Cited by 85Technology Adoption and User BehaviourCustomer Service Quality and LoyaltyHealth, Technology, Consumer Behavior

The DOI matches its Crossref record; 3 of the 3 references it cites were found in a registry or an index.

Adopters and non-adopters of Internet banking: A segmentation study

Open access
Patsiotis, Athanasios G., Hughes, Tim, Webber, Don J.·2012·International Journal of Bank Marketing

Abstract

Purpose: This study examines internet banking adoption and resistance behaviour in Greece in order to develop profiles of adopters and non‐adopters of the service. The aim is to illustrate customers' resistance behaviour towards internet banking. The existing research does not explain resistance behaviour, since it does not clearly distinguish non‐adoption from resistance. Consequently, it has not recognised the different types of non‐adoption. Design/methodology/approach: A measuring instrument was developed and utilised in a survey of a convenience sample of 1,200 customers. The derived dimensionality of the relevant perceptual variables was used to explore the existence of different customer segments through cluster analysis. Findings: Three segments were identified, where the description of their profiles is based on customer perceptions of the service and general usage data. Across these segments adopters and non‐adopters were found to have different characteristics. With regard to demographics, only income was found to be associated with segment membership. Research limitations/implications: Perceptual and usage variables are useful in market segmentation. The results also suggest the possible existence of sub‐groups within each segment characterised by different aspects of resistance behaviour. Further research could identify and explore their potential and study non‐adopter behaviour. Practical implications: Service providers should target users and non‐users across the segments differently. While the users identified require different retention policies, the resistance or non‐resistance observed in non‐users suggest the proper management of delay and rejection behaviours. Originality/value: The customer segments identified in this study are based on new links found between the factors that drive diffusion and resistance to diffusion and general usage data. Non‐adopters across the segments resist for different reasons, or not resist.

Overview

Integrity signals

Registry

Crossref · 10.1108/02652321211195686

Cites

3 of 3 references verified0 citation errors · 0 not checkable

Statistics

Recomputing p-values needs the paper’s full text.

Verification

Claims the paper makes

We couldn’t retrieve this paper’s full text, so its claims and self-check weren’t run. The registry and citation checks still apply.

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

Citations

Cites

Flagged first, then by citations

Research works printed but not linked: 44

  1. Alfansi, L. and Sargeant, A. (2000), “Market segmentation in the Indonesian banking sector: the relationship between demographics and desired customer benefits”, International Journal of Bank Marketing, Vol. 18 No. 2, pp. 64‐74. · DOI
  2. Beane, T.P. and Ennis, D.M. (1987), “Market segmentation: a review”, European Journal of Marketing, Vol. 21 No. 5, pp. 20‐42. · DOI
  3. Black, N.J., Lockett, A., Winklhofer, H. and Ennew, C. (2001), “The adoption of internet financial services: a qualitative study”, International Journal of Retail & Distribution Management, Vol. 29 No. 8, pp. 390‐8. · DOI
  4. Burke, R.R. (2002), “Technology and the customer interface: what consumers want in the physical and virtual store”, Journal of the Academy of Marketing Science, Vol. 30 No. 4, pp. 411‐32. · DOI
  5. Chen, R. and He, F. (2003), “Examination of brand knowledge, perceived risk and consumers' intention to adopt an online retailer”, TQM & Business Excellence, Vol. 14 No. 6, pp. 677‐93. · DOI
  6. Cheung, C.M.K. and Lee, M.K.O. (2001), “Trust in internet shopping: instrument development and validation through classical and modern approaches”, Journal of Global Information Management, Vol. 9 No. 3, pp. 23‐35. · DOI
  7. Curran, J.M. and Meuter, M.L. (2005), “Self‐service technology adoption: comparing three technologies”, Journal of Services Marketing, Vol. 19 No. 2, pp. 103‐13. · DOI
  8. Durkin, M. (2007), “Understanding registration influences for electronic banking”, International Review of Retail, Distribution and Consumer Research, Vol. 17 No. 3, pp. 219‐31. · DOI
  9. Ellen, P.S., Bearden, W.O. and Sharma, S. (1991), “Resistance to technological innovations: an examination of the role of self‐efficacy and performance satisfaction”, Journal of the Academy of Marketing Science, Vol. 19 No. 4, pp. 297‐307. · DOI
  10. Gatignon, H. and Robertson, T.S. (1989), “Technology diffusion: an empirical test of competitive effects”, Journal of Marketing, Vol. 53 No. 1, pp. 35‐49. · DOI
  11. Gerrard, P. and Cunningham, J.B. (2003), “The diffusion of internet banking among Singapore consumers”, International Journal of Bank Marketing, Vol. 21 No. 1, pp. 16‐28. · DOI · Paper page
  12. Gerrard, P., Cunningham, J.B. and Devlin, J.F. (2006), “Why consumers are not using internet banking: a qualitative study”, Journal of Services Marketing, Vol. 20 No. 3, pp. 160‐8. · DOI
  13. Hair, J.F., Bush, R.P. and Ortinau, D.J. (2003), Marketing Research – Within a Changing Information Environment, 2nd ed., McGraw‐Hill/Irwin, New York, NY.
  14. Hair, J.F. Jr, Anderson, R.E., Tatham, R.L. and Black, W.C. (1998), Multivariate Data Analysis, Prentice Hall, Englewood Cliffs, NJ.
  15. Harrison, T. (1994), “Mapping customer segments for personal financial services”, International Journal of Bank Marketing, Vol. 12 No. 8, pp. 17‐25. · DOI
  16. Hughes, T. (2006), “New channels/old channels – customer management and multi‐channels”, European Journal of Marketing, Vol. 40 Nos 1/2, pp. 113‐29. · DOI
  17. Janssens, W., Wijnen, K., De Pelsmacker, P. and Van Kenhove, P. (2008), Marketing Research with SPSS, Prentice Hall, Harlow.
  18. Kimiloglou, H. (2004), “The e‐literature: a framework for understanding the accumulated knowledge about internet marketing”, Academy of Marketing Science Review, Vol. 8 No. 6, pp. 1‐36, available at: www.amsreview.org/articles/kimiloglu06‐2004.pdf (accessed 13 January 2011).
  19. Kotler, P. (2000), Marketing Management, Prentice Hall, Englewood Cliffs, NJ.
  20. Lassar, W.M., Manolis, C. and Lassar, S. (2005), “The relationship between consumer innovativeness, personal characteristics, and online banking adoption”, International Journal of Bank Marketing, Vol. 23 No. 2, pp. 176‐99. · DOI
  21. Laukkanen, P., Sinkkonen, S. and Laukkanen, T. (2008), “Consumer resistance to internet banking: postponers, opponents and rejectors”, International Journal of Bank Marketing, Vol. 26 No. 6, pp. 440‐55. · DOI
  22. Lee, E.‐J., Kwon, K.‐N. and Schumann, D.W. (2005), “Segmenting the non‐adopter category in the diffusion of internet banking”, International Journal of Bank Marketing, Vol. 23 No. 5, pp. 414‐37. · DOI
  23. Lockett, A. and Littler, D. (1997), “The adoption of direct banking services”, Journal of Marketing Management, Vol. 13 No. 8, pp. 791‐811. · DOI
  24. McKechnie, S., Winklhofer, H. and Ennew, C. (2006), “Applying the technology acceptance model to online retailing of financial services”, International Journal of Retail & Distribution Management, Vol. 34 Nos 4/5, pp. 388‐410. · DOI
  25. McMillan, S.J. and Hwang, J.‐S. (2002), “Measures of perceived interactivity: an exploration of the role of direction of communication, user control, and time in shaping perceptions of interactivity”, Journal of Advertising, Vol. 31 No. 3, pp. 29‐42. · DOI
  26. Machauer, A. and Morgner, S. (2001), “Segmentation of bank customers by expected benefits and attitudes”, International Journal of Bank Marketing, Vol. 19 No. 1, pp. 6‐17. · DOI
  27. Minhas, R.S. and Jacobs, E.M. (1996), “Benefit segmentation by factor analysis: an improved method of targeting customers for financial services”, International Journal of Bank Marketing, Vol. 14 No. 3, pp. 3‐13. · DOI
  28. Molesworth, M. and Suortti, J.‐P. (2001), “Buying cars online: the adoption of the web for high‐involvement, high‐cost purchases”, Journal of Consumer Behaviour, Vol. 2 No. 2, pp. 155‐68. · DOI
  29. Moore, G.C. and Benbasat, I. (1991), “Development of an instrument to measure the perceptions of adopting an information technology innovation”, Information Systems Research, Vol. 2 No. 3, pp. 192‐222. · DOI · Paper page
  30. Nysveen, H., Pedersen, P.E. and Thorbjornsen, H. (2005), “Intentions to use mobile services: antecedents and cross‐service comparisons”, Journal of the Academy of Marketing Science, Vol. 33 No. 3, pp. 330‐46. · DOI
  31. Ozdemir, S. and Trott, P. (2009), “Exploring the adoption of a service innovation: a study of internet banking adopters and non‐adopters”, Journal of Financial Services Marketing, Vol. 13 No. 4, pp. 284‐99. · DOI
  32. Ram, S. and Sheth, R. (1989), “Consumer resistance to innovations: the marketing problem and its solutions”, Journal of Consumer Marketing, Vol. 6 No. 2, pp. 5‐14. · DOI
  33. Rogers, E.M. (1995), Diffusion of Innovations, The Free Press, New York, NY.
  34. Sathye, M. (1999), “Adoption of internet banking by Australian consumers: an empirical investigation”, International Journal of Bank Marketing, Vol. 17 No. 7, pp. 324‐34. · DOI
  35. Schmidt, M.J. and Hollensen, S. (2006), Marketing Research – An International Approach, Prentice Hall, Harlow.
  36. Sheth, J.N. (1981), “Psychology of innovation resistance: the less developed concept (LDC) in diffusion research”, in Sheth, J.N. (Ed.), Research in Marketing, Vol. 4, JAI Press, Greenwich, CT, pp. 273‐82.
  37. Stafford, M.R. (1996), “Demographic discriminators of service quality in the banking industry”, Journal of Services Marketing, Vol. 10 No. 4, pp. 6‐22. · DOI
  38. Suzuki, Y. and Williams, L.R. (1998), “Analysis of EDI resistance behaviour”, Transportation Journal, Vol. 37 No. 4, pp. 36‐44.
  39. Walker, R.H. and Johnson, L.W. (2006), “Why consumers use and do not use technology‐enabled services”, Journal of Services Marketing, Vol. 20 No. 2, pp. 125‐35. · DOI
  40. Wang, Y.‐S., Wang, Y.‐M., Lin, H‐H. and Tang, T.‐I. (2003), “Determinants of user acceptance of internet banking: an empirical study”, International Journal of Service Industry Management, Vol. 14 No. 5, pp. 501‐19. · DOI
  41. Watson, L. and Spence, M.T. (2007), “Causes and consequences of emotions on consumer behaviour – a review and integrative cognitive appraisal theory”, European Journal of Marketing, Vol. 41 Nos 5/6, pp. 487‐511. · DOI
  42. Wood, S.L. and Moreau, C.P. (2006), “From fear to loathing? How emotion influences the evaluation and early use of innovations”, Journal of Marketing, Vol. 70 No. 3, pp. 44‐57. · DOI
  43. Yadav, M.S. and Varadarajan, R.R. (2005a), “Understanding product migration to the electronic marketplace: a conceptual framework”, Journal of Retailing, Vol. 81 No. 2, pp. 125‐40. · DOI
  44. Yadav, M.S. and Varadarajan, R.R. (2005b), “Interactivity in the electronic marketplace: an exposition of the concept and implications for research”, Journal of the Academy of Marketing Science, Vol. 33 No. 4, pp. 585‐603. · DOI

Cited by

Sorted by citations

Metadata

Authors
Patsiotis, A. G., Hughes, T., & Webber, D. J.
Affiliations
  • The American College of Greece (GR)
  • University of the West of England (GB)
  • Auckland University of Technology (NZ)
Venue
International Journal of Bank Marketing
Publisher
Emerald
Published
2012-01-27
Volume
30
Issue
1
Pages
20-42
ISSN
0265-2323 (ISSN-L)
OpenAlex
W2052392449
Cited by
85
References
3
Citations by year
2025: 2 · 2024: 10 · 2023: 3 · 2022: 5 · 2021: 9 · 2020: 6 · 2019: 6 · 2018: 8 · 2017: 4 · 2016: 5 · 2015: 10 · 2014: 3 · 2013: 12 · 2012: 2
FWCI
17.64
Type
journal article
Language
en
Open access
Locations
  • International Journal of Bank Marketing (publishedVersion)
  • UWE Research Repository (UWE Bristol) (submittedVersion, cc-by)
Topics
  • Social Sciences › Decision Sciences › Information Systems and Management › Technology Adoption and User Behaviour
  • Social Sciences › Business, Management and Accounting › Marketing › Customer Service Quality and Loyalty
  • Health Sciences › Health Professions › Health Information Management › Health, Technology, Consumer Behavior
Keywords
internet banking, technology adoption, non-adopters, customer segmentation, consumer profile, diffusion of innovations, consumer perception, Greece

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review