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1
Feldmann, Louise Mort. "TechCrunch and CrunchBase." Charleston Advisor 17, no. 3 (January 1, 2016): 34–37. http://dx.doi.org/10.5260/chara.17.3.34.
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Ingham, Alexander, and Leah Kodner. "PrivCo versus Crunchbase." Journal of Business & Finance Librarianship 22, no. 3-4 (October 2, 2017): 250–52. http://dx.doi.org/10.1080/08963568.2017.1372019.
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Färber, Michael, Carsten Menne, and Andreas Harth. "A Linked Data wrapper for CrunchBase." Semantic Web 9, no. 4 (June 29, 2018): 505–15. http://dx.doi.org/10.3233/sw-170278.
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Liang, Yuxian Eugene, and Soe-Tsyr Daphne Yuan. "Predicting investor funding behavior using crunchbase social network features." Internet Research 26, no. 1 (February 1, 2016): 74–100. http://dx.doi.org/10.1108/intr-09-2014-0231.
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Purpose – What makes investors tick? Largely counter-intuitive compared to the findings of most past research, this study explores the possibility that funding investors invest in companies based on social relationships, which could be positive or negative, similar or dissimilar. The purpose of this paper is to build a social network graph using data from CrunchBase, the largest public database with profiles about companies. The authors combine social network analysis with the study of investing behavior in order to explore how similarity between investors and companies affects investing behavior through social network analysis. Design/methodology/approach – This study crawls and analyzes data from CrunchBase and builds a social network graph which includes people, companies, social links and funding investment links. The problem is then formalized as a link (or relationship) prediction task in a social network to model and predict (across various machine learning methods and evaluation metrics) whether an investor will create a link to a company in the social network. Various link prediction techniques such as common neighbors, shortest path, Jaccard Coefficient and others are integrated to provide a holistic view of a social network and provide useful insights as to how a pair of nodes may be related (i.e., whether the investor will invest in the particular company at a time) within the social network. Findings – This study finds that funding investors are more likely to invest in a particular company if they have a stronger social relationship in terms of closeness, be it direct or indirect. At the same time, if investors and companies share too many common neighbors, investors are less likely to invest in such companies. Originality/value – The author’s study is among the first to use data from the largest public company profile database of CrunchBase as a social network for research purposes. The author ' s also identify certain social relationship factors that can help prescribe the investor funding behavior. Authors prediction strategy based on these factors and modeling it as a link prediction problem generally works well across the most prominent learning algorithms and perform well in terms of aggregate performance as well as individual industries. In other words, this study would like to encourage companies to focus on social relationship factors in addition to other factors when seeking external funding investments.
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Żbikowski, Kamil, and Piotr Antosiuk. "A machine learning, bias-free approach for predicting business success using Crunchbase data." Information Processing & Management 58, no. 4 (July 2021): 102555. http://dx.doi.org/10.1016/j.ipm.2021.102555.
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Chae, Bongsug (Kevin), and Gyuhyeong Goh. "Digital Entrepreneurs in Artificial Intelligence and Data Analytics: Who Are They?" Journal of Open Innovation: Technology, Market, and Complexity 6, no. 3 (July 29, 2020): 56. http://dx.doi.org/10.3390/joitmc6030056.
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Digital technologies are key resources for entrepreneurial activities and there is great interest in digital entrepreneurship. While much research has focused on the role of digital technologies in entrepreneurship and how they are shaping the field, there has been relatively little research on those key players of digital entrepreneurship. Using data from Crunchbase and Twitter API and a learning machine, this study attempts to answer the question of “who are digital entrepreneurs?” This study reports that digital entrepreneurs in the artificial intelligence and data analytics (AIDA) industry are more likely to be male and to be active and connected online than non-digital entrepreneurs. In addition, they tend to be more extroverted and less conscientious and agreeable than other, non-digital, entrepreneurs. Our findings help to develop a clearer picture of digital entrepreneurs, which would be of great interest to investors, policy makers, current and future digital entrepreneurs and educators.
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Kézai, Petra Kinga, Szabolcs Fischer, and Mihály Lados. "Smart Economy and Startup Enterprises in the Visegrád Countries—A Comparative Analysis Based on the Crunchbase Database." Smart Cities 3, no. 4 (December 3, 2020): 1477–94. http://dx.doi.org/10.3390/smartcities3040070.
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The present study seeks to explore the concept of “smart economy” through the definition of the smart city. It also presents smart city subsystems and the smart city model. It focuses on smart and creative startups within the smart city model. The research examines medium-sized cities in the Visegrád countries (Czech Republic, Slovakia, Poland, Hungary) with a population ranging from 100,000 to 1 million inhabitants for startups. The research question is: Where are the medium-sized cities in the Visegrád countries that are both startup centers and smart cities? In the course of the research, the term “smart cities” was based on the definition set by the European Commission and the definition of startup centers was made using data analysis of the American Crunchbase database. As a result of the two studies, it can be concluded that there are no cities in the Visegrád countries with an above average level of both startup presence and smart cities.
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Bishop, Alex, and Juan Mateos-Garcia. "Exploring the Link Between Economic Complexity and Emergent Economic Activities." National Institute Economic Review 249 (August 2019): R47—R58. http://dx.doi.org/10.1177/002795011924900114.
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Recent studies have shown a strong link between the complexity of economies and their economic development. There remain gaps in our understanding of the mechanisms underpinning these links, in part because they are difficult to analyse with highly aggregated, official data sources that do not capture the emergence of new industrial activities, a potential benefit from complexity. We seek to address some of these gaps by calculating two indices of economic complexity for functional local economies (Travel to Work Areas) in Great Britain, and explore their link with these locations’ economic performance. Seeking to gain a better understanding of the mechanism connecting economic complexity with economic performance, we create a measure of emergent technological activity in a location based on a combination of novel data sources including text from UK business websites and CrunchBase, a technology company directory, and study its link with economic complexity. Our results highlight the potential value of novel, unstructured data sources for the analysis of the links between economic complexity and regional economic development.
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Yang, Song, and Ron Berger. "Relation between start-ups’ online social media presence and fundraising." Journal of Science and Technology Policy Management 8, no. 2 (July 3, 2017): 161–80. http://dx.doi.org/10.1108/jstpm-09-2016-0022.
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Purpose The purpose of this study is to examine the emergences of social media such as Facebook, Twitter and Instagram have changed the way human beings communicate and interact. In the past few years, this has become crucial in the context of business, especially in start-up fund raising. Access to venture capital financing is a crucial issue in the entrepreneurial finance literature. To further explore the use of social media for entrepreneurs, the authors have explored how entrepreneurs use social media for fund-raising purposes. The authors have used Application Programming Interfaces (APIs) to collect entrepreneurs’ funding data from Crunchbase and entrepreneurs’ social media data from Facebook and Twitter. The results show that social media is significant for start-ups in their success or failure in fund raising. Investing energy into utilizing online social media and exhausting these platforms consciously contributes to the financial success of start-ups. Therefore, start-ups which are popular among online fans and followers can manage to raise larger amounts of funding in the early stages. Design/methodology/approach This research relies on a wide range of quantitative data, which was obtained from three different online sources which includes Facebook, Twitter and CrunchBase. The use of a variety of internet technologies have been linked to increases in individuals’ social network diversity, which likely increases access to social capital at the individual level (Hampton and Wellman, 2003). The dataset was retrieved by using APIs, which enables the collection of novel metrics, from various sources that provide a well-structured dataset (Priem and Hemminger, 2010). Hypotheses were tested on a longitudinal dataset from 2000 to 2013, comprising general and investment data and social media metrics of start-ups. First, a sample from the database was selected to ensure data availability and reliability. After sampling, all the selected companies’ Twitter and Facebook activities were observed and metrics were analysed. SPSS was used to conduct correlation and regression analyses. Findings This study analysed whether start-ups’ social media convention is able to influence investors’ choices, especially the amount of total funding given. The paper showed that innovative start-up companies were able to benefit from communicating on social media platforms. Start-ups, which were using Facebook and Twitter effectively, focusing on valuable social media metrics, received larger amount of funding in total. Furthermore, it was observed that as their business grew, they intended to put more effort into online social networking. It confirmed the idea that businesses are using social media consciously. Originality/value This is the only paper that the authors could find that examines the relationship between fundraising and activity on social networks.
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Amoroso, Nicola, Loredana Bellantuono, Alfonso Monaco, Francesco De Nicolò, Ernesto Somma, and Roberto Bellotti. "Economic Interplay Forecasting Business Success." Complexity 2021 (March 19, 2021): 1–12. http://dx.doi.org/10.1155/2021/8861267.
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A startup ecosystem is a dynamic environment in which several actors, such as investors, venture capitalists, angels, and facilitators, are the protagonists of a complex interplay. Most of these interactions involve the flow of capital whose size and direction help to map the intricate system of relationships. This quantity is also considered a good proxy of economic success. Given the complexity of such systems, it would be more desirable to supplement this information with other informative features, and a natural choice is to adopt mathematical measures. In this work, we will specifically consider network centrality measures, borrowed by network theory. In particular, using the largest publicly available dataset for startups, the Crunchbase dataset, we show how centrality measures highlight the importance of particular players, such as angels and accelerators, whose role could be underestimated by focusing on collected funds only. We also provide a quantitative criterion to establish which firms should be considered strategic and rank them. Finally, as funding is a widespread measure for success in economic settings, we investigate to which extent this measure is in agreement with network metrics; the model accurately forecasts which firms will receive the highest funding in future years.
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Morales-Alonso, Gustavo, Guzmán A. Vila, Isaac Lemus-Aguilar, and Antonio Hidalgo. "Data retrieval from online social media networks for defining business angels’ profile." Journal of Enterprising Communities: People and Places in the Global Economy 14, no. 1 (November 18, 2019): 57–75. http://dx.doi.org/10.1108/jec-10-2019-0095.
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Purpose Entrepreneurship is the basis of economic development but is somehow limited by the lack of access to financing sources, especially in the crucial moments of start-up early-stage development. For crossing the so-called “valley of death,” start-ups need to access informal finance sources, such as business angels. This study aims at defining the profile of business angels and comparing it with the existing literature. Design/methodology/approach A novel methodology for sampling the business angles population has been used, which extracts data from online social media networks. This allows taking a closer look at informal sources of entrepreneurial finance. A total of 500 real business angels, acting worldwide, from the LinkedIn and Crunchbase databases has been retrieved for this study. Findings Results point out that younger investors seem to be entering the entrepreneurial informal finance market. They are mainly males between 40 and 50 years of age, with a previous entrepreneurial record, and more highly educated than previously stated. They tend to have studies from Business Administration and Economics, although they prefer to invest in the ICT sector. Originality/value Besides the novel data retrieval technique for analyzing the informal sources of finance, the originality of the work lies in updating the archetype for business angels.
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Rodrigues, Fabiano, Francisco Aparecido Rodrigues, and Thelma Valéria Rocha Rodrigues. "Modelos de machine learning para predição do sucesso de startups." Revista de Gestão e Projetos 12, no. 2 (June 15, 2021): 28–55. http://dx.doi.org/10.5585/gep.v12i2.18942.
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Este estudo analisa resultados obtidos com modelos de machine learning para predição do sucesso de startups. Como proxy de sucesso considera-se a perspectiva do investidor, na qual a aquisição da startup ou realização de IPO (Initial Public Offering) são formas de recuperação do investimento. A revisão da literatura aborda startups e veículos de financiamento, estudos anteriores sobre predição do sucesso de startups via modelos de machine learning, e trade-offs entre técnicas de machine learning. Na parte empírica, foi realizada uma pesquisa quantitativa baseada em dados secundários oriundos da plataforma americana Crunchbase, com startups de 171 países. O design de pesquisa estabeleceu como filtro startups fundadas entre junho/2010 e junho/2015, e uma janela de predição entre junho/2015 e junho/2020 para prever o sucesso das startups. A amostra utilizada, após etapa de pré-processamento dos dados, foi de 18.571 startups. Foram utilizados seis modelos de classificação binária para a predição: Regressão Logística, Decision Tree, Random Forest, Extreme Gradiente Boosting, Support Vector Machine e Rede Neural. Ao final, os modelos Random Forest e Extreme Gradient Boosting apresentaram os melhores desempenhos na tarefa de classificação. Este artigo, envolvendo machine learning e startups, contribui para áreas de pesquisa híbridas ao mesclar os campos da Administração e Ciência de Dados. Além disso, contribui para investidores com uma ferramenta de mapeamento inicial de startups na busca de targets com maior probabilidade de sucesso.
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Hermes, Sebastian, Tobias Riasanow, Eric K. Clemons, Markus Böhm, and Helmut Krcmar. "The digital transformation of the healthcare industry: exploring the rise of emerging platform ecosystems and their influence on the role of patients." Business Research 13, no. 3 (September 11, 2020): 1033–69. http://dx.doi.org/10.1007/s40685-020-00125-x.
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AbstractWhile traditional organizations create value within the boundaries of their firm or supply chain, digital platforms leverage and orchestrate a platform-mediated ecosystem to create and co-create value with a much wider array of partners and actors. Although the change to two-sided markets and their generalization to platform ecosystems have been adopted among various industries, both academic research and industry adoption have lagged behind in the healthcare industry. To the best of our knowledge current Information Systems research has not yet incorporated an interorganizational perspective of the digital transformation of healthcare. This neglects a wide range of emerging changes, including changing segmentation of industry market participants, changing patient segments, changing patient roles as decision makers, and their interaction in patient care. This study therefore investigates the digital transformation of the healthcare industry by analyzing 1830 healthcare organizations found on Crunchbase. We derived a generic value ecosystem of the digital healthcare industry and validated our findings with industry experts from the traditional and the start-up healthcare domains. The results indicate 8 new roles within healthcare, namely: information platforms, data collection technology, market intermediaries, services for remote and on-demand healthcare, augmented and virtual reality provider, blockchain-based PHR, cloud service provider, and intelligent data analysis for healthcare provider. Our results further illustrate how these roles transform value proposition, value capture, and value delivery in the healthcare industry. We discuss competition between new entrants and incumbents and elaborate how digital health innovations contribute to the changing role of patients.
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Barykin, Sergey A., and Andrei L. Bulgakov. "Factors of the fintech market development in the global economy (the case of the alternative lending)." Vestnik of Saint Petersburg University. Management 20, no. 1 (2021): 108–27. http://dx.doi.org/10.21638/11701/spbu08.2021.105.
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Alternative lending is one of the largest segments of the financial technology market in the world which is represented by online platforms specializing in organizing the lending process. The purpose of the article is to assess the impact of key factors on the dynamics of venture capital investments in alternative lending platforms. The objectives of this study are to define the concept of alternative lending, build an econometric model to analyze the factors of development of alternative lending in the world, and interpret the results from the point of view of the prospects for the development of alternative lending. Alternative lending has been defined as a segment of the fintech market that can be characterized as parallel financing of economic activities based on digital platforms through the provision of syndicated loans after decentralized business models. To test the hypotheses of the study, an econometric model was built on the analysis of 5,234 investment transactions completed in the period from 2013 to 2019 in 35 countries of the world and included in the CrunchBase database. According to the model, such factors as the availability of venture capital, the number of workforce, the digital competitiveness of the economy (the factor of future readiness), and the availability of credit information have a significant impact on the dynamics of direct and venture capital investments in alternative lending companies. The obtained results can be considered when improving the national strategy for regulating the alternative lending market, which is especially important for Russia, where the segment of alternative lending is at the stage of stagnation.
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Gereto, Marcos, and Gilberto Sarfati. "Caracterização do ciclo de investimentos de venture capital em startups brasileiras em termos de rodadas de investimentos e estratégias de desinvestimento a partir de dados da Crunchbase." Revista da Micro e Pequena Empresa 13, no. 3 (January 3, 2020): 38–54. http://dx.doi.org/10.21714/19-82-25372019v13n3p3854.
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Tatomyr, Iryna. "«Academic unicorns» as a new category of economic science." Economic discourse, no. 2 (June 2019): 7–19. http://dx.doi.org/10.36742/2410-0919-2019-2-1.
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Introduction. In recent years, the number of people who use professional assets to generate sustainable incomes, which leads to the formation of a new stratum of academic circles has been an increase in the academic environment. This led to the need to introduce a new economic category into scientific circulation, which would have shown the privilege of the status of participants in the educational process in the academic hierarchy. Methods. The materials of the research served the work of domestic and foreign specialists. General scientific methods of research are used in the process of preparation of the article: analysis, synthesis, concretization, scientific abstraction, logical and graphic structuring and generalization. The statistical basis for the study was data of Crunchbase Pro, Business Insider, JRC Technical Report, Vêctor.media. Results. It is proposed to introduce into the scientific circle a new economic category «academic unicorns», which would certify the privilege of the status of participants in the educational process in the academic hierarchy for the amount of income from educational activities and substantiates its methodological significance for economic science. The proposal was made to divide «academic unicorns» into «unicorns educational companies», «unicorn teachers», «unicorn students», «unicorns of adolescents» and their main features are outlined. Examples of academic community members who have this status are given. The common features, which unite all the representatives of the academic community for belonging to the status of unicorn, are substantiated. Discussion. The selection of "academic unicorns" on the fact of possessing the necessary qualities will make it possible to distinguish those among the members of the academic community who have achieved the highest level of financial evaluation of their professional assets. Prospects for further research should be directed formation of the list of potential leaders who will become a benchmark of productive work for the rest of the academic community. Keywords: academic unicorns, startup companies, educational online providers.
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Pisoni, Alessia, and Alberto Onetti. "When startups exit: comparing strategies in Europe and the USA." Journal of Business Strategy 39, no. 3 (May 21, 2018): 26–33. http://dx.doi.org/10.1108/jbs-02-2017-0022.
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Purpose The purpose of this paper is to present an overview of trends toward start-up exits. Exits represent the “end phase” of the start-up process, at least for the founders and the early investors. For high-growth venture-capital-backed companies, exits are often considered the ultimate goal of building a profitable venture. These ventures are intended from the beginning to harvest the financial value created by the business at some point in the future, and return capital to early investors. Design/methodology/approach The authors tracked 5,744 merger and acquisition transactions that have occurred between European and US tech start-ups since 2012. Data are drawn from CrunchBase, the most comprehensive database of high-tech companies and investors with information on the companies and investors around the world. The authors then compared the trends of acquisitions between European and US companies. Findings Results show that US companies are far more inclined to make acquisitions than European ones. Acquirers of start-ups, both from Europe and the US, prefer to buy local companies. However, recently, US companies have started to show more interest in European start-ups. Thus, signaling that the European start-up ecosystem is growing and becoming more attractive for US buyers. Furthermore, results show that start-up exits typically happen within a few years after a company’s establishment. Research limitations/implications The research does not take into consideration the price of the transaction, or the amount of capital invested by venture capitalists in the high-tech start-ups that have been acquired. Further research should address this specific problem by helping European start-ups understand how to plan the exit phase within few years from establishment. Practical implications The results have important implications both for entrepreneurs/managers and policymakers. Early exit appears to be a global trend among start-ups. This suggests that the exit phase should be properly planned to happen in the very early stage of the start-up process. On the other hand, the research also shows that there is still a gap to be filled in the European start-up ecosystems’ ability to produce exits and create new large innovative companies (the so-called “unicorns”). Originality/value To date, there has been a little research about exits for young high-tech ventures. This paper will attempt to shed new light on this so far under-explored issue by specifically analyzing exits as financial strategy for investors and entrepreneurs.
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Caviggioli, Federico, Alessandra Colombelli, Antonio De Marco, and Emilio Paolucci. "How venture capitalists evaluate young innovative company patent portfolios: empirical evidence from Europe." International Journal of Entrepreneurial Behavior & Research 26, no. 4 (April 20, 2020): 695–721. http://dx.doi.org/10.1108/ijebr-10-2018-0692.
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PurposeThis paper analyzes the importance given by venture capital (VC) firms to the different characteristics of the patent portfolio of a young innovative company (YIC). In an attempt to go beyond previous studies, the authors argue that not only is the size of a technological portfolio significant but also its nature. It is also examined whether the correlation between patents and VC financing varies across different industrial sectors and over different rounds of VC investments.Design/methodology/approachThe empirical analysis has focused on a sample of 1,096 European YICs between the years 2010 and 2014. Target companies were identified in the monthly bulletins of Go4Venture, which reported the largest European deals and gathered information on the amount of VC financing. Additional data was derived from FinSMEs and crunchbase. Industrial sectors were differentiated according to their ability to appropriate the returns of innovation by relying on patent protection mechanisms. A multivariate regression framework at the patent family level was adopted to investigate empirical associations between the amount of VC financing and the characteristics of a YIC's patent portfolio.FindingsThe results confirm the positive value of patents. Both the size and the characteristics of a YIC patent portfolio have been found to be positively associated with the total amount of VC financing. Additionally, the correlation between a YIC patent portfolio and VC investment varies across industries and over rounds of funding. Although the number of patents is positively correlated with VC investments in sectors with strong Intellectual Property (IP) regimes, the same does not apply to sectors characterized by lower patent intensity, where qualitative metrics seem to have a stronger correlation. Significant differences have also been found for the different rounds of VC investments.Research limitations/implicationsThe limitations of this paper are related to data availability. Empirical associations have been investigated, but causal effects cannot be ascertained in this framework. The authors focused on a sample of firms that received VC funding. Several transactions were excluded, due to a lack of specifications pertaining to the round series. Furthermore, a number of potential drivers of the financed amounts, such as variables related to the founder or the management team, have not been considered in this study.Practical implicationsFor firms operating in sectors with weak IP regimes, patents are positively associated with attracting equity capital, if they are the output of R&D collaborations and have higher technical merit. In industries where patent intensity is higher, patent portfolio size matters more than quality. This suggests that VC investors award innovation quality to cases in which patenting is less frequent. Since the results indicate that positive associations between patenting and VC financing are more significant in later stages, managers should plan their patenting strategy in advance to reap the related benefits, and then collect the premium at later VC stages.Originality/valueIn this paper, the importance given by VC firms to different characteristics of a YIC patent portfolio has been analyzed in terms of size, quality, and complexity. While previous empirical analyses mainly focused on a single sector, the authors have examined whether the relevance of patents for VC financing decisions varies across industries and over different rounds of investment. The geographical coverage of the sample is another novelty of the paper. Previous works focused on a limited number of countries, whereas this research has considered firms operating in several European countries.
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den Besten, Matthijs L. "Crunchbase Research: Monitoring Entrepreneurship Research in the Age of Big Data." SSRN Electronic Journal, 2020. http://dx.doi.org/10.2139/ssrn.3724395.
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den Besten, Matthijs L. "Crunchbase Research: Monitoring Entrepreneurship Research in the Age of Big Data." SSRN Electronic Journal, 2020. http://dx.doi.org/10.2139/ssrn.3724395.
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Cong, Yu, Hui Du, and Miklos A. Vasarhelyi. "Cloud Computing Start-ups and Emerging Technologies: From Private Investors' Perspective." Journal of Information Systems, June 24, 2020. http://dx.doi.org/10.2308/isys-17-040.
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We examine private investor's funding preferences for cloud computing start-ups that provide services in various information technology (IT) areas. The funding preference is measured in funding size and frequency. Using data from CrunchBase, an unconventional dynamic database, we find significantly positive associations between the funding preference and the cloud computing services provided in IT security, and big data and data analytics among cloud computing start-ups that have received at least two rounds of funding. The association is negatively significant when the cloud computing services are provided in ERP systems and when the funding preference is measured only in size. The results suggest that private investors differentiate among start-ups by specific technology and the lifecycle of the technology. During the sample period of rapid growth in the cloud computing industry, we document that the funding preference by private investors favors start-ups that provide services in critical, newer and fast-growing IT areas.