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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.

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.

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.

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.

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.

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.

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.

This is the only paper that the authors could find that examines the relationship between fundraising and activity on social networks.

As a response to global population growth and increasing demand for food, farmers have been complementing traditional agriculture practices with vertical farming (VF) and indoor hydroponic systems. To facilitate the growth of the VF industry, this paper aims to identify business model elements and their configurations that lead to high firm performance.

The research goals were met by conducting literature reviews coupled with a fuzzy-set qualitative comparative analysis (fsQCA) on five business model elements, “superior” OR “strong” performance as two possible outcomes, and the top-ranked global VF growers listed in the Crunchbase Database.

From the fsQCA results, it was observed that several business model configurations lead to strong firm performance. Vertical farms growing in urban settings and having strong customer engagement platforms, coupled with a presence of business-to-business (B2B) sales channels, are more consistently associated with superior performance. These results imply that the decision configuration of location, along with customer engagement activity and sales activity are differentiating factors between good firm performance and superior firm performance in the case of vertical farms.

This paper contributes to expanding the knowledge of business model theory, business model configurations and VF management, providing specific guidelines for vertical farm owners and investors related to decision-making for higher firm performance, as well as positive environmental, social and economic impact.

This study aims to investigate different types of platform providers (PPs) to gain a deeper understanding of the characteristics and underlying logic of this group within collaborative consumption (CC). As CC occurs with three groups of actors (PP, peer service provider and customer) and is predominantly viewed from the customer perspective, this study offers insights from the under-researched PP perspective.

This research applies a multiple case study approach and analyzes descriptively and thematically 92 cases of CC PPs gathered through the Crunchbase database.

The authors derive four archetypes of CC PPs, namely, the hedonist, functionalist, environmentalist and connector, that differ in their offered values, dominating motives and activities across industries.

The authors conceptualize CC by clearly describing the four archetypes and their characteristics. However, further research would benefit from including databases other than Crunchbase.

PPs need to understand their value offerings and customer preferences to develop convincing value propositions and offer engaging activities. PPs would benefit from a more active social media presence to build strong relations with customers and peer service providers to effectively communicate their values.

The paper is pioneering as it encompasses the perspective of CC PPs and operationalizes the concept of CC. The authors address the lack of research on CC by conducting an extensive case study.

This study aims to explore the rise of virtual specialty care startups and understand how the ventures leverage digital services to create a new market space. Given the high level of competition in an established industry like health care, the authors investigate the business models and competitive strategies of leading virtual specialty care startups with unicorn status (i.e. emerging, current and exited unicorns).

The authors performed an analysis of Crunchbase data to examine whether rising virtual care ventures target specialty care. They focused on companies from the USA, Europe and Asia-Pacific. The identified virtual specialty care ventures were investigated in-depth via a multiple case study. By reviewing corporate websites, Crunchbase data and media coverage, the authors analyzed the ventures’ business models and competitive strategies.

This study demonstrates that even in established and highly competitive markets such as health care, managers and entrepreneurs can still leverage digital services to unlock new market spaces. The data analysis reveals that virtual care startups target the field of specialty care. They create a new market space by focusing on fast access to services, personalization, measurable outcomes and affordability. The majority of investigated companies pursues a platform-based business model approach.

In the context of an established industry like health care, this study gives insights into a new generation of virtual specialty care ventures. By investigating the ventures’ business models and competitive strategies, the authors advance a young field of research.

How are city demographics correlated with the amount of venture capital they receive? This chapter uses a unique dataset of 58,000 venture deals from 2000 to 2014 from the CrunchBase dataset and census data from the same period. Place and the role of venture capital asserts venture capital’s spatial dependency and uses statistical software to find a strong positive correlation between the amount of venture capital funding and foreign, international, male professionals within a city, the gendering of venture capital, and the negative correlation of unskilled, foreign labor with funding.

As venture capital travels along social ties, this chapter suggests that foreign, international, and male professionals’ positive correlation may be due to these members having a wider and more diverse social network, allowing the ability to conjure funds. Moreover, the demographic may be a synonym for Sassen’s International Class, allowing the study to dovetail with a broader set of research. Finally, this chapter also provides a mechanism to classify cities based off their venture capital activity. The implications of this study are a better understanding of the trends correlated with venture capital, a classification system for cities, and a possible caveat to “virtuous cycle” theory. A supplement to the paper and to visualize implications for cities, we also created this D3 visualization visualizing the geographic positioning and relationships of those 58,000 deals, providing communicable and interactive research.

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.

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.

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.

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.

Entrepreneurial communication describes the communication activities of entrepreneurs and is an essential tool for entrepreneurs to build relationships. However, there is a lack of research regarding how entrepreneurs adapt their communication styles in times of crisis. Nevertheless, entrepreneurial communication during a crisis is essential because entrepreneurs must continue communicating with their stakeholders and be visible. In this regard, communication has the central aim of preventing the startup from suffering any damage that may result from the crisis. Thus, the present paper explores potential shifts in the communication styles of entrepreneurs during the first wave of the COVID-19 pandemic.

The authors examined the digital footprints of 780 entrepreneurs based in the USA on the social network Twitter. This study used a longitudinal dataset with the software Linguistic Inquiry and Word Count (LIWC) to analyze 110,283 tweets sent pre-crisis and during the first wave of COVID-19.

The results of the exploratory analysis revealed a connection between crisis and both analytical thinking and emotional responses. In the case of emotions, the results also suggest that entrepreneurs who had already received funding from venture capital investors remained emotionally robust during the crisis, as evidenced by the expression of more positive emotions compared to entrepreneurs without funding.

This study contributes to the understanding of entrepreneurial communication and adds the context of an exogenous shock to this research stream. Furthermore, this study highlights the effects of venture funding on the digital communication style of entrepreneurs, especially in the context of expressed emotions, and suggests emotional robustness for these entrepreneurs.

This paper aims to address which resources provided by an entrepreneurial ecosystem (EE) are necessary for deep technology entrepreneurship.

The authors used a novel approach known as necessary condition analysis (NCA) to data on EEs and deep-tech startups from 132 countries, collected in a global innovation index and Crunchbase data sets. The NCA makes it possible to identify whether an EEs resource is a necessary condition that enables entrepreneurship.

Necessary conditions are related to political and business environment; education, research and development; general infrastructure; credit; trade; diversification and market size; and knowledge absorption capacity.

The results show that business and political environments are the most necessary conditions to drive deep-tech entrepreneurship.

Policymakers could prioritize conditions that maximize entrepreneurial output levels rather than focusing on less necessary elements.

Some resources require less performance than others. So, policymakers should consider allocating policy efforts to strengthen resources that maximize output levels.

Studies on deep-tech entrepreneurship are scarce. This study provides a bottleneck analysis that can guide the formulation of policies to support deep-tech entrepreneurship, as it allows to identify priority areas for resource allocation.