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Cited by 260

The DOI matches its Crossref record; 21 of the 21 references it cites were found in a registry or an index.

Understanding collaborative consumption: Test of a theoretical model

Open access
Barnes, Stuart J., Mattsson, Jan·2017·Technological Forecasting and Social Change
DOI 10.1016/j.techfore.2017.02.029
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Abstract

Abstract Collaborative consumption websites have enabled consumers to focus on shared access to products rather than owning them. This study aims at developing a comprehensive theoretical model to explain consumer outcomes for collaborative consumption. It develops and tests a structural equation model using partial least squares path modelling and survey data collected from a car-sharing website. The results suggest that consumer intentions to rent are driven primarily by perceived economic, environmental and social benefits through the mediator of perceived usefulness, and enjoyment, in turn driven by sense of belonging to the sharing community. Interestingly, social influence did not play a role. When making word-of-mouth recommendations, in addition to these factors, consumers also take website trust into account, underpinned by the structural assurances of the website. The paper rounds off further implications of the research for theory and practice.

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Metadata

Authors
Barnes, S. J., & Mattsson, J.
Venue
Technological Forecasting and Social Change
Publisher
Elsevier BV
Published
2017-05
Volume
118
Pages
281-292
ISSN
0040-1625 (ISSN-L)
DOI
10.1016/j.techfore.2017.02.029
OpenAlex
W2594482581
Cited by
260
References
21
FWCI
37.13
Type
journal article
Language
en
Open access
green

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CoChat. (2026). Citation check: Understanding collaborative consumption: Test of a theoretical model. https://app.cochat.ai/papers/10.1016/j.techfore.2017.02.029
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Barnes, S. J., & Mattsson, J. (2017). Understanding collaborative consumption: Test of a theoretical model. Technological Forecasting and Social Change. https://doi.org/10.1016/j.techfore.2017.02.029

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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.