Knowledge sharing in organizations: A Bayesian analysis of the role of reciprocity and formal structure

This is the author accepted manuscript. The final version is available from the publisher via the DOI in this recordWe examine the conditions under which knowledge embedded in advice relations is likely to reach across intraorganizational boundaries and be shared between distant organizational members. We emphasize boundary-crossing relations because activities of knowledge transfer and sharing across subunit boundaries are systematically related to desirable organizational outcomes. Our main objective is to understand how organizational and social processes interact to sustain the transfer of knowledge carried by advice relations. Using original fieldwork and data that we have collected on members of the top management team in a multiunit industrial group, we show that knowledge embedded in task advice relations is unlikely to crosscut intraorganizational boundaries, unless advice relations are reciprocated, and supported by the presence of hierarchical relations linking managers in different subunits. The results we report are based on a novel Bayesian Exponential Random Graph Models (BERGMs) framework that allows us to test and assess the empirical value of our hypotheses while at the same time accounting for structural characteristics of the intraorganizational network of advice relations. We rely on computational and simulation methods to establish the consistency of the network implied by the model we propose with the structure of the intraorganizational network that we actually observed

The analysis of multilevel networks in organizations: models and empirical tests

This is the author accepted manuscript. The final version is available from the publisher via the DOI in this recordStudies of social networks in organizations confront analytical challenges posed by the multilevel effects of hierarchical relations between organizational subunits on the presence or absence of informal network relations among organizational members. Conventional multilevel models may be usefully adopted to control for generic forms of non-independence between tie variables defined at multiple levels of analysis. Such models, however, are unable to identify the specific multilevel dependence mechanisms generating the observed network data. This is the basic difference between multilevel analysis of networks and the analysis of multilevel networks. The aim of this article is to show how recently derived multilevel exponential random graph models (MERGMs) may be specified and estimated to address the problems posed by the analysis of multilevel networks in organizations. We illustrate our methodological proposal using data on hierarchical subordination and informal communication relations between top managers in a multiunit industrial group. We discuss the implications of our results in the broader context of current theories of organizations as connected multilevel systems.Swiss National Science Foundation (SNSF

Fast maximum likelihood estimation via equilibrium expectation for large network data

This is the final version. Available from the publisher via the DOI in this record.A major line of contemporary research on complex networks is based on the development of statistical models that specify the local motifs associated with macro-structural properties observed in actual networks. This statistical approach becomes increasingly problematic as network size increases. In the context of current research on efficient estimation of models for large network data sets, we propose a fast algorithm for maximum likelihood estimation (MLE) that affords a significant increase in the size of networks amenable to direct empirical analysis. The algorithm we propose in this paper relies on properties of Markov chains at equilibrium, and for this reason it is called equilibrium expectation (EE). We demonstrate the performance of the EE algorithm in the context of exponential random graph models (ERGMs) a family of statistical models commonly used in empirical research based on network data observed at a single period in time. Thus far, the lack of efficient computational strategies has limited the empirical scope of ERGMs to relatively small networks with a few thousand nodes. The approach we propose allows a dramatic increase in the size of networks that may be analyzed using ERGMs. This is illustrated in an analysis of several biological networks and one social network with 104,103 nodes.Swiss National Science Foundatio

Investigating the temporal dynamics of inter-organizational exchange: patient transfers among Italian hospitals

Previous research on interaction behavior among organizations (resource exchange, collaboration, communication) has typically aggregated records of those behaviors over time to constitute a ‘network’ of organizational relationships. We instead directly study structural-temporal patterns in organizational exchange, focusing on the dynamics of reciprocation. Applying this lens to a community of Italian hospitals during the period 2003-2007, we observe two mechanisms of interorganizational reciprocation: organizational embedding and resource dependence. We flesh out these two mechanisms by showing how they operate in distinct time frames: Dependence operates on contemporaneous exchange structures, whereas embedding develops through longer-term historical patterns. We also show how these processes operate differently in competitive and noncompetitive contexts, operationalized in terms of market differentiation and geographic space. In noncompetitive contexts, we observe both logics of reciprocation, dependence in the short term and embedding over the long term, developing into patterns of generalized exchange in this population. In competitive contexts, we observe neither form of reciprocation and instead observe the microfoundations of status hierarchies in exchange

Implementasi Penetapan Pajak Kendaraan Bermotor Ubah Bentuk pada Samsat Kabupaten Timor Tengah Selatan

The problem in doing the majoring in SAMSAT of sub-province of Timor Tengah Selatan can be solved by using information system. In a month SAMSAT of sub-province of Timor Tengah have served 3.131 taxpayer, that means for a day SAMSAT of sub-province of Timor Tengah served approximately reach 150 taxpayer and total vehicles in registration is 39.492 vehicles. The system that is developed to maintain vehicles data, types of vehicle data, vehicles brands data, dumps data, vehicles price data, registration data, and to count vehicles tax determining rightly dan quickly and can gain the report of all registration data, specific report of the vehicles, specific report of vehicles tax determining and receipt tax payments of vehicles transform. This system capable to answered the hypothesis H0 about contentment of service with satisfaction level more than 70% viz 78%.     &nbsp

The co-evolution of organizational and network structure: The role of multilevel mixing and closure mechanisms

We present a dynamic multilevel framework for analyzing the mutual dependence of change in interorganizational networks and internal organizational structure. Change occurring at the former (interorganizational) level involves decisions to change the portfolio of network ties to external partners. Change occurring in the latter (intraorganizational) level involves decisions to change the portfolio of internal activities. We estimate a recently derived class of stochastic actor-oriented models (SAOMs) that we adopt and adapt to specify how decisions to change internal portfolios of activities and external portfolios of partners are connected by theoretically derived multilevel mixing and closure mechanisms that link organizational and network structures. We show that statistical models for multilevel networks reproduce with high fidelity the structural regularities observed in the distribution of: (i) activities within organizations; (ii) network ties between organizations, and (iii) knowledge available in the organizational field. We discuss the implications of the study for theory development, and for empirical research on interorganizational and other kinds of multilevel networks