Motives,Supporting Activities,and Selection Criteria of Social Impact Incubators: An Experimental Conjoint Study

Abstract

Social impact incubators (SIIs) are a new type of incubator that support social enterprises (SEs) in their early business stages to foster and develop their hybrid objectives. However, research on SIIs is still scarce, and little is known about SIIs’ motives, supporting activities, and selection criteria. In investigating 71 SII decision-makers, we find the societal duty motive stated as “most important,” while the financial motive is stated as “least important.” Furthermore, we identify the authenticity of the founding team and the importance of the societal problem addressed as SIIs’ most important selection criteria. However, significant heterogeneity exists within the group of SIIs with regard to their selection criteria. In particular, SIIs with strong innovation and societal duty motives stand out and differ in their SE selection criteria from other SIIs. Our results extend prior research on SIIs and contribute to the discussion on the selection criteria of SE supporters.

Keywords

selection criteria social impact incubator social entrepreneurship social enterprise conjoint analysis

Introduction

Social impact incubators (SIIs) have emerged worldwide along with an increasing number of newly founded social enterprises (SEs) in recent years. SIIs, similar to traditional business incubators, help SEs overcome early-stage barriers by providing them with mainly nonfinancial support consisting of value-added services to develop the businesses of incubator participants (e.g., Allen & McCluskey, 1991; Amezcua et al., 2013; Mas-Verdú et al., 2015; Pena, 2004). With the support of SIIs, SEs develop sustainable business models that aim to fulfill their social and economic objectives (e.g., Battilana & Lee, 2014; Cooney, 2011). However, despite their importance in practice, research lacks a deep understanding of the particularities of SIIs as a new organizational type of business incubator (Sansone et al., 2020; Yang et al., 2020). In particular, we know little about the motives and supporting activities of SIIs and about their selection criteria. The answer to these questions is not trivial as SIIs similar to SEs are in a paradoxical situation pursuing hybrid objectives comprising both economic and social goals (Child, 2020; Smith & Besharov, 2019; Smith et al., 2013). It is, therefore, an open question how SIIs manage the paradoxical situation and the tensions arising from hybridity and how this influences their selection criteria for SEs. Prior research on SIIs was mainly using qualitative empirical approaches (e.g., Aernoudt, 2004; Almeida et al., 2012; Etzkowitz et al., 2005; Nicolopoulou et al., 2017). Our study is quantitative. It measures the importance of SII’s selection criteria and thereby gives SEs guidance on which criteria really matter.

In addition, our study regards SIIs as a heterogeneous group where some SIIs lean more toward social goals while other SIIs have a stronger focus on economic goals (Casasnovas & Bruno, 2013). We expect this heterogeneity to influence SIIs selection criteria. To summarize, our study investigates the following research questions:

Research Question 1 (RQ1): What are the motives and supporting activities of SIIs?

Research Question 2 (RQ2): Which selection criteria do SIIs use in their decision-making processes, what is their relative importance, and how heterogeneous are SIIs with regard to their selection criteria?

Finding answers to these questions is important because SIIs are in a unique position to help SEs realize their goals and tackle societal challenges. This view is supported by prior research finding that SIIs are an important driver of social innovation (e.g., Almeida et al., 2012; Nicolopoulou et al., 2017). With their specific support activities, SIIs can help SEs manage the underlying tensions between their social and economic objectives (Pache & Santos, 2013; Smith et al., 2013). Understanding the motives and supporting activities of SIIs, and connected to this, their selection criteria provide further insights into how SEs can access this support mechanism.

To answer our research questions, we take an exploratory approach in investigating this new phenomenon because such an approach allows us to analyze this trend in a more rigorous and detailed way (Wennberg & Anderson, 2019). More specifically, we use a multimethod design. To identify the most important selection criteria of SIIs, we first conducted 12 interviews with experts on SEs. Based on our findings, we designed a choice-based conjoint (CBC) experiment including seven selection criteria and assessed their importance for SII decision-makers. In addition, we investigated the motives, supporting activities, and characteristics of SIIs using a questionnaire that followed the experiment. Our final sample consists of 71 SII decision-makers from the DACH region (i.e., Germany, Austria, and Switzerland) and encompasses private as well as public SIIs (e.g., Social Impact Labs or Impact Hubs).

Our study’s contribution to the literature is threefold. First, we contribute to the scarce research on SIIs (e.g., Nicolopoulou et al., 2017; Sansone et al., 2020; Yang et al., 2020) by outlining the distinctive motives, supporting activities, and selection criteria of SIIs. With regard to the latter, we emphasize heterogeneity within the group of SIIs and show how the diversity of SIIs is reflected also in their selection processes. Second, our study adds to prior literature examining the selection criteria of SE supporters, which so far has mainly focused on financial investors (e.g., Achleitner et al., 2013; Miller & Wesley, 2010; Yang et al., 2020). Our study extends this line of research by exploring the selection criteria of SIIs as a new organizational type that provides SEs with non-financial support. Third, we contribute to prior research on paradox theory and its applications to hybrid organizations and particularly SEs (Child, 2020; Jay, 2013; Schad & Bansal, 2018; Smith et al., 2017). Our results indicate that SIIs seem to focus particularly on social objectives while selecting SEs for their programs. Hence, SIIs seem to manage the competing logics of and tensions between social and economic objectives in their selection process by giving priority to the social aspects of SEs. Overall, the explorative approach applied in our study enables us to provide not only theoretical but also practical implications. Our results can help SEs that apply for SII support to better understand the selection processes and motives of SIIs and thereby increase their chances of approval and acquiring important resources. The heterogeneity that exists within the group of SIIs forces them to provide customized applications. SIIs can use our findings to benchmark their own selection processes against the market.

Background on SIIs

Research on SIIs is still limited. Table 1 provides an overview of SII research that has been published in peer-reviewed journals. As the focus of our study is on the motives and selection criteria of SIIs to better understand how SEs can access SII support, in the following, we offer a deeper review of where SIIs come from and what their motives are, how the SII process unfolds, and what is known so far about SIIs’ selection criteria.

Table 1.

Prior Research on SIIs.

References	Journal	Method	Main content
Aernoudt (2004)	Small Business Economics	Qualitative	Explores different types of business incubators and initially describes SIIs’ main objectives as supporting new ventures that integrate people with low prospects in the labor market, such as, for example, disabled people or the long-term unemployed.
Almeida et al. (2012)	International Journal of Technology and Globalisation	Qualitative	Examines a specific SII program that aims to foster social innovations in Brazil. Based on a triple helix dynamic model, which consists of the government, academia, and different industries, the article explains the diffusion and expansion of innovations in SEs.
Casasnovas & Bruno (2013)	Journal of Management for Global Sustainability	Qualitative	Explores the potential for social incubators and social accelerators to scale SEs. Based on a comparison of 40 social incubator and social accelerator programs, the article classifies both types and offers ten propositions for future research in the field.
Etzkowitz et al. (2005)	Research Policy	Qualitative	Identifies SIIs as organizations that foster business and social goals simultaneously. In addition, the study examines how a “meta-innovation system” in Brazil promotes innovation in areas of society that are normally hardly innovative.
Lall et al. (2013)	Innovations: Technology, Governance, Globalization	Quantitative	Investigates the role of SIIs in the formation of SEs. The authors explore the relationship between impact investors and social impact incubation programs based on a survey of 60 impact investors. The descriptive results range cover types of financing to affect targets and SII services.
Nicolopoulou et al. (2017)	R&D Management	Qualitative	Investigates the London Hub, a specific SII, to identify how social innovations are achieved out of incubation programs. The article identifies SIIs as an emerging focus of research, which must be explored empirically. Furthermore, the impact of social capital on the relationship between innovation and incubation is examined.
Pandey et al. (2017)	Journal of Social Entrepreneurship	Quantitative	Based on a sample of 4,125 SEs that have applied for support from an SII, the article explores the supporting activities that SEs seek from SII programs. In addition, the authors investigate how the founding teams’ human capital is associated with the search for different types of SII support.
Sonne (2012)	Technological Forecasting & Social Change	Qualitative	Identifies a gap in the financing of social innovation and social entrepreneurship in India and shows how SIIs and microventure capitalists can help bridge this gap while fostering social innovation.
Sansone et al. (2020)	Technological Forecasting & Social Change	Quantitative	Investigates differences between traditional business incubators and SIIs based on a quantitative analysis of a sample of 162 active incubators in Italy in 2016. The authors find that SIIs are just as efficient at developing start-ups as traditional incubators, although they do not solely focus on economic objectives.
Yang et al. (2020)	Journal of Business Venturing	Quantitative	Examines the most important signals of SEs when applying for social acceleration programs. The authors identify social and economic credibility as important decision-making factors for SIIs and furthermore show that gender role congruity has a significant impact on SIIs’ selection processes.

Note. SEs = social enterprises; SII = social impact incubator.

Origins and Motives of SIIs

SIIs are a new organizational type that emerged in response to an increasing number of SEs (McKinsey & Ashoka, 2019). Since the advent of the business incubation phenomenon, different incubation types have developed following different objectives and motives (e.g., Grimaldi & Grandi, 2005; Mian et al., 2016, 1997; Tamásy, 2007; von Zedtwitz, 2003), such as technology or economic development incubators. Aernoudt (2004) initially introduced SIIs as a new incubation type that supports companies that employ people with limited prospects in the labor market and thus concentrate on the nonprofit sector. Over the last decade, however, the work of SIIs has shifted to the field of SEs that aim for financial independence and having a significant social impact in various fields (e.g., Nicolopoulou et al., 2017; Yang et al., 2020). This hybrid feature of SEs differentiates them from traditional business incubation attendees. In line with the characteristics of SEs, SIIs goals are defined by fostering social innovations and thus achieving social impact (e.g., Etzkowitz et al., 2005; Lall et al., 2013; Nicolopoulou et al., 2017).

SIIs themselves are diverse with regard to their different operating dimensions. In particular, SIIs can either be publicly or privately funded, which is reflected in their missions. Whereas publicly funded SIIs have the primary objective of building a sustainable environment that fosters the creation of social innovations to solve societal problems (Choi & Majumdar, 2014), privately financed SIIs are either financed by corporations and thus also serve company-specific objectives such as creating reputational gains (Phan et al., 2009) or are established completely independently as private initiatives to support SEs. An example of the latter is the Impact Hub (see www.impacthub.net), which is active globally in over 50 countries. The goal of the Impact Hub is to scale the impact of SEs that create solutions to global problems. Overall, different funding types and missions among SIIs indicate heterogeneity among SIIs.

Supporting Activities and Selection Criteria of SIIs

In examining the supporting activities of SIIs more closely, prior research shows two main offerings of SII programs (e.g., Sansone et al., 2020; Yang et al., 2020). On one hand, SIIs provide SEs with value-added services to foster their economic objectives, similar to traditional business incubators. On the other hand, SIIs help SEs develop their social objectives and thus achieve greater social impact, which clearly distinguishes them from other types of incubators. Thus, in addition to providing financial support in the form of grants or investments, SIIs typically provide SEs with nonfinancial support in the form of business development support, infrastructure for SEs, or network access (e.g., Lall et al., 2013; Sonne, 2012). These support mechanisms are designed to teach SEs how to scale their solutions to address societal problems and, at the same time, develop sustainable (profitable) business models that allow them to scale their ideas. Hence, SIIs also support SEs in managing the tension between these often opposing goals and avoiding drifting from their missions (Agafonow, 2015). The fact that SIIs have a positive effect on the economic performance of SEs while simultaneously promoting social objectives has been shown by Sansone et al. (2020). The authors investigated all operating incubators in Italy in 2016 and demonstrated that tenants of SIIs grow as fast as tenants from other types of business incubators. Overall, prior research has argued that SIIs are a suitable tool for establishing a supportive environment for SEs and their specific needs (Chell, 2007).

However, to date, little is known about the selection processes and criteria of SIIs and how they differ between SIIs.¹ Yang et al. (2020) recently analyzed the selection criteria of social impact accelerators² closely connected to SIIs. The authors reveal that social startups that signal both economic and social credibility are more likely to be selected. This is an important finding for social entrepreneurs applying for social impact accelerator support, as it provides answers to the question of which aspects of SEs’ hybrid objectives applicants should focus on. We aim to extent these findings by investigating specific selection criteria that are used by SIIs when selecting SEs for their programs.

Conflicts Between Different Objectives, Motives, and Selection Criteria of SIIs

SIIs are faced with the challenge to select suitable SEs for their programs. Prior research has discussed SEs extensively as an example for hybrid organizations (e.g., Battilana, 2018; Child, 2020; Galaskiewicz & Barringer, 2012; Pache & Santos, 2013). SEs typically are established to deliver social value and follow economic objectives to be self-sustainable instead of surviving through donations and grants (Ebrahim et al., 2014; Hirschmann & Moritz, 2020). Hence, SEs are hybrid organizations combining competing institutional logics (Child, 2020; Jay, 2013; McMullen & Bergman, 2017). In this context, paradox theory has been argued to be ideally suited to investigate this type of organization (Cherrier et al., 2018; Child, 2020). Paradoxes are defined as “contradictory yet interrelated elements that exist simultaneously and persist over time” (Smith & Lewis, 2011, p. 382). Therefore, SEs need to find ways to manage this paradox of following competing objectives (Cherrier et al., 2018; Pache & Santos, 2013).

Solving this paradoxical situation is likely to be reflected on the level of the SII. SIIs need to decide which criteria they should focus on while selecting an SE—social or economic. Even though without profits the SEs cannot survive in the long run, it could be argued, that achieving a sustainable or even profitable business model is part of the value-added of the SIIs support program. As a result, SIIs might be more likely to focus on social criteria in their selection process. However, based on the type of funding and the mission of SII funders, SIIs themselves could be faced with the tension between achieving social and economic objectives of varying severity (e.g., Etzkowitz et al., 2005). Hence, SIIs could be argued to be hybrid organizations themselves facing a similar paradox than SEs which might be reflected in how they support and select SEs for their programs.

Based on this reasoning, it is not self-explanatory and difficult to predict which motives SIIs follow and related to those, which selection criteria dominate the decisions of SIIs. Therefore, our study investigates the motives, supporting activities, and selection criteria of SIIs. Furthermore, we explore how heterogeneity within the group of SIIs affects the evaluation of different selection criteria.

Prior Research on the Selection Criteria of SE Supporters

Previous literature has explored the selection processes of different organizations supporting SEs (e.g., Achleitner et al., 2014; Miller & Wesley, 2010; Scarlata & Alemany, 2009). In particular, the selection processes of impact investors, such as social venture capitalists and venture philanthropic organizations, have been investigated in depth (e.g., Achleitner et al., 2011; Block et al., 2021; Serrano-Cinca & Gutiérrez-Nieto, 2013; Spiess-Knafl & Aschari-Lincoln, 2015). This research has mainly focused on comparing idea- and entrepreneur-focused criteria (Achleitner et al., 2013; Scarlata & Alemany, 2009) and provides ambivalent results. Scarlata and Alemany (2009) find that the entrepreneur and the management team have the strongest impact on decision-makers. Achleitner et al. (2013) investigate the importance of human capital aspects of SEs for social venture capitalists and show that entrepreneur-related criteria are less important than other criteria.

However, first attempts have also been made to examine the influence of SEs’ hybrid character on the selection processes of supporting organizations (Miller & Wesley, 2010; Yang et al., 2020). For instance, Miller and Wesley (2010) show that both social and economic objectives are acknowledged in the decision-making processes of social venture capitalists. The authors find that economic selection criteria are valued more than social criteria. In their study, entrepreneurial selection criteria include management experience, earnings, performance, and innovation capabilities. Social selection criteria such as the social mission, the network size of a concerned community, or passion for social change have been found to be of lesser importance. However, Miller and Wesley (2010) also demonstrate that the more experience an investor has with venture capital funding, the more important social selection criteria become. Botetzagias and Koutiva (2014) show that donors place great value on the moral legitimacy of funded SEs. Finally, Yang et al. (2020) find that social impact accelerators are more likely to select an SE if both economic and social credibility are highlighted.

Table 2 highlights the findings of previous research conducted in this field. Overall, the literature still lacks a deeper understanding of the distinctive selection criteria of SIIs as a new type of organization within the field of social entrepreneurship.

Table 2.

Selection criteria of SE supporters.

References	Method	Type of SE supporter	Selection criteria
Achleitner et al. (2013)	Quantitative	Social venture capitalist	• Investigates the influence of five criteria on the assessment of an SE’s integrity • Voluntary accountability efforts and the entrepreneur’s reputation are the most important for assessment
Achleitner et al. (2014)	Qualitative	Venture philanthropy funds	• Identifies (a) the concept, (b) social impact, (c) the market, (d) the social entrepreneur, (e) and financials as the most important criteria from interviews • Reveals interdependencies between selection criteria
Block et al. (2021)	Quantitative	Impact investors	• Investigates the importance of seven criteria for the screening decisions of impact investors • Reveals that impact investors differ in terms of the funding that they provide to SEs
Botetzagias & Koutiva (2014)	Qualitative	Foundations and businesses	• Investigates how donors select environmental SEs • Identifies that moral legitimacy is of highest importance for donors generally
Lee et al. (2020)	Quantitative	Impact investors	• Investigates how impact investors can achieve efficient social and financial performance • Shows that the tendency to think in terms of categories such as “social enterprise” or “charity” prevents impact investors from achieving their full financial and social impact
Miller & Wesley (2010)	Quantitative	Social venture capitalist	• Financial and social sector criteria influence the assessments of social venture capitalists • Finds that greater value is attributed to entrepreneurial criteria
Roundy et al. (2017)	Qualitative	Impact investors	• Both social and financial returns are important for impact investors • Identifies similarities between impact and traditional investors with regard to selection criteria
Scarlata & Alemany (2009)	Quantitative	Philanthropic venture capitalist	• Finds that philanthropic and traditional venture capitalists use similar selection criteria • Philanthropic venture capitalists attach the most importance to (a) management teams, (b) significant social impact, and (c) social markets served
Spiess-Knafl & Aschari-Lincoln (2015)	Quantitative	Venture philanthropy funds	• Finds that in North America, investees such as children, disadvantaged beneficiaries, and disabled and sick persons are more likely to receive grants
Yang et al. (2020)	Quantitative	Social impact accelerators	• Signaling economic and social credibility simultaneously increases the likelihood of being selected • Identifies how gender stereotypes influence selection processes

Note. SE = social enterprise.

Data and Method

Interviews, Conjoint Experiment, and Postexperimental Survey

We conducted a multimethod approach to assess the importance attached to the different selection criteria of the participants. This approach was necessary due to the scarce research on decision-making criteria in the field of SEs, particularly in the context of SIIs. We started by identifying a list of the most relevant selection criteria from the literature and conducted interviews with 12 experts with considerable experience with the SE selection process to verify and shorten this list. We selected these experts based on theoretical considerations and conducted interviews until we obtained a sufficient number of different views demonstrating converged agreement between the participants on the selection criteria (Glaser et al., 1968). Thus, our interview partners belonged to German SIIs and impact investing organizations that also provide incubator-like services to SEs.³ We selected only individuals with decision-making functions in their organizations (e.g., SII founder or project manager) and a high level of expertise in the social entrepreneurship field. The interviews were semistructured using an interview guideline with open-ended questions to ensure a free expression of the views and experiences of the experts (Galletta, 2013).⁴ The aim of these expert interviews, which were conducted between November 2017 and March 2018, was to identify selection criteria that reflect a realistic decision-making environment for SII decision-makers. Hence, the most relevant social and economic selection criteria and idea- and entrepreneur-related selection criteria were identified in the interviews. For this step, all interviews were analyzed according to the criteria mentioned by the experts. Based on our literature analysis and the results obtained from the interviews, we decided to use the following seven selection criteria, which also fulfill the requirement of being as independent as possible, for our CBC experiment: (a) authenticity of the founding team, (b) professional background of the founding team, (c) financial sustainability, (d) scalability, (e) proof of concept, (f) degree of innovation, and (g) the importance of the societal problem. Each criterion was varied on two or three different attribute levels (e.g., proof of concept “provided” or “not provided”). All attributes—including the specifications shown to the participants of our conjoint experiment—are presented in Table 3. For example, the importance of the societal problem addressed captures the urgency of solving a societal problem, the authenticity of the founding team describes the overall authenticity or credibility of the founders, and financial sustainability indicates to what extent an SE is likely to finance itself in the foreseeable future.

Table 3.

Attributes and Levels Used in the Conjoint Experiment.

Attribute	Levels	Labels/explanations for respondents	Rationale for inclusion
Financial sustainability (three levels—ordinal)	Low Moderate High	Represents the extent to which the SE will be able to finance itself in the foreseeable future	Describes how likely an SE is to achieve financial goals in the future and not be dependent on external sources. Due to the hybrid nature of SEs, many are dependent on external support over the long term (e.g., Chell, 2007). Therefore, becoming financially sustainable represents a great obstacle SEs must overcome.
Scalability (three levels—ordinal)	Low Moderate High	Describes the likelihood of the transfer and large-scale implementation of the project	The scalability covers the social impact an SE wants to have, hence, showing the extent to which an SE’s social project can be scaled to achieve greater impact and reach more stakeholders for the social part of the business.
Degree of innovation (three levels—ordinal)	Low Moderate High	Describes the novelty with which the societal problem is addressed	Innovativeness is an important component of the definition of an SE (e.g., Dart, 2004), covering how a SE is addressing a societal problem in a new way. Social innovation has become a major governmental focus for solving global problems and achieves the Sustainable Development Goals (Eichler & Schwarz, 2019).
Proof of concept (two levels—ordinal)	Not provided Provided	Proof of the feasibility of the project	Describes whether a proof of concept is provided for SEs’ business models. Thus, the variable proves the feasibility of the social (and financial) part of an SE.
Importance of the societal problem (three levels—ordinal)	Low Moderate High	Describes the relevance and urgency of solving the societal problem	The importance of the societal problem describes the extent of an issue that an SE aims to solve. Thus, next to the attribute’s scalability, this attribute covers the social impact an SE wants to achieve.
Professional background of the founding team (three levels—nominal)	Technical Business Social	Represents the educational and professional background of the founders	Previous literature has shown that the professional background of the founding team influences selection processes used in venture finance (e.g., Franke et al., 2006, 2008; Kaplan & Strömberg, 2004). Therefore, this attribute describes whether the founding team has a technical, social, or business educational and professional background.
Authenticity of the founding team (three levels—ordinal)	Low Moderate High	Describes the authenticity or credibility of the founders	Davies et al. (2019) argue that SEs must be authentic; otherwise, barriers to growth may arise. Furthermore, several interview partners mention the authenticity of the founding team as an important attribute in their screening phase. The measure provides an indication of how credible the founding team is in solving a certain societal problem. Finally, the attribute measures how authentically or credibly founders present business ideas designed to solve a societal problem.

Note. SE = social enterprise.

In our study, we applied a discrete CBC experiment. The premise of this design is that decision-makers always must select between two different hypothetical SEs described with different characteristics. We chose this approach to reveal the selection preferences of each participant by forcing them to make a discrete choice (“yes” or “no”) because it has the advantage of jointly measuring decision criteria. Thus, CBC experiments require participants to evaluate a series of SEs based on fixed selection criteria. This experimental approach has been used in previous studies to evaluate venture capital decision criteria (e.g., Block et al., 2019; Franke et al., 2006, 2008; Shepherd & Zacharakis, 1999). In reference to SEs, Mayer and Scheck (2018) used a conjoint experiment to evaluate the selection criteria employed by SEs in choosing among different social venture capital investment options, and Achleitner et al. (2013) used this type of experiment to examine different criteria used by social venture capitalists to assess social entrepreneurs’ integrity.

In line with previous research, we used a full-profile CBC including all attributes from Table 2 (Franke et al., 2008). To make the decision-making situation as comprehensible as possible, the participants received a brief description of the decision-making situation before the experiment. Furthermore, during the experiment, the respondents could always read definitions of the decision-making criteria by clicking on the respective criterion (Table 3).

Based on our different criteria and attribute levels, we created a total of 500 unique experimental designs including different combinations of attribute levels. However, we conducted the experiment with a reduced conjoint design (Chrzan & Orme, 2000) to ensure that participants would not be overwhelmed by too many decision-making tasks. Hence, each participant was asked to make 14 decisions in total; these decisions involved 12 randomly assigned tasks and 2 fixed tasks that were equal for every respondent.

Data collection took place between March 2018 and March 2019.⁵ On average, each respondent took 23 s to make a selection between two different SEs. This finding is consistent with previous literature (Johnson & Orme, 1996). To confirm the face validity of our experiment (attributes, the number of choices and complexity), we performed a pretest with 12 SE supporters and four researchers. Furthermore, we accounted for order effects (Chrzan, 1994) that could harm the reliability of a CBC experiment. On one hand, we circumvented issues originating from the ordering of options given for a choice task by randomly ordering the two options offered by each choice task of the 500 different experimental designs. On the other hand, to prevent possible issues resulting from the ordering of attributes within a choice task, we randomized the presented order across the participants while simultaneously keeping the ordering stable within an ongoing experiment.

To identify the SIIs’ most relevant selection criteria, we conducted a multilevel logistic regression analysis. The decision to select or not select an SE served as the dependent variable. The different attribute levels demonstrate our independent variables. A multilevel regression is used because our data consist of two levels with multiple decision observations nested within each respondent. Thus, the levels cannot be treated as independent from each other, and a multilevel model allows us to evaluate effects on cross-level interactions while the decisions are nested.

After the experiment, each participant was asked to complete a questionnaire consisting of individual and organizational- and SE-related questions (see Appendix A.II). For example, for the organizational part, to investigate our first research question, we asked the participants about the motives behind their SIIs. The motives also serve as moderator variables in our subsequent analysis.

Identification and Description of the Sample

We decided to investigate the DACH region since Germany, Austria, and Switzerland are characterized by numerous similarities such as geographic proximity, language, social security systems, and state-controlled wages and rents. The countries also offer income support, free access to schools and universities, free health care for low-income earners and very similar legal and tax systems. These characteristics of the DACH region provide a similar starting point for SEs and make the countries comparable. This is also evident in the absence of a specific legal form for SEs, which distinguishes the DACH area from almost all neighboring European countries (Wilkinson et al., 2014).

As no lists of SIIs in the DACH region exist, the search strategy was carried out manually. First, we identified SIIs within the countries of the DACH region. Thus, we identified DACH-specific SIIs such as Social Impact Labs as well as worldwide operating SIIs such as the Impact Hub, which is already established in all continents and in over 50 countries. Second, listed partner organizations from the websites of identified SIIs and SIIs identified in various publications were collected manually. The decision-makers of each SII were identified through the websites of the organizations. However, if a team description was missing from a website, we used the social network platforms LinkedIn and XING to identify the relevant decision-makers. These platforms are the most commonly used platforms in the DACH region to communicate current and past personal and professional activities. Furthermore, a computerized search of these social media platforms was conducted to ensure that no SIIs and their decision-makers were overlooked. The following keywords were used: “social incubator,” “social entrepreneurship,” “social lab,” and “social hub.”

Altogether, we identified 72 SIIs with 441 potential decision-makers in the DACH region. We invited the identified decision-makers via mail or through direct messages sent on a platform. Each of these decision-makers received up to three reminder messages. In total, we collected 71 (response rate = 16.10%) responses from 46 SII organizations. Fifty-two (73.2%) participants were from Germany, 10 were from Austria (14.1%), and 9 were from Switzerland (12.7%). Each of the 71 respondents had to make 28 decisions on whether to select an SE resulting in 1,704 observations in total.

To assess whether our results were influenced by nonresponse bias, we compared our initial sample (N = 441) to our final sample (N = 71). Thus, we conducted a chi-square test to evaluate the representativeness of our sample by comparing participants to nonparticipants (e.g., Armstrong & Overton, 1977). Using the variables male and educational degree, we find no significant differences between the samples.

Characteristics of the Sample

Individual-level characteristics

Table 4 shows the respondents’ individual characteristics. A total of 52% of the respondents are male, and the average age is 35 years (Min = 19 years, Max = 59 years). Overall, the respondents are highly educated. Of all decision-makers, 66% have a master’s degree or MBA. The respondents’ characteristics are similar to those of individuals participating in previous studies in the field of impact investing, which also report a rather young collection of decision-makers with high levels of education (Lee et al., 2020). The participants of our study most often have a business (55%) or social science background (42%), which is in line with the hybridity of the social and financial goals of SEs. On average, each participant had made between 5 and 10 SE-selection decisions in the past. This finding demonstrates that although social venture incubation has been a rather new phenomenon in recent years (Casasnovas & Bruno, 2013), SII decision-makers already show a certain level of experience with the selection process. In addition, noteworthy is the high degree of work experience in the field of social entrepreneurship; 52% of the respondents have a social entrepreneurship background.

Table 4.

Individual Level Statistics.

Variable	%
Demographic variables
Male	52
Age
<20 years	2
20–30 years	42
30–40 years	28
40–50 years	20
>50 years	8
Education and decision experience
Level of education (highest formal degree)
High school graduation	4
Bachelor degree	19
Master degree or MBA	66
PhD or doctoral degree	11
Field of education (multiple choice possible)
Business/economics	55
Social sciences	42
Natural sciences	14
Liberal arts	23
Other	8
Decision experience
1	6
2–4	34
5–10	8
>10	52
Experiences as a social entrepreneur
Own background	52

Note. N = 71 decision-makers.

Organization level characteristics

Table 5 provides an overview of the SIIs’ organizational characteristics. On average, the SIIs included in our study have actively supported social entrepreneurship for 8 years, even though 25% of the SIIs were established within the last 3 years. The SIIs are relatively small organizations, 40% of which have fewer than 10 employees in total. SEs in very early stages (i.e., idea development stage) were most frequently supported (79%), followed by SEs in the seed (68%) and startup stages (66%). This finding is consistent with prior research on business incubators (e.g., Amezcua et al., 2013; Mas-Verdú et al., 2015) and is explained by the idea of business incubation, which fosters startups, particularly in their early years. SIIs in our sample mostly identify new participants through recommendations of third parties (75%) and focus particularly on the impact topic of sustainability (77%).

Table 5.

Organizational Level Statistics.

Variable	%
Company age
0–3 years	25
3–5 years	8
5–10 years	25
>10 years	43
Type of support
Only financial	–
Rather financial	3
Both equally	20
Rather nonfinancial	49
Only nonfinancial	28
Investment stage (multiple answers possible, Ø 2,6 stages)
Idea development	79
Seed	68
Startup	66
Expansion	28
Establishment	11
Exit	4
Financial Support
Donations	27
Equity	11
Debt	14
Mezzanine capital	3
Convertible loans	7
Guarantee	3
Nonfinancial support
Networks and contacts	100
Infrastructural equipment	65
Mentoring/coaching	96
Qualified advice (e.g., tax consulting)	83
Selective support (e.g., workshops)	79
Others	14
Deal origination (multiple answers possible)
Initiative requests from SEs	49
Targeted own search	49
Tenders	55
Recommendations by third parties	75
Others	11
Impact topic (multiple answers possible)
Sustainability and environment	77
Food supply and nutrition	47
Health care	37
Economic development	53
Child and youth welfare	34
Education and enlightenment	67
Social inclusion	59
Others	4
Impact location(multiple answers possible)
Germany	65
Within Europe	49
Africa	30
Asia	18
North America	7
South America	11
Australia	1

Notes: N = 71 decision-makers.

Results

Motives and Supporting Activities

To be able to answer our first research question about the motives of SIIs to support SEs, each participant was asked to evaluate each SII organizational motive on a 5-point Likert-type scale (“1 = not important at all” to “5 = highly important”). Table 6 presents a correlation matrix as well as the single-item mean values, standard deviations, and multi-item mean values of SIIs’ motives in the DACH region. We identified five types of motives for SIIs. First, the stakeholder expectation motive encompasses the single items “expectations of society” and “expectations of stakeholders,” which correlate positively (.49) (Cronbach’s α = .66). Second, the reputation motive consists of the single items “image” and “employer branding” (Cronbach’s α = .70). Third, we categorize the “pursuit of inspiration,” ‘employee development,’ and “new knowledge” under the term innovation motive (Cronbach’s α = .69). Finally, the duty to society motive and financial motive is captured through single items.

Table 6.

Correlations between motives and utilities of the selection criteria.

Motives and utilities	Variables	Single item mean	Standard deviation.	Multi item mean	(1)	(2)	(3)	(4)	(5)	(6)	(7)	(8)	(9)	(10)	(11)	(12)	(13)	(14)	(15)
Stakeholder expectation motive	(1) Expectations of stakeholders	3.32	1.17	3.34
Stakeholder expectation motive	(2) Expectations of society	3.35	1.12	3.34	0.49
Reputation motive	(3) Image	3.07	1.06	2.89	0.21	0.41
Reputation motive	(4) Employer branding	2.72	1.12	2.89	0.16	0.27	0.54
Innovation motive	(5) Be inspired by the startup spirit	2.96	1.26	3.27	0.19	0.24	0.34	0.26
	(6) Employee development	3.13	1.17		0.03	0.02	0.25	0.23	0.37
	(7) Learning from the innovations of others	3.72	1.00		0.20	0.18	0.14	0.18	0.45	0.47
Societal duty motive	(8) Sense of duty to society	3.89	1.14	3.89	−0.10	0.14	−0.06	−0.09	0.28	0.33	0.36
Financial motive	(9) Financial interests	2.54	1.04	2.54	0.20	0.15	0.04	0.17	−0.12	−0.14	−0.11	−0.30
Utilities	(10) Financial sustainability	11.47	3.17	–	0.03	−0.01	0.11	0.04	0.09	0.05	−0.10	0.08	0.01
	(11) Scalability	11.00	3.30		0.09	−0.02	−0.04	−0.08	0.18	0.26	0.19	0.20	0.08	0.45
	(12) Degree of innovation	12.17	6.60		0.04	0.22	−0.05	−0.13	0.14	−0.11	0.24	0.23	−0.23	−0.17	−0.27
	(13) Proof of concept	7.52	5.12		−0.20	−0.24	−0.05	−0.01	−0.11	−0.33	−0.28	−0.29	−0.12	0.02	−0.33	0.10
	(14) Importance of the societal problem	24.75	7.73		0.08	0.11	0.01	0.13	0.08	0.10	0.09	0.16	0.06	−0.15	−0.00	0.20	−0.64
	(15) Background of the founding team	4.94	2.66		0.17	0.14	0.15	−0.05	−0.00	0.18	0.21	0.15	0.03	−0.27	−0.21	0.27	0.03	−0.11
	(16) Authenticity of the founding team	28.11	10.25		−0.06	−0.13	−0.01	0.01	−0.18	0.01	−0.16	−0.25	0.13	−0.18	−0.07	−0.78	0.01	−0.49	−0.22

Table 6 shows that SIIs’ most important motive is the societal duty motive (M = 3.89). In contrast, the financial motive is of least importance (M = 2.54). The stakeholder expectation (M = 3.34) and innovation motives (M = 3.27) rank second and third, respectively. The reputational motive, which is also closely connected to the business of an SII, is the second least important motive (M = 2.89).

In line with previous business incubation research (Allen & McCluskey, 1991; Lalkaka, 2002; Lalkaka & Abetti, 1999), the organizations in our sample provide mostly nonfinancial support to their attendees. Regarding different types of nonfinancial support, we find that all SIIs support their SEs with their personal networks and contacts. This finding is in line with Bergek and Norrman (2008) who show that incubators play an important role as intermediaries between startups and business support organizations (e.g., follow-up investors). Furthermore, 96% of the SIIs provide specific mentoring or coaching programs, and 83% offer qualified advice (e.g., tax consulting). Finally, 65% also provide SEs with coworking spaces or other forms of infrastructure. Table 5 highlights the supporting activities of the studied SIIs.

Selection Criteria

To answer our RQ2 about the selection criteria of SIIs, we conducted a multilevel (hierarchical) logistic regression. The results shown in Table 7 demonstrate that SIIs seem to focus mostly on the authenticity of the founding team and the importance of a societal problem in their selection processes. Our results also show that the professional background of the founding team is considered to be the least important criterion in the selection process. In examining the attributes of this criterion more closely, we find that only the social background of the founding team has a significant positive impact on decision-making. Regarding business versus technological background, the participants are indifferent. All other criteria have a significant influence on the decision-makers (p < .01). The degree of innovation ranks third, which is in line with the motives of SIIs, as learning from the innovation of others was also identified as the third most important motive for SII support of SEs. Less important to the selection processes of SIIs are proof of concept and financial sustainability, but they still have a significant influence on decision-making.

Table 7.

Main Effects Model.

Attributes and levels	Log-odds (SE)
Financial sustainability: high	0.704 (0.160)***
Financial sustainability: medium	0.455 (0.151)***
(reference group: low)
Scalability: high	0.766 (0.163)***
Scalability: medium	0.422 (0.153)***
(reference group: low)
Degree of innovation: high	0.834 (0.177)***
Degree of innovation: medium	0.515 (0.152)***
(reference group: low)
Proof of concept: provided	0.752 (0.172)***
(reference group: not provided)
Importance of the societal problem: high	1.718 (0.181)***
Importance of the societal problem: medium	0.942 (0.154)***
(reference group: low)
Professional background of the founding team: social	0.293 (0.150)*
Professional background of the founding team: technical	0.176 (0.157)
(reference group: business)
Authenticity of the founding team: high	1.95 (0.202)***
Authenticity of the founding team: medium	1.412 (0.160)***
(reference group: low)
N (decisions)	1.704
N (decision-makers)	71

Note. Estimated with robust standard errors. Regression type: multi-level logistic regression with random intercepts and random slopes. Dependent variable: preference of decision-maker.

p < .10. **p < .05. ***p < .01.

We estimate the relative importance of each attribute to enable better comparability between the selection criteria. Therefore, first, zero-centered utility values for each attribute level of every decision-maker are calculated. Second, we measure the range between the lowest and highest utility value of each attribute level to evaluate the effect of a change in an attribute’s level on the total utility of a specific SE. In the third and last step, the range of each attribute level is divided by the sum of all ranges to calculate its relative importance. Figure 1 shows the values for the relative importance of each attribute. These values are normalized (zero-centered) for comparability reasons. Thus, the sum of all relative importance values is 100. Accordingly, higher values make greater contributions to an SE’s total utility value.

Figure 1.

Relative importance of SIIs’ attributes.

Figure 1 demonstrates that the authenticity of the founding team accounts for 27.8% of the total utility of an SII decision-maker. Thus, this attribute is almost 7 times more important for a decision-maker than the professional background of the founding team. The same is true for the importance of the societal problem, which is the second most important attribute. This attribute’s relative importance is almost 6 times greater than that of the least important attribute and is still twice as high as that of the third most important attribute degree of innovation. Overall, with 52.3%, the first two attributes have a greater influence on an SE’s decision-making than all other five attributes combined. However, with a relative importance of 10%, even the second least important attribute of financial sustainability still has a significant influence and is twice as important as the professional background of the founding team.

Finally, to further explore the effect sizes of the different attribute levels, we created Figure 2, which displays the odds ratios of each attribute level. SEs with “high” scores for the authenticity of the founding team have an odds ratio of 7.03, meaning that they are 7 times more likely to be selected by an SII decision-maker than an SE with a “low” score for the authenticity of the founding team. Even SEs with an authenticity of the founding team score described as “moderate” are still chosen 4.10 times more often than their low-authenticity counterparts. Regarding the importance of the societal problem, SEs addressing very important problems (e.g., measures against climate change) are 5 times more likely to be selected than SEs focused on less important problems. For all other attributes (i.e., except for the background of the founding team), SEs with the highest level for a given attribute are more than twice as likely to be selected than those with the lowest level. Thus, the overall likelihood of being selected by an SII decision-maker is strongly affected by high levels of (a) the authenticity of the founding team and (b) the importance of the societal problem.

Figure 2.

Odds ratios of attribute levels.

Impact of SII Heterogeneity on SE Selection

To investigate the impact of SIIs’ motives on the relationship between selection criteria and a participant’s decision, we conducted additional analyses. Table 8 displays the results of each attribute level interacting with the motives of SIIs (see “Motives and Supporting Activities” section). Observing these interaction effects enables us to explore the heterogeneity of SIIs with regard to their SE selection decisions.

Table 8.

Interaction Effects Between Selection Criteria and Motives and Supporting Activities of SIIs.

Model	(1)		(2)		(3)		(4)		(5)		(6)
Sample	Stakeholder expectation motive		Reputationmotive		Innovationmotive		Societal dutymotive		Financialmotive		Extent supporting activities
Variables	OR	(SE)	OR	(SE)	OR	(SE)	OR	(SE)	OR	(SE)	OR	(SE)
Financial sustainability: high	0.146	(0.167)	0.010	(0.162)	−0.019	(0.159)	0.092	(0.140)	−0.011	(0.126)	0.194	(0.146)
Financial sustainability: medium	−0.001	(0.169)	0.001	(0.170)	−0.211	(0.134)	−0.082	(0.103)	0.043	(0.124)	−0.026	(0.131)
Scalability: high	−0.065	(0.144)	0.064	(0.158)	0.507	(0.126)***	0.244	(0.120)**	−0.013	(0.115)	−0.202	(0.122)*
Scalability: medium	0.059	(0.173)	−0.085	(0.190)	0.376	(0.159)**	0.318	(0.108)***	−0.092	(0.143)	0.091	(0.185)
Degree of innovation: high	0.199	(0.210)	−0.237	(0.194)	0.349	(0.205)*	0.328	(0.149)**	−0.172	(0.148)	0.022	(0.179)
Degree of innovation: medium	0.083	(0.148)	−0.115	(0.151)	−0.137	(0.140)	−0.147	(0.128)	−0.030	(0.155)	0.039	(0.150)
Proof of concept: provided	−0.277	(0.172)	−0.029	(0.187)	−0.446	(0.154)***	−0.290	(0.127)**	−0.026	(0.155)	−0.001	(0.154)
Importance of the societal problem: high	−0.061	(0.168)	0.025	(0.186)	−0.036	(0.181)	0.063	(0.159)	0.049	(0.169)	0.073	(0.212)
Importance of the societal problem: medium	0.251	(0.154)	0.274	(0.146)*	−0.010	(0.161)	−0.021	(0.135)	0.051	(0.143)	0.099	(0.144)
Professional background of the founding team: social	0.128	(0.156)	0.136	(0.131)	0.084	(0.167)	0.103	(0.131)	0.103	(0.133)	0.088	(0.134)
Professional background of the founding team: technical	0.088	(0.144)	0.254	(0.141)*	−0.040	(0.162)	0.010	(0.117)	0.197	(0.163)	−0.028	(0.143)
Authenticity of the founding team: high	−0.332	(0.190)*	−0.172	(0.192)	−0.126	(0.215)	−0.260	(0.158)	−0.049	(0.210)	−0.131	(0.196)
Authenticity of the founding team: medium	−0.145	(0.125)	−0.097	(0.141)	−0.086	(0.163)	−0.242	(0.106)**	−0.034	(0.146)	−0.215	(0.165)
Wald test	22.41**		18.92		37.28***		26.63**		5.75		20.53*
N (decisions)	1,704		1,704		1,704		1,704		1,704		1,704
N (decision-makers)	71		71		71		71		71		71

Note. Regression type: multi-level logistic regression with random intercepts and random slopes. Dependent variable: preference of the decision-maker. In Models 1–5, each attribute level interacts with a SII motive. For example, in Model 1, every attribute level is interacted with the stakeholder expectation motive. Model 6 captures the scope of nonfinancial supporting activities by an SII. The main effects are included in the estimation but are omitted for reasons of brevity so that the coefficients displayed here only refer to interaction effects. However, the main effects are qualitatively similar to the effects displayed in Table 7. OR = odds ratio; SE = standard error; SII = social impact incubator.

p < .10. **p < .05. ***p < .01.

Model 1 shows the results of the interaction effects between the stakeholder expectation motive and SIIs’ selection criteria. For this group, we do not find significant differences regarding their evaluation of the different selection criteria, except a slightly lower importance of the authenticity attribute. Model 2, however, shows that SIIs more focused on their own reputation place more importance on the societal problem and prefer a technical professional background in the founding team. In Model 3, we reveal that SIIs that strongly follow the innovative motive tend to assign less value to the proof of concept (−.446, p < .01) but favor ideas with a possibility of large-scale implementation (.507, p < .01) and those with a high degree of innovation (.349, p < .1). These results are similar to those of Model 4, which explores SIIs with a high duty to society motive. In addition to the greater importance assigned to the scalability of a project and the lesser importance assigned to the proof of concept, SIIs which focus strongly on their societal duty assigned less importance to a moderate authentic founding team (−.242, p < .05). Model 5 shows no significant differences regarding the evaluation of different screening criteria for SIIs that follow more financial motives. This result could be explained by the limited variation and generally low relative importance of this attribute (see Table 6). Finally, in Model 6, we investigate whether the scope of supporting activities provided by an SII affects their selection criteria. However, we do not find that SIIs with a larger scope of nonfinancial supporting activities have significantly different selection criteria. Applying a Wald test comparing the respective interaction model with the base model, we find statistically significant improvements for Models 3 and 4. Hence, in particular, SIIs with a high importance attached to innovation and societal duty motives stand out and differ in their SE selection from other SIIs.

Discussion, Contributions, and Future Research

Discussion

In investigating SIIs as a new type of incubator, our findings indicate that SIIs seem to focus strongly on the social outcomes of their activities. The main motive behind SIIs support of SEs seems to be the achievement of societal impact. By contrast, economic motives such as financial and reputation motives seem to be of comparably lesser importance for SIIs. This result indicates that SIIs are driven by the objective of fostering social entrepreneurship rather than being financially motivated (e.g., Aernoudt, 2004; Lalkaka, 2002). This finding is in line with prior research on business incubators, which argues that business incubators—rather than being driven by financial objectives—are primarily a tool to enhance the entrepreneurial environment in a region overall or in a certain field (e.g., Allen & Rahman, 1985). Even though social motives are of particular importance for SIIs, it could be argued that they still need to consider their own financial situation, at least if they must be self-sustainable. However, this is not reflected in their motives, which clearly prioritize social objectives. This result could be an indication that SIIs do not experience their own business situation as paradoxical but rather focus on the bigger picture of solving societal problems by supporting social entrepreneurship (Child, 2020).

With regard to supporting activities, SIIs are similar to traditional business incubators. Thus, they provide SEs with a diverse set of mainly nonfinancial supporting activities. Our findings are, therefore, in line with prior business incubation research (e.g., Allen & Rahman, 1985; Mian, 1996; Smilor, 1987). However, in contrast to the findings of Bruneel et al. (2012), we show that SIIs focus more on providing access to personal networks and less on providing infrastructure.

Furthermore, applying a CBC experiment, we identify the most relevant selection criteria of SII decision-makers. Thus, we draw on previous literature analyzing the selection criteria of SE supporters (Achleitner et al., 2013; Miller & Wesley, 2010; Yang et al., 2020). In particular, we extend the results of Yang et al. (2020), who suggest that both social and economic criteria are important to be selected into an impact acceleration program. In contrast to these findings, our results highlight that the authenticity of the founding team and the importance of a societal problem are the top selection criteria of SIIs. Since financial interests seem to be of lesser importance for SIIs, we demonstrate that they seem to value social criteria more than economic criteria.

Our finding that SIIs attribute relatively low importance to financial sustainability and the degree of SE innovation indicates that the financial performance of their program participants does not seem to be their main priority even though these criteria are components of the definition of an SE (e.g., Dees, 1998; Martin & Osberg, 2007). This finding diverges from previous research on impact investors (Achleitner et al., 2013; Block et al., 2021; Miller & Wesley, 2010). For these types of investors, financial criteria such as earned income or voluntary accountability reports of their supported ventures are of comparatively high relevance to the decision-making process. These differences might be explained by the diverse motives of both types of supporters. Although SIIs seem to be particularly motivated by the social impact they wish to achieve, impact investors typically seek ventures to achieve both social and financial returns for their investors (Achleitner et al., 2013). However, Achleitner et al. (2014) also indicate that the passion of the founding team has a great impact on the decisions of impact investors, echoing the relevance of our authenticity criterion for SII decisions.

Furthermore, the relatively low importance attributed to the financial sustainability of SEs could be explained by the business models of SIIs, which typically support ventures by fostering their economic orientation through the value-adding services they provide (Grimaldi & Grandi, 2005). Therefore, SIIs might not place much weight on the financial criteria of SEs because SIIs—similar to traditional incubators—aim to help SEs become financially sustainable as part of their value-adding inputs. Hence, the specific business model of SIIs allows them to manage the paradoxical situation of SEs by clearly prioritizing one objective over the other. First of all, they follow their social mission by focusing on social criteria and only afterward focus on other aspects. However, compared with traditional business incubators, SIIs also help SEs develop their social objectives. Overall, our findings are in line with Hirschmann and Moritz (2020) and Lall and Park (2020), who indicate that SEs should highlight their soft skills and sell their ideas in an authentic manner if they wish to obtain initial grants and signal their credibility to follow-up investors.

Finally, we show that SIIs are heterogeneous, as reflected by their evaluations of different selection criteria. Our results indicate that SIIs wishing to gather ideas from SEs and thus strongly follow an innovation motive also place more importance on SE innovativeness and on the potential to scale an SE’s social solution and focus less on an already provided proof of concept. Hence, for these SIIs, innovative projects that inspire them and with the potential to have large-scale social impact seem to be of particular relevance. This finding is in line with prior research on SIIs indicating that SIIs’ objectives are mainly to expand social innovations in society through the scaling of SEs (Almeida et al., 2012; Casasnovas & Bruno, 2013; Sansone et al., 2020). Finally, we show that SIIs that strongly value the motive to achieve societal duty also attribute more importance to SEs with scalable business ideas, which is in line with the findings of Yang et al. (2020) on social impact accelerators.

Implications

Theoretical implications

Our findings reveal important insights into a new incubation type and thus contribute to the literature in three ways. Two of our contributions address the extensive gap that exists with regard to prior research in the field of SIIs. Thus, we expand the literature focused on the particularities of SIIs (e.g., Aernoudt, 2004; Etzkowitz et al., 2005; Sansone et al., 2020) by exploring the motives, supporting activities and selection criteria of SIIs. In contrast to previous literature that identifies promoting social innovation as the driving motive (e.g., Almeida et al., 2012; Nicolopoulou et al., 2017; Sonne, 2012), the results of our quantitative study indicate that the societal duty motive is SIIs’ most important motive. Thus, our findings show that in contrast to the economic motivations of other supporting organizations such as social venture capitalists (Achleitner et al., 2014; Miller & Wesley, 2010; Scarlata & Alemany, 2009), SIIs seem to be more socially oriented and less driven by financial objectives. Furthermore, with our explorative multimethod approach, we are the first to identify the distinct selection criteria of SIIs as well as their heterogeneity, which is reflected in their evaluations of different selection criteria. Hence, we provide new insights into and a deeper understanding of the phenomenon of SIIs.

Second, our results contribute to the previous literature on the selection criteria of SE supporters (e.g., Lee et al., 2020; Miller & Wesley, 2010; Yang et al., 2020). Our finding that the authenticity of the founding team is the top criterion, which suggests that SIIs use an entrepreneur-focused selection process, which is consistent with the findings of Scarlata and Alemany (2009). However, the professional background of the founding team seems to be of comparatively low relevance for SIIs. This is surprising because the professional background of the SE team is another important criterion for entrepreneur-focused selection. However, this finding is in line with Achleitner et al. (2013), who also show that this criterion has little influence on social venture capitalists’ assessments of the integrity of SEs. In addition, we find that the importance of the societal problem addressed is the second most important selection criterion for SIIs. In contrast to social impact accelerators (Yang et al., 2020) and impact investors (Achleitner et al., 2013), SIIs seem to focus mainly on social selection criteria rather than economic criteria.

Third, we contribute to prior research on paradox theory investigating hybrid organizations and, in particular, SEs (e.g., Cherrier et al., 2018; Child, 2020; Jay, 2013; Pache & Santos, 2013). Our results highlight that SIIs seem to follow, in particular, social motives and value financial motives as least important. This could be an indication that SIIs do not experience their own business situation as paradoxical but look at the big picture of solving societal problems by supporting social entrepreneurship (Child, 2020). The focus on their social mission is also reflected in their screening criteria as they focus particularly on the authenticity of the management team and the importance of the societal problem. This result suggests that SIIs manage the paradox between the competing goals of SEs by setting clear priorities—first their social objectives need to be fulfilled before they look into economic criteria. This could be the result of the specific business model of SIIs where helping SEs to become financially sustainable is an important value-added service provided by SIIs.

Practical implications

The empirical insights of our study are of particular relevance to SEs seeking support from an SII and for SIIs themselves. First, our findings provide insights into how SIIs evaluate different selection criteria in their decision-making processes and hence offer knowledge to SEs on which criteria should be emphasized in their applications for SII support. We find that the authenticity of the SE team and the importance of the societal problem addressed are the most important selection criteria for SIIs, suggesting that SEs applying for SII support should focus on these criteria in their pitches. Other criteria that have been found to be highly relevant for other SE supporters, such as the background of the founding team and financial sustainability, receive the least attention from SIIs’ decision-makers. Hence, these criteria should not be the center of attention in an application for SII support. The motives of SIIs are represented by these results because SIIs seem to be especially motivated by achieving societal impact and not by pursuing financial interests. Thus, for SEs, our results illustrate that SIIs might provide very helpful support for developing their social ideas and establishing their businesses. Furthermore, our results with regard to the heterogeneity of SIIs suggest that SEs should emphasize different attributes in their application depending on the type of SII. For example, an application for an SII with a strong innovation motive should highlight the potential scalability and innovativeness of a project.

Decision-makers of SIIs can use our findings to better understand their own screening processes and benchmark themselves against the overall market for social incubation. Because our results reveal that the background of the founding team, financial sustainability, and proof of concept have a comparatively limited impact on SIIs’ selection decisions, SEs can evaluate whether these findings are in line with their overall business strategies. In particular, the observed strong preference for the perceived authenticity of the team and the importance of the societal problem addressed can provide SIIs with more transparency about their own evaluations of specific ideas, target groups, and beneficiaries.

Limitations and Avenues for Future Research

This study is not without limitations. Some of these limitations are related to the CBC method used. Whereas early research on selection criteria using questionnaires and qualitative interviews (e.g., Hall & Hofer, 1993; Tyebjee & Bruno, 1984) has been criticized for self-report, recall and response biases, conjoint analysis can suffer from the preselection of decision-making criteria and construct validity (Shepherd & Zacharakis, 1999). Thus, we were not able to test selection criteria other than the seven chosen. Nevertheless, conjoint experiments have been developed to more closely reflect actual selection processes because decision-makers are forced to trade-off criteria against each other. To minimize the risk of choosing the “wrong” selection criteria, we conducted expert interviews beforehand to identify the most relevant selection criteria. Furthermore, for external validity, we also conducted a pretest with SIIs to confirm our selection of attributes and attribute levels. Another drawback of the conjoint method is that participants are confronted with hypothetical SEs without providing additional material, such as business plans. The conjoint experiment, however, assumes that the decision-maker possesses all relevant information, even though in real-life situations, more or less information might be available during a screening phase. Hence, it is important to provide goals that are as realistic as possible to elicit reliable selections from decision-makers (Hsu et al., 2017). Our expert interviews, as well as the pretest, provide assurances that our choices are realistic and reflect real-life decision-making situations. Finally, our results are limited to the decision-making behavior of our 71 participants from the DACH region. Since the conception, characteristics, and degree of development of social entrepreneurship differ between countries (e.g., Defourny & Nyssens, 2010; Kerlin, 2006), it is possible that the motives and selection criteria of SIIs also show geographic differences. Even though we have included SIIs that operate globally (e.g., Impact Hub), and we would expect the same types of organizations to make decisions similarly across countries, future research could replicate our approach in other geographical areas to identify possible differences. For example, a similar research project could investigate the motives of SIIs in other geographic and cultural areas. Differences might especially exist between SIIs from developing and developed countries. Furthermore, a larger sample would enable a deeper investigation of the heterogeneity of SIIs and not only focus on differences with regard to their selection criteria but also on differences regarding value-added and (social and economic) impact achieved.

Another interesting research avenue would be to understand how the different motives of SIIs attract different SEs for their programs. Hence, future research could investigate whether SIIs that communicate a strong innovation focus and mission are successful in attracting SEs with a strong focus on social innovation. Taking the perspective of SEs, it could be investigated how the supporting activities offered by an SII might influence the attractiveness of a social incubation program. Furthermore, it would be interesting to see how these characteristics of SIIs influence SE performance. This approach could also provide further insights into whether performance is mainly driven by a focus on specific selection criteria (i.e., a specific preselection approach) or by SIIs’ value-added services (Croce et al., 2013; Di & Jiang, 2013). Another important area for future research would be to further investigate the heterogeneous landscape of SIIs. Since SIIs may be affected differently by tensions between their social and economic objectives depending on how they are motivated and funded, further research could explore this relationship in more detail. This would also help provide even deeper insights into the interconnections between the motivations and selection criteria of SIIs.

Research Data

sj-do-1-nvs-10.1177_08997640211057402 – for Motives, Supporting Activities, and Selection Criteria of Social Impact Incubators: An Experimental Conjoint Study

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sj-dta-1-nvs-10.1177_08997640211057402 for Motives, Supporting Activities, and Selection Criteria of Social Impact Incubators: An Experimental Conjoint Study by Mirko Hirschmann, Alexandra Moritz and Joern H. Block in Nonprofit and Voluntary Sector Quarterly

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sj-xlsx-1-nvs-10.1177_08997640211057402 for Motives, Supporting Activities, and Selection Criteria of Social Impact Incubators: An Experimental Conjoint Study by Mirko Hirschmann, Alexandra Moritz and Joern H. Block in Nonprofit and Voluntary Sector Quarterly

Footnotes

Appendix

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) received no financial support for the research, authorship, and/or publication of this article.

ORCID iD

Alexandra Moritz

Data Availability Statement

The data and codes that produce the findings reported in this article are available at .

Notes

Author Biographies

Mirko Hirschmann is a research assistant and doctoral candidate at the Chair of Management at Trier University. His research focuses on the particularities of financial and nonfinancial supporters of social enterprises, entrepreneurship in crises, and intellectual properties in the field of social entrepreneurship.

Alexandra Moritz is a postdoctoral researcher at the Chair of Management at Trier University, where she finished her PhD on financing patterns of SMEs and crowdfunding. Her research focus is on entrepreneurship, entrepreneurial finance, and strategic management of SMEs.

Joern H. Block is a professor of entrepreneurship and innovation management at Trier University and Erasmus University Rotterdam. His research is mostly of quantitative empirical nature and has appeared in journals such as Administrative Science Quarterly, Journal of Business Venturing, and Entrepreneurship Theory and Practice.

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