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A practical model to predict the repeat purchasing pattern of consumers in the C2C e-commerce

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Abstract

In the recent decade, the C2C e-commerce has developed very fast and played a key role in the internet transaction. However, no work has been reported about predicting the consumers’ repeat purchasing pattern in the area so far. To fill the gap, this paper develops a novel predicting model according to some special characteristics of the C2C e-commerce. This model only uses the information about frequencies and timings of transactions. Thus, it is simple and convenient to be implemented. To verify the validity of the model, we test some samples from the real transaction data. The numerical results show that the new model outperforms the benchmark Pareto/NBD model. Thus, it is indeed an easy but powerful tool for the vendors on the C2C platform to predict the repeat purchasing pattern of consumers in the C2C e-commerce.

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References

  1. Kerstin, R., & Sönke, A. (2014). Modeling repeat purchases in the internet when RFM captures past influence of marketing. Working Paper. http://hdl.handle.net/10419/50730.

  2. Fader, P. S., Hardie, B., & Lee, K. L. (2005). “Counting your customers” the easy way: An alternative to the Pareto/NBD model. Marketing Science, 24(2), 275–284.

    Article  Google Scholar 

  3. Sichel, H. (1982). Repeat-buying and the generalized inverse gaussian-poisson distribution. Journal of the Royal Statistical Society: Series C (Applied Statistics), 31(3), 193–204.

    Google Scholar 

  4. Chiang, D. A., Wang, Y. H., & Chen, S. P. (2010). Analysis on repeat-buying patterns. Knowledge Based Systems, 23(8), 757–768.

    Article  Google Scholar 

  5. Kim, H. W., Xu, Y. J., & Gupta, S. (2012). Which is more important in internet shopping, perceived price or trust? Electronic Commerce Research and Applications, 11(3), 241–252.

    Article  Google Scholar 

  6. Lee, P. M. (2002). Behavioral model of online purchasers in ecommerce environment. Electronic Commerce Research, 2(1–2), 75–85.

    Article  Google Scholar 

  7. Leeflang, P., & Wittink, D. (2000). Building models for marketing decisions: Past, present and future. International Journal of Research in Marketing, 17(2–3), 105–126.

    Article  Google Scholar 

  8. Uncles, M., Ehrenberg, A., & Hammond, K. (1995). Patterns of buyer behavior: Regularities, models and extensions. Marking Science, 14(3), 71–78.

    Article  Google Scholar 

  9. Lu, Y. B., Zhao, L., & Wang, B. (2010). From virtual community members to C2C e-commerce buyers: trust in virtual communities and its effect on consumers’ purchase intention. Electronic Commerce Research and Applications, 9(4), 346–360.

    Article  Google Scholar 

  10. Du, H. S., Yu, H., Fang, Y. L., & Wang, S. Y. (2012). Empirical investigation of Eachnet: The eBay model of C2C online auction in China. IEEE Transaction on Engineering Management, 59(1), 160–175.

    Article  Google Scholar 

  11. iResearch (2013). 2012 China’s e-commerce deal size report. http://ec.iresearch.cn.

  12. Moe, W. W., & Fader, P. S. (2004). Dynamic conversion behavior at e-commerce sites. Management Science, 50(3), 326–335.

    Article  Google Scholar 

  13. Olbrich, R., & Holsing, C. (2011). Modeling consumer purchasing behavior in social shopping communities with clickstream data. International Journal of Electronic Commerce, 16(2), 15–40.

    Article  Google Scholar 

  14. Oliveira-Castro, J. M., Ferreira, D. L., Foxall, G. R., & Schrezenmaier, T. C. (2005). Dynamics of repeat buying for packaged food products. Journal of Marketing Management, 21(1–2), 37–61.

    Article  Google Scholar 

  15. Rose, S., Hair, N., & Clark, M. (2011). Online customer experience: A review of the business-to-consumer online purchase context. International Journal of Management Reviews, 13(1), 24–39.

    Article  Google Scholar 

  16. Abe, M. (2009). “Counting your customers” one by one: A hierarchical Bayes extension to the Pareto/NBD model. Marketing Science, 28(3), 541–553.

    Article  Google Scholar 

  17. Jerath, K., Fader, P. S., & Hardie, B. G. (2011). New perspectives on Customer “Death” using a generalization of the Pareto/NBD model. Marketing Science, 30(5), 866–880.

    Article  Google Scholar 

  18. Ehrenberg, A. (1968). The practical meaning and usefulness of the NBD/LSD theory of repeat-buying. Journal of the Royal Statistical Society: Series C (Applied Statistics), 17(1), 17–32.

    Google Scholar 

  19. Schmittlein, D. C., Bemmaor, A. C., & Morrison, D. G. (1985). Technical note—why does the NBD model work? Robustness in representing product purchases, brand purchases and imperfectly recorded purchases. Marketing Science, 4(3), 255–266.

    Article  Google Scholar 

  20. Foxall, G. R. (2010). Invitation to consumer behavior analysis. Journal of Organizational Behavior Management, 30(2), 92–109.

    Article  Google Scholar 

  21. Meyer-Waarden, L., & Benavent, C. (2006). The impact of loyalty programmes on repeat purchase behavior. Journal of Marketing Management, 22(1–2), 61–88.

    Article  Google Scholar 

  22. Tapiero, C. S. (2000). The NBD repeat purchase process and M/G/∞ queues. International Journal of Production Economics, 63(2), 141–145.

    Article  Google Scholar 

  23. Trinh, G., Rungie, C., Wright, M., Driesener, C., & Dawes, J. (2014). Predicting future purchases with the Poisson log-normal model. Marketing Letters, 25(2), 219–234.

    Article  Google Scholar 

  24. Corbitt, B. J., Thanasankit, T., & Yi, H. (2003). Trust and e-commerce: A study of consumer perceptions. Electronic Commerce Research and Applications, 2(3), 203–215.

    Article  Google Scholar 

  25. Thibaut, J. W., & Kelly, H. (1959). The social psychology of groups. New York: Wiley.

    Google Scholar 

  26. Adamic, L. A., & Huberman, B. A. (2000). Power-law distribution of the world wide web. Science, 287, 2115.

    Article  ADS  Google Scholar 

  27. Clauset, A., Shalizi, C. R., & Newman, M. J. (2009). Power-law distributions in empirical data. SIAM Review, 51(4), 661–703.

    Article  MathSciNet  ADS  MATH  Google Scholar 

  28. Stumpf, M. U., & Porter, M. A. (2012). Critical truths about power laws. Science, 335, 665.

    Article  CAS  MathSciNet  PubMed  ADS  Google Scholar 

  29. Ehrenberg, A. (1988). Repeat-buying: Facts, theory and applications. London: Griffin.

    Google Scholar 

  30. Spiegelhalter, D., Thomas, A., & Best, N. G., (2003). WinBUGS: Bayesian inference using Gibbs sampling. Manual version 1.4. Imperial College, Medical Research Council Biostatistics Unit, Cambrige. http://www.mrc-bsu.cam.ac.uk/bugs.

  31. Smith, B. J. (2005). Bayesian output analysis program (BOA) for MCMC. Version 1.1.5. University of Iowa. http://www.public-health.uiowa.edu/boa.

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Acknowledgments

Tian’s research has been supported by the Chinese National Science Foundation #11401485 and #71331004. Ye’s research has been supported by the Chinese National Science Foundation #71271172.

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Authors and Affiliations

  1. School of Business Administration, Southwestern University of Finance and Economics, Chengdu, 611130, China

    Ye Tian, Zuoliang Ye, Yufei Yan & Miao Sun

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  1. Ye Tian
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  2. Zuoliang Ye
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  3. Yufei Yan
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  4. Miao Sun
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Correspondence to Ye Tian.

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Tian, Y., Ye, Z., Yan, Y. et al. A practical model to predict the repeat purchasing pattern of consumers in the C2C e-commerce. Electron Commer Res 15, 571–583 (2015). https://doi.org/10.1007/s10660-015-9201-8

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