Skip to main content

A Characterization of Non-buyers in B2C E-Commerce and the Drivers to Turn Them into E-Shoppers

  • Conference paper
Information Systems, E-learning, and Knowledge Management Research (WSKS 2011)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 278))

Included in the following conference series:

  • 4263 Accesses

Abstract

This exploratory study deals with the characterization of non-buyers groups in the context of business-to-consumer electronic commerce (B2C-EC), based on their motivations for not purchasing on the Internet and explores which factors would incline them to make a first purchase on a website. In order to do so, a household panel survey was taken to 1075 Spanish respondents and analyzed with a Latent Class Analysis (LCA) approach for grouping both consumers’ motivations to reject online shopping and possible motivations to start buying online. After the definition of both sets of groups, a k-means clustering was performed in order to relate both groups in disjoint sets. The results from our study show that there are mainly three types of causes for not shopping through the electronic channel –namely, absence of physical presence of the goods or channel preference, security concerns and privacy risks, and lack of internet access and/or skills– and six different attitudes towards future use of Internet as a shopping channel, revealing a total of ten different sets of non-buyers. Implications for theory and practice are discussed in the final section.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 84.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 109.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Akaike, H.: Information Theory and an Extension of the Maximum Likelihood Principle. In: Petrov, B.N., Csake, F. (eds.) Second International Symposium on Information Theory, pp. 267–281. Akademiai Kiado, Budapest (1973)

    Google Scholar 

  2. Aldred, C.R., Smith, S.M., Swinyard, W.R.: E-shopping lovers and fearful conservatives: a market segmentation analysis. International Journal of Retail & Distribution Management 34(4/5), 308 (2006)

    Article  Google Scholar 

  3. Barnes, S.J., Bauer, H.H., Neumann, M.N., Huber, F.: Segmenting cyberspace: a customer typology for the internet. European Journal of Marketing 41(1/2), 71–93 (2007)

    Article  Google Scholar 

  4. Bhatnagar, A., Ghose, S.: A latent class segmentation analysis of e-shoppers. Journal of Business Research 57, 758–767 (2004)

    Article  Google Scholar 

  5. Brengman, M., Geuens, M., Weitjers, B., Smith, S.M., Swinyard, W.R.: Segmenting Internet shoppers based on their Web-usage-related lifestyle: a cross-cultural validation. Journal of Business Research 58, 79–88 (2005)

    Article  Google Scholar 

  6. Brown, M., Pope, N., Voges, K.: Buying or browsing? An exploration of shopping orientations and online purchase intention. European Journal of Marketing 37(11), 1666–1684 (2003)

    Article  Google Scholar 

  7. Chen, S., Li, J.: Factors Influencing the Consumers’ Willingness to Buy in E-Commerce. In: International Conference on E-Business and Information System Security, EBISS 2009, May 23-24, pp. 1–8 (2009)

    Google Scholar 

  8. Garson, G.D.: Latent class analysis, from Statnotes: Topics in Multivariate Analysis (2009), http://faculty.chass.ncsu.edu/garson/pa765/statnote.html (Date of retrieval: October 30, 2009)

  9. Ganesh, J., Reynolds, K.E., Luckett, M., Pomirleanu, N.: Online Shopper Motivations, and e-Store Attributes: An Examination of Online Patronage Behavior and Shopper Typologies. Journal of Retailing 86(1), 106–115 (2010)

    Article  Google Scholar 

  10. Hagenaars, J.A., McCutcheon, A.L.: Applied Latent Class Analysis. Cambridge University Press, Cambridge (2002)

    Book  MATH  Google Scholar 

  11. Jayawardhena, C., Wright, L.T., Dennis, C.: Consumers online: intentions, orientations and segmentation. International Journal of Retail & Distribution Management 35(6), 515–526 (2007)

    Article  Google Scholar 

  12. Kau, A.K., Tang, Y.E., Ghose, S.: Typology of online shoppers. The Journal of Consumer Marketing 20(2), 139 (2003)

    Article  Google Scholar 

  13. Linzer, D.A., Lewis, J.: poLCA: Polytomous Variable Latent Class Analysis. Version 1.1 (2009), http://userwww.service.emory.edu/~dlinzer/poLCA (Date of retrieval: November 05, 2009)

  14. McLachlan, G.J., Krishnan, T.: The EM Algorithm and Extensions. John Wiley & Sons, New York (1997)

    MATH  Google Scholar 

  15. Ng, C.F.: Satisfying shoppers’psychological needs: From public market to cyber-mall. Journal of Environmental Psychology 23, 439–455 (2003)

    Article  Google Scholar 

  16. Plummer, J.T.: The Concept and Application of Life Style Segmentation. The Journal of Marketing 38(1), 33–37 (1974)

    Article  Google Scholar 

  17. Rohm, A.J., Swaminathan, V.: A typology of online shoppers based on shopping motivations. Journal of Business Research 57, 748–757 (2004)

    Article  Google Scholar 

  18. Schwartz, G.: Estimating the Dimension of a Model. The Annals of Statistics 6, 461–464 (1978)

    Article  MathSciNet  Google Scholar 

  19. Smith, W.R.: Product Differentiation and Market Segmentation as Alternative Marketing Strategies. Journal of Marketing 21(1/4), 3 (1956)

    Article  Google Scholar 

  20. Swinyard, W.R., Smith, S.M.: Why people (don’t) shop online: A lifestyle study of the internet consumer. Psychology & Marketing 20(7), 567 (2003)

    Article  Google Scholar 

  21. Udo, G.J.: Privacy and security concerns as major barriers for e-commerce: a survey study. Information Management & Computer Security 9(4), 165–174 (2001)

    Article  Google Scholar 

  22. Urueña, A.: e-commerce B2C 2009. National Spanish Observatory of Telecommunications and Information Society (Ministry of Industry, Trade and Commerce) (2009), http://www.ontsi.red.es/articles/detail.action?id=4001&request_locale=en (Date of retrieval: September 20, 2010)

  23. Vermunt, J.K., Magidson, J.: Latent class cluster analysis. In: Hagenaars, McCutcheon (eds.) Advances in Latent Class Models, ch. B1. Cambridge University Press, Cambridge (2000)

    Google Scholar 

  24. Ye, Q., Li, G., Gu, B.: A cross-cultural validation of the web usage-related lifestyle scale: An empirical investigation in China. Electronic Commerce Research and Applications 10(3), 304–312 (2011)

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2013 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Hernández-García, Á., Iglesias-Pradas, S., Urueña-López, A. (2013). A Characterization of Non-buyers in B2C E-Commerce and the Drivers to Turn Them into E-Shoppers. In: Lytras, M.D., Ruan, D., Tennyson, R.D., Ordonez De Pablos, P., García Peñalvo, F.J., Rusu, L. (eds) Information Systems, E-learning, and Knowledge Management Research. WSKS 2011. Communications in Computer and Information Science, vol 278. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-35879-1_10

Download citation

  • DOI: https://doi.org/10.1007/978-3-642-35879-1_10

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-35878-4

  • Online ISBN: 978-3-642-35879-1

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics