Entrepreneurial Ecosystems and Networks Project
There is a general consensus in that networks play a central role in the functioning of entrepreneurial ecosystems around the world, particularly for entrepreneurial finance. With networks we refer to social and professional connections among the individuals that take relevant roles in these settings.
Networks transmit information, and are key to obtain resources of different types. The ideas that many economic markets are embedded in networks, and that these networks have a role on them have a long history. Literature has stressed, for example, the concrete role of network structures in transmitting information, and in generating trust and discouraging misconduct (or agency). Despite of the shared understanding on their decisive role, a careful understanding on how networks shape entrepreneurial finance markets’ functioning and outcomes is pending.
In particular, empirical research on the subject has remained limited. This seems not surprising given the limited availability of data on such a complex phenomenon. Collecting data on social and professional networks is generally a hard task. Traditional research, typically based on the use of surveys, has been limited by a small network size, and other problems intrinsic of this methodology. In the case of entrepreneurial finance, this problem is aggravated by the fact that entrepreneurial ventures are -in a large extent- an ephemeral phenomenon.
Recent developments in the Web have created an opportunity to study this phenomenon. Entrepreneurial finance practitioners, actively participate in online marketplaces and collaborative databases. They also leave a trace of their connections in their social media usage. As a result, data on social and professional networks from entrepreneurial settings is increasingly available from different sources in the Web. Specialized sites such as Angellist and Crunchbase, as well as related social media (such as Linked-in or Twitter), constitute a valuable source of network data that can be exploited for empirical research on this topic. The resulting set of data is rich, vast in its amount, and has a considerable representation of the phenomena of interest.
Exploiting this data requires, nonetheless, addressing a number of technological issues related with its collection, storage, ordering, manipulation, and analysis. It requires specific skills, and expertise of software engineers and data-mining.
In response to this challenge, we have put together an interdisciplinary team that aims to order to exploit these data sources and advance the entrepreneurship/entrepreneurial finance research agenda. Our team is comprised by social sciences/business school researchers, and software engineers / dataminers.
The objective of this project is to develop data collection tools that will gather high-frequency data on entrepreneurial activity, including individuals, organizations and their (financial, professional and social) connections. On the basis of the resulting data: i) Construct dynamic networks suitable for network analysis, ii) Develop metrics and tools in order to allow monitoring entrepreneurial activity and network dynamics.
Learning Objectives (for developers):
From a technical perspective, the project allows developers to gain skills that are increasingly demanded both in the scientific as in the professional market. For instance, in terms of:
- Web mining + APIs
- Graph Oriented Databases and Handling
- Large Scale Data Analysis. Big Data Technologies
The project provides tools for relevant data collection, storage, manipulation, and analysis (particularly, large-scale network analysis).
The chart below summarizes some of the project elements, including sources of information and some of the technologies and libraries used for both data management and analysis.
Results: Our Apps and Database
The results of this research as today includes an international network-oriented database of entrepreneurial finance covering the period 2011-2016. By this date, a number of working papers on entrepreneurial finance has been written and are in process of publicaton. (See below).
By 2016 we have developed four different applications, which collect data from different sources.
- Tangela (2014) – Financing rounds and network collector- (no longer active)
- Tanchella (2016) – Financing rounds and network collector (includes new sources)
- VCDeals(2015) – VC Funds and invested startups
- Shelob (2015) – Education and Experience collector
The following is a list of research papers using the data and tools developed by the project:
- Pasquini, Ricardo y Robiolo, Gabriela (2016) “Matching in Entrepreneurial Finance Networks” Submitted
- Pasquini, Ricardo, Sarria Allende, Virginia y Robiolo, Gabriela (2016) “The Added-Value of Network Connections in Entrepreneurial Finance” Submitted
- Pasquini, Ricardo, y Sarria Allende, Virginia (2016) “Random Network Formation in Entrepreneurial Finance: A Simple Model and Evidence”. In progress
- Carolina Dams, Virginia Sarria Allende, Ricardo Pasquini, Gabriela Robiolo “Accelerated Female Entrepreneurs and their Access to Venture Capital” In progress. Presented at Babson College Entrepreneurship Research Conference (BCERC) 2016, and at Diana International Research Conference 2016.
- Carolina Dams, Virginia Sarria Allende, Ricardo Pasquini, Gabriela Robiolo “Accelerators, network and Venture Capital” In progress. Presented at the Academy of Management Meeting 2016.
- Ricardo Pasquini, Virginia Sarria Allende, Carolina Dams “Network Robustness and Performance of Entrepreneurial Finance Ecosystems” In progress