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Conference in Montreal, July 2015

Les.Dolega
August 25, 2015

Conference in Montreal, July 2015

Les.Dolega

August 25, 2015
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  1. Content  Background  Research question  The concept of

    e-resilience  Methodology  Outputs  Value added
  2.  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
  3.  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)
  4.  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
  5. 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
  6. 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
  7. 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
  8. 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
  9. 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
  10. 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
  11. 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
  12. Next steps  Updating retail centres boundaries  Re-evaluation of

    retail catchments considering variable propensity for online shopping  Evaluation of models using customers’ insight data