Impact of government support on users' participation in emerging green crowdsourcing logistics model: evidence from digital freight platform in China

Author:

Xiao Liang,Ke TongpingORCID,Yu Fumao,Guo Peihua

Abstract

PurposeDigital freight platform is an innovation practice of green concept, sharing economy and crowdsourcing concept in China's logistics field. It has many advantages, such as improving the utilization rate of logistics resources, reducing carbon emissions, etc., so it has been highly regarded by the government. This paper systematically studies what types of government supports are available and explores the influence mechanism of these government supports on users' participation intention in digital freight platform.Design/methodology/approachIn total 191 valid questionnaires were collected through a questionnaire survey in China. Then SmartPLS is used to analyze the collected data.FindingsThe empirical results show that user subsidies, standardization of tax administration and financial resource support have a significant impact on actual carriers' participation intention in digital freight platform. The impact of standardization of tax administration on actual carriers' participation intention is the most substantial, followed by that of financial resource support, while the user subsidies exert a minimum impact. Moreover, the impact of standardization of tax administration and user subsidies on legitimacy perception is related to enterprise scale.Originality/valueThis study enriches the field of crowdsourcing logistics research and provides referential suggestions for the formulation and implementation of government supports to promote the sustainable development of green crowdsourcing logistics platforms represented by digital freight platform. In addition, in the growth process of new models with strong social benefits, the government can promote its development through a variety of policy tools to improve the accuracy of government policies.

Publisher

Emerald

Subject

Information Systems,Management of Technology and Innovation,General Decision Sciences

Reference64 articles.

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