Skip to main content

Research on the Influence Factors of Consumer Repurchase in Dutch Auction

  • Conference paper
  • First Online:
Human Centered Computing (HCC 2018)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 11354))

Included in the following conference series:

Abstract

With the rapid development of e-commerce, the online shopping market becomes more and more competitive. How to design sales models to retain consumers and make them become continuous buying is the biggest concern of most e-commerce companies. This study was under the situation of Dutch auction model, using a large number of real auction data in Gongtianxia’s “7 days auction” and “15 min auction”. We use quantitative research method combining statistical analysis and panel data regression model, to study the influencing factors of consumers’ repeat purchase. The results show that auction methods, consumers’ perceived performance and bidding structure can affect consumers repurchase. At the same time, we established random effects regression models of the rate of consumers repurchase in 7 days and 30 days. According to the conclusion of the research in this article, we can provide some practical suggestions for Gongtianxia and a reference for other e-commerce.

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. Ping, H.: Wholesale market trading “new method”: dutch auction. Chinese market, (Z1), 56–57 (2004)

    Google Scholar 

  2. Petrowski, A.: A clearing procedure as a niching method for genetic algorithms. In: Proceedings of the 3rd IEEE Conference on Evolutionary Computation, pp. 798–803. IEEE Press, Piscataway (1996)

    Google Scholar 

  3. Comment, R., Jarrell, G.A.: The relative signalling power of dutch-auction and fixed-price self-tender offers and open-market share repurchases. J. Finance 46(4), 1243–1271 (1991)

    Article  Google Scholar 

  4. Katok, E., Roth, A.E.: Auctions of homogeneous goods with increasing returns: experimental comparison of alternative dutch auctions. Manage. Sci. 50(8), 1044–1063 (2004)

    Article  Google Scholar 

  5. Kaida, Q., Baojian, Y., Miaohua, Z., et al.: Fresh agricultural products auction market: research hotspots and new trends. J. Kunming Univ. Sci. Technol. (Nat. Sci. Ed.) 39(01), 98–109 (2014)

    Google Scholar 

  6. Guerci, E., Kirman, A., Moulet, S.: Learning to bid in sequential Dutch Auctions. J. Econ. Dyn. Control 48, 374–393 (2014)

    Article  MathSciNet  Google Scholar 

  7. Shneyerov, A.: An optimal slow Dutch auction. Econ. Theory 57(3), 577–602 (2014)

    Article  MathSciNet  Google Scholar 

  8. Hailiang, Z., Jiang, W.: Reflections on the way of flower auction trading. Market Res. 10, 59–60 (2007)

    Google Scholar 

  9. Chenhui, L.: Study on the pricing model of “Lutch auction” for the transfer of farmland contract management rights. Central South University (2012)

    Google Scholar 

  10. Ampere, Q.Y.: Mathematical problems in Dutch auctions. Neijiang Technol. 29(07), 41–42 (2008)

    Google Scholar 

  11. Jones, T.O.: Why satisfied customers defect. Harvard Bus. Rev. 73(6), 11 (1995)

    Google Scholar 

  12. Reichheld, F.F.: Learning from customer defections. Harvard Bus. Rev. 74(2), 56 (1996)

    Google Scholar 

  13. Cardozo, R.N.: An experimental study of customer effort, expectation, and satisfaction. J. Mark. Res. 2(3), 244–249 (1965)

    Article  Google Scholar 

  14. 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 

  15. Oliver, R.L.: A cognitive model of the antecedents and consequences of satisfaction decisions. J. Mark. Res. 17(4), 460–469 (1980)

    Article  Google Scholar 

  16. Khalifa, M., Lam, R.: Web-based learning: effects on learning process and outcome. IEEE Trans. Educ. 45(4), 350–356 (2002)

    Article  Google Scholar 

Download references

Acknowledgement

This work was supported by the National Natural Science Foundation of China (61472136; 61772196), the Hunan Provincial Focus Social Science Fund (2016ZDB006), Hunan Provincial Social Science Achievement Review Committee results appraisal identification project (Xiang social assessment 2016JD05) The authors gratefully acknowledge the financial support provided by the Key Laboratory of Hunan Province for New Retail Virtual Reality Technology (2017TP1026). The authors gratefully acknowledge the financial support provided by the Key Laboratory of Hunan Province for Mobile Business Intelligence (2015TP1002).

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Weijin Jiang .

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

Jiang, W., Chen, J., Xu, Y., Wang, Y., Tan, L. (2019). Research on the Influence Factors of Consumer Repurchase in Dutch Auction. In: Tang, Y., Zu, Q., Rodríguez García, J. (eds) Human Centered Computing. HCC 2018. Lecture Notes in Computer Science(), vol 11354. Springer, Cham. https://doi.org/10.1007/978-3-030-15127-0_32

Download citation

  • DOI: https://doi.org/10.1007/978-3-030-15127-0_32

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-15126-3

  • Online ISBN: 978-3-030-15127-0

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics