<abstract xmlns="http://www.w3.org/1999/xhtml"><p>This picture, produced by Julien Brailly et al. (2016) and David Schoch (2020), visualizes multilevel networks of individuals and organizations.</p></abstract>

This picture, produced by Julien Brailly et al. (2016) and David Schoch (2020), visualizes multilevel networks of individuals and organizations.


<div xmlns="http://www.w3.org/1999/xhtml"><sec id="j_connections-2019.019_s_001"><div>The upper level</div><p>This is the inter-organizational network in which the ties are economic relationships (business deals) signed at time t between companies (the nodes). The pattern represents a core-periphery structure. In the core, the more central companies (the Majors of this industry and a few other of smaller companies that managed to sign a contract with the Majors) drive the economic action (contracting). The periphery is composed of many small companies (the nodes on the outer upper circle) that did not sign any contract that year and thus find themselves isolated, as if they were watching the action from a balcony.</p><figure id="j_connections-2019.019_fig_001" fig-type="figure"><img xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="graphic/j_connections-2019.019_fig_001.jpg" src="https://sciendo-parsed.s3.eu-central-1.amazonaws.com/6471598d2b88470fbea16d63/j_connections-2019.019_fig_001.jpg?X-Amz-Algorithm=AWS4-HMAC-SHA256&amp;X-Amz-Date=20240816T225947Z&amp;X-Amz-SignedHeaders=host&amp;X-Amz-Expires=18000&amp;X-Amz-Credential=AKIA6AP2G7AKP25APDM2%2F20240816%2Feu-central-1%2Fs3%2Faws4_request&amp;X-Amz-Signature=7eb72dbf8f5c0d4f06daf365065e2485b2a132e6f915e1f292f99eb834a49839" class="mw-100"/></figure></sec><sec id="j_connections-2019.019_s_002"><div>The lower level</div><p>This is the inter-individual level in which the ties are informal discussion and personal information gathering at time <italic>t</italic>−1 between these individuals. The high density of this lower, inter-individual network represents the fact that members of competing companies talk to each other actively.</p></sec><sec id="j_connections-2019.019_s_003"><div>Vertical ties</div><p>These ties between nodes from the lower level and nodes at the upper level are affiliation ties of each individual in their organizations.</p></sec><sec id="j_connections-2019.019_s_004"><div>The empirical setting</div><p>This multilevel network was measured in the largest trade fair for television programs in Eastern Europe. In this trade fair, nodes at the upper level are companies and institutions of the global and regional television industry. They sell, buy, distribute programs, and regulate the industry. Color codes at this upper level represent the organizations composing the value chain in 2012, for example broadcasters in blue, distributors in green, independent buyers in purple, media groups in yellow, producers in brown. Nodes at the Lower level are mainly individual sales representatives, sellers and buyers of TV programs meeting at this trade fair to keep abreast of new films, series and game shows, to observe market trends and evolutions, and to discuss contracts in 2011. Sellers mainly from the USA and Western Europe come to pitch and sell their audiovisual products to regional and local buyers such as the broadcasting companies (television channels for example). The density of this inter-individual network represents the “buzz” network between these sales representatives in this trade fair, emphasizing the crucial role of cooperation among interdependent competitors (Lazega and Mounier, 2002; Lazega et al., 2008; Lazega, 2020) as a multilevel phenomenon. For a substantive explanation of this graph, see Brailly (2016).</p></sec><sec id="j_connections-2019.019_s_005"><div>Sociological interpretation</div><p>From an economic sociology perspective, such patterns facilitate the study of multilevel, multiplex and multisided overlaps across levels, to provide a new perspective on markets as multilevel networks. In these multilevel networks, a relationship between two firms creates a context that facilitates the creation or maintenance of relationships between their employees, and the other way around: interpersonal relationships between sales representatives contribute to the formation of inter-organizational, contracting ties (Bathelt and Glückler, 2003; Berends et al., 2011). In this context, social relationships are not only behind the deals, they are also around them. In other words, social relationships are not only between buyers and sellers, but also among buyers and among sellers. As a result, such relationships need to be contextualized in their relational neighborhood. For example, imagine the following hypothetical scenario: seller A can give an opportunity to seller B concerning a buyer C such as “C is looking for products you have.” Seller A gives this opportunity to seller B only because they are “friends” and they have known each other for a long time, expecting direct reciprocity. This opportunity is relevant because seller A’s company has already closed a deal with buyer C’s company and so seller A is aware of buyer C’s needs and bargaining behavior. This situation leads to the creation of a new relationship between seller B and buyer C in the form of a meeting to discuss a potential deal. This complex pattern helps redefine the nature of markets (<a ref-type="bibr" href="#j_connections-2019.019_ref_005">Brailly et al., 2016</a>) as multilevel, socially organized settings.</p><p>In this specific setting, a limited number of very large companies dominate the market with smaller companies gravitating around this core, suggesting an oligopolistic structure that economists call “oligopoly with fringes.” Trade fairs as field-configuring events contribute to the reproduction of this oligopolistic, multilevel and coopetitive structure. In the sociology of culture, it helps understand, from a neo-structural perspective, the mechanisms underlying contemporary globalization and uniformization of culture (<a ref-type="bibr" href="#j_connections-2019.019_ref_005">Brailly et al., 2016</a>; <a ref-type="bibr" href="#j_connections-2019.019_ref_007">Favre et al., 2016</a>).</p></sec><sec id="j_connections-2019.019_s_006"><div>Methodological foundations and extensions</div><p>For a general perspective on multilevel networks in the social sciences, see Snijders (2016). Multilevel blockmodels and stochastic blockmodels for such data are available in <a ref-type="bibr" href="#j_connections-2019.019_ref_013">Žiberna (2014)</a>, <a ref-type="bibr" href="#j_connections-2019.019_ref_001">Barbillon et al. (2016)</a> and <a ref-type="bibr" href="#j_connections-2019.019_ref_006">Chabert-Liddell et al. (2019)</a>. For multilevel ERGMs associated with this data format, see <a ref-type="bibr" href="#j_connections-2019.019_ref_012">Wang et al. (2013)</a>. For multilevel ERGMs analyzing this dataset, see Brailly (2016) <a ref-type="bibr" href="#j_connections-2019.019_ref_005">Brailly et al. (2016</a>) and <a ref-type="bibr" href="#j_connections-2019.019_ref_007">Favre et al. (2016)</a>. For more methods using multilevel network analyses, see various chapters in Lazega and Snijders (2016), Lomi et al. (2016), Koskinen et al. (2017), Tranmer et al. (2017).</p></sec></div>

Visualizing Multilevel Networks for the Analysis of Superposed Levels of Collective Agency

Connections

This work is licensed under the Creative Commons Attribution 4.0 International License.

Visualizing Multilevel Networks for the Analysis of Superposed Levels of Collective Agency

Published Online: Jan 05, 2021

Page range: 143 - 145

DOI: https://doi.org/10.21307/connections-2019.019

Keywords
Multilevel networks, image

© 2020 Emmanuel Lazega published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Visualizing Multilevel Networks for the Analysis of Superposed Levels of Collective Agency

Published Online: Jan 05, 2021

Page range: 143 - 145

DOI: https://doi.org/10.21307/connections-2019.019

KeywordsMultilevel networks, image

© 2020 Emmanuel Lazega published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Keywords
Multilevel networks, image