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The seasonal data of offline and offline total retail sales of consumer goods (TRSCG) and online market sales between 2008 and 2015 in China were selected. Then a vector error correction model was built for fitting and prediction, and used to empirically study the dynamic coupling effect between online and offline commodity retail markets. We found online sales tended to gradually invade offline sales from the perspective of retail sales of customer goods. Nevertheless, through fitting and prediction, we found a significant dynamic coupling effect between online and offline sales. In the long run, when the online retail sales of customer goods increased by 1% and other conditions were unchanged, the retail sales of offline customer goods would rise by 0.092402%.

Fitting and Prediction of Dynamic Coupling Effect Between Online and Offline Total Retail Sales of Consumer Goods