Figure 1: Conceptual model of entrepreneurial networks (adapted from Hakansson 1989) (Hakansson et al. 2009, 33). Because of this layering of multiple actors, resources, and activities, the model is inclusive of dyadic and network multi- plexity. Over the next sections, we review the two dominant network perspec- tives, and use our representation of Hakansson’s model as a reference point for discussing the extent to which these perspectives integrate structure and flow elements, and thus network multiplexity. Table 1: Incidence matrix (simplified example) 3.6 Equivalence classes and the Q-table Table 3: Q-table (simplified example) Table 4: Types of relationships for CDT (1998-2000 segment) To maintain focus on demonstrating the method, we aggregate individual rela- tionships up to three stylized types of relationships — financing, licensing, and manufacturing — as shown in Tables 4 and 5. Each type of relationship involves a different set of multiple resources and activities. A more detailed analysis of this case study may have included naming each actor (including individual investors, licensees, and manufacturers), finer temporal segmentation (by year), more specificity about resources (including individual patents, specific materials, or payments), and provided finer granularity of activities (including specific steps in the process of licensing, manufacturing or financing, such as bidding, negotiating, exchanging, maintaining, or dissolving). 4.3 Dataset segmentation Table 5: Types of relationships for CDT (2001-2002 segment) Table 9: CDT connectivity matrix (2001-2002 segment) 4.6 Equivalence classes and Q-tables Table 10: CDT Q-table (1998-2000 segment) form one equivalence class. It is also the only equivalence class at dimension level 0, as summarized in the second row in the Q-table (Table 10). This equivalence class provides greater detail regarding the how CDT manages theit relationships. C ships may direc hanges in the flow of materials and IP in the licensing relation- ly cause changes in the flows of cash and reputation in the same type of relationship. These changes then affect the cash and reputation flows in the financing relationships, and thus also affect how investors value their equity positions in CDT. Such interactions within and across relationships reveal net- work multiplexity processes that are often overlooked in network research (Shipilov 2012) and can inform entrepreneurs about how to manage the function and evolution o f their networks. Table 11: CDT Q-table (2001-2002 segment)
