Network similarity and collusion
This study focuses on how collusive construction industry cartels structure their bidding patterns to increase their market shares, while preserving an illusion of competition. Using past research on the economics and social organization of bid-rigging and collusion, we examine a key issue related to similarities within bidding structures that are likely tainted by cartels. The study is empirically based on public procurement data to recreate the structure of interactions between construction industry firms in the province of Quebec (Canada) over a 12-year period (2002–2013). Cross-level multivariate analyses demonstrate...
Source: Social Networks - July 5, 2018 Category: Psychiatry & Psychology Source Type: research
Social network structure and the trade-off between social utility and economic performance
Publication date: October 2018Source: Social Networks, Volume 55Author(s): Katarzyna Growiec, Jakub Growiec, Bogumił KamińskiAbstractWe put forward a computational multi-agent model capturing the impact of social network structure on individuals’ social trust, willingness to cooperate, social utility and economic performance. Social network structure is modeled as four distinct social capital dimensions: degree, centrality, bridging and bonding social capital. Model setup draws from socio-economic theory and empirical findings based on our novel survey dataset. Results include aggregate-level comparative statics and in...
Source: Social Networks - July 5, 2018 Category: Psychiatry & Psychology Source Type: research
Homophily and prestige: An assessment of their relative strength to explain link formation in the online climate change debate
Publication date: October 2018Source: Social Networks, Volume 55Author(s): Hannah Schmid-Petri, Silke Adam, Ueli Reber, Thomas Häussler, Daniel Maier, Peter Miltner, Barbara Pfetsch, Annie WaldherrAbstractPrevious work has shown that hyperlinks reflect actors’ strategic choices; these dyadic relationships depend on the actors’ exogenous attributes (e.g., homophily) and the network’s endogenous features (e.g., prestige distribution among actors). We combine these factors as explanatory variables in different exponential random graph models (ERGMs) to assess the relative strength of prestige and homophily for the acto...
Source: Social Networks - July 5, 2018 Category: Psychiatry & Psychology Source Type: research
Mutual assent or unilateral nomination? A performance comparison of intersection and union rules for integrating self-reports of social relationships
Publication date: October 2018Source: Social Networks, Volume 55Author(s): Francis Lee, Carter T. ButtsAbstractData collection designs for social network studies frequently involve asking both parties to a potential relationship to report on the presence of absence of that relationship, resulting in two measurements per potential tie. When inferring the underlying network, is it better to estimate the tie as present only when both parties report it as present or do so when either reports it? Employing several data sets in which network structure can be well-determined from large numbers of informant reports, we examine the...
Source: Social Networks - July 5, 2018 Category: Psychiatry & Psychology Source Type: research
Measuring knowledge and experience in two mode temporal networks
Publication date: October 2018Source: Social Networks, Volume 55Author(s): Martin G. Everett, Chiara Broccatelli, Stephen P. Borgatti, Johan KoskinenAbstractTwo mode social network data consisting of actors attending events is a common type of social network data. For these kinds of data it is also common to have additional information about the timing or sequence of the events. We call data of this type two-mode temporal data. We explore the idea that actors attending events gain information from the event in two ways. Firstly the event itself may provide information or training; secondly, as co-attendees interact, they m...
Source: Social Networks - July 5, 2018 Category: Psychiatry & Psychology Source Type: research
