By Hanna Maoh and Pavlos Kanaroglou E-mail: maohhf@mcmaster

1. 9th Computers in Urban Planning & Urban Management (CUPUM) meeting University College London, London June 29th – July 1st, 2005 Business Establishment Mobility Behavior in Urban Areas: An Application to the City of Hamilton in Ontario, Canada By Hanna Maoh and Pavlos Kanaroglou E-mail: maohhf@mcmaster.ca

2. Outline • Introduction • Theoretical Background • Study Area and Firm Micro-Data • Mobility Model • Overview of Results • Conclusions and Future Research • Acknowledgments

3. Introduction • Sustainable planning of cities via Integrated Land use and Transportation Models • Adoption of the agent-based approach • Our research is focused on the change in the distribution of business establishments in the city • Apply concepts from firm demography to model the evolution of business establishment population

4. Intra-urban migration In-migration Formation (Birth) + + Establishment population at time t Establishment population at time t + 1 – – Out-migration Failure (death) Mobility Process Evolutionary Process of Business Establishment Population

5. Modeling Framework Establishment population t Establishment population t Failure submodule Survivals Firmographic Processes Processes Output Newly formed & in-migrating establishments t+1 Newly formed & in-migrating establishments t+1 Mobility submodule Migrants Location choice submodule Assign a business to a site Growth submodule Size of business t+1 Establishment population t+1 Establishment population t+1

6. Theoretical Background • Studies that model firm mobility are rare • Existing studies (Bade, 1984; van Wissen, 2000; Dijk and Pellenbarg, 2000; Brouwer et al., 2004) suggest: • Firms have a strong preference to remain in situ and will only move due to location pressure (deficiencies) • Location deficiencies: change in market orientation, space requirements, technological change, location cost and accessibility problems, labour mismatch, etc.

7. Location theories and factors influencing business mobility Source: Adapted from Brouwer et al. (2004)

8. Around 500,000 people in 2001 Around 12,000 business establishments and 230,000 jobs in 2002

9. CBD

10. CBD

11. Firm Micro-Data: Statistics Canada Business Register (BR) • Maintains annual information about business establishments in Canada since 1990 • Confidential and can only be used to conduct statistical analysis • Attributes: Establishment size, location (postal code and SGC), SIC code and Establishment Number (EN) • BR provides the life trajectory of business establishments over space and time • BR can be used to measure firmographic events such as: the formation, migration, location choice, failure, growth and decline of business establishments

12. Small and Medium (SME) Size establishments • SME with less than 200 employees is the target of our analysis • Account for more than 94% of establishments in 1990, 1996 and 2002 • Extracted population was constrained to self-owned single establishments • Establishments that are part of a chain were not included in the model! • However, the extracted sample is deemed appropriate • Around 80% of SME are with less than 10 employees, 93% of which are single owned establishments

13. Mobility Trends • 7% and 2% of 1996 SME establishments relocated and out-migrated by 1997, respectively • 12% and 3% of 1996 total establishment population relocated and out-migrated by 2002, respectively • Mean employment size of relocating establishments is 15 and mean relocating distance is 5 kilometres (1996 – 2002) • 50% of moves happened at short distance within the same municipality • 91% of out-migrating establishments moved within a radius of 100 kilometres around Hamilton between 1996 and 2002 • 57% of out-migrants moved to close by location in the Greater Toronto Area

14. Establishment Mobility Model • Objective: Determine if an individual establishment will choose to Stay (S) at its current location, Relocate (R) to a different place within the city or will Leave (L) the city between 1996 and 1997 • We use a MNL model to predict probabilities P(S), P(R) and P(L) • Mobility is modeled by main economic sector

15. Utility Specification for establishment i • Establishment internal factors and location factors are used in the specification of the Stay, Relocate and move utilities • Internal factors included: Size, Age, Growth rate and dummies for type of industry industry_d • Location factors included: Geography dummies, a measure for agglomeration economies (Agglom), distance between old and new location (Dod)and a measure for location competition (Lcomp)

16. Overview of Results • Mobility is more prominent among very small and very large establishments as depicted by the Size and Size2 parameters • The Age parameter suggests that young establishments are more likely to relocate or out-migrate • The need to grow as suggested by the Growth parameter push manufacturing establishments to relocate

17. Overview of Results • The Growth parameter in retail and wholesale models appear as a proxy for performance since growing establishments were less mobile • The location dummies suggest decentralization and suburbanization of establishments in Hamilton • Mobility is more pronounced among the Central Business District (CBD) establishments

18. Overview of Results • Agglomeration increases the propensity of inertia. This effect is more prominent among retail and service industry establishments • The increase in local competition (location pressure) will push the establishment to move long distance • Mobility vary by the type of industry as discerned from the specified industry dummies

19. Conclusions and Future Research • Mobility is not common place in the urban context • Firm internal factors and location factors are important determinants of mobility • The research emphasizes the value in using data from Statistics Canada Business Register to study firmography in the urban context • More work need to be done to investigate the role of organizational structure on mobility • Future research is still needed to thoroughly scrutinize the relation between public policy and establishment mobility behavior in the urban context; Therefore, enhancing the attributes of existing firm micro data is required

20. Acknowledgments • We would like to thank Statistics Canada for supporting this research through their (2003 – 2004) Statistics Canada PhD Research Stipend program. • We are grateful to SSHRC for financial support through a Standard Research Grant and a SSHRC doctoral fellowship