1 / 12

E-shopping and its relationship with in-store shopping empirically investigated

E-shopping and its relationship with in-store shopping empirically investigated. ICT Specialist Meeting Doorn, The Netherlands 4-7 November Sendy Farag, Tim Schwanen & Martin Dijst Utrecht University. Presentation outline. 1 Introduction 2 Methodology 3 Results

wayne
Download Presentation

E-shopping and its relationship with in-store shopping empirically investigated

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. E-shopping and its relationship with in-store shopping empirically investigated ICT Specialist Meeting Doorn, The Netherlands 4-7 November Sendy Farag, Tim Schwanen & Martin Dijst Utrecht University

  2. Presentation outline 1 Introduction 2 Methodology 3 Results 4 Preliminary conclusions

  3. 1 Introduction • Research question How do the frequencies of online searching and online buying relate to the frequency of non-daily shopping trips? • Accounting for these variables: • Behavioural (Internet use, home shopping) • Attitudinal (e-shopping, in-store shopping) • Land use (residential environment, shop accessibility) • Personality (active lifestyle, adventurous) • Sociodemographic (gender, age, education, income)

  4. 2 Methodology (1) • Data collection period: November + December 2003 • Research areas: Utrecht, Nieuwegein, Culemborg, and Lopik • Research instruments: 1. Shopping survey 2. Two-day travel diary (Friday & Saturday)

  5. 2 Methodology (2) Step 1: selection survey per mail 8,000 households  1946 (24% of households) Willing to participate  1566 (80% of households) Internet users  1210 (77% of willing to participate) Step 2: main survey per mail or online 1210 Internet users  827 (68% of Internet users) 656 mail survey  464 (71% of mail respondents) 554 online survey  363 (65% of online respondents)

  6. 2 Methodology (3) • Method of analysis Structural Equation Modeling = combination of path analysis and factor analysis • Stepwise approach model building Step 1: Online searching, online buying, shopping trips Step 2: Behavioural & attitudinal variables Step 3: Land use variables Step 4: Personality & sociodemographic variables

  7. 3 Results (1) • Sample description • 61% female, mean age 41 years, 28% single • 57% high education, 28% high income • 2.3 non-daily shopping trips per month • Internet use and e-shopping • 5 years Internet experience, 57% daily use • 58% ever bought online, average 4.6 times • only 14% neither search, nor buy online

  8. - - - + + + + + + + + + + + + + - + 3 Results (2) Urban environment Shop accessibility Trip chaining Internet connection Internet use Like e-shopping Home shopping Car Online searching Online buying Shopping trips Adventurous Like in-store shopping

  9. 4 Preliminary conclusions • Frequencies of online searching and buying positively related to the frequency of non-daily shopping trips • Residential environment indirectly affects e-shopping via Internet use and Internet connection • Complementarity or expansion more likely than substitution

  10. Whether online or in-store……

More Related