Town centre retailing: forces impacting the vitality & viability

Dr Les Dolega e-mail: [email protected]

Content

 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

Forces shaping town centre performance

 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

Impact of retail planning policies

    ‘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

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’ Source: Griffith and Harmgart, 2008

Progressive rise of online sales

    Online sales reached 12% of total sales in the UK Amazon - 8 th biggest retailer in the UK Major retailers transformed into ‘bricks & clicks’ Impact on traditional high streets

Response of UK town centres to the economic crisis and austerity

Cross-regional analysis

 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 study – descriptive results

40% 30% 20% 10% 0% -10% 28,2%

Relative change in retail categories

North South Avg across sample pp 4 3 2 1 0 -1 -2 -3 -4 Vacant Retail 4,3% 0,4% -5,3% -1,1% Comparison Convenience Retail Service -3,2% Financial & Business Services

Absolute change in retail categories

Leisure Services 2,7 0,6 Vacant Retail -0,2 -0,1 -2,5 Comparison Convenience Retail Service -0,5 Financial & Business Services Leisure Services

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 – change in comparison retail

30% 20% 10% 0% -10% -20% -30% -40% -8,6% -9,4% -7,8% 6,9% North 0,6% South -3,4% -4,3% Avg across sample 8,0% -9,9% -9,2% -12,1% -1,1% 15,9% -26,5% -29,5%

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 resilient

 Phones & accessories +15.9%  Household discounters +8.0%

As a result of filling vacant space:

 Charity shops +6.9%

Cross-regional study – change in convenience retail

75% 60% 45% 30% 15% 0% -15% -30% -0,3% -8,2% 25,2% 21,4% North 42,2% South -3,8% 5,6% Avg across sample -3,7% -7,9% -7,1%

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

Response Variable



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

Explanatory variables

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’)

Best supported model

Explanatory Variable

Constant South-North divide Centre size (Log) Retail diversity pre-crisis Corporate food store entry Retail vs services % pre-crisis Structural vacancy pre-crisis Std Avg Store Size x Std magnet store floorspace ** parameter estimate significant at 1%, * significant at 5%.

Parameter estimate

-0.076

-0.016

0.013

-0.027

0.095

0.060

-0.349

R squared = 35.6% N = 259 P-value for normality test of residuals =0.84

Durbin-Watson d value = 2.17 Condition index value = 28.61

--------------------------------------------------------

Standard Error T-value

0.019 0.004 0.002 0.013 -2.139

* 0.004 * 0.021

4.463

** 0.010

0.082

-3.998

**

-4.170

** 5.743

** 6.130

** -4.243

**

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

Impact of the cross-regional study

 Published in E&PA (Oct 2011)  Attracted large interest in the UK and internationally  Nominated for the AESOP best published paper prize

Intra-urban study: Bristol

Intra-urban study design



Main aims

 Validate cross-regional results at local scale  Model the performance of UK retail centres during austerity  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)

Characteristics of Bristol centres

   

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%

Modelling of VRC between pre-crisis and within-crisis

Explanatory Variable

Best supported model

Constant Retail vs services % pre-crisis Centre size (Ln) Retail diversity pre-crisis Structural vacancy pre-crisis Corporate supermarket presence Income deprivation R squared = 48.4% N = 47

Parameter estimate

-0.099

0.168

0.020

-0.110

0.098

-0.039

0.101

Standard Error

0.047

0.069

0.008

0.033

0.028

0.017

0.057

T-value

-2.124

2.428

2.415

-3.321

3.506

-2.258

1.755



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

Model of VRC between pre-crisis and austerity



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

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’

Three concepts of resilience (Martin, 2011)



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

Adaptive resilience of town centres



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 

Town centre adaptive



resilience linked to:

pre-crisis position in adaptive   cycles knowledge and innovation of various actors successful interventions across multiple scales

Growth

 INNOVATION & CREATIVITY HIGH 

NEW RETAIL UNITS OPEN UP



HIGH RETAIL CHURN

RESILIENCE HIGH

Consolidation



PERIOD OF STABILITY



LOW RETAIL CHURN



SLOW RESPONSIVENESS TO CHANGE



INCREASING RIGIDITY

RESILIENCE DECLINING

The Adaptive Cycle

RESILIENCE INCREASING

Reorientation



EMERGENCE OF INNOVATION

 

NEW INTERDEPENDENCIES AND SYMBIOTIC RELATIONSHIPS INSTITUTIONAL SUPPORT

RESILIENCE LOW

Release

 

INCREASING VACANCY RATES/ SHOP CLOSURES ECONOMIC OR COMPETITIVE SHOCK TRIGGERS CHANGE

Reconfigured town centres?

Reorientation may be: spontaneous or controlled Four main drivers:

 Supportive institutional structures  Knowledge of actors  Innovation and creativity  Changes in consumer culture

Emerging versions of reconfigured high streets:

 High growth Britain  Low growth Britain  Emergence of new interdependencies

E-resilience of town centres

 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    

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

2013 2014 2015 2016

15-24 25-34 35-44 45-54

3.5% 4.1% 1.5% 4.3% 3.8% 3.5% 1.0% 3.8% 3.5% 2.8% 0.8% 3.1% 3.0% 2.1% 0.5% 2.4% Aims of the study:

55+ 6.5% 5.5% 5.0% 4.0%

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)

Changing face of internet use and online shopping

 Emergence of a new demographic group – the ‘digital generation'  Demographics of internet use  Geography of online shopping  e-commerce, m-commerce

Value added

 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

Any questions?