Repurchase intention in sports brand industry in China: Attributes of live streamers and customer-to-customer interaction of live streaming e-commerce
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DOIhttp://dx.doi.org/10.21511/im.20(2).2024.04
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Article InfoVolume 20 2024, Issue #2, pp. 40-53
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The rapid growth of live streaming e-commerce is hindered by its high rate of product returns, which poses a challenge to its long-term sustainability. Specifically, clothes shoppers account for 30% of all sales made during live broadcasts. This study aims to evaluate the impact of live streaming e-commerce on repurchase intention in the sports brand industry in China. The paper used quantitative research methods with 398 data collected from consumers of sports brands who were willing to provide information regarding their shopping experience on the live streaming platform. 224 respondents were females (56.3%), and 174 were males (43.7%). The study adopted a questionnaire to collect the data. Partial least squares-structural equation modeling was used to test the correlation between the variables. The results revealed direct and positive effect of consumer trust (β = 0.397, p = 0.000) and perceived value (β = 0.215, p = 0.001) on repurchase intention in live streaming e-commerce. The findings also indicated that both consumer trust and perceived value play a mediating role. In addition, the results supported the assumption that the characteristics of live streamers (β = 0.389, p = 0.000) have a positive impact on consumer trust, and customer-to-customer interaction (β = 0.678, p = 0.000) has a significant impact on perceived value. Finally, sports brands are advised to optimize live streaming platforms to better meet consumers’ needs.
Acknowledgment
The authors acknowledge Universiti Utara Malaysia (UUM) that supported this study.
- Keywords
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JEL Classification (Paper profile tab)L67, L81, M31
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References71
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Tables6
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Figures1
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- Figure 1. Research framework
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- Table 1. Sample characteristics
- Table 2. Assessment of the measurement model
- Table 3. Heterotrait-monotrait (HTMT) values
- Table 4. R2 results
- Table 5. Results of hypothesis testing – direct effects
- Table 6. Results of hypothesis testing – indirect and moderation effects
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