The purpose of this paper is to examine the potential impacts of various variables on product return activities after online shopping. Previous studies on customer behaviour have been predominantly concerned with return on used products and other product-quality-related constructs in the model. This study aims to specially examine the logistics service-related and customer intention–related variables for general products under the e-commerce circumstance.
Structured questionnaire data for this study were collected in the two southeast cities of China (162 useable responses). Structural equation modelling was used to examine the latent variables.
The results confirmed that product return intention has the greatest impact on online shopping returns with a direct effect of 0.63, followed by the flexibility in return (logistics service) with a direct effect of 0.49.
Such a model not only enriches the theoretical understanding of customer behaviour studies but also offers online shopping stores and platforms a quantitative benchmark and new perspective on the design of online shopping supply chains by considering product returns so as to improve the customer satisfaction.
This work is supported by the National Natural Science Foundation of China (grant number 71701126) and the Shanghai Pujiang Program (grant number 15PJ1402800).
Lin, D., Lee, C., Siu, M., Lau, H. and Choy, K. (2020), "Analysis of customers' return behaviour after online shopping in China using SEM", Industrial Management & Data Systems, Vol. ahead-of-print No. ahead-of-print. https://doi.org/10.1108/IMDS-05-2019-0296Download as .RIS
Emerald Publishing Limited
Copyright © 2020, Emerald Publishing Limited