What could we learn from startup failures?

Abstract This study aimed to empirically investigate resource-based and dynamic capability theories in startup failures, categorize factors that contributed to failures, and study the gender effect on startup failure. Data consists of 40 information and communication technology startups in the voluntary liquidation phase. The questionnaire technique was developed based on SHELL model. Research questions were investigated using principal component analysis, Ward’s hierarchical cluster, and cross-table analysis. The main identified groups of startup failure factors are mostly dynamic capabilities, supporting dynamic capability over a resource-based view. The lack of dynamic capabilities is clearly identifiable in one subgroup of failed startups. The relevance of some failure factors changes with the life cycle of startups. This study found a positive relationship between the presence of female founders and the startup survival. Besides, it highlights the importance of innovation and corporate foresight training programs, mentorship access, and the need to strengthen project screening standards by focusing more on dynamic capabilities. This study underpins the necessity to develop policies easing the gender gap. These would improve the efficiency of the startup ecosystem and entail positive social effects.

Authors

Institutions

Publication Details

Journal
Journal of Innovation and Entrepreneurship
Published
2025-03-28
DOI
https://doi.org/10.1186/s13731-025-00493-w
Citations
4
Primary Topic
Private Equity and Venture Capital
Type
article
Field-Weighted Citation Impact
15.64

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

What could we learn from startup failures?

Szilárd Hegedűs, Árpád Szőcs, András Bethlendi
4 citations
Journal of Innovation and Entrepreneurship
Private Equity and Venture Capital
15.64
article

What could we learn from startup failures?

Szilárd Hegedűs, Árpád Szőcs, András Bethlendi
article en
4 citations

Abstract

Abstract This study aimed to empirically investigate resource-based and dynamic capability theories in startup failures, categorize factors that contributed to failures, and study the gender effect on startup failure. Data consists of 40 information and communication technology startups in the voluntary liquidation phase. The questionnaire technique was developed based on SHELL model. Research questions were investigated using principal component analysis, Ward’s hierarchical cluster, and cross-table analysis. The main identified groups of startup failure factors are mostly dynamic capabilities, supporting dynamic capability over a resource-based view. The lack of dynamic capabilities is clearly identifiable in one subgroup of failed startups. The relevance of some failure factors changes with the life cycle of startups. This study found a positive relationship between the presence of female founders and the startup survival. Besides, it highlights the importance of innovation and corporate foresight training programs, mentorship access, and the need to strengthen project screening standards by focusing more on dynamic capabilities. This study underpins the necessity to develop policies easing the gender gap. These would improve the efficiency of the startup ecosystem and entail positive social effects.

Journal of Innovation and EntrepreneurshipVol. 14(1)
Budapest University of Economics and Business (HU), Budapest University of Technology and Economics (HU)
Budapesti Műszaki és Gazdaságtudományi Egyetem, Magyar Tudományos Akadémia
Openalex Percentile: Top 1%
Private Equity and Venture Capital
15.64
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.