Izmir_RSA.pdf

Transcript

1. E-Resilience of UK town centres Dr L.Dolega & Dr A. Singleton Email: L.Dolega@liv.ac.uk www.cdrc.ac.uk
2. Content  Forces impacting town centre performance  The e-resilience project  Research methods  Outputs / next steps
3. Forces impacting town centre performance
4. Competition from out-of-centre large retail developments  ‘Free for all’ approach  ‘Town centre first’ policies  Adaptive response of major retailers
5. Shock of the economic crisis  Impact on town centres structure  Increase in vacant outlets  Comparison retail impacted most  Leisure services most resilient  Factors enhancing resilience of town centres  North-south divide  Centre size  High proportion of services  Retail diversity  Corporate foodstore entry/presence
6. Changing demographics and consumer culture  Ageing society  Decreasing household size  Increased demand for ‘value for money’  Progressive rise of convenience culture  Impact of convenience culture on UK high streets  Rapid growth of convenience stores (all types of retailers)  Potential adverse impact on small specialist retailers
7. Rapid growth of online sales  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 the traditional high street  substitution  complementarity  modification
8. Geo-demographics and online shopping  Demographics of internet use  e-commerce, m-commerce  Geography of online shopping  Role of geo-demographics in predicting town centres performance and internet shopping patterns
9. The e-resilience project  Initial stage of the project  E-resilience linked to an extent to which retail centres are exposed to consumers who heavily engage with ICT  Aims and objectives:  Catchment areas estimation for evolved retail centres  Defining characteristics of e-resilient catchments  Measures of the engagement with ICT at small area level
10. Research methodology  Defining retail centres and delineating their primary/secondary catchment areas  Estimating consumers engagement with information and communication technologies at small area level  Creating a framework for measuring e-resilience  Conducting sensitivity analyses on retail centre catchments and their e-resilience
11. Estimating conventional catchment areas  Catchment area estimation techniques  Simple methods – buffers, drive distance/time  Spatial interaction approach – gravity and probabilistic models  Major components and calibration of the model  Distance  Study area  Town centre attractiveness  Catchment models for regional/national scale
12. Evolved town centre approaches  Boundary free modelling  Impact of internet sales on catchment areas  Role of social media and transactional data
13. Framework for measuring e-resilience  Connectivity (broadband availability, 3G/4G signal strength, hotspots locations)  Behaviour (whether or not use internet for shopping)  Demographics (ethnicity, age, gender, disability)  Contextual (retail supply offer, town centre attractiveness & accessibility) Four key dimensions responsible for spatial variability in e-resilience:
14. Next steps  Developing town centre attractiveness index  Defining catchment areas at national scale  Validating models with customers’ insight data  Examination of demographics for all catchment areas at small area geography (LSOA)  Bespoke nationwide e-resilience classification  Characteristics of the ‘e-resilient catchment’
15. Questions please