Designing a talents training model for cross-border e-commerce: a mixed approach of problem-based learning with social media
journal contributionposted on 2019-04-08, 12:23 authored by Xusen Cheng, Linlin Su, Alex Zarifis
© 2019, Springer Science+Business Media, LLC, part of Springer Nature. Cross-border e-commerce has developed rapidly integrating the global economy. Research has presented some solutions for the challenges and barriers in cross-border e-commerce from the perspective of the enterprise. However, little is known about the requirements of cross-border e-commerce talents and how to train them. In this paper, we firstly conducted semi-structured interviews to acquire the requirements of cross-border e-commerce talents. Business and market knowledge, technical skills, analytical ability and business practical ability were found to be the four core requirements. Then, we integrated problem-based learning and social media to design a talents training model for cross-border e-commerce and did a program to evaluate effectiveness of the model. Finally, its effectiveness was evaluated from the four evaluation dimensions of attitude, perceived enjoyment, concentration and work intention. The talents training model was improved according to the suggestions.
We thank the National Natural Science Foundation of China (Grant No. 71571045), the Fundamental Research Funds for the Central Universities in UIBE (Grant No. CXTD10-06), Program for Excellent Talents in UIBE (Grant No. 18JQ04), and the Foundation for Disciplinary Development of SITM in UIBE for providing funding for part of this research.
- Business and Economics
Published inElectronic Commerce Research
Pages801 - 822
CitationCHENG, X., SU, L. and ZARIFIS, A., 2019. Designing a talents training model for cross-border e-commerce: a mixed approach of problem-based learning with social media. Electronic Commerce Research, 19 (4), pp.801-822.
- AM (Accepted Manuscript)
Rights holder© Springer Science+Business Media, LLC, part of Springer Nature
Publisher statementThis is a post-peer-review, pre-copyedit version of an article published in Electronic Commerce Research. The final authenticated version is available online at: https://doi.org/10.1007/s10660-019-09341-y.