Author:
Beata Łopaciuk-Gonczaryk | University of Warsaw, Faculty of Economic Sciences | Poland
The paper will examine socio-economic mechanisms operating in a Polish, non-commercial local exchange and trade system (LETS), based on community currency, and its impact on social capital formation. LETS allows, through the use of an internet platform, to extend the traditional neighbourly help to a wider group of people, and also contributes to the creation of social ties, especially if transactions include direct interpersonal interactions and are accompanied by additional events strengthening the existence of the community. Performance of peer-to-peer transaction platforms is conditioned both by technical solutions, as well as norms and preferences of their users. To some extent, those norms and preferences may be influenced and developed by social interactions connected with conducting transactions within LETS. The main focus of the study is to determine how interpersonal interactions connected with transactions within the LETS under study may influence social norms and collaboration attitudes.
Data have been obtained from the web-based platform, supporting the transactions and enabling to give recommendations. Additional information has been acquired from in-depth interviews. Data on transactions, in context of the LETS analysed, can be treated as evidences of interpersonal interactions, as most of them involve face-to-face contact and have a social component. Some users are given recommendations, which are almost in all cases enthusiastically positive (only one recommendation is negative) and look like credentials that somebody fits well into the system. Therefore they may be treated as information that the recommended user follows the system norms and suits its internal culture. Comparing the network of transactions with the data on recommendations may provide information on norms’ diffusion.
The study faces the challenge of distinguishing between influence and selection, as system users may not only influence each other while interacting but also they may be attracted into the system in the first place because of their specific views and attitudes. In order to try to solve this puzzle, evolution of the network is going to be observed, as the data cover the period from September 2012 to December 2016. During the whole period, there were in total 919 active users, 6599 transactions completed and only 446 (positive) recommendations given. There are no incentives to give recommendations, other than sense of gratitude, and as a result the number of recommendations is very small in comparison to the number of transactions. Therefore a fact of receiving recommendations by an actor in a given period is treated as a proxy attribute indicating following system norms and showing highly collaborative attitudes. This attribute’s change from period to period is supposed to be influenced by interactions with well-behaving, experienced system users in a role of providers of goods or services. Stochastic actor-based model for co-evolution of social network and individual behaviour is utilized to verify the hypothesis stated. The approach taken involves controlling the effects of endogenous network formation (reciprocity and network closure), possible selection effect (system users with good reputation will probably have high popularity as providers) and other attributes (like the fact of being a recommendation giver).