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Abstract

This article examines the main determinants for entrepreneurial activities among return migrants in a regional context within Romania. The analytical framework is based on conceptual tools provided by the intersection of entrepreneurship theory and return migration research. The study aimed to answer a set of research questions regarding migrant individuals’ probability for entrepreneurial careers upon return, and Romania constitutes a fertile European origin country for testing them. Returnees are perceived as one of the main transformational forces within the country, and great expectations are related to their entrepreneurial orientation. We test this general assumption using survey data collected from 840 returnees and several logistic regression models which included variables about employment status before the individuals’ first migration, country of destination, length of stay abroad, return reasons, use of savings, and sociodemographics. Individuals’ characteristics as well as features of the migration experiences were found to be highly relevant for predicting the chances of migrants entering into entrepreneurship upon return.

Keywords

international migration return migration entrepreneurship employment status Romanian migration

Introduction

Great expectations are cast upon return migration’s transformative effects within most origin countries. Romania is no exception and return migrants are perceived as transformational agents (Sandu, 2010c; Vlase, 2013a, 2013b), with their entrepreneurial orientation being one of the key expectations related to their role upon return (Anghel & Cosciug, 2018; Shima, 2010). Building on a theoretical framework articulated at the crossroads of entrepreneurship research and migration literature, our study explores the main predictors of entrepreneurship in the case of Romanian returnees in a specific regional context.

Romanians’ temporary migration to other European Union (EU) destinations is often presented as a strategic behavior to overcome problems in the origin country (Anghel & Cosciug, 2018; Potot, 2010; Sandu, 2010a), mainly through the accumulation of economic, human, and social forms of capital (Sandu, 2010c). Along with other Central and Eastern European (CEE) countries, Romania has become an important origin country in terms of intra-European migration, and more than three million Romanians are officially registered as residents in other EU countries (Eurostat, 2018). This is a heterogeneous phenomenon in terms of emigration motivations, countries of destination, and the period spent abroad (Anghel et al., 2016; Sandu et al., 2018).

As a consequence of rising migration, Romanians’ return migration and its effects have begun to enter the migration research agenda, whereas the Romanian government has recently started to implement policies oriented toward attracting migrants to come back home (mainly through business-fostering mechanisms). However, there is a paucity of literature that provides empirical-based knowledge about the migrants who return in this new context of increased intra-European mobility. Our study aims to contribute to the better understanding of returnees’ probability to enter into entrepreneurship using a quantitative methodology and data collected in a regional sample conducted among Romanian returnees. It provides novel knowledge in the field of return migration and entrepreneurship and reveals several key features of the returnees who fulfill the “great expectations” of becoming entrepreneurs upon return.

This article is presented in the following structure: The first section outlines a theoretical understanding of entrepreneurship with a special focus on return migrants. The second part offers the main relevant details about Romania’s return migration and the regional context where the data were collected. These are followed by a third section with a detailed depiction of the methodological design, definitions for each variable included in the study, as well as the main research questions. The fourth section comprises the data analyses and the results, presents the main characteristics of the sample, and outlines the logistic regression models for answering to article’s research questions. The final section presents the key conclusions of this article.

Literature Review

The Schumpeterian legacy is still present in numerous contemporary studies in the field of entrepreneurship (Block et al., 2017; Swedberg, 2002). Within the context of this classical legacy (e.g., Schumpeter, 1934/2008), individual entrepreneurs are perceived as risk-takers who are eager to create market opportunities and who impact economic and social systems through their innovative actions. Nowadays, the term of entrepreneurs is used for labeling a heterogeneous population which includes individuals with different motivations for starting businesses (Jayawarna et al., 2013; Shane et al., 2012), people who use various resources for enterprising (economic, human, or social capitals are privileged topics in the study of the entrepreneurial activity) in market contexts characterized by specific structural features (Bosma & Kelley, 2019). We use a broad definition of entrepreneurship where self-employed individuals and employers are expected to have a mixture of similarities which can be contrasted to other categories of employment. Self-employment is understood as a simplified form of entrepreneurship as it requires the use of resources and assuming an independent work status associated with certain economic risks (Startienė et al., 2010; Szarucki et al., 2016). We acknowledge that some differences can be found between self-employed individuals and employers and this requires some cautiousness in interpreting the findings of the article (Østergaard, 2019; Piracha & Vadean, 2010).

In spite of the high complexity embedded in the migration–development nexus, there is a solid body of literature that emphasizes return migration’s positive effects on origin countries. The advance of entrepreneurship is one of the lines of inquiry, and returnees’ higher propensity toward entrepreneurship has been noted in different geographical settings (Batista et al., 2014; Dustmann & Kirchkamp, 2002; Piracha & Vadean, 2010; Reiner & Radu, 2012). Numerous empirical studies on the relationship between return migration and entrepreneurship have been conducted in terms of economic capital accumulation (Anghel & Cosciug, 2018; Diatta & Mbow, 1999; McCormick & Wahba, 2001; Schulte, 2008), returnees’ increased work-related skills and their improved stocks of knowledge (Ammassari, 2004; Liu et al., 2010; McCormick & Wahba, 2001; Williams, 2007), as well as their capacity to develop transnational social networks (Anghel & Cosciug, 2018; Cassarino, 2000; Levitt & Schiller, 2004; Mayer et al., 2015; Sinatti, 2015a). Some authors have found evidence concerning the axiological transformations through migration, pointing out that returnees augmented their entrepreneurial spirit during migration, and that this can be implemented in the return context (e.g., Sabar & Pagis, 2015). Others have pointed out that origin countries’ governments should focus on creating fertile business grounds for allowing returnees to invest their savings and skills gained abroad (e.g., Cantore & Cali, 2015). All these approaches to return migration point out several competitive advantages obtained by returnees compared with nonmigrants. Their desire to start businesses after return along with the capacity to mobilize various resources is embedded in their opportunity-driven entrepreneurship. One’s expectations from returnees’ entrepreneurship have to be moderate; otherwise, we can speak about the “naïve optimism” emphasized by De Haas (2010). Similarly, Black et al. (2003) stated that it is not reasonable to expect that all return migrants turn into Schumpeterian entrepreneurs even if they can assume a role in the economic growth of the origin countries. Only the returnees with specific profiles will contribute through entrepreneurship to the economic growth and social transformation of the origin societies (Dustmann & Kirchkamp, 2002; Piracha & Vadean, 2010).

Framed by a nonorthodox theoretical tradition, necessity-driven entrepreneurship places an emphasis on structural characteristics that determine individuals to enter into entrepreneurship (Block & Wagner, 2010; Deli, 2011; Fairlie & Fossen, 2018; Maritz, 2004; Williams, 2009). Entering into entrepreneurship is a decision adopted after all others labor market opportunities have been found unsatisfactory or if employment options were unavailable for particular individuals (Valliere & Peterson, 2009). The term has gained importance and it is used as an alternative explanation for understanding small-scale entrepreneurs who did not possess the required capital for starting a business but were determined to enter into this occupational trajectory. Among the return migrants, we expect that necessity entrepreneurs did not have a plan to start a business at the moment of their return and they had reduced capacity to invest economic resources gained during migration. As a proxy for identifying opportunity and necessity entrepreneurs, we will look at self-assessed return motivation (return decision based on economic accumulation vs. return based on other motivations) and the use of savings resulted from the migratory experience (the use of savings for lucrative investments is a feature of the opportunity entrepreneurs, whereas the use of savings for various types of consumption is a characteristic of necessity entrepreneurs). At the same time, this cluster of literature is important for our study because it emphasizes that the level of economic development and labor market’ characteristics from the return area should be considered when we analyze returnees’ decision to become entrepreneurs.

Several studies with a special focus on work reintegration upon return were conducted within CEE countries (Co et al., 2000; Piracha & Vadean, 2010; Reiner & Radu, 2012). Scholarship in this area revealed significant differences concerning returnees’ employment choices, earnings premium compared with nonmigrants, as well as gender-biased effects of the migratory experience. However, in relation to our own research objective, one can mention also serious limits of these studies: For example, the data set used by Co et al. (2000) was relevant for Hungarian migration during the early phase of transition to free market; Piracha and Vadean’s (2010) study on men returnees was conducted within a labor market context (Albania) with structural determinants for self-employment as a survival strategy; Reiner and Radu (2012) tested their theoretical assumptions on a population of recent returnees (first year after arrival). For discussing challenges of the return process, Cassarino (2004) pointed out that migrants’ “preparedness” to return affects their reintegration into the labor market of the origin country and their propensity toward entrepreneurship. All these constituted key incentives to focus our study on returnees’ entrepreneurship in a Romanian context reconfigured through the EU enlargement and the reduction of barriers and costs for intra-European mobility (Marcu, 2016).

One of the challenges in studying the entrepreneurship of returnees is the selectivity of both entrepreneurship and migration (Ambrosini et al., 2011; Batista et al., 2017; Wahba, 2015). Migrants are self-selected at the moment of emigration and at the moment of return, just as self-selectedness marks entrepreneurship as well. This influenced our decision to work on a sample which included only returnees which were already self-selected at the time of emigration and return. Prior research distinguished between those returnees who had entrepreneurial experiences before migration and those who entered into entrepreneurship only after return (Dustmann & Kirchkamp, 2002; McCormick & Wahba, 2001). Similar evidence in this regard can be derived from the research centered on habitual entrepreneurs (Ucbasaran et al., 2003, 2008) which pointed out psychological traits which make people who had entrepreneurial experiences have increased probability to start businesses even if they had another employment status for a period of time.

Individuals’ stocks of human and cultural capital are important in analyzing their work prospects and directly affect their probability for entering into entrepreneurship (Jayawarna et al., 2014). The accumulation of human capital is a complex mixture which includes formal education and processes of learning which are socially embedded (Jayawarna et al., 2014; Williams, 2006). It is widely accepted that human capital is an important analytical dimension in the study of entrepreneurship (Marvel et al., 2016), and specific categories of migrants can transfer knowledge and skills across borders (A. M. Williams, 2007; for Polish returnees, Klagge & Klein-Hitpaß, 2010; for Romanian returnees, Ambrosini et al., 2011). On one hand, the relationship between one’s human capital and his or her probability to enter into entrepreneurship is expected to be relevant for the general population and not only for migrants. On the other hand, for migrants, this is an argument for paying attention to several features of the migratory experience because during migration individuals are exposed to different economic, cultural, and social values (Voicu & Vasile, 2014).

The idea that economic growth through entrepreneurship is expected from some returnees is part of a broader trend in which origin countries assume roles in managing migration and return flows (Østergaard-Nielsen, 2003). Motivated by a complex group of factors linked to economic development, origin countries are interested in specific categories of returnees (Sinatti, 2015b). Several CEE countries have started to discuss return migration and its implications more frequently (Lesińska, 2013; Zareva, 2018) and Romania authorities are also paying more attention to the potential associated with return migration even if their attitude toward implementing real measures for attracting migrants back home was quite hesitant for two decades (Șerban, 2015).

The reintegration process raises serious challenges for returnees in postcommunist CEE countries which are EU members where reentering into a migratory pathway is rather simple compared with other flows of migration. For understanding returnees’ reintegration and their potential to enter into entrepreneurship, research has to pay attention to their level of preparedness for return and to their return motivations (Cassarino, 2004). Quantitative and qualitative studies among intra-European migrants pointed out that home orientation and the return decision-making are relevant components of the general discussion of the return migration (e.g., Anghel & Cosciug, 2018; Sandu, 2010b). Furthermore, White’s (2013) study documented that many Polish return migrants are not committed to settle at origin and their decisions are dependent on the labor opportunities from the regional context. Failure in return transforms remigrated individuals’ experiences at destination and makes them more inclined to settle in the United Kingdom. Coniglio and Brzozowski (2018) use a conceptual distinction between “bitter return” and “sweet return” and show that structural determinants as well as individuals’ characteristics (human capital included) are important factors in explaining the chances of reintegration even in conditions of low preparedness for return.

Overview of Romanian Return Migration and the Regional Context

Romania is an Eastern European country, and its migration is part of the broader East–West migration phenomenon (Black et al., 2010; Favell, 2008; King & Okólski, 2018). Its communist past as well as the prolonged transition toward democracy and capitalism has drastically affected the quality of life and the structure of labor opportunity for its citizens (Voicu, 2005). The negative economic effects of the transition process were noticeably all over the country, but some Western and Central regions recovered faster compared with Eastern and Southern parts of the country. The number of Romanians who live abroad has consistently increased over the last three decades and also many Romanians lived abroad for a while and have now returned to the origin country (in 2017, more than 3.2 million Romanian citizens were officially registered as residents in other EU countries). Hitherto, there have been no accurate official statistics on Romanian return migration and this is an important issue in designing representative sampling for the return population. Furthermore, since 2007, when Romania became an EU member state, the circularity between origin and destinations has increased, and more fluid forms of migration have been developed (Engbersen & Snel, 2013). Germany, Italy, and Spain are still the traditional destinations for Romanians, but a new series of other European destinations emerged during the last decade (UK, Scandinavian countries, the Netherlands, etc.). The demarcation line between temporary and permanent return is difficult to draw in a context of high circularity and a conceptual shift of return (Engbersen & Snel, 2013; Lesińska, 2013; White, 2013; for Romanian returnees, Anghel & Cosciug, 2018). Neither emigration, nor return is a homogeneous phenomenon and this is highly relevant for the purpose of this study which aims to contribute to a better understanding of the individual predictors for entrepreneurship among returnees. The Romanian population of returnees includes people with diverse economic, social, and demographic characteristics and their experiences of migration have particular features.

Romanian returnees’ entrepreneurship is underresearched, and only a few studies discussed employment choices after return (Author, 2018; Reiner & Radu, 2012; Shima, 2010). Return migration in Romania has been analyzed mainly through qualitative field studies. These have focused on how the migration experience changes individuals’ values (Vlase, 2013a, 2013b), the use of money gained abroad for locative investments (Larionescu, 2012), effects of migration on ethnic relations in multiethnic origin localities (Anghel, 2016), as well as the influence of migration on individuals’ work trajectories (Author, 2018). Umbres (2014) illustrated the struggle of returnee entrepreneurs in the niche of construction market, emphasizing the neoliberal transformation of the return context, and paying attention to the modality in which individuals’ social circle of reintegration interferes with business development. Anghel and Cosciug (2018) identified transnational entrepreneurs who pendulated between Romanian and other EU countries, as well as return migrant entrepreneurs who started businesses using savings and human capital resulted from the migratory experience. From a life-course perspective, XXX and Author (2019) unpacked returnees’ self-employment experiences upon a long period spent abroad and pointed out the importance of individuals’ habitus in relation to their families’ social class of origin and educational background. Using a quantitative approach, our article will verify, in a regional context, some of the qualitative insights regarding returnees’ characteristics and will explore the relevance of several features of the migratory experience.

In Romania, previous research has revealed higher earnings for entrepreneurs compared with full-time employees (Stoica, 2012) and this is accompanied by a vigorous neoliberalism in which mobility and entrepreneurship were promoted by governmental rhetoric (Chelcea & Druţă, 2016). As we have already mentioned, the migratory experience is often presented as having positive effects for active returnees in the labor market (for example, wage premium). Furthermore, improved skills and foreign language proficiency can assure better employment opportunities upon return (Piracha & Vadean, 2010; Williams, 2007) and allow some returnees to be more selective in the process of engaging in employment (qualitative evidence from Poland were provided by Klagge and Klein-Hitpaß, 2010). Within this complex mixture, both migration and entrepreneurship are perceived as mechanisms for improving one’s socioeconomic status.

Romanian government interest in supporting returnees’ entrepreneurship is rather new. Studying the legislative measures adopted by the Romanian authorities for dealing with the challenge of migration, Şerban (2015) pointed out a low level of consistency in dealing with emigration, diaspora, and return. In addition, the Romanian authorities’ interest in this area was sporadic, and only one measure was adopted for supporting voluntary return in a context of higher demand for labor. The measure was adopted in 2008, but in the context of the global economic crises it ceased to exist. The idea was recently renewed, but with the focus shifted toward entrepreneurship (e.g., Diaspora Start-Up Programme, 2017).

To sum up, Romania provides one of the main intra-European flows of migration. Economic motivations are central to its understanding, and a significant part of these migration experiences are designed as temporary stays abroad for instrumental reasons. Romanians’ return migration is a new component of the migration scholars’ research agenda, and there is little empirical evidence (mainly qualitative) about the profile of people who enter into entrepreneurship upon return.

The Regional Context

The data collection was concentrated in the central part of Romania and included returnees who were residents at the moment of the study in one of the following six counties: Sibiu, Brasov, Mures, Alba, Valcea, and Hunedoara. Two main arguments stand for the value of this regional concentration in the study of return migration in Romania.

First, in spite of their geographical proximity, these six counties register different levels of economic and social development (Ionescu-Heroiu et al., 2013; Sandu, 2011). Two of these counties, Sibiu and Brasov, are among the highly developed Romanian counties, whereas the other four counties have an average level of development. None of these four counties is among the underdeveloped parts of Romania, but the gap between the developed ones and the others allows us to differentiate between two distinct categories of labor market contexts within this regional framework. Sibiu and Brasov occupy top positions in the hierarchy of gross domestic product (GDP) per capita, net earnings and record low unemployment rates. All these factors made them attractive for internal migrants and both of them score high in the net settling of domicile. Only a few Romanian counties succeeded to attract internal migrants for increasing their number of residents after 2007 when Romania became part of the EU and external migration increased considerably. The second category includes counties which have an average performance regarding their level of development during the period of time covered by this study. It is characterized by middling values within the national context and an important decrease in the resident population (Table 1).

Table 1.

Economic and Social Development Within the Regional Context.

Type of return context	Indicator	Net earnings^a	GDP per capita^a	Unemployment rate^a	Net settling of domicile^a	Evolution of the county’s population^b
Type of return context	County	Net earnings^a	GDP per capita^a	Unemployment rate^a	Net settling of domicile^a	Evolution of the county’s population^b
Highly developed counties	Sibiu	6	6	7	5	+10,890
Highly developed counties	Brasov	7	5	9	6	+11,160
Counties with an average level of development	Mures	11	15	15	12	−11,696
	Alba	15	9	19	17	−17,029
	Valcea	33	19	17	30	−18,856
	Hunedoara	28	18	24	37	−40,611

Source. National Institute of Statistics (2018).

Note. GDP = gross domestic product.

The number included in the column reveals the county’s average position between 2015 and 2018 in the hierarchy of the Romanian counties (41 counties; Bucharest as a capital city was excluded due to its high specificity).

The last column presents the increase or the reduction in county’s total population between 2007 and 2018.

Additional evidences about similarities between the labor market in Sibiu and Brasov are provided by Cristea et al. (2017). Using a series of official statistics, they pointed out several characteristics of these Romanian “magnet cities” and the “functional urban zones” which were developed mainly through foreign investments in the reindustrialization of the area after the collapse of the former communist industrial facilities. This new economic reality requires mainly skilled workers with proper technical training and willingness to work. The Romanian educational system has a consolidate tradition in vocational and technical education (Malamud & Pop-Eleches, 2010), even if during the transition period this was seriously challenged by a long series of chaotic reforms. This category of people registers a lower number of completed years of education because the core of the vocational and technical education offers limited access to higher educational programs (Florian & Țoc, 2018). Coniglio and Brzozowski (2018) found a lower successful rate of reintegration for Polish returnees with vocational training compared with those with tertiary education. However, in this regional context, they can easily find jobs and we expect individuals’ chances to enter into entrepreneurship to be affected and individuals who graduated vocational or technical programs to be rather in wage employment. At the same time, the development of the functional urban zones mentioned above offers labor opportunities for residents in some rural areas and this makes problematic the use of a simple dichotomy between rural and urban residential areas.

A second argument for concentrating the research in this regional context is provided by the fact that emigration from this region is oriented toward multiple destinations compared with other Romanian regions which are highly connected to a dominant destination (e.g., the North-East is oriented mainly toward Italy, and the South-Muntenia which is dominated by Spain; Sandu, 2010a). This regional specificity is useful for exploring the impact of the country of destination on individuals’ employment choices upon return to Romania because it provides consistent subsamples of returnees who lived in three main destination countries (Germany, Italy, Spain).

Method

Data Collection

The data were collected in four waves of a regional research project conducted between 2015 and 2018.¹ The main focus of the research was linked to the exploration of the return migration in the central region of Romania (see Figure 1 and Table 2). The data collection process was the result of collaborative work between students and research staff in the sociology department of Lucian Blaga University of Sibiu. The face-to-face questionnaires were filled in by interviewers who used their social networks for identifying “seeds” (return migrants) and the data collection progressed on a snowballing technique. The entire team of interviewers was changed in each year and this allowed us to annually update the set of “seeds” for starting the fieldwork and to identify a relatively large number of returnees. At the same time, this strategy covered a broad regional area and assured constant control over the quality of the data (the author of this article organized the trainings, provided support for data collection, and directly supervised this process). The purposing sampling focused on returnees generated a total sample of 1,020 individuals who cumulatively satisfied the following conditions: (a) They were adults at the moment of the survey; (b) they spent at least three consecutive months abroad; and (c) they cumulated minimum 3 months after they return to Romania. In direct relation with the research objectives assumed in this article, we adopted the following methodological decisions which affected the size and composition of the sample. First, we maintained in the sample only those returnees who were residents in the regional context presented in the previous section because for other counties we had only a few respondents. Second, in the analyses were included only individuals who were adults at the moment of return because only for them entering into entrepreneurship was a potential employment option. Third, we excluded individuals who were already in retirement at the moment of the survey because we did not have other information about their employment status upon return. The resulted sample included 842 return migrants.

Figure 1.

The map of Romania (the regional context for this study is highlighted).

Table 2.

Descriptive Statistics for the Sample of Romanian Returnees Included in the Study.

Descriptive statistics
(DV) Employment status at the moment of the survey	Full-time employment	Part-time employment	Entrepreneurship/self-employment	Unemployment	Looking after the home or family	In education	Total
	67%	4%	6%	4%	11%	8%	100%
Country of destination	Germany	Italy	Spain	Total
	52%	26%	22%	100%
County of residence upon return	Highly developed economic context		Average level of economic development				Total
	Sibiu	Brasov	Valcea	Hunedoara	Alba	Mures
	57%	7%	22%	6%	4%	4%	100%
Dichotomous variables
	Yes	No	Total
Male	51%	49%	100%
Youth at last return (≤35 years)	65%	35%	100%
Entrepreneurship before migration	3%	97%	100%
Return motivation based on accumulation	27%	73%	100%
Lucrative investment with savings from migration	5%	95%	100%
Nontertiary technical or vocational education	26%	74%	100%
Level of education (categories)	Primary or lower secondary	Upper secondary (high school diploma)	Tertiary	Total	Number of completed years of education:Mean value: 13.12 years and Median value: 12 yearsNote: In the logistic regression model, the number of completed years of education was used for measuring individuals’ human capital. These categories are provided for a general image on the sample.
	28%	45%	27%	100%
Length of the period spent abroad	Mean value: 31 months		Median value: 14 months

Note. The percentages included in the table were reported for a total of 842 returnees (except the country of destination with a reference value of 448 because returnees from other destinations than those mentioned in the table and returned migrants who lived in two or more distinct destinations were excluded). DV = dependent variable.

The quantitative approach in which this study was built and the type of available information influenced our decision to use logistic regression models for analyzing which are the main predictors for entrepreneurship. We selected a particular type of logistic regression model (Firth-corrected binomial logistic model) because this is suitable for analyzing rare events² and the percentage of entrepreneurs within our sample was rather low. This type of logistic regression was used in other studies conducted on migrant population (e.g., Stanek & Hosnedlová, 2012; Szarucki et al., 2016). One of the main advantages provided by the logistic regression models is the possibility to include in the analytical model predictors which were validated by prior research along with a new set of predictors proposed by our study on Romanian returnees.

Several limits should be mentioned before proceeding to the data analyses. The questionnaire did not include questions for allowing us to differentiate between return migrants who benefited from a return mechanism (if any) and those who were not part benefited from such governmental programs. At the same time, the lack of information about the employment status hold during migration or about the accumulation of human and/or social capital during migration did not allow us to introduce these factors in explaining migrants’ employment decisions adopted upon return. Further research should include returnees’ motivations for starting businesses for clearly distinguishing between opportunity- and necessity-driven entrepreneurship. Finally, the lack of accurate statistical data concerning return migration and the dynamic nature of the phenomenon constitute serious barriers for obtaining a representative sample of Romanian returnees. Hitherto, we have not had knowledge of any survey focused on Romanian return migration that has employed a representative sample of returnees.

Discussion on the Variables Included in the Analyses

The variables included in the analytical models offer relevant information about the period before migration, during migration, and the period upon return. Part of them were derived from the literature review, and others are used for extending the knowledge on this topic.

Dependent variable

Entrepreneurship was based on individual, self-assessed, main occupational status at the time of the study, and it was codified as a dichotomous variable, using the values of 1 = entrepreneur and 0 = other employment status than entrepreneur. Measured in this simple modality, the variable is useful mainly for identifying those individuals who register an independent employment status at the moment of the survey and to contrast them to individuals who hold positions of employees or have the potential to be active on the labor market (adults who are enrolled in education, unemployment, or people who were looking after the home or family).

Independent variables

Migratory experience

Migratory experience was defined as a stay abroad for at least three uninterrupted months. Returnees were those migrants who were living in Romania at the time of the study for a similar period of minimum three consecutive months. This was the single selection criterion used for evaluating the eligibility of subjects for being interviewed in this regional study.

Occupational status before migration

The respondents were asked about the main occupational status before their first migration, and the information was collected at the time of the study (these were the only two specific periods of time for which the information was registered in the questionnaire). In the analytical model, we used a dichotomous variable for distinguishing between those who had entrepreneurial status before migration and those who did not. This variable mirrors the modality in which the dependent variable (DV) was measured. Using findings from the literature (Dustmann & Kirchkamp, 2002; McCormick & Wahba, 2001; Ucbasaran et al., 2003), we expected to find a positive significant relationship between this predictor and the DV and people who had this employment status before their first migratory experience to have higher probability of being entrepreneurs upon return.

Length of the migratory experience

This was measured as the total number of months spent abroad. Some studies argue that this variable can be used as a proxy for various types of capital accumulation during migration (Dustmann & Kirchkamp, 2002; McCormick & Wahba, 2001). There is an optimal duration of migration and theoretical models, and also empirical findings emphasized its influence on individuals’ occupational choice after return (Dustmann & Kirchkamp, 2002; Stark et al., 1997). At the same time, this can be used also as a control variable for discussing about migrants’ exposure to economic, cultural, and social contexts from various destination countries. Migrants who return only at the age of retirement have substantially lower chances to be entrepreneurs. Based on these aspects, we excluded from our sample respondents already retired from work and we expect to find a positive significant relationship between the length of the migratory experience and the log odds of engaging into entrepreneurship upon return.

Self-assessed return reasons

Self-assessed return reasons were assessed using an established advance list of possible motivations for return. The respondent had the possibility to select one or multiple answer(s) and we post-coded their answers into a dichotomous variable: return motivation based on accumulation (“I thought that what I have accumulated abroad gives me a decent living in Romania” and/or “The desire to start a business in Romania”) versus any other motivations for return. Our focus was on return decisions and, considering classical insights concerning the variety of return reasons (Cerase, 1974), we were mainly interested in identifying those migrants who self-assessed that they accumulated enough economic capital abroad and/or they desired to invest in the origin country. For this category of people who adopted their decision to return on accumulation, we expect to find a higher degree of “resource mobilization” and “preparedness” for establishing businesses in the origin context (Cassarino, 2004). Two other factors affected our decision to introduce the return motivation linked to the idea of investing in the home country in the list of predictors. First, scholars in entrepreneurship emphasized the long and sinuous path from the idea to start a business to the moment of actually assuming this employment status (e.g., Dimov, 2007). Second, numerous necessity entrepreneurs are determined to assume this work status without prior planification (Block & Wagner, 2010; Deli, 2011; Fairlie & Fossen, 2018; Maritz, 2004; Williams, 2009). A positive relationship is expected if the returnees have a profile linked to the opportunity-driven entrepreneurship, whereas a negative relationship can be an indicator of the necessity-driven entrepreneurship. However, cautiousness is required in interpreting the results in this logic because the survey did not collect data about motivations for entrepreneurship and further research should validate the insights provided by our analytical model.

The use of savings gained abroad

Other empirical studies have noted the importance of financial accumulation in starting businesses upon return (e.g., Dustmann & Kirchkamp, 2002). In this context, we were interested in exploring the relationship between the use of savings and an entrepreneurial career upon return. We collected information about the use of savings gained abroad and post-coded all the answers in the following two categories: lucrative investment versus the use of savings for other purposes. The presence of lucrative investment was labeled with the value of 1 and the absence with the value of 0.

Human capital

The use of individuals’ human capital is highly dependent of economic, cultural, and social contexts and scholars focused on migration contributed to a better understanding of the complex relationship between physical mobility and the use of skills and knowledge (A. M. Williams, 2006). The data available for our study offer the possibility to introduce two variables into the analytical model (number of completed years of education and type of education). The relationship between the returnees’ level of education and their tendency for entering into entrepreneurship provided contradictory evidences in different geographical settings (for example, Dustmann and Kirchkamp, 2002, found a positive relationship, whereas Reiner and Radu, 2012, found a negative relationship between these variables). This is an argument for controlling the number of completed years of education, but the regional context presented above requires also differentiating between types of human capital. The observations were collected within a regional labor market characterized by a high demand for workers with vocational and technical skills. Building on this fact, we aim to explore if the presence of nontertiary technical or vocational education negatively affects individuals’ probability to be entrepreneurs. These are arguments for interpreting the results in relation to the regional context and to be cautious in extrapolating these results to the national labor market of the origin country. The number of completed years of education is a numerical variable, whereas graduates of vocational and technical education were labeled using a dichotomous variable (vocational and technical education = 1 and other type of education= 0).

Gender

In a similar fashion to other research on entrepreneurship, we expected to see significant differences between the probability of men and women for being entrepreneurs. General literature on entrepreneurship has shown that men have higher chances of entering into entrepreneurship based on cultural representations of men’s higher propensity to take risks and to be competitive and aggressive, attributes that are highly correlated with the reification of entrepreneurship (Ogbor, 2000). Furthermore, Vlase (2018) illustrated with recent qualitative evidence the relationship between masculinity and entrepreneurial profiles among Romanian returnees.

Age

We introduced in the final sample only those returnees who were adult at the moment of last return and this variable was measured in years at the age of return.

Country of destination

In spite of the fact that Romanian migration is oriented (almost entirely) toward EU destinations, there are important arguments for exploring the destination’s effect on individuals’ employment decisions after return. First, we anticipated an effect of self-selection linked to the emigration process. Sandu et al. (2018) showed how the selection of a destination country among Romanian migrants is a complex process that includes individuals’ features and social networks, as well as an important regional component. In addition, Polavieja et al. (2018) compared Romanian migrants into Spain with those from other rich European Economic Area (EEA) countries³ and found evidence that Romanians from Spain were negatively self-selected regarding motivational register (e.g., ambition, achievement orientation, money drive, and risk orientation). This is highly relevant for understanding the fact that Romanian migrant population is heterogeneous and people with different qualities migrated toward specific destinations. Second, Voicu and Vasile (2014) documented that migrants’ evaluations of life satisfaction are a mixture of cultural aspects from the origin and destination countries. They found evidences that the host countries’ social norms are internalized by immigrants and became part of the explanatory model for the individuals’ attitudes and behaviors. During the time spent in the host country, the immigrants are exposed to different economic, cultural, and social factors. The scholarship focused on social remittances emphasizes that some of these new values are transferred to the origin context after return or by migrants who remain connected with those left behind (e.g., Levitt & Schiller, 2004; Vlase, 2013b). Building on this basis, we explore if the country of destination has a significant effect on returnees’ propensity toward entrepreneurship even. We excluded, from these especially designed models, returnees with experiences in two or more countries of destination⁴. The data allowed us to identify a subsample of returnees from Germany, Italy, and Spain.

Residential status

Respondents’ residential status was registered at the moment of the survey and offers the possibility to differentiate between migrants who decided to live after their return in areas characterized by one of the two different levels of economic development presented in the previous section about the regional context. Returnees who were residents in Sibiu and Brasov were placed in the category of a highly developed economic context, whereas the other four counties were evaluated as having an average level of economic development. A dichotomous variable was built with highly developed economic context = 1 and other areas = 0.

The following research questions were formulated for guiding the analyses:

Research Question 1: How is affected the returnee’s probability to enter into entrepreneurship by certain individual characteristics?

Research Question 2: Which features of the migratory experience change the returnee’s probability to enter into entrepreneurship?

Research Question 3: Should we add the level of development of the return context in the explanatory model for evaluating Romanian returnees’ probability to enter into entrepreneurship?

Analyses and Results

The quantitative approach used in this article allowed us to better understand who are the Romanian returnees entering into entrepreneurship in this regional context. To attend to this general objective, we draw the main features of the sample and advanced several logistic regression models for answering our research questions. We discuss in this article the models where we contrasted entrepreneurship to all other employment statuses, but all the results remain consistent or are stronger if we replicate these models on the smaller sample of returnees who were in employment (excluding those in education, unemployment, or working within their own households without searching for jobs on the labor market) (see Appendix A for these results).

Descriptive Statistics

The main descriptive statistics relevant for our sample are presented in Table 2. At the time when the data were collected, around 77% of the returnees had one of the following employment statuses on the labor market: full-time employment (67%), entrepreneurship (6%), part-time employment (4%), or in unemployment and searching for a job (4%). In addition, other returnees were in education (8%) or working within their own households without searching for jobs on the labor market (11%). Those in retirement were excluded.

Eurostat’s (2017) statistics allow us to see which countries were the main destinations for Romanian migrants based on the residents’ citizenship. According to this official source, Italy (n = 1,168,552), Spain (n = 683,797), and Germany (n = 507,062), were, by far, the favorite destinations for Romanian citizens, and these three countries have hosted around 75% of the number of Romanians registered in other EU countries. We restricted our sample to these three traditional destinations because we gathered substantial subsamples for each of them. However, we obtained a different distribution between countries due to the region’s specificity (Sandu, 2010a) and returnees from Germany created the largest category.

Around two-thirds from the returnees included in the sample were residents in a highly developed economic context (Sibiu and Brasov). This was a direct result of the available resources for collecting data through a network of interviewers dominated by those who were located in Sibiu. The main county for the area with an average level of economic development was Valcea (22%).

In terms of gender, the sample was balanced and the share of men was around 51%. Around 65% of the respondents finished their migratory experience before the age of 35. The percentage of individuals who were in entrepreneurship before their first migration is very low (3%). Even if nearly 27% of the sample linked the return motivation to accumulation or to their desire to start a business, only 5% of them used the most of the money saved abroad for lucrative investment.

The sample had the following structure on education levels: primary or secondary education (without high school diploma)—28%, upper secondary education (with high school diploma)—45%, and tertiary education—27%. For the designed analytical model, it is also relevant that 26% of the respondents included in the sample graduated nontertiary technical or vocational education.

The results of the Firth-corrected binomial logit regressions are provided in Table 3. First, we interpret each model and afterward discuss these results in relation to our research questions.

Table 3.

Firth-Corrected Binomial Logit Regression Models for Predicting Romanian Returnees’ Log Odds to Engage in Entrepreneurship Upon Return.

Independent variables	First Model			Second Model			Third Model			Fourth Model^a
Independent variables	Coefficient	SE	z	Coefficient	SE	z	Coefficient	SE	z	Coefficient	SE	z
Gender (male = 1)	0.920*	0.368	2.50	0.757^†	0.387	1.95	0.784*	0.388	2.02	1.145*	0.552	2.07
Age at last return (no. of years)	0.010	0.018	0.58	0.021	0.020	1.05	0.028	0.021	1.36	0.023	0.029	0.80
Education (no. of years of education)	0.007	0.014	0.51	0.007	0.015	0.47	0.004	0.016	0.31	0.004	0.018	0.19
Length of migration (no. of months spent abroad)	0.013***	0.003	4.22	0.012***	0.003	3.98	0.014***	0.003	4.19	0.019***	0.005	3.80
Entrepreneurship before first migration (yes = 1)	2.552***	0.471	5.42	2.683***	0.537	5.00	2.891***	0.547	5.29	2.074*	0.940	2.21
Return motivation based on accumulation (yes = 1)				1.190**	0.374	3.18	1.343***	0.383	3.51	1.351*	0.536	2.52
Savings used for lucrative investment (yes = 1)				2.179***	0.449	4.85	2.238***	0.455	4.92	2.051**	0.648	3.16
Nontertiary technical or vocational education (yes = 1)							−1.117*	0.474	−2.35
Respondents’ residential status in a highly developed area (yes = 1)							−0.698^†	0.371	−1.88
Returned from Italy (yes = 1)										1.456^†	0.844	1.73
Returned from Germany (yes = 1)										1.260	0.887	1.42
Constant	−4.636***	0.696	−6.66	−5.694***	0.827	−6.89	−5.371***	0.852	−6.30	−7.32***	1.434	−5.17
Penalized log likelihood	−124.62			−101.90			−95.56			−37.629
Cox–Snell/ML	0.071			0.117			0.126			0.117
McFadden	0.200			0.340			0.373			0.426
Tjur’s D	0.143			0.233			0.260			0.223
No. of cases	842			842			842			448

Note. ML = maximum likelihood.

All the individuals included in the fourth model are returnees from Germany, Italy, or Spain. We built dummy for each country and used Spain as the reference category.

†

p < .1. *p < .05. **p < .01. ***p < .001.

The first model built for this analysis included five predictors which were expected to affect individuals’ log odds for engaging in entrepreneurship upon return. We found within this analytical model that three independent variables (IVs) were in positive statistically significant relationships with the DV and this was consistent with the literature discussed in the previous sections. We identified a strong effect linked to the employment status of entrepreneurship before the first migratory experience (Coeff. = 2.552 and p < .001). The next factor with predictive value was the length of the migratory experience, and longer periods of time spent abroad increased individuals’ log odds of being into entrepreneurship after return (Coeff. = 0.013 and p < .001). However, the value of each additional month spent abroad was rather low. The third statistically significant determinant was gender and men had higher log odds for entrepreneurship (Coeff. = 0.920 and p < .05). Individuals’ age at last return and their level of education did not statistically significantly affect returnees’ log odds to be entrepreneurs in this combination of factors.

The second model expanded the analysis by adding two other features of the return process to the first model. These variables were important in the general logic in which migrants’ preparedness for return was linked to the opportunity-driven entrepreneurship. These measured if the individual based his or her decision to return on the accumulation of economic capital and if he or she used savings for lucrative investment. Within this model, the strongest predictor remained the status of entrepreneur before emigration (Coeff. = 2.683 and p < .001) and it was followed by the use of savings for investment (Coeff. = 2.179 and p < .001). We found for both of them positive statistically significant relationships with the DV. At the same time, longer experiences of migration (Coeff. = 0.012 and p < .001) and return motivation based on accumulation (Coeff. = 1.190 and p < .01) increase returnees’ log odds to have this employment status. Within the second model, gender had weaker positive effects on the log odds to enter into entrepreneurship (Coeff. = 0.757 and p < .1). Nonsignificant relationships were found between the individual’s age at last return and the number of years of education and the DV.

The third model maintained all the variables discussed for the previous one and included in the analysis two variables for measuring if individuals’ type of human capital and their residential status in highly developed areas affected their log odds for entering into entrepreneurship. The set of the statistically significant predictors presented above remained in similar positive relationships with the DV: entrepreneurship before emigration (Coeff. = 2.891 and p < .001), the use of savings for investment (Coeff. = 2.238 and p < .001), length of migration (Coeff. = 0.014 and p < .001), return based on accumulation (Coeff. = 1.343 and p < .001), and being men (Coeff. = 0.784 and p < .05). For graduates of nontertiary vocational or technical educational programs, we found a negative statistically significant effect on the DV and within the presented regional context returnees with this type of human capital had lower log odds to be in entrepreneurship (Coeff. = −1.117 and p < .05). At the same time, respondents’ residential status in highly developed areas decreased returnees’ log odds for this employment status, but the relationship was weaker compared with other determinants (Coeff. = −0.698 and p < .1). However, the relationship became stronger and statically significant (p < .05) when we replicated the model on a population of returnees who were in employment (see Appendix A for results). Only if the sample was restricted to those in employment, returnees’ age was a statistically significant predictor, and older returnees had higher log odds to be in entrepreneurship (see Appendix A for results). The number of completed years of education was not in statistically significant relationships with the DV. In brief, we found negative effects of both factors introduced in the third model on the returnee’s log odds to be an entrepreneur, other things held constant.

The fourth model explored the effects associated to the country of destination in predicting the migrant’s log odds for engaging into entrepreneurship upon return. Due to the low number of returnees from other destinations, we analyzed only the three main destinations. Italy and Germany were introduced in the model as dummy variables, whereas Spain was used as the reference category. Among the predictors discussed for the previous models, we observed that all remained in similar and statistically significant relationships with the DV (p < .05). In terms of country of destination, there were higher log odds for entrepreneurship as employment status for those who returned from Italy compared with returnees from Spain, but the relationship was rather weak (Coeff. = 1.456 and p < .1). We did not find statistically significant differences between migrants returned from Germany compared with Spain, other things held constant.

Based on these results, we answer the research questions formulated above (for simplifying the interpretation, we discuss in general terms about the individual’s probability instead of log odds).

Research Question 1

We found empirical evidences that the profile of the return migrant entrepreneurs from our sample is consistent with the results obtained in prior research. First, male respondents have a higher probability to have this employment status; Vlase (2018) recently illustrated this for Romanian returnees based on qualitative insights, but the relationship is also expected for the general population (Ogbor, 2000). Second, the experience of entrepreneurship before emigration is an important predictor of entrepreneurship among returnees and this fact was also consistent with the literature (Dustmann & Kirchkamp, 2002; McCormick & Wahba, 2001). Third, age at return is not a statistically significant predictor when we control for certain features of the migratory experience and the return process. Fourth, when we discuss about education, the important predictor is related to the type of graduated program (vocational and technical education) and not the total number of years of education; Reiner and Radu (2012) found a negative relationship for the Romanian returnees’ level of education and their probability to be entrepreneurs, but they worked on a population of recent returnees which were in the first year after return.

Research Question 2

To answer this question, we can look at two analytical dimensions. The first one offers an image on the length of migration and the destination country where the migrant lived abroad, whereas the second dimension is useful for looking at the process of return.

First, longer experiences of migration increase returnees’ log odds to be entrepreneurs and prior research argued for the accumulations of various types of capitals (Dustmann & Kirchkamp, 2002; McCormick & Wahba, 2001). Our expectations about identifying differences associated to the country of destination were partially confirmed in this regional context. Compared with Spain, both Italy and Germany are in positive relationships with the entrepreneurship, but only for Italy this is statistically significant. Further research should clarify if the fact is linked to self-selectedness of Romanian emigrants toward various destinations (Polavieja et al., 2018; Sandu et al., 2018). These results about the length of migration and the importance of some destinations where the migrant lived can also be related to the transformation of individuals’ values in interaction with different types of economic, cultural, and social values (Sabar & Pagis, 2015; Voicu & Vasile, 2014). For example, we can discuss about social values about entrepreneurship in the countries for which we have a subsample of Romanian returnees.

The analyses provided by the Global Entrepreneurship Monitor (GEM) allow us to identify some differences among the three main countries of destinations for Romanian migrants. There are two main indicators offered by GEM within each country profile which allow to compare societal values about entrepreneurship: (1) the percentage of respondents which assess a “high status to entrepreneurs” and (2) the percentage of respondents who evaluate that “entrepreneurship is a good career choice” (for details, see Bosma & Kelley, 2019). It is revealed from Table 4 that Spain has a substantially lower percentage of people who link entrepreneurship to a high status, whereas analyzing the second indicator shows that Italy has a considerably higher percentage of people who think that being an entrepreneur is a good career choice compared with Germany and Spain. Based on our data, we cannot conclude which are the exact determinants beyond the country of destination, but we can argue that further research should place greater emphasis on this aspect instead of treating returnee population as homogeneous (numerous qualitative studies on return migration do not pay enough attention to these aspects).

Table 4.

Societal Values About Entrepreneurship Registered in Germany, Italy, and Spain.

Country	(1) High status to entrepreneurs				(2) Entrepreneurship is a good career choice
Country	Year 2015–2016	Year 2016–2017	Year 2017–2018	Average value	Year 2015–2016	Year 2016–2017	Year 2017–2018	Average value
Germany (%)	75.7	78.9	77.9	77.5	50.8	51.8	51.3	51.3
Italy (%)	69	69.7	73.2	70.63	60.9	63.3	64.2	62.8
Spain (%)	48.4	50.7	47.9	49	53.2	53.7	53.8	53.57

Source. Global Entrepreneurship Monitor (Global Reports 2015/16, 2016/17, and 2017/18).

Second, the results linked to the importance of individuals’ return motivations based on accumulation and their capacity to use savings for lucrative investment can be interpreted using Cassarino’s (2004) concept of preparedness for return. At the same time, these results are important for identifying that the entrepreneurs included in our sample are closer to the idea of opportunity-driven entrepreneurship who planned to open a business at the moment of return and who were able to mobilize resources for implementing a business idea in an economic context.

Research Question 3

Our model was based on the idea of differentiating between two levels of economic development of the return areas and to place them in relation to entrepreneurs’ profile. Based on this regional survey, we found a weak negative relationship between the high level of development and returnees’ probability to be entrepreneurs. On one hand, returnees have lower probability to enter into entrepreneurship in a highly developed context and various factors can be behind this fact (e.g., the jobs are attractive enough, the economic costs for enterprising are higher, and the savings from migration have lower relative value). On the other hand, the type of entrepreneurs identified by our study has competitive advantages for enterprising in areas characterized by an average level of development.

Conclusion

This article offered empirical-based knowledge about one of the highest intra-European migration populations and contributed to the general debate on migrants’ probability to engage in entrepreneurship upon return. The main objective of the study was to reveal the distinctive features of the Romanian returnees who enter into entrepreneurship by looking at individuals’ characteristics and features of the migratory experience. Our study answered several research questions and opened new important lines of inquiry using a theoretical framework resulting from the intersection of the entrepreneurship literature and return migration studies. The research design was carefully adapted to the specificity of the Romanian context, but it aimed to contribute to the broader debate about migration effects at the individual level.

Survey data collected within a large regional sample, including around 840 returned migrants who were adults at their return and were not retired at the moment of the study, were analyzed for adding new insights to the existent knowledge about Romanian return migration. The regional concentration of the sample allowed us to contrast two levels of economic development (average and highly developed return contexts), but underdeveloped areas were not included in the study. Even if our results cannot be generalized to the entire population of Romanian return migrants, there are some important findings that can be stated.

The profile of the returnees who entered into entrepreneurship was closer to opportunity-driven entrepreneurship. First, entrepreneurial status before migration affected migrants’ probability for entering into entrepreneurship upon return, and this is consistent with findings from other geographical settings. Second, the self-assessed return motivation was an important predictor for entering into this occupational trajectory, and the probability was higher for those migrants who based their decision to return on economic accumulation. Third, returnees who used savings resulted from the migratory experience for lucrative investments had higher chances of entering into entrepreneurship compared with those who used their savings for locative investments or consumption. Correspondingly, longer periods abroad increased individuals’ chances for entrepreneurship upon return. Aggregating these aspects, the article emphasizes that features of migration and return are relevant for understanding the specificity of people who are oriented toward entrepreneurship upon return.

The country in which the return migrant spent a period of time has some importance for predicting his or her chances for entrepreneurship upon return. For example, controlling for a series of individual characteristics, features of the migratory experience, as well as determinants of return, we found that Romanian returnees from Italy have a higher probability for entrepreneurship compared with those from Spain.

Among the sociodemographic characteristics, such as gender, age, and education, we found important effects only for gender. Men have a higher probability of entering into entrepreneurship upon return, whereas age’s effects were not statistically significant within our sample of returnees (apart from the case when the analyses were restricted only to those in employment; see Appendix A). At the same time, education as a measure for one’s stock of human capital is in a more complex relationship with returnees’ probability to enter into entrepreneurship. The number of completed years of education is not a statistically significant predictor, whereas the graduates of nontertiary technical or vocational education have decreased chances to be entrepreneurs.

These findings can be discussed in relation to the increased interest of origin countries in stimulating return migration through mechanisms based on entrepreneurship. Our study reveals a real need for understanding better the challenges related to reintegration of the return migrants in countries such as Romania which are characterized by massive emigration. The sustainability of governmental programs designed for attracting migrants at origin should take into consideration the existence of a complex mixture of determinants for entrepreneurship (including gender differences, stock of human capital, and features of the migratory experience) and to address also intraregional differences.

Footnotes

The author is grateful to Andrei Gheorghiţă,Horaţiu Rusu,Mihai Stelian Rusu,Ionela Vlase and Bogdan Voicu,as well as to journal’s reviewers for their useful comments and constructive suggestions on earlier drafts of the article.

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) disclosed receipt of the following financial support for the research,authorship,and/or publication of this article: The work related to this paper was undertaken as part of the research project “Returnees’ Innovative Skills and Knowledge: Becoming Entrepreneur through Migration Experience”,grant reference PN-III-P1-1.1-PD-2016-0659 (CNCS – UEFISCDI). Also,this work was supported by a research grant of the Lucian Blaga University of Sibiu (LBUS-IRG-2017-03).

ORCID iD

Alin Croitoru

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