Conference in Montreal, July 2015

Transcript

1. E-Resilience of UK retail centres Dr L.Dolega & Dr A. Singleton Email: L.Dolega@liv.ac.uk www.cdrc.ac.uk
2. Content  Background  Research question  The concept of e-resilience  Methodology  Outputs  Value added
3.  Competition from out-of-centre large retail developments  Shock of the economic crisis  Changing demographics and consumer culture  Rapid growth of online sales Evolution of town centres
4.  Impact of online sales on UK retail centres  Geography of online sales little understood  How the structure of traditional high streets is being impacted by consumers' propensity for online shopping?  How can we measure ‘e-resilience’ of retail centres? Research question(s)
5.  Better understanding of the drivers of retail centres performance and future challenges  Of which use of the Internet engagement is widely attributed  Estimation of catchment areas for town centres  Creation of retail centres exposure and vulnerability indices A Business Need
6. E-resilience concept  E-resilience measures the vulnerability of British retail centres to the impacts of growing online sales  Aims and objectives:  Investigating the resistance/adaptation of retail centres to the impact of online sales  Deriving meaningful measures of e-resilience  Creating useful tools for various stakeholders assessing retail centre performance
7. Research methodology  Conceptual framework of e-resilience  Definition of retail centres and delineation their catchment areas  Estimation of consumers' propensity for online shopping at small area level  e-Resilience scores  Sensitivity analyses on retail centre catchments and their e-resilience
8. Conceptual framework of e-resilience  Connectivity - available infrastructure to get online  Behaviour - propensity to use internet for shopping  Demographics (ethnicity, age, gender, disability)  Retail supply - attractiveness, accessibility & convenience
9. Estimating town centre catchments  Catchment area estimation techniques  Simple methods – buffers, drive distance/time  Spatial interaction approach – gravity and probabilistic models  Components of the model  Attractiveness  Competition  Distance/decay parameter  Catchment model for a national scale
10. The Huff probability model
11. Outputs & model calibration
12. Consumers’ propensity for online shopping  Specific geodemographic classification - Internet User Classification (IUC)  Data  Oxford Internet Survey (OXIS)  Internet enabling infrastructures  Socio-demographic indicators from the 2011 census
14. e-Resilience scores  Index of high exposure  propensity for online shopping  Index of retail supply vulnerability  Positive - anchor stores & leisure units  Negative - ‘digitalisation’ retail  E-resilience score - intersection of the above indices
15. Value added  Providing new insights into the debate on impacts of online retailing on traditional ‘brick and mortar’ retailers  Investigating how the resistance to impact of online sales can be measured, and what role local demographics may have in that context  Offering valuable tools for various stakeholders to re-evaluate retail capacity models or improve town centres performance
16. Next steps  Updating retail centres boundaries  Re-evaluation of retail catchments considering variable propensity for online shopping  Evaluation of models using customers’ insight data
17. Questions please