Prediction on transaction amounts of China’s CBEC with improved GM (1, 1) models based on the principle of new information priority

Chuanmin Mi, Yijing Wang and Lin Xiao ()
Additional contact information
Chuanmin Mi: Nanjing University of Aeronautics and Astronautics
Yijing Wang: Nanjing University of Aeronautics and Astronautics
Lin Xiao: Nanjing University of Aeronautics and Astronautics

Electronic Commerce Research, 2021, vol. 21, issue 1, No 5, 125-146

Abstract: Abstract Benefited by e-commerce activities and information technology development, cross-border e-commerce (CBEC) has experienced rapid growth and attracted much research attention. This study takes China’s CBEC as a typical research object and intends to forecast its future development trend based on an exploration of its dynamic changing rules as a whole. The data set of transaction amounts of China’s CBEC from 2008 to 2018 was used in the modeling processes of improved grey models (GM) (1,1) proposed in this study, after which forecast results on the development of China’s CBEC from 2019 to 2020 were achieved. The experimental results reveal that, introducing the principle of new information priority to the improvement of grey models indeed works when forecasting a newly-emerging and vulnerable system like CBEC. Finally, it is predicted that China’s CBEC promises to continue to grow in the near future.

Keywords: CBEC; Reversed GM (1; 1) model; Renewal GM (1; 1) model; New information priority; Forecast (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
http://link.springer.com/10.1007/s10660-020-09434-z Abstract (text/html)
Access to the full text of the articles in this series is restricted.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:elcore:v:21:y:2021:i:1:d:10.1007_s10660-020-09434-z

Ordering information: This journal article can be ordered from
http://www.springer.com/journal/10660

DOI: 10.1007/s10660-020-09434-z

Access Statistics for this article

Electronic Commerce Research is currently edited by James Westland

More articles in Electronic Commerce Research from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().