Exploring small-world network with an elite-clique: Bringing embeddedness theory into the dynamic evolution of a venture capital network

Abstract

This paper uses a network dynamics model to explain the formation of a small-world network with an elite-clique. This network is a small-world network with an elite-clique at its center in which elites are also the centers of many small groups. These leaders also act as bridges between different small groups. Network dynamics are an important research topic due to their ability to explain the evolution of network structures. In this paper, a Chinese Venture Capital (VC) network was coded from joint investments between VC firms and then analyzed to uncover its network properties and factors that influence its evolution. We first built a random graph model to control for factors such as network scale, network growth, investment frequency and syndication tendency. Then we added a partner-selection mechanism and used two theories to analyze the formation of network structure: relational embeddedness and structural embeddedness. After that, we ran simulations and compared the three models with the actual Chinese VC network. To do this we computed the elite-clique's EI index, degree distribution, clustering coefficient distribution and motifs. Results show that adding embeddedness theories significantly improved the network dynamic model's predictive power, and help us uncover the mechanisms that affect the formation of a small-world industrial network with an elite-clique at its center. (Jar-der. Luo)  These authors share the first co-authorship. This paper will present a partner-selection mechanism that integrates embeddedness theory to show the formation of a small-world network with an elite-clique at its center. These elites are the centers of their respective center-satellites groups and also act as bridges to other small groups. In an industry of this type, a major firm often initiates a business plan and then chooses followers to join in the plan. For example, in a VC investment plan, there is always a major investor who assesses an investment opportunity, is responsible for setting up the plan, and organizes the syndication partners. There may be one seat in an investee's board for investors, and in general, this major player will represent investors by being on the board. This paper incorporates the selection mechanism stated above into the model, and illustrates significant structural results of this selection mechanism in the dynamics of the industry network.Modeling networks serves at least two purposes. Firstly, it helps us understand how networks form and evolve, e.g., in terms of community evolution, changes in network statistics, and emergence of central roles, etc. Secondly, in studying simulations of network-dependent social processes, successful network models can be used to specify the structure of interaction, such as link prediction (Tylenda, Angelova, & Bedathur, 2009) and community detection (Nguyen, Dinh, Tokala, & Thai, 2011). A large variety of models have appeared in the physics-oriented network literature in recent years. Some models focused on understanding the structure and evolution of...

State-of-art review of information diffusion models and their impact on social network vulnerabilities

“…The connection topology of the social and biological networks is neither entirely regular nor fully random. These networks refer to as small-world network (Ha et al, 2015;Gu and Liu, 2019). The small-world network model was introduced in (Soriano-Sánchez and Posadas-Castillo, 2018).…”

Dynamic Evolution of Venture Capital Network in Clean Energy Industries Based on STERGM

“…In this type of high-uncertainty environment, VC firms seek syndications to hedge against various types of risks. Building "guanxi", which is defined as "a high-trust relationship which is relatively independent of the social structure around it", is a common strategy for VC firms in this industry [8].…”

“…Existing research on VC networks mostly focuses on the characteristics of static VC networks and their effects. The black box of the process of venture capital network evolution has not been solved [8]. The essence of the evolution of venture capital networks is the choice of partners and the resulting formation and dissolution of partnerships [6,8].…”

“…The black box of the process of venture capital network evolution has not been solved [8]. The essence of the evolution of venture capital networks is the choice of partners and the resulting formation and dissolution of partnerships [6,8]. On the one hand, based on resources demand, such as project information and network status, VC firms will select suitable syndication partners to build network relationships.…”

“…Despite the popularity of VC syndicated investments in clean energy industries, we still know relatively little about how clean energy industry VC networks evolve. In addition, there are many theoretical and empirical studies on VC network formation [8][9][10], but there have been few rigorous studies that explore how VC networks dissolve, especially in clean energy industries. Actually, network evolution involves the sequential processes of network formation and dissolution [6,8,11]; moreover, different factors might drive each process and the formation and dissolution of a network are not generally strictly inverse mechanisms [12,13].…”