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An empirical comparison of sales time series for online and offline channels for commodities in China†

Published online by Cambridge University Press:  04 September 2014

JINLONG WANG ,
CAN WEN  and
XIAOYI WANG
JINLONG WANG
Affiliation:
School of Computer Engineering, Qingdao Technological University, Qingdao, China and Medical College of Qingdao University, Qingdao, China Email: wangjinlong@gmail.com
CAN WEN
Affiliation:
School of Computer Engineering, Qingdao Technological University, Qingdao, China Email: wencan314@gmail.com
XIAOYI WANG
Affiliation:
School of Management, Zhejiang University, Hangzhou, China Email: kevinwxy@zju.edu.cn
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Abstract

In this paper we make an empirical comparison of sales time series for online and offline channels. In particular, we analyse the sales dynamic and fluctuation level underlying the sales time series in different channels. The accumulative daily sales distributions of commodities are analysed statistically and the daily sales series are also studied from the perspective of complex networks. We find that most of the commodities' accumulative sales distributions can be fitted by power-law distributions. Visibility graphs are constructed for the daily sales series, and the accumulative degree distributions are also investigated – it is found that they also almost follow power-law distribution. The constant parameter α indicates that different specifications of the same goods have different sales characteristics, and different forms of packaging of commodities, either special offer or ordinary, also show distinctive sales fluctuation levels. The differences show that the direction of these relationships is opposite for online and offline channels.

Type
Paper
Information
Mathematical Structures in Computer Science , Volume 24 , Special Issue 5: Mathematical Method in Intelligent Computing and Automation , October 2014 , e240505
Copyright
Copyright © Cambridge University Press 2014 

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Footnotes

†

This work was partially supported by the National Natural Science Foundation of P. R. China (Numbers 60802066, 51005202, 61004104, 70902061 and 61173056), the China Postdoctoral Science Foundation (Numbers 20100471494 and 20100471720), vand the Excellent Young Scientist Foundation of Shandong Province of China under Grant (Number 2008BS01009).

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