New venture legitimacy diffusion beyond the local entrepreneurial ecosystem: the transformative role of brokerage and network activities

Abstract

Purpose

New ventures often encounter legitimation challenges due to their liability of newness and foreignness. This particularly applies to the legitimacy beyond the local entrepreneurial ecosystem (EE). The present study examines how new ventures’ local legitimacy influences legitimacy diffusion beyond the local EEs. It considers both the direct relationship between new venture local legitimacy and its diffusion beyond the EE and the moderating effects of legitimacy brokerage and network activities on this relationship.

Design/methodology/approach

A hierarchical multiple linear regression is employed to test a series of hypotheses using the data of 228 Finnish firms which was collected with an online survey.

Findings

Firms that garner active local legitimacy have a greater chance to diffuse that legitimacy beyond an existing ecosystem. Results also reveal that network activities and legitimacy brokerage enhance (positively moderate) the association between (passive and active) local legitimacy and its diffusion.

Originality/value

The present study contributes to and extends the literature at the intersection of new venture legitimacy and legitimacy diffusion beyond the existing EE – an aspect which has not been sufficiently studied.

Citation

Kansheba, J.M., Fubah, C.N. and Wald, A. (2024), "New venture legitimacy diffusion beyond the local entrepreneurial ecosystem: the transformative role of brokerage and network activities", International Journal of Entrepreneurial Behavior & Research, Vol. 30 No. 11, pp. 164-180. https://doi.org/10.1108/IJEBR-08-2023-0867

1. Introduction

A new venture is legitimate when it is perceived by others as desirable and appropriate within a socially constructed system of norms, values, beliefs and definitions (Zimmerman and Zeitz, 2002). Establishing and legitimizing a new venture in the face of a diverse range of audiences is challenging (Fisher, 2020) and requires a delicate balance between conforming to established norms and pushing boundaries to break new ground. Garnering legitimacy can be already difficult in the local entrepreneurial ecosystems (EEs), with even stronger challenges for the diffusion of legitimacy beyond the existing EE – an aspect which has not been sufficiently studied.

Obtaining legitimacy entails receiving an active or passive judgment from other actors (Tost, 2011). In the passive scenario, audiences within the EE in which the business operates invest very little effort to determine whether the venture is legitimate; whereas, in the active scenario, audiences make considerable effort to determine the legitimacy of the venture (Tost, 2011). These audience judgments (both active and passive) are critical to the venture because they influence important aspects, such as access to critical resources (Elfring et al., 2021).

The venture must first be deemed legitimate by internal actors, as this will allow them to disseminate information about the legitimacy of the new venture beyond or to the external institutional environment (Kuratko et al., 2017). Thus, the legitimacy of new ventures beyond EEs is somehow dependent on the venture’s legitimacy in the internal environment. However, despite the growing body of knowledge on possible approaches for new venture legitimacy (Fisher et al., 2017; Suchman, 1995; Überbacher, 2014; Zimmerman and Zeitz, 2002), there is limited empirical evidence on how various legitimation strategies influence new ventures’ legitimacy beyond existing EEs (Kuratko et al., 2017). The first research question of this paper is therefore:

• (1)

  How do new ventures’ (active and passive) local legitimacy influence their legitimacy (diffusion) beyond existing EEs?

Network activities, ties and information flow between different audiences and across different institutional settings also aid in the legitimacy of new ventures in various settings (Elfring et al., 2021). In this regard, diverse network ties can be used to broker information across multiple audiences, where trusted brokers in the local community with a high reputation outside the community can signal to other audiences (in other communities) that the venture is appropriate (Elfring et al., 2021). Accordingly, the second research question can be specified as follows:

• (2)

  How do legitimacy brokerage and network activities influence (moderate) the relationship between new ventures’ local legitimacy and their legitimacy diffusion beyond existing EEs?

To answer the research questions, the study at hand examines how new ventures’ local legitimacy influences their legitimacy diffusion beyond existing EEs. The study also explores the moderating effects of legitimacy brokerage and network activities on the relationship between new venture local legitimacy and its diffusion. Based on survey data from 228 Finnish firms, a hierarchical regression analysis is employed to test the hypotheses. The analysis reveals that firms that garner active local legitimacy have a greater chance to diffuse that legitimacy beyond an existing ecosystem. Results also reveal that legitimacy brokerage and network activities enhance (positively moderate) the association between (passive and active) local legitimacy and its diffusion. Thus, the present study contributes to and extends the debate by presenting a more nuanced and empirical-based understanding of the dynamics of focal actors (entrepreneurs) and how they legitimize their new ventures beyond their local EE.

The paper is organized as follows. Section 2 provides a review integrating ideas from entrepreneurship and legitimacy literature, which results in the hypotheses development. Section 3 documents the methods and data used. Section 4 provides the findings, followed by the discussion in Section 5. Section 6 concludes the paper with implications and avenues for further research.

2. Literature review and hypotheses development

2.1 Entrepreneurial ecosystems and new venture legitimacy

EEs “are combinations of social, political, economic and cultural elements within a region that support the development and growth of innovative startups and encourage nascent entrepreneurs and other actors to take the risks of starting, funding, and otherwise assisting high-risk ventures” (Spigel, 2017, p. 50). Legitimacy, on the other hand, is a “generalized perception or assumption that the actions of an entity are desirable, proper, or appropriate within some socially constructed system of norms, values, beliefs and definitions” (Suchman, 1995, p. 574). Legitimacy is an essential asset for new ventures, as it facilitates their access to critical resources while overcoming the liability of newness (Fisher, 2020; Fisher et al., 2017; Kuratko et al., 2017) and the liability of foreignness (Hymer, 1960). The liability of newness is associated with the fact that new organizations lack important relationships with other actors (and consequently lack of trust) which makes it difficult for them to be considered legitimate by such actors (Stinchcombe, 1965). The concept of the liability of foreignness which stems originally from international business has not yet been applied in EE research. It is associated with the additional cost that foreign firms incur in comparison to local firms (Hymer, 1960; Zaheer, 1995). To overcome the liability of foreignness and compete successfully with local firms, foreign firms need to provide some advantages to their firms which can enable them to get legitimacy. Moreover, research suggests that the acquisition and flow of resources into new ventures mainly depend on their legitimacy (Becker-Blease and Sohl, 2015; Fisher et al., 2017; Nagy et al., 2012). As such, investors will be reluctant to invest in ventures that are not legitimate.

An essential feature of EEs is their focus on creating a conducive environment for entrepreneurial activities and new venture creation (Longva, 2021). EE scholars have identified different elements that drive entrepreneurial activities within different geographical settings (Kansheba et al., 2024; Nicotra et al., 2018; Stam and Van de Ven, 2021). These elements include networks, finance, knowledge and talent, leadership, markets and infrastructure. Moreover, Stam and Van de Ven (2021) categorize these essential elements into systemic and framework conditions whose continuous interactions define EE quality and output (productive entrepreneurship).

Entrepreneurs depend on other ecosystem actors for resources to launch and grow new ventures (Fisher et al., 2017). However, nascent entrepreneurs usually face enormous challenges when looking for resources for their new ventures compared to established entrepreneurs (Fisher et al., 2017; Überbacher, 2014) due to their liability of newness (Stinchcombe, 1965) and liability of foreignness (Hymer, 1960). Moreover, Kuratko et al. (2017) posit that technological and market newness are a significant liability for new ventures. Research also suggests that these new venture challenges are sometimes due to their inability to secure resources from investors due to their lack of legitimacy (Nagy et al., 2012). In line with this, prior research (Zimmerman and Zeitz, 2002) argues that legitimacy is an invaluable asset for new ventures and critical for their operations in the early years. As such, legitimacy enables new ventures to overcome their liabilities of newness and foreignness and, consequently, increases their chances of survival (Überbacher, 2014).

2.2 Legitimation mechanisms and strategies

Prior research (e.g. Fisher et al., 2017; Zimmerman and Zeitz, 2002) identified different mechanisms and strategies that new venture owners can use to legitimize their venture. Accordingly, Fisher et al. (2017) categorized the different legitimation mechanisms into identity mechanisms, associative mechanisms and organizational tools. The identity mechanisms revolve around the entrepreneurs’ use of cultural tools and identity claims such as language, images and symbols to acquire new venture legitimacy. In this regard, the use of cultural tools, stories and language that is understood by certain groups can enable the entrepreneur to establish (some) credibility and consequently legitimacy (Clarke, 2011; Navis and Glynn, 2011; Zott and Huy, 2007). The associative mechanisms focus on the relationships of the entrepreneur with other important market actors. As research indicates, having strong and established relationships with key actors can signal to other actors that the business has evaluative approval and, as a result, should be regarded as legitimate (Fisher et al., 2017; Rindova et al., 2007). The organizational mechanism is associated with the implementation of specific organizational standards and structures, as well as critical organizational achievements that can aid in the venture’s legitimacy (Fisher et al., 2017).

The different legitimation strategies (Zimmerman and Zeitz, 2002) are associated with either active or passive audience judgments (Tost, 2011). These strategies include conformance (complying with the rules and regulations that govern their operations in a specific setting), selection (locating a business in the most advantageous setting), manipulation (changing rules and regulations to accommodate one’s business) and creation (creating new rules to guide business operations) strategies (Suchman, 1995; Zimmerman and Zeitz, 2002). The degree of novelty and associated uncertainty in a venture determines which strategies to implement and which legitimacy judgment the audience can render (Elfring et al., 2021).

To be considered legitimate, new ventures should first gain local legitimacy (from the audience) within their existing EEs (Fisher et al., 2017; Suchman, 1995; Überbacher, 2014). The audience comprises those in close/direct contact with the venture and its founder. Being in close contact enables the individual to judge whether the venture meets their expectations to be considered legitimate. Individuals engage in either an evaluative (active) or a passive information processing process to judge the appropriateness, desirability or legitimacy of a new venture (Tost, 2011). In the passive assessment scenario, individuals within the EE use minimal effort to validate a venture as legitimate if it meets their expectations (Tost, 2011). The active assessment scenario involves those in the EE expending efforts to determine and consider the venture legitimate (Kuratko et al., 2017; Tost, 2011). To be accepted as legitimate by the evaluative judgments of institutions, individuals and resource providers within the EE, new ventures have to prove their worth (must be appropriate and desirable) (Molecke and Pinkse, 2020; Tost, 2011; Überbacher, 2014).

2.3 New venture legitimacy diffusion beyond existing entrepreneurial ecosystems

Establishing legitimacy takes a significant amount of time and effort since the audience has to understand the offering before making a legitimacy judgment and, thus, does not happen quickly (Suddaby et al., 2017). The new (and established) venture legitimacy judgment is an integrative process that begins with innovation (local), judgment formation and then judgment diffusion (Tost, 2011). According to Kuratko et al. (2017), legitimacy diffusion is the degree to which a venture’s knowledge and comprehension spreads outside of a local (existing) EE. The diffusion scope indicates the venture’s knowledge and acceptance reach outside of its immediate ecosystem audience. Furthermore, legitimacy diffusion occurs when other actors in the larger population (other than in the immediate ecosystem) view the firm as a way to solve their problems. According to Johnson et al. (2006), the degree of local validation (judgment) of actors in an existing ecosystem affects the venture’s adoption by actors in new (social contexts) ecosystems. They also contend that for new ventures to be recognized more widely, they must first be validated by local actors, either by explicit or implicit acceptance. Therefore, localized representations and the venture’s increasing prominence are necessary for disseminating legitimacy.

Tost (2011) characterizes two (local) ways of judgment construction, which can be either be unconscious (passive) or an evaluative (active) processes of information processing. The impact of these two-venture judgment processes within a local ecosystem on the diffusion of legitimacy may differ. Active local legitimacy (validation) entails concerted efforts to create judgments. Local ecosystem actors are incentivized to shape the venture’s judgment by virtue of their instrumental, relational and moral assessments. Institutional theory holds that this proactive endorsement contributes to the venture’s perceived legitimacy and conformance with existing social notions (DiMaggio and Powell, 1983). Positive word-of-mouth and knowledge sharing beyond the current EE are likely to be sparked by the increased legitimacy, which is reinforced by local actors’ conscious validation efforts (Zimmerman and Zeitz, 2002). Consequently, the new venture gains affiliation with an expanded network of legitimacy, resulting in increased dissemination in new ecosystems. On the other hand, modest judgmental efforts associated with passive local legitimacy may result in a restricted transmission of legitimacy (Tost, 2011). According to this type of local legitimacy, people make decisions by merely accepting something as conforming to their existing social constructs or utilizing cognitive shortcuts such as validity cues (Kuratko et al., 2017). The venture’s acceptance and proliferation in larger contexts may be limited because participants in other (social contexts) ecosystems see this passive evaluation as a less strong endorsement. Accordingly, the authors hypothesize the following:

H1.

New venture active local legitimacy positively relates to legitimacy diffusion beyond the existing EE.

H2.

New venture passive local legitimacy negatively relates to legitimacy diffusion beyond the existing EE.

2.4 The moderating role of legitimacy brokerage and network activities

Network activities and legitimacy brokerage can moderate the relationship between local legitimacy (both active and passive) and its spread outside of the current ecosystem. Legitimacy brokerage refers to the process of exchanging information about the new venture between actors both inside and outside of the existing EE (Kuratko et al., 2017). The legitimacy signals propagate more widely and gain credibility when EE actors actively participate in verifying the new business and simultaneously disseminate this information. According to Tost (2011), the deliberate and intentional efforts of venture validation guarantees that the information communicated is positively framed and of value, highlighting the venture’s congruence with prevalent social conceptions. Therefore, high legitimacy brokerage promotes a wider acceptance and diffusion of legitimacy by efficiently distributing these favorable signals outside of the local EE.

Furthermore, in the event of passive local legitimacy, the existence of strong legitimacy brokerage might compensate for the absence of deliberate validation by improving information flow, which promotes wider acceptance and diffusion. A high level of information exchange plays a compensatory role in the context of passive local legitimacy when validation attempts may be modest or indirect. According to Zimmerman and Zeitz (2002), passive local legitimacy may be perceived as having less credibility or sending out weaker signals of adherence to established social norms since it lacks the intentional efforts associated with active legitimacy. On the other hand, high legitimacy brokerage actively promotes the venture’s informational transmission, serving as a compensation mechanism. The widespread distribution and regularity of information transfer could compensate for less validation efforts (Burt, 2007). In this case, the sheer number and variety of actors engaged in the information-sharing process may cause the legitimacy signals (though of low value) to become more prominent. The wide information flow created by high legitimacy brokerage can fill the gap, encouraging wider acceptance and dissemination of legitimacy for the venture, even though the validation may not be as deliberate or effortful as in the case of active legitimacy (Tost, 2011). The subtle dynamics of legitimacy dissemination are emphasized by this compensatory process, which also shows the importance of information flow made possible by legitimacy brokerage in reducing the possible drawbacks of passive local legitimacy.

Moreover, the influence of both passive and active local legitimacy on the dissemination of legitimacy is significantly shaped by network activities. According to Bloodgood et al. (2017), network activities encompass the strategic relationships a new business makes inside and outside its current EE. In addition to improving the venture’s visibility and credibility, robust network activities may offer ways to increase the effect of deliberate validation efforts (the case for active local legitimacy) (Elfring et al., 2021; Tajeddini et al., 2020). Taking part in collaborative ventures, partnerships and alliances within the network can act as channels for the effective dissemination of positive signals (Kuratko et al., 2017), which can lead to a wider diffusion of legitimacy. On the other hand, strong network activities could offset the lack of intentional validation attempts (the case for passive local legitimacy). Engaging in external networks can help offset the limited local validation by creating relationships and partnerships that extend the venture’s legitimacy outside the local ecosystem. Thus, the authors hypothesize:

H3a/b.

Legitimacy brokerage positively moderates the influence of (a) active and (b) passive local legitimacy on legitimacy diffusion.

H4a/b.

Network activities positively moderate the influence of (a) active and (b) passive local legitimacy on legitimacy diffusion.

3. Data and method

As Brown and Mason (2017, p. 12) argued, the concept of the EE as a “highly variegated, multi-actor and multi-scalar phenomenon” remains obscure. This obscurity is due to the diversity of definitions and the various degrees and multidimensionality of analysis (Neumeyer and Santos, 2018; Kansheba and Wald, 2020). Following Theodoraki et al. (2020), this study takes the EE as the context and focuses on examining the new venture’s local legitimacy and its (spread) diffusion beyond an ecosystem through the perspective of focal actors (i.e. entrepreneurs and their ventures).

3.1 Data collection and sample

This study employs survey data to test the hypotheses. The authors collected the data using an online survey administered to Finnish firms’ top managers. The Finnish startup ecosystem is one of Europe’s most vibrant and innovative. Finland has a strong network of accelerators and investors that are actively supporting the growth of startups. Based on the Ministry of Economic Affairs and Employment of Finland (MEAEF, 2023), the Finnish government has also created numerous initiatives to encourage the growth of startups in the country. Each ecosystem has a different emphasis on particular industries and strategies for promoting and supporting startups and entrepreneurs. Business Helsinki, for example, has a strong focus on technology and innovation, while Business Tampere has a strong focus on digitalization and Industry 4.0.

The authors first pre-tested the survey by circulating 20 questionnaires to fellow academics and few selected business respondents. Their feedback helped the authors to modify the survey before administering it to a large sample. Thereafter, a link to the questionnaire was sent to 1,000 contacts identified via specialized websites and support networks. The authors received 360 completed questionnaires after three rounds of follow-up reminders. The authors removed 132 questionnaires from the analysis due to incompleteness (missing items) and straight-lining problem, where respondents fill in identical answers to 10 or more consecutive items from distinct constructs. As a result, 228 questionnaires (22.8%) remained in the sample. The sample profile indicates a reasonable spread across demographic and firm characteristics of the respondents regarding gender, age, position, firm size and sector (see Table 1). Most respondents (67%) were firm owners, while the remainder were managers. These two respondent types were selected because they have knowledge and comprehension of their businesses’ dynamics. Health care (24%) was the most common industry, followed by information technology (26%), hotels (23%), and construction (18%) and 9% in financial services.

3.2 Constructs and their assessment

To operationalize the investigated constructs, the authors adopted a 7-point Likert scales of newly developed (based on the extant literature) and existing (with slight changes to fit the studied context) measures. Table 2 shows the constructs and their related measurements. The authors started with an exploratory factor analysis (EFA) and removed items that did not load onto their respective constructs effectively. The authors kept items with factor loadings of 0.7 or above. The data were then evaluated for convergent and discriminant validity. Cronbach’s alpha and composite reliabilities were higher than 0.7 for all constructs. The extracted average variance (AVE) exceeded the 0.5 threshold, showing construct validity. Furthermore, the AVE values were more significant than the squared correlation between latent constructs, confirming discriminant validity. Table 1 includes the findings on validity and reliability.

The authors considered several control variables. First, the demographic nature of the audience (other EE members) that validates the ventures or entrepreneurs (startup owners and/or managers) may influence the legitimacy judgment. Biases based on gender may influence how entrepreneurs are viewed (e.g. Pistilli et al., 2023), which may have an impact on the spread of their legitimacy. Given its potential correlations with experience, networking skills, general trustworthiness and age are also an important control variable. More experienced business owners/managers may have wider pool of connections (Kotha and George, 2012) that aid in the spread of legitimacy. Higher educated entrepreneurs may be seen as more successful, capable and credible (Millan et al., 2014), which may influence their legitimacy judgement and diffusion. Different industries may have differing standards and expectations regarding legitimacy. Additionally, firm age reflects the time a firm had to establish itself within a local (and beyond) EE. Firm size reflects resources and capabilities (Verwaal et al., 2010), which play a role not only in forging but also in diffusing legitimacy. Large firms may have more resources to devote to legitimation tactics.

3.3 Non-response and common method biases check

The authors checked for non-response bias following Shneor and Munim (2019). The sample was divided into two sub-samples of 114 respondents each. The mean differences in chosen demographic characteristics were then compared between these sub-samples. The findings (see Table 2) revealed no statistically significant mean difference, indicating no major non-response bias. The authors used Harman’s single factor and common latent factor tests to check for and confirm the absence of a common method bias. The single-factor analysis revealed that approximately 3% of the variation fell below the 50% threshold, indicating that common method bias is of minor concern. Furthermore, the common factor was uncorrelated with other latent factors, and all common factor measurement items had equal factor loadings set at 0.07. This equal factor loading number indicates that the common factor accounted for approximately 0.0049 of the variances, significantly below the suggested threshold of 0.5.

4. Results

Hierarchical multiple linear regressions were used to test the hypotheses. The variables were standardized before computing their product terms to reduce the risk of multicollinearity among the moderating variables (Theodoraki et al., 2020). Results in Table 3 indicate that collinearity was not a concern, as the variance inflation factors (VIFs) for all the variables included in the models were below 1.70. Table 3 provides the hierarchical regression results of new venture legitimacy diffusion beyond existing EE. Model 1 is the base model for the new venture legitimacy diffusion beyond existing EE. The model only consisted of the control variables and accounted for 13% of the new venture legitimacy diffusion variance.

After that, new ventures passive and active local legitimacy within the existing ecosystem were introduced in model 2. The results show that only new ventures’ active local legitimacy has a positive and significant influence on their legitimacy diffusion beyond existing EE, thus, supporting H1. The results do not support H2 regarding the negative association between the new venture’s passive local legitimacy and legitimacy diffusion. Overall, the added variables have a significant contribution to the base Model 1 (ΔR² = 0.13, p < 0.05). The moderating variables were then introduced in Model 3 revealing a significant contribution (ΔR² = 0.10, p < 0.01) The final Model 4 tested the interaction effects on the relationship between (passive and active) local legitimacy and legitimacy diffusion (see Table 3). Although the introduction of the interacting variables had a limited contribution (ΔR² = 0.04, p < 0.1), the results still show and support H3 and H4 postulated the positive and significant moderating role of legitimacy brokerage and network activities, respectively.

Moreover, the authors follow Mitchell (2012) in generating the interaction graphs where the mean values of the moderators were adjusted by ± 1 standard deviations to examine their influence on the new venture legitimacy diffusion beyond the existing EE. Figures 1 and 2 illustrate the moderating effects of legitimacy brokerage and network activities on the diffusion of new venture legitimacy beyond the EE. According to Figure 1, new venture local legitimacy is more likely to propagate broadly when there is a strong moderating effect from legitimacy brokerage, particularly for ventures with high local legitimacy and active brokerage. On the other hand, Figure 2 shows that network activities moderate the relationship between new venture local legitimacy and its diffusion. This implies that the successful spread of new venture legitimacy depends on active participation in these networks, especially when coupled with high local legitimacy. Overall, results illustrate the critical roles that network interactions and strategic brokerages play in enabling the external legitimacy of new ventures, highlighting them as essential components for entrepreneurial success outside of established ecosystems.

A post-hoc analysis of the residuals revealed there were no violations of variance homogeneity or linearity, as well as the absence of any cases that were either very influential or extreme. As a result of the preceding tests, the regression model appears accurate and robust for the sample and generalizable to the population.

5. Discussion

The EEs’ goal is to foster an entrepreneurially supportive environment for entrepreneurs and their (new and existing) companies. As a result, EEs can be resource centers and habitats for innovative entrepreneurs (Kansheba and Wald, 2020; Lux et al., 2020). However, with their modest size and inexperience, entrepreneurs often need help establishing their credibility and legitimacy within and beyond their existing EEs (Lechner et al., 2022). According to Kuratko et al. (2017), one of the disadvantages of the newness of entrepreneurs and their new ventures is that they need to be more familiar and better understood by other ecosystem members, individuals and organizations.

Fisher et al. (2017) added that new businesses typically struggle to obtain crucial entrepreneurial resources and assistance such as money, strategic alliances and media exposure. Despite its novelty, current research shows that there is still limited knowledge on how entrepreneurs, as the focal point of EEs, may demonstrate their credibility/legitimacy for their new companies within and beyond their existing ecosystems (Kuratko et al., 2017). In answer to this call, the authors empirically examined how the (passive and active) local legitimacy within the local ecosystem influence the subsequent legitimacy diffusion beyond the current ecosystem. The authors also examine the moderation role of legitimacy brokerage and network activities on the linkage between local legitimacy within the existing ecosystem and its diffusion beyond the existing ecosystem.

The study revealed that new venture’s active local legitimacy positively influences legitimacy diffusion beyond existing EEs (supporting H1). If new ventures do not comply to the rules and regulations in their operating environment, it triggers the need for actors in the local EE to judge the offering of the venture (its legitimacy) in a concerted effort. Similarly, new ventures that find it difficult to adhere to the rules and regulations within their operating environment tend to create their own operating rules or manipulate (convince) audiences on the legitimacy of their ventures (Zimmerman and Zeitz, 2002). They accomplish this by putting forth efforts on strengthening existing relationships while also establishing new relationships with actors within the local EE, who are also part of the audience that assesses the legitimacy of new ventures. As such, all the venture’s efforts are aimed at influencing social structures and persuading the EE audience to accept the venture as a legitimate entity. Consequently, the established relationships are more likely to spread information to other audience members, who will then spend some time (actively) evaluating the information about the new venture, thereby forming an opinion on its legitimacy (Bitektine, 2011; Suddaby et al., 2017). As a result, this study argues that once the new venture has captured and gained the trust the actors within the local EE, the local audience will disseminate critical information about the new venture (legitimacy diffusion) beyond their (local) existing EE.

Although the results show an insignificant relationship between new ventures’ passive local legitimacy and their legitimacy diffusion beyond existing ecosystems (H2), it is still worth mentioning that the negative association among the two variables remained consistent throughout all models. This consistency in their association might indicate that when a new venture conforms to the rules and regulations or decides to locate itself in an operating environment with favorable rules and regulations, it is most likely that audiences will not be actively involved in forming an opinion on its legitimacy since it fits within the norms. Thus, they passively judge the legitimacy of the venture. As passive local legitimacy judgments are constrained, new companies may achieve some acceptance within the EE but may not be entirely (actively) welcomed or regarded as legitimate organizations. As previously documented by Bloodgood et al. (2017), this could be attributed to reasons such as their newness, lack of experience or inadequate integration into the ecosystem’s social networks. Ultimately such limited validation hinders the spread of information regarding the ventures beyond their local ecosystems.

The results also show a nuanced relationship between network activities, legitimacy brokerage and the influence of new ventures’ local legitimacy within and beyond their current EEs. Network activities help ecosystem actors collaborate and exchange information and access resources. These actions increase new ventures’ perceived value and visibility. By actively participating in network activities, ventures can access common resources, expertise and social capital, which strengthens their credibility both inside and outside of their immediate ecosystem. Conversely, legitimacy brokerage entails information sharing about ventures’ activities among actors both within and beyond immediate ecosystem. Brokers are essential channels for spreading good news (signals) about the ventures, which enhances their perceived legitimacy both inside and outside of the current EE. In addition, brokers serve as middlemen, navigating the knowledge gaps and unpredictabilities related to startups. Through dissemination of positive information, brokers are essential in influencing opinions and establishing the ventures’ credibility.

5.1 Theoretical implications

This study advances the knowledge of legitimacy in EEs. In contrast to earlier theoretical work (e.g. Kuratko et al., 2017; Bloodgood et al., 2017; Lechner et al., 2022), this study offers empirical evidence regarding the process by which new ventures diffuse their legitimacy beyond their local ecosystems. It presents a novel perspective by emphasizing the dynamic interaction between new ventures, their networks, information brokerage and the larger ecosystem. The results highlight the critical role that networks and information brokers play in extending legitimacy beyond traditional EEs by illuminating the complex link between network activities, legitimacy brokerage and venture legitimacy. This study departs from previous research by demonstrating that legitimacy is a dynamic process enabled by networks and brokerage activities rather than only a static asset. It fills in a crucial void by directly connecting legitimacy diffusion to network interactions – a relationship that was underexplored. Furthermore, this research advances our knowledge of the mechanisms behind EEs by concentrating on the measures taken by focal actors (entrepreneurs) to legitimize their enterprises. This is particularly significant since it suggests a change in the conceptualization of legitimacy in entrepreneurial studies by shifting the focus from structural components of EEs to the entrepreneurial activity within them. As a result, our study adds to the discussion and offers a solid, empirical base for more research in this area in the future.

5.2 Practical implications

The study’s findings have significant practical ramifications for policymakers, entrepreneurs and other actors in EEs. Understanding how new ventures get legitimacy is critical to their growth and success. Several recommendations can be made based on the findings. Policymakers must establish an environment encouraging alternative paths to legitimacy for startups by offering resources and assistance. Policymakers should also enable startups to network and provide opportunities to demonstrate their legitimacy to external stakeholders. Policymakers can improve the overall vibrancy and creativity of EEs by promoting an ecosystem that allows for multiple legitimation options. Based on the findings, new venture owners and managers should appreciate and invest in legitimacy brokerage and network activities such as building networks, establishing collaborations and demonstrating their distinctive value propositions to expedite external legitimacy dispersion. Other EE actors, including funders, mentors and industry groups, can play an essential role in assisting emerging companies with their legitimacy efforts. These actors can help to spread external legitimacy by recognizing and rewarding ventures that use innovative and boundary-breaking techniques. They can also provide information and resources to assist businesses in navigating the complex legitimization process.

6. Conclusion

This study explores how new ventures garner legitimacy within and beyond their EEs. Key findings show that new ventures that receive active legitimacy within their existing ecosystems can break their boundaries, leading to the diffusion of external legitimacy compared to those receiving passive legitimacy. Moreover, such legitimacy diffusion is accelerated (moderated) by new ventures’ legitimacy brokerage and networking activities.

6.1 Limitations and future research

The study’s findings serve as a foundation for various avenues for future research. First, new ventures’ organizational identities influence their strategies and outcomes to gain legitimacy. Future research may examine how organizational identity affects legitimacy within and outside EEs, shedding light on the relationship between identity construction and legitimacy acquisition. Second, it is critical to comprehend the impact of various stakeholder groups on the legitimacy judgments and the diffusion of new initiatives. Future research can consider various stakeholders’ power, legitimacy and urgency to understand how their interactions impact the legitimation process. Third, cross-cultural research can illuminate the contextual elements influencing legitimation tactics and outcomes. Researchers can gain a more comprehensive understanding of legitimation dynamics by comparing findings from diverse cultural contexts. Fourth, the temporal aspects associated with legitimacy formation and diffusion must be investigated more. The study of how new ventures’ actions and strategies evolve should be conducted, exploring the many stages of legitimation and their impact on long-term performance. Understanding the temporal dynamics can help startups achieve and maintain credibility. Finally, the dynamics and growth of EEs have substantial consequences for the legitimacy processes of new businesses. Future research can investigate how changes within EEs, such as shifts in industry trends or the emergence of unique ecosystems, affect new venture legitimation tactics and outcomes. This investigation may yield new techniques for navigating and capitalizing on changing entrepreneurial landscapes.

Figures

Figure 1

Interaction (NV local legitimacy * brokerage) effects for NV legitimacy diffusion beyond EE

Figure 2

Interaction (NV local legitimacy * Network Activities) effects for NV legitimacy diffusion beyond EE

Table 1

Descriptive statistics

Variable		Obs	Mean	SD
Gender	Female	65	0.29	0.45
	Male	163	0.71	0.45
	Age	228	48.52	9.14
Education	College and Vocation	14	0.06	0.24
	High education	214	0.94	0.24
Industry	Health	54	0.24	0.43
	Information tech	60	0.26	0.44
	Construction	41	0.18	0.38
	Hospitality	52	0.23	0.42
	Financial services	21	0.09	0.29
Position	Owners	152	0.67	0.47
	Managers	76	0.33	0.47
	Experience	228	17	9.96
	Firm age	228	12.8	10.72
	Firm size	228	33.44	76.34
	New venture legitimacy diffusion beyond existing EE (LD)	228	3.58	0.81
	Passive local legitimacy within existing EE (PLL)	228	3.34	0.7
	Active local legitimacy within existing EE (ALL)	228	3.12	0.61
	Legitimacy brokerage (LB)	228	3.65	0.72
	Network activities (NET)	228	3.81	0.87

Source(s): Authors’ own work

Table 2

Construct operationalization

Constructs	Measurement items	Factor loading (FL)	Sources
New venture legitimacy diffusion beyond existing EE	Our venture’s products/services gained much recognition outside our ecosystem	0.84	Tost (2011), Kahneman (2011), Kuratko et al. (2017), Bloodgood et al. (2017), McKnight and Zietsma (2018)
	We secured business partners outside our existing ecosystem	0.91
	We engaged more efforts to advertise our products/services beyond existing markets and ecosystem	0.77
	We received feedback from customers outside our ecosystem regarding the quality of our products/services	0.83
New venture passive local legitimacy within existing EE	The community automatically validated our company because we aligned with their cultural expectations	0.86	Fisher (2020), Kuratko et al. (2017), Tost (2011), Kahneman (2011), Zimmerman and Zeitz (2002)
	The community engaged minimal effort to understand precisely what our company was doing	0.79
	We did not receive any challenges from the community regarding the products/services we offer	0.91
	Our company was readily accepted as we met their expectations	0.85
New venture Active local legitimacy within existing EE	The community consciously invested time and energy to legitimize (understand) our company	0.75	Kuratko et al. (2017), McKnight and Zietsma (2018), Tost (2011), Kahneman (2011), Zimmerman and Zeitz (2002)
	The community engaged in cognitive efforts to validate our company	0.88
	We received several challenges regarding the products/services we offer	0.87
	The community carefully and deliberately assessed our venture and its relatedness to the environment	0.93
Legitimacy brokerage	We actively seek media coverage and public relations opportunities to increase our visibility and credibility	0.89	Fisher (2020), Kuratko et al. (2017), Burt (2007), Davies and Prince (2005)
	We often participate in industry events, conferences, or exhibitions to enhance our visibility and credibility	0.94
	Individuals spread information regarding our products/services even beyond our ecosystem	0.80
	Individuals discuss the quality of our products/services in their networks even beyond our ecosystem	0.81
	Individuals regularly share potential information about our products within and beyond our ecosystem	0.79
Network activities	Occurrence of network events such as meet-ups, startup weekends, conferences, pitch competitions	0.71	Bloodgood et al. (2017), Kuratko et al. (2017), Motoyama and Knowlton (2017), Jensen (2008)
	Connections among actors within and beyond the existing ecosystem	0.76
	Social ties among actors within and beyond the existing ecosystem	0.69
	Interactions among actors within and beyond the existing ecosystem	0.81
	We had to persuade the government to design new regulations that favor our products	0.88
	We had to create a new social context for our venture	0.80
	We created ecosystem partners that better understand our products/services	0.73

Source(s): Authors’ own work

Table 3

Hierarchical regression results: the moderation effect of legitimacy brokerage and network activities on the new venture legitimacy diffusion beyond existing EE

	Legitimacy Diffusion beyond existing EE
	1	2	3	4
gen	−0.068 (0.225)	−0.074 (0.221)	−0.158 (0.215)	−0.079 (0.223)
age	0.002 (0.012)	0.001 (0.011)	0.006 (0.011)	0.003 (0.011)
edu	0.353 (0.345)	0.415 (0.341)	0.589° (0.330)	0.475 (0.345)
indst	0.047 (0.065)	0.044 (0.064)	0.087 (0.063)	0.077 (0.065)
exper	0.012 (0.011)	0.015 (0.011)	0.016 (0.010)	0.014 (0.011)
fimag	0.015° (0.008)	0.013 (0.007)	0.017* (0.007)	0.014 (0.007)
fimsiz	0.003* (0.002)	0.002 (0.001)	0.003 (0.001)	0.002 (0.001)
PLL		−0.107 (0.124)	−0.087 (0.117)	−0.124 (0.119)
ALL		0.290** (0.083)	0.128** (0.048)	0.120** (0.051)
LB			0.187° (0.113)	0.221° (0.118)
NET			0.237** (0.084)	0.190* (0.089)
PLL × LB				0.141° (0.081)
ALL × LB				0.055* (0.028)
PLL × NET				0.021** (0.008)
ALL × NET				0.073** (0.023)
F-test	1.56	2.38*	2.57**	2.14*
R2	0.13	0.18	0.28	0.32
Adj R2	0.05	0.08	0.17	0.17
Δ R2		0.05*	0.10***	0.04°

Note(s): gen, gender; edu, education; indst, industry; exper, experience; fimag, firm's age; fimsiz, firm's size; N = 228, in parentheses are the standard errors. ° p < 0.10, *p < 0.05, **p < 0.01, ***p < 0.001

Source(s): Authors’ own work