The rise and fall of startups: Creation and destruction of revenue and jobs by young companies

Dávila, Antonio; Foster, George; He, Xinming; Shimizu, Carlos

doi:10.1177/0312896214525793

Cited by 45 publications

(23 citation statements)

References 32 publications

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“…decline). We agree with Davila et al (2015) that the research community has focussed disproportionately upon both growth and high growth. 18 Detailed data on fractional or part-time employees, total wage bill, or total hours worked, are extremely unusual in longitudinal databases on new venture performance.…”

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confidence: 59%

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Predicting new venture survival and growth: Does the fog lift?

et al. 2016

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This paper investigates whether new venture performance becomes easier to predict as the venture ages: does the fog lift? To address this question we primarily draw upon a theoretical framework, initially formulated in a managerial context by Levinthal (Adm Sci Q 36(3):397-420, 1991) that sees new venture sales as a random walk but survival being determined by the stock of available resources (proxied by size). We derive theoretical predictions that are tested with a 10-year cohort of 6579 UK new ventures in the UK. We observe that our ability to predict firm growth deteriorates in the years after entry-in terms of the selection environment, the 'fog' seems to thicken. However, our survival predictions improve with time-implying that the 'fog' does lift.

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confidence: 59%

“…The mean growth rate is negative in every single year, although the median growth rate is only negative in 3 years. The term 'sales growth,' when applied to NVs, is for this reason potentially misleading if it is not understood that growth rates can be negative (Davila et al 2015). Indeed, negative growth rates (i.e.…”

Section: Summary Statisticsmentioning

confidence: 99%

Predicting new venture survival and growth: Does the fog lift?

et al. 2016

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“…The success of startups is important for economies investing on innovations and growth. Therefore, especially the early years of startups have been popular themes of business research, literature, and government policy debate [1]. Startups are necessary for the creative destruction process as they enter the market and replace old and stagnant firms [2].…”

Section: Introductionmentioning

confidence: 99%

“…This means that the time-series of cash flow are in this study described using parameters that characterize the target startup in a relevant way. In reality, the time-series of startups are usually nonstationary [1] [11] [12] [13]. Prior studies generally indicate that the development of startups is non-linear and prone to interruptions and setbacks, which are stochastic and quite difficult to explain using different variables and processes [11].…”

Section: Introductionmentioning

confidence: 99%

Discounted Cash Flow (DCF) as a Measure of Startup Financial Success

Laitinen¹

2019

TEL

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The purpose of the study is to investigate the characteristics of the discounted cash flow (DCF) as a measure of startup financial success. In general, DCF is found the most popular method in startup valuation followed by the internal rate of return (IRR) and the payback period methods. However, the consequences of using this method in startup valuation are rarely analyzed in financial research. In this study, a simplified mathematical model is developed to describe the time-series development of the cash flow. This model is based on the growth of expenditures and their ability to generate revenues from the founding of the startup. The model employs IRR as the measure of true profitability and the average lagin revenue generation as a proxy of the payback period. Numerical experiments are used to show the sensitivity of DCF to the parameters of the model. The results indicate that the use of DCF favors startups that grow slowly and have a short payback period but that also exhibit a high IRR. The longer the time series of the startup used in the analysis, the more significant role IRR tends to play in DCF. Empirical evidence extracted from a sample of Finnish startups supports the numerical findings.

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“…Research studies, however, do not shed light on the structure and consequences of the business model of start-ups. Davila et al (2015) draw attention that the start-up enters an established market with a business model that ex-post turns out to be economically nonviable. Kopera et al (2018) explain that a source of success is rarely a technological superiority alone but rather a business model that stays behind.…”

Section: Introductionmentioning

confidence: 99%

The Business Model of Start-Up—Structure and Consequences

Slávik

2019

Administrative Sciences

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A start-up already at its origin has to solve the crucial existential condition that is a viable business model. The purpose of the research is to deepen and expand the knowledge about the structure of the start-up business model and its impact on entrepreneurial performance. Field research was carried out in three stages over one and a half years. The source of knowledge about the studied start-ups has been the personal experience recorded in the questionnaire. Start-ups are small closed communities that do not sufficiently shape external partnerships, cannot reach the customers, although they can identify them well enough, try to improve the business model blocks but they do not pay attention to their coordination and perceive the monetization in a simplified way. The impact of the business model on start-up performance has been confirmed but the internal blocks affect business performance unambiguously over the three stages of the research. The best conversion of users to customers and subsequently to revenues are distinctive for the start-ups with their own simple distribution channel and partners who are experienced distributors. The lessons learned can directly improve the results of start-ups when their incompleteness and imperfection will be substituted by appropriate partners. Start-ups provide a space for the new jobs and the self-realization of ambitious people with a sense of service for society. Empirical research on start-ups identifies their weaknesses and possibilities to increase their entrepreneurial performance.

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The rise and fall of startups: Creation and destruction of revenue and jobs by young companies

Cited by 45 publications

References 32 publications

Predicting new venture survival and growth: Does the fog lift?

Predicting new venture survival and growth: Does the fog lift?

Discounted Cash Flow (DCF) as a Measure of Startup Financial Success

The Business Model of Start-Up—Structure and Consequences

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