Search results

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.

The purpose of this paper is to explore the relationship between low-wealth business founders in the USA and external startup funding. Specifically, the authors test whether a founders’ low personal net worth is correlated with a lower probability of acquiring funding from outside sources during the business creation process.

The authors use a double-hurdle Cragg model to jointly estimate: first, the decision to acquire external financing; and second, the amount received. The sample is the US-based Panel Study of Entrepreneurial Dynamics II (PSED II). The PSED II tracks business founders attempting to start ventures from 2005 to 2012.

Receipt of outside financing during business formation is largely determined by the business founder’s personal finances (controlling for human capital, venture type and industry, and whether money was sought in the first place). A higher household net worth results in larger amounts of external funding received. Low-wealth business founders, therefore, are less likely to get external funds, and they receive lower amounts when they do. The disparity between low-and high-wealth business founders is more pronounced for formal, monitored sources of external financing such as bank loans.

Because the study eliminates survivor bias by using a nationally representative sample of business founders who are in the venture creation process, the findings apply to both successful business founders and those who disengaged during the business creation process. The authors offer insights into the sources and amounts of external funds acquired by individuals across all levels of wealth. The authors accomplish this by disaggregating business founders into wealth quintiles. The study demonstrates the importance of personal wealth as a factor in acquiring external startup financing compared to human capital, industry, or personal characteristics.

If the ability to acquire external funding is significantly constrained, the quality of the opportunity and the skill of the business founder may be less a determinant of success at creating a new business as prior studies have suggested. Consequently, entrepreneurship (as measured by business formation) as a path toward upward, socioeconomic mobility will be afforded only to those individuals with sufficient financial endowments at the outset.

Unlike prior studies, the data used are not subject to survivor bias or an underrepresentation of self-employment. The statistical model jointly estimates acquisition of financing and the amount received. This resolves selection and censoring problems. Finally, the dependent variables directly measure liquidity constraints in the context of business formation, that is, before a new venture is created. Prior research contexts have typically studied existing businesses, and are therefore not true examinations of conditions affecting business creation.

This study offers empirical evidence from a nationally representative panel dataset of nascent entrepreneurs (PSED-II) regarding when external financing is acquired and how certain factors affect this timing during the cumulative process of nascent entrepreneurs taking actions toward establishing an operational entity. By assessing the relationship between the external financing event and the cumulative set of actions that nascent entrepreneurs undertake to create new businesses, we improve our understanding of how the timing of acquiring external financing affects organizational survival and growth.

We apply nonparametric and semiparametric survival analysis techniques to a nationally representative panel dataset of nascent entrepreneurs. This ascertains the probability of an external financing event at any given moment in time and a set of startup conditions that we hypothesize will affect this timing. First, we use Kaplan–Meier analysis to explore when external financing occurs during new business creation. We then use discrete-time survival analysis to investigate whether certain startup conditions affect when external financing occurs. Finally, we conduct a test of independence to examine the external financing event relative to other startup activities completed during new business creation.

Nascent entrepreneurs tend to acquire external funding relatively late in the new venture startup process – on average, about two-thirds of the way from conceiving of the idea and becoming operational. They tend to take actions that are less resource-demanding early in the startup process to build their organizations to a fundable stage. Net worth tends to speed up the acquisition of external funding as wealthy entrepreneurs tend to ask for funding earlier in the process. Finally, entrepreneurs in capital-intensive industries do not seem to get outside funding before entrepreneurs in other industries.

This study is unique in three ways. First, we investigate the timing of the highly important external financing event. Timing is critical in unpacking and making sense of the very early stages of a new business and in guiding entrepreneurs and students about when to do what. Second, we do so in a subsample of preoperational, nascent, funded entrepreneurs derived from a nationally representative panel dataset of startup attempts. Third, our findings provide a counter-intuitive yet systematic understanding of organizational emergence and very early-stage financing.

The operational framework of external financing in the correlation between the gender of entrepreneurs and firm performance remains to be resolved. This study aims to investigate the mediating effect of external financing on gender-based disparities in private firm performance and to explore its heterogeneity within the Chinese context.

Based on national data from the 10th to 13th Chinese Private Enterprise Survey, this study used a bootstrap-based mediation effect model to analyze the role of external financing as a mediator in the relationship between entrepreneur gender and firm performance.

This study found that external financing is a constructive mediator between entrepreneur gender and firm performance. Heterogeneity analysis revealed that external financing plays a complementary mediation role in the impact of entrepreneur gender on performance in West China. In the tertiary industry, external financing acts as the sole mediator for the impact of gender on firm performance. Notably, this mediating effect is present in non-startups but not in startups.

The findings suggest that external financing can improve the firm performance of female entrepreneurs. Governments and policymakers should strengthen financial support for female entrepreneurs in West China, tertiary industry and non-startup enterprises.

This paper contributes to the literature on gender and corporate governance by shedding light on the mediating role of external financing in the relationship between the gender of business owners and firm performance.

The purpose of this paper is to ascertain the factors determining the choice of sources of finance for a tech startup over its lifecycle.

This study adopts simple random sampling technique to choose 93 sample tech startups in Bangalore. Further, this study employs the primary data collection from the sampled startups under study through a semi-structured questionnaire and in-depth interviews with the founders/CEOs of these startups. Furthermore, it carries out binary logistic regression analysis to primarily examine the likelihood of a tech startup to approach and access a particular source of finance over its lifecycle.

Our results indicate that a tech startup's choice for a financial source varies with its lifecycle stage and financial requirements. We find that while in its early stage, a tech startup's choice of a financial source is limited to business angels (BA), in the growth stage, it approaches the institutional sources, viz. Venture Capital (VC), Corporate Venture Capital (CVC), Banks and Private Equity (PE) firms alternatively. Out of the three major categories of financial requirements: Human Capital (HC), Research Capital (RC) and Social Capital (SC), the requirement for HC and SC is predominantly funded by VCs, while the acquisition of RC is facilitated by early stage investors (BAs) as well as growth stage investors (CVC and PEs).

The research implication of the study lies in bringing out the need to understand both the nature and the quantum of financial requirements of tech startups would influence the sources of finance it would approach and obtain finance for its operations and growth.

The major policy implication of the study refers to the need to promote the diverse sources of finance to meet the diverse needs of finance in different stages of a tech startup's lifecycle. Particularly in an emerging economy, where we do not see the emergence and growth of highly innovative tech startups, the need to promote adequate availability of RC is especially important.

This study makes a key contribution to the entrepreneurial finance literature by empirically investigating the factors determining a tech startup's propensity to approach and access a particular source of finance over its lifecycle.

Using a novel monthly data set, this study aims to examine the factors affecting the funding of Indian start-ups.

Given the panel structure of the data, the fixed effects regression technique has been used.

The findings reveal that years of operation is a key factor. Amongst others, angel investors and equity financing are the key drivers of startup financing. Government policy does not appear to have gained adequate traction, although the improvement in the business reform action by state governments has begun to exert a salutary effect.

From a policy standpoint, the study provides insights into what policies and practices can be exploited to streamline the funding bottlenecks affecting startups in the Indian context.

Notwithstanding being a country with a significant presence in the startup space, there are admittedly limited studies, which examine this issue for India. Viewed from this standpoint to the best of the knowledge, the analysis is one of the early studies to shed light on the factors driving the funding of startups in the Indian context.

This paper aims to explain the fundraising and valuation processes of startups and discuss the conflicts of interest between entrepreneurs, venture capital (VC) firms and stakeholders in the context of startup corporate governance. Further, this paper uses the examples of WeWork and Zenefits to explain how a failure of stakeholders to demand an external audit from an independent accounting firm in early stages of funding led to an opportunity for fraud.

The methodology used is a literature review and analysis of startup valuation combined with the Fraud Triangle Theory. This paper also provides a discussion of WeWork and Zenefits, both highly visible examples of startup fraud, and explores an increased role for independent external auditors in fraud risk mitigation on behalf of stakeholders prior to an initial public offering (IPO).

This paper documents a number of fraud risks posed by the “fake it till you make it” ethos and investor behavior and pricing in the world of entrepreneurial finance and VC, which could be mitigated by a greater awareness of startup stakeholders of the value of an external audit performed by an independent accounting firm prior to an IPO.

An implication of this paper is that regulators should consider greater oversight of the startup financing process and potentially take steps to facilitate greater independence of participants in the IPO process.

Given the potential conflicts of interest between VC firms, investment banks and startup founders, the investors at the time of an IPO may be exposed to the risk that the shares of the IPO firms are overvalued at offering.

This study demonstrates how startup practices can be extended to the Fraud Triangle and issue a call to action for the accounting profession to take a greater role in protecting the public from startup fraud. This study then offers recommendations for regulators and standards entities.

There are few academic papers in the financial crime literature that link the valuation and culture of startup firms with fraud risk. This study provides a concise explanation of the process of valuation for startups and highlights the considerations for stakeholders in assessing fraud risk. In addition, this study documents an emerging role for auditors as stewards of proper valuation for pre-IPO firms.

This study aims to examine which categories of management control systems (MCSs) in startups are most important to external financiers. Furthermore, this paper investigates how equity and debt financiers differ in their perceptions of MCS categories and examines the relevance of MCSs for their investment decisions.

This study collects data through a cross-sectional survey sent to equity and debt financiers actively investing in startups. The results are based on survey responses from 73 financiers.

The results show that financial MCSs are considered most important, followed by strategic MCSs, while human resources MCSs are perceived as only moderately important. This paper finds significant differences in the perceived importance of MCS categories between equity and debt providers, which can be explained by differing risk profiles and monitoring needs. Although debt financiers consider financial and strategic MCSs to be less important for their portfolios’ startups than equity financiers do, debt financiers perceive MCSs as more important for their initial investment decisions.

The study sheds new light on the importance of different MCS categories in startups by analyzing external financiers’ perceptions. Overall, the empirical study provides insights that are particularly valuable for startups seeking external financing for company growth.

To satisfy the demand of initial investor for above-average capital return and the expectation of entrepreneurial management to establish their own business, this paper aims to explore a dynamic equity allocation model in which the shareholding ratio of the technology-based entrepreneurial firm changes with its growth and profit. Based on the dynamic equity allocation model, the authors design a financing structure which not only ensures timely and adequately obtaining the fund but also avoids equity dilution and safeguards the integrity of equity.

The paper selects high-tech companies listed in China as the sample for empirical research to identify the role of stock incentive and uses model deduction to find the equitable quantized benchmark for entrepreneurial management equity allocation. The study uses capital exclusivity as an entry point to perform theoretical analysis and demonstrates how the equity allocation of a technology-based entrepreneurial firm changes dynamically as the presentation speed of entrepreneurial management’s human capital exclusivity accelerates. The paper then constructs a conceptual model to design the financing structure of the technology-based entrepreneurial firm.

The study finds that stock incentive upwardly regulates debt financing and downwardly regulates equity financing. Based on characteristics of technology-based entrepreneurial firms, the paper suggests that the immediate surplus capital increment can signify the increasing presentation speed of human capital exclusivity, and it is proposed as an equitable quantized benchmark for equity allocation to entrepreneurial management. Based on the dynamic equity allocation model, the paper designs an internal equity and external debt financing structure.

The conclusions enrich the theoretical foundation for entrepreneurial management to participate in residual claim and provide practical guidance for equity allocation and financing structure design in the context of mass entrepreneurship and innovation. The paper also sets up a conceptual framework for solving two major issues of the technology-based entrepreneurial firm: timely acquisition of external funding and lasting maintenance of entrepreneurial management stability.

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.