Skip to main content

Understanding Consumers’ Continuance Intention Toward Self-service Stores: An Integrated Model of the Theory of Planned Behavior and Push-Pull-Mooring Theory

  • Conference paper
  • First Online:
Knowledge Management in Organizations (KMO 2019)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1027))

Included in the following conference series:

Abstract

The development of self-service technologies (SSTs) has significantly changed the interactions between customers and enterprises. Similarly, traditional services are gradually being replaced. Self-service businesses are emerging one after the other, including self-service laundries, gas stations, car washes, ticketing machines, and even self-service stores. This is not merely a new trend, but a revolution in traditional consumption patterns and service models. Why do consumers continue to patronize self-service stores? Is the pushing force or the pulling force leading them to continue to switch from traditional shops to self-service stores? Or is this change the result of planned behavior or intention, determined by attitudes, subjective norms, and perceived behavioral control? This study integrates the theory of planned behavior and push-pull-mooring theory to determine the factors that influence consumers’ continuance intention toward self-service stores. Data was collected and analyzed, using structural equation modelling, from 231 consumers who accessed self-service car washes. Results showed that attitude was the most important factor affecting consumers’ continuance intention toward self-service stores. This was followed in order of relative importance by fun, habit, perceived behavioral control, and personal innovativeness. Subjective norms, low user satisfaction, perceived ease of use, and cost-savings did not affect consumers’ continuance intention toward self-service stores. Implications for theory and practice are being derived from these findings.

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 39.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 54.99
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. Meuter, M.L., et al.: Self-service technologies: understanding customer satisfaction with technology-based service encounters. J. Market. 6(3), 50–64 (2000)

    Article  Google Scholar 

  2. Dabholkar, P.A.: Consumer evaluations of new technology-based self-service options: an investigation of alternative models of service quality. Int. J. Res. Market. 13(1), 29–51 (1996)

    Article  Google Scholar 

  3. Rosenbaum, M.S., Wong, I.A.: If you install it, will they use it? understanding why hospitality customers take “technological pauses” from self-service technology. J. Bus. Res. 68(9), 1862–1868 (2015)

    Article  Google Scholar 

  4. Weijters, B., et al.: Determinants and outcomes of customers’ use of self-service technology in a retail setting. J. Serv. Res. 10(1), 3–21 (2007)

    Article  Google Scholar 

  5. Globerson, S., Maggard, M.J.: A conceptual model of self-service. Int. J. Oper. Prod. Manag. 11(4), 33–43 (1991)

    Article  Google Scholar 

  6. Ding, X., Verma, R., Iqbal, Z.: Self-service technology and online financial service choice. Int. J. Serv. Ind. Manag. 18(3), 246–268 (2007)

    Article  Google Scholar 

  7. Rayport, J.F., Sviokla, J.J.: Exploiting the virtual value chain. Harv. Bus. Rev. 73(6), 75–85 (1995)

    Google Scholar 

  8. Lin, J.-S.C., Hsieh, P.-L.: The influence of technology readiness on satisfaction and behavioral intentions toward self-service technologies. Comput. Hum. Behav. 23(3), 1597–1615 (2007)

    Article  Google Scholar 

  9. Curran, J.M., Meuter, M.L., Surprenant, C.F.: Intentions to use self-service technologies: a confluence of multiple attitudes. J. Serv. Res. 5(3), 209–224 (2003)

    Article  Google Scholar 

  10. Dabholkar, P.A., Bagozzi, R.P.: An attitudinal model of technology-based self-service: moderating effects of consumer traits and situational factors. J. Acad. Mark. Sci. 30(3), 184–201 (2002)

    Article  Google Scholar 

  11. Curran, J.M., Meuter, M.L.: Self-service technology adoption: comparing three technologies. J. Serv. Mark. 19(2), 109–113 (2005)

    Article  Google Scholar 

  12. Liu, S.-F., Huang, L.-S., Chiou, Y.-H.: An integrated attitude model of self-service technologies: evidence from online stock trading systems brokers. Serv. Ind. J. 32(11), 1823–1835 (2012)

    Article  Google Scholar 

  13. Elliott, K., Meng, G., Hall, M.: The influence of technology readiness on the evaluation of self-service technology attributes and resulting attitude toward technology usage. Serv. Mark. Q. 33(4), 311–329 (2012)

    Article  Google Scholar 

  14. Liu, S.: The impact of forced use on customer adoption of self-service technologies. Comput. Hum. Behav. 28(4), 1194–1201 (2012)

    Article  Google Scholar 

  15. Wang, C., Harris, J., Patterson, P.: The roles of habit, self-efficacy, and satisfaction in driving continued use of self-service technologies: a longitudinal study. J. Serv. Res. 16(3), 400–414 (2013)

    Article  Google Scholar 

  16. Demoulin, N.T.M., Djelassi, S.: An integrated model of self-service technology (SST) usage in a retail context. Int. J. Retail. Distrib. Manag. 44(5), 540–559 (2016)

    Article  Google Scholar 

  17. Elliott, K.M., Hall, M.C., Meng, J.G.: Consumers’ intention to use self-scanning technology: the role of technology readiness and perceptions toward self-service technology. Acad. Mark. Stud. J. 17(1), 129–143 (2013)

    Google Scholar 

  18. Gelderman, C.J., Ghijsen, P.W.T., Diemen, R.: Choosing self-service technologies or interpersonal services—the impact of situational factors and technology-related attitudes. J. Retail. Consum. Serv. 18(5), 414–421 (2011)

    Article  Google Scholar 

  19. Bhattacherjee, A.: Understanding information systems continuance: an expectation-confirmation model. MIS Q. 25(3), 351–370 (2001)

    Article  Google Scholar 

  20. Šavareikienė, D., Galinytė, R.: Self-Service as a Motivation to Choose Innovative Service. Socialiniai tyrimai/Soc. Res. 2(27), 19–28 (2012)

    Google Scholar 

  21. Ajzen, I.: From intentions to actions: a theory of planned behavior. In: Kuhl, J., Beckmann, J. (eds.) Action Control. SSSSP, pp. 11–39. Springer, Heidelberg (1985). https://doi.org/10.1007/978-3-642-69746-3_2

    Chapter  Google Scholar 

  22. Ajzen, I.: The theory of planned behavior. Organ. Behav. Hum. Decis. Process. 50(2), 179–211 (1991)

    Article  Google Scholar 

  23. Ajzen, I., Fishbein, M.: Belief, Attitude, Intention and Behavior: An Introduction to Theory and Research. Addison-Wesley, Reading (1975)

    Google Scholar 

  24. Taylor, S., Todd, P.A.: Understanding information technology usage: a test of competing models. Inf. Syst. Res. 6(2), 144–176 (1995)

    Article  Google Scholar 

  25. Ravenstein, E.G.: The laws of migration. J. Stat. Soc. Lond. 48(2), 167–235 (1885)

    Article  Google Scholar 

  26. Lee, E.S.: A theory of migration. Demography 3(1), 47–57 (1966)

    Article  Google Scholar 

  27. Longino, C.F.: The Forest and the Trees: Micro-Level Considerations in the Study of Geographic Mobility in Old Age, in Elderly Migration and Population Redistribution, pp. 23–24. Belhaven Press, London (1992)

    Google Scholar 

  28. Nimako, S.G., Ntim, B.A.: Construct specification and misspecification within the application of push-pull-mooring theory of switching behaviour. J. Bus. Manag. Sci. 1(5), 83–95 (2013)

    Google Scholar 

  29. Moon, B.: Paradigms in migration research: exploring’moorings’ as a schema. Prog. Hum. Geogr. 19(4), 504–524 (1995)

    Article  Google Scholar 

  30. Bansal, H.S., Taylor, S.F., James, Y.: “Migrating” to new service providers: Toward a unifying framework of consumers’ switching behaviors. J. Acad. Mark. Sci. 33(1), 96–115 (2005)

    Article  Google Scholar 

  31. Langeard, E., et al.: Services Marketing: New Insights from Consumers and Managers. Marketing Science Institute, Cambridge (1981)

    Google Scholar 

  32. Keaveney, S.M., Parthasarathy, M.: Customer switching behavior in online services: an exploratory study of the role of selected attitudinal, behavioral, and demographic factors. J. Acad. Mark. Sci. 29(4), 374–390 (2001)

    Article  Google Scholar 

  33. Dagger, T.S., David, M.E.: Uncovering the real effect of switching costs on the satisfaction-loyalty association: the critical role of involvement and relationship benefits. Eur. J. Mark. 46(3/4), 447–468 (2012)

    Article  Google Scholar 

  34. Lam, S.Y., et al.: Customer value, satisfaction, loyalty, and switching costs: an illustration from a business-to-business service context. J. Acad. Mark. Sci. 32(3), 293–311 (2004)

    Article  Google Scholar 

  35. Bansal, H.S., Taylor, S.F.: The service provider switching model (SPSM) a model of consumer switching behavior in the services industry. J. Serv. Res. 2(2), 200–218 (1999)

    Article  Google Scholar 

  36. Jones, M.A., Mothersbaugh, D.L., Beatty, S.E.: Switching barriers and repurchase intentions in services. J. Retail. 76(2), 259–274 (2000)

    Article  Google Scholar 

  37. Keaveney, S.M.: Customer switching behavior in service industries: an exploratory study. J. Mark. 59(2), 71–82 (1995)

    Article  Google Scholar 

  38. Venkatesh, V., et al.: User acceptance of information technology: toward a unified view. MIS Q. 27(3), 425–478 (2003)

    Article  Google Scholar 

  39. Wang, C.: Consumer acceptance of self-service technologies: an ability–willingness model. International Journal of Market Research 59(6), 787–802 (2017)

    Article  Google Scholar 

  40. Xiaoren, Z., Xiangdong, C., Ling, D.: Comparative study of self-service technology adoption based on product function. Inf. Technol. J. 12(12), 2350–2357 (2013)

    Article  Google Scholar 

  41. Howard, M., Worboys, C.: Self-service – a contradiction in terms or customer-led choice? J. Consum. Behav. 2(4), 382–392 (2003)

    Article  Google Scholar 

  42. Agarwal, R., Prasad, J.: A conceptual and operational definition of personal innovativeness in the domain of information technology. Inf. Syst. Res. 9(2), 204–215 (1998)

    Article  Google Scholar 

  43. Boyle, R.J., Ruppel, C.P.: The effects of personal innovativeness, perceived risk, and computer self-efficacy on online purchasing intent. J. Int. Technol. Inf. Manag. 15(2), 61–73 (2006)

    Google Scholar 

  44. Limayem, M., Hirt, S.G.: Force of habit and information systems usage: theory and initial validation. J. Assoc. Inf. Syst. 4, 65–97 (2003)

    Google Scholar 

  45. Limayem, M., Hirt, S.G., Cheung, C.M.K.: How habit limits the predictive power of intention: the case of information systems continuance. MIS Q. 31(4), 705–737 (2007)

    Article  Google Scholar 

  46. Bamberg, S., Ajzen, I., Schmidt, P.: Choice of travel mode in the theory of planned behavior: the roles of past behavior, habit, and reasoned action. Basic Appl. Soc. Psychol. 25(3), 175–187 (2003)

    Article  Google Scholar 

  47. Hair, J., et al.: Multivariate Data Analysis, 6th edn. Pearson Education, New Jersey (2006)

    Google Scholar 

  48. Nunnally, J.C.: Psychometric Theory. McGraw Hill, New York (1978)

    Google Scholar 

  49. Fornell, C., Larcker, D.F.: Evaluating structural equation models with unobservable variables and measurement error. J. Mark. Res. 18(1), 39–50 (1981)

    Article  Google Scholar 

  50. Wang, Y.S.: Assessing ecommerce systems success: a respecification and validation of the DeLone and McLean model of IS success. Inf. Syst. J. 18(5), 529–557 (2008)

    Article  Google Scholar 

  51. Ringle, C.M., Wende, S., Becker, J.M.: SmartPLS 3. SmartPLS GmbH, Boenningstedt (2015). http://www.smartpls.com

  52. Chin, W.W.: The partial least squares approach for structural equation modeling. In: Marcoulides, G.A. (ed.) Modern Methods for Business Research. Lawrence Erlbaum Associates, Mahwah (1998)

    Google Scholar 

  53. Ganesh, J., Arnold, M.J., Reynolds, K.E.: Understanding the customer base of service providers: an examination of the differences between switchers and stayers. J. Mark. 64(3), 65–87 (2000)

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Hui-Min Lai .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2019 Springer Nature Switzerland AG

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Chuang, SS., Lai, HM. (2019). Understanding Consumers’ Continuance Intention Toward Self-service Stores: An Integrated Model of the Theory of Planned Behavior and Push-Pull-Mooring Theory. In: Uden, L., Ting, IH., Corchado, J. (eds) Knowledge Management in Organizations. KMO 2019. Communications in Computer and Information Science, vol 1027. Springer, Cham. https://doi.org/10.1007/978-3-030-21451-7_13

Download citation

  • DOI: https://doi.org/10.1007/978-3-030-21451-7_13

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-21450-0

  • Online ISBN: 978-3-030-21451-7

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics