Chasin F, von Hoffen M, Cramer M, Matzner M (2017)
Publication Language: English
Publication Type: Journal article, Original article
Publication year: 2017
Pages Range: 1-33
Journal Issue: 10257
URI: http://rdcu.be/tIF4
DOI: 10.1007/s10257-017-0357-8
Airbnb and Uber enable private individuals to share physical resources via their Internet platforms, and both have become popular subjects of information systems and e-business research. In the top dogs’ slipstream resides a variety of less-known platforms that allow to share different resources or to share resources in different ways. Researchers who study these platforms and the underlying consumer behaviors face the problem of situating their findings precisely. Practitioners lack an overview of the diversity of these platforms and their characteristics too. This article suggests a taxonomy that helps to better characterize platforms for Peer-to-Peer (P2P) Sharing and Collaborative Consumption (SCC). We used the taxonomy to describe the evolution of 522 P2P SCC platforms over the period of 35 months and to demonstrate and partly evaluate its application. All descriptions taken together constitute a comprehensive data source to study P2P SCC platforms. When researchers use the taxonomy, they can describe and situate insights precisely so that stakeholders can access them more easily. Furthermore, researchers and practitioners can use our database as well as the analyses we made based on the data for their purpose. Because we deliver the computer scripts that we used in our analysis, our study can easily be reproduced in the future to investigate the dynamics of the P2P SCC market.
APA:
Chasin, F., von Hoffen, M., Cramer, M., & Matzner, M. (2017). Peer-to-peer sharing and collaborative consumption platforms: a taxonomy and a reproducible analysis. Information Systems and E-Business Management, 10257, 1-33. https://doi.org/10.1007/s10257-017-0357-8
MLA:
Chasin, Friedrich, et al. "Peer-to-peer sharing and collaborative consumption platforms: a taxonomy and a reproducible analysis." Information Systems and E-Business Management 10257 (2017): 1-33.
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