2021
DOI: 10.4018/jgim.20210901.oa4
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What Determines the Pattern of China's Cross-Border E-Commence With the World?

Abstract: Cross-border e-commerce has gradually expanded in international trade markets over the past decades. This paper analyzes the determinants of the volume of cross-border e-commerce in a gravity model framework. Moreover, the paper explores the role of internet popularity and finds a significant promotion effect on the volume of cross-border e-commerce. Furthermore, by utilizing cross-border express delivery data, the analysis indicates a significant difference in the impacts of the determinants between the aggre… Show more

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Cited by 6 publications
(6 citation statements)
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References 23 publications
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“…Sellers can achieve the purpose of improving consumers’ purchase intentions by combining different strategies of network structure characteristics (network density, network centrality) and customer experience. Yang et al (2021) combined perceived risk, transfer cost, and user loyalty VSL framework theory, constructed a new cross-border e-commerce mobile market user transfer intention framework, and analyzed user loyalty in the cross-border e-commerce mobile market, transfer costs, and transfer intentions.…”
Section: Resultsmentioning
confidence: 99%
“…Sellers can achieve the purpose of improving consumers’ purchase intentions by combining different strategies of network structure characteristics (network density, network centrality) and customer experience. Yang et al (2021) combined perceived risk, transfer cost, and user loyalty VSL framework theory, constructed a new cross-border e-commerce mobile market user transfer intention framework, and analyzed user loyalty in the cross-border e-commerce mobile market, transfer costs, and transfer intentions.…”
Section: Resultsmentioning
confidence: 99%
“…Technological stimuli involve factors related to technological development and advancement and fashion trends in consumer behaviour. As presented in Table B10 in Appendix B, internet popularity was the only one observed (Yang et al, 2021).…”
Section: Outer Cbec Ecosystem Stimulimentioning
confidence: 99%
“…Secondary data were the second most popular method adopted by seven studies that applied econometrics (e.g., ordinary least squares and logistic regression) to the relationships between the focal variables and CBEC transaction. The data source included survey data from national institutes of statistics (Sleuwaegen & Smith, 2020; Valarezo et al, 2018), the literature (Gomez‐Herrera et al, 2014), transactional data concerning CBEC delivery services (Anson et al, 2019; Kim et al, 2017; Yang et al, 2021), the United Nations (UN) Comtrade databases (Du et al, 2022) and financial reports of CBEC platforms (Du et al, 2022).…”
Section: Descriptive Analysismentioning
confidence: 99%
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“…Meanwhile, additional drivers for e-commerce in influencing consumer's purchasing intention and perceived value are associated with platform characteristics. Yang et al (2021) note that internet popularity acts as a catalyst to lift the sales volume up. China's market has more than 989 million internet users in 2020, while 79% of them shopped online (Evelyn, 2021).…”
Section: Market Driven Value Creationmentioning
confidence: 99%