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-establishment companies in large locations  Organizational capabilities are only partially mobile

7. Local Supply Conditions for IT Projects IT Projects at Establishment 2 Other projects at Establishment 1 IT Project at Establishment 1 Physical infrastructure Labor pooling Consultant availability Knowledge Spillovers Shared human capital Shared physical capital Economies of Scale and Scope Learning economies Knowledge Spillovers Shared human capital Shared physical capital Economies of Scale and Scope Learning economies Knowledge Spillovers How Internal and External Channels Influence Diffusion

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 >500,000)  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 OnlyDirect Effect and Interaction Effect Capability Defined by Programmers Capability Defined by Factors Capability Defined by Programmers Capability Defined by Factors OC0.0021**0.0062 **0.0054 **0.0118 ** EC0.0361**0.0303 **0.0457 **0.0550 ** OC * City-0.0038 **-0.0069 * EC* City-0.0108 **-0.0266 ** City0.0129 **0.0180 **0.0256 **0.0188 ** Multiestablishment Firm Dummy 0.0154 **0.0217 **0.0149 **0.0213 ** Log(Establishment Employment) 0.0313 **0.0309 ** Observations86871 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 Factors OC0.0069**0.0089**0.0111**0.0144** EC0.0446**0.0527**0.0335**0.0566** OC*EC-0.0033**-0.0036**-0.0066**-0.0084** OC*City-0.0026*-0.0042 EC*City-0.0098**-0.0251** OC*EC*City0.00050.0023 City0.0174**0.0184**0.0091**0.0198** Multiestablishment Firm Dummy0.0197**0.0194**0.0096**0.0095** Log(Establishment Employment)0.0351**0.0347** Observations86871 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, EC*City, and OC*City  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