arbiter
JournalsPricingAccount

Dynamic Econometric Analysis of Supply Chain Relationship Between China and Five Continents Based on Time Series Regression Model

Cheng Zhang et al.

International Journal of Information Technology and Web Engineering2025https://doi.org/10.4018/ijitwe.373259article
ABDC C
Weight
0.50

What the paper says

In response to the overall national security concept and the guiding ideology of and supply chain security proposed by President Xi, based on the authoritative data of the National Bureau of Statistics in the past 19 years from 2000 to 2018, the long-term dependence trend of the supply chain relationship between China and each continent is analyzed through the time series trend chart and time series regression model of China's trade relationship with the five continents. And the short-term abnormal phenomenon, and further explain the contribution value of the influencing variable factors between China and the supply chain relationship of the supply chain of various continents through the variance decomposition.

Open paper page →

Cite this paper

https://doi.org/https://doi.org/10.4018/ijitwe.373259

Or copy a formatted citation

@article{cheng2025,
  title        = {{Dynamic Econometric Analysis of Supply Chain Relationship Between China and Five Continents Based on Time Series Regression Model}},
  author       = {Cheng Zhang et al.},
  journal      = {International Journal of Information Technology and Web Engineering},
  year         = {2025},
  doi          = {https://doi.org/https://doi.org/10.4018/ijitwe.373259},
}

Paste directly into BibTeX, Zotero, or your reference manager.

Flag this paper

Dynamic Econometric Analysis of Supply Chain Relationship Between China and Five Continents Based on Time Series Regression Model

Flags are reviewed by the Arbiter methodology team within 5 business days.

Evidence weight

0.50

Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40

F · citation impact0.50 × 0.4 = 0.20
M · momentum0.50 × 0.15 = 0.07
V · venue signal0.50 × 0.05 = 0.03
R · text relevance †0.50 × 0.4 = 0.20

† Text relevance is estimated at 0.50 on the detail page — for your query’s actual relevance score, open this paper from a search result.