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Audretsch, David B.; Houweling, Patrick; Thurik, Roy

doi:10.1023/a:1007824501527

Cited by 115 publications

(16 citation statements)

References 16 publications

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“…We also find a negative impact of the share of R&D employment (employees with a degree in engineering or a natural science) in the particular industry, region and year on the survival chances of new businesses in many of the models. This confirms the findings of Brüderl, Preisendörfer and Ziegler (1996), Grotz and Brixy (2002) as well as of Audretsch (1995) and Audretsch, Houweling and Thurik (2000). There are three possible explanations for the negative sign of the regression coefficient.…”

Section: Resultssupporting

confidence: 90%

“…Therefore, larger start-ups may have less difficulty attaining the breakeven point than smaller ones. Because the minimum efficient size varies from industry to industry, survival rates should be higher in industries where the minimum efficient size is relatively small (Audretsch, Houweling and Thurik, 2000;Tvetrås and Eide, 2000). Accordingly, high capital intensity in an industry may be expected to hinder the set-up and survival of new firms due to the relatively large amount of resources that is needed for attaining the minimum efficient size (Audretsch, Houweling and Thurik, 2000;Mayer and Chappell, 1992).…”

Section: Hypothesesmentioning

confidence: 99%

“…Because the minimum efficient size varies from industry to industry, survival rates should be higher in industries where the minimum efficient size is relatively small (Audretsch, Houweling and Thurik, 2000;Tvetrås and Eide, 2000). Accordingly, high capital intensity in an industry may be expected to hinder the set-up and survival of new firms due to the relatively large amount of resources that is needed for attaining the minimum efficient size (Audretsch, Houweling and Thurik, 2000;Mayer and Chappell, 1992). However, relatively distinct barriers to entry such as a large minimum efficient size or high capital intensity could also induce a self-selection process that results in relatively few but high-quality startups with above-average chances of surviving (Dunne and Roberts, 1991).…”

Section: Hypothesesmentioning

confidence: 99%

“…Significant market power of the incumbents may imply low prospects for successful entry (Ilmakunnas and Topi, 1999;Rosenbaum, 1993). It could, however, also be the case that market concentration and market power result in a relatively high price level that provides favorable economic conditions (Audretsch, Houweling and Thurik, 2000). Given the presence of such an 'umbrella effect', start-ups may have relatively good chances of survival.…”

Section: Hypothesesmentioning

confidence: 99%

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The Effect of Industry, Region, and Time on New Business Survival – A Multi-Dimensional Analysis

2006

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Section: Resultssupporting

confidence: 90%

Section: Hypothesesmentioning

confidence: 99%

Section: Hypothesesmentioning

confidence: 99%

Section: Hypothesesmentioning

confidence: 99%

See 2 more Smart Citations

The Effect of Industry, Region, and Time on New Business Survival – A Multi-Dimensional Analysis

2006

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“…Though the result of the negative impact is contrary to the theoretical assumption and some empirical results, like of Baggs (2005), similar results can still be found frompast research, for example the research of Audretsch et al (2000) where the negative effect of industry growth is kept till age 8. So the statement of Audretsch et al (2000) that uncertainty is entwined with industry's high growth could be employed to explain the negative effect; however, this effect seems to be maintained at early ages, because positive effect emerges later.…”

Section: Conclusion Implication and Future Researchsupporting

confidence: 60%

The predictability of financial, accounting‐based, and industrial factors on the success of newly incorporated Spanish firms

Tong

Solé

2018

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Purpose: The purpose of this paper is to identify the impacts and predictability of financial, accounting-based, and industrial factors (as well as corporate venturing) on survival-based success of newly incorporated firms in Spain.Design/methodology: Logistic regression is used for comparing the differences of factors in the prediction of future success after different time periods since the studying years (age 1, age 2, and age 3 respectively) in manufacturing and distributive sectors.Findings: Differences in predictability are observed between manufacturing and distributive sectors: it is obvious in distributive sector (rather than manufacturing sector) that liquidity, bank credit, trade credit, and concentration are positively related to success while entry rate is negatively related to success. In spite of that, some factors still show strong predictability in both two sectors. Firm size and profitability are the strongest positive factors, which are followed by corporate venturing and the growth of industrial operating revenues with positive and generally negative relationships to success separately. Besides, for some factors and variables frequently showing statistical significance, their impacts in the same age tend to be relatively stable. Practical implications:The findings of this paper can help to identify the predictability of different factors on the success of newly incorporated firms and catch the differences between manufacturing and distributive sectors.Originality/value: This paper enriches the empirical study of new firm success in Spain in depression and stagnant environment (because the observed years here are from 2009 to 2014); besides, the findings also contribute to the specific prediction study of manufacturing and distributive sectors.

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Analysis of the determinants of survival for the Russian commercial banking industry: A new approach

Orbe

Núñez‐Antón

2010

Appl. Stochastic Models Bus. Ind.

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We propose the study of the relevant factors for the survival of Russian commercial banks during the transition period. The accelerated development of the Russian commercial banking industry after the banking reform caused high rates of entry followed by a period of high rates of exit. As a consequence, many banks had to exit the market without refunding their deposits. Therefore, both for the banks and for the banks' depositors, it is of interest to identify the relevant factors that motivate the exit or the closing of the bank. We propose a different methodology based on penalized weighted least squares that represents a very general, flexible and innovative approach for this type of analysis. That is, the proposed methodology does not require the assumptions of a probability distribution for the variable under study or of any covariate parametric functional form for the covariate whose effect on the survival variable we wish to address.

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Untitled

Cited by 115 publications

References 16 publications

The Effect of Industry, Region, and Time on New Business Survival – A Multi-Dimensional Analysis

The Effect of Industry, Region, and Time on New Business Survival – A Multi-Dimensional Analysis

The predictability of financial, accounting‐based, and industrial factors on the success of newly incorporated Spanish firms

Analysis of the determinants of survival for the Russian commercial banking industry: A new approach

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