Multimode and Multilevel: Vertical Dimension in Historical and Literary Networks

In the field of global history, especially when it comes to « histoire croisée », the use of metaphors describing the vertical organization of a society, its structuration into layers or into overlapping systems, is common. The temptation to use a second metaphor, calling everything a “network”, is also very important in this domain, whose objects of study are often transnational organizations with multiple branches, intertwined within umbrella organizations, sharing board members and including several levels of secretariats and subcommittees (Grandjean 2017). However, the use of these images is not limited to historical studies, since we use the same vocabulary in other disciplines to describe social situations or textual structures. When we go beyond the metaphor to develop a formal analysis, we often produce multigraphs who, because they simultaneously express horizontal and vertical relationships, are generally unsuitable for the analysis (and visualisation, except in very simple cases). If the “exploratory” dimension of social network analysis – and especially the fact that its display is relatively subjective – is often a subject of criticism, we propose here to play with the visual representation to show precisely how an original modelling can improve the reading of complex graphs, and helping to restore a “morphological” (Moretti 1999, 68) information where disorder seems to prevail. Based on two examples from archives mapping and theatre character networks, this paper proposes a reflection on the different ways to take account of verticality in graphs. In particular, we are developing a way to impose a macro-structure to a network, allowing a two-dimensions view that reflects the hierarchical affiliations of its components. We will see that this method, by constructing a stable visual representation in time and space, helps to compare different types of relationships and/or different time states of the graph

Exponential random graph models for management research: a case study of executive recruitment

We introduce a recent development in the statistical analysis of relational data that offers rigorous discrimination of a variety of structural and behavioural effects of interest to management research. Exponential Random Graph Models (ERGMs) account for the highly interdependent nature of network data that is problematic for the predominant inferential statistical analysis used in management research. We illustrate the value of the approach with an application focused on executive recruitment by large UK firms, modelling migrations of managers among firms as a network of relationships. We find rigorous statistical support for the influences of industry origin in executive recruitment, particularly in relation to legal and accounting activities. The flexibility and sophisticated relational variables available in the models offer considerable analytical power of value to a wide range of management applications

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

Analisi e visualizzazioni delle reti in storia. L'esempio della cooperazione intellettuale della Società delle Nazioni

Traduction française de Grandjean Martin, "Analisi e visualizzazioni delle reti in storia. L’esempio della cooperazione intellettuale della Società delle Nazioni”, Memoria e Ricerca, 2, 2017, pp. 371-39

The firm’s knowledge network and the transfer of advice among corporate inventors—A multilevel network study

Knowledge networks consisting of links between knowledge elements and social networks composed of interactions between inventors both play a critical role for innovation. Taking a multilevel network approach, this study integrates research on the two types of networks and investigates how the knowledge network of a firm influences work-related interactions among its inventors. To this end, we associate inventors with specific knowledge elements in the firm’s knowledge network and examine how this association affects the inventors’ popularity and activity in a work-related advice network. Empirically, we combine survey data on 135 inventors working in a German high-tech firm with information derived from the firm’s 1031 patents. Results from multilevel exponential random graph models (ERGM) show that different dimensions of knowledge derived from the firm’s knowledge network shape the transfer of advice among inventors in unique ways. Thus, our study demonstrates how structural features of the firm’s knowledge stock influence interpersonal interactions among its inventors thereby affecting the intra-organizational diffusion of knowledge and the recombinant possibilities of the firm