What's interesting in entrepreneurial education research? Identifying conversants sharing common interests in the field

2.1 EE as a field of research

EE constitutes a young field of research characterized by high growth and extensive changes (Duran-Sanchez et al., 2018) – evolving toward a field in its own right (Gabrielsson et al., 2020). Compared to more mature fields of research, the EE research field is characterized by less-developed constructs and models and a high degree of open-ended inquiries (e.g. Edmondson and Mcmanus, 2007). Studies have depicted the EE field as having a diverse multi-centric structure built around a range of largely disconnected core themes (Loi et al., 2016; Fellnhofer, 2019). Moreover, there is a relatively diverse pool of theories and teaching methods in the field (Hägg and Gabrielsson, 2020), with large variations in what EE implies in the classroom in relation to course content (Pittaway and Cope, 2007; Fayolle, 2013) and learning outcomes (Mandel and Noyes, 2016; Scott et al., 2016). Thus, there is little co-ordination of results or problems in the research field and EE researchers can thus deal with fairly broad problems and issues in a relatively diffuse manner.

In this particular context, we expect the intrinsic and personal interests of individual researchers to be a markedly influential driver of new research initiatives as well as building conversations in EE research. Engaging in scholarly conversations based on personal interests is a means of building enthusiasm and ensuring progress in the field (Fayolle, 2013), and also something that keeps certain groups of researchers together (Gartner, 2013; Frank and Landström, 2016). On the other hand, different views on what is perceived as interesting will support the development of parallel conversations in a research field that over time may depart in different directions (Gabrielsson et al., 2020). Conversations driven by passionate interest may thus serve as an imperceptible coordinator of scholarly efforts in EE research.

2.2 Interestingness in research – what do we know?

Researchers' subjective and intrinsic perception of interestingness plays a crucial role in science, for example, in initiating new research projects, and in building a research profile within the field. Research takes time, as an article may take a couple of years to complete, while a PhD thesis requires even more time. Thus, an intrinsic interest in an issue that the researcher finds intriguing, engaging and fascinating will be crucial for sustaining the intensive effort over a long period (Tsui et al., 2007; Shepherd et al., 2021). The opposite – a research project that the researcher does not find interesting – often turns out to be a self-inflicted torture, the reason for unfinished papers and dissertations and failure to build a sustainable research profile over the course of one's career.

2.3 Perception of interestingness in EE – outlining research questions

Davis' seminal work in the 1970s put forward counterintuitivity and novelty as the key aspects that make a study interesting. We recognize that these aspects are important, but in line with arguments put forward by scholars like Bartunek et al. (2006), and Das and Long (2010) we call for a broader view of interestingness as a concept. This means including elements such as practical relevance and usefulness, scientific craftsmanship and methodological rigor as important aspects of interestingness. In line with the argument put forward by Landström and Harichi (2019) that the perception of interestingness is to some extent unique for a specific research field, we will also explore to what extent the perceptions of interestingsness in the EE field are advanced by key scholars or what scholars consider to be hot topics. In order to elaborate on this assumptions we formulate the first research question (RQ1) in the following way:

A key finding from Das and Long (2010) is that perceptions of interestingsness are multidimensional and complex. In line with a broader view of interestingsness we argue that the perception of interestingsness will differ among groups of EE researchers. We can assume that different scholars, but also external stakeholders, may vary in their perceptions of interestingness, which will affect the focus and characteristics of conversations going on within EE research. In this paper we explore the individual interest in relation to other researchers and stakeholders in the field, where similar interests becomes essential focal points for scholarly conversations in the field. Thus, we propose as our second research question:

Researchers' perception of interestingness will not only influence their own research profile, and how different groups of researchers within the field are linked together in a social structure, but will also influence which conversations researchers within the field will end up in. According to Huff (1999), researchers need to identify subgroups of scholars within the field who perceive interestingness in a similar way and are attracted by the same research issues in order to initiate conversations and build collaborative networks. In a young and emergent research field we expect individual researchers to be particularly influential drivers of conversations in EE research. The argumentation leads to our third research question:

3.1 Identification of respondents

Our interest in perceptions of interestingness required us to collect first-hand data from EE researchers. Potential respondents were identified by reviewing a large number of conference papers, book chapters and journal articles. For conference papers, we selected 10 major conferences with a tradition of including papers on EE. The selected conferences and their coverage (years) were: AOM Annual Meeting (2014–2018), EURAM Annual Meeting (2014–2018), Babson Conference (2014–2018), the RENT Conference (2013–2018), ESU (2014–2018), EERC (2019), USASBE (2014–2019), ACERE (2014–2019) and 3E (2014–2019). Manuscripts addressing issues related to EE in the title or abstract were identified and the authors included in our sample. For book chapters, we selected 10 edited books that address EE. The following volumes were included in the search process: Faghih and Zali (2018), Fayolle (2006, 2007a, b, 2010, 2018), Manimala and Thomas (2017), Morris (2014), Morris and Liguori (2016), Matthews and Liguori (2018), Page West et al. (2009) and Thomas and Kelly (2008). In addition, we identified authors of published articles on EE in peer-reviewed academic journals in the period 2000–2018. The list of authors was identified via the literature review conducted by Hägg and Gabrielsson (2020).

The sources described above were used to compile a final database with author names, affiliations and e-mail addresses of all identified EE researchers. In many cases the e-mail addresses were available in the paper/chapter/article. If not, we expanded our search via the Google Web Search engine. Duplicates were deleted and we checked for other inconsistencies such as spelling. We managed to identify 1,409 unique EE researchers.

3.2 Questionnaire development

Both open-ended and closed-ended questions were included in the survey. The reasoning behind this was, on the one hand to gain general insight to the question of interestingness based on concepts used in similar studies within other fields, and on the other hand to gain a deeper and richer insight into the specific artifacts of interestingsness within entrepreneurial education. As a result, a fairly detailed questionnaire comprising almost 50 questions, both open-ended and closed-ended, to assess the respondents' perceptions of interestingness. In addition, the respondents were asked to provide information about characteristics such as age, gender, geographic affiliation, disciplinary background, seniority of position and time allocated to research and teaching.

Two approaches were employed to analyze scholars' perceptions of interestingness in EE studies. The first is an inductive approach that takes into account that scholars tend to assign different meanings to interestingness due to individual preferences and idiosyncratic opinions (see Subsection 2.2). Consequently, we used open-ended measures where respondents could freely elaborate on their perceptions of interestingness, based on Landström and Harirchi (2019). We asked the following questions; (1) What do you regard as “interesting” in EE studies?, (2) What do you regard as “uninteresting” in EE studies? and (3) Can you please nominate the most interesting work (book, article etc.) related to EE studies? This inductive approach compares well with previous studies on interestingness in scientific fields (e.g. Bartunek et al., 2006; Salvato and Aldrich, 2012).

The second is a deductive approach anchored in Das and Long (2010) who developed measures to gauge different (more generic) attributes of interestingness based on the theory of interestingness in sciences (see also Landström and Harirchi, 2019). In this way, we obtain measures of interestingness attributes that can be used across different fields of research. In this approach, the respondents were asked to rate 23 different attributes to assess their importance in making a study on EE interesting, ranging from 1 = unimportant to 4 = extremely important. An exploratory factor analysis of the attributes was conducted to identify the underlying structure of the interestingness attributes in our dataset. The factor analysis is presented in Subsection 4.4 “Attributes that make EE research interesting”. All attributes including means and standard deviations are presented in Appendix.

Overall, combining inductive and deductive approaches provided opportunities to make rich and insightful analyses of the perceptions of interestingsness in the EE field. At the same time, the mixed approach enabled us to explore and analyze the data thoroughly by using complementary insights from the open open-ended and closed-ended questions for each cluster in Section 5.

3.3 Data collection

A web link to the questionnaire was e-mailed in April 2019 to all 1,409 EE researchers identified in the previous step. Of these, 67 e-mails were returned as undelivered and those researchers were removed, resulting in 1,342 researchers receiving the questionnaire. The first question concerned whether the respondents identified themselves as EE researchers (either today and/or in the past). If they did not perceive themselves as EE researchers, they were directed to the end of the survey and excluded from the study. The remaining respondents were led through the questionnaire. At the end of the questionnaire the respondents were also provided with the opportunity to propose additional respondents who they identified as EE researchers. This snowball sampling resulted in 51 additional respondents who were not included in the first mailing. After a six-wave mailing, i.e. five reminders, 555 valid completed questionnaires were obtained from respondents identifying themselves as EE researchers, as illustrated in Table 1. Thereafter we excluded respondents who failed to provide information on the key variables of interestingness relevant for this study. In total, 465 respondents provided complete data for the selected variables used in our analyses.

3.4 Analyses

We performed non-respondent analyses to test for possible biases concerning respondents and non-respondents with respect to gender and geographic affiliation. Our analysis showed no significant differences with respect to gender. However, the analyses revealed an overrepresentation of European researchers and an underrepresentation of North American researchers among the respondents compared to the total population of researchers who received the survey, significant at p < 0.00. This implies a potential limitation in our dataset in terms of geographical representation.

In addition, we compared early and late responders with respect to academic position, age, educational background, gender and geographic affiliation, assuming that the late responders would have strong similarities to non-responders (Armstrong and Overton, 1977). Furthermore, we compared the 465 responses with full information on the key variables of interestingness with those that were not useable due to incomplete data. These comparisons did not show any significant differences apart from an overrepresentation of male respondents in the sample used for the analyses, significant at p < 0.05.

We conducted analyses of both the open-ended and the closed questions about interestingness. The open-ended questions were analyzed by inductively categorizing the raw data into meaningful units without any a priori theory-based expectations. The coding was made independently by two of the authors. The inter-rater reliabilities showed a high degree of agreement between the coding (Cohen's kappa [3] between 0.939 and 0.973). The closed questions were subject to factor and cluster analyses. The statistical analyses associated with the closed questions are presented in more detail in Subsection 4.4 and Section 5.

Several steps were taken to minimize common method bias as the variables come from self-reported data, including the protection of respondent anonymity and ensuring that items were placed in different sections of the questionnaire to reduce the likelihood that responses were cross-checked for internal consistency. In addition, Harman's one-factor test (Podsakoff et al., 2003) was conducted to check whether one component accounted for most of the variance. No evidence of common method bias was detected.

3.5 Description of the sample

A descriptive overview of the 465 respondents is presented in Table 2. As can be seen from the table, a majority of the respondents are male (58.3%), which corresponds well with the gender distribution seen in other samples of entrepreneurship scholars (e.g. Landström and Harirchi, 2019). The respondents come from different geographical contexts, of which Europe and North America are dominant; 63.4% have their main affiliation in Europe and 24.3% in North America. Most of the respondents (80.2%) hold a PhD degree. The average age of the respondents is quite high (50.1 years), which is reflected in the large proportion of senior scholars in terms of full professors and associate professors (54.0% of the total sample). While a large majority of the respondents (68.6%) have their educational background in “Business administration and law”, a large proportion (31.4%) of respondents have other disciplinary backgrounds such as “Education”, “Social and behavioral sciences”, “Engineering, manufacturing and construction” and “Arts and humanities”. In this respect, the sample represents a diverse group of scholars in terms of disciplinary backgrounds, which is also reflected in the considerable proportion of respondents (43.4%) who are partly (rather than fully) active in conducting EE studies. Hence, it seems that many scholars conducting EE studies also allocate substantial time and effort to research activities within other areas or domains.

4.1 Perception of interestingness among EE researchers

Table 3 shows the top responses to the question: What do you regard as “interesting” in EE studies? The respondents could freely elaborate on what they perceive as interesting and nominate more than one aspect. In total, 938 aspects of interestingness were nominated. The nominations were reviewed and inductively coded into six distinct categories.

The top category includes nominations with respect to “Interesting topic-driven issues” and represents 73.2% of the total number of nominations. As can be seen from Table 3, the top-three nominations in this category reflect topic issues directly related to EE (39.2%). The first top research topic includes nominations that indicate an interest in “teaching and learning entrepreneurship” (16.1%) with a focus on subtopics such as teaching methods and pedagogical approaches, program and curricula design, and learning processes in EE. The second top research topic includes nominations that reveal an interest in the various “Entrepreneurial characteristics” (12.4%) that are in focus when discussing EE, such as intentions, traits, cognition, passion, identity, mindsets or other personal characteristics necessary or essential for performing entrepreneurship. The third top research topic includes nominations that demonstrate an interest in the “Outcomes of EE” (10.7%), such as post-graduation activities of alumni, the impact and effectiveness of EE, the employability of graduates as well as alumni engagement. The remaining topic-driven issues (34%) comprised two general subcategories. The first contains issues embedded in EE, such as student engagement and student teams, the teachers' role, and the varying contexts of EE, while the second consists of different subthemes of practical EE, such as creativity and innovation, management, entrepreneurial universities and ecosystems, and specific forms of entrepreneurship (e.g. intrapreneurship, social entrepreneurship, academic entrepreneurship).

The second most frequently nominated category represents an interest in “Methodological issues” (11.1%). In this category, the top issue reflects interest in “Definitional and paradigmatic discussions of EE” (5.0%), which includes debates about the teaching domain such as why provide EE and for whom is it intended?, what are the disciplinary boundaries of the field? and other discussions about EE as a scholarly field. The second highest top issue within this category reflects an interest in “General methodological issues” (2.7%) such as methodological rigor and issues related to novel research questions and methods. A third top nomination is “Critical studies” (1.7%) where nominations reflect an interest in studies that challenge taken-for-granted assumptions in EE research.

Of the remaining categories we received nominations expressing an interest in “Practice links to EE” (5.1% of the total number of nominations), “Theoretical considerations” (4.3%), “Research results” (2.3%) and “Other issues” (4.2%). The category “Other issues” also includes nominations that we were unable to code due to difficulties in understanding the respondents' answers (3.9%).

4.2 Perception of uninterestingness among EE researchers

In the next step we analyzed the responses to the question: What do you regard as “uninteresting” in EE studies? In total, 538 aspects of uninterestingness were nominated. The nominations were reviewed and inductively coded into five categories. Yet again, it is clear from Table 4 that particular research topics within the field are perceived as uninteresting by EE researchers. The top category of uninterestingness includes nominations that address “Uninteresting topic-driven issues” (29.45). Of the specific topics that EE researchers perceive as uninteresting, the most frequently mentioned were “Entrepreneurial characteristics” (15.2%), “Business planning and business canvas models” (5.7%) and “Economics/management/finance” (4.7%).

The second most frequent category of uninterestingness addressed “Concerns regarding research approaches/methodologies” (25.7%). The two most common concerns raised in these nominations were studies that lack novelty and have methodological flaws. In this respect, EE researchers seem to have some concerns regarding the low level of quality studies within the field, but also an aversion to studies that cannot show novelty and challenging results.

Of the remaining nominations a relatively large share belongs to the category “Uninteresting EE studies” (17.9%). This category includes concerns about studies having a too strong business or normative focus, as well as studies focusing on the impact and assessment of EE. Another category regarded as uninteresting addresses “Concerns regarding EE teaching and administration” (14.3%), which includes dissatisfaction about the way entrepreneurship is taught and descriptions of academic work (e.g. teaching, grading, meetings, administration, etc.). Finally, the nominations also include a notable share (9.5%) explicitly stating that there is nothing uninteresting in EE research.

Comparing perceptions of interestingness vs uninterestingness suggests that EE is a highly topic-driven field. Many scholars have opinions on which topics are worth researching or not researching in EE. In Tables 3 and 4 it is shown that “topic-driven” issues is the largest category for the perception of interestingness (73.2%) as well as for the perception of uninterestingness (29.4%). It should also be noted that in many cases the responses are highly contradictory, for example, responses related to “Entrepreneurial characteristics” constitute both the second largest number of responses on the most interesting issues in EE and on the issue that is perceived as the most uninteresting. Similar contradictions were found with regard to other issues, such as definitional and paradigmatic discussions, theory development and theory-driven studies, and the respondents' perceptions of qualitative and quantitative research methods. The results suggest that EE is a highly heterogeneous scholarly field – comprising different groups of scholars with contradictory perceptions of what is interesting in EE research.

4.3 Interesting works in EE research

When looking into the actual nominations of works, the most interesting finding is the absence of core works that unite EE researchers (Table 5). In total, 358 nominations were made, and the top-10 works only account for 83 of these nominations (or 23.2%). In addition, as many as 220 different unique works were mentioned as being the most interesting works in the field. Even though the names of the authors of the most interesting works are not surprising, the proportion of the high-ranking works perceived as interesting is surprisingly low, the most interesting work (Sarasvathy, 2001) only generating 4.3% of the total number of nominations.

Inspired by the categorization of EE research developed by Loi et al. (2016) we decided to analyze the diverse characteristics of interesting works in EE in more depth (Table 6). Less than half of the nominations (48.5%) are related to works on EE and more than 30% to entrepreneurship in general. Only a handful of nominations are solely connected to the pedagogy field. This means that the EE field in general is less connected to the pedagogy field and far more strongly linked to the entrepreneurship field.

One of the most intriguing findings from this analysis is the lack of nominations of works related to entrepreneurial intentions, i.e. individuals' orientation which might lead to venture creation. Previous studies (see, e.g. Nabi et al., 2017) have shown that studies of entrepreneurial intentions are one of the key areas in EE research when it comes to published works. Our study demonstrates that research on intentions is not considered particularly interesting by EE researchers. It is also worth noting that the literature on entrepreneurial learning in the general entrepreneurship domain is only considered most interesting by a small number of EE researchers. This is surprising in light of the strong influence of entrepreneurship researchers in the EE field. Another interesting finding is that only 6.2% of the nominated works are “tool” oriented (e.g. related to lean start up, business model, canvas, design thinking, etc.), despite the fact that these tools are present in almost every EE program around the world. Finally, we would like to underline the fact that 189 of the respondents did not nominate any interesting work. This strengthens the impression of a field where the researchers have only created a common ground or platform to a very limited extent.

4.4 Attributes that make EE research interesting

To enable systematic analyses of interestingness we asked the respondents to rate 23 attributes on their importance in making a study on EE interesting. The attributes were taken from Das and Long (2010; see also Landström and Harirchi, 2019). On aggregate, our data suggest that EE researchers tend to highly rate attributes related to practical relevance and novelty, while perceiving studies that rely on sophisticated statistical analysis and large samples as less interesting. The three most highly rated attributes are related to practical applications with regard to a theory or research findings (e.g. attribute 12), the investigation of novel issues (e.g. attribute 16) and the practical relevance of the topic (e.g. attribute 18). The lowest ratings were for attributes related to instructive details about data analytical tools (e.g. attribute 2), application of sophisticated data analytical tools (e.g. attribute 9) as well as the use of large samples (e.g. attribute 3). We present means and standard deviations for all attributes in Appendix.

However, the attributes that make a study interesting are complex and multidimensional (Das and Long, 2010). For this reason, we employed exploratory factor analysis to uncover the underlying structure of the interestingness attributes. We used principal components as the extraction model combined with orthogonal rotation to find interpretable solutions, where the number of retained factors relies on Eigenvalues greater than 1 (Kaiser, 1960). The results are presented in Table 7.

The factor analysis reveals four factors with underlying relationships between attributes. The first factor, “Novelty” (items no. 6, 7, 11 and 16), focuses on attributes associated with new paradigms or perspectives, new research designs and methodologies, and new questions or topics, thus indicating that interesting EE research has the quality of being original or even unusual in character (e.g. Barley, 2006). The second factor, “Theory” (items no. 1, 8, 13, 15 and 21), contains attributes that emphasize theory development and the application of and contribution to existing theory, as well as acknowledging existing theories and uncovering hidden assumptions. This factor indicates an interest in advancing EE research by using and developing robust theoretical frameworks.

The third factor, “Relevance” (items no. 12, 17, 18 and 22), includes attributes associated with practical applications, relevance to practitioners, the use of an engaging writing style, as well as an emphasis on intuitive and common-sense findings. This factor reflects the practice-oriented focus often found in EE research. Finally, the fourth factor is “Rigor” (items no. 3, 19 and 20), which focuses on logical and rational methodological approaches, and the use of large samples to generate findings that can be generalized to larger populations. This factor captures an underlying interest in the application of sophisticated methods and statistical techniques as a starting point for advancing EE research.

In this section we have elaborated on the perception of interestingness among EE scholars. We have taken an inductive approach to analyze interesting (and uninteresting) issues and works, as well as a deductive approach to identify more generic attributes of interestingness in EE research. These insights form the basis for the following two sections. First, we discuss how perceptions of interestingness in EE research differ between subgroups of EE researchers (Section 5), and, second, we elaborate on how the different perceptions will affect the focus and characteristics of conversations going on within the research field (Section 6).

7.1 Contributions

The aim of this study has been to advance the understanding of how perception of interestingness influence the structure and focus of conversations in EE research. Particularly, our analysis provide theoretical and empirical insights into what researchers in the field perceive as interesting (RQ1), how the perception of interestingness differs among subgroups of EE researchers (RQ2), and finally, based on the focus and characteristics of conversations going on within the subgroups, how EE researchers can engage in conversations centered on common interest (RQ3). In light of our analysis and findings, we will in this final section reflect on the development of EE as a research field, and how researchers can support the integrity and relevance of EE research by identifying conversants sharing common interests in the field.

EE is a young and less institutionalized field in the academic system (Neck and Corbett, 2018; Gabrielsson et al., 2020), and similar to other young research fields (e.g. Fink et al., 2016) it is highly driven by subjective and idiosyncratic perceptions of interestingness. In line with such arguments, our results reveal that EE is a fragmented research field when it comes to the perception of interestingness, as well as the absence of core research works within the field. Our analysis shows that EE is a highly “topic-driven” research field, in which researchers perceive topics such as teaching and learning entrepreneurship, the characteristics of the entrepreneur and outcomes of EE as particularly interesting. Many EE researchers tend to have an interest in issues related to practical relevance and, not least, to novel and challenging ideas, at the expense of sophisticated statistical analysis and large sample studies. In this respect, the topic oriented interest, strong focus on novelty and challenging research, as well as the practical relevance of the research are similar to other young research fields (Salvato and Aldrich, 2012; Landström and Harirchi, 2019), which is understandable in research fields that need to compete for fundings, talent and recognition (Tsang, 2021). In this respect, our findings can serve as input for a discussion of how to continue building scholarly conversations and communication arenas within the field – on the one hand embedded in a passionate interest among the community of researchers, on the other acknowledging the value of building and disseminating knowledge based on systematic studies and replicable findings (e.g. Rideout and Gray, 2013; Neck and Corbett, 2018).

The analysis identified five subgroups (clusters) of EE researchers. Subgroups 1 and 2 can be seen as main advocates of the EE field. They are both very concerned with improving and advancing EE research as a unique scholarly domain. Subgroup 1 has a particular interest in practically relevant research that generate novel theoretical insights, and the members of subgroup 2 are interested in novel paradigmatic and theoretical contributions. Researchers in subgroup 3 place more emphasis on methodological rigor. Subgroups 4 and 5 differ from the other subgroups in that they are not particularly interested in novelty and challenging current assumptions. But, there are also major differences between the two subgroups, for example, subgroup 4 has a strong research orientation and an interest in studies that demonstrate solid scientific craftmanship that focus on theory and rigor, whereas subgroup 5 consists of a large group of researchers who are not particularly involved in EE research (“Spectators”).

Finally, our analysis generates insights on how EE researchers can navigate the EE landscape and engage in conversations with audiences who share similar research interests. From our analysis it becomes obvious that the field of EE in general is largely characterized by a pioneering spirit, and many conversations focus on novelty and challenging current knowledge. In Section 6 this general statement is nuanced and it is shown that three core conversations are going on within the field. The PROGRESS conversation is driven by the main advocates of EE research (subgroups 1 and 2) and includes dialogues on “differentiation” and “reorganization”, the UTILIZATION conversation (driven by subgroup 3) centered around bridging the rigor-relevance gap, and finally, the ACCUMULATION conversation that attracts researchers with an interest in knowledge accumulation, identifying research gaps and theory building in EE research (mainly in subgroup 4).

Our findings encourage the integrity and relevance of EE scholarship by explicating the pluralism of EE research in regards what makes a study interesting. In this respect, researchers who seek and want to participate in conversations discussing new topics, approaches, methods, etc., appear to have great opportunities to find like-minded researchers within the field. However, there are also nuances in this statement. Researchers with an interest in practical applicable research should approach the dialogue on “differentiation” taking place at conferences such as 3E, ESU, RENT and USASBE, or engage in the UTILIZATION conversation (with a stronger entrepreneurship focus) at conferences such as AOM and Babson. Researchers interested in challenging the paradigmatic and theoretical assumptions in EE research will find their like-minded colleagues at the dialogue on “reorientation” going on at EE and entrepreneurship journals and conferences. Finally, researchers interested in relevance, methodological and theoretical issues should approach the dialogue on “differentiation”, but particularly, the core conversation on ACCUMULATION, with an interest in knowledge accumulation via theory development and quantitative research designs – conversations that are going on at more general management and entrepreneurship conferences, for example, RENT, AOM and EURAM. Concurrently, the different conversations contribute to making EE a vibrant scholarly field with multiple opportunities to build a research profile, create social ties and networks and carve out niches in the research domain.

7.2 Limitations and future research opportunities

Our study has some limitations that need to be acknowledged. First, we are unable to assess the representativeness of our database due to the lack of information about the population of EE researchers around the world. We tried to resolve this problem by using a broad range of different sources to identify potential respondents, including conferences, edited handbooks and published articles, as well as several rounds of “snowball sampling” in the survey. Nevertheless, the question of representativeness remains unresolved, which should be kept in mind when interpreting the findings. Future studies would hence be useful for clarifying the extent to which our sample reflects the characteristics of the global population of EE researchers. Second, the database has an over-representation of European EE researchers compared with the full list of potential respondents identified in our broad search who received an invitation to participate in the survey. However, as respondents were promised full anonymity, we were unable to send extra reminders to non-responders from outside Europe to balance the sample. Accordingly, we note this as a potential limitation in our dataset and we encourage future replications of our study to remedy this bias.