The paper aims to develop (1) a comprehensive framework for classifying crowdshipping business models and (2) a taxonomy of currently implemented crowdshipping business models.
The business models of 105 companies offering crowdsourced delivery services are analysed. Cluster analysis and principal component analysis are applied to develop a business model taxonomy.
A detailed crowdsourced delivery business model framework with 74 features is developed. Based on it, six distinct clusters of crowdshipping business models are identified. One cluster stands out as the most appealing to customers based on social media metrics, indicating which type of crowdshipping business models is the most successful.
Detailed investigations of each of the six clusters and of recent crowdshipping business model developments are needed in further research in order to enhance the derived taxonomy.
This paper serves as a best-practices guide for both start-ups and global logistics operators for establishing or further developing their crowdsourced delivery business models.
This paper provides a holistic understanding of the business models applied in the crowdshipping industry and is a valuable contribution to the yet small amount of studies in the crowd logistics field.
The authors thank Prof. Dr. oec. Julia Arlinghaus and Prof. Dr. Eugenia Rosca for discussions and helpful comments on an initial version of the manuscript.
Ciobotaru, G. and Chankov, S. (2021), "Towards a taxonomy of crowdsourced delivery business models", International Journal of Physical Distribution & Logistics Management, Vol. 51 No. 5, pp. 460-485. https://doi.org/10.1108/IJPDLM-10-2019-0326
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