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on Entrepreneurship |
| By: | Joern Block; Miriam Gnad; Alexander S. Kritikos; Caroline Stiel |
| Abstract: | Despite substantial research on job satisfaction in self-employment, we know little about the specific consequences for the venture when job satisfaction declines after an external shock. Taking the COVID-19 pandemic as an example of an external shock and drawing on a sample of nearly 7, 000 self-employed individuals living in Germany, we investigate how declines in job satisfaction are related to investment decisions of self-employed individuals. Having separated job satisfaction into its financial and non-financial aspects, we build in our analysis on two complementary behavioral perspectives to predict how reductions in financial and non-financial job satisfaction relate to investments in venture development. Our results show that decreasing financial job satisfaction is positively related to time investments. This finding provides support for the performance feedback perspective, where negative performance, in terms of reduced financial job satisfaction, induces higher search efforts to improve the business situation. Moreover, we also observe that reductions in non-financial job satisfaction are negatively associated with both time and monetary investments. This supports the broadening-and-build perspective in that negative experiences – in the form of reduced non-financial job satisfaction – narrow the thought-action repertoire, thus hindering resource deployment. Implications of reduced job satisfaction on investment behavior are discussed. |
| Keywords: | Job satisfaction, investment decisions, self-employment and entrepreneurship, performance feedback perspective, broadening-and-build perspective, behavioral economics, economic psychology, Germany |
| JEL: | L26 J28 G11 |
| Date: | 2025 |
| URL: | https://d.repec.org/n?u=RePEc:diw:diwwpp:dp2142 |
| By: | Schneck, Stefan |
| Abstract: | This exploratory study examines the effects of parental socialization and parental role models at ages 7 to 10 on the entrepreneurial intentions of their children in adolescence. Analysis of German household data and more than 1, 400 observations shows a moderation effect between parental role models and socialization. An adolescent's willingness to become self-employed in the future is influenced by parental role models and moderated by parental child-rearing practices related to risk-taking during childhood. While child-rearing practices not focused on risk-avoidance reinforce the parental role model effect and increase an adolescent's intentions to become self-employed, parental child-rearing practices geared toward risk aversion nullify any positive effects of having self-employed parents as role models. Parental socialization during childhood thus casts a long-term shadow and may explain why some children with self-employed parents have as little intention of becoming self-employed as children of employees. Early parental socialization practices may, thus, contribute to explaining the lack of willing entrepreneurs and family business successors. |
| Keywords: | entrepreneurial intentions, life course theory, role model, self-employment, socialization |
| JEL: | L26 D19 |
| Date: | 2025 |
| URL: | https://d.repec.org/n?u=RePEc:zbw:glodps:1678 |
| By: | Fairlie, Robert W. (University of California, Los Angeles); Fossen, Frank M. (University of Nevada, Reno); Lyu, Ke (Nevada State University) |
| Abstract: | The COVID-19 pandemic delivered an unprecedented shock to business entry, with sharply contrasting effects on different types of startups. Using newly constructed administrative data from the Comprehensive Startup Panel covering the universe of U.S. startups, we provide the first official numbers of the pandemic’s impact on employer and nonemployer startup dynamics. Nonemployer startup formation declined substantially in 2020, while employer startups unexpectedly increased. Survival outcomes also diverged: nonemployer startup survival dropped markedly, whereas employer startup survival remained largely stable. These findings reveal a pronounced compositional shift and underscore the importance of designing policies tailored to nonemployer startups in economic crises. |
| Keywords: | survival, pandemic, COVID-19, nonemployers, employers, startups, entrepreneurship, resilience |
| JEL: | L26 E32 M13 |
| Date: | 2025–10 |
| URL: | https://d.repec.org/n?u=RePEc:iza:izadps:dp18160 |
| By: | António Afonso; M. Carmen Blanco-Arana; Ana J. Cisneros-Ruiz |
| Abstract: | The main aim of this paper is to empirically assess the impact of education and tax revenue on fostering new business creation in the OECD countries. To this end, we employ fixed effects and random effects models using panel data from 2006 to 2022, incorporating alternative conditions. Results confirm that while education and the economic situation are key pillars in fostering new business creation, the role of tax revenue in supporting economic development – and, by extension, new business formation – is fundamental, even if non-linear, with a threshold of 30% of GDP. Tax revenue collected by governments provides essential funding for public goods and services such as infrastructure, education, and innovation support programs, all of which contribute to creating an environment where new businesses can emerge and thrive. Our findings remain robust under the GMM estimation. |
| Keywords: | New Business; Tax Revenue; Education; Economic Growth; Panel Data. |
| JEL: | C23 H2 I2 M20 |
| Date: | 2025–10 |
| URL: | https://d.repec.org/n?u=RePEc:ise:remwps:wp03952025 |
| By: | Mukasa, Stanley; Sangwa, Sixbert |
| Abstract: | Background. African startups operate amid acute capital scarcity and fragmented institutions, which complicates credible quality revelation to investors. Purpose. Focusing on the venture as the unit of analysis, this study investigates how milestones pursued inside university-affiliated accelerators function as signals of venture quality under scarcity, and how entrepreneurial behaviors shape the clarity and credibility of those signals. Design/methodology/approach. We track 17 technology ventures across East- and West-African university accelerators over 185 venture-quarters, combining venture-level panel regressions, event-study analysis, and fuzzy-set QCA. Two composite measures—the Governance-Readiness Index and the Signal-Portfolio Index—capture internal capability building and externally legible signals. Findings. Ventures graduating from university-affiliated accelerators secured roughly three times more equity than matched non-accelerated peers, with heterogeneity explained by milestone attainment and the breadth/strength of signal portfolios. We articulate a signal–noise paradox: effectuation/bricolage behaviors enable survival and progress under constraint yet can appear ambiguous to investors, attenuating signal clarity unless paired with governance readiness and externally validated milestones. Originality/value. The paper elevates signaling theory as the primary lens for early-stage ventures in emerging-market contexts, treats effectuation/bricolage as behavioral mechanisms, and situates staged financing as process logic and triple-helix/institutional-voids as contextual moderators. In doing so, it refines entrepreneurial signaling theory for scarcity contexts and offers actionable diagnostics for accelerators and policymakers designing inclusive, quality-assuring programs. |
| Date: | 2025–10–08 |
| URL: | https://d.repec.org/n?u=RePEc:osf:socarx:6jafg_v1 |
| By: | Saeid Mashhadi; Amirhossein Saghezchi; Vesal Ghassemzadeh Kashani |
| Abstract: | This study develops an interpretable machine learning framework to forecast startup outcomes, including funding, patenting, and exit. A firm-quarter panel for 2010-2023 is constructed from Crunchbase and matched to U.S. Patent and Trademark Office (USPTO) data. Three horizons are evaluated: next funding within 12 months, patent-stock growth within 24 months, and exit through an initial public offering (IPO) or acquisition within 36 months. Preprocessing is fit on a development window (2010-2019) and applied without change to later cohorts to avoid leakage. Class imbalance is addressed using inverse-prevalence weights and the Synthetic Minority Oversampling Technique for Nominal and Continuous features (SMOTE-NC). Logistic regression and tree ensembles, including Random Forest, XGBoost, LightGBM, and CatBoost, are compared using the area under the precision-recall curve (PR-AUC) and the area under the receiver operating characteristic curve (AUROC). Patent, funding, and exit predictions achieve AUROC values of 0.921, 0.817, and 0.872, providing transparent and reproducible rankings for innovation finance. |
| Date: | 2025–10 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2510.09465 |
| By: | Mohammad Zeqi Yasin |
| Abstract: | Do industrial "superstars" help others up or crowd them out? We examine the relationship between the spillovers of superstar firms (those with the top market share in their industry) and the productivity dynamics in Indonesia. Employing data on Indonesian manufacturing firms from 2001 to 2015, we find that superstar exposures in the market raise both the productivity level and the growth of non-superstar firms through horizontal (within a sector-province) and vertical (across sectors) channels. When we distinguish by ownership, foreign superstars consistently encourage productivity except through the horizontal channel. In contrast, domestic superstars generate positive spillovers through both horizontal and vertical linkages, indicating that foreign firms do not solely drive positive externalities. Furthermore, despite overall productivity growth being positive in 2001-2015, the source of negative growth is mainly driven by within-group reallocation, evidence of misallocation among surviving firms, notably by domestic superstars. Although Indonesian superstar firms are more efficient in their operations, their relatively modest growth rates suggest a potential stagnation, which can be plausibly attributed to limited innovation activity or a slow pace of adopting new technologies. |
| Date: | 2025–10 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2510.11139 |
| By: | Corina Boar; Denis Gorea; Virgiliu Midrigan |
| Abstract: | We use firm-level data to document that private businesses experience large fluctuations in their profit shares. These are due to large, fat-tailed and transitory changes in output that are not fully accompanied by changes in their inputs. We interpret this evidence using a model of entrepreneurial dynamics. Because firms can limit their exposure to risk by operating at a smaller scale, our model predicts large macroeconomic losses from uninsurable business risk, much larger than those stemming from credit constraints. While self-financing allows entrepreneurs to quickly overcome credit constraints, even wealthy entrepreneurs remain considerably exposed to risk. |
| Keywords: | entrepreneurship, risk, credit constraints, misallocation |
| JEL: | E2 E44 G32 |
| Date: | 2025–10 |
| URL: | https://d.repec.org/n?u=RePEc:bis:biswps:1300 |
| By: | Oluwatosin Agbaakin (Indiana University Indianapolis) |
| Abstract: | Artificial Intelligence (AI) has transitioned from a futuristic concept reserved for large corporations to a present-day, accessible, and essential growth lever for Small and Medium-sized Enterprises (SMEs). For entrepreneurs and business leaders, strategic AI adoption is no longer an option but an imperative for competitiveness, operational efficiency, and long-term survival. This report provides a comprehensive framework for SME leaders to navigate this technological shift, offering the foundational knowledge, business case, practical applications, and strategic guidance necessary to harness the power of AI. The quantitative evidence supporting AI adoption is compelling; 91% of SMEs using AI report that it directly boosts their revenue. Beyond top-line growth, AI drives profound operational efficiencies, with studies showing it can reduce operational costs by up to 30% and save businesses more than 20 hours of valuable time each month. This transformation is occurring within the context of a seismic economic shift; the global AI market is projected to surge from $233.46 Billion in 2024 to an astonishing $1.77 Trillion by 2032. This paper demystifies the core concepts of AI, presents a business case based on market data, details practical applications, and lays out a phased, actionable adoption strategy. |
| Date: | 2025–09 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2509.14532 |
| By: | Zoltan Bartha; Adam Bereczk |
| Abstract: | Our study presents a model of factors influencing the financial viability of Hungarian social enterprises, and tests the model on a sample of 220 Hungarian firms involved in social entrepreneurship. In the model we suggest that the most important factors for financial viability are the Regulatory environment (the transparency of regulations); the Entrepreneurial attributes of the entrepreneur (business orientation, business skills and experience, business planning tendencies); the Financial support provided by the environment (the ratio of grants, donations and subsidies within the total revenues of the firm); and the Strategy followed by the firms (the presence of such generic strategies as cost leadership or differentiation). We find that only two of the model's four factors are significantly associated with Financial viability: Entrepreneurial attributes and Financial support. The results suggest that the best way of strengthening the viability of social enterprises is through entrepreneurship training (to enhance the business skills and experience of the entrepreneurs, and to propagate business planning), and to provide grants and subsidies to these firms. As no significant association was found between Financial viability and Strategy, we can conclude that the role of market competition is probably relatively week among Hungarian social enterprises. |
| Date: | 2025–09 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2509.21415 |
| By: | Sasso Simone (European Commission - JRC); Perpiña Castillo Carolina |
| Abstract: | "This brief presents JRC analyses exploring entrepreneurship and business dynamics across EU territories. The evidence confirms urban–rural gaps in firm creation, high-growth enterprises, and especially in the startup landscape, while also highlighting distinctive strengths and success stories showing that rural areas can be engines of growth not only in sectors often associated with rural economies, but also in more diversified and knowledge-intensive activities. These findings point to untapped entrepreneurial potential of rural territories and the need for place-based policies to turn it into a driver of Europe’s competitiveness." |
| Date: | 2025–09 |
| URL: | https://d.repec.org/n?u=RePEc:ipt:iptwpa:jrc143536 |
| By: | Sahab Zandi; Kamesh Korangi; Juan C. Moreno-Paredes; Mar\'ia \'Oskarsd\'ottir; Christophe Mues; Cristi\'an Bravo |
| Abstract: | Small and Medium-sized Enterprises (SMEs) are known to play a vital role in economic growth, employment, and innovation. However, they tend to face significant challenges in accessing credit due to limited financial histories, collateral constraints, and exposure to macroeconomic shocks. These challenges make an accurate credit risk assessment by lenders crucial, particularly since SMEs frequently operate within interconnected firm networks through which default risk can propagate. This paper presents and tests a novel approach for modelling the risk of SME credit, using a unique large data set of SME loans provided by a prominent financial institution. Specifically, our approach employs Graph Neural Networks to predict SME default using multilayer network data derived from common ownership and financial transactions between firms. We show that combining this information with traditional structured data not only improves application scoring performance, but also explicitly models contagion risk between companies. Further analysis shows how the directionality and intensity of these connections influence financial risk contagion, offering a deeper understanding of the underlying processes. Our findings highlight the predictive power of network data, as well as the role of supply chain networks in exposing SMEs to correlated default risk. |
| Date: | 2025–10 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2510.09407 |
| By: | Mauri Kotamaki (Turku School of Economics, University of Turku, Finland) |
| Abstract: | This paper estimates the causal effect of financial constraints on the short-term performance of Finnish SMEs using survey data from 2016-2024 and propensity score matching (PSM). We examine six outcomes: turnover, employment, investment, profitability, solvency, and innovation, and report effects on both odds and probability scales. Financial constraints significantly increase the likelihood of adverse outcomes: constrained firms face 10-30\% higher odds of reporting deterioration in core indicators, with the largest effects on solvency (29\% higher odds) and profitability, followed by investment and turnover; employment effects are smaller, and innovation effects modest. Marginal effects indicate up to a 4 percentage point reduction in the probability of improvement for key outcomes. Results are robust to multiple-testing adjustments, and alternative specifications. Heterogeneity analysis reveals that the effects vary by firm size, pointing to a dual mechanism: turnover and profitability effects are strongest for micro and small firms, reflecting immediate liquidity stress, while employment and investment effects intensify with firm size, suggesting real adjustments (growth obstacles) are more pronounced in mid-sized SMEs. Policy implications and directions for future research are discussed. |
| Keywords: | credit constraints, financing, impact analysis, propensity score matching |
| JEL: | G32 D22 L25 C21 O16 |
| Date: | 2025–10 |
| URL: | https://d.repec.org/n?u=RePEc:tkk:dpaper:dp172 |
| By: | Bertoni, Fabio; Colombo, Massimo G.; Quas, Anita |
| Abstract: | This working paper evaluates the impact of the COSME Loan Guarantee Facility (LGF) on SMEs in Greece, Poland, Spain, and Romania between 2015 and 2023. Using advanced econometric methods, we compare SMEs that received a guarantee with a control group of similar companies. We find that SMEs benefiting from guaranteed loans outgrow their counterparts three years after the signature year, in terms of total assets, sales, and both tangible and intangible fixed assets. Moreover, beneficiary companies are less likely to go bankrupt by the end of 2023, particularly smaller and older firms. The results confirm that guaranteed loans support SME growth without adverse long-term effects on productivity or business survival. This paper is part of the ongoing work of the Impact Assessment division to support the EIF's transition to an impact-driven institution by designing and implementing a comprehensive Impact Assessment Framework. Ex-post impact studies, such as this report, play a key role in this Framework by informing and refining future support measures, while also enhancing the accuracy of predicted outcomes. |
| Date: | 2025 |
| URL: | https://d.repec.org/n?u=RePEc:zbw:eifwps:328255 |
| By: | Bertoni, Fabio; Colombo, Massimo G.; Quas, Anita |
| Abstract: | This paper assesses the impact of the COSME Loan Guarantee Facility (LGF) on SMEs in Belgium, France, and Italy between 2015 and 2023. Using advanced econometric methods, we compare SMEs that received a guarantee with a control group of similar companies and find that beneficiaries experienced higher growth in total assets, sales, employment, and both tangible and intangible fixed assets three years after the signature year. The analysis also shows that guaranteed loans improve firms' survival prospects, without adverse long-term effects on productivity. Moreover the study highlights that the effects tend to be larger for smaller and younger firms. This study is part of our ongoing effort to design and implement a comprehensive Impact Assessment Framework. Ex-post evaluations, such as this report, provide essential evidence for shaping future support measures and improving the accuracy of impact forecasts. |
| Date: | 2025 |
| URL: | https://d.repec.org/n?u=RePEc:zbw:eifwps:328250 |