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The (Teaching) Role of Universities in the Diffusion of the Internet

Avi Goldfarb

University of Toronto

June 16, 2005

CIDE, Mexico City

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The Internet and Universities I

• Universities played an important role in the invention of the Internet and its applications. – The browser was invented at the University of Illinois

(Netscape)

– Gopher was created at the University of Minnesota

– Google & Yahoo were created at Stanford

– Akamai was created at MIT

– Broadcom was created at UCLA

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The Internet and Universities II

• Students in the mid 1990s often got their first exposure to the Internet at school.

• Students needed to use the Internet in order to succeed (for research & communication).

• Students then brought their knowledge of the Internet to their homes (and workplaces) after graduation.

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43.8%

83.1%

40.8%

73.2%

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

No post-secondaryeducation

Post-secondaryeducation

No post-secondaryeducation

Post-secondaryeducation

born 1971-79 . Not born 1971-79

Fra

ctio

n w

ho

use

th

e In

tern

et

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Key Points

1. Students in the mid-1990s are more likely to use the Internet than others, controlling for age and education.

2. Those who live with people in this cohort are also more likely to use the Internet

3. These effects do not hold for other computer applications

4. Former students adopt because of higher communications benefits

5. Household members adopt because of lower adoption costs

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How I will proceed:

1. Data

2. Are former students (and those who live with them) more likely to adopt the Internet than others?

3. Why are they more likely to adopt the Internet?

4. Conclusions

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Data

• US Census Current Population Survey Sept. 2001 Computer and Internet Use Supplement– 142,667 individuals in 2001

– Survey asks whether use the Internet and a variety of Internet applications, also includes demographics

– Asks about use of other computing technologies

– Results on all household members

– Former student defined by college attendees in the age cohort that attended school between 1993 and 1997 (i.e. born 1971-79).

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Data

• Nielsen Panel of Canadian Households– 5,519 individuals in 2000, but have information

on occupation going from 1995– Therefore accurately identify student status– Survey asks whether use the Internet and a

variety of Internet applications, also includes demographics

– Weakness is that this is a strange population

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Method

• Are former students (and those who live with them) more likely to adopt than others?– Straightforward probit model of adoption– Difference-in-difference identification– Controlling for observables (including income,

education, occupation, industry, etc), are former students and those who live with them more likely to adopt the Internet?

– Look at other computing applications to see if this is a result of being technology savvy, owning a computer, or something Internet-specific

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Results: Factors Driving Internet UseCENSUS DATA Coefficient Marg. Effect

Former Student 0.0919** 0.0352**

Lives with Former Student 0.133** 0.0506**

Born 1971-79 -0.131** -0.0512**

Age -0.0239** -0.00925**

Postsecondary Graduate 0.582** 0.216**

Current Student 0.841** 0.272**

Also income, race, marital status, gender, citizen, metropolitan, homeowner, employment status, state, occupation, and industry.

NIELSEN DATA

Former Student 0.235* 0.0835*

Also current student, income, age, education, location, gender, etc.**significant at 99% confidence; *significant at 95% confidence

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-0.1

-0.05

0

0.05

0.1

0.15

0.2

0.25

0.3

0.35

0.4

Age

Mar

gin

al E

ffec

t o

f E

du

cati

on

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-0.02

-0.01

0

0.01

0.02

0.03

0.04

0.05

0.06

Postsecondary graduate born 1971-79 Lives with postsecondary graduate born1971-79

Ma

rgin

al E

ffe

ct

Connect to the Internet

Use a computer at work

Do word processing or desktop publishing

Play games on the computer

Use home computer to manage household records or finances

**

**

**

+

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So postsecondary educational institutions likely played a role in influencing Internet adoption.

What kind of role did they play?1. Who benefited?

2. What did universities do?

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Low Income Households and Non-Citizens Benefited Most

ALL Income <$40k

Income >=60k

Non-Citizens

Former Student 0.0352** 0.0602** 0.0135 0.0922*

Lives with

Former Student

0.0506** 0.129** -0.00227 0.0595*

Also current student, age, born 1971-79, education, gender, race, employment status, homeowner, metropolitan, marital status, citizen, income

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– Did they teach that the Internet is a library? • higher skills at accessing online information

– Or a shopping mall? • trust

– Or a communications medium? • network effects, comfort with electronic communication, etc

– Or do they merely reduce the overall barriers to adoption?

• Rogers’ (1995) trialability & complexity; Stoneman’s (2002) risk, uncertainty and learning-by-doing

• The Internet has no value to the user without complementary software applications

• Internet adoption will depend on overall adoption costs and application net benefits

What did Universities Do?

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Nested Adoption Process

– Choose to adopt the Internet, and choose which applications to adopt simultaneously.

Adopt Internet

Adopt E-commerce Adopt E-communication Adopt E-Information

A

aantantaIntInt CostBenefitCostNB

1

0,max

antantant CostBenefitNB XinXan

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Identification

• Simultaneously estimate adoption of the Internet and adoption of applications

• Therefore for each application– Estimate parameters of the relationship between

former student status and adoption, controlling for overall adoption propensity and adoption propensity of other applications.

• Therefore, the methodology allows for student status to have a different effect on the adoption of different applications.

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Identification

• I interpret these different effects as follows:– If former student status affects the adoption of a

particular application, then it is likely that universities played a role in increasing the net benefit of that application.

– If former student status affects the adoption of the Internet in general, then it is likely that universities played a role in decreasing the costs associated with adoption (as the Internet brings no utility without applications)

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Variable Overall E-Commerce E-Information E-Communication

Former student^ -0.00529 -0.000743 -0.0262 0.250**

Former student in HH^ 0.0431** 0.135** 0.119** 0.167**

Student 1.03** 0.222** 0.295** 0.970**

Born 1971-79 -0.336** 0.548** 0.588** 0.476**

Postsec. education 0.715** 0.801** 0.652** 0.715**

Age -0.0230** 0.0158** 0.00792** 0.0250**

HH inc. <US$20K# -0.518** -0.354** -0.246** -0.201**

HH inc. US$20-60K# -0.0155 -0.109** 0.0145 -0.156**

HH inc. >US$60K# 0.364** 0.402** 0.270** 0.303**

Employed## 0.600**

Unemployed## 0.552**

Female -0.316 **

Metropolitan area -0.0801**

US citizen 0.0430+

White 0.227**

E-commerce -5.40**

E-information 592.1**

E-communication 879.0**

Results: Nested Diffusion Regression

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Network Effects

• The results strongly suggest that universities created a network effect. Two results point in this direction:

1. The benefit of university attendance is driven by online communications

2. Students passed the knowledge to those living in the same household.

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Conclusion• The effect of university education on Internet

adoption is particularly strong for the cohort born 1971-79.

• This is not true of other computing technologies• The effect appears to be transferred to other

members of the household• For the former students, this effect is driven by

online communication. For those who live with them, it is driven by a reduction in the cost of adoption.

• Universities appear to have created a network externality.

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Discussion

• In addition to creating knowledge and educating the workforce, universities help new innovations diffuse.

• Microsoft Donations

• Digital divide implications

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Some Unanswered Questions

• Did educational institutions play a key role in diffusing other technologies as well as the Internet? Which technologies?

• How important was the diffusion of the Internet through educational institutions to economic growth in the 1990s?

• What are the most effective ways to diffuse technology through educational institutions?