Guido Conaldi

Dynamic Models of Affiliation and the Network Structure of Problem Solving in an Open Source Software Project

Two-mode networks are used to describe dual patterns of association between distinct social entities through their joint involvement in categories, activities, issues, and events. In empirical organizational research, the analysis of two-mode networks is typically accomplished either by (a) decomposition of the dual structure into its two unimodal components defined in terms of indirect relations between entities of the same kind or (b) direct statistical analysis of individual two-mode dyads. Both strategies are useful, but neither is fully satisfactory. In this article, the authors introduce newly developed stochastic actor-based models for two-mode networks that may be adopted to redress the limitations of current analytical strategies. The authors specify and estimate the model in the context of data they have collected on the dual association between software developers and software problems observed during a complete release cycle of an open source software project. The authors discuss the general methodological implications of the models for organizational research based on the empirical analysis of two-mode networks.

Quality of Care and Interhospital Collaboration: A study of Patient Transfers in Italy

Objectives:We examine the dynamics of patient-sharing relations within an Italian regional community of 35 hospitals serving approximately 1,300,000 people. We test whether interorganizational relations provide individual patients access to higher quality providers of care. Research Design and Methods:We reconstruct the complete temporal sequence of the 3461 consecutive interhospital patient-sharing events observed between each pair of hospitals in the community during 2005–2008. We distinguish between transfers occurring between and within different medical specialties. We estimate newly derived models for relational event sequences that allow us to control for the most common forms of network-like dependencies that are known to characterize collaborative relations between hospitals. We use 45-day risk-adjusted readmission rate as a proxy for hospital quality. Results:After controls (eg, geographical distance, size, and the existence of prior collaborative relations), we find that patients flow from less to more capable hospitals. We show that this result holds for patient being shared both between as well as within medical specialties. Nonetheless there are strong and persistent other organizational and relational effects driving transfers. Conclusions:Decentralized patient-sharing decisions taken by the 35 hospitals give rise to a system of collaborative interorganizational arrangements that allow the patient to access hospitals delivering a higher quality of care. This result is relevant for health care policy because it suggests that collaborative relations between hospitals may produce desirable outcomes both for individual patients, and for regional health care systems.

Modeling Relational Events: A Case Study on an Open Source Software Project

Sequences of relational events underlie much empirical research on organizational relations. Yet relational event data are typically aggregated and dichotomized to derive networks that can be analyzed with specialized statistical methods. Transforming sequences of relational events into binary network ties entails two main limitations: the loss of information about the order and number of events that compose each tie and the inability to account for compositional changes in the set of actors and/or recipients. In this article, we introduce a newly developed class of statistical models that enables researchers to exploit the full information contained in sequences of relational events. We propose an extension of the models to cater for sequences of relational events linking different sets of actors. We illustrate the empirical application of relational event models in the context of a free/open source software project with the aim to explain the level of effort produced by contributors to the project. We offer guidance in the interpretation of model parameters by characterizing the social processes underlying organizational problem solving. We discuss the applicability of relational events models in organizational research.

The dual network structure of organizational problem solving: A case study on open source software development

Abstract We reconstruct the dual network structure generated by the association between 72 contributors and 737 software bugs engaged during a full development cycle of the free/open source software project Epiphany. Estimates of structural parameters of Exponential Random Graph Models for two-mode networks reveal the structural logics shaping activities of collaborative problem solving. After controlling for contributor-specific and software bug-specific characteristics, we find that contributors (“problem solvers”) tend to distribute their activity over multiple software bugs. At the same time, however, we find that software bugs (“problems”) tend not to share multiple contributors. This dual tendency toward de-specialization and exclusivity is sustained by specific local network dependencies revealed by our analysis which also suggests possible organizational mechanisms that may be underlying the puzzling macro-structural regularities frequently observed, but rarely explained, in the production of open source software. By combining these mechanisms with the influence of contributors characterized by different levels of involvement in the project, we provide micro-level evidence of structural interdependence between “core” and “peripheral” members identified exclusively on the basis of their individual level of contribution to the project.

Comparing Fields of Sciences: Multilevel Networks of Research Collaborations in Italian Academia

In this chapter we model the multilevel structure of scientific work, looking at social networks of collaborations between scientists, and at how these networks are embedded in disciplinary and organizational levels. Once the relational structure of scientific collaboration is described, we look at the role that it plays in scholars’ successes. We adopt the linked-design approach to analyse the local system of public funding to academic disciplines in Italy using bipartite networks across disciplinary areas. We thus analyse the mechanisms that lie beyond the structure of research project collaborations in Italian academia. We find that individual attributes (being a national coordinator, a full professor, and having being promoted) play a role in getting funded. It is however the position of being a broker across otherwise unconnected research groups that makes a difference in the total amount of funding received by a scientist over the years under analysis, in some cases combined with egonet closure. These results confirm the importance of looking at individual network properties when analyzing scientific collaborations. Leadership is a characteristic that seems to be related both to career achievements (becoming a full professor) and to the capability of attracting multiple research groups for scientific collaborations.

Organized Anarchies and the Network Dynamics of Decision Opportunities in an Open Source Software Project

When considered as organized solutions to problems of provision of public goods, Free/Open Source Software (F/OSS) productions share a number of their defining features with the organized anarchies described by Cohen, March and Olsen in their “Garbage Can Model” (GCM). The open and voluntary contribution of software developers creates constant fluctuations in levels of attention and an extremely fluid participation. The lack of predefined hierarchical access to organizational problems determines a fundamental uncertainty about how collective goals may be linked to individual activities, and in how responsibilities and tasks may be allocated efficiently within the project. Finally, the complexity involved in the collective production of tens of thousands of lines of computer code without explicit coordination creates a situation of technological ambiguity supported by a radically decentralized activity of organizational problem finding and problem solving. In this paper we take these broad similarities as point of departure to specify an empirical model that captures some of the garbage can properties of organizational problem-solving activities in the context of a specific F/OSS project followed throughout a complete release cycle. We examine the interconnected system of individual decisions emerging from problem-solving activities performed by the 135 contributors involved in the F/OSS project on the 719 software bugs reported during the period of observation. We treat the evolving two-mode network produced by encounters between carriers of organizational solutions (contributors) and organizational problems (software bugs) as a dynamic opportunity structure that constrains and enables organizational decision making. We document how stable local configurations linking problems and solutions are induced by – and at the same time sustain – decentralized problem-solving activities with meaningful self-organizing properties.

At the core of innovation: network reconfiguration during radical and incremental innovation episodes in an open source software project

Innovation is crucial for competitive advantage of firms. The innovation model adopted by open source software projects has therefore attracted the attention of several managers. Consequently, private firms are increasingly supporting open source communities. However, the heterogeneous results obtained by open source software projects call for a deeper understanding of the organisational factors sustaining the innovativeness of these communities. We contribute to fill this gap through a case study that investigates which knowledge networks connecting developers inside open source communities support radical and incremental innovation. Our findings show that two distinguishable network configurations are associated with the two types of innovation. Particularly the presence of a single core of knowledge interaction involving the developers actually implementing the innovative code appears to be a requirement for radical innovation.

The Meso-level Structure of F/OSS Collaboration Network: Local Communities and Their Innovativeness

Social networks in Free/Open Source Software (F/OSS) have been usually analyzed at the level of the single project e.g., [6], or at the level of a whole ecology of projects, e.g., [33]. In this paper, we also investigate the social network generated by developers who collaborate to one or multiple F/OSS projects, but we focus on the less-studied meso-level structure emerging when applying to this network a community-detection technique. The network of ‘communities’ emerging from this analysis links sub-groups of densely connected developers, sub-groups that are smaller than the components of the network but larger than the teams working on single projects. Our results reveal the complexity of this meso-level structure, where several dense sub-groups of developers are connected by sparse collaboration among different sub-groups. We discuss the theoretical implications of our findings with reference to the wider literature on collaboration networks and potential for innovation. We argue that the observed empirical meso-structure in F/OSS collaboration network resembles that associated to the highest levels of innovativeness.

Flat for the Few, Steep for the Many: Structural Cohesion and Rich-Club Effect as Measures of Hierarchy and Control in FLOSS Communities

A discrepancy exists between the emphasis posed by practitioners on decentralized and non-hierarchical communication in Free Libre/Open Source Software FLOSS communities and empirical evidence of their hierarchical structure. To explain this paradox, it is hypothesized firstly that in FLOSS communities local sub-groups exist and are less hierarchical, more decentralized than the whole social network. Secondly, it is hypothesized that the bulk of communication exchanges taking place in the community happens inside local sub-groups formed by the most active community members. The recollection that practitioners have of FLOSS communities to which they participate would then be influenced by the position that they occupy inside those sub-groups. A measure of structural cohesion based on network node connectivity is proposed as an effective method to test whether FLOSS communication networks can be decomposed in nested hierarchies of progressively less centralized sub-groups. The recently introduced measure of weighted rich-club effect is adopted to test for the tendency of the most active community members to control communication by interacting more intensely with each other than with other members of the network. Results from a case study that are consistent with the hypotheses are presented and discussed.