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Prosocial exchange systems: Nonreciprocal giving, lending, and skill-sharing.

Authors :
Harvey, John
Smith, Andrew
Golightly, David
Goulding, James
Gallage, H.P. Samanthika
Source :
Computers in Human Behavior. Jun2020, Vol. 107, pN.PAG-N.PAG. 1p.
Publication Year :
2020

Abstract

Prosocial exchange systems support cooperation and exchange in support of more sustainable forms of consumption. While often assumed that exchanges within such systems are reciprocal, it remains unproven as to what extent reciprocity occurs. This study uses data from a live service – Streetbank.com - to present an analysis of direct and indirect reciprocal relationships (for interactions of giving, lending, and skillsharing) over 4 and half years. The dataset contains behavioural data relating to 5053 acts of offline non-monetary exchange. The analysis categorised different forms of exchange that took place – giving, lending, and skill sharing. These exchanges were then analysed for direct (one-to-one) and indirect reciprocity (chains of three or more users). The results show that instances of reciprocity are rare, and when present often span more than one type of exchange. The conclusion is that reciprocity cannot be assumed to be the norm in prosocial exchange systems. Practically, design and deployment should not be predicated on reciprocity. Furthermore, any means to encourage reciprocity should make patterns of exchange visible, and do so across hybrid forms of exchange. • Direct and indirect reciprocity between users of a popular prosocial exchange system are examined. •Reciprocal relationships are rare (1.58%) across three forms of prosocial behaviour (giving, lending, and skill-sharing). •Results challenge the idea that prosocial exchange is motivated and sustained through 'generalised reciprocity'. •Network analysis reveals users interact through fragmented chains of dyads rather than channels for indirect reciprocity. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
07475632
Volume :
107
Database :
Academic Search Index
Journal :
Computers in Human Behavior
Publication Type :
Academic Journal
Accession number :
142597828
Full Text :
https://doi.org/10.1016/j.chb.2020.106268