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.
| Original language | English |
|---|---|
| Pages (from-to) | 571-583 |
| Number of pages | 13 |
| Journal | Electronic Commerce Research |
| Volume | 15 |
| Issue number | 4 |
| DOIs | |
| Publication status | Published - Dec 1 2015 |
| Externally published | Yes |
Bibliographical note
Funding Information: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.
Publisher Copyright:
© 2015, Springer Science+Business Media New York.
ASJC Scopus Subject Areas
- Economics, Econometrics and Finance (miscellaneous)
- Human-Computer Interaction