Alessandro Lomi

Manufacturing Relations: An Empirical Study of the Organization of Production Across Multiple Networks

Organizational communities present two generic features that are recurrently documented in empirical studies, but only imperfectly accounted for in current models of interorganizational relations. The first is the tendency of participant organizations to construct observed macrostructure locally, through relational activities that involve only a small subset of possible network ties. The second is the tendency for different types of ties to overlap, concatenate, and induce a variety of local structuresor relational motifsacross network domains. A critical task in the analysis of organizational communities is to specify appropriate local dependence structures across multiple networks, starting from detailed observation of dyadic interaction among participants. In this paper we illustrate one way in which this analytical task might be accomplished in the context of a study of interorganizational networks. We use data that we have collected on different types of relationships among 106 organizations, located in Southern Italy, involved in the production of means of transportation to test hypotheses about patterns of local network ties and paths across multiple networks. Our empirical analysis is guided by the general claim that the formation of network ties is subject to endogenous and exogenous processes. We specify statistical models for random graphs that allow us to examine this claim, and to formulate and test specific hypotheses about the form that such network-based processes might take. The results that we report provide clear empirical support for the relational motifs implied by our hypotheses. We also find strong empirical support for the proposition that interorganizational dependencies extend across multiple networks.

Interacting Locally and Evolving Globally: A Computational Approach to the Dynamics of Organizational Populations

We present a computational model of organizational evolution according to which the global dynamics of organizational populations emerge from simple rules of local interaction among individual orga...

Adaptive Learning in Organizations: A System Dynamics-Based Exploration

This paper employs a system dynamics-based framework to examine the limitations of experiential learning as a guide for decision-making in organizations. This framework departs from the more traditional approach to modelling experiential learning processes in organizations by emphasizing the systematic interaction between decision-making agents and their environments, rather than the effects of varying degrees of noise on performance. We present the results of a series of computer simulations that examined the consequences of adaptive learning in organizations by concentrating explicitly on the link between individual decisions and the system-level consequences generated by the interaction of individual choices. The results show that experience is a poor basis for learning primarily because the understanding of structural relations between individual actions and their aggregate consequences is confounded by nonlinear dynamics, time delays, and misperception of feedback.

Representing change: a system model of organizational inertia and capabilities as dynamic accumulation processes

Abstract Using system dynamics models and methods, in this paper we suggest a feedback representation of the ecological theory of organizational inertia and change. The paper pursues two main objectives related to the representation and specification of organizational theories. The first is to identify and specify dynamic elements that are left implicit in the original theoretical narrative. The second objective is to explore conceptual connections between core features of ecological and evolutionary theories of organizations that are typically believed to lead to incommensurable empirical models. We perform a series of simple simulation experiments to explore the behavioral consequences of our representations and identify issues that future research on dynamics of organizations may help to clarify. The main insight offered by our model-based exploration is that organizational inertia––defined as the tendency of formal organizations to resist change––and organizational capabilities––defined as the ability of organizations to innovate and reconfigure their internal resources––should be represented as paired concepts, each understandable only in terms of the other.

Relational collaboration among spatial multipoint competitors

The presence of network ties between multipoint competitors is frequently assumed but rarely examined directly. The outcomes of multipoint competition, therefore, are better understood than their underlying relational mechanisms. Using original fieldwork and data that we have collected on an interorganizational network of patient transfer relations within a regional community of hospitals, we report and interpret estimates of Exponential Random Graph Models (ERGM) that specify the probability of observing network ties between organizations as a function of the degree of their spatial multipoint contact. We find that hospitals competing more intensely for patients across multiple geographical segments of their market (spatial multipoint competitors) are significantly more likely to collaborate. This conclusion is robust to alternative explanations for the formation of network ties based on organizational size differences, resource complementarities, performance differentials, and capacity constraints. We show that interorganizational networks between spatial multipoint competitors are characterized by clear tendencies toward clustering and a global core-periphery structure arising as consequences of multiple mechanisms of triadic closure operating simultaneously. We conclude that the effects of competition on the structure of interorganizational fields depends on how markets as physical and social settings are connected by cross-cutting network ties between competitors.

Things Change: Dynamic Resource Constraints and System-Dependent Selection in the Evolution of Organizational Populations

An extensive empirical literature has demonstrated the existence of density-dependent selection in organizational vital rates. This research has also shown that historical trajectories followed by organizational populations only partly conform to the predictions of the original model. Inconsistencies with the models predictions prompt a series of questions: Why do organizational populations suddenly collapse after reaching a peak? Why do organizational populations oscillate after collapsing? What causes extinction of organizational forms? To address these questions, scholars have proposed a variety of modifications to the original model of density dependence. All have merit, but none is completely satisfying. The main objective of this study is to narrow the gap between theories, models, and observed historical trajectories by identifying a unitary analytical framework that can account for the variety of empirical trajectories typically followed by mature organizational populations. The model that we present is based on the hypothesis of system-dependent selection, according to which patterns of resource availability are produced by processes that are partly endogenous to organizational populations. The main analytical insight of the study is that under conditions of dynamic resource constraints introduced by system-dependent selection, the presence of population-level inertia leads to a rich variety of historical trajectories during population maturity. We show that this result holds in the absence of any particular assumption about the microstructure of organizational populations. Possible trajectories include sustained oscillations, resurgence, and extinction.

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.

Getting There: Exploring the Role of Expectations and Preproduction Delays in Processes of Organizational Founding

Because of preproduction delays, environmental conditions at founding cannot explain organization-building decisions taken earlier. As a consequence, environmental conditions at founding cannot explain organizational founding. Future levels of resource availability may be estimated, but not directly observed by potential entrepreneurs at the time at which they decide to enter preproduction. In this paper, we take these considerations as our starting point to build a dynamic feedback model of organization founding. According to the model, organizational founding is driven by expectations that entrepreneurs form about future levels of resources and, only indirectly, by current levels of population density. We explore the behavior of the model under a variety of experimental conditions. We show that the qualitative behavior of the model is consistent with studies that have linked the duration of preproduction stage with fluctuations in density during population maturity. Our simulation analyses sustains three main conclusions. First, historical trajectories of organizational populations that are consistent with empirical observations may be produced by mechanisms that are not directly dependent on density. Second, alternative hypotheses about how expectations are formed produce qualitatively different historical trajectories of density. Third, fluctuations in numbers of organizations are linked to specific aspects of individual organization-building decisions.

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.

Passing the buck in the garbage can model of organizational choice

We reconstruct Cohen, March and Olsen’s Garbage Can model of organizational choice as an agent-based model. In the original model, the members of an organization can postpone decision-making. We add another means for avoiding making decisions, that of buck-passing difficult problems to colleagues. We find that selfish individual behavior, such as postponing decision-making and buck-passing, does not necessarily imply dysfunctional consequences for an organization.The simulation experiments confirm and extend some of the most interesting conclusions of the Garbage Can model: Most decisions are made without solving any problem, organization members face the same old problems again and again, and the few problems that are solved are generally handled at low hierarchical levels. These findings have an implication that was overseen in the original model, namely, that top executives need not be good problem-solvers.