Does It Matter? Experimental Evidence on the (Signaling) Effect of Gender-Specific Accelerator Programs on Access to Angel Capital

Abstract

Despite the acknowledged importance of capital for start-up success, gender disparities persist when trying to raise funds from external sources, including angel investors, venture capitalists, and financial institutions. Many studies have shown that gender stereotypes are harmful and prevent women from gaining access to resources, e.g., capital, distorting their start-up valuations, and influencing the resulting financing decisions. In recent years, gender-specific support measures have emerged that attempt to overcome gender inequalities in early-stage entrepreneurship, including gender-specific accelerator programs. However, there remains a lack of research on the effects of these gender-specific support programs. This study therefore investigates the influence of participating in gender-specific accelerator programs on access to angel capital, as a highly relevant source for the early financing of (women-founded) start-ups, considering signaling theory and its influence by the role congruity theory in an entrepreneurial context. A laboratory experiment involving 227 participants was conducted to explore these dynamics, reflecting perceptions of signals for angel investors. Overall, the findings suggest that gender-specific accelerator programs may positively influence perceived investment decisions by enhancing perceived team competence. Furthermore, investor gender moderates the perception of team competence. The signaling effect that (gender-specific) accelerators have on angel investors does not appear to be as great for men investors as it is for women investors. The findings contribute to signaling theory by understanding the impact of participation in (gender-specific) accelerator programs on the investment decision of angel investors while advocating for more inclusive approaches to fostering diversity and inclusivity within the start-up ecosystem.

1. Introduction

Current research and studies show that there is a persistent gender gap in the allocation of early-stage capital for start-ups (e.g., Bringmann & Veer, 2021; Hirschfeld et al., 2022; Ewens & Townsend, 2020; PitchBook, 2025a, 2025b; Solal, 2019). Research has revealed that women entrepreneurs are disadvantaged due to hidden biases rooted in gender stereotypes when seeking capital (Balachandra et al., 2017; Brush et al., 2018; Kanze et al., 2018; Raina, 2021).

In the field of early-stage start-ups looking for financing (Knickerbocker, 2024), angel capital is a frequently used means of financing (Angel Capital Association, 2024; Harrison et al., 2016; Hellmann et al., 2021), especially because of the unique advantage regarding the mentoring and access to networks provided by angel investors in the field of experimentation for early-stage start-ups (Sariri, 2022). Therefore, this source of early-stage capital could be especially important for women-founded start-ups, as mentoring can be particularly beneficial for women entrepreneurs (Giglio, 2021; Theaker, 2024). However, gender disparities also refer to the allocation of angel capital (Aernoudt & De San José, 2020; Becker-Blease & Sohl, 2007; Brush et al., 2018).

In the phase of experimentation for early-stage start-ups, track records are often limited and investors rely strongly on observable characteristics and signals of quality and legitimacy (Pierrakis & Owen, 2022). Especially for angel investors, (entrepreneurial) human capital, such as formal education and founding experience, and team attributes hold particular significance regarding their investment decisions (Mason & Stark, 2004; Pierrakis & Owen, 2022; Svetek & Drnovšek, 2022), as these factors help to reduce information asymmetries and signal the potential for success (Pierrakis & Owen, 2022). Start-up accelerators are seen as entrepreneurship education and training programs (Dams et al., 2022), whereby participation in these can increase the productivity and capabilities of the start-up team (Polo García-Ochoa et al., 2020) as well as the human and social capital of entrepreneurs (Dams et al., 2016; Martin et al., 2013; Seet et al., 2018), and the likelihood of building relationships with other players in the entrepreneurial ecosystem (Dalle et al., 2023) and receiving external funding (O. Colombo, 2021). Although the nature and impact of the signal can vary, accelerator programs in the seed stage can increase and improve the clarity, credibility, and visibility of signals, as well as the efficiency of signaling strategies (Hallen et al., 2023) and can therefore enhance a start-up’s ability to attract angel investors by overcoming the existing information asymmetries (Cohen, 2013; Pierrakis & Owen, 2022; Venâncio & Jorge, 2022).

In contradiction, although accelerator programs have the potential to support women entrepreneurs, they often fail to close the gender gap in entrepreneurship due to reinforcing deep-rooted structural inequalities (C. Chen, 2020; Galmangodage et al., 2025). Recent approaches therefore refer to the development of gender-specific support programs to counteract these gender differences. This highlights the need to examine the (signaling) effects of accelerators through a gendered lens. Based on that, the following research questions arise:

• How does participation in gender-specific accelerator programs affect the investment decisions of angel investors under the lens of signaling theory?
• What influence does the gender of the angel investor have on the investment decision if the start-up to be assessed has participated in a gender-specific accelerator program?

This study investigates the impact of signaling effects in both gender-open and gender-specific accelerator programs on perceived industry experience, perceived market knowledge, and perceived competence, all of which are significant factors for angel investors (Franke et al., 2008; Ko & McKelvie, 2018; Mason & Stark, 2004; Mason et al., 2017; Pierrakis & Owen, 2022; Skalicka et al., 2022). Furthermore, we analyze how these factors influence access to angel investments. Additionally, we postulate that the gender of the angel investor has an impact on the relationship between participation in gender-open and gender-specific accelerator programs and perceived industry experience, market knowledge, and competence of the team.

The laboratory experiment revealed that participation in both gender-specific and gender-open accelerator programs positively influences perceived team competence, increasing the likelihood of funding for women-founded start-ups. Additionally, both types of programs indirectly enhance investment prospects through perceived competence, although no effects were found on perceived industry experience or market knowledge. The investor’s gender also moderated perceptions, with men angel investors being less likely than women to acknowledge the impact of accelerator programs. Supplementary insights from expert interviews highlighted the broader investment culture and reinforced the need for more inclusive entrepreneurship programs. With this article, we contribute to research on closing the gender gap in capital acquisition, especially angel capital, for start-ups and provide practical implications for the design of gender-specific measures in an entrepreneurial context, especially gender-specific accelerator programs. We show the impact of signals of completed accelerator programs on women-founded start-ups with regard to the investment decisions of angel investors and address the question of whether gender-specific accelerator programs can help close the disparities which exist regarding the allocation of angel capital.

2. Theoretical Framework

2.1. Gender Gap in Angel Funding

In 2024, global venture investments1 in start-ups raised USD 314 billion, edging above the totals of 2023, which was the lowest year for venture funding since the pandemic starting in 2020 (Teare, 2025). Although the percentage of deals for purely women-founded start-ups increased slightly up to 2023, reaching 7.0% in the US and 5.2% in Europe (PitchBook, 2025a, 2025b), they started to fall again in 2024. Although women-led businesses tend to show a higher return on investment and higher cumulated revenues over a five-year period (Krentz et al., 2018), disparities in the allocation of early-stage venture capital still persist. Female entrepreneurs, furthermore, tend to over-perform particularly in male-dominated relative to female-dominated industry sectors (Hebert, 2025). According to Aernoudt and De San José (2020), this could be related to their high level of efficiency in resource management, their ability of adoption of innovative strategies and solutions, their customer-centric focus, effective leadership qualities, and emotional intelligence. Although these factors enable them to outperform male-only businesses, they are facing challenges in securing venture capital. Women entrepreneurs have a lower number of deal counts and receive less capital (Bellucci et al., 2025; Edelman et al., 2018; PitchBook, 2025a, 2025b; Poczter & Shapsis, 2018; Wu & Chua, 2012). Research in the field of VC indicates that start-ups founded by men are about four times more likely to receive funding compared to those founded by women (Aernoudt & De San José, 2020; Alsos et al., 2006; Brush et al., 2018; Edelman et al., 2018; Guzman & Kacperczyk, 2019; Kanze et al., 2018; Nigam et al., 2022; Shuttleworth et al., 2018)—even when mixed-gender teams are included (PitchBook, 2025a, 2025b). This result also applies directly to angel investments, as a highly relevant source of early-stage financing for start-ups (Angel Capital Association, 2024; Harrison et al., 2016). In the angel/seed phase, about 18% of the capital in the US and 12% in Europe was invested in start-ups solely founded by women (PitchBook, 2025a, 2025b).

Angel investors are private individuals who play a crucial role for the long-term growth and success of start-ups in the early stage (Edelman et al., 2017; Gregson et al., 2017; Ibrahim, 2008; Maus et al., 2023; Wichert, 2011). Although there is a difference in the behavior of angel investors regarding their experience level, investment approach, and if they act as individual angels or on behalf of an angel fund (Hellmann et al., 2021), angel investors generally can be defined as individuals who, in place of equity, ownership stakes, or convertible debt (Edelman et al., 2017; Olaore & Adetoye, 2014), invest in early-stage ventures, often when those companies are just starting out and need initial funding to develop and grow their start-up (Sariri, 2022). Angel investors use their personal funds and make smaller investments in early stages (Cumming & Zhang, 2019; Hellmann et al., 2021; Ibrahim, 2008; Sariri, 2022). This allows them to make faster and more flexible investment decisions without consulting other stakeholders (Sariri, 2022). Beyond financial support, angel investors contribute significant non-financial resources, including strategic advice, access to professional networks, and mentoring for start-up founders (Kirihata, 2022; Wichert, 2011). These contributions are particularly valuable in areas where angel investors possess substantial experience and expertise, often derived from their involvement in successful ventures or personal entrepreneurial endeavors (Edelman et al., 2017; Maus et al., 2023).

When evaluating the potential success of a business and making investment decisions, angel investors place heightened emphasis on the management team and human capital signals, often assigning significant weight to the entrepreneur’s skills, experience, and personal attributes (Granz et al., 2020; Mason & Stark, 2004; Svetek & Drnovšek, 2022). The process of investment decision-making of angel investors involves two stages: initially the evaluation if there is a fit with their own subjective investment criteria, followed by a detailed examination focused on human factors such as the entrepreneur’s personality, management team, and skills, often assessed intuitively (Haines et al., 2003; Mason et al., 2010; Mason & Stark, 2004; Riding et al., 1995; Svetek & Drnovšek, 2022). This subjective approach (Haines et al., 2003; Mason et al., 2010; Riding et al., 1995) to evaluation can exacerbate gender biases (Tinkler et al., 2015), as male entrepreneurs are often perceived to possess the qualities deemed necessary for success more than their female counterparts. Gender differences in evaluations emerge particularly when assessing individuals rather than start-ups, with technical skills helping mitigate bias toward women (Tinkler et al., 2015). Overall, while multiple factors influence the investment decisions of angel investors, the characteristics of the entrepreneur and the management team, especially trustworthiness (based on signals of experience and the entrepreneur’s character (Sapienza et al., 2013)), experience, and competence, stand out as the most important criteria (e.g., Gürol & Ener, 2022; Hanák, 2020; Mason et al., 2017; Pierrakis & Owen, 2022; Skalicka et al., 2022).

The reasons for the unequal distribution of angel capital are multifaceted and can be related to the entrepreneur as well as to the angel investors. Avnimelech and Rechter (2023) identified several factors contributing to this gender gap, including lower entrepreneurial human capital (a), lower entrepreneurial self-efficacy (b), inferior business networks (c), limited access to finance (d), along with discrimination and stereotypes within the entrepreneurial ecosystem (e).

(a)

Dams et al. (2022) found that women entrepreneurial human capital characteristics differ from those of men. Entrepreneurial human capital in particular is more important for entrepreneurial success than general human capital, especially for young entrepreneurs (Avnimelech & Rechter, 2023). Examples are entrepreneurial education, entrepreneurial self-efficacy, entrepreneurial skills, and entrepreneurial knowledge (Dams et al., 2022).

(b)

Women entrepreneurs are less likely to resort to external financing—combined with having a rather negative attitude towards raising capital and a possible lack of desire for strong growth (Chilazi, 2019; Kanze et al., 2018). In addition, women entrepreneurs tend to have a lower risk tolerance (e.g., Brush et al., 2018; Kanze et al., 2018; Kwapisz & Hechavarría, 2017) and see themselves discouraged from entrepreneurship (Thébaud, 2015). Thus, women tend to think that they do not have the necessary experience and knowledge to start a business (Dams et al., 2022; GEM, 2023), which translates into lower entrepreneurial self-efficacy. Additionally, research indicates that women tend to ask for less money, offer lower valuations for their ventures, and offer higher equity shares for less capital which could indicate a self-imposed limitation (Poczter & Shapsis, 2016, 2018; Prokop & Wang, 2022).

(c)

Another reason is attributed to social capital or, more precisely, women’s lack of network access to male-dominated social networks in the ecosystem (Kwapisz & Hechavarría, 2017; Stahl et al., 2023). As women-founded start-ups are more likely to search for angel capital of women angels, they tend to search within their own social networks (Becker-Blease & Sohl, 2007). According to social identity theory, angel investors also tend to favor entrepreneurs who belong to their own social group, which they share identity with (e.g., Edelman et al., 2018; Mason et al., 2017). Therefore, male angel investors are more likely to invest in male entrepreneurs as part of their “in-group” (Edelman et al., 2018; Ewens & Townsend, 2020). Furthermore, angel investors are more likely to invest in companies recommended to them through their network connections (Bonini et al., 2018; Crick & Crick, 2018; Piazza, 2019). However, as the vast majority of angel investors are male (Becker-Blease & Sohl, 2008, 2011; Poczter & Shapsis, 2018), it may be less likely that the networks of women entrepreneurs overlap with the networks of angel investors.

(d)

Women angel investors exhibit lower confidence levels and higher risk aversion and tend to invest in later-stage ventures, which is resulting in fewer investments in early-stage start-ups (Becker-Blease & Sohl, 2008). As women entrepreneurs may be more likely to seek funding from women angels (Amatucci, 2016; Oranburg & Geiger, 2019), this behavior related to women angel investors may result in limited requests and therefore access to angel capital for women-founded start-ups (Becker-Blease & Sohl, 2008). Furthermore, there is a male dominance in the investor ecosystem which extends to angel investing (Huang et al., 2017). This homogeneity within the ecosystem of angel investors is linked to homophily and therefore a negative impact on women entrepreneurs, as women angels tend to invest in women-founded start-ups (Amatucci, 2016; Ewens & Townsend, 2020; Oranburg & Geiger, 2019) and male angels tend to invest into male-led start-ups (Becker-Blease & Sohl, 2007; Edelman et al., 2018; Ewens & Townsend, 2020; Oranburg & Geiger, 2019). For instance, in Europe, women angels are 35% more likely than their male counterparts to invest in women entrepreneurs (Jetter & Stockley, 2023).

(e)

Gender biases and stereotypes persist in the investment ecosystem, affecting pitch evaluations and investment decisions (Balachandra et al., 2017; Brush et al., 2018; Kanze et al., 2018; Lee & Huang, 2018; Shuttleworth et al., 2018; Snellman & Solal, 2022). Investors evaluate women and men differently. This can be explained by gender role congruity theory, which suggests that women are perceived less positively in leadership roles than men (Eagly & Karau, 2002; Edelman et al., 2018). Gender role congruity theory posits that individuals are viewed more favorably when their behavior aligns with gender expectations (Eagly & Karau, 2002; Rudman & Phelan, 2008). This theory suggests that societal expectations for women to exhibit community-oriented traits clash with the entrepreneurial stereotype, which is masculine and values task-oriented and agentic traits (Balachandra et al., 2017). Stereotypes of men’s traits are represented by the “competence and achievement-orientation cluster” while women’s traits are represented by the “social and communication orientation” cluster (Eagly et al., 2020; Fiske et al., 2002). Stereotypes are automatically activated in people’s minds (Devine et al., 2012), leading to gender belief systems (Tonoyan & Strohmeyer, 2021) and they influence perceptions and evaluations of others (Hentschel et al., 2019). This bias leads to higher expectations and challenges for women entrepreneurs compared to men (Alsos & Ljunggren, 2017), as they violate the gender-based expectations and are therefore viewed as less competent and agentic (Alsos & Ljunggren, 2017; Edelman et al., 2018; Tonoyan & Strohmeyer, 2021). Balachandra et al. (2017) identified that investment biases are associated with constructs of femininity and masculinity rather than gender itself. Their findings suggest that both women and men could benefit from aligning with masculine norms to mitigate the penalties associated with the perceived femininity construct in the context of entrepreneurship.

In recent years, gender-specific support measures have emerged that attempt to overcome these gender inequalities in early-stage entrepreneurship, including gender-specific accelerator programs (Galmangodage et al., 2025).

2.2. The Signaling Effect of Accelerators on Access to Angel Capital

Accelerators have become an important player in the entrepreneurial ecosystem (Avnimelech & Rechter, 2023; Chan et al., 2020; Hallen et al., 2020; Yu, 2020). They have emerged over the last decade as a new form of support for entrepreneurship (Bańka et al., 2022). As breeding grounds for innovation in various areas, they not only contribute to economic growth, but also to social development by facilitating the internalization of opportunities, improving the flow of entrepreneurial knowledge and promoting the development of entrepreneurial communities (Drori & Wright, 2018; Heshmati et al., 2024). Accelerators can be seen as entrepreneurial micro-ecosystems, which aim to facilitate the integration of start-ups into the entrepreneurial ecosystem (Dalle et al., 2023), e.g., by providing advice, access to industry contacts and resources (Heshmati et al., 2024). At the same time, they increase the legitimacy of new business models, intensify competition and drive strategic dynamics—to the benefit of individual companies as well as the entire corporate landscape (Banc & Messeghem, 2020).

The literature considers various aspects of accelerators such as the structure, impact, and content of accelerator programs (Bańka et al., 2022; Drori & Wright, 2018). According to GALI, there are more than 300 accelerators worldwide, most of which are located in America and Canada (102) as well as in Europe and Central Asia (73) (GALI, 2023).

Accelerators can be operated by public or private sector institutions. The former are run by the government or non-profit educational institutions and aim to promote entrepreneurial activities at the local or regional level and the exploitation of scientific research results (Bańka et al., 2022; BMWK, 2022; Møller, 2023). Private sector institutions include investor-driven or company-driven accelerators and aim to generate returns on their investments or to improve their own competitiveness in line with the company’s overall strategy (BMWK, 2022). Some programs set specific priorities, for example regarding the target group (e.g., high-potential start-ups), the impact (e.g., support for disadvantaged entrepreneurs), or regions or sectors (BMWK, 2022; Hallen et al., 2023). Around 50% of accelerators worldwide are sector-independent, while the other half focus on a specific area (most frequently ICT, healthcare, and financial services (GALI, 2023)). Start-ups must apply for limited places. Prerequisites are usually a pre-formulated business model, first developed products and/or services, and the start of initial market activities (Bańka et al., 2022; BMWK, 2022). Accelerators then apply different criteria for project selection (Bańka et al., 2022). The programs typically last from three to nine months (Bańka et al., 2022; BMWK, 2022), with most teams completing a three- to six-month program (GALI, 2023). Accelerator programs, often linked to start-up financing, typically involve start-ups giving up shares ranging from five to fifteen percent in exchange for funding, usually in the form of convertible loans or direct investments (BMWK, 2022). According to GALI (2023), more than half of the accelerators provide some form of financing, either directly through start-up financing or via a related branch of financing (GALI, 2023; Kwapisz, 2022).

Accelerator programs vary widely in their support offerings and operate on individualized models (Bańka et al., 2022). The overall aim of accelerators is to increase the skills and, consequently, the success of start-ups through structured development and learning processes (Bańka et al., 2022) and the provision of resources (e.g., work equipment, premises, and access to legal advice and other management services) (BMWK, 2022; Cohen et al., 2019b). Accelerators speed up the business development of start-ups (BMWK, 2022) by compressing years of learning-by-doing (Hathaway, 2016; Pierrakis & Owen, 2022) and focus on comprehensive company development (Kwapisz, 2022). They shorten the start-up time by using existing networks and managing scarcity (Stayton & Mangematin, 2019). According to Kwapisz (2022), accelerators are intermediary spaces that provide missing resources and mitigate market discrimination and imperfections. They strengthen the capabilities and performance of start-ups by developing them, improving their chances of success and bringing them into contact with external partners (e.g., Gonzalez-Uribe & Leatherbee, 2018; Hallen et al., 2020; Polo García-Ochoa et al., 2020; Yu, 2020). This includes, for example, preparing for equity investments from seed VCs and angel investors (Hallen et al., 2023; Pierrakis & Owen, 2022). However, understanding of the processes and practices by which these effects are achieved is limited (Drori & Wright, 2018).

Due to the dynamic capabilities view and resource-based view, accelerators contribute to the dynamic capabilities of (a) sensing the market (ability to identify and select the right opportunities), (b) absorption (ability to recognize and process new external information and to use it for organizational advantage), (c) integration (capability to achieve a positive and value-creating interaction among different resources), and (d) innovation of start-ups; the last three capabilities have a positive influence on start-ups performance (Polo García-Ochoa et al., 2020). Kwapisz (2022), furthermore, highlights the fact that accelerator programs support start-ups through buffer and bridging mechanisms. Buffers reduce external dependency, enabling start-ups to focus on entrepreneurial activities, while bridges facilitate connections with the external environment, offering legitimacy and access to partners. Examples include government funding and access to expert advice. Depending on the investors associated with the accelerator, start-ups are also attracted by them (Dalle et al., 2023). These partners (e.g., investors, sales partners, and potential customers) are crucial to the success of start-ups as they provide access to resources, knowledge, skills, and legitimacy (Hallen et al., 2023). High-status partners are especially desirable because they offer superior resources and knowledge while also benefiting from the status conferred by the start-ups, serving as an indicator of partner quality (Hallen et al., 2023). For start-ups, this status is an indicator of the otherwise not assessable quality of the partner (Hallen et al., 2023).

Based on existing literature, Hallen et al. (2023) describe learning and signal transmission as causal drivers for the effect of accelerators, whereby these are complementary and can coexist. Learning changes the quality of the start-up through the accelerator services described (mentoring, advice, training, exchange with cohort partners). The founders learn how to work on certain tasks (Cohen et al., 2019b). Signaling, on the other hand, does not directly influence the quality of the start-ups, but accelerators can reflect the quality of the supervised start-ups to the outside world (Hallen et al., 2023). A “signal” is defined as an action, attribute, or communication that conveys credible and valuable information to external parties (Connelly et al., 2024; Spence, 1973). These signals represent observable information correlated with otherwise hard-to-observe attributes, which is particularly crucial for early-stage ventures (Stuart et al., 1999). Start-ups can benefit from this as they can attract partners with higher status and become more attractive as they send quality signals other than their own status (Hallen et al., 2023). Thus, accelerators can increase and improve (a) the clarity and credibility of signals through mediated guidance in the context of supportive mentoring, the proven ability to access accelerator resources, the aspiration for growth associated with accelerator participation, and validated business models, (b) the visibility of signals through the connection to external network partners, and (c) the development of efficient signaling strategies through structured programs (Hallen et al., 2023). Accelerators therefore play an important moderating role in strengthening the signaling effect, which significantly influences the acquisition of strategic collaborations and financial resources for start-ups (Hallen et al., 2023). An improved signaling effect is crucial for the perception of equity investors and is therefore a significant factor for the growth and development of young companies (Murillo-Rojas & Brinckmann, 2023).

This effect is further amplified in successful entrepreneurial ecosystems, as start-ups from such contexts have been shown to generate higher profits (Fehder, 2023). In less developed markets, on the other hand, accelerators face greater challenges, for example due to structural deficits, which can lead to muted effects (Roberts & Lall, 2019). Nevertheless, they can also provide important impetus there—albeit with significantly different effects, depending on the local conditions and the specific needs of the start-ups (Roberts & Lall, 2019).

The effectiveness of the signals can also vary considerably depending on the reputation, quality, and characteristics of the accelerator (Assenova & Amit, 2024; Hallen et al., 2023; Pierrakis & Owen, 2022; Roberts & Lall, 2019; Yu, 2020). According to Dalle et al. (2023) and Hallen et al. (2023), participation in renowned programs in particular is associated with increased visibility, credibility, and quality for investors. Accelerators with a high reputation, e.g., by rigorous selection processes, access to high-status investors, and access to quality mentorship, resources, and networking opportunities, as well as those that focus on growth and scaling and show consistent positive outcomes, e.g., by successful funding rounds and achieving growth milestones, are recognized for sending positive signals to investors (Assenova & Amit, 2024; Hallen et al., 2023). These factors collectively enhance the attractiveness of startups associated with the programs. Accelerators that have a lower status or a negative market perception, offer limited resources and support, or have high acceptance rates or show inconsistent results can, therefore, send limited or even negative signals in a “market for lemons” with regard to the perceived quality of the start-ups (Assenova & Amit, 2024; Hallen et al., 2023). This perception can cause skepticism among investors and lead to start-ups associated with such programs being considered less attractive—regardless of their actual quality (Assenova & Amit, 2024; Hallen et al., 2023). The selection of participating start-ups also plays a role—programs that act selectively and support start-ups with high potential generally achieve better results (Hallen et al., 2023).

Limited positive and negative signals can affect the chances of funding and strategic partnerships, making it more difficult for start-ups to grow and develop. The selection of a suitable program for start-ups therefore requires an understanding of the underlying influencing factors. This is the only way that start-ups can use the potential signaling effects to their advantage.

2.3. The Gender-Specific Signaling Effect of Accelerators

The signaling effect of an accelerator can help to increase the confidence of angel investors in early-stage start-ups and thus the likelihood of an investment (Cohen, 2013). Women entrepreneurs benefit more from tailored support measures in accelerators compared to men due to differences in their personal backgrounds and how they are influenced by the entrepreneurial ecosystem. Women entrepreneurs demonstrate gender-specific aspirations and experience varying effects from accelerator programs, which depend on the stage of their start-ups (Avnimelech & Rechter, 2023; Kwapisz, 2022). For instance, they actively seek and acquire more entrepreneurial knowledge, focus on strengthening their networks, and exhibit greater improvements in entrepreneurial self-efficacy compared to male entrepreneurs (Avnimelech & Rechter, 2023; Kwapisz, 2022). In addition, they strive more to increase their legitimacy (Avnimelech & Rechter, 2023). However, according to Kwapisz (2022) there are no gender-specific differences in the degree of goal achievement. Nevertheless, access to capital as a goal and the progress made in accessing this capital as well as the improvement of their own fundraising skills are rated lower in meaning by women entrepreneurs (Avnimelech & Rechter, 2023), although women-led start-ups that participate in an accelerator program increase their chances of equity financing by 14–30% compared to male-led start-ups (Dams et al., 2022). Interestingly, this trend shifts for women in growth-oriented start-ups, who prioritize access to investors and VC donors more than men do, suggesting a gender-specific divergence in financing priorities at growth stages (Kwapisz, 2022). Women founders also benefit from mentoring or support from role models, which has a greater influence on women than men (Entrialgo & Iglesias, 2018). Mentoring helps women to gain more confidence in their own skills and abilities (Roper & Scott, 2009) and increases their sense of competence, identity, and effectiveness in their professional roles (Kram & Isabella, 1985). Additionally, mentoring has a positive causal effect on fundraising (Gonzalez-Uribe & Leatherbee, 2018). Nevertheless, women entrepreneurs tend to receive fewer financial, human, social, and market resources and these on less favorable terms (Rawal & Repishti, 2022; Tonoyan & Strohmeyer, 2021).

Research has shown that gender has an influence on how entrepreneurs signal quality and legitimacy of their start-up and that gender stereotypes influence the interpretation of this signals by angel investors (Alsos & Ljunggren, 2017; Edelman et al., 2018). This can also lead to less legitimacy for women-founded ventures (Edelman et al., 2018).

Although accelerator programs theoretically have the potential to reduce gender inequalities and foster a more inclusive entrepreneurial ecosystem, they often fail to close the gender gap in entrepreneurship due to deep-rooted structural inequalities (Galmangodage et al., 2025). Accelerator programs often unconsciously reproduce traditional gender roles and further hinder women’s entrepreneurial progress (Galmangodage et al., 2025). Recent research has combined signaling theory and role congruity theory to study how gender stereotypes shape signal interpretation in accelerator-selection processes, showing that acceptance is most likely when startups’ signals are congruent with the lead founder’s gender (Yang et al., 2020). Our study builds on this approach but shifts the focus from accelerator admission to the investment stage. Specifically, we examine whether participation in gender-specific accelerators itself functions as a credible or discounted signal in angel investors’ evaluations of women entrepreneurs. By integrating role congruence theory (Eagly & Karau, 2002; Edelman et al., 2018) into the context of signaling effects of accelerators, it is shown that the interpretation of the signals sent is influenced by the entrepreneurs’ fit with cultural norms, gender-specific expectations, and existing gender stereotypes (Alsos & Ljunggren, 2017; Edelman et al., 2018; Yang et al., 2020). Entrepreneurs who meet these expectations send out more credible and consistent signals to the targeted persons, which makes it easier for them to access accelerator programs in general and to obtain access to important support services like equity investment (Murillo-Rojas & Brinckmann, 2023).

When selecting start-ups, accelerators tend to favor start-ups whose profile and appearance are oriented towards socially anchored gender expectations (Diekman & Eagly, 2008). In this context, men entrepreneurs benefit disproportionately from gender-based incongruences (Yang et al., 2020). Women entrepreneurs therefore face limitations in the efficiency and power of signaling effects by missed chances of participation (see Section 2.2).

When taking part in accelerator programs, women often encounter gender-specific social capital constraints that affect their access to influential networks (Muntean & Ozkazanc-Pan, 2014, 2015). Consequently, this limited network dynamics not only reduces the visibility of the signals sent, but also lowers the credibility of signals, making it more difficult to access resources that are essential for business success. The role of accelerators in shaping corporate identity and developing business models is also influenced by how entrepreneurs perceive themselves in relation to societal role expectations (Tobiassen et al., 2022). This perception can affect their engagement in accelerator programs and the outcomes of their participation (Tobiassen et al., 2022). As explained in Section 2.1, women entrepreneurs often deviate from these stereotypical expectations in their behavior and therefore face additional hurdles.

As a result, gender influences how entrepreneurs signal the quality and legitimacy of their start-up and also how angel investors interpret these signals based on prevailing stereotypes (Alsos & Ljunggren, 2017; Edelman et al., 2018). Therefore, accelerator programs often do not adequately address the specific challenges faced by women, leading to a gap in effective support mechanisms (Muntean & Ozkazanc-Pan, 2015). In view of these challenges, accelerator programs that are specifically tailored to the particular needs of women entrepreneurs, like female accelerators, have emerged over time.

3. Materials and Methods

3.1. Hypothesis Development

In order to study the signaling effect of gender-specific support measures in the start-up ecosystem on access to angel capital, we focus on participation in non-profit, governmental accelerator programs as an example for a training program. Based on the theoretical explanations, we analyze our research through the lens of signaling theory (Spence, 1973), including contextual insights of gender role congruity theory (Eagly & Karau, 2002), determining the investment process of angel investors.

Accelerators with their features and main components are designed to promote a start-up’s performance (Dams et al., 2022) and to drive the development of entrepreneurial capabilities quickly. As there is less information about the quality and potential of early-stage ventures, there is a high importance of signals (e.g., grants, prior investments, human and social capital) for (angel) investors to overcome information asymmetries (Cohen, 2013; Kleinert et al., 2020; Svetek, 2022). Therefore, accelerators form a platform between start-ups and investors (Dalle et al., 2023), which reduces information asymmetries (Yu, 2020) and lends legitimacy to both groups (Avnimelech & Rechter, 2023). Drawing on signaling theory, accelerators can positively influence investors’ perceptions as the signals sent can support the evaluation of start-ups regarding their quality and the commitment of the entrepreneurs and therefore aid in making funding decisions (Hallen et al., 2023, 2020; Kim & Wagman, 2014; Kleinert et al., 2020; Svetek, 2022; Yang et al., 2020).

With regard to the signaling effects of accelerators, considered under a gendered lens, research indicates that women entrepreneurs encounter disadvantages in the improvement of clarity, credibility, and visibility of signals, as well as in the efficient development of signaling strategies (Section 2.2). These disadvantages also persist if they present incongruent signals to important support services like investors (Edelman et al., 2018; Kleinert & Mochkabadi, 2022; Liao, 2021; Murillo-Rojas & Brinckmann, 2023). This phenomenon can be attributed to the combination of positive signals from accelerators and the negative stereotypes associated with women entrepreneurs. The inconsistency of signals—such as the gendered reception of accelerator participation—can lead to biased perceptions, as noted by Solal and Snellman (2019), who stress the importance of signal consistency across different groups. Moreover, Eddleston et al. (2016) demonstrated that even though women and men entrepreneurs displayed the same signals about their ventures, women received less financing. Therefore, while accelerator programs signal the potential success of start-ups, it is critical to understand how these signals are interpreted differently by investors, especially when gender dynamics are involved.

Figure 1 illustrates our theoretical model. The hypotheses are explained below.

To assess the signaling effect of participation in gender-specific accelerator programs on angel investors’ investment decisions, we first intend to map the most important criteria of the decision-making process of angel investors. These are the characteristics of the entrepreneur and the management team, in particular trustworthiness (based on signals of the entrepreneur’s experience and character (Sapienza et al., 2013)), experience,2 and competence (e.g., Gürol & Ener, 2022; Hanák, 2020; Mason et al., 2017; Pierrakis & Owen, 2022; Skalicka et al., 2022). Since the experiment does not involve a live pitch or pre-information on the entrepreneurs,3 which is associated with a measurement of the first mentioned variable, in this study we focus on perceived competence as well as perceived experience, assed by industry experience and perceived market knowledge, as well-known recognized characteristics of experience. Notably, the latter is considered a particularly important factor by angel investors (Hanák, 2020; Skalicka et al., 2022).

Studies demonstrate that entrepreneurs with relevant prior industry experience have a higher chance of successfully launching their product on the market (Klepper, 2002; Thompson, 2005) and for firm growth (M. G. Colombo & Grilli, 2005). Accelerators offer avenues to connect with industry experts and the opportunity to access a network of companies (Hallen et al., 2020; Yu, 2020). Consequently, we posit that such programs can significantly contribute to enhancing the industry experience of early-stage entrepreneurs. Building upon signaling theory and considering the favorable effects of accelerators on participants, we formulate the following hypothesis: Participation in a gender-open accelerator is positively correlated with perceived industry experience (H1a). Given the emerging nature of the research domain concerning gender-specific entrepreneurship programs, there is currently limited existing literature in this area. Nonetheless, there are apprehensions that these programs may not adequately account for broader factors such as socioeconomic class and ethnicity, which extend beyond gender distinctions (Marlow & Martinez Dy, 2018). Furthermore, these initiatives have faced criticism for potentially restricting women’s access to broader networks (Harrison et al., 2020). Gendered expectations may further complicate the interpretation of signals (Edelman et al., 2018; Kleinert & Mochkabadi, 2022; Liao, 2021). Gender role congruity theory suggests that gendered expectations influence how signals from women entrepreneurs are interpreted by investors. Additionally, Heilman (1994) demonstrated that participants in gender-specific support measures were often perceived as less competent, both by others and, in some cases, by themselves. While her findings focus primarily on perceived competence, they provide a relevant parallel for exploring how participation in gender-specific accelerator programs may influence perceptions of industry experience. If investors view these programs as compensatory rather than merit-based, they might devalue the signals of industry experience provided by participants, aligning with the notion of gender role congruity theory that gendered expectations shape signal interpretation. Women entrepreneurs in male-dominated industries may face biases related to perceived competence and agency, particularly in fields like high-tech ventures (Thébaud, 2015; Tak et al., 2019). Therefore, while we posit a positive relationship between gender-open accelerator participation and perceived industry experience, we must also consider the impact of gendered biases on signal reception. Therefore, we assumed that there is a negative relationship between participation in a gender-specific accelerator and perceived industry experience (H1b). The entrepreneurs’ industry experience can positively impact companies’ survival rates (Delmar & Shane, 2006) and enhance the likelihood of recognizing and perceiving business opportunities within the specific industry (Cassar, 2014). As already mentioned, research shows that entrepreneurial and team characteristics, like the skills and knowledge of the entrepreneurs, are curial for angel investors’ decisions (Croce et al., 2017; Mason & Stark, 2004; Van Osnabrugge, 2000). Furthermore, Fiet (1995) noted that angel investors rely on the entrepreneur to evaluate market risk. Consequently, entrepreneurs with relevant industry experience are more likely to effectively assess the market, thereby providing greater security to angel investors. We therefore hypothesize that perceived industry experience will act as a mediator influencing access to angel capital (H1c, H1d).

A great challenge of especially early-stage entrepreneurs is to understand their target market and therefore to develop a successful marketing strategy (Radojevich-Kelley & Hoffman, 2012). Accelerators contribute to the establishment of a new venture by aiding in the modeling of the business concept and identifying a suitable entry strategy into the target market (Uhm et al., 2018). Particularly tailored accelerator programs within specific industries can facilitate the acquisition of specialized market knowledge (Hochberg, 2016). Hence, we hypothesized that investors perceive participants who have undergone an accelerator program as possessing enhanced market knowledge (H2a). However, gendered biases could complicate this perception. Gender role congruity theory posits that investors may interpret market knowledge differently depending on the entrepreneur’s gender. Women entrepreneurs may face biases that question their market knowledge, particularly when involved in male-typed industries. Furthermore, taking into account potential stigmatization and stereotyping that may arise within gender-specific support programs (Marlow & McAdam, 2015; Mmbaga et al., 2020), we again postulated a negative association between gender-specific accelerator programs and the perception of market knowledge (H2b). Given our understanding that the expertise and capabilities of entrepreneurs play a crucial role in the development of early-stage companies (M. G. Colombo & Grilli, 2010), and that angel investors place significant importance on the human capital of entrepreneurs (Mason & Stark, 2004; Svetek & Drnovšek, 2022), particularly in the initial stages (Ko & McKelvie, 2018), we hypothesize that the perceived market knowledge displays a positive correlation with access to angel capital. Moreover, we propose that perceived market knowledge functions as a mediator in our model (H2c, H2d).

As mentioned above, in addition to scaling the business model, accelerators are also intended to help advance the entrepreneurial skills and competencies of the entrepreneurs (Cohen et al., 2019a) as well as facilitate self-reflection (Miles et al., 2017). Due to the well-known content and goals of accelerators among investors and the aforementioned signaling effect (Kim & Wagman, 2014), it can be assumed that participation in such a program also has a positive effect on the perceived competence of the entrepreneurs. In an entrepreneurial context, competence pertains to the ability to identify and capitalize on entrepreneurial opportunities (Lans et al., 2008). From this, we derive the assumption that there will be a positive relationship between participation in a universal accelerator program and perceived competence of the entrepreneurs (H3a). However, the consideration of accelerator programs that are specifically for women can be discussed controversially. In principle, the positive effect of accelerator programs should be pointed out. However, if research on non-intended negative effects of specific support measures is considered, other conclusions can be drawn. As mentioned above, Heilman (1994) showed in her study that participants in support measures were perceived as less competent by others and partly also by themselves. Moreover, studies have demonstrated that investors exhibit a bias against entrepreneurial behaviors associated with femininity (Balachandra et al., 2017). Consequently, women-specific accelerator programs may inadvertently perpetuate this bias. Therefore, we presume a negative relationship between participation in a gender-specific accelerator program and the perceived competence of the founding team (H3b). Research has shown that entrepreneurial competence is a critical factor for angel investors (Brush et al., 2018). In a study by Svetek (2023), it was emphasized that competence signals significantly influence the final decisions of the majority of investors. Therefore, we posit that the perceived competence of the founding team serves as a mediator in our proposed model (H3c, H3d).

Drawing from existing literature, it is evident that early-stage capital is not equally distributed between genders, highlighting a persistent gender bias among investors (Aernoudt & De San José, 2020; Edelman et al., 2018; Kanze et al., 2018). Investors are likely to take an entrepreneur’s gender into account to assess the venture–founder fit (Lee & Huang, 2018; Thébaud, 2015). Empirical evidence suggests that investors are more likely to allocate funding to entrepreneurs of the same gender, with women business angels displaying a greater propensity to invest in women-owned businesses (Harrison & Mason, 2007). While women tend to react more positively to affirmative action measures compared to men (Moscoso et al., 2010), both genders generally favor initiatives aimed at eliminating discrimination or ensuring equal opportunities over more controversial measures like quotas or preferential treatment. Men, in particular, are less likely to support affirmative action programs for women, often perceiving them as career threats or unnecessary due to traditional attitudes or skepticism about gender discrimination (Konrad & Hartmann, 2001). Given these dynamics, it could be assumed that women entrepreneurs who have participated in a female-specific measure will be better evaluated by women angel investors than by male investors. This assumption is grounded in the idea that women investors may align more closely with initiatives promoting equity and gender-specific support measures. Therefore, we hypothesize that the relationship between participation in a gender-open or gender-specific accelerator program and the variables of perceived industry experience, competence, and market knowledge is moderated by the investor’s gender (H4a–H4f). In summary, while our hypotheses build on established theory and prior evidence, they are formulated with respect to perceived signals in a controlled laboratory setting. We acknowledge this boundary condition and call for future research that examines whether these mechanisms also hold in real-world investor contexts

3.2. Research Design

Participants and Procedure.

Consistent with prior work, this study employed a student sample to simulate the role of angel investors. While students naturally lack the extensive entrepreneurial experience of professional business angels, they have been widely used in experimental investment research to investigate how evaluators respond to signals and biases. For instance, X. P. Chen et al. (2009) asked MBA and EMBA students to evaluate business plans as venture capitalists, and Tinkler et al. (2015) employed MBA students to study how gender, technical background, and social ties affect venture evaluations. More recently, Snellman and Solal (2022) explicitly adopted a similar design in their experiment on founder evaluations, demonstrating the established precedent of using student samples in this research stream.

This approach is appropriate for several reasons. First, structural parallels in decision-making patterns across investor groups—particularly regarding attention to team, market, innovation, and timing—make it possible to realistically capture investment logics with students when the underlying heuristics and evaluation criteria are considered (X. P. Chen et al., 2009). Second, investment decisions often rely on general cognitive heuristics and biases rather than exclusively on domain-specific expertise, which means that students provide a valid setting to study mechanisms such as gender bias or the interpretation of competence and industry experience signals. Third, student samples allow for a high degree of experimental control, minimizing unobservable contextual influences and enabling clearer identification of causal relationships—an important advantage over field studies with active business angels.

To further strengthen validity, we took care to ensure that participants from non-economic disciplines were familiar with the basic principles of equity investing. We provided brief explanations of central concepts such as angel investing, equity investment, and accelerator programs. In addition, we conducted short comprehension checks in which participants were asked to explain terms like ETFs, direct investments, savings accounts, and accelerator programs. This procedure helped ensure that all participants—regardless of their disciplinary background—understood the task and the investment-related terminology.

At the same time, we recognize the limitations of this approach. The use of student participants restricts external validity, and conclusions about actual investor behavior must therefore be drawn cautiously.

We also asked comprehension questions about the pitch deck shown in the experiment (e.g., how many team members there are) to ensure that everyone had read the pitch deck thoroughly. If a respondent provides an incorrect answer, they must rectify it before proceeding with the survey. Of these, 80 were female participants, and 147 were male participants. The study’s participants had an average age of 27.46 years, with 53.3% being of German nationality. The remaining participants were drawn from diverse countries, and, notably, a significant portion of the international participants originated from India, comprising 24.2% of the total cohort. The descriptive statistics can be found in

Table 1. Descriptive statistics.

	N	Mean	Min	Max
Female investor	80	0.352	0	1
Male investor	147	0.648	0	1
Age	227	27.46	19	53
Nationality German	121	0.533	0	1
Nationality Indian	55	0.2423	0	1
Nationality others	51	0.2447	0	1
Founding experience	21	0.09	0	1
Crowdfunding experience	45	0.20	0	1

. The entire survey is available in the Supplementary Material.

Since experiments can suffer from noise and reduced experimental power due to participants who fail to follow the instructions, we incorporated a manipulation check in order to increase the statistical power and the reliability of the dataset (Oppenheimer et al., 2009). We therefore pointed out in the introduction that participants would only receive full compensation if they answered the questions carefully. Participants who failed the manipulation check would only receive half the money. In order to ensure real decision-making processes, participants in economic experiments are often motivated with financial incentives (Koumparoulis, 2013; Nielsen et al., 2014).

After reading the instructions, participants in the study were given autonomy to choose their own computers, ensuring a randomized sample. All participants provided written informed consent for both the conduct and publication of the study, with the assurance of anonymity for their responses. They were then tasked with reviewing the pitch deck of a tech start-up (based on a real business case) which encompassed the business model, a market and competition analysis, as well as a presentation of the team including photos of the entrepreneurs. To mitigate potential bias from the pictures a pre-test was conducted to select images with similar scores in competence, attractiveness, trustworthiness, and estimated age, as these factors might influence investment decisions (Brooks et al., 2014; M. G. Colombo et al., 2022; Matthews et al., 2024). The rationale for utilizing a pitch deck to investigate our research questions is that the team characteristics presented in a pitch deck are comparatively objective, unlike other criteria such as personal fit, which can only be assessed in later stages (Franke et al., 2008).

Materials and Manipulations. In the first part of the survey, we explained the role that the participants should take on. They are a wealthy private individual in Germany who has free assets of EUR 100,000.00 (5% of their total assets), which they should invest. In this way, we wanted to ensure that the students, as private investors, fit into the setting of a business angel, which on average invest between EUR 25,000 and 100,000 in Germany (BMWK, 2014). The median ticket size per angel and financing round in 2023 was EUR 50,000 (Google for Startups & AddedVal.io, 2023) and therefore differs from Venture Capital (2.0 mn (Honold et al., 2023)) and Family & Friends. We provided three different options: (a) the start-up, (b) an ETF, or (c) a savings account.

Furthermore, they had to justify their investment decision, and regardless of which form of investment they chose, they had to assess the founding team in the categories of perceived competence, industry experience, and market knowledge. The study comprised four groups: an all-women team without accelerator participation, an all-women team from a gender-open accelerator, an all-women team from a gender-specific accelerator, and an all-men team without accelerator participation. All accelerators were stated as non-profit, governmental accelerator programs. This was clearly stated on the team presentation page (if applicable).

Measures. In our study, we examined the impact of participating in gender-open or gender-specific accelerator programs as the independent variable. Perceived industry experience as well as perceived market knowledge, and perceived competence were measured using a seven-point Likert scale partly adopted from Brooks et al. (2014) and Snellman and Solal (2022), in which the participants had to assess how they perceive the founding team in terms of these three factors. These variables served as mediators in our model. We determined access to angel capital based on the investment decision made, which is why the variable is binary. If the participants decided for an investment in the start-up, number 1 was assigned. For all other investment options, the variable was coded 0. The gender of the participants functioned as a moderator in the model. Although all genders were considered in the questionnaire, the sample only resulted in a binary analysis (for women = 0 and men = 1). We controlled for several individual and contextual factors that could influence investment decisions. These included ambiguity aversion (Bonilla & Gutiérrez Cubillos, 2020), risk tolerance (Grable & Lytton, 1999), loss aversion (Li et al., 2021). Additionally, we accounted for participants’ educational background, specifically whether they were from a STEM field, as the featured start-up operates in AI-driven microstructure analysis. Further controls included prior experience with crowdfunding, which may affect the likelihood of choosing equity investments in start-ups (Hoegen et al., 2018). We also considered the investors’ previous start-up experience, operationalized as a dichotomous variable, in line with established methodologies (Mitteness et al., 2012). Finally, given evidence that cultural dimensions can shape investment behavior (Perry et al., 2015), we introduced a dummy variable for German participants. This accounted for the predominantly German composition of our international sample and allowed for an assessment of cultural background as a potential moderating factor.

Prior to applying the structural equation model in our analysis, we utilized chi-square tests to confirm the equitable distribution of gender among participants across the groups. The test results indicated no statistically significant differences in terms of gender distribution among participants in the various groups (Pearson’s χ² = 0.158; p = 0.984). To examine the experiment’s results, we utilized Wold’s (1982) Partial Least Squares (PLS) algorithm. Adhering to the approach recommended by Edwards and Parry (1993), we employed bootstrapping to determine the significance levels of coefficients in hypothesis tests. The measurement statistics are displayed in

Table 2. Measurement statistics.

	No. of Items	Theoretical Range	Actual Range	Median	Mean	SD	R-Square Adjusted
Dependent variable
Access to angel capital	0–1	0–1	0–1	-	0.612	0.488	0.235
Mediation variables
Perceived industry experience	1	1–7	2–7	5	5.264	1.259	0.190
Perceived market knowledge	1	1–7	2–7	6	6.084	1.084	0.123
Perceived competence	1	1–7	3–7	7	6.414	0.919	0.103

.

4. Results

Given that the study relied on a student sample, the findings should be interpreted as reflecting perceptions of accelerator signals in an experimental setting rather than actual investor behavior. Accordingly, “access to angel capital” in this study refers to the simulated allocation of capital by student participants, not to real-world investment decisions by practicing business angels. Nevertheless, such controlled experiments provide valuable insights into how accelerator participation may shape the perceived competence, experience, and market knowledge of founding teams, and thereby offer an important basis for understanding potential dynamics in real investor contexts.

Therefore, our sample shows no significant relationships between participation in an accelerator program and the perceived industry experience of the founding team. This applies to both gender-open and gender-specific accelerator programs. Accordingly, hypotheses H1a and H1b are rejected and consequently industry experience does not act as a mediator in our model (rejection of hypotheses H1c, H1d).

Table 3. Hypothesis and results of the PLS Analysis.

	Hypothesis	Beta	T-Value	p Values	Results
	Perceived industry experience
H1a	Participation in a gender-open accelerator program correlates positively with perceived industry experience.	0.206	1.119	0.263	Not Confirmed
H1b	Participation in a gender-specific accelerator program correlates negatively with perceived industry experience.	0.265	1.363	0.173	Not Confirmed
H1c	Perceived industry experience mediates access to angel capital when participating in a gender-open accelerator program.	0.002	0.183	0.855	Not Confirmed
H1d	Perceived industry experience mediates access to angel capital when participating in a gender-specific accelerator program.	0.003	0.197	0.844	Not Confirmed
	Perceived market knowledge
H2a	Participation in a gender-open accelerator program correlates positively with perceived market knowledge.	0.143	0.784	0.433	Not Confirmed
H2b	Participation in a gender-specific accelerator program correlates negatively with perceived market knowledge.	0.260	1.502	0.133	Not Confirmed
H2c	Perceived market knowledge mediates access to angel capital when participating in a gender-open accelerator program.	0.013	0.709	0.478	Not Confirmed
H2d	Perceived market knowledge mediates access to angel capital when participating in a gender-specific accelerator program.	0.024	1.204	0.229	Not Confirmed
	Moderation Effects
H3a	Participation in a gender-open accelerator program correlates positively with perceived competence.	0.420	2.338	0.019	Confirmed
H3b	Participation in a gender-specific accelerator program correlates negatively with perceived competence.	0.524	3.165	0.002	Rejected
H3c	Perceived competence mediates access to angel capital when participating in a gender-open accelerator program.	0.051	1.875	0.061	Confirmed
H3d	Perceived competence mediates access to angel capital when participating in a gender-specific accelerator program.	0.064	2.234	0.026	Confirmed
H4a	The gender of the angel investor moderates the relationship between participation in a gender-open accelerator and perceived industry experience.	−0.851	2.809	0.005	Confirmed
H4b	The gender of the angel investor moderates the relationship between participation in a gender-open accelerator and perceived market knowledge.	−0.152	0.459	0.646	Not Confirmed
H4c	The gender of the angel investor moderates the relationship between participation in a gender-open accelerator and perceived competence.	−0.962	2.818	0.005	Confirmed
H4d	The gender of the angel investor moderates the relationship between participation in a gender-specific accelerator and perceived industry experience.	−0.026	0.081	0.935	Not Confirmed
H4e	The gender of the angel investor moderates the relationship between participation in a gender-specific accelerator and perceived market knowledge.	−0.027	0.080	0.936	Not Confirmed
H4f	The gender of the angel investor moderates the relationship between participation in a gender-specific accelerator and perceived competence.	−0.985	3.076	0.002	Confirmed

displays the results of the PLS analysis. Additionally, our examination of the direct effects of perceived industry experience on access to angel capital did not reveal any significant relationship, consistent with findings in existing research (Hall & Hofer, 1993; Lange & Sopp, 2024). However, it necessitates analysis through a critical lens, as participants had access solely to the pitch deck and were unable to interact with the entrepreneur team regarding the matching of past experiences in the field and the entrepreneurial character, which makes it hard to assess trustworthiness as one critical component of the decision process (Sapienza et al., 2013).

Similarly, the correlation between engagement in a gender-open or gender-specific accelerator program and perceived market knowledge is subject to the same scrutiny. Our sample analysis revealed no notable associations, leading to the rejection of hypotheses H2a and H2b. Consequently, this variable does not function as a mediator in our model (H2c, H2d).

Engaging in a gender-open accelerator program exhibited a significantly positive effect on the entrepreneurs’ perceived competence (β = 0.420; p = 0.019, two-tailed). As a result, we can confirm hypothesis H3a. Drawing upon research on the stigmatization of participants in specialized support services, we posited that the association would be adverse for gender-specific accelerators. However, we cannot substantiate this hypothesis (rejection of H3b). Conversely, the examination of the sample revealed a positive significant relationship between gender-specific accelerators and the perceived competence of the founding team (β = 0.524; p = 0.002, two-tailed). Moreover, we found a significant indirect effect of this variable on access to angel capital (β = 0.051; p = 0.061, two-tailed), thus confirming hypothesis H3c. Furthermore, we successfully identified a noteworthy indirect effect through participation in gender-specific accelerators on the perceived competence to access angel capital. In this relationship, the variable functioned as a mediator (β = 0.064; p = 0.026, two-tailed), thus supporting hypothesis H3d. Hence, our findings align with the established body of research indicating that accelerators have the potential to signal positive attributes to angel investors, serving as a quality indicator for the company and the founding team (Hallen et al., 2023; Kim & Wagman, 2014). Therefore, our study did not demonstrate that joining gender-specific accelerators results in team stigmatization or diminishes perceived competence.

We also examined how the investor’s gender influences the founding team’s perceived industry experience, market knowledge, and entrepreneurial competence. Although perceived industry experience was not found to be a significant determinant of access to angel capital, we observed important moderation effects for investor gender. Specifically, male investors rated participation in a gender-open accelerator as less indicative of perceived industry experience compared to female investors (β = −0.851, p = 0.005, two-tailed). A similar pattern was found for perceived competence (β = −0.962, p = 0.005, two-tailed), suggesting that male investors are less influenced by gender-open accelerator participation when evaluating industry experience and entrepreneurial competence. Consequently, hypotheses H4a and H4c could be confirmed. Regarding perceived market knowledge, our analysis did not reveal any evidence that investor gender moderated the relationship between accelerator participation and this outcome. Thus, we found no support for hypothesis H4b. We further conducted moderation analyses for gender-specific accelerator participation. Here, no significant moderation effects emerged for perceived industry experience or market knowledge. However, for perceived entrepreneurial competence, a significant negative interaction effect was found (β = −0.985, p = 0.002, two-tailed). This indicates that the positive effect of gender-specific accelerator participation on perceived competence is weaker for male investors. In other words, male investors are less influenced by the competence signal derived from participation in a gender-specific accelerator compared to female investors, pointing to a potential divergence in how accelerator signals are interpreted through a gendered lens. Accordingly, hypothesis H4f could be confirmed. Overall, these results suggest that signals from (gender-open and gender-specific) accelerator programs are interpreted differently depending on the gender of the investor, with female investors generally attributing more value to such participation than male investors.4

In the logistic regression robustness check (

Table 4. Results of the logistic regression analysis.

Predictor	B	SE	Wald χ2	OR (Exp(B))	95% CI for OR	p
Female Accelerator	−0.056	0.417	0.018	0.95	[0.42, 2.15]	0.894
Gender Open Accelerator	0.708	0.450	2.475	2.03	[0.84, 4.89]	0.116
Investor Gender (male = 1)	−0.162	0.370	0.191	0.85	[0.41, 1.78]	0.662
Competence	0.711	0.235	9.183	2.04	[1.29, 3.22]	0.002 *
Industry Experience	0.157	0.175	0.800	1.17	[0.83, 1.65]	0.371
Market Knowledge	0.411	0.216	3.631	1.51	[0.99, 2.30]	0.057
Constant	−7.634	1.690	20.400	—	—	<0.001

Model fit: χ²(6) = 34.28, p < 0.001; Nagelkerke R² = 0.25; Overall accuracy = 70.7%. Note. OR = Odds Ratio. CI = Confidence Interval. * p < 0.05.

), the overall model was significant (χ²(6) = 34.28, p < 0.001) and explained 25% of the variance in investment decisions (Nagelkerke R² = 0.25). Among the predictors, perceived competence had a strong and significant effect (OR = 2.04, p = 0.002), indicating that higher perceived competence more than doubled the likelihood of investment. Market knowledge showed a marginal effect (OR = 1.51, p = 0.057), while perceived industry experience was not significant. Program type (open vs. women-only) and investor gender did not have significant direct effects. These results reinforce the PLS findings by underlining the central role of perceived competence in shaping investment decisions. Table 4 demonstrates the results of the logistic regression.

Additional Evidence. To gain deeper insights into our findings, particularly regarding the consideration of gender-specific accelerators, we conducted semi-structured interviews with active angel investors based in Germany, maintaining a consistent cultural context. To ensure heterogeneity within the sample, we purposefully selected investors with diverse profiles based on criteria such as geographic region, investment ticket size, and the number of active investments. Additionally, we balanced the gender distribution among participants to capture a broad spectrum of perspectives. The characteristics of the investors are displayed in

Table 5. Overview characteristics angel investors.

Interviewee	Gender	Ticket Size	Active Investments
Investor 1	Male	EUR 20–80 k	1
Investor 2	Male	EUR 25–100 k	9
Investor 3	Male	EUR 25–250 k	7
Investor 4	Female	EUR 25–50 k	3
Investor 5	Female	EUR 50 k	1
Investor 6	Female	EUR 50–500 k	16

.

The employed sampling method is purposive sampling, predominantly recognized as subjective and selective sampling (Robinson, 2014). The investors surveyed were not informed of the actual research objective. Instead, it was generalized and communicated that this was a survey on “the impact of business angels in the start-up ecosystem”. All participants were granted anonymity and confidentiality. Consent was secured through participants signing a written declaration before each interview. The interviews commenced with four personal questions, delving into the participants’ journey to becoming angel investors and their roles in investments. Subsequently, a series of eleven open-ended questions explored their investment decisions and perspectives on support programs, such as incubators and accelerator programs. The semi-structured interviews lasted between 25 and 40 min. The interviews were conducted via GoToMeeting in German and were recorded. Each interview was transcribed, coded, and systematically analyzed for patterns using the MAXQDA 2022 software to address the research question in this study.

We followed an inductive thematic coding approach, allowing themes to emerge directly from the data rather than imposing predefined categories. First, two researchers independently coded a subset of transcripts and compared coding to ensure consistency in the codebook. Inter-coder agreement was discussed and refined iteratively, resulting in a final coding scheme applied to all interviews. This process enhanced the reliability and transparency of the analysis.

Results. To conceal the specific focus of the study, we initiated the inquiry with a broad question regarding the decision-making process of the individual angel investor and the factors influencing it. This approach facilitated an impartial exploration of diverse investment aspects, allowing us to objectively assess their significance and make comparisons with existing research.

The analysis revealed that soft factors significantly influence the investment decisions of angel investors. The team, in particular, plays a central role, with angel investors emphasizing the necessity of establishing trust within the team. This is demonstrated by the following quote:

“[…] So there has to be a wavelength where you say: “OK, you can build up a certain level of trust, you trust the person to just take the business forward. Or you trust that the team will still work well together in six months’ time. In other words, that the chemistry between the people is right and that it suits me. So I think that’s very important. It’s also very much a gut decision, of course. […]”

Additionally, harmony among team members and the representation of all essential skills were identified as key considerations for angel investors, which is supported by the prevailing literature. One angel investor even stated that the team supersedes the idea, which supports to the statement from Bygrave (1997) “Venture capitalists would rather invest in a grade A team with a grade B idea than in a grade B team with a grade A idea”. Other important points in addition to the business idea or the technology itself are the composition of investors, the angel investor’s own professional experience in the market, and the sustainability of the business model. Hard factors, such as the company valuation, were mentioned less frequently.

Once we understood which factors play a role for angel investors in particular, we asked them specifically how they look at accelerators and whether they take such aspects into account when making investment decisions. In this respect, the positive effects outweighed the negative ones. The primary benefits identified included the role of accelerators in fostering the growth and market comprehension of start-ups, as well as facilitating access to crucial networks. Furthermore, it was noted that participation in accelerators could serve as a signal of quality, which is highlighted by the following quote:

“[…] Well, we now have sponsors in our network who have their own accelerator programs at different stages of maturity. And for me it’s not about (unicorns), it’s about somehow investing in a substance. And the quality criteria are checked in a different way than what you can look at as a private investor. […]”

(05_P20)

One major disadvantage was when accelerators receive shares in the company for their work. Criticism was also voiced regarding the lack of differentiation, suggesting that participation in industry-specific accelerators would be a more favorable approach.

From these questions, we subsequently asked for opinions and assessments of gender-specific accelerator programs. The most frequently mentioned point centered around the preference of nearly all angel investors for inclusive approaches within start-up programs, rather than advocating for separate support programs, as demonstrated by the following phrase:

“[…] That’s why I think these initiatives are good. But we still have to make sure that we are inclusive enough. Because it’s still men out there who are funding it. And we need to mix it up even more. We really need to treat the men’s and women’s teams more equally. […]”

(06_P34)

No significant differences were found between male and female angel investors, except for one instance where a male investor unequivocally expressed doubt about the value of such support programs. Moreover, this statement highlights a lack of awareness regarding gender biases in investment decision-making.

“[…] In my opinion, this is going in the wrong direction […] I think it’s important to promote and support this, but one must be careful not to overdo it. Not to go too far, because in the end, we are investors, and ultimately, it doesn’t matter.[…]”

(01_P33)

Nevertheless, both male and women angel investors positively highlighted that these targeted support programs can indeed contribute to enhancing the self-efficacy and self-confidence of women, providing them with a valuable platform. This is highlighted by the following quote:

“[…] So basically it’s a good initiative to support women and to say, here we are giving you support, we are really helping you with this topic and so on […]”

(06_P34)

5. Discussion

In this paper, by analyzing the effects of gender-specific accelerator programs in the early stage of start-ups on the perceived investment decision of angel investors through the lens of signaling theory (Spence, 1973), including contextual insights of gender role congruity theory (Eagly & Karau, 2002), we postulated that participation in gender-open accelerator programs has the potential to positively affect the variables of perceived industry experience, perceived market knowledge, and perceived competence for angel investors—while participation in gender-specific accelerator programs might have a negative impact on these variables. We also assumed that the relationship between the variables and the investment decision is affected by the gender of the angel investor.

Our laboratory experiment, which forms the core of this study, provides strong evidence that both gender-open and gender-specific accelerator programs positively influenced angel investors’ perceptions of the entrepreneurs’ competence. Contrary to our expectations, based on gender role congruity theory, no evidence was found to suggest that participation in gender-specific accelerators leads to negative biases or stigmatization. This outcome challenges the traditional assumptions of gender role congruity theory, which posits that traits such as competence and leadership are often viewed as incongruent with traditional female gender roles and entrepreneurship (Gupta et al., 2019). One possible reason for this result is the reflection of broader societal changes in perceptions of gender and competence. Prior research has demonstrated that feminist activism and societal shifts have made gender stereotypes increasingly politically incorrect, promoting a belief in gender equality (Eagly, 2018) and promoting the calls to close the gap with effective support mechanisms (Galmangodage et al., 2025; Muntean & Ozkazanc-Pan, 2015). This evolving perspective might explain why stigmatization associated with gender-specific programs did not emerge in our study. Furthermore, it aligns with evidence suggesting that while perceptions of women’s competence are improving, even though the specific context or domain of competence being evaluated can still influence these perceptions (Eagly et al., 2020). Another possible reason is that the potentially negative effects of the gender specific accelerator programs are outweighed by other, stronger mechanisms. In particular, highly regarded accelerators serve as status signals and quality indicators (Hallen et al., 2023). The visibility and credibility of participating start-ups increase if the program itself has a strong track record, which puts stigma fears into perspective. In addition, strict selection processes by accelerators can act as a positive selection signal, showing investors that the teams have already passed an external quality filter (Assenova & Amit, 2024). The high-quality mentoring and training elements offered in many programs are also visible to external observers and can be interpreted as learning and quality signals (Gonzalez-Uribe & Leatherbee, 2018; Hochberg, 2016). Finally, accelerators facilitate access to investors through their networks and create targeted points of contact, which in turn can be interpreted as indicators of connectivity and market validity (Dalle et al., 2023). These mechanisms suggest that participation in a women’s accelerator can send positive signals about competence that outweigh any potential stigma effects. At the same time, it can be assumed that these positive effects do not have the same impact in every context. The reputation and selectivity of the program are particularly important: While high-ranking accelerators send out strong status and performance signals, programs with lower status or high acceptance rates can hardly generate any positive effects, and sometimes even have negative effects (Hallen et al., 2023). The specific program design also plays a role. If high-quality mentoring and learning opportunities are visible to investors, the chances of positive competence attributions increase; if such signals are missing, neutral or ambivalent assessments may result (Assenova & Amit, 2024; Gonzalez-Uribe & Leatherbee, 2018). However, it is important to note that in our experimental design, investors had no direct insight into the specific content or processes of the accelerator program. Instead, they were only presented with a high-quality label indicating program participation. While this label served as a credible status signal, we did not control for the actual reputation, track record, or quality standards of the underlying program. This design choice increases internal validity but limits conclusions regarding how investors would react if they had more comprehensive information about the accelerator itself.

In addition, individual characteristics and attitudes of investors act as boundary conditions: people who are critical of affirmative action measures may be more likely to interpret the women’s label as an indication of preferential treatment and thus activate stigmatization (Heilman, 1996). Our own findings, which show a lower signaling effect among male investors, are consistent with this argument. Finally, the maturity of the respective ecosystem is also likely to play a role: in established startup ecosystems, investors are more familiar with the quality of certain programs, while in less developed contexts, the same labels may have a weaker or neutral effect. Overall, our findings suggest that the competence signals of accelerator participation outweigh the potential negative effects of stigmatization and thus indirectly influence investment decisions.

The expert interviews provided additional context, reinforcing the experiment’s findings. Angel investors emphasized the importance of accelerator programs in fostering trust and competence among entrepreneurs, particularly by strengthening women entrepreneurs’ self-confidence—a factor closely linked to perceived trustworthiness and capability. This focus on confidence-building contrasts with traditional interpretations of gender role congruity theory, which suggest that traits such as assertiveness or self-assurance primarily benefit male entrepreneurs (Karlstrøm et al., 2023). Moreover, investors highlighted the relevance of soft factors, including personal skills and experience, when evaluating start-ups. This aligns with prior research showing that investors prioritize personal relationships and entrepreneurial characteristics, such as trustworthiness and competence, partly because they often spend substantial time working closely with entrepreneurs (Mason, 2008; Morrissette, 2007; Van Osnabrugge, 2000). As a result, mutual trust between investors and entrepreneurs emerges as a crucial determinant in the investment relationship (Haines et al., 2003; Sapienza et al., 2013). The rejection of hypotheses H1a and H1b as well as H2a and H2b indicates that participation in accelerator programs is not interpreted as a valid signal of perceived industry experience or perceived market knowledge. It should be noted that our experimental design included a cross-industry, non-profit accelerator rather than an industry-specific program. Such generalist accelerators typically bring together ventures from diverse sectors, with a focus on developing entrepreneurial knowledge, networking, and transversal skills rather than providing sector-specific expertise (e.g., Pauwels et al., 2016; Cohen et al., 2019b). Although the literature emphasizes that industry experience and market knowledge are central decision-making criteria for business angels (e.g., Klepper, 2002; M. G. Colombo & Grilli, 2005; Mason & Stark, 2004; Skalicka et al., 2022), this knowledge is typically inferred from the entrepreneur’s actual professional background, prior industry activities, or direct interactions with the founding team (Fiet, 1995; Croce et al., 2017; Sapienza et al., 2013). In this context, authentic indicators such as industry experience and market familiarity play a more decisive role in shaping investors’ perceptions than signals derived from accelerator participation. With regard to market knowledge, our findings similarly suggest that investors derive their assessments primarily from the substantive quality of the business model and the strategic considerations for market entry (M. G. Colombo & Grilli, 2010; Uhm et al., 2018), rather than from affiliation with an accelerator program. From the perspective of signaling theory (Spence, 1973), this outcome can be explained by the fact that signals are most effective when they are difficult to imitate and clearly linked to an underlying capability. While accelerator programs certainly emit signals about learning and development processes, they are comparatively accessible and therefore provide less credible information regarding industry-specific experience or market expertise. Instead, their signaling effect is more pronounced with respect to perceived competence and self-efficacy, as demonstrated by our findings on Hypothesis H3. This confirms that investors are more likely to interpret accelerator participation as an indicator of transversal competencies and professionalism, but not as a substitute for authentic indicators of experience such as professional background, industry networks, or demonstrated market achievements. These findings contribute to the existing literature by highlighting the discrepancy between the theoretical importance of industry experience and market knowledge on the one hand, and the practical signaling effect of accelerator programs on the other. While prior research emphasizes the central role of experience and market knowledge in the evaluation of young ventures, our results show that accelerator programs do not possess the same signaling power as biographically anchored indicators of experience. This underlines the need to interpret accelerator participation primarily as a complementary signal that enhances perceptions of competence, but does not substitute for perceived industry experience or market knowledge. Moreover, the expert interviews revealed that angel investors tend to invest in industries where they possess expertise, reinforcing previous studies that emphasize the importance of industry knowledge for angel investors (Croce et al., 2017; Mason, 2008). This suggests that while accelerator programs can improve perceptions of competence, investors still prefer entrepreneurs who share similar industry backgrounds and have relevant experience.

Importantly, our study uncovered gender-based differences in how accelerator signals are interpreted. While we hypothesized that male and female investors might evaluate founders similarly, moderation analyses revealed otherwise. In regard of gender-open accelerator programs male investors were less influenced by program participation when evaluating industry experience and entrepreneurial competence compared to female investors.

First, the confirmation of Hypothesis H4a demonstrates that the gender of the angel investor moderates the relationship between participation in a gender-open accelerator and the perception of industry experience. Industry experience is thereby evaluated differently depending on the investor’s gender, but it does not emerge as a decisive factor for investment decisions. This result indicates that accelerator signals are not interpreted uniformly but rather filtered through gender-specific interpretive frameworks. Gender-open accelerators are broadly recognized within the entrepreneurial ecosystem as merit-based institutions aimed at fostering venture growth. Consequently, female investors may be more inclined to interpret participation in such programs as a credible signal of industry-related learning and network development, while male investors rely more heavily on indicators derived from the entrepreneur’s background and professional history (Mason & Stark, 2004). Moreover, gender role congruity theory (Eagly & Karau, 2002) offers an additional explanation: since entrepreneurial and industry expertise are traditionally associated with male-typed roles, women entrepreneurs often face skepticism about their industry experience. Female investors may interpret accelerator participation as a credible corrective to this bias. The confirmation of Hypothesis H4a shows that the moderating effect of investor gender occurs in the context of gender-open accelerators, but not in gender-specific ones (H4d). This indicates that the type of support program plays an important role in shaping how investors interpret signals of industry experience. As gender-specific accelerators explicitly target women, they may be interpreted less as a marker of industry expertise and more as a form of corrective or supportive intervention. As prior studies note, such specialized programs can unintentionally shift the interpretive focus away from technical or industry-related skills toward broader notions of competence and self-efficacy (Heilman, 1994; Balachandra et al., 2017). Our results reflect this dynamic: while gender-specific accelerators positively influenced perceptions of competence (H3d), they did not moderate perceptions of industry experience. In other words, industry experience is still seen as biographically anchored and difficult to substitute through targeted support programs. Gender-open programs can shape perceptions of industry experience differently for male and female investors, while gender-specific programs are more strongly associated with competence signals (H4f) and therefore do not trigger the same moderating effect on industry experience. Specifically, the positive effect of gender-specific accelerator participation on perceived competence was significantly weaker among male investors. These findings suggest that female investors attribute greater value to accelerator signals, particularly those linked to structured entrepreneurial support mechanisms. These results are consistent with previous research on gendered perceptions in entrepreneurial finance. From the perspective of signaling theory (Spence, 1973), participation in an accelerator functions as a quality signal aimed at reducing information asymmetries between entrepreneurs and investors. However, the effectiveness of such signals depends not only on their credibility and clarity but also on the cognitive and social schemas of the receivers (Connelly et al., 2011). In this regard, investor gender emerges as a crucial moderating factor shaping the interpretation of signals (Drover et al., 2018; Nagy et al., 2012).

The differential interpretation of signals can partly be explained by the concept of homophily—the tendency of individuals to connect with those similar to themselves (McPherson et al., 2001). Building on role congruity theory (Eagly & Karau, 2002), female investors may be more inclined to perceive accelerator participation—especially in gender-specific programs—as a credible indicator of competence, since these programs directly address structural barriers faced by women entrepreneurs. For female investors, accelerator signals may therefore resonate both with personal experiences and with a broader awareness of gendered disadvantages within entrepreneurial ecosystems. Within the context of investment decisions, activist choice homophily (Greenberg & Mollick, 2017) further explains why female investors react more positively: their support may be motivated not only by similarity but also by a conscious desire to dismantle structural barriers for women entrepreneurs. This mechanism is reinforced by evidence that the prevailing entrepreneurship prototype is male-coded and agentic, making signals from women more readily accepted when they align with that prototype (Rudman & Phelan, 2008). When women display stereotypically “masculine” (agentic) behaviors to match this prototype, they can also face backlash, which further complicates signal reception.

Similarly, the interviews reinforced the experimental evidence that male investors tend to be more skeptical toward competence signals derived from accelerator participation—particularly when such programs are explicitly gender-specific. This tendency was illustrated in the interviews, where one male investor voiced critical views of gender-specific programs. This aligns with prior studies showing that men often respond more negatively to affirmative action initiatives (Moscoso et al., 2010; Konrad & Hartmann, 2001). Two interrelated mechanisms may explain this skepticism. First, male investors are more likely to adhere to traditional meritocratic norms and interpret gender-specific support as compensatory rather than performance-based (Konrad & Hartmann, 2001). Second, in line with research on gender stereotypes in entrepreneurship, male investors may implicitly associate entrepreneurial competence with agentic, masculine-coded traits, leading them to discount signals that deviate from this prototype (Balachandra et al., 2017; Lee & Huang, 2018). Consistent with earlier evidence showing that women entrepreneurs receive less funding despite offering equivalent signals of competence and experience (Eddleston et al., 2016; Kanze et al., 2018), our results suggest that male investors are more prone to stereotype-driven interpretations that devalue participation in gender-specific accelerator programs.

These insights demonstrate that accelerator signals are not universally effective but filtered through gendered interpretive logics. For female investors, accelerator programs—particularly gender-specific ones—enhance perceptions of competence. For male investors, however, such signals, although enhancing perceptions of competence, appear weaker or less credible, reflecting tensions between gender equality initiatives and entrenched beliefs in meritocracy within entrepreneurship. This duality underscores the importance of integrating signaling theory with gender studies, as it reveals that the credibility of signals is co-constructed by entrepreneurs and investors within a context of persistent gendered expectations and stereotypes.

Nonetheless, it is important to note that students in the experiment evaluated their investment decisions based solely on the pitch deck. In reality, many angel investors assess start-ups through live pitches and direct interactions with the founding team regarding shared former experiences or the character of the entrepreneur (e.g., Mason et al., 2017; Pierrakis & Owen, 2022; Sapienza et al., 2013; Skalicka et al., 2022), which can have an influence on the assessment of the start-up (X. P. Chen et al., 2009; Clark, 2008; Mason & Harrison, 2003). We therefore postulate that the investment decision is not only determined by the participation in an accelerator program itself, but by the “live” contact with the angel investor. Accordingly, future research should employ richer and more ecologically valid stimuli, such as video pitches or field experiments with real investors, to capture actual decision-making processes more directly. Given that our experimental setting relied on a student sample and on pitch decks only, the results should be interpreted as reflecting perceptions of signals rather than actual investment behavior of angel investors. The scope of the conclusions is therefore deliberately narrowed.

Moreover, the absence of a male team participating in an open accelerator condition further limits the generalizability of our findings, which should primarily be interpreted in the context of female-founded teams.

Limitations and Future Directions.

In line with the four classic threats to valid conclusions in experimental research (Shadish et al., 2002), our study primarily faces limitations regarding external validity.

First, the sample consisted of students who were asked to take on the role of angel investors. While students are frequently used as proxies for resource providers in experimental entrepreneurship research (e.g., Snellman & Solal, 2022; Brooks et al., 2014), the results primarily reflect perceptions of signals rather than actual investment behavior. Accordingly, the conclusions should be interpreted as indicative of how (gender specific) accelerator participation may be perceived, rather than as evidence of concrete investment decisions made by practicing business angels.

Although the test subjects were all in advanced academic training (master’s student, diploma student, doctoral student) or had already completed this, they had different professional backgrounds. The influence of professional knowledge on the investment decision (positive or negative) can therefore not be completely neglected—especially in the area of investments by angels investors, who are often co-founders of the start-up (Svetek & Drnovšek, 2022) and tend to invest according to their intuition and gut feeling as their own subjective investment criteria instead of doing a formal analysis (Haines et al., 2003; Mason et al., 2010; Mason & Stark, 2004; Riding et al., 1995; Svetek & Drnovšek, 2022). This limitation primarily concerns external validity (student sample as proxy for angel investors) but also touches internal validity since participants’ heterogeneous professional backgrounds may have influenced their evaluations independently of the experimental manipulation.

Furthermore, the experimental design relied on pitch decks as the main stimulus material. While this approach allowed for control and comparability, it also limits the comparability that angel investors rely on, such as verbal and non-verbal communication, interaction with the founding team, and live question-and-answer dynamics (e.g., Clark, 2008; Mason & Harrison, 2003; Mason & Rodgers, 1997; Sudek, 2006). Considering the fact that entrepreneurs usually present their business ideas to investors and the entrepreneur’s trustworthiness (based on signals of experience and the entrepreneur’s character) influences the investment decision as one of the most important criteria (Balachandra et al., 2017; Kanze et al., 2018; Sapienza et al., 2013; Tsay, 2021), the external validity should be enhanced by repeating the experiment with richer stimuli, such as video pitches, live pitch simulations, or field experiments with actual angel investors.

A further limitation of the chosen setting is related to the mentioned social-capital constraints, which women entrepreneurs could face by taking part in accelerator programs. In our experiment, the students, who had to make the investment decision, were facing the start-up as the only given investment opportunity with regard to angel investment, instead of using their own social networks to look for a potential start-up to invest in. This design choice limits external validity (since real investors choose among several opportunities) and may also influence internal validity by constraining decision strategies to a single option. Further studies therefore could use several pitch decks as an investment opportunity in the experimental setting.

Additionally, in the experiment conducted, the start-ups were composed of all-women or all-men teams. We did not include a mixed-gender team and were therefore unable to record these effects. This is due to the fact that our research addresses female accelerator programs, which limit participation in the programs to women. The integration of a mixed-gender founding team into the design thus can have an impact on the perception of the teams, as one of the individuals would not be able to participate in the program. Nevertheless, it is crucial to examine the performance of women-led start-ups in comparison to mixed-gender teams, particularly by analyzing start-ups that have not participated in accelerator programs versus those engaged in gender-inclusive accelerator programs. Our experimental design incorporated several control groups (a female team without accelerator participation and a male team without accelerator participation) as well as treatment groups (a female team in a gender-open accelerator and a female team in a gender-specific accelerator). While this design allowed us to isolate the signaling effects of accelerator participation for female-founded teams, one important condition was not included: a male team participating in a gender-open accelerator. Without this additional comparison, it remains unclear whether the observed signaling effects are specific to female teams or reflect a more general accelerator effect across team genders. This limitation restricts the generalizability of our findings, which should therefore be interpreted primarily in the context of female-founded teams.

Furthermore, the study focused exclusively on governmental non-profit accelerator programs and a single cultural context. The data were gathered exclusively in Germany, which may lead to different results when studied in other cultural contexts, as cognitive and emotional factors, influenced by cultural experiences, affect investment decisions (Statman, 2008; Calza et al., 2022; Perry et al., 2015). Future work could examine specific types of accelerators (e.g., investor-driven or corporate programs), test for cultural variations across ecosystems and the interaction between start-up type or industry affiliation and accelerator program participation, operationalizing industry affiliation as a separate variable and testing whether accelerator programs have a stronger influence in certain industries. A further limitation is provided by previous research on signaling effects in relation to participation in accelerator programs, which shows that the effect of signaling with regard to clarity, visibility, and credibility of the signals, as well as the development of efficient signal strategies, depends on the reputation, quality, and characteristics of the accelerator itself. For this study, we cannot determine how the test persons evaluated the accelerator with regard to the mentioned characteristics. We have attempted to overcome this hurdle by using a quality state for the accelerators in the pitch decks. However, we cannot determine the extent to which the status of the accelerator positively or negatively influenced or limited the signals. A further study should therefore compare the effects of high-status gender-specific accelerators with less well-recommended gender-specific accelerators in order to examine the impact of the signaling effects on the decision of the angel investors. Such extensions would provide a more nuanced understanding of how accelerator signals are interpreted in different entrepreneurial environments.

With regard to construct validity, perceived industry experience and perceived market knowledge should be captured more accurately. Future studies should consider adding items that reflect variables such as network quality, depth of market experience, or the relevance of specific industry expertise. This could help provide a more nuanced understanding of these factors and their impact on investment decisions. A related limitation is that perceived industry experience, perceived market knowledge, and perceived competence were measured using single items. While single-item measures are sometimes applied in experimental research to reduce cognitive load, they may suffer from lower reliability and increased measurement error (Diamantopoulos et al., 2012). Future research should therefore employ validated multi-item scales to strengthen construct validity.

Our findings highlight that women investors attribute greater value to signals from gender-specific accelerators than their male counterparts. However, the underlying mechanisms behind this divergence remain unclear. Future research should therefore investigate the gender dynamics at play, particularly in relation to signaling theory, to better understand why women investors interpret these signals differently. Such insights would deepen our understanding of how gender shapes the evaluation of accelerator participation and could contribute to a more comprehensive theoretical framework of investor decision making.

6. Conclusions

Given the persistent gender gap in access to external capital (Aernoudt & De San José, 2020; Becker-Blease & Sohl, 2007; Brush et al., 2018; Guzman & Kacperczyk, 2019; Kanze et al., 2018; Shuttleworth et al., 2018), especially angel capital (Aernoudt & De San José, 2020; Becker-Blease & Sohl, 2007; Brush et al., 2018) as a hindrance for women entrepreneurs (Hirschfeld et al., 2022), our research aims to investigate whether participation in gender-specific accelerator programs influence signals sent to angel investors and thus access to angel capital.

By integrating role congruence theory (Eagly & Karau, 2002; Edelman et al., 2018) into the context of signaling effects of accelerators, this inquiry aims to determine whether participation in gender-specific accelerators serves as an impediment or an advantage for women entrepreneurs in securing capital from angel investors. Additionally, this study explores whether the signaling effect of gender-specific accelerator participation is influenced not only by the gender of the entrepreneurs but also by the gender of the investor. We believe our findings offer several important theoretical and normative implications. Accelerator programs are seen as entrepreneurship education and training programs, which focus on rising human and social capital (Dams et al., 2016; Martin et al., 2013; Seet et al., 2018) and could therefore work as a signal to angel investors to overcome information asymmetries about the quality and potential of early-stage ventures (Kleinert et al., 2020; Svetek, 2022).

Our study indicates that involvement in both gender-open and gender-specific accelerators does not influence the perceived market expertise or industry experience of the entrepreneurs. Nonetheless, it does have a positive impact on the perceived competence of the founding team. Our implication concurs with the findings of Dams et al. (2022), which indicate that women entrepreneurs who undergo an accelerator program enhance their prospects of securing equity capital funding. Furthermore, our study indicates that gender-specific accelerators have not resulted in any stigmatization of female participants, contrary to assumptions based on Heilman’s (1994) research. One possible explanation for this discrepancy is provided by a recent meta-analysis on the effects of affirmative action, which found that the impact of such initiatives is moderated by the age of the study. Specifically, more recent research tends to report less negative effects associated with affirmative action (Greig et al., 2023). Furthermore, individuals also tend to act on their perceived consensus in the social environment by means of which stereotypes and beliefs are shared by most others (Troyer & Younts, 1997; Tonoyan et al., 2010; Tonoyan & Strohmeyer, 2021). A possible explanation for that is that our society has changed over time and therefore also our assumptions and beliefs changed due to societal discussions about injustices and inequality (Eagly et al., 2020; Galmangodage et al., 2025). Our research contributes to the literature on the signaling effects of accelerators, especially to angel investors, by showing that the signaling effects also apply to gender-specific accelerator programs. This finding suggests that such programs can help overcome the gender-specific challenges faced by women entrepreneurs. By forming gender-specific support measures, they could help challenge traditional gender norms and ultimately pave the way for a more inclusive and equitable entrepreneurial landscape. Studies suggest that women entrepreneurs are facing missed chances of participation in gender-open accelerator programs (Diekman & Eagly, 2008; Yang et al., 2020) and our research indicates that gender-specific support programs could promote women’s participation and success in entrepreneurship with regard to signaling effects to angel investors. Furthermore, our research contributes to signaling theory by demonstrating that it is not solely the gender of the entrepreneur (Alsos & Ljunggren, 2017; Edelman et al., 2018) that affects the evaluation of signals, but also the gender of the investor that shapes the perception of accelerator programs. Female investors appear more responsive to accelerator signals, a pattern that may be explained by mechanisms of homophily and activist choice homophily (McPherson et al., 2001; Greenberg & Mollick, 2017), whereby investors consciously support underrepresented groups facing structural barriers. However, the gender of the investor also influences perceived competence differently, with male investors showing lower responsiveness to accelerator participation signals.

At the same time, insights from our interviews reveal a critical tension: while targeted support for women entrepreneurs is important, angel investors often express a preference for more inclusive approaches within the entrepreneurial ecosystem. Current research highlights that gender stereotypes not only disadvantage women entrepreneurs but also penalize men who exhibit female-stereotypical traits (Avnimelech & Rechter, 2023; Balachandra et al., 2017), who might be excluded from women-only programs. Moreover, underlying homophily patterns in angel investing—with male investors tending to support male-led ventures (Edelman et al., 2018; Ewens & Townsend, 2020; Oranburg & Geiger, 2019)—could place participants in gender-specific programs at a social capital disadvantage. McAdam et al. (2019) caution that separatist solutions for women entrepreneurs may limit access to vital economic, cultural, and symbolic capital, restricting their ability to establish credibility within broader entrepreneurial fields. Similarly, Arshed et al. (2023) argue that experienced and growth-oriented women entrepreneurs may find greater benefit in tailored, inclusive support structures rather than exclusively gender-segregated spaces. These insights underscore the importance of designing support measures that enhance inclusion without reinforcing segregation.

Gender-specific signaling effects manifest themselves in accelerator programs in a distorted perception of founder personalities and company profiles. Traditional gender stereotypes act as a filter that often penalizes the signals from companies led by women. These unequal framework conditions not only require a critical reflection of existing structures, but also targeted measures to create a more inclusive and fairer entrepreneurial environment. The need for customized approaches that take into account the specific challenges of women is crucial for the promotion of equitable entrepreneurial ecosystems (Neumeyer, 2022). Understanding these dynamics is critical for accelerators that aim to foster diverse and inclusive entrepreneurial ecosystems, as accelerators can unintentionally perpetuate existing gender and cultural norms, leaving the systemic inequalities faced by women unchallenged (Galmangodage et al., 2025).

At the same time, it is important to emphasize that the conclusions drawn from our study are based on perceptions of signals in a controlled laboratory experiment with a student sample. Accordingly, the external validity of our findings is limited, as they do not directly capture actual investor behavior. Future research should therefore investigate whether the identified mechanisms also hold in real-world contexts, for example by using video pitches, live interactions, or field studies with practicing business angels. Moreover, our experimental design did not include a male team participating in an open accelerator, which further constrains the generalizability of the results. The conclusions of this study should therefore be interpreted primarily in the context of women-founded teams, and future research is encouraged to replicate and extend the design by incorporating a male team with open accelerator conditions to assess whether the observed signaling effects are gender-specific or more generalizable.

Still, we provide particularly practical implications for organizations wanting to promote entrepreneurship and improve access to finance for women entrepreneurs. While both gender-specific and gender-open accelerator programs are successful instruments for increasing the perceived team competence and thus increasing the investment probability of angel investors, we recommend pursuing a more inclusive approach, as the signaling effect to men angel investors does not appear as great as for women angel investors. Moreover, gender-specific support programs risk segregating women into separate networks without facilitating access to other vital networks, as highlighted by the interviews with angel investors, and already pointed out by scholars (Harrison et al., 2020; McAdam et al., 2019). In this respect, a need- and phase-oriented orientation of gender-open accelerator programs could offer a potential solution and should be investigated further—as already mentioned by Arshed et al. (2023). Modular components of the accelerator programs, which can be selected according to the individual needs of the start-ups, could enable both women and men who exhibit female-stereotypical traits to be included in the ecosystem and still address current hurdles.