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This 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.

The 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.

The 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.

The 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.

For 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.

In 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.

Staged financing is a prominent feature of the venture capital investment process. With staged financing, venture capitalists (VCs) may choose to either make an investment or delay it at each round. The purpose of this paper is to investigate the influence of market uncertainty, project-specific uncertainty and agency problems on these decisions.

The study uses data from Indian firms that received venture capital funding between 2000 and 2017. The duration between funding rounds is analysed using survival analysis. An accelerated failure time model is used to estimate the influence of market uncertainty, project-specific uncertainty and agency problems on the length of time between funding rounds.

VCs delay investment when there are high levels of uncertainty in the market; if market uncertainty increases by 1%, delay in funding increases by more than 6% (almost a month) on average. There is no statistically significant relationship found between the funding duration and project-specific uncertainty. Agency problems motivate VCs to invest sooner. An increase in agency problems results in a reduction of 55% (almost five months) in the length of time before the next funding round.

This study has useful business policy implications. It provides VCs with real option value drivers such as market uncertainty, agency problems, which influence the timing of decisions in staged investment processes. It will help to make the choice between investing and delaying at each round of financing more robust. Further, it is useful for VCs to differentiate between market uncertainty and agency problems against the backdrop of their different implications for staging decisions.

Few studies have examined staging decisions from a real options perspective in the context of a developed economy and very few from a developing economy perspective. This study increases understanding of staging decisions in the Indian context.

The venture capital and private equity (VCPE) industry in India has grown significantly in recent years. During five‐year period 2004‐2008, the industry growth rate in India was the fastest globally and it rose to occupy the number three slot worldwide in terms of quantum of investments. However, academic research on the Indian VCPE industry has been limited. This paper seeks to fill the gap in research on the recent trends in the Indian VCPE industry.

Studies on the VCPE transactions have traditionally focused on one of the components of the investment lifecycle, i.e. investments, monitoring, or exit. This study is based on analyzing the investment life cycle in its entirety, from the time of investment by the VCPE fund till the time of exit. The analysis was based on a total of 1,912 VCPE transactions involving 1,503 firms during the years 2004‐2008.

Most VCPE investments were in late stage financing and took place many years after the incorporation of the investee firm. The industry was also characterized by the short duration of the investments. The type of exit was well predicted by the type of industry, financing stage, region of investment, and type of VCPE fund.

This paper highlights some of the key areas to ensure sustainable growth of the industry. Early stage funding opportunities should be increased to ensure that there is a strong pipeline of investment opportunities for late stage investors. VCPE investments should be seen as long‐term investments and not as “quick flips”. To achieve this, it is important to have a strong domestic VCPE industry which can stay invested in the portfolio company for a longer term.

Financing investments in a knowledge-intensive sector may be more difficult as there is a greater degree of uncertainty and asymmetries of information. This paper aims to examine whether a company’s intellectual capital (human capital, relational capital and structural capital) can serve as a quality signal in the financing of health care startups with new business models.

The study constructed a manual database using several paid and unpaid databases. This paper collected random data from 204 startups that obtained funding during the 2014–2017 period and used signaling theory to examine the factors that impact access to external financing for Indian health care technology startups.

This paper found that venture capitalists partly base their financing decisions on the relational capital of the startup represented by startups’ age and the average number of website visits, the presence of a syndicate of investors. Human capital variables and structural variables do not show much significant impact. This paper also find some business models show a negative impact on financing implying that investors are reluctant to invest in new technologies that carry more uncertainty and take a longer time to become profitable.

Before concluding this paper, it is important to acknowledge the limitations of the study and some implications for future research purposes. First, the study is conducted on only 204 startups from India, and as such, it suffers from a small sample size, like many other comparable survey-based studies in entrepreneurship. Second, the results are obtained with respect to data collected from Indian startups and represent the Indian context which limits the generalization on a global level.

The results suggest that years of experience and prior relevant experience, do not actually impact the financing of a new venture. These results are crucial as India has a unique demographic advantage over other countries in relation to age. If young minds are adequately nurtured, this can result in innovation, entrepreneurship and job creation (which still remains as a foremost challenge for India).

From a policy perspective, a number of implications emerge from the current study. There is a need for ameliorating the capacity of the education system in providing top-quality support including a greater focus on entrepreneurship courses and to replicate the education delivery model from top foreign institutes. The government should take this opportunity to revive the system of education and follow the methodology of elite institutes and to develop entrepreneurship spirit in other colleges and schools.

Financing the investments of young startups with new business models in knowledge-based sectors may be more difficult. In this paper, this paper demonstrates that startups have to effectively use and manage their intellectual assets to achieve sustainable competitive advantage. The findings of the paper emphasize the role of intellectual capital in securing financing through venture capital.

This study aims to examine the venture capital (VC) industry in China. It has demonstrated a history of high growth with significant variations over time. The authors have examined the trends and determinants of VC investments in China over a 20-year period from 1995 to 2014. They find that the aggregate amount of VC investments, the total number of venture deals and the average amount of venture investments per deal in China are all significantly impacted by macroeconomic conditions (i.e. GDP, export, money supply), technology innovations and financial market indicators (i.e. initial public offerings (IPOs), interest rate, price-to-earnings ratio, etc.). They also find that the 2007 China A-Share stock market crash and the subsequent global financial crisis have motivated VCists in China to adjust their investment strategies and risk levels by allocating more capital to later-stage investments and securing more deals with later-round financings. However, after the 2008 global financial crisis, the China’s venture industry has recovered faster compared to the US counterpart response.

The authors first perform trend analysis of VC investments at an aggregate level, by stages of development, and across industry from 1995 to 2014.To test H1 and H2, the authors use multiple regression models with lagged explanatory variables. To test H3, the authors use univariate tests to compare the measures of VC investments at an aggregate level, stage funds ratios, stage deals ratios and financing series ratios during both a five-year and seven-year time windows around the 2007 A-Share stock market crash and the subsequent financial crisis.

The development of the VC industry in China has demonstrated a history of high growth with significant variation over time. The authors find that the aggregate amount of VC investments, the total number of venture deals and the average amount of venture investments per deal in China are all significantly impacted by macroeconomic conditions (i.e. GDP, export, money supply), technology innovations and financial market indicators (i.e. IPOs, interest rate, price-to-earnings ratio, etc.). The authors also find that the 2007 China A-Share stock market crash and the subsequent global financial crisis have motivated VCists in China to adjust their investment strategies and risk by allocating more capital to later-stage investments and securing more deals with later-round financings. However, the China VC industry has recovered faster compared to the USA just after the 2008 global financial crisis.

There are also limitations in the study. The VC data in China in the earlier 1990s might not be very reliable due to the quality of statistics. Therefore, the trend analysis and discussions mainly focus on the time after 2000. Also, the authors cannot find VC financing sequence data for the analysis. Second, there is no doubt that the policy impact from Chinese transforming economic system and government policies on its VC industry is substantial (Su and Wang, 2013). However, they cannot find an appropriate variable to be included in the empirical models to consider this effect. Further study on this area would provide meaningful information. Third, although the authors have done comparison study between the VC industry in China in this study and the VC industry in the US documented in Ning et al. (2015) and discussed some interesting findings, more in-depth research in this area will be very useful.

The findings have meaningful implications for VCists and start-up companies seeking equity financings in China. VCists should closely monitor macroeconomic and market conditions to make appropriate adjustments to their risk and investment strategies. Entrepreneurs seeking equity financings for their business could also monitor the identified macroeconomic and market indicators, which can help them with their timing and to negotiate a better equity financing deal. VC financing is more likely to succeed when key macroeconomic and market indicators become favorable.

This paper contributes to the literature by testing the supply and demand theory on the VC market proposed by Poterba (1989) and Gompers and Lerner (1998) from the macroeconomic perspective using 20 years’ VC data from China. The authors also examine how the 2007 A-Share stock market crash and the subsequent financial crisis affected VCists to adjust their risk levels and investment strategies. It provides useful information for international academia and policymakers to understand the quick rise of China VC industry. The authors also find that the macroeconomic drivers of VC industry are somewhat different under different economic systems.

Most entrepreneurs are continually concerned about their finances. Their companies perhaps not yet profitable, they may have a fear of “running out of dry powder.” These entrepreneurs often have fallen in love with their company's technologies, products, and potential markets, but they require more resources. Invariably these emerging ventures shroud their fear of the grueling capital raising marathon by presenting voluminous business plans to potential investors. They often flaunt their “optimized business models.”” Investors, however, typically want to know why the potential investment is such a good deal. The entrepreneur often wants guidance regarding what to say to whom in a changing financing environment.

In this article, our “Practitioner's Corner” associate editor Joe Levangie collaborates with a long-time colleague Paul Broude to address how businesses should “make their capital-raising initiatives happen.” Levangie, a venture advisor and entrepreneur, first worked with Broude, a business and securities attorney, in 1985 when they went to London to pursue financing for an American startup. They successfully survived all-night drafting sessions, late-night clubbing by the company founder, and even skeet shooting and barbequing at the investment banker's country house to achieve the first “Greenfield” flotation by an American company on the Unlisted Securities Market of the London Stock Exchange. To ascertain how the entrepreneur can determine what financing options exist in today's investing climate, read on.

Institutional venture capitalists (IVCs) and corporate venture capitalists (CVCs) deploy analogous activities but adopt different approaches to financing innovation and value creation for venture-backed firms. Thus, this paper aims to investigate their potential ambidexterity as a result of knowledge management (KM) strategies and processes.

After a focused literature review showing evidence of KM behaviors as a source of potential ambidexterity for IVCs and CVCs, descriptive, inferential and discriminant analyses on the 15 most active IVCs and CVCs in the world in 2019 are presented. Correlations between numbers of deals, prevailing entrepreneurial intensity and potential ambidexterity are investigated.

Specific differences are analyzed from a KM perspective, revealing that the number/percentage of operations per round can result as a misleading criterion of knowledge accumulation. Finally, a theoretical model for ambidexterity for venture capitalists is developed.

The study shows that IVCs act with greater investment capacity because of their organizational structure and purpose and focus on financial goals; moreover, they are ambidextrous, although their exploration may more frequently entail exploitation than “real” exploration. CVCs tend to invest in sectors related to their core business, coherent with their strategic purpose and more oriented with KM strategies for accumulating intellectual capital.

This paper aims to examine the relative performance of multilateral development banks venture capital funds (MDBVCs) compared to that of government-sponsored venture capital funds (GVCs), assessing their impact on invested start-ups.

First, the authors survey the literature to understand the performance drivers of public programs designed to foster venture capital (VC). Second, the authors analyze the characteristics of multilateral development banks (MDBs) VC-related efforts. Third, based on their goals, structure, governance and management processes, the authors propose and test the hypothesis that MDBs initiatives outperform comparable public programs, overcoming the main limitations of the latter.

The authors find that start-ups funded by MDBVCs outperform GVC-funded start-ups in terms of access to subsequent financing and international expansion. Consistent with previous studies, the authors find that start-ups funded by private VCs show the highest levels of performance.

The paper features an unstudied actor – i.e. MDBVCs-, and an unstudied region – i.e., Latin America-, using a unique data set of 437 start-ups that received VC investments in 7 Latin American countries during the study period 2000–2018.

This paper aims to explore the financing mechanisms towards Mars commercialisation and SpaceX’s Mars mission programme to achieve the interplanetary settlement. This study also suggests the path to avoid the failure of space commercialisation.

This research uses a case study methodology (Eisenhardt, 1989; Yin, 2013). The analysis is based on the construct of technology S-curves and attempts to answer the research question: What are the financing mechanisms to achieve successful aerospace financing for Mars mission? This research used semi-structured questionnaire and conducted 51 in-depth interviews. The interview data were supported by an examination of secondary data to provide a cross check on the validity of research (Yin, 2013). The research findings provide lessons and insights into the challenges of aerospace financing to Mars.

This study has shown that financing via cryptocurrency and initial coin offering as well as crowdfunding (particularly donation- and equity-based crowdfunding) provide promising financial solutions to achieve Mars commercialisation. The implementation of Mars programme demonstrates the fifth generation of innovation development model – systems integration and extensive networking model.

Given a dearth of study focusing on the links between S-curves and technology financing of aerospace commercialisation, this research study attempts to fill a gap in this neglected area with a focus on exploring the financing mechanisms towards Mars commercialisation.

This paper provides a structural model to value startup companies and determine the optimal level of research and development (R&D) spending by these companies.

This paper describes a new variant of float-the-money options, which can act as a financial instrument for financing R&D expenses for a specific time horizon or development stage, allowing the investor to share in the startup's value appreciation over that duration. Another innovation of this paper is that it develops a structural model for evaluating optimal level of R&D spending over a given time horizon. The paper deploys the Gompertz-Cox model for the R&D project outcomes, which facilitates investigation of how increased level of R&D input can enhance the company's value growth.

The author first introduces a time-varying drift term into standard Black-Scholes model to account for the varying growth rates of the startup at different stages, and the author interprets venture capital's investment in the startup as a “float-the-money” option. The author then incorporates the probabilities of startup failures at multiple stages into their financial valuation. The author gets a closed-form pricing formula for the contingent option of value appreciation. Finally, the author utilizes Cox proportional hazards model to analyze the optimal level of R&D input that maximizes the return on investment.

The integrated contingent claims model links the change in the financial valuation of startups with the incremental R&D spending. The Gompertz-Cox contingency model for R&D success rate is used to quantify the optimal level of R&D input. This model assumption may be simplistic, but nevertheless illustrative.

Once supplemented with actual transaction data, the model can serve as a reference benchmark valuation of new project deals and previously invested projects seeking exit.

The integrated structural model can potentially have much wider applications beyond valuation of startup companies. For instance, in valuing a company's risk management, the level of R&D spending in the model can be replaced by the company's budget for risk management. As another promising application, in evaluating a country's economic growth rate in the face of rising climate risks, the level of R&D spending in this paper can be replaced by a country's investment in addressing climate risks.

This paper is the first to develop an integrated valuation model for startups by combining the real-world R&D project contingencies with risk-neutral valuation of the potential payoffs.