Business Establishment Mobility Behavior Business Establishment Mobility Behavior in Urban Areas: An Application to the City in Urban Areas: An Application to the City

of Hamilton in Ontario, Canadaof Hamilton in Ontario, Canada

ByBy

Hanna Maoh and Pavlos KanaroglouHanna Maoh and Pavlos Kanaroglou

E-mail: E-mail: maohhf@mcmaster.camaohhf@mcmaster.ca

99thth Computers in Urban Planning & Urban Management Computers in Urban Planning & Urban Management (CUPUM) meeting(CUPUM) meeting

University College London, LondonUniversity College London, LondonJune 29June 29thth – July 1 – July 1stst, 2005, 2005

OutlineOutline

IntroductionIntroduction

TheoreticalTheoretical Background Background

Study Area and Firm Micro-DataStudy Area and Firm Micro-Data

Mobility ModelMobility Model

Overview of ResultsOverview of Results

Conclusions and Future Research Conclusions and Future Research

AcknowledgmentsAcknowledgments

IntroductionIntroduction

Sustainable planning of cities via Integrated Land use Sustainable planning of cities via Integrated Land use and Transportation Models and Transportation Models

Adoption of the agent-based approachAdoption of the agent-based approach

Our research is focused on the change in the Our research is focused on the change in the distribution of business establishments in the citydistribution of business establishments in the city

Apply concepts from firm demography to model the Apply concepts from firm demography to model the evolution of business establishment populationevolution of business establishment population

Evolutionary Process of Business Establishment Evolutionary Process of Business Establishment PopulationPopulation

Intra-urban migration

In-migration Formation (Birth)

Establishment population at

time t

Establishment population at

time t + 1

Out-migration Failure (death)

+ +

– –

Mobility Process

Modeling FrameworkModeling FrameworkEstablishment

populationt

Failuresubmodul

e

Establishment population

t+1

Newly formed & in-migrating establishments

t+1

Mobilitysubmodul

e

Locationchoice

submodule

Growthsubmodul

e

Establishment population

t

Survivals

Establishment population

t+1

Newly formed & in-migrating establishments

t+1

Migrants

Assign a business to a site

Size of business

t+1

Firmographic Processes Processes Output

Theoretical BackgroundTheoretical Background

Studies that model firm mobility are rareStudies that model firm mobility are rare Existing studies (Bade, 1984; van Wissen, 2000; Existing studies (Bade, 1984; van Wissen, 2000;

Dijk and Pellenbarg, 2000; Brouwer et al., 2004) Dijk and Pellenbarg, 2000; Brouwer et al., 2004) suggest:suggest:– Firms have a strong preference to remain in situ Firms have a strong preference to remain in situ

and will only move due to location pressure and will only move due to location pressure (deficiencies)(deficiencies)

– Location deficiencies: change in market Location deficiencies: change in market orientation, space requirements, technological orientation, space requirements, technological change, location cost and accessibility problems, change, location cost and accessibility problems, labour mismatch, etc. labour mismatch, etc.

Location theories and factors Location theories and factors influencing business mobility influencing business mobility

Theoretical Theoretical frameworkframework

Key concepts Key concepts (factors)(factors)

VariablesVariables

Neo-classical theory Neo-classical theory Market situation Market situation (Location factors) (Location factors)

-Market size-Market size

-Country of location -Country of location

Behavioural theoryBehavioural theory Information/Abilities Information/Abilities (Internal factors) (Internal factors)

-Firm size-Firm size

-Firm age -Firm age

Institutional theoryInstitutional theory Networks (External Networks (External factors) factors)

-Firm growth-Firm growth

(positive and negative; (positive and negative; merger; acquisition; merger; acquisition; take-over) take-over)

Source: Adapted from Brouwer et al. (2004)

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

CBD

CBD

Firm Micro-Data: Firm Micro-Data: Statistics Canada Statistics Canada Business Register (BR)Business Register (BR)

Maintains annual information about business Maintains annual information about business establishments in Canada since 1990establishments in Canada since 1990

Confidential and can only be used to conduct Confidential and can only be used to conduct statistical analysisstatistical analysis

Attributes: Establishment size, location (postal code Attributes: Establishment size, location (postal code and SGC), SIC code and Establishment Number (EN)and SGC), SIC code and Establishment Number (EN)

BR provides the life trajectory of business BR provides the life trajectory of business establishments over space and timeestablishments over space and time

BR can be used to measure firmographic events such BR can be used to measure firmographic events such as: the formation, migration, location choice, failure, as: the formation, migration, location choice, failure, growth and decline of business establishmentsgrowth and decline of business establishments

Small and Medium (SME) Small and Medium (SME) Size establishmentsSize establishments

SME with less than 200 employees is the target of our analysisSME with less than 200 employees is the target of our analysis

Account for more than 94% of establishments in 1990, 1996 and 2002Account for more than 94% of establishments in 1990, 1996 and 2002

Extracted population was constrained to self-owned single Extracted population was constrained to self-owned single establishmentsestablishments

Establishments that are part of a chain were not included in the model!Establishments that are part of a chain were not included in the model!

However, the extracted sample is deemed appropriateHowever, the extracted sample is deemed appropriate

Around 80% of SME are with less than 10 employees, 93% of which Around 80% of SME are with less than 10 employees, 93% of which are single owned establishmentsare single owned establishments

Mobility TrendsMobility Trends

7% and 2% of 1996 SME establishments relocated and out-migrated by 7% and 2% of 1996 SME establishments relocated and out-migrated by 1997, respectively1997, respectively

12% and 3% of 1996 total establishment population relocated and out-12% and 3% of 1996 total establishment population relocated and out-migrated by 2002, respectivelymigrated by 2002, respectively

Mean employment size of relocating establishments is 15 and mean Mean employment size of relocating establishments is 15 and mean relocating distance is 5 kilometres (1996 – 2002)relocating distance is 5 kilometres (1996 – 2002)

50% of moves happened at short distance within the same municipality50% of moves happened at short distance within the same municipality

91% of out-migrating establishments moved within a radius of 100 91% of out-migrating establishments moved within a radius of 100 kilometres around Hamilton between 1996 and 2002kilometres around Hamilton between 1996 and 2002

57% of out-migrants moved to close by location in the Greater Toronto 57% of out-migrants moved to close by location in the Greater Toronto AreaArea

Establishment Mobility ModelEstablishment Mobility Model

Objective: Determine if an individual Objective: Determine if an individual establishment will choose to establishment will choose to StayStay ( (SS) at its ) at its current location, current location, RelocateRelocate ( (RR) to a different ) to a different place within the city or will place within the city or will LeaveLeave ( (LL) the city ) the city between 1996 and 1997 between 1996 and 1997

We use a MNL model to predict probabilities We use a MNL model to predict probabilities PP((SS), ), PP((RR) and ) and PP((LL))

Mobility is modeled by main economic sectorMobility is modeled by main economic sector

Utility Specification for Utility Specification for establishment establishment i i

Establishment internal factors and location factors are used in the Establishment internal factors and location factors are used in the specification of the specification of the StayStay, , RelocateRelocate and and movemove utilities utilities

Internal factors includedInternal factors included: : SizeSize, , AgeAge, , Growth Growth rate and dummies rate and dummies for type of industry for type of industry industry_d industry_d

Location factors includedLocation factors included: Geography dummies, a measure for : Geography dummies, a measure for agglomeration economies (agglomeration economies (AgglomAgglom), distance between old and ), distance between old and new location (new location (DDodod)) and a measure for location competition and a measure for location competition ((LcompLcomp))

Overview of ResultsOverview of Results

Mobility is more prominent among very small Mobility is more prominent among very small and very large establishmentsand very large establishments as depicted by the as depicted by the SizeSize and and SizeSize2 2 parametersparameters

The The AgeAge parameter suggests that young parameter suggests that young establishments are more likely to relocate or out-establishments are more likely to relocate or out-migratemigrate

The need to grow as suggested by the The need to grow as suggested by the Growth Growth parameter push manufacturing establishments to parameter push manufacturing establishments to relocaterelocate

Overview of ResultsOverview of Results

The The Growth Growth parameter in retail and wholesale parameter in retail and wholesale models appear as a proxy for performance since models appear as a proxy for performance since growing establishments were less mobilegrowing establishments were less mobile

The location dummies suggest decentralization and The location dummies suggest decentralization and suburbanization of establishments in Hamiltonsuburbanization of establishments in Hamilton

Mobility is more pronounced among the Central Mobility is more pronounced among the Central Business District (CBD) establishmentsBusiness District (CBD) establishments

Overview of ResultsOverview of Results

Agglomeration increases the propensity of Agglomeration increases the propensity of inertia. This effect is more prominent among inertia. This effect is more prominent among retail and service industry establishmentsretail and service industry establishments

The increase in local competition (location The increase in local competition (location pressure) will push the establishment to move pressure) will push the establishment to move long distancelong distance

Mobility vary by the type of industry as Mobility vary by the type of industry as discerned from the specified industry dummiesdiscerned from the specified industry dummies

Conclusions and Future Conclusions and Future ResearchResearch

Mobility is not common place in the urban contextMobility is not common place in the urban context Firm internal factors and location factors are important Firm internal factors and location factors are important

determinants of mobilitydeterminants of mobility The research emphasizes the value in using data from The research emphasizes the value in using data from

Statistics Canada Business Register to study firmography Statistics Canada Business Register to study firmography in the urban contextin the urban context

More work need to be done to investigate the role of More work need to be done to investigate the role of organizational structure on mobilityorganizational structure on mobility

Future research is still needed to thoroughly scrutinize the Future research is still needed to thoroughly scrutinize the relation between public policy and establishment mobility relation between public policy and establishment mobility behavior in the urban context; Therefore, enhancing the behavior in the urban context; Therefore, enhancing the attributes of existing firm micro data is requiredattributes of existing firm micro data is required

AcknowledgmentsAcknowledgments

We would like to thank Statistics Canada for We would like to thank Statistics Canada for supporting this research through their (2003 supporting this research through their (2003 – 2004) – 2004) Statistics Canada PhD Research Statistics Canada PhD Research Stipend Stipend program. program.

We are grateful to SSHRC for financial We are grateful to SSHRC for financial support through a Standard Research Grant support through a Standard Research Grant and a SSHRC doctoral fellowship and a SSHRC doctoral fellowship