Asymmetric modelling predicting migrants versus refugees starting new ventures

Catalina Crisan-Mitra (Department of Management, Babeș-Bolyai University, Cluj-Napoca, Romania, and)
Gregorio Martín-de Castro (Department of Business Organisation, Complutense University of Madrid, Madrid, Spain)

Journal of Ethics in Entrepreneurship and Technology

ISSN: 2633-7436

Article publication date: 8 December 2023

Issue publication date: 14 December 2023




This study aims to examine the entrepreneurship profiles of migrants and refugees relying on a neo-configurational approach that increases understanding of causal complexity, equifinality and causal asymmetry patterns to high entrepreneurial intentions in the two groups.


Using a fuzzy set qualitative comparative analysis method, the authors analysed 52 respondents – migrants and refugees. The findings show the existence of equifinality in which different configurations can lead to high and low entrepreneurial intentions, underlying that traumatic experiences have a major role in entrepreneurial intention. It also demonstrates that core conditions are associated with refugee’s configurations and causal asymmetry. The cross-sectional character of this research impedes the searching for a better causal relationship. The lack of studies that approach the subject of refugees makes it challenging to develop a robust theory in this sense.


The paper highlights five main configurations – two related to migrants’ profile and three related to refugees’ profile – that enable expanding the current knowledge and practices to better customize practices to increase entrepreneurial intention.


To the best of the authors’ knowledge, this is the first research using a configurational approach to explore migrant and refugee entrepreneurship intention profiles.



Crisan-Mitra, C. and Martín-de Castro, G. (2023), "Asymmetric modelling predicting migrants versus refugees starting new ventures", Journal of Ethics in Entrepreneurship and Technology, Vol. 3 No. 2, pp. 111-126.



Emerald Publishing Limited

Copyright © 2023, Catalina Crisan-Mitra and Gregorio Martín-de Castro.


Published in Journal of Ethics in Entrepreneurship and Technology. Published by Emerald Publishing Limited. This article is published under the Creative Commons Attribution (CC BY 4.0) licence. Anyone may reproduce, distribute, translate and create derivative works of this article (for both commercial and non-commercial purposes), subject to full attribution to the original publication and authors. The full terms of this licence may be seen at

1. Introduction

Immigration pressures are expected to be more intense in European countries which will challenge the European Union (EU) policies (Dao et al., 2021). Massive population movements require building societal resilience, a challenging mission due to the context specificity of EU policies (Ozcurumez, 2021). Education as well as cultural awareness and entrepreneurship competence are essential conditions for new commers integration (Byabashaija and Katono, 2011). EU resilience strategies priorities recognize the importance of supporting refugees to create opportunities within hosting states (Anholt and Sinatti, 2019), while entrepreneurship due to its impact on social cohesion, sustainability and poverty alleviation is seen as a key driver of vulnerable groups’ opportunity development (European Commission, 2020).

The circumstantial status of migrants is an influential factor to predict entrepreneurial intentions (EIs) and predisposition towards entrepreneurship (e.g. Kushnirovich et al., 2018). Exploring the relationship between forced migration experiences and EI remains largely absent (Mawson and Kasem, 2019). Furthermore, numerous distinctions set them apart, necessitating individualized analyses (Wauters and Lambrecht, 2008; Bizri, 2017). Our paper provides an understanding of entrepreneurship development among vulnerable groups (e.g. migrants/refugees) by explaining several patterns leading to EI and underlining the role of extreme violence on EI.

The authors apply a neo-configurational approach to frame this research. This framework is adequate to understand the complex phenomenon of individual entrepreneurship, due to its interrelated external and personal circumstances embodied in the human being, which implies a new asymmetric logic for theory construction (Woodside, 2019). Traditionally, for management scholars, configurations have been used to explain organizational performance. We consider that (1) refugees and migrants require separate analyses due to the exposure to war-related stress; (2) configurations of causal conditions leading to EI are different in the case of refugees and migrants.

Our study starts with Section 2 which covers theory development and propositions about migrants’/refugees’ entrepreneurship profile, entrepreneurship intentions particularities and a new configurational framework. Section 3 presents the method of fuzzy set qualitative comparative analysis (FsQCA), the research methods and the variables. Section 4 encompasses the findings pertaining to essential core and peripheral conditions, along with an analysis of causal asymmetry. The final trio of sections is dedicated to discourse on the findings, theory refinement and the conclusive remarks derived from this study.

2. Theory development

2.1 Precursors of migrants’ and refugees’ entrepreneurial intentions

EI is defined as “the conscious state of mind that precedes action and directs attention toward starting a business or becoming an entrepreneur” (Esfandiar et al., 2019). During the past decades, migrants’ and refugees’ entrepreneurial behaviour has developed into a significant field of study (Ram and Jones, 2008; Turkina and Thai, 2013). Entrepreneurship is considered a viable employment and income solution, an option for economic advancement and an avenue of integration of newcomers in the host country (Heilbrunn and Kushnirovich, 2008). Refugees are forced to leave their country because their lives, safety or freedom have been threatened (UN Refugee Agency, 2023), whereas “migrants” are individuals who make a conscious choice to leave their country to seek improved living conditions (European Commission, 2019). Due to the traumatic experiences given by war, refugee entrepreneurs have a particular profile due to their past life experiences, making them more resilient to harsh conditions (Brzozowski et al., 2014).

Refugees and migrants require separate analyses due to the many discrepancies between them (Bizri, 2017; Fong et al., 2007; Wauters and Lambrecht, 2008), and a differentiator is the exposure to war/extreme violence (see Refugee_Character), a construct specific to refugees. Also, according to the authors, the individual ability, access to specialized support, cultural heritage, willingness to embrace the host culture and traumatic experiences are considered the most relevant precursors of EI, and their influence will to be proved in this study.

Individual ability and adaptability (Indiv_ab_ad): The intellectual capacity, educational background and previous experiences shape people’s attitude towards creativity and problem-solving and, more specifically, their learning abilities (Naidoo, 2013). The emotional state and negative feelings due to traumatic stressors lead to frustration and anxiety, negatively affecting the learning process. EI is influenced by the entrepreneur’s self-motivation and other personal needs, in particular to each individual and on the predisposition to learn (Koyuncuoğlu, 2023). Personal characteristics, culturally determined features and the constraints faced allow migrants to develop more reliable motivations to become hard workers and risk-takers in business activity (Brzozowski et al., 2014). Being used to having access to limited resources, migrant entrepreneurs are more resistant to failure and find ways to outperform competitors. Migrants’ readiness to stay in the host country depends on their ability to accept what is new and different in the host community (Turney and Kao, 2009). According to Ventres (2017), understanding the socio-economic and cultural barriers and the value system of the host community enhances the migrant’s predisposition to accept new approaches. Understanding the education system and knowing the language of the host country ease the integration process (Turney and Kao, 2009).

2.1.1 Assistance and training (Ass_tr).

Constraints and opportunities coming from the new environment have a significant influence on migrants’ predisposition towards start-ups (Phizacklea and Ram, 1996). Previous life experiences, education and professional experiences have a significant influence on the predisposition to start a business (Irastorza and Peña-Legazkue, 2018). Migrant entrepreneurs need support, regular monitoring and long-term based entrepreneurship training to make them competent and motivated (Yeasmin, 2016). They need knowledge about local opportunities, tax codes, social insurance systems, labour market legislation, competition policy, trade policies, capital market regulation and contract law (Hall and Jones, 1999). Encouraging credit and training programmes, native language courses and access to programmes facilitate the integration of youth refugees and their families, fostering entrepreneurial actions and overcoming prejudice (Fong et al., 2007). Despite the challenging adaptation problems, refugees having access to professional support are more open to change (Chou, 2009). Exposure to entrepreneurship and consulting support is a representative factor to stimulate EI (Peterman and Kennedy, 2003). Entrepreneurship training is more impactful once migrants rely on previous entrepreneurial experiences, especially if they were self-employed and had role models entrepreneurs (Krueger, 1993) and are more disposed to accept advice and capital from informal sources, rather than formal (Basu, 1998).

2.1.2 Cultural heritage (Cult_herit).

The values and attitudes towards entrepreneurship differ substantially across countries and nations (Glinka and Brzozowska, 2015). Cultural heritage norms, traditions, ethnic identities and networks profoundly shape migrants’ EI (Irastorza and Peña-Legazkue, 2018). Greve and Salaff (2005) claimed that, by sharing the same culture, migrant entrepreneurs promote networking among members to access support and are more likely to serve the needs shared by their counterparts. The religious practices, their social behaviour and their habitation strategies affect the economic decisions of migrants and their families in the host country (Brzozowski et al., 2014). Discrimination on ethnicity or cultural differences, associated with earning differences, can lead to a more prominent predisposition towards entrepreneurship (Wauters and Lambrecht, 2008).

2.1.3 Understandings of the host community (HCom_und).

According to Portes and Zhou (1993), migrants must profoundly understand socio-economic barriers, to become alike to the receiving society and take initiative. Migrants must deeply understand socio-economic barriers, to become much more alike to the receiving society. Turney and Kao (2009) also point out that cultural differences, culturally appropriate school transition and experienced trauma influence the adaptation. The difficulty to assimilate the new knowledge stems from the shortage of entrepreneurial education, poor language skills and limited understanding of the local culture, policies and laws that are relevant to business (Yeasmin, 2016). Besides that, the interaction of refugees with schools is influenced by linguistic and cultural differences, which makes it hard to advocate for their needs. Usually, migrant businesses are small and low-income ventures (Neville et al., 2014), and they are more likely to quit their business than regular citizens because of the complex challenges due to their migrant status (Irastorza and Peña-Legazkue, 2018).

2.1.4 Refugee’s character (R_C).

The loss of social status and personal identity, cultural duality and the new norms tend to determine feelings of anxiety, frustration and post-traumatic stress disorder, making refugees sometimes engage in socially inappropriate and dysfunctional behaviours (Kröger et al., 2016). A decisive factor in the mental health and long-term adjustment of young refugees – except education and care in the initial years of resettlement – is the refugee’s commitment to succeed (Eide and Hjern, 2013). Exposure to high risks influences individuals’ EI (Kushnirovich et al., 2018). Increased mistrust, anxiety, aggression, revenge and disruptive behaviour are often associated with highly experienced risks (Kröger et al., 2016). Rosner et al. (2003) underlined that people who experienced the Bosnian War show an increased risk of post-traumatic stress disorder, anxiety and depression, imposing specialized treatment and a tailored approach. Furthermore, Hollifield et al. (2018) described that war-related stress produces not a direct but a sizeable indirect effect through post-migration stress on mental health, leading to disruptive effects on the learning and integration process. In the case of migrants, the traumatic experiences are reduced, compared to refugees and are more related to the integration process and managing cultural differences. Past exposure to severe violence and trauma requires customized training and social care to enable their smooth integration within the host communities.

3. Method

3.1 Population, sample and data gathering

This study is qualitative research relying on semi-structured interviews applied to 52 respondents – refugees/migrants from an organization that operates in Romania. The causal conditions described in the previous chapter were developed by the authors relying on the literature to analyse pathways leading to the low and high EI of refugees/migrants. Our study used a pre-test by selecting a sample of five migrants approached by the organization, to see if items are clearly understood. We used a Likert-type scale anchored with five frequency adverbs.

The respondents’ nationality structure was as follows: 23 Syrian, and the other 28 were Afghans, Iranians, Egyptians, Stateless, Trinidadian, Eritrean, Palestinian, Estonian, Indian, Iroquoian, Myannarian, Brazilians and Sudanese.

We chose this organization for several reasons. Firstly, this organization uses a revolutionary approach to integrate migrants and refugees within host communities, relying on developing IT skills to facilitate their integration into the market. Secondly, among several organizations approached in our previous projects, this was selected because the founder was interested in involving the beneficiaries in research initiatives, to better address their needs. The research raised some ethical issues, such as consent and confidentiality, and thus everyone who participated in the study freely consented to do so without being coerced or unfairly pressured.

3.2 Measurement and calibration of causal conditions and output

An exploratory factor analysis (EFA) was carried out to extract latent variables using varimax rotation. According to the literature, factor analysis assumes that a small number of latent constructs are responsible for the correlations between large numbers of observed variables and a measuring model whose value is greater than 0.6 is considered reliable. The results of EFA, item-to-total correlation and analysis of internal consistency (Cronbach’s alpha) confirmed the reliability factor. We excluded from the analysis, items with low correlation (less than 0.45). The process continued with an internal consistency analysis and consistency, according to the alpha coefficient.

EFA results showed a good fit, with a KMO value of 0.718 (Kline, 1994), and Bartlett’s test of sphericity with a significance of 0.000 and 136 df. Thus, four main factors with eigenvalues over one were extracted, with a total explained variance of 66%. In addition, the rotated component matrix, with a principal component analysis extraction method, shows good fit indexes.

3.3 Fuzzy set qualitative comparative analysis

Configurations are a set of interrelated causal conditions with a synergetic nature (Pappas and Woodside, 2021) and are an adequate framework to understand a complex phenomenon associated with individual and organizational behaviours (Ragin, 2008). A configurational perspective highlights causal complexity (Woodside, 2017; Misangyi et al., 2017). It goes beyond applications of regression analyses (Woodside, 2017) and commonly implies:

  • conjunction – rarely a behavioural outcome has a single cause;

  • Equifinality – an output can have multiple causal paths; and

  • Causal asymmetry – causal conditions and configurations linked to a determined output and its reverse or negation do not imply the negation of those same causal conditions and configurations (González-Velasco et al., 2019).

The fsQCA, based on Boolean algebra, was used to determine a new configurational approach. We propose fsQCA for several reasons: (i) it enables us to test the propositions regarding the influence of migrant’s profile configurations as complex sets of attributes on EI outputs (Greckhamer et al., 2008); (ii) fsQCA has the advantage of being suited to small sample sizes – with less than 100 cases –, and limited diversity (52 questionnaires). As Fiss (2011) remarked, in contrast to standard econometric methods, the non-parametric fsQCA does not draw data from a given probability distribution; and (iii), as Fiss (2011) and Martín-de Castro et al. (2014) highlight, some promising applications of fsQCA to management research include the RBV framework and micro-foundations.

4. Results

4.1 Validation of causal conditions

According to the model of refugees and migrant entrepreneurship profile, this study proposes the following five causal conditions that remained after the analyses:

  1. Individual ability and adaptability (Indiv_ab_ad). Is a causal condition made from the following items: “the predisposition to accept what is new and different” (Turney and Kao, 2009), “putting aside the preconceptions” (Portes and Clark, 1987), “understanding the value system of the community” (Ventres, 2017) and “understanding how the education system works” (Turney and Kao, 2009), with an explained variance of 20.5% and a Cronbach’s alpha of 0.849. This causal condition embodies personal understanding and willingness to gain new knowledge about the host community. Respondents consider that the integration process relies on the individuals on their determination to assimilate new knowledge to change behaviour according to the new context.

  2. Assistance and training (Ass_tr) is a causal condition made up of the following items: “economic support received as a migrant” (Heilbrunn and Kushnirovich, 2008), “social support received as a migrant” (Yeasmin, 2016), “access to entrepreneurship practices” (Peterman and Kennedy, 2003) and “access to training programs” (Ventres, 2017). The explained variance is 18.3%, and Cronbach alpha is 0.829. This causal condition highlights the role played by the new ecosystem and the means available to fill in the host community gaps.

  3. Cultural heritage (Cult_herit). This causal condition encapsulates four items: “the stereotypes about refugees”, “history and culture of the community of origin” (Mora and Davila, 2005; Glinka and Brzozowska, 2015; Irastorza and Peña-Legazkue, 2018), “culturally appropriate school transition” (Turney and Kao, 2009), and “traumatic experiences” (Turney and Kao, 2009; Kröger et al., 2016), with a total explained variance of 13.9% and a Cronbach’s alpha of 0.65. Migrants’ cultural heritage and their cultural background jointly with the inconsistency with the host community culture slow the integration process, making stressful mediation among individuals.

  4. Understandings of the host community (HCom_und). This causal condition includes the following questionnaire items: “understanding socio-economic and/or cultural barriers” (Ventres, 2017), “natural environment conditions of the host country” (El-Bialy and Mulay, 2015) and “knowing the language of the host country” (Portes and Clark, 1987), with a total explained variance of 13.2% and a Cronbach’s alpha of 0.682. It highlights the role of the new environment and its influence on the migrant’s integration process.

  5. Refugee character (R_C) emphasizes if migrants are coming or not from countries characterized by a high degree of conflict and war. This causal condition has a dichotomous character. We use value 1 for refugees – migrants coming from countries where there is still war (Afghanistan and Syria), and 0 for migrants coming from countries without war. Thus, as a crisp causal condition, its calibration is already done. This causal condition has profound implications for the malleability of migrants and refugees. Because they have a particular background, they tend to set connections with members who share the same experiences.

4.1.1 Output.

Once the five causal conditions are detailed, we continue to describe the measurement and calibration of the desired output, called EI. We use a Likert 1–5 scale following the scale designed by Liñán and Chen (2009) and Nowińskia and Haddoud (2019). It highlights the effort that a person will make to carry out EI. The output captures the motivational factors or antecedents describing EI. It relies on the following items: “I have very seriously thought of starting a firm”; “I have the firm intention to start a firm someday”; “I am determined to create a firm in the future”; “I will make every effort to start and run my firm”; “My professional goal is to become an entrepreneur”; “I am ready to do anything to be an entrepreneur”. Cronbach’s alpha is 0.941, showing the high reliability of the items that develop the construct.

4.2 Necessary conditions and truth table analyses

According to Schneider et al. (2010), the first step for assessing the causal conditions of the desired output is to test their necessity. Following Ragin (2008), a causal condition can be called “necessary” if the instances of the outcome constitute a subset of the instances of it. Consequently, a consistency score of 1 indicates that the combination of causal conditions meets the rule across all cases. There is a general agreement that a “necessary” or “almost always necessary” condition if its consistency score exceeds the threshold of 0.9. In that sense, we have analysed whether the five causal conditions, as well as their negations, are necessary for EI (see Table 1).

None of the five causal conditions, as well as their negations, reached 0.9, showing the inexistence of necessary conditions, leading us to the second step in fsQCA analysis: exploring causal complexity and equifinality. Table 2 reports the truth table analysis showing different causal combinations and associated frequencies both to EI (1 value) or not (0 value). We observe all 32 logically possible causal combinations for the high EI.

Sets of causal conditions are those that exceed an appropriate cut-off consistency score, assigning, in that case, a value of 1 in the raw of EI. The EI has been assigned a value of 0. Following Ragin (2008) and Fiss (2011), a cut-off value of 0.75 constitutes an acceptable threshold for exploratory studies. Table 2 shows the main findings in this sense.

At this stage, we observe a frequency of 22 cases belonging to eight configurations leading to high EI, exceeding the minimum consistency threshold of 0.75. Following fsQCA reasoning, the following step is to use Boolean algebra to reduce all possible logical combinations displayed in the truth table into more simplified combinations (Fiss, 2011). Thus, as Greckhamer et al. (2008) state, necessity and sufficiently should be investigated. For that purpose, we use the concept of quasi-sufficiency, based on several benchmarks depending on exploratory or more confirmatory research purposes (0.80 always sufficient; 0.65 usually sufficient) in causing our desired output: entrepreneurial orientation.

Table 3 includes both complex and intermediate solutions showing the performance of a Boolean algorithm used to find causal conditions and combinations in complex configurations sufficient to reach high EI. Following traditional fsQCA nomenclature (Fiss, 2011), we used the following Boolean operators: logical “and” (represented by *) means the intersection of sets. Logical “or” (represented by +) means the union of two sets – finally, logical “not” (represented by∼). We can appreciate five configurations (or sets of causal conditions) that are usually sufficient for high EI. One of the first implications of this analysis is the evidence of equifinality (González-Velasco et al., 2019). Instead of a unique and better way leading to EI, we can find in the intermediate solution five ways (configurations) of high EI.

Secondly, as reported in Table 3, solutions show an acceptable consistency value of 73% for exploratory studies (Ragin, 2008) and solution coverage of 72%. Putting the focus on the five causal configurations leading to EI, three of them are related to refugees, and the other two are related to regular migrants.

Refugees have three configurations leading to high levels of EI. Configuration 1 shows that with low levels of individual ability and adaptability and understanding of host country characteristics, refugees need personalized assistance and training. Less experienced refugees but with great flexibility and desire to succeed have a significant predisposition to start a business covering less attractive and uncovered domains (e.g. cleaning services, constructions), even if they do not have a deep understanding of the host communities. Less educated and less productive migrant entrepreneurs tend to launch a business in domains such as retail and service industries.

Alternatively, with high levels of individual ability and adaptability, refugees have two possibilities: (i) having high levels of assistance and training, jointly with a great understanding of host country characteristics (Configuration 4), or having low levels of assistance and training, low cultural heritage and limited understanding of host country (Configuration 5). Configuration 4 shows that skilled refugees determined to remain in the host country are more open to absorbing new knowledge, especially if they are assisted and have access to training. These essential premises will ensure a smooth transition to reach self-sustainability, capitalizing on valuable knowledge and expertise.

Configuration 5 leads to high EI once refugees have complex personal abilities and show adaptability even if they do not have access to professional support. Also, refugees exhibiting a low level of cultural heritage are more likely to embrace the host community’s distinctiveness. If cultural heritage has low importance for refugees, the gap between the two cultures is reduced, making the new context easier to accept.

Configuration 2 shows high levels of individual abilities and adaptability (Indiv_ab_ad) and deep understanding of the host country (Hcon_und), as well as low levels of cultural heritage (Cult_herit). This configuration emphasizes that talented migrants without cultural prejudices can manifest high EI. Moreover, understanding the socio-economic context of the new community and knowing the host’s language makes more natural wisdom about the new culture, setting the premises of an improved relationship with knowledge providers. Configuration 3 shows that migrants can reach high EI if the following variables are met: access to assistance and training (Ass_tr); insightful understanding of the host country (Hcon_und); low awareness of cultural heritage (Cult_herit).

This configuration underlines that having access to professional training and assistance while showing a willingness to comprehend the host country’s language barriers encourages EI. In the case of migrants, both configurations underline that cultural heritage should be low, reinforcing the idea that cultural heritage is a consistent variable in a migrant’s behavioural pattern to pursue an entrepreneurial activity.

4.3 Core and periphery condition analysis

Methodological advances introduced by Fiss (2011) enable to make distinction between core and periphery causal conditions, by comparing intermediate (Table 3) and parsimonious solutions (Table 4). Fiss (2011, p. 394) defines core condition as:

The causal conditions for which the evidence indicates a strong causal relationship with the outcome of interest and peripheral elements as those for which the evidence for a causal relationship with the outcome, is weaker.

To identify them, a core condition in the simplest solution, that is, the parsimonious one.

In this vein, and by comparing intermediate and parsimonious solutions, and following Fiss (2011) nomenclature, Table 5 shows core and periphery conditions of high levels of EI (black circles imply the presence of the causal variable, and large size implies core condition).

The preliminary analysis of core–periphery causal conditions highlights that core conditions appear only in Configurations 1, 4 and 5. Configuration 1 underlines two core conditions leading to high EI. There are high levels of assistance and training jointly with low levels of individual ability and adaptability, showing that even those refugees that are not skilled can become valuable resources through training and assistance. As an opposite configuration, number 5 highlights that the core condition “low assistance and training” can be completed by “high individual ability and adaptability” as a complementary core condition. Also, Configuration 4 remarks a refugee’s characteristics as a self-care condition leading to EI, jointly with the core role of assistance and training.

As Table 5 shows, Configurations 2 and 3 associated with regular migrant’s configurations do not contain any core causal conditions. This important finding reinforces one of our main theses, by highlighting the essential differences between refugees’ and migrants’ EI profiles.

4.4 Causal asymmetry analysis

Configurational analysis developed until now goes beyond traditional linear theories, towards a configurational approach with complex and non-linear relationships among constructs. We have tested the causal complexity associated with the EI phenomenon, going a step beyond the distinction between core and periphery conditions, as proposed by Fiss (2011). At this point, and extending the utility of configurational analysis (Ragin, 2008; Fiss, 2011; González-Velasco et al., 2019), we develop a causal asymmetry analysis demonstrating causal configurations leading to high EI may be quite different from those, leading to low EI. Table 6 summarizes causal asymmetry.

Six configurations are leading to a low EI, instead of five configurations leading to a high EI and the additional one is associated with the migrant’s profile. In the case of refugees, we have identified three configurations (1, 3 and 5) that lead to low EI. Configuration 1 shows low assistance and training (Ass_tr), low cultural heritage (Cult_herit) and low host community understanding (Hcon_und). This configuration highlights an apathetic profile without a desire to undertake entrepreneurial initiatives. This category of refugees might not have the predisposition to become entrepreneurs nor the determination to get involved in entrepreneurial initiatives. Configuration 3 has the following causal conditions: professional assistance and training (Ass_tr), low individual ability and adaptability (Indiv_ab_ad) and low understanding of the host country (Hcon_und). This category shows that refugees with low individual abilities and low levels of host country understanding, even if they have access to professional support due to the integration process, do not show a predisposition towards entrepreneurship. Skills possessed and the ability to implement them is a primary stimulus to entrepreneurship intention. Configuration 5 is made up of high individual ability and adaptability (Indiv_ab_ad), high assistance and training (Ass_tr) and host country understandings (Hcom_und), demonstrating that this group of refugees even if they have all conditions, they still have low entrepreneurship intention. They might consider other alternatives to support themselves as becoming employees or waiting for new opportunities to come.

In the case of regular migrants, with low EI, three configurations were identified (2, 4 and 6). Configuration 2 includes the following constructs: low assistance and training (Ass_tr), low cultural heritage (Cult_herit) and high host country understanding (Hcon_und). Even if migrants understand the host country’s conditions, manifest a low cultural heritage and do not have access to professional training and assistance, they have EI. Configuration 4 is made up of high individual ability and adaptability (Indiv_ab_ad), low assistance and training (Ass_tr) and high host community understanding (Hcon_und). This configuration shows that individual capability and adaptability, knowing the language, socio-economic and environmental conditions, is not enough to nurture EI, without adequate training and assistance. Configuration 6 includes a high individual ability (Indiv_cp_ad), high assistance and training (Ass_tr), high cultural heritage (Cult_herit) and a low host community understanding (Hcon_und). This configuration underlines that migrants with deep roots in their native culture, even if they have a high predisposition to evolve and access professional support, without understanding the implications of the new context still manifest low EI.

5. Discussions and theory development based on the results

Due to the inherent complexities and interrelated external and personal circumstances embodied in the human being, a configurational approach is convenient in the case of refugees’ and migrants’ entrepreneurship. Configurations enable a better understanding of complex phenomena, used in management and business research (Fiss, 2011; Wagemann et al., 2016; Misangyi et al., 2017; Woodside, 2017; González-Velasco et al., 2019). Our study underlines the factors driving migrants and refugees to become actively involved in host communities via entrepreneurship. The authors proposed a new configurational framework to understand refugees’ entrepreneurship profiles and EI, expanding in several ways the current knowledge on this phenomenon. From a theoretical point of view, it offers two new insights. Firstly, our proposal explores four main personal and contextual circumstances that explain migrants’ refugees’ EI profile. Secondly, and more importantly, we developed our theory and analysis in a new framework: a neo-configurational approach.

From an empirical point of view, our research indicates a causal complexity in migrants’ and refugees’ cases, leading to high EI. We obtained five main configurations: two related to migrants’ profiles and three related to refugees’ profiles. The high EI in both cases – of refugees and migrants – is associated with a low level of cultural heritage, stressing the importance of adjustment to the new context. In migrants’ case, an explanation of this result is the low identification with the origin country. Moreover, the experiences might be less traumatizing in the case of migrants compared to refugees, which explains the circumstances because the refugees usually are forced to leave their countries. In the case of refugees, in the absence of individual abilities and host community understanding, through customized training and assistance, improvements can be made. This result reinforces the perception that even low-skilled and less flexible refugees are likely to be stimulated towards entrepreneurship. Moreover, with a high determination to surpass cultural gaps, they are likely to succeed even if they do not have access to training and support.

In addition, to develop a more fine-grained analysis of causal complexity, a distinction between core and periphery analyses has been made, highlighting that (i) in the configurations of refugee profiles all the core causal conditions are embedded; and (ii) refugee’s status is, by itself, a core condition leading to high levels of EI.

Finally, we tested the causal asymmetry, confirming the pertinence of a configurational approach. Table 6 shows six configurations leading to low levels of EI, highlighting that individual abilities are not enough for EI. Even if migrants have access to professional training programmes, in the case of refugees, this variable is associated with low EI. Assistance and training are significantly relevant in association with EI. However, providing refugees with professional assistance services, and training only, is not enough to stimulate their EI. While in the case of migrants, only one configuration includes this variable and still leads to low EI. Many of these configurations leading to a low EI might be determined by the willingness of both categories – migrants and refugees – to perform a career as an employee, a follow-up that the authors will approach in their further studies.

6. Concluding remarks

Our study constitutes an original endeavour aimed at elucidating how refugee character (R_C) influences EIs, emphasizing the significant role of extreme violence in shaping Refugee EI. This research extends its applicability by presenting a methodology that facilitates the differentiation of groups through the identification of causal conditions leading to both high and low EI.

The factors under consideration were twofold:

  1. inherent in the respondent’s profile – variables intrinsic to the individual; and

  2. stemming from the external environment – market conditions, institutional support, infrastructure, cultural heritage and the cultural influence of the host community.

Configurations leading to high EI consistently indicate that cultural heritage (Cult_herit) must be low, reinforcing the notion that only individuals prepared to unlearn old practices can thrive in a new context. For migrants, this variable appears in both configurations, suggesting that migration often results from a lack of alignment with the originating culture. In contrast, for refugees, the cause lies in the absence of alternatives in the country of origin. In the case of refugees, deficiencies in individual abilities and flexibility, as well as a poor understanding of the host community, can be mitigated through tailored training and assistance.

Both refugees and migrants with high individual potential and flexibility are likely to succeed, even without access to formal training and assistance, as they can navigate cultural differences and adapt to new circumstances. A comparative analysis of configurations leading to low EI for refugees and migrants reveals several differences, indicating a causal asymmetry. For migrants, possessing skills and access to professional training/assistance is insufficient to activate EI, while for refugees, this variable is not associated with low EI. Moreover, all configurations involve the variable assistance and training (Ass_tr), indicating respondents’ awareness of the relevance of such interventions. However, in refugees’ cases, professional assistance and training (Ass_tr) are insufficient to stimulate EI, whereas in the case of migrants, only one configuration includes this variable and still leads to low EI. Despite the insights gained, our research has certain limitations. The cross-sectional nature impedes the exploration of robust causal relationships, while the use of perceptual scales and potential respondent bias related to English language knowledge pose limitations. A larger sample size could enhance the precision of conclusions. A significant gap in the literature on refugees makes it challenging to develop a robust theory. Nonetheless, we encourage further studies to investigate whether our conclusions are specific to the cultural context of the refugees and migrants we studied.

Comprehending the impact of migration on migrants and refugees in terms of their EIs and gaining practical insights to effectively address the challenges of integration in a sustainable manner are imperative for the development and management of effective support programmes.

Necessary conditions of EI

Condition tested Consistency Coverage
Outcome variable: EI
R_C 0.490 0.430
∼ R_C 0.507 0.478
Ind_ab_ad 0.799 0.632
∼Ind_ab_ad 0.634 0.673
Ass_tr 9.767 0.625
∼Ass_tr 0.610 0.623
Cult_herit 0.730 0.636
∼Cult_herit 0.746 0.705
Hcon_und 0.762 0.620
∼Hcon_und 0.606 0.621

Source: Table by authors

Truth table analysis

R_C Indiv_ab_ad Ass_tr Cult_herit Hcond_ind No.(%) EI RawConsis PriConsis
Minimum threshold: 2 cases
0 1 1 1 1 5 (10) 0 0.74 0.49
1 0 0 0 0 4 (19) 0 0.75 0.10
0 0 1 0 1 4 (27) 1 0.77 0.54
1 0 1 0 0 3 (34) 1 0.92 0.34
0 1 1 0 1 3 (40) 1 0.76 0.52
1 1 1 0 1 3 (46) 1 0.89 0.29
0 1 0 1 1 3 (53) 0 0.72 0.22
1 1 1 1 1 3 (59) 1 0.85 0.13
1 1 0 0 0 2 (63) 1 0.86 0.47
1 0 1 1 0 2 (68) 1 0.85 0.26
0 1 1 1 0 2 (72) 0 0.75 0.43
0 0 0 0 1 2 (76) 0 0.72 0.35
0 1 0 0 1 2 (80) 1 0.76 0.37

Source: Table by authors

Complex and intermediate solutions

ConfigurationRaw coverageUnique coverageConsistency
Frequency cut-off: 2/Consistency cut-off: 0.76
1) R_C*∼Indiv_ab_ad*Ass_tr*∼Hcon_und 0.255 0.060 0.820
2) ∼R_C*Indiv_ab_ad*∼Cult_herit*Hcon_und 0.288 0.033 0.757
3) ∼R_C*Ass_tr*∼M_cult_herit*Hcon_und 0.276 0.021 0.734
4) R_C*Indiv_ab_ad*Ass_tr*Hcon_und 0.242 0.086 0.742
5) R_Stat*Indiv_ab_ad*∼Ass_tr*∼Cult_herit*∼Hcon_und 0.247 0.055 0.863

Solution coverage = 0.72; solution consistency = 0.73

Source: Table by authors

Parsimonious solution

Configuration Raw coverage Unique coverage Consistency
Frequency cut-off: 2/Consistency cut-off: 0.76
Indiv_cp_ad*∼Cult_herit 0.651 0.175 0.799
∼Indiv_cp_ad*Ass_tr 0.523 0.032 0.763
R_C*Ass_tr 0.357 0.005 0.630

Solution coverage = 0.77; Solution consistency = 0.67

Source: Table by authors

Core and periphery conditions

Causal conditions High EI
1 2 3 4 5
Raw coverage 0.255 0.288 0.276 0.242 0.247
Unique coverage 0.060 0.033 0.021 0.086 0.055
Consistency 0.820 0.757 0.086 0.742 0.863

Solution coverage = 0.72; solution consistency = 0.73

Source: Table by authors

Complex and intermediate solutions for low levels of EI

ConfigurationRaw coverageUnique coverageConsistency
Frequency cut-off: 2
Consistency cut-off: 0.81
1) R_C*∼Ass_tr*∼Cult_herit*∼Hcon_und 0.273 0.101 0.867
2) ∼R_C*∼Ass_tr*∼cult_herit*Hcon_und 0.187 0.015 0.840
3) R_C*Ass_tr*∼Ind_cp_ad*∼Hcon_und 0.235 0.045 0.913
4) ∼R_C*Indiv_ab_ad*∼Ass_tr*Hcon_und 0.217 0.036 0.837
5) R_C*Indiv_ab_ad*Ass_tr*Hcon_und 0.235 0.096 0.870
6) ∼R_C*Indiv_cp_ad*Ass_tr*Cult_herit*∼Hcon_und 0.176 0.048 0.810

Solution coverage = 0.72; solution consistency = 0.82

Source: Table by authors


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The authors express their gratitude to the organizations that facilitated the data collection process, thereby contributing to the realization of this research endeavor.

Corresponding author

Catalina Crisan-Mitra is the corresponding author and can be contacted at:

About the authors

Catalina Crisan-Mitra is Associate Professor at the Department of Management, the Faculty of Economics and Business Administration, Babeş-Bolyai University, Romania. Her main research fields of interests are entrepreneurship, social entrepreneurship and corporate social responsibility. Her current work explores the impact of Covid-19 on digital innovation and on digital entrepreneurs and how social innovations lead to legitimation in social enterprises. In 2021, she obtained a Fulbright Grant for Research and Academic Training in the field of Entrepreneurship and Entrepreneurial Studies, at University of Rochester, New York, USA. Her latest articles were focused on digital innovation and were published in Journal of International Management and Technological Forecasting and Social Change. She is also the Operational Coordinator of UBB-Student i-Lab, a structure that provides professional support to students to develop their business concepts.

Gregorio Martín-de Castro is Professor of Strategy and Business Sustainability at the Department of Management and Marketing, the Faculty of Economics and Business Administration, Complutense University of Madrid, Spain, and since 2000 he is teaching courses at undergraduate, master and PhD levels. His main research fields of interest are a strategy, sustainable development, knowledge management and intellectual capital. He is author and co-author of 9 books and over 50 research papers in leading journals such as Journal of Cleaner Production, Technovation and Journal of Business Ethics. He has been visiting scholar in different universities as Harvard University, University of Manchester, University of Southern California, University of California Los Angeles (UCLA) or University of Edinburgh.

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