Skip to main content

Personal Information Protection Behaviors of Consumers in Different Country Context and User Interface Designs

  • Conference paper
  • First Online:
Cross-Cultural Design. Applications in Business, Communication, Health, Well-being, and Inclusiveness (HCII 2022)

Abstract

Internet information security is getting more attention. Users are adopting more and more ways to protect their information when browsing the web and shopping online, and more users are choosing not to disclose personal information to websites. Many factors influence consumers’ privacy disclosure intention. This study innovatively introduces consumers’ country background and website user interface design to explore their influence on behavioural intention. We developed a model of factors influencing consumers’ intention to disclose personal information, organized experiments to collect data, and conducted an empirical study using partial least squares structural equation modeling (PLS-SEM). The study results showed that consumers’ general trust in companies is influenced by many factors and significantly affects consumers’ intention to disclose information. Corporate reputation significantly affects consumers’ intention to disclose information directly and indirectly. Consumers’ privacy concerns can also have a significant impact. Country context and user interface design also influenced consumer behaviour, but not as much as corporate reputation and consumer privacy concerns. Research provides targeted development recommendations for consumers, businesses, and legislators.

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 69.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 89.99
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

References

  1. UNCTAD: Digital economy report 2021. Tech. rep., United Nations Conference on Trade and Development, Palais des Nations, 8–14, Av. de la Paix, 1211 Geneva 10, Switzerland (2021)

    Google Scholar 

  2. UNCTAD: Estimates of global e-commerce 2019 and preliminary assessment ofcovid-19 impact on online retail 2020. Tech. rep., United Nations Conference on Trade and Development, Palais des Nations, 8–14, Av. de la Paix, 1211 Geneva 10, Switzerland (2021)

    Google Scholar 

  3. Huang, G.B.: Global ecommerce forecast 2021(2021). https://www.emarketer.com

  4. Regulation, P.: Regulation (EU) 2016/679 of the European Parliament and of the Council. Regulation (EU), 679, (2016)

    Google Scholar 

  5. Voigt, P., Von dem Bussche, A.: The EU General Data Protection Regulation (GDPR). A Practical Guide, 1st edn., vol. 10, pp. 10–5555 Springer, Cham (2017). https://doi.org/10.1007/978-3-319-57959-7

  6. Culnan, M.J., Armstrong, P.K.: Information privacy concerns, procedural fairness, and impersonal trust: an empirical investigation. Organ. Sci. 10(1), 104–115 (1999)

    Article  Google Scholar 

  7. Robinson, C.: Disclosure of personal data in ecommerce: a cross-national comparison of Estonia and the united states. Telematics Inform. 34(2), 569–582 (2017)

    Article  Google Scholar 

  8. Leach, E.: Social BEhavior: Its Elementary Forms. Harcourt, Brace (1961)

    Google Scholar 

  9. Martin, K.D., Murphy, P.E.: The role of data privacy in marketing. J. Acad. Mark. Sci. 45(2), 135–155 (2016). https://doi.org/10.1007/s11747-016-0495-4

    Article  Google Scholar 

  10. Kokolakis, S.: Privacy attitudes and privacy behaviour: a review of current research on the privacy paradox phenomenon. Comput. Secur. 64, 122–134 (2017)

    Article  Google Scholar 

  11. Punyatoya, P.: Effects of cognitive and affective trust on online customer behavior. Market. Intell. Plann. 37(2018)

    Google Scholar 

  12. Huang, J.S., Pan, S.L.: China’s suning: combining online and offline businesses units. In: Digital Enablement and Innovation in China: A Casebook, pp. 39–44. World Scientific, Beijing (2019)

    Google Scholar 

  13. Corritore, C.L., Kracher, B., Wiedenbeck, S.: On-line trust: concepts, evolving themes, a model. Int. J. Hum Comput Stud. 58(6), 737–758 (2003)

    Article  Google Scholar 

  14. Liu, Y., Tang, X.: The effects of online trust-building mechanisms on trust and repurchase intentions: an empirical study on eBay. Inf. Technol. People 31(2018)

    Google Scholar 

  15. Liang, Y.: Research on factors affecting mobile E-commerce consumer trust. In: Zhang, R., Zhang, Z., Liu, K., Zhang, J. (eds.) LISS 2013, pp. 1023–1028. Springer, Berlin (2013). https://doi.org/10.1007/978-3-642-40660-7_153

  16. Hoffman, D.L., Novak, T.P., Peralta, M.A.: Information privacy in the marketspace: implications for the commercial uses of anonymity on the web. Inf. Soc. 15(2), 129–139 (1999)

    Article  Google Scholar 

  17. Jarvenpaa, S.L., Tractinsky, N., Vitale, M.: Consumer trust in an internet store. Inf. Technol. Manage. 1(1), 45–71 (2000)

    Article  Google Scholar 

  18. Jarvenpaa, S.L., Knoll, K., Leidner, D.E.: Is anybody out there? Antecedents of trust in global virtual teams. J. Manag. Inf. Syst. 14(4), 29–64 (1998)

    Article  Google Scholar 

  19. Swaminathan, V., Lepkowska-White, E., Rao, B.P.: Browsers or buyers in cyberspace? An investigation of factors influencing electronic exchange. J. Comput. Mediat. Commun. 5(2), JCMC523 (1999)

    Google Scholar 

  20. Steel, J.L.: Interpersonal correlates of trust and self-disclosure. Psychol. Rep. 68(3 suppl), 1319–1320 (1991)

    Article  Google Scholar 

  21. Wakefield, R.: The influence of user affect in online information disclosure. J. Strateg. Inf. Syst. 22(2), 157–174 (2013)

    Article  Google Scholar 

  22. Dinev, T., Hart, P.: An extended privacy calculus model for e-commerce transactions. Inf. Syst. Res. 17(1), 61–80 (2006)

    Article  Google Scholar 

  23. Bansal, G., Zahedi, F.M., Gefen, D.: Do context and personality matter? Trust and privacy concerns in disclosing private information online. Inf. Manag. 53(1), 1–21 (2016)

    Article  Google Scholar 

  24. Smith, H.J., Dinev, T., Xu, H.: Information privacy research: an interdisciplinary review. MIS Q. 35, 989–1015 (2011)

    Google Scholar 

  25. Dinev, T., Hart, P.: Internet privacy concerns and social awareness as determinants of intention to transact. Int. J. Electron. Commer. 10(2), 7–29 (2005)

    Article  Google Scholar 

  26. Eastlick, M.A., Lotz, S.L., Warrington, P.: Understanding online B-to-C relationships: an integrated model of privacy concerns, trust, and commitment. J. Bus. Res. 59(8), 877–886 (2006)

    Article  Google Scholar 

  27. Sheehan, K.B., Hoy, M.G.: Flaming, complaining, abstaining: how online users respond to privacy concerns. J. Advert. 28(3), 37–51 (1999)

    Article  Google Scholar 

  28. Dinev, T., Hart, P., Mullen, M.R.: Internet privacy concerns and beliefs about government surveillance–an empirical investigation. J. Strateg. Inf. Syst. 17(3), 214–233 (2008)

    Article  Google Scholar 

  29. Yu, L., Li, H., He, W., Wang, F.K., Jiao, S.: A meta-analysis to explore privacy cognition and information disclosure of internet users. Int. J. Inf. Manage. 51, 102015 (2020)

    Article  Google Scholar 

  30. Bol, N., et al.: Understanding the effects of personalization as a privacy calculus: analyzing self-disclosure across health, news, and commerce contexts. J. Comput.-Mediat. Commun. 23(6), 370–388 (2018)

    Article  Google Scholar 

  31. Fernandes, T., Pereira, N.: Revisiting the privacy calculus: why are consumers (really) willing to disclose personal data online? Telematics Inform. 65, 101717 (2021)

    Article  Google Scholar 

  32. Sun, Y., Wang, N., Shen, X.L., Zhang, J.X.: Location information disclosure in location-based social network services: privacy calculus, benefit structure, and gender differences. Comput. Hum. Behav. 52, 278–292 (2015)

    Article  Google Scholar 

  33. Venkatesh, V., Morris, M.G.: Why don’t men ever stop to ask for directions? Gender, social influence, and their role in technology acceptance and usage behavior. MIS Q 24, 115–139 (2000)

    Google Scholar 

  34. Plangger, K., Montecchi, M.: Thinking beyond privacy calculus: investigating reactions to customer surveillance. J. Interact. Mark. 50, 32–44 (2020)

    Article  Google Scholar 

  35. Doney, P.M., Cannon, J.P.: An examination of the nature of trust in buyer–seller relationships. J. Mark. 61(2), 35–51 (1997)

    Google Scholar 

  36. Ganesan, S.: Determinants of long-term orientation in buyer-seller relationships. J. Mark. 58(2), 1–19 (1994)

    Article  Google Scholar 

  37. Burke, P.F., Dowling, G., Wei, E.: The relative impact of corporate reputation on consumer choice: beyond a halo effect. J. Mark. Manag. 34(1314), 1227–1257 (2018)

    Article  Google Scholar 

  38. Earp, J.B., Baumer, D.: Innovative web use to learn about consumer behavior and online privacy. Commun. ACM 46(4), 81–83 (2003)

    Article  Google Scholar 

  39. Imler, B.B., Garcia, K.R., Clements, N.: Are reference pop-up widgets welcome or annoying? A usability study. Ref. Serv. Rev. 44(3), 282–291 (2016)

    Google Scholar 

  40. Adjerid, I., Peer, E., Acquisti, A.: Beyond the privacy paradox: objective versus relative risk in privacy decision making. MIS Q. 42(2), 465–488 (2018)

    Article  Google Scholar 

  41. Acquisti, A., Grossklags, J.: What can behavioral economics teach us about privacy. Digit. Privacy Theory Technol. Pract. 18, 363–377 (2007)

    Google Scholar 

  42. Barth, S., De Jong, M.D.: The privacy paradox–investigating discrepancies between expressed privacy concerns and actual online behavior–a systematic literature review. Telematics Inform. 34(7), 1038–1058 (2017)

    Article  Google Scholar 

  43. Quinn, K.: Why we share: a uses and gratifications approach to privacy regulation in social media use. J. Broadcast. Electron. Media 60(1), 61–86 (2016)

    Article  Google Scholar 

  44. Podsakoff, P.M., MacKenzie, S.B., Podsakoff, N.P.: Sources of method bias in social science research and recommendations on how to control it. Annu. Rev. Psychol. 63, 539–569 (2012)

    Article  Google Scholar 

  45. Ringle, C.M., Wende, S., Becker, J.M.: SmartPLS 3. SmartPLS GmbH, Boenningstedt. J. Serv, Sci. Manag. 10(3), 32–49 (2015)

    Google Scholar 

  46. Sarstedt, M., Ringle, C.M., Hair, J.F., et al.: Partial least squares structural equation modeling. Handb. Market Res. 26(1), 1–40 (2017)

    MATH  Google Scholar 

  47. Cronbach, L.J.: Coefficient alpha and the internal structure of tests. Psychometrika 16(3), 297–334 (1951)

    Article  Google Scholar 

  48. Hair, J.F.: Multivariate Data Analysis, 7th edn. Prentice Hall, Upper Saddle River (2009)

    Google Scholar 

  49. Nunnally, J.C.: Psychometric Theory 3E. Tata McGraw-Hill Education, New York (1994)

    Google Scholar 

  50. Forza, C.: Survey research in operations management: a process-based perspective. Int. J. Oper. Prod. Manag. 22(2), 152–194 (2002)

    Google Scholar 

  51. Hair, J.F., Sarstedt, M., Ringle, C.M., Mena, J.A.: An assessment of the use of partial least squares structural equation modeling in marketing research. J. Acad. Mark. Sci. 40(3), 414–433 (2012)

    Article  Google Scholar 

  52. Barclay, D., Thompson, R., Higgins, C.: The partial least squares (PLS) approach to causal modeling: personal computer use as an illustration. Technol. Stud. 2 (1995)

    Google Scholar 

  53. Chin, W.W., Newsted, P.R.: Structural equation modeling analysis with small samples using partial least squares. Stat. Strat. Small Sample Res. 1(1), 307–341 (1999)

    Google Scholar 

  54. Luhmann, N.: Trust and Power. Wiley, Chichester (2018)

    Google Scholar 

  55. Li, S.: Study on development of small and medium-sized enterprises cluster in china with view of regional cultural perspective. Sci. Res. 37, 7–18 (2010)

    Google Scholar 

  56. Manchala, D.W.: E-commerce trust metrics and models. IEEE Internet Comput. 4(2), 36–44 (2000)

    Article  Google Scholar 

Download references

Acknowledgments

This study is supported by grants from the Zhejiang University of Technology Humanities and Social Sciences Pre-Research Fund Project (GZ21731320013), the Zhejiang University of Technology Subject Reform Project (GZ21511320030), and China’s National Undergraduate Innovation and Entrepreneurship Training Program (File No. 202110337048).

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Cong Cao .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2022 The Author(s), under exclusive license to Springer Nature Switzerland AG

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Wei, T., Cao, C., Shi, Y. (2022). Personal Information Protection Behaviors of Consumers in Different Country Context and User Interface Designs. In: Rau, PL.P. (eds) Cross-Cultural Design. Applications in Business, Communication, Health, Well-being, and Inclusiveness. HCII 2022. Lecture Notes in Computer Science, vol 13313. Springer, Cham. https://doi.org/10.1007/978-3-031-06050-2_7

Download citation

  • DOI: https://doi.org/10.1007/978-3-031-06050-2_7

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-06049-6

  • Online ISBN: 978-3-031-06050-2

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics