in order to determine if respondents were consistent and unbiased by

negative or positive framing. Below are the answer choices in all 6 questions organized by their

association to one of the sub-differentiation strategies:

Product Leadership

Operational Excellence

Customer Intimacy

Strategy

Product leadership: selling superior products in the market

Operational Excellence: production efficiency leading to a high volume of sales

Customer Intimacy: creating strong relationships with customers

Differentiation: unique product for different customer segments

Low cost: selling at similar prices with lower costs than competitors

Consumer Focus: placing customer service above all other priorities

Success Factor

Unique product in the market

Pricing goods more cheaply than competitors

Providing the best customer service

Possessing the most cutting-edge features

Hiring the best talent

Attracting highly loyal customers

Challenges

Too many competitors in the

High production costs

Low quality perception among

4

market

consumers

Not enough superior features

Low profit margin

Minimal interaction with customers

Respondents were randomly assigned to one of two groups upon entering the survey; one

group was asked to answer questions thinking in the context of a “new business” and the other

in the context of an “established business.” This was an extremely important condition because

we wanted to determine if respondents felt differently when primed to think about business

generally rather than focusing on the startup environment. Our survey could be completed by

any USC student, and this random assignment allowed us to make sure there were real

differences in the way students perceive new versus established businesses. If we saw that

respondents did not differ in the way they answered questions about new versus established

businesses, then we would not be able to make any conclusions about students’ perceptions of

differentiation strategy for specifically new businesses.

We also asked questions gauging their education, personality, exposure to media, and personal

entrepreneurial experiences, respectively. First, we asked respondents what classes had they

taken and how influential were the classes in shaping entrepreneurial thinking in addition to

asking about their majors/minors and year in school (Appendix Q7, Q10, Q11). We also asked

respondents to fill out a brief “Big 5” personality test, shown in Appendix Q9 (John 2007). The

Big 5 test is recognized as a proven and basic method to describe human personality. The five

factors of openness, extraversion, agreeableness, neuroticism, and conscientiousness are

consistent across different ages and cultures and we identified the “Big 5” test as a simple,

accurate method to measure respondents’ personality. We also asked respondents to indicate

how many times per week they read media sources that we had identified as startup-focused

(Appendix Q8). Examining how much students engage with business journalism and thought

leaders is important because exposure to media-based information may influence related

perspectives that are aligned with or contrary to well-known entrepreneurship strategies.

Lastly, we asked respondents whether they had started their own business and if any family or

friends had started a business (Appendix Q12). These were demographic variables that we

wanted to test in our research beyond the experimental condition of new versus established

businesses.

After removing incomplete responses from our study, we obtained a final N of 144 responses.

From our data collection, we narrowed down and identified the following relevant variables for

5

our analysis of education, media exposure, and personal experience. We decided to leave out

the “Big 5” personality test in our results due to the wide-ranging responses and variety in

individual personalities for a limited sample size.

Results

It is important to first explain in detail our method in organizing the survey data for analysis. As

mentioned in the methodology section, each question had six key phrases that were aligned

with one of the three strategies in which respondents rated the importance of each phrase to

the success of a new business. We had exactly two phrases aligned with each of the three

strategies and combined each set of phrases into one number. From this, each question had a

number to represent the responses for product leadership, operational excellence, and

customer intimacy. Then, we sought to combine the Likert scale and slider questions together,

so we used a simple conversion formula that converts the five-point Likert scale ratings onto a

scale of 100 and then averaged the two:

((100/7)*Likert)+Slider)/2

After this conversion, we had a single chart for each set of questions asking about strategy,

success factors, or challenges. Additionally, we combined the responses across strategy, success

factors, and challenges into a total chart for each of the three sub-differentiation strategies,

and also created a graph that had no grouping or testing variable. We created a total of 25

graphs from the data.

Each graph will display the average mean for respondents’ answers. The data table of the actual

means is displayed below the graph. The Y-axis scale was zoomed into 35 to 55 to better display

the data. Included in the graphs are standard error bars that are equal to the bounds of the

confidence interval, the range in which we can be 95% sure the true value falls. The confidence

interval bounds are calculated to be from [mean-1.96*SE, mean+1.96*SE]. On the graphs, any

bars that don’t overlap are defined as “significantly different”, which would indicate that there

is a conclusive difference between the means. On the x-axis, product leadership, operational

excellence, and customer intimacy are abbreviated as PL, OE, and CI respectively.

6

Stage of a Business

This was the test condition in which respondents were randomly assigned. There were 74

respondents who received the “New” condition in their survey (refer to Q1 in Appendix), and

70 who received the “Established” condition. We found no significant effects between

respondents who saw new or established questions in the survey on their ratings of importance

for PI, OE, and CI. As Figure 1 below displays, the bounds for each sub-differentiation strategy

overlap and tell us that there is no significant difference between the means. For individual

graphs displaying the results for strategies, success factors, and challenges, refer to Appendix

items 1-3.

Figure 1.

Education

To test education, we asked questions about the respondents’ majors, years in school, and the

number of entrepreneurship-related classes taken at USC. We obtained a range of responses

for majors and consolidated them into two main groups: those who were pursuing business,

PL OE CI

New 45.52622265 41.36759974 49.85006435

Established 45.07857143 44.15238095 49.27244898

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Me

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Stage of Business vs. Importance of Strategy, Success, and Challenge

New

Established

7

accounting, joint business degree, or world bachelors in business degrees and those who were

NOT pursuing any of the previously listed degrees. There were 79 respondents identified as

business-related majors and 65 respondents identified as non-business. We found no significant

effects between business and non-business students on their ratings of importance for PI, OE,

and CI. As Figure 2 displays, the bounds for each sub-differentiation strategy overlap and tell us

that there is no significant difference between the means. For individual graphs displaying the

results for strategies, success factors, and challenges, refer to Appendix items 4-6.

Figure 2.

Additionally, we consolidated students into two groups based on their listed year in school:

underclassmen (including 1st and 2nd years) and upperclassmen (including 3rd and 4th years). We

did have graduate students, but did not include them in this particular test due to the limited

sample size. There were 47 respondents identified as underclassmen and 87 identified as

upperclassmen. We found no significant effects between underclassmen and upperclassmen

students on their ratings of importance for PI, OE, and CI. As Figure 3 displays, the bounds for

each sub-differentiation strategy overlap and tell us that there is no significant difference

PL OE CI

Business major 45.50904159 42.61784207 49.98342375

Non-business 45.06501832 42.8470696 49.06593407

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Major vs. Importance of Strategy, Success, and Challenge

Business major

Non-business

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between the means. For individual graphs displaying the results for strategies, success factors,

and challenges, refer to Appendix items 7-9.

Figure 3.

Our final variable to test the effect of education was the cumulative number of

entrepreneurship-related classes the respondents had taken. We identified a list of classes that

taught or introduced relevant entrepreneurial concepts across finance, marketing, operations,

strategy, management, and planning (Appendix Q7). We consolidated student responses into

three groups based on the number of classes they had taken: 0 (not interested in business or

entrepreneurship at all), 1-4 (minors or interested students), and 5+ (majors or students

seeking to pursue entrepreneurship). There were 44 respondents identified as being in the first

group, 48 in the second group, and 52 in the third group. We found no significant effects

between students who had taken varying numbers of classes on their ratings of importance for

PI, OE, and CI. As Figure 4 displays, the bounds for each sub-differentiation strategy overlap and

PL OE CI

Underclassmen 46.14488349 43.54736575 49.87208713

Upperclassmen 45.16817187 42.33565955 49.42829776

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Year in School vs. Importance of Strategy, Success, and Challenge

Underclassmen

Upperclassmen

9

tell us that there is no significant difference between the means. For individual graphs

displaying the results for strategies, success factors, and challenges, refer to Appendix items 10-

12.

Figure 4.

Number of Entrepreneurship-related Media Sources Read Weekly

In order to measure the effect of media exposure, we asked respondents to check all of the

media sources they read on a weekly basis from a list of sources we curated based on the

relevance and frequency of entrepreneurship-related content (Appendix Q8). The higher the

number of sources read, the more exposure an individual would face, and potentially bias. We

consolidated responses into three groups based on the total number of sources they read

weekly: 0 (individuals who are not seeking out entrepreneurship-related content), 1-2

(individuals who have a casual interest), 3+ (individuals who are actively seeking out

entrepreneurship content in the media). There were 64 respondents identified as being in the

PL OE CI

0 45.10010823 43.90205628 47.87554113

1 to 4 45.63507326 42.83127289 51.07119963

5+ 45.14608135 41.51984127 49.49479167

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# of Entrepreneurship-related Classes Taken vs. Importance of Strategy, Success, and Challenge

0

1 to 4

5+

10

first group, 46 in the second, and 34 in the third. We found no significant effects between

students who had taken varying numbers of classes on their ratings of importance for PI, OE,

and CI. As Figure 5 displays, the bounds for each sub-differentiation strategy overlap and tell us

that there is no significant difference between the means. For individual graphs displaying the

results for strategies, success factors, and challenges, refer to Appendix items 13-15.

Figure 5.

Startup Experience

Our final variable was measuring the effect of personal startup experience. We asked

respondents to identify whether they had been personally involved in founding a new business

(Appendix Q12). Responses were either yes, which was scored as startup experience, or no,

which was scored as no startup. There were 19 respondents who had startup experience and

125 who did not. We found no significant effects between students who had taken varying

PL OE CI

0 45.48995536 43.6421131 48.7922247

1 to 4 45.28881988 42.78519669 50.72851967

5+ 45.23091737 41.48914566 47.92139356

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# of Entrepreneurship-related Media Sources Read vs. Importance of Strategy, Success, and

Challenge

0

1 to 4

5+

11

numbers of classes on their ratings of importance for PI, OE, and CI. As Figure 6 displays, the

bounds for each sub-differentiation strategy overlap and tell us that there is no significant

difference between the means. For individual graphs displaying the results for strategies,

success factors, and challenges, refer to Appendix items 16-18.

Figure 6.

Totals

To conclude our analysis, we created a table that did NOT include any grouping variables in

order to determine whether there were differences in the perception of PI, OE, and CI in the

sample as a whole. Figure 7 shows that there is a significant difference between CI and both PI

and OE. Therefore, we can conclude that the respondents in the survey perceive CI to be more

important in the consideration of strategy, success factors, and potential challenges for a

PL OE CI

Startup experience 45.16619048 43.03695238 49.7587619

No startup 46.24561404 40.64473684 48.3226817

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Startup Experience vs. Importance of Strategy, Success, and Challenge

Startup experience

No startup

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business than the two other sub-differentiation strategies. There is no significant difference

between PI and OE so we conclude our results section.

Figure 7.

Discussion

Overall, the only significant insight from our data was that customer intimacy was rated to be

consistently more important than both product leadership and operational excellence. This in

itself was an interesting finding as we were expecting to find that product leadership would be

perceived as the most important strategy, success factor, and challenge in new businesses.

Applying this finding to a real life scenario, students who seek to start new businesses would be

smart to pay special attention to customer intimacy when determining the key strategies,

success factors, and challenges that will drive the business. On the university side, the school

PL OE CI

Total 45.30239704 42.75999035 49.56125666

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Cumulative Importance of Strategy, Success, and Challenge (n=144)

13

should understand that if students perceive customer intimacy to be the most important sub-

differentiation strategy, the curriculum is either shaping this perspective purposefully or

accidentally. Because we do not know the intention of the curriculum, we can only propose

that administrators, faculty, and other groups that influence the curriculum be especially aware

of this research that pinpoints focusing on customer intimacy as a key strategy for businesses

and evaluating the effect that the current curriculum is having on this student perception.

Specifically, we were focused on the effect of education because academia is the setting in

which this research will likely have the greatest impact.

However, because our experimental treatment of testing whether the stage of a business had a

an effect on perceptions of the differentiation sub-strategies established that there was not a

significant difference in the way that people perceived the importance of the sub-strategies for

a new or established business; our results could not be applied specifically to new businesses,

which was the initial intention of the project. We were also not able to make conclusions about

the effect of education, experience, or media on the preferences for the sub-differentiation

strategies. To clarify these findings, we are not to concluding that there are NO differences in

how business majors or non-business majors, for instance, perceive the importance of the three

sub-strategies, but rather that the differences are small enough in the context of this

experiment that we cannot claim with 95% confidence that this is true. With the confidence

interval bounds on the graph, we observed that there is a chance that the true means could be

any number in the range of the bounds, and we do not have 95% confidence that the mean of

how important a business major perceives product leadership is definitively higher than the

mean of how important non-business majors perceive product leadership. By addressing the

limitations of our study, we believe that more of our results could have been statistically

significant.

We identified the most important limitations of our study that, if remedied, could have resulted

in significant differences in the means of PL, OE, and CI across our testing variables. With a

sample size of only 144 respondents, we had limited sample sizes when we divided the

respondents down even further based on major, year in school, etc. Additionally, the low

sample sizes directly resulted in larger standard errors and thus bigger confidence intervals in

which the true means had a larger possible range. Another significant limitation of this study

was related to the high number of unique terms and phrases that were potentially confusing to

survey respondents. Even though we included descriptive statements and clear directions,

there was entrepreneurship and strategy-specific terminology that was difficult to define

concisely. And lastly, there were differences in how respondents perceived the phrases that we

14

classified as falling under product leadership, operational excellence, or customer intimacy. As

listed in the methodology, we made assumptions based on research about which key phrases

were most highly associated with a particular differentiation sub-strategy. However, we openly

acknowledge that our definitions might conflict with others’, and that many of these phrases

could arguably fall under more than one of the sub-strategies. Therefore, a more refined and

well-defined set of key phrases based on targeted research and feedback from experts would

make a noticeable difference on the results.

Future research could include much larger scale testing across the USC campus and other

campuses across the nation. Additionally, based on our findings that customer intimacy is

perceived to be more important than product leadership and operational excellence, there

could be studies on why this is the case. Furthermore, referring back to the original purpose of

this study, it would be important to understand whether a strong belief in customer intimacy is

justified by the quantifiable success of businesses and new ventures. Similarly, there is also new

reason to re-evaluate the business and entrepreneurship curriculum to test whether the

perceived learnings of the students match the stated goals of the institution and its curriculum.

15

Acknowledgements

I would like to thank my faculty advisor and mentor, Professor Victor Bennett at the USC

Marshall School of Business, for his mentorship and guidance this academic year in helping me

define and pursue this project.

I would also like to thank Professor Lucy Lee at the USC Marshall School of Business for her

guidance throughout the writing and execution of my analysis.

16

Appendix

Figure 1.

PL OE CI

New 49.10666023 40.72201 51.9667

Established 49.5 43.6551 49.70204

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Stage of Business vs. Importance of Strategy

New

Established

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Figure 2.

PL OE CI

New 44.55260618 40.31322394 49.78667954

Established 44.01020408 44.71887755 49.99540816

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53

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Stage of Business vs. Importance of Success Factor

New

Established

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Figure 3.

PL OE CI

New 42.91940154 43.06756757 47.79681467

Eststablished 41.7255102 44.08316327 48.11989796

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Stage of Business vs. Importance of Challenge

New

Eststablished

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Figure 4.

PL OE CI

Business major 49.24095841 41.34538879 51.72830018

Non-business 49.36703297 43.12307692 49.81758242

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Major vs. Importance of Strategy

Business major

Non-business

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Figure 5.

PL OE CI

Business major 45.25542495 41.96745027 49.66681736

Non-business 43.11428571 43.04725275 50.15714286

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Major vs. Importance of Success Factor

Business major

Non-business

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Figure 6.

PL OE CI

Business major 42.03074141 44.54068716 48.55515371

Non-business 42.71373626 42.37087912 47.22307692

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53

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Major vs. Importance of Challenge

Business major

Non-business

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Figure 7.

PL OE CI

Underclassmen 50.08890578 41.59042553 50.64589666

Upperclassmen 49.10837438 42.73522167 50.97249589

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Year in School vs. Importance of Strategy

Underclassmen

Upperclassmen

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Figure 8.

PL OE CI

Underclassmen 45.85942249 43.76975684 49.35258359

Upperclassmen 43.84688013 41.52791461 50.33949097

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Year in School vs. Importance of Success Factor

Underclassmen

Upperclassmen

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Figure 9.

PL OE CI

Underclassmen 42.48632219 45.28191489 49.61778116

Upperclassmen 42.54926108 42.74384236 46.9729064

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Year in School vs. Importance of Challenge

Underclassmen

Upperclassmen

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Figure 10.

PL OE CI

0 48.86444805 44.28571429 48.48944805

1 to 4 49.48076923 41.56936813 52.69986264

5+ 49.49702381 40.81473214 51.05729167

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# of Entrepreneurship-related Classes Taken vs. Importance of Strategy

0

1 to 4

5+

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Figure 11.

PL OE CI

0 44.13798701 44.13068182 48.50081169

1 to 4 45.20398352 42.87019231 51.3489011

5+ 43.4360119 40.46875 49.57738095

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# of Entrepreneurship-related Classes Taken vs. Importance of Success Factor

0

1 to 4

5+

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Figure 12.

PL OE CI

0 42.29788961 43.28977273 46.63636364

1 to 4 42.22046703 44.05425824 49.16483516

5+ 42.50520833 43.27604167 47.84970238

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# of Entrepreneurship-related Classes Taken vs. Importance of Challenge

0

1 to 4

5+

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Figure 13.

PL OE CI

0 48.66852679 43.93694196 50.08426339

1 to 2 49.625 42.19487578 51.73602484

3+ 50.03991597 38.71638655 51.15966387

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# of Entrepreneurship-related Media Sources Read Weekly vs. Importance of Strategy

0

1 to 2

3+

29

Figure 14.

PL OE CI

0 44.04631696 41.95424107 48.93247768

1 to 2 45.14751553 42.30900621 51.28571429

3+ 44.29464286 45.35714286 45.16964286

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# of Entrepreneurship-related Media Sources Read Weekly vs. Importance of Success Factor

0

1 to 2

3+

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Figure 15.

PL OE CI

0 43.75502232 45.03515625 47.35993304

1 to 2 41.0939441 43.85170807 49.16381988

3+ 41.35819328 40.39390756 47.43487395

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# of Entrepreneurship-related Media Sources Read vs. Importance of Challenge

0

1 to 2

3+

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Figure 16.

PL OE CI

Startup experience 48.78428571 42.804 51.01171429

No startup 52.67669173 37.83082707 49.90601504

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Startup Experience vs. Importance of Strategy

Startup experience

No startup

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Figure 17.

PL OE CI

Startup experience 44.26828571 42.62971429 50.64485714

No startup 44.42481203 41.30451128 44.90977444

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Startup Experience vs. Importance of Success Factor

Startup experience

No startup

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Figure 18.

PL OE CI

Startup experience 42.446 43.67714286 47.61971429

No startup 41.63533835 42.79887218 50.15225564

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Startup Experience vs. Importance of Challenge

Startup experience

No startup

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Qualtrics Survey (Full Transcript)

University of Southern California Marshall School of Business

INFORMED CONSENT FORM FOR NON-MEDICAL RESEARCH

**************************************************************** INFORMED CONSENT TO PARTICIPATE IN RESEARCH Subject Pool Participants PERCEPTIONS STUDY You are invited to participate in a research study conducted by Vincent Tsao of the USC Marshall School of Business. You were chosen to participate in this study because you are aged 18 or older and volunteered to participate. Your participation is voluntary. You should read the information below, and ask questions about anything you do not understand, before deciding whether to participate. Please take as much time as you need to read the consent form. You may also decide to discuss participation with your family or friends. If you decide to participate, clicking next will be the signing of consent. You will be given a copy of this form upon request. PURPOSE OF THE STUDY We are asking you to take part in a research study because we are trying to learn about factors that can influence perceptions of people and behaviors. The study is designed to enable us to understand the effect of various psychological and sociological phenomena that can influence perceptions. PROCEDURES You will complete several questionnaires. The study will take about 10 minutes in total. POTENTIAL RISKS AND DISCOMFORTS There are no anticipated risks or discomforts associated with this study. POTENTIAL BENEFITS TO SUBJECTS AND/OR TO SOCIETY The study is not designed to benefit you directly. Society may benefit from our increased understanding of how people perceive people and things. PAYMENT/COMPENSATION FOR PARTICIPATION You have the option of being entered in a drawing for one of two $25 gift cards. CONFIDENTIALITY

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Any identifiable information obtained in connection with this study will remain confidential and will be disclosed only with your permission or as required by law. Your name will not be linked to your responses, the data will be coded with a number. Data will be stored in a locked office, and/or on secure computer accounts, for a period of 3 years after the publication of the study. There will be no way to link individuals to participation in the study. When the results of the research are published or discussed in conferences, no information will be included that would reveal your identity. PARTICIPATION AND WITHDRAWAL You can choose whether to be in this study or not. If you volunteer to be in this study, you may withdraw at any time without consequences of any kind. You may also refuse to answer any questions you don’t want to answer and still remain in the study. The investigator may withdraw you from this research if circumstances arise which warrant doing so. If the procedures of the study are unacceptable to you for any reason, your alternative is to not participate in the study without penalty or credit. ALTERNATIVES TO PARTICIPATION Your alternative is to not participate. IDENTIFICATION OF INVESTIGATORS If you have any questions or concerns about the research, please feel free to contact Professor Bennett at vbennett@marshall.usc.edu or at Marshall School of Business, University of Southern California, Los Angeles, CA 90089-0808. RIGHTS OF RESEARCH SUBJECTS You may withdraw your consent at any time and discontinue participation without penalty or credit. You are not waiving any legal claims, rights or remedies because of your participation in this research study. If you have questions regarding your rights as a research subject, contact the University Park IRB, Stonier Hall (STO) 224a, MC 1146, Los Angeles, CA 90089-1146, (213) 821-5272 or upirb@usc.edu.

This study is intended for USC students. If you are not a USC student, please do not continue.

Answer all questions with your personal opinion.

At the conclusion, you will have the opportunity to enter into a drawing to win one of two $25 Starbucks gift cards, if you choose.

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Q1.

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Q2.

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Q3.

Q4.

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Q5.

Q6.

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Q7.

Q8.

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Q9.

Q10.

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Q11.

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Q12.

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