Simulation of the Entrepreneurial Process Based on the Online Social Network Structure

Simulation of the Entrepreneurial Process Based on the Online Social Network Structure

Yang Songa, Ron Bergerb, Zhiyuan Zhangc

Extended Abstract:Network based entrepreneurship research addresses issues pertaining to network structure, content and governance. In order to start up a new business, entrepreneurs need to search for information and resources through their personal networks. In this paper, we study the entrepreneurs’ collaboration position in a given network and its impact on entrepreneurial success. Using entrepreneurs’ network data extracted from their online social network, we develop a simulation model of the entrepreneurial process and its outcomes in terms of growth and survival. We assume one entrepreneur needs to find their partner in the network to start up a business. We find that initial wealth at start-up, network density, time to first collaboration, has an impact on the probability of survival. Using the simulation model we created, one can infer to the maximum survival time of a venture and the survival probability at a given time based on the network density, start-up time and collaboration. 

According to the entrepreneurial literature, the formation of a business can be pided into three main stages: (1) idea development; (2) organizing the founding of a firm; and (3) running the newly established firm (Greve, 1995. At the beginning of the start-up phase, entrepreneurs need to find business ideas through their networks. During the second phase, entrepreneurs experience the problems associated with limited capacity and resources. While the network supplies entrepreneurs with the connections which may possibly solve these difficulties, opportunities for start-ups are limited and transitory. Entrepreneurs may waste their opportunities if they devote too much time searching for the collaborators in the network (Greve, 1995. While, there is a particular point in time which an entrepreneur starts a business, the boundary between the first and the second phase may thus be blurred. The mechanisms and processes by which specific ties play a role in the expansion of an emerging start-up remain blurred (Elfring and Hulsink, 2003.; de Jong and Marsili, 2015; Colombelli et al., 2016)), Wilken, 1979)

In our model, we found that entrepreneurial growth is not only related to wealth but also to their network degree. An entrepreneur’s start-up wealth can guarantee survival even without a collaborator. Although we were not able to determine the threshold for entrepreneurs to survive at a given time, we could still infer the survival probability from the start-up time frame.

We expected that entrepreneurs with a higher network degree would collaborate more with other actors. However, our simulation model only allowed entrepreneurs to collaborate with one entrepreneur at a time. In other words, the probability that an entrepreneur would collaborate with someone in the network became lower when their network degree was high. In fact, entrepreneurs with fewer connections may collaborate more and survive longer than those with a higher network degree.

During the entrepreneurial process, the network can be used to search for information. By using simulation approach, we can predict entrepreneurial process via our model. The methodology provides us more opportunities to test network collaboration theories and can be applied to actual entrepreneurs’ activities. Our research not only contributes to the field of entrepreneurship but also to a further understanding of online social networks and the benefits of social media arising from the ubiquitous use of the internet. Our simulation model provides a novel approach to understanding the entrepreneurial process in a fixed network.

aEconomics School, Jilin University

bCollege of Law and Business

cCorresponding author, Accounting School, Jilin University of Finance and Economics

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