Shahriar Tanvir Hasan Murshed

Communication network dynamics during organizational crisis

Communication network is a personal or professional set of relationships between individuals or organizations. In other words, it is a pattern of contacts which are created due to the flow of information among the participating actors. The flow of information establishes various types of relationships among the participating entities. These relationships eventually form an overall pattern that could form a gestalt of the total structure within organizational context. In this paper, we analyze the changing communications structure in order to investigate the patterns associated with the final stages of organizational crisis. Organizational crisis has been defined as organizational mortality, organizational death, organizational exit, bankruptcy, decline, retrenchment and failure to characterize various forms of organizational crisis. We draw on theoretical perspectives on organizational crisis proposed by social network analysts and other sociologists to test 5 key propositions on the changes in the network communication structure associated with organizational crisis: (1) a few actors, who are prominent or more active, will become central during the organizational crisis period; (2) reciprocity within the organizational communication network will increase during crisis period; (3) organizational communication network becomes less transitive as organizations experience crisis; (4) number of cliques increases in a communication network as organizations are going through crisis; and (5) communication network becomes increasingly centralized as organizations go through crisis.

Exploring temporal communication through social networks

The dissemination of information in social networks and the relative effect of ICT (Information and Communications Technology) use has long been an interesting area of study in the field of sociology, human computer interaction and computer supported cooperative work. To date, a lot of research has been conducted regarding an actors mobile phone usage behavior while disseminating information within a mobile social network. In this study, we explore the structured network position of individuals using mobile phone and their ability to disseminate information within their social network. Our proposition is that an actors ability to disseminate information within a social group is affected by their structural network position. In this paper, we determine an actors structural network position by four different measures of centrality--(i) degree, (ii) closeness, (iii) betweenness, and (iv) eigenvector centrality. We analyse the Reality Mining dataset, which contains mobile phone usage data over a 9 month period for exploring the association between the structural positions of different actors in a temporal communication. We extract relational data to construct a social network of the mobile phone users in order to determine the association between their position in the network and their ability to disseminate information. The following questions form the basis for this study: Does information dissemination capability of an actor reflect their structural position within a social network? How do different measures of centrality associate with the information dissemination capability of an actor? Are highly central actors able to disseminate information more effectively than those who have a lower central position within a social network?

Static versus dynamic topology of complex communications network during organizational crisis

The significance of temporal changes in the topology of organizational communication networks during a crisis is studied using static and dynamic social network analysis (SNA). In static SNA, the network of interactions made during an entire data collection period is studied. For dynamic SNA, shorter segments of network data are used in the analysis. Using measures of degree centrality and core-periphery analysis, the prominence of actors is characterized and compared in the aggregate network (i.e., using static topology) and in daily networks (i.e., using dynamic topology) of a complex email network in a large organization during crisis. We show that while static typology cannot capture the network behavior completely, there are particular situations where the additional description provided by dynamic analysis is not significant. The limitations of dynamic topological SNA are discussed and we stress the importance of associating function with network structure in moving towards a more informative dynamical description.

Transitivity, hierarchy and reciprocity of organizational communication network during crisis

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 networ...

Organizational Communication Networks and its Structural Changes Correlates to Organizational Disintegration

Email networks in contemporary organizations are fairly representative of the underlying communications networks. We show that changes in communication networks have implications for studying organization disintegration. In this paper, we analyzed the changing communication network structure at Enron Corporation during the period of its disintegration (2000-2001). Our goal was to understand how communication patterns and structure were affected by organizational disintegration. Drawing on (social) network disintegration theory, we tested several propositions using the Enron email corpus: 1) Number of cliques increases 2) Communication network becomes increasingly centralized, and 3) Connectedness among the top management executives increases, as organizations move towards disintegration. The results of the analyses and their implications indicate that during organizational disintegration process there are: higher level of clique activities, tendency toward greater decentralization, and increased connectivity among top management.

Exploring interaction patterns of cohesive subgroups during organizational disintegration

We suggest that changes in the interactions patterns of communications networks have implications for exploring the phases of organisational disintegration. We develop a set of criteria for measuring the phases of organisational disintegration and apply that to Enron e-mail communications data for testing our preliminary assumptions. We explore the roles of cohesive subgroups (or cliques) and the changes in the composition of clique structure during organisational disintegration. Our preliminary assumptions that drive the work are as follows: (i) the number of cliques increase during organisational disintegration; (ii) structural changes occur in the composition of clique structure and its membership (i.e., we see more contributing actors for the disintegration state clique structure than during the normal state of an organisation).

Exploring structural changes of the communications network during organizational crisis

In this study, we explore patterns of organizational communication during normal state and crisis state using e-mail communications data. We apply social networks analysis (SNA) to understand the communication behavior and its structural changes during crisis from a real-world organization’s communication data. By applying SNA, we first analyze the changes of social network structures from normal organizational state to crisis state. Second, we explore the changes of different positions or roles of the organizational communication networks during the crisis. Third, we apply measures of centrality (i.e., degree, betweenness, and closeness) for studying how different structural changes in social networks correlate to organizational hierarchy during normal and crisis state.