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Oedzge Atzema & Jesse Weltevreden U rban & R egional research centre U trecht ( URU )

Adoption of b2c e-commerce by city centre retailers: The relevance of place, product and organisation. Oedzge Atzema & Jesse Weltevreden U rban & R egional research centre U trecht ( URU ) ICT: Mobilizing persons, places and spaces, November 4-7 2004, Doorn. Outline Objectives

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Oedzge Atzema & Jesse Weltevreden U rban & R egional research centre U trecht ( URU )

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  1. Adoption of b2c e-commerce by city centre retailers:The relevance of place, product and organisation. Oedzge Atzema & Jesse Weltevreden Urban & Regional research centre Utrecht (URU) ICT: Mobilizing persons, places and spaces, November 4-7 2004, Doorn

  2. Outline Objectives City centres Consumer data Data collection Results Conclusions Outline Presentation • Main objectives • City centres • Consumer data • Data Collection • Results • Conclusions

  3. Outline Objectives City centres Consumer data Data collection Results Conclusions Main Objectives • To investigate the factors that determine the adoption of online shopping by consumers; • To investigate the impact of consumers' online shopping behaviour on their physical shopping behaviour in city centres (this presentation); • To investigate the factors that determine the adoption of b2c e-commerce by city centre retailers (this presentation); • To investigate the effects of retailers’ Internet strategy on their organisation and city centre stores.

  4. Outline Objectives City centres Consumer data Data collection Results Conclusions City centres

  5. Outline Objectives City centres Consumer data (1) Data collection Results Conclusions (1) 10 Most popular products on the Internet and in the city centre (based on respondents’ last 3 purchases)

  6. Outline Objectives City centres Consumer data (2) Data collection Results Conclusions (2) Bought online from whom? (Based on respondents’ last 3 online purchases)

  7. Outline Objectives City centres Consumer data (3) Data collection Results Conclusions (3) Impact of online buying on purchases in various city centre stores (N= 2,010)

  8. Outline Objectives City centres Consumer data Data collection (1) Results Conclusions Data Collection (1) • Examination of the retail composition of 8 city centres (October-November, 2003) (N= 3,369 shops); • Searching for a retailer’s Website via a Search Engine (November, 2003); • Brief Interviews about Web presence and promotion of Website (December-February, 2004) (N= 3,274 shops, Response of 97.2%); • Analysing the Internet strategy of each retailer (March, 2004).

  9. Outline Objectives City centres Consumer data Data collection (2) Results Conclusions Data Collection (2): Operationalisation • Shop level approach; • B2c e-commerce adoption 2 stages: active website & online sales; • Place: 4 types of city centres; and pedestrian vs. non pedestrian areas; • Product: 4 product categories; and 12 main sectors; • Organisation: 6 types.

  10. Table II: Logistic regression of active website and online sales adoption by city centre shops using a product classification Outline Objectives City centres Consumer data Data collection Results (1.1) Conclusions Logistic regression of active website and online sales adoption using a product classification (part 1) * = p < 0.10; ** = p < 0.05; *** = p < 0.01 * = p < 0.10; ** = p <0.05; *** = p <0.01

  11. Outline Objectives City centres Consumer data Data collection Results (1.2) Conclusions Logistic regression of active website and online sales adoption using a product classification (part II) * = p < 0.10; ** = p < 0.05; *** = p < 0.01

  12. Table II: Logistic regression of active website and online sales adoption by city centre shops using a product classification Outline Objectives City centres Consumer data Data collection Results (2.1) Conclusions Logistic regression of active website and online sales adoption using a sector classification (part I) * = p < 0.10; ** = p < 0.05; *** = p < 0.01 * = p < 0.10; ** = p <0.05; *** = p <0.01

  13. Outline Objectives City centres Consumer data Data collection Results (2.2) Conclusions Logistic regression of active website and online sales adoption using a sector classification (part II)

  14. Outline Objectives City centres Consumer data Data collection Results Conclusions Conclusions • Some city centre retailers may already begin to feel the impact of changes in consumers’ shopping habits because of online shopping; • For active website adoption organisation has the most explanatory value; • For online sales sector type is more important; • A high chance having a website need not coincide with a high likelihood of online sales adoption as well; • Retailers not necessarily need to sell the same merchandise online as in their physical outlets; • Location matters for both the adoption of an active website and online selling strategy.

  15. End of Presentation

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