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. 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 (e.g., 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 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, as well as for regional health-care systems.

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.

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Intended beneficiaries have an undeniable relevance to regulation. However, current research has focused mainly on the two‐party relationship between rulemaking and rule‐taking. We attempt to fill this gap by exploring the formal and informal roles that beneficiaries’ intermediaries played in co‐creating European Corporate Social Responsibility (CSR) rules and associated practices between 2000 and 2017. By linking recent conceptualizations of regulatory intermediaries with the literature on critical political CSR, we offer a more dynamic and contextualized understanding of the roles of beneficiaries’ intermediaries. Specifically, we identify six micro‐dynamics through which they influenced the regulatory process. Notably, our findings highlight how the convergence of interests between three groups of beneficiaries’ intermediaries – the Non‐governmental organization–Investor–Union nexus – had a key role in reshaping CSR rules. We conclude that, in the European context, stronger and better‐coordinated beneficiaries’ intermediaries are crucial in order to achieve more effective corporate conduct regulation.

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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.

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