Exponential random graph modeling of communication networks to understand organizational crisis

Hamra, Jafar; Uddin, Shahadat; Hossain, Liaquat

doi:10.1145/1982143.1982163

Cited by 7 publications

(7 citation statements)

References 20 publications

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“…This theory-driven modelling approach also allows to test the significance of structural parameters in the process of the formation of a given network [18,49]. For instance, a given cost effective PCN may be explored using ERG model to examine what micro structures play a statistically significant role in the development process of this PCN.…”

Section: Methodsmentioning

confidence: 99%

“…In modelling structures of PCN, this study uses the Exponential Random Graph (ERG) model which is a probabilistic model and has been utilised extensively in the social science literature to study the dynamics of network formation from underlying locally prominent micro structures such as 2-star, 3-star, triangle and so on [15]. Although most of the studies about ERG focus on building the theory of ERG models, recently researchers have applied ERG models in practice, such as, to understand whether external connections beyond the department are important to the understanding of the departmental structure of an Australian Government Organisation [16], to explore the dynamics of biological networks [17] and to examining the communication dynamics of networks under stress [18]. This study considers hospitalisation cost and readmission rate as surrogate measures for the effectiveness and efficiency of physician collaborations.…”

Section: Introductionmentioning

confidence: 99%

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A study of physician collaborations through social network and exponential random graph

Uddin

Hossain

Hamra

et al. 2013

BMC Health Serv Res

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BackgroundPhysician collaboration, which evolves among physicians during the course of providing healthcare services to hospitalised patients, has been seen crucial to effective patient outcomes in healthcare organisations and hospitals. This study aims to explore physician collaborations using measures of social network analysis (SNA) and exponential random graph (ERG) model.MethodsBased on the underlying assumption that collaborations evolve among physicians when they visit a common hospitalised patient, this study first proposes an approach to map collaboration network among physicians from the details of their visits to patients. This paper terms this network as physician collaboration network (PCN). Second, SNA measures of degree centralisation, betweenness centralisation and density are used to examine the impact of SNA measures on hospitalisation cost and readmission rate. As a control variable, the impact of patient age on the relation between network measures (i.e. degree centralisation, betweenness centralisation and density) and hospital outcome variables (i.e. hospitalisation cost and readmission rate) are also explored. Finally, ERG models are developed to identify micro-level structural properties of (i) high-cost versus low-cost PCN; and (ii) high-readmission rate versus low-readmission rate PCN. An electronic health insurance claim dataset of a very large Australian health insurance organisation is utilised to construct and explore PCN in this study.ResultsIt is revealed that the density of PCN is positively correlated with hospitalisation cost and readmission rate. In contrast, betweenness centralisation is found negatively correlated with hospitalisation cost and readmission rate. Degree centralisation shows a negative correlation with readmission rate, but does not show any correlation with hospitalisation cost. Patient age does not have any impact for the relation of SNA measures with hospitalisation cost and hospital readmission rate. The 2-star parameter of ERG model has significant impact on hospitalisation cost. Furthermore, it is found that alternative-k-star and alternative-k-two-path parameters of ERG model have impact on readmission rate.ConclusionsCollaboration structures among physicians affect hospitalisation cost and hospital readmission rate. The implications of the findings of this study in terms of their potentiality in developing guidelines to improve the performance of collaborative environments among healthcare professionals within healthcare organisations are discussed in this paper.

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Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

A study of physician collaborations through social network and exponential random graph

Uddin

Hossain

Hamra

et al. 2013

BMC Health Serv Res

Self Cite

View full text Add to dashboard Cite

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“…Using ERG Models Hamra et al [16], for instance, investigated the changing communication network structure at Enron Corporation during the period of its disintegration for identifying structural drivers of the formation of such networks. Schweinberger et al [17] have studied the inter-organizational network that emerged in response to the September 11, 2001 attacks by introducing ERG Models which can answer the substantive questions of interest while being as simple and parsimonious as possible.…”

Section: Soft-target Organisationmentioning

confidence: 99%

Exponential random graph modeling of emergency collaboration networks

Hossain

Hamra

Wigand

et al. 2015

Knowledge-Based Systems

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“…The communication network becomes more dynamic (Hamra et al, 2011;Uddin et al, 2012), and the static topology of network analysis cannot capture the complete dynamicity of the network during crisis (Uddin et al, 2011a). Krackhardt and Stern (1988) found evidence that the structure of communication patterns in crisis situations is an important contributor to organizational success.…”

Section: Transitivity Hierarchy and Reciprocitymentioning

confidence: 99%

Transitivity, hierarchy and reciprocity of organizational communication network during crisis

Murshed

Uddin

Hossain

2015

International Journal of Organizational Analysis

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Purpose – This paper aims to explore changes in communication networks during organizational crisis. In the literature, various terms such as organizational mortality, organizational death, bankruptcy, decline, retrenchment and failure have been used to characterize different forms and facets of organizational crisis. Communication network studies have typically focussed on nodes (e.g. individuals or organizations), relationships between those nodes and subsequent affects of these relationships upon the network as a whole. Email networks in contemporary organizations are fairly representative of the underlying communication networks. Design/methodology/approach – The changing communication network structure at Enron Corporation during the crisis period (2000-2001) has been analyzed. The goal is to understand how communication patterns and structures are affected by organizational crisis. Drawing on communication network crisis and group behaviour theory, three propositions are tested: communication network becomes increasingly transitive as organizations experience crisis; communication network becomes less hierarchical as organizations are going through crisis; and communication network becomes more reciprocal as organizations are going through crisis. Findings – In this research analysis, the support of these three propositions was noticed. The results of tests and their implications are discussed in this paper. Originality/value – This study builds on an emerging stream of research area that applies social network analysis to organizational interaction data to study various questions related to organizational change and disintegration. These findings could help managers in designing an effective approach to monitor regular functionalities of their organizations.

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Exponential random graph modeling of communication networks to understand organizational crisis

Cited by 7 publications

References 20 publications

A study of physician collaborations through social network and exponential random graph

A study of physician collaborations through social network and exponential random graph

Exponential random graph modeling of emergency collaboration networks

Transitivity, hierarchy and reciprocity of organizational communication network during crisis

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