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Do Cities Substitute for Internal Firm Resources? A Study of Advanced Internet Technology Adoption

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Title: Do Cities Substitute for Internal Firm Resources? A Study of Advanced Internet Technology Adoption Author: cforman Last modified by: Cide Created Date – PowerPoint PPT presentation

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Title: Do Cities Substitute for Internal Firm Resources? A Study of Advanced Internet Technology Adoption


1
Do Cities Substitute for Internal Firm Resources?
A Study of Advanced Internet Technology Adoption
  • Chris Forman
  • Avi Goldfarb
  • Shane Greenstein

2
Location, Firm Resources, and Internet Investment
  • Location
  • Are the costs of Internet investment lower in
    large cities?
  • Firm Resources
  • How do resources available through internal
    channels shape adoption of frontier IT?
  • Substitution between cities and internal firm
    resources
  • How do internal and external channels substitute
    for one another in reducing the costs of adopting
    frontier IT?

3
Broad Overview
  • Examine how internal and external channels shape
    the adoption of new IT
  • Examine how external channels shape Internet
    adoption
  • Examine how local establishment capabilities and
    mobile firm capabilities shape adoption
  • Measure the extent of substitution between
  • External and internal channels
  • Local and mobile firm channels

4
Why care?
  • Contributes to understanding the factors that
    nurture technological development and their
    mobility
  • Further builds on our research program to alter
    the conversation about the Digital Divide
  • How does the affect of location on Internet use
    vary across economic units?

5
Bottom line
  • External resources found in cities play a
    significant role in decreasing the adaptation
    costs of complex Internet technology
  • Internal channels also play a role
  • This is true for both establishment capabilities
    and mobile firm capabilities
  • Internal and external channels substitute for one
    another in lowering the costs of adopting
    frontier Internet
  • Moreover, establishment capabilities and firm
    capabilities are substitutes

6
Implications
  • Large companies in major cities are the biggest
    adopters of all. Single establishment companies
    in isolated locations do worst of all.
  • If these types of investments matter for
    competitive survival, then the single
    establishments in isolated locations are at a
    disadvantage
  • Establishments from major companies in isolated
    locations do better than those not from major
    companies, but not as well as single-establishment
    companies located in cities
  • A major company can be in an isolated location
    and draw on resources from its other locations,
    but that will mostly, not fully, makes up for
    poor locations
  • Large single establishment companies in isolated
    locations do better than small single-establishmen
    t companies in large locations
  • Organizational capabilities are only partially
    mobile

7
How Internal and External Channels Influence
Diffusion
Other projects at Establishment 1
Shared human capital Shared physical
capital Economies of Scale and Scope Learning
economies Knowledge Spillovers
IT Project at Establishment 1
Shared human capital Shared physical
capital Economies of Scale and Scope Learning
economies Knowledge Spillovers
Physical infrastructure Labor pooling Consultant
availability Knowledge Spillovers
Local Supply Conditions for IT Projects
IT Projects at Establishment 2
8
Location and Internet Adoption
  • We examine adoption of Internet technologies that
    involve within-firm communication and where
    benefits of adopting do not depend on location
  • We label these technologies within-establishment
    Internet (WEI)
  • As a result, we expect urban leadership to hold
    adoption costs decrease as population size and
    density increase
  • Our results are robust to other measures of
    Internet investment

9
Hypotheses Internal Capabilities and Adoption
  • H1A Firms with greater organizational
    capabilities will be more likely to adopt
    Internet technology at any of their
    establishments
  • H2A Establishments with greater establishment
    capabilities will be more likely to adopt
    Internet technology

10
Hypotheses Interactions
  • H1B The sensitivity of Internet adoption to
    increases in location size will be declining in
    the internal organizational capabilities found in
    other establishments within the same firm.
  • H2B The sensitivity of Internet adoption to
    increases in location size will be declining in
    the internal establishment capabilities.
  • H3 Establishment Capability and Organizational
    Capability are substitutes

11
Understanding the hypotheses
12
Data
  • Survey of 86,879 business establishments in the
    US with 100 employees in 3Q-4Q,2000
  • Only private, non-farm
  • Approx half of all such establishments in US
  • Two-thirds of US labor force work in such
    establishments
  • Detailed information about IT capabilities.

13
Data
  • Endogenous Variables
  • Within-Establishment Internet
  • Involves Internet protocols in the input and
    output of data to and from business applications
    software. E.g. ERP, CRM.
  • Robustness
  • CEI adoption, Internet language use, PC server
    adoption
  • Exogenous Variables
  • Capabilities
  • Programmers
  • Factor analysis of programmers, employees,
    software
  • City dummy (MSA population gt500,000)
  • Controls for industry (NAICS dummies),
    multi-establishment firm, establishment employment

14
Econometric Methodology
  • Probit model of Internet adoption
  • At the level of the establishment
  • Interpret as Net benefit to an establishment of
    Internet adoption
  • Weight by 1999 County Business Patterns
  • Generally already representative of
    industry/location of US business establishments,
    so weighting not too important to the results.

15
Econometric Assumptions
  • Location is predetermined (exogenous to
    technology adoption)
  • Decisions are made at the establishment level.
  • Capabilities are exogenous to the adoption
    decision.
  • Robustness checks examine these assumptions

16
Main Results
  • Present results using number of programmers,
    results using composite measure of capabilities
    are qualitatively similar
  • Direct Effects all results are statistically and
    economically significant (average adoption rate
    11.9)
  • Establishments located in cities are 1.3 more
    likely to adopt (urban leadership)
  • One SD increase in log of establishment
    programmers increases likelihood of adoption by
    3.6
  • One SD increase in log of organization
    programmers increases likelihood of adoption by
    0.45

17
Main Results
  • Interaction Effects All results are
    statistically and economically significant
  • One SD increase in log of establishment
    programmers decreases the likelihood of adoption
    by 1.1 for establishments located in cities
  • One SD increase in log of organization
    programmers decreases the likelihood of adoption
    by 0.9 for establishments located in cities
  • While establishment programmers have a much
    stronger direct effect on adoption, substitution
    between cities and internal capabilities is
    similar at establishment and organization level

18
Table 2 Main Results
Direct Effect Only Direct Effect Only Direct Effect and Interaction Effect Direct Effect and Interaction Effect
Capability Defined by Programmers Capability Defined by Factors Capability Defined by Programmers Capability Defined by Factors
OC 0.0021 0.0062 0.0054 0.0118
EC 0.0361 0.0303 0.0457 0.0550
OC City -0.0038 -0.0069
EC City -0.0108 -0.0266
City 0.0129 0.0180 0.0256 0.0188
Multiestablishment Firm Dummy 0.0154 0.0217 0.0149 0.0213
Log(Establishment Employment) 0.0313 0.0309

Observations 86871 86871 86871 86871
LL -24550.40 -25914.41 -24528.56 -25861.03
19
Table 3 Predictions Using Organizational
Capabilities
Low Organization Capability Medium Organization Capability High Organization Capability
Low density location 13.44 15.00 17.23
High density location 18.44 18.97 19.69
20
Table 3 Predictions Using Establishment
Capabilities
Low Establishment Capability Medium Establishment Capability High Establish Capability
Low density location 13.44 17.55 27.87
High density location 18.44 22.17 30.76
21
Substitution between establishment and
organization capabilities
  • There is significant substitution between
    establishment and organization capabilities
  • No matter how we measure them, the interaction of
    establishment and organization capabilities is
    negative and significant
  • A one SD increase in the log of organization
    programmers will decrease the marginal effect of
    establishment capabilities by 0.42

22
Table 5 Are Establishment Capabilities and
Organizational Capabilities Substitutes?
Capability Defined by Programmers Capability Defined by Programmers Capability Defined by Factors Capability Defined by Factors
OC 0.0069 0.0089 0.0111 0.0144
EC 0.0446 0.0527 0.0335 0.0566
OCEC -0.0033 -0.0036 -0.0066 -0.0084
OCCity -0.0026 -0.0042
ECCity -0.0098 -0.0251
OCECCity 0.0005 0.0023
City 0.0174 0.0184 0.0091 0.0198
Multiestablishment Firm Dummy 0.0197 0.0194 0.0096 0.0095
Log(Establishment Employment) 0.0351 0.0347

Observations 86871 86871 86872 86872
LL -25823.42 -25778.86 -25199.06 -25185.64
23
Robustness
  • Results are not isolated in any particular
    industry
  • Results are robust to
  • Instruments for EC, OC, ECCity, and OCCity
  • Subset of establishments that explicitly claim in
    the survey that they conduct the adoption
    decision
  • Different city definitions
  • Different adoption measures
  • Controls for competition

24
Conclusions
  • External resources found in cities decrease the
    costs of technology adoption
  • Internal resources decrease the costs of
    technology adoption. IT capabilities are mobile
    within firms.
  • These resources substitute for each other
  • Therefore, complementary resources found in
    cities will be most important for
    single-establishment firms that do not have such
    internal resources
  • Implication is that geographic digital divide in
    business Internet use, where it exists, will be
    most apparent in small firms
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