Town centre retailing: Town centre retailing: forces impacting the vitality & viabilityforces impacting the vitality & viability

Dr Les Dolega e-mail: L.Dolega@liv.ac.uk

Forces shaping UK town centres performance

Response of UK retail centres to the economic crisis and austerity

Cross-regional empirical evidence

Intra-urban (local scale) evidence

Conceptualisation - resilience of British retail centres

Content

Competition from out-of-centre retail developments and adoption of ‘town centres first’ policies

Rapid expansion of online retailing

Economic crisis and austerity

Shifting consumer behaviour and progressive rise of ‘convenience culture’

Changing demographics

Forces shaping town centre performance

‘Free for all’ approach (Guy, 2007)

‘Town centres first’ – regulatory tightening

Prioritisation of UK town centres by PPG 6 Adoption of the ‘sequential test’

Promotion of the vitality & viability of town centres by PPS 6

‘Social inclusion’ and ‘urban regeneration’ agendas

Impact of retail planning policies

Source: Griffith and Harmgart, 2008

Effects of policy tightening on retail developments

Decrease in large retail developments

Adjustment of the major retailers to the planning regime

‘Policy friendly’ stores - located in/edge-of-town centre

Store formats flexibility

Retail-led urban regeneration

‘Food deserts’ and social inequality agendas

‘Mezzanine floor loophole’

Online sales reached 12% of total sales in the UK

Amazon - 8th biggest retailer in the UK

Major retailers transformed into ‘bricks & clicks’

Impact on traditional high streets

Progressive rise of online sales

Response of UK town centres to the economic crisis and

austerity

267 centres with retail composition surveys completed after the collapse of CCI - Oct 2008

119 in South West 31 in East Anglia 93 in North West 24 in West Yorkshire

Pre-crisis surveys completed in 2006 – 2007

Within-crisis surveys carried out either in Q4 2008 or 2009

Cross-regional analysis

Change in retail categories

Large increase in vacant retail:Relative change +28.2%Absolute change +2.7pp (increase from 10.4% to 13.1%)

Major contributors to closures: comparison retail (-5.3%)financial services (-3.2%)

Convenience retail more resilient Leisure services - positive growth

in all regions

Cross-regional study – descriptive results

Most fragile Department stores -29.5% Music, video and photography -26.5% Florists -12.1% Furniture shops -9.9% Booksellers -9.2% Gift and Toys -9.2%

Most resilientPhones & accessories +15.9%Household discounters +8.0%

As a result of filling vacant space:Charity shops +6.9%

Cross-regional study – change in comparison retail

Cross-regional study – change in convenience retail

Most fragile

Butchers & Fishmongers -8.2%

Greengrocers -7.9%

CTN & Off licences -7.1%

Most resilient

Convenience Stores: Multiple +42.2% Independent +25.2% Symbol Group +21.4% Grocers & delicatessen +5.6%

Modelling cross-regional change

in vacancy rate

Change in retail vacancy rates – response variable

Spatial variability in vacancy rate: up in 185 (69.3%) centres down in 61 (22.8%) centres unchanged in 21 (7.9%) centres

The average cross-regional increase in vacancy rate: +2.2pp for fixed boundaries +1.9pp for variable boundaries

Response Variable

Changes in Vacancy Rates have been filtered through two systems:

1. Regional economic system in which centres are located North–South divide Affluent catchments

2. Existing local economic structures

The mix and interdependencies of businesses (balance of retail vs. services, diversity and presence/entry of a corporate foodstores)

Local supportive/unsupportive institutional structures (car park charges, town centre manager, BIDs schemes or attracting key ‘magnet stores’)

Physical configuration of a centre (size, proportion of larger modern shops and level of ‘structural – harmful vacancy’)

Explanatory variables

Explanatory Variable Explanatory Variable Parameter Parameter estimate estimate

Standard Standard ErrorError

T-valueT-value

Constant

-0.076 0.019 -3.998**

South-North divide

-0.016 0.004 -4.170**

Centre size (Log)

0.013 0.002 5.743**

Retail diversity pre-crisis

-0.027 0.013 -2.139*

Corporate food store entry -0.008

0.004

-2.081*

Retail vs services % pre-crisis

0.095 0.021 4.463**

Structural vacancy pre-crisis 0.060 0.010 6.130**

Std Avg Store Size x Std magnet store floorspace

-0.349 0.082 -4.243**

Best supported model

**parameter estimate significant at 1%, * significant at 5%. R squared = 35.6% N = 259P-value for normality test of residuals =0.84Durbin-Watson d value = 2.17 Condition index value = 28.61

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Characteristics of resilient town centres

‘southern’ rather than ‘northern’ ‘smaller’ rather than ‘larger’ ‘diverse’ measured by higher proportions of independent stores experienced corporate foodstore entry (in/edge-of-centre) higher proportions of service relative to retail units in pre-crisis low levels of ‘structural vacancy’ in the pre-crisis period

physical structures are both relatively attractive and capable of re-configuration – proxied by the multiplicative variable

Published in E&PA (Oct 2011)

Attracted large interest in the UK and internationally

Nominated for the AESOP best published paper prize

Impact of the cross-regional study

Intra-urban study: Bristol

Intra-urban study design

47 retail centres in Bristol surveyed by Goad down to a shopping parade with 12 units

All centres surveyed in three different periods:

Pre-crisis (Jul 2006) Within-crisis (Oct 2008-Feb 2009) Austerity period (Feb-Mar 2012)

Main aimsValidate cross-regional results at local scaleModel the performance of UK retail centres during austerity

Main characteristics of

Bristol centres in pre-crisis 75% centres small - average

centre size 88 units High ratio of services (1.7)

relative to retail High diversity - independent

retailers 73%

Characteristics of Bristol centres

Cross-regional findings hold well at local scale

Four of seven explanatory variables retained the same, however: No North-South divide Corporate foodstore entry replaced with presence Income deprivation – significant variable Multiplicative variable insignificant

Explanatory Variable Explanatory Variable Parameter Parameter estimate estimate

Standard Standard ErrorError

T-valueT-value

Constant

-0.099 0.047 -2.124

Retail vs services % pre-crisis 0.168 0.069 2.428 Centre size (Ln)

0.020 0.008 2.415

Retail diversity pre-crisis -0.110 0.033 -3.321 Structural vacancy pre-crisis 0.098 0.028 3.506Corporate supermarket presence -0.039 0.017 -2.258Income deprivation 0.101 0.057 1.755R squared = 48.4% N = 47

Best supported model

Modelling of VRC between pre-crisis and within-crisis

Only three variables remained significant:

Proportion of retail vs. services

Diversity in pre-crisis

Presence of policy-compliant corporate foodstore

Significance of centre size, structural vacancy and income deprivation waned

Model of VRC between pre-crisis and austerity

Conceptualising our work

Intriguing question in economic geography – ‘why some regional economies manage to renew themselves,

whereas others remain locked in decline’? (Hassink, 2010)

Resilience of economic systems recently attracted wide-spread attention of social sciences

Resilience is defined as:‘the ability to recover form and position elastically following a

disturbance of some form’

Engineering resilience (physical science) – the resistance of a system to disturbances and the speed of return (bounce back) to its pre-shock state

Ecological resilience (biological science) - the scale of shock a system can absorb before it is destabilised and moved to another configuration (tipping point notion).

Adaptive resilience (complex system theory) – anticipatory or reactive reorganisation of the form and/or function of a system to minimise the impact of the external/internal shock

Three concepts of resilience (Martin, 2011)

Evolution of UK town centres affected by:

Unexpected shocks – economic crisis

‘Slow burns’ – competition from online and out-of-town retailers, changes in consumer culture

Adaptive resilience of town centres

Town centre adaptive resilience linked to:

pre-crisis position in adaptive cycles

knowledge and innovation of various actors

successful interventions across multiple scales

TheAdaptive

Cycle

Growth  

INNOVATION & CREATIVITY HIGHNEW RETAIL UNITS OPEN UPHIGH RETAIL CHURN

RESILIENCE HIGH

Consolidation 

PERIOD OF STABILITY LOW RETAIL CHURN SLOW RESPONSIVENESS TO CHANGEINCREASING RIGIDITY

RESILIENCE DECLINING 

RESILIENCE LOW

Release

INCREASING VACANCY RATES/ SHOP CLOSURESECONOMIC OR COMPETITIVE SHOCK TRIGGERS CHANGE

RESILIENCE INCREASING

Reorientation

EMERGENCE OF INNOVATIONNEW INTERDEPENDENCIES AND SYMBIOTIC RELATIONSHIPSINSTITUTIONAL SUPPORT 

Reconfigured town centres?

Reorientation may be: spontaneous or controlled

Four main drivers:Supportive institutional structuresKnowledge of actorsInnovation and creativityChanges in consumer culture

Emerging versions of reconfigured high streets:High growth BritainLow growth BritainEmergence of new interdependencies

Role of geo-demographics in predicting town centres performance and internet shopping patterns

E-resilience linked to an extent to which retail centres are exposed to consumers who heavily engage with ICT

Aims of the study: Estimation of conventional catchment areas for evolved retail centres Defining characteristics of e-resilient centres Measures of the engagement with ICT at small area level (LSOA)

E-resilience of town centres

Growth in UK Online Buyers, by Age 2013-2016 (% change)

2013 2014 2015 2016

15-24 3.5% 3.8% 3.5% 3.0%

25-34 4.1% 3.5% 2.8% 2.1%

35-44 1.5% 1.0% 0.8% 0.5%

45-54 4.3% 3.8% 3.1% 2.4%

55+ 6.5% 5.5% 5.0% 4.0%

Emergence of a new demographic group – the ‘digital generation'

Demographics of internet use Geography of online shopping e-commerce, m-commerce

Changing face of internet use and online shopping

Systematic evidence on cross-regional and intra-urban high street performance during economic crisis and austerity provided

First multiplicative modelling of drivers of that performance

Evidence on both diversity and corporate food store entry benefiting

the economic health of retail centres, despite being portrayed as

polar opposites

Conceptualisation of adaptive resilience of UK high streets

Exploring the relationship between the geo-demographics and e-resilience of town centres

Value added

Any questions?