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Innovative Self-concept of Micro-entrepreneurs: Perception of Barriers and Intention to Invest.


Entrepreneurship has been recognized as a relevant activity for economic development, as it encourages self-employment and economic activity (Schumpeter, 1934). Moreover, studies have described entrepreneurial activity as a source of job creation and economic growth (Ovaska & Sobel, 2005; Zacharakis, Shepherd, & Bygrave, 2000).

The recognized effect of entrepreneurship on countries' economic growth has encouraged the development of research to identify factors that favor or hinder it. These factors relate to conditions in the entrepreneurial environment or with internal motivations to perform a different job to that of salaried workers. Two areas of research development in recent years are the study of the perception of barriers to entrepreneurship (Kouriloff, 2000; Lofstrom, Bates, & Parker, 2014; Sarasvathy, 2004) and individual entrepreneur conditions related to a company's results (Hisrich & Brush, 1986; Kozubikova, Belas, Bilan, & Bartos, 2015).

Regarding the study of individual conditions of the entrepreneur, research has mainly analyzed demographic conditions such as gender (Henry, Foss, & Ahl, 2016; Humbert & Drew, 2010; Shinnar, Hsu, & Powell, 2014) and age (Minola, Criaco, & Obschonka, 2016). These demographic variables are easily identifiable, however, they have limited ability to predict behaviors, since people with similar demographic conditions may present different behaviors (Camino & Rua, 2012). As an alternative to the aforementioned demographic variables, in recent years studies of entrepreneurs' psychological variables, such as their personality (Miller, 2015) and personal values have been developed (Fayolle, Linan, & Moriano, 2014). One of the variables that integrates this category is the entrepreneurial self-concept, which consists of an individual's knowledge and belief about themselves at a moment in time (Hamachek, 1990), as Hamachek (1987, p. 10) points out, "it is our private mental image of ourselves, a set of beliefs about the kind of people we are".

Several researches have recognized the impact of entrepreneurial self-concept, self-perception or self-image of entrepreneurship (Krueger & Brazeal, 1994; Rhodes & Butler, 2004; Verheul, Uhlaner, & Thurik, 2005). A term in this area that has received primary attention is self-efficacy, defined as "the self-perception of individual capacities that affect motivation, personal resources and courses of action according to situational demands" (Wood & Bandura, 1989, p. 408).

Despite the recognition of self-concept, especially self-efficacy, with motivation and results of entrepreneurship, there is scant evidence to link innovative self-concept with perceived barriers to entrepreneurship and the intention to invest in new assets, in the context of micro-enterprises in Latin America. In these countries, authors such as Ambrosini and Lopez (2006), Munoz (2011), Valladares and Lajo (2013), Berrios (2015), have studied the influence of self-concept or self-perception in areas such as motivation to start a business and entrepreneurial skills. In a complementary way, Vargas (2007) and Ferrer and Jimenez (2009), analyzed the relevance of entrepreneurial self-efficacy on variables such as intention to develop ventures and life satisfaction.

Specifically, the relationship of innovative self-concept on the perception of particular barriers has not been analyzed in the context of micro-enterprises in Latin America, and the innovative self-concept differs according to its demographic conditions of micro-entrepreneurs. That is, it has not yet been identified as to whether innovative self-appointed entrepreneurs, present differentiated perceptions about difficulties in undertaking and intention to invest and/or if sociodemographic variables such as gender, age and educational level have an impact on their innovative self-concept. Consequently, there is an apparent knowledge gap.

This knowledge would allow us to understand the benefits of current activities implemented for entrepreneurship training. It would also help to design programs directed towards specific groups, since self-concept is a condition that can be intervened through activities such as workshops and coaching. Chile is considered to be a country of interest, as it integrates the emerging Latin American economies (Morgan Stanley Capital International, n.d.) and may represent conditions present in Brazil, Mexico and Colombia, or other countries.

Theoretical Framework

Entrepreneurship and self-concept

From the perspective of the psychological characteristics of the entrepreneur, investigations have studied the relevance of aspects such as personality traits (Brandstatter, 2011; Leutner, Ahmetoglu, Akhtar, & Chamorro-Premuzic, 2014; Miller, 2015), lifestyles (Cederholm, 2015; Dale, 2015) and entrepreneurial self-concept (Poon, Ainuddin, & Juniy, 2006). Entrepreneur self-concept has been studied under different conceptions, using terms such as entrepreneur identity (Akerlof & Kranton, 2000), self-image (Verheul et al., 2005), self-awareness (Connell & Wood, 2005) and self-knowledge (Lans, Biemans, Mulder, & Verstegen, 2010).

For example, Akerlof and Kranton (2000) define the concept of identity as the sense of self in economic analysis and point out that it plays a key role in explaining individual intentions for carrying out entrepreneurship. The relevance of the entrepreneur identity concept has been recognized as a condition that implies stable behaviors in the field of entrepreneurship activities (Dobrev & Barnett, 2005; Milton, 2009). In this area, Hoang and Gimeno (2010) study the relationship between business identity and business persistence and Mitchell and Shepherd (2010) have analyzed the association between the entrepreneur's self-image and decisions about entrepreneurial opportunities.

According to James (1890, 1950), self-concept consists of an empirical self in quote, which is a material, social and spiritual component, and fundamental to the understanding of an individual's experiences. Mitchell and Shepherd (2010) acknowledge the importance of self-perception for entrepreneurs as they must estimate coherence between their self-concept and the business opportunities they identify. In a complementary way, Bird (1995) estimates that self-image affects entrepreneurs' capacities. To explain its relevance under a theoretical foundation, social learning theory (Bandura, 1977, 1986) suggests that there is a triangle of reciprocal causes, including behaviors, cognitions and other environmental factors. This means that the perception of the environment and of oneself affects behavior, and that the behavior of an individual affects the perception of self and of one's environment.

The relationship between entrepreneurial activity and self-concept has been studied mainly from the perspective of self-efficacy (Boyd & Vozikis, 1994; Bullough, Renko, & Myatt, 2014; Hsu, Wiklund, & Cotton, 2017), defined as self-perception of an individual's ability to perform certain tasks (Bandura, 1987) or self-confidence in performance within a self-perceived domain of personal abilities (Wilson, Kickul, & Marlino, 2007). It has been recognized that the self-perception of entrepreneurs' abilities impairs their performance, since it has been estimated that entrepreneurs are successful in activities that they believe to be competitive (Bandura, 1989). It has also been suggested that the motivations of the entrepreneur may depend on their self-efficacy, since self-perception affects affective and behavioral states (Markham, Balkin, & Baron, 2002), as well as individual motivation and persistence when developing ventures (Bandura, 1997).

Previous research evidences differences in performance, motivation and persistence of the entrepreneur, derived from self-perception. Consistent with this evidence, I estimate that there should also be variation in the intention to invest in assets according to the innovative self-concept of micro-entrepreneurs and, thus, I propose the following hypothesis:

Ho: There are differences in intention to invest in entrepreneurships according to the innovative self-concept of micro-entrepreneurs.

Barriers to Entrepreneurship

The study of barriers to entrepreneurship, defined as conditions that hinder or impede entrepreneurship, is relevant (Lien, Lytle, & Komro, 2002), since they help to identify aspects that affect entrepreneurial activity and, in an indirect way, the economic development of countries. It has been recognized that entrepreneurship intentions depend on the perception of barriers to entrepreneurship (Carayannis, Evans, & Hanson, 2003; Luthje & Franke, 2003). In this sense, Krueger (2008) considers that barriers perceived by entrepreneurs moderate their intentions and efforts to develop new businesses.

Regarding classification of barriers to entrepreneurship, Choo and Wong (2006) pose as barriers: lack of capital, lack of skills, high risk, lack of confidence and costs for government regulations. Moreover, Giacomin et al. (2011) define barriers as: lack of support structure and high fiscal and administrative costs, lack of knowledge and experience, economic climate and lack of entrepreneurship skills, lack of confidence and risk aversion. Finally, Donga, Ngirande and Shumba (2016) identify the following barriers: Lack of financing, market access, outdated equipment and technology, and poor infrastructure.

Among those mentioned, lack of financing has been estimated as outstanding (Robertson, Collins, Medeira, & Slater, 2003; Volery, Doss, Mazzarol, & Thein, 1997). In the field of micro-enterprises, Fielden, Davidson and Makin (2000) emphasize lack of funding as a prominent barrier. In addition, Villanger (2015) argues that access to capital and lack of skills and knowledge are significant obstacles for growth. Ahmad (2012) acknowledge the lack of financial support, bureaucracy, lack of credit options and lack of training as major problems.

The perception of external situations relates to the self-perception of an individual (Bandura 1977, 1986), therefore, it is estimated that the innovative self-concept, understood as micro-entrepreneurs' self-appreciation of innovator status, should affect the difficulties they perceive from their environment. For example, microentertainers might perceive some barriers to entrepreneurship as less relevant, since they consider that their inventive capacity reduces the impact of these conditions. By contrast, they might perceive some barriers as more important, since they limit the implementation of their innovative projects. Consequently, I propose the following hypothesis:

H1: There are differences in perception of barriers to entrepreneurship, according to micro-entrepreneurs' innovative self-concept.

Demographic Conditions of Entrepreneurs

In the area of entrepreneurial personal characteristics, which are related to their motivation and propensity to develop ventures, previous research recognized the incidence of different sociodemographic conditions, such as gender (Brush, Briun, & Welter, 2009; Henry et al., 2016; Humbert & Drew, 2010; Shinnar et al., 2014; Wilson et al., 2007), age (Kautonen, 2008; Levesque & Minniti, 2011; Minola, Criaco, & Cassia, 2014), and educational level (Martin, McNally, & Kay, 2013; Oosterbeek, Van Praag, & Ijsselstein, 2010). The relationship of these conditions has been studied in aspects such as propensity for entrepreneurship, entrepreneurial skills and performance of the developed enterprises.

Regarding age, Welmilla, Weerakkody and Ediriweera (2011) affirm that the abilities of the entrepreneur can improve with longevity. In this sense, Rose, Kumar and Yen (2006) positively associate entrepreneurial age with the success of their business. Moreover, Bosma, Praag and Wit (2000) point out that over the years more knowledge of the factors that influence the success of the company is generated. Regarding the propensity to develop ventures according to age, Karadeniz and Ozdemir (2009) recognize that entrepreneurial propensity is lower in the age cohort of 18-24 years, increases in the stage of 25-34 years and decays again after the age of 44. Most research indicates that the chances of a venture's success increase with experience and that the propensity to develop new ventures decreases with age.

Consistent with these assessments, it is estimated that at an older age it is more challenging to develop new ideas for entrepreneurship. Moreover, the entrepreneur gains more experience and, therefore, his/her self-perception should be different from younger entrepreneurs. Consequently, I propose the following hypothesis:

H2: The innovative self-concept presents differences according to the age of the micro-entrepreneur.

In relation to the gender of the entrepreneur, different aspects have been studied, such as risk orientation in investments, capacities and entrepreneurial performance and propensity towards entrepreneurship. Regarding the relationship of gender with risky investments, studies tend to indicate that women are more conservative with investment decisions (Raposo, Paco, & Ferreira, 2008; Reynolds, 2004). In the field of opportunities, they have recognized advantages for both male and female entrepreneurs. For example, Shinnar, Giacornin and Janssen (2012) point out that the male role in society facilitates their search for business success. With respect to entrepreneurial capacities, advantages have been estimated for women.

In this sense, Ferk, Quien and Posavec (2013) estimate greater management skills in women and Scott (1986) recognizes advantages for women in relational skills. In relation to the propensity for entrepreneurship Tkachev and Kolvereid (1999) do not recognize difference by gender. Other studies, on the other hand, indicate that men have greater intention to develop business ventures (Kelley, Singer, & Herrington, 2012; Verheul, Thurik, Grilo, & Zwan, 2012). One of the causes to explain this difference is a lower perception of self-efficacy in women (Mueller & Dato-on, 2013; Wilson et al., 2007) and greater self-perception as an entrepreneur for men (Verheul et al., 2005).

The evidence obtained regarding propensity, performance and entrepreneurship capacities by gender is diverse. Some studies evidence advantages of men and others attribute advantage to women in particular conditions. Consistent with previous research, it is estimated that the innovative self-concept should also vary according to the gender of the micro-entrepreneur, therefore, the following hypothesis is proposed:

H3: There is a difference regarding innovative self-perception, according to micro-entrepreneur gender.

In relation to the level of training of the entrepreneur, a positive relationship between educational level and entrepreneurial performance has been recognized. Specifically, a link has been estimated between the level of training and the acquisition of skills and knowledge that strengthen the entrepreneurship, as well as the development of positive perception towards entrepreneurship and a greater intention to develop ventures (Honig, 1998; Martin et al., 2013).

Moreover, investigations have related entrepreneurial education and greater self-efficacy. In this regard, the education of the entrepreneur seems to strengthen their expertise on a topic, the possession of relevant experience and verbal persuasion, and consequently on self-efficacy (Bandura, 1982, 1986). For example, Zhao, Seibert and Hills (2005) indicate that self-efficacy is a condition that favorably mediates the relationship of entrepreneurial education and intention to develop a new venture. Regarding participation in activities related to innovation, Barrera Verdugo and Bisama Castillo (2016) show a positive relationship between the educational level of company managers and the participation of their organizations in research and development activities.

Considering the results of previous research, the entrepreneur training level and their innovative self-concept should be positively related and, thus, the following hypotheses are proposed:

H4: The innovative self-concept is positively related to the educational level of the micro-entrepreneur.

H5: The innovative self-concept is positively related to the participation of the micro-entrepreneur in training.

In the scope of entrepreneurial civil status the results are diverse. Seoane and Alvarez (2009) point out that having a partner negatively affects the probability of being an entrepreneur. In contrast, Flores, Landerretche and Sanchez (2011) indicate that having children and partners increases the probability of starting a new business. In the investment field, Love (2010) recognizes differences in risk orientation as a function of marital status, for example, it indicates that widowhood leads to a sharp reduction in the shares of the investment portfolio. In relation to self-concept, Tamayo (1986) shows variation according to the marital status of individuals.

Previous research shows differences in results regarding entrepreneurs' marital status, risk orientation, propensity to develop ventures, entrepreneurial persistence and self-concept. Consistent with these results I estimated that regarding innovative self-concept and entrepreneurship there should also be variations, therefore, I propose the following hypothesis:

H6: The innovative self-concept of micro-entrepreneurs presents differences depending on their marital status.

Materials and methods

The responses of the Fourth Micro-Entrepreneurship Survey, carried out by the Ministry of Economy and Tourism of Chile (Ministerio de Economia, Fomento y Turismo, n.d.), were analyzed. Of these, 5,836 responses from entrepreneurs were selected who declared to keep up their activities: 3,677 men and 2,159 women. Organizations with less than 10 workers are considered to be microenterprises (Ministerio de Economia, Fomento y Turismo, 2016). The methodologies used to perform analysis were as follows: first, percentage frequency analysis to estimate the most relevant barriers to entrepreneurship; second, logistic regressions to relate demographic conditions of the entrepreneurs with their innovative self-concept; and third, Chi-squared tests to estimate differences in perception of barriers to entrepreneurship and intention to invest in assets, according to the innovative self-concept declared by entrepreneurs.

The following are the estimated logistic regression models. Model 1 includes primary and secondary educational level. Model 2 considers secondary and tertiary education. Model 3 focuses on participation in training. Marital status variables, separated or annulled, and widowed are not included to avoid multicollinearity in the results.

Innovative self-concept= [BETA]0+ [BETA]1*Gender+[BETA]2*Age+ [BETA]3*E. Primary+ [BETA]4*E. Secondary+ [BETA]5* Divorced + [BETA]6* Cohabitant (1)

Innovative self-concept = [BETA]0+ [BETA]1*Gender+[BETA]2*Age+ [BETA]3*E. Secondary+ [BETA]4*E. Tertiary+ [BETA]5* Divorced + [BETA]6* Cohabitant (2)

Innovative self-concept = [BETA]0+ [BETA]1*Gender+[BETA]2*Age+[BETA]3*Training+ [BETA]4* Divorced + [BETA]5* Cohabitant (3)

The studied conditions of entrepreneurs and their scales of measurement are presented in Table 1. These characteristics are related to innovative self-concept in logistic regressions. The measurement scales are nominal (dummy) and scalar.

The barriers to entrepreneurship considered in the analysis are based on the classification of Giacomin et al. (2011), who identified the categories: Lack of support structure, high fiscal and administrative costs, lack of knowledge and experience, economic climate, lack of confidence and risk aversion. Lack of inputs and lack of financing are included within the lack of support structure. Moreover, high fiscal and administrative costs include high contracting costs, high cost of regulations or legal regulations and high tax rate. The factor related to knowledge and experience includes lack of qualified personnel. Uncertainty about the state of the economy is considered in the economic climate category. The perception of lack of clients is estimated in the factors lacking confidence and aversion to risk. Selected barriers are also consistent with Choo and Wong (2006), who pose five types of barriers: lack of capital, lack of skills, high risk, lack of confidence, and costs for government regulations.

In Table 2, the variables and measurement scales are incorporated in Chi-squared analysis. These variables are used to recognize differences in perception of barriers to entrepreneurship, depending on the innovative self-concept of the micro-entrepreneur and intent to invest in the next 12 months.

Results and Discussion

Description of perceived barriers

To analyze the perception of barriers for the development of surveyed micro-enterprises, I obtained the percentage of barriers perceived as being more relevant. Also included is the percentage of entrepreneurs who do not declare to perceive barriers to entrepreneurship.

The results obtained indicate that the barrier perceived as being more relevant is the lack of financing. This evidence is consistent with that posed by previous authors such as Volery, Doss, Mazzarol and Thein (1997), Robertson, Collins, Medeira and Slater (2003) and Villanger (2015). In contrast, the barriers perceived as being less relevant for the development of micro-enterprises are high costs for hiring employees and high costs for regulations and legal regulations.
            Lack of  Lack of    Lack of   Lack of   cost of
            clients  supplies  financing  skilled   hiring
                                          workers  employees

Frecuency    1627      394        1628       179      127
Percentage  29,40%    7,14       29,50%     3,24%    2,30%

                High                Uncertainty   Do not
              cost of     High tax     about      believe
            regulations     rate        the        that
            /legal norms              economy    there are

Frecuency       144          178       423          821
Percentage     2,61%        3,17%     7,67%       14,88%

Figure 1. Distribution of Frequency of Barriers for the Development of

Note: Table made from bar graph.

Relationship of characteristics of micro-entrepreneurs and innovative self-concept

Logistic regressions that relate characteristics of the micro-entrepreneur with their innovative self-concept as presented in Table 3 show that age, gender, primary or lower education, tertiary education, divorced civil status, and cohabitant marital status affect the probability of the micro-entrepreneur being perceived as innovative. Specifically, men, primary or lower education, and older age reduce the likelihood of innovative self-perception. On the contrary, tertiary education, participation in training, divorced and cohabitant marital status increase this likelihood.

I transformed the odds ratios into probability using the formula:

Probability = [[Odd ratio]/(odd ratio + 1)] (4)

I noted that divorced status, participation in training and tertiary education are the variables with the highest increase in probability, with values 68.9%, 62.5% and 55.8%, respectively. For Multicollinearity evaluation, Variance Inflation Factor Analysis (VIF) was performed in the regression models. The resulting FV values associated with the variables are less than 1.15 and have an average of less than 1.1 in all three regression models. Consequently, I estimated that there is no significant multicollinearity between the study variables.

To corroborate the results obtained in regressions in a complementary way, Chi-squared tests were carried out to evaluate differences of innovative self-perception regarding entrepreneurs' characteristics, including the study of married, single, separated/annulled, widowed conditions, previously obviated by multicollinearity. The results presented in Table 4 are consistent with those obtained in logistic regressions. In a complementary form they recognize that with married and widowed micro-entrepreneurs, the proportion of people declaring innovative self-perception is lower, and with single marital status there is no statistically significant difference.

Barriers to entrepreneurs differentiated by innovative self-concept

The Chi-squared analysis presented in Table 5 shows that micro-entrepreneurs who perceive themselves as innovators and, in greater proportion, the existence of factors that impede the growth of their business. Moreover, entrepreneurs who perceive themselves as innovators are more likely to invest or buy assets in the next 12 months. The hypothesis tests of equality of proportion between groups with and without innovative self-perception are rejected with 99% confidence.

Regarding differences in perception of specific barriers, the results presented in Table 5 show greater importance among micro-entrepreneurs with innovative self-concept regarding the barriers lack of financing, lack of inputs and lack of trained workers, and in contrast, less perceived relevance of the barriers lack of clients and uncertainty about the state of the economy. There is no evidence of perceived differences for the barriers employee recruitment cost, legal regulation costs, and high tax rates.


Regression analysis and Chi-squared tests allow us to validate the presented hypotheses. Differences are recognized both in the intention to invest and to buy assets (H0) and in the perception of barriers (H1) in micro-entrepreneurs perceived as innovators. Similarly, there are variations regarding innovative self-concept according to age (H2), gender (H3), training level (H4), participation in training (H5) and marital status (H6) of the micro-entrepreneur.

Regarding specific barriers, the micro-entrepreneurs who are considered to be innovative perceive with greater relevance the lack of financing, lack of supplies and lack of qualified personnel. On the contrary, they consider the lack of clients and the uncertainty due to the state of the economy as less important. In a complementary way, the results show that women, tertiary education level, participation in training, divorced and cohabitant marital status are positively associated with a propensity for innovative self-concept, and in contrast, greater age, primary or lower level of education, married civil status and civil widowhood are negatively related to innovative self-perception.

After interpreting results related to intention to invest and perception of barriers, it is possible to estimate that:

* Consistent with Dyer, Gregersen and Christensen (2008), who point out that innovative entrepreneurs develop unique value propositions and can develop new ideas to start a business, entrepreneurs with innovative self-perception could perceive greater barriers because they require resources to implement novel and unique proposals.

* On the contrary, entrepreneurs perceived as innovative could appreciate less relevance regarding lack of customers and economic conditions because they believe that their individual capacities support the acquisition of clients and economic situations.

With the analysis of conditions that relate to innovative self-concept, it is possible to consider that:

* Entrepreneurial and managerial women constitute a smaller proportion of their gender (Berbel, 2014), therefore, it is coherent for women microentrepreneurs to perceive themselves as innovators, as they are a minority within their gender.

* Age favors gaining experience (Rose, Kumar, & Yen, 2006; Welmilla, Weerakkody, & Ediriweera, 2011) and lower adoption of investment risks and less propensity to develop ventures for the first time (Jianakoplos & Bernasek, 2006). Qualities are consistent with less innovative self-perception.

* Educational level and training strengthen cognitive complexity and ability to incorporate new ideas and adopt innovations (Wally & Baum, 1994). They also favor self-efficacy (Wilson et al., 2007), therefore training develops competencies to seek new solutions and strengthens innovative self-perception.

* The Married condition relates to conservative values (McAdams, Hanek, & Dadabo, 2013) and the civil status Divorced and Cohabitant associates with alternative situations that imply differentiation from tradition (Cole, 2015). This evidence is consistent with variations of innovative self-concept.

As a proposal to strengthen innovative self-concept and reduce the perception of barriers that affect the development of micro-enterprises, I estimated the design of training programs that seek to strengthen innovative self-perception and that increase support for access to financial resources, to human resources and to the necessary supplies for the operation of these organizations. Particularly, I propose the following:

* To implement training and/or coaching programs for micro-entrepreneurs with conditions associated with less innovative self-concept, to guide their self-perception towards innovation, and thereby increase their propensity to develop new initiatives.

* To develop training programs to improve competencies in the search for financing, inputs from suppliers and training of staff.

* To strengthen programs for financing support, oriented at micro-entrepreneurs with conditions related to innovative self-concept, such as women, people with tertiary education, participants in training programs and young entrepreneurs with less experience.

* To develop programs for the strengthening of networks with suppliers within and outside the country that facilitate access to inputs, focused on micro-entrepreneurs with positively related conditions with innovative self-concept.

The proposed initiatives would strengthen the innovative self-concept and thus the willingness to invest in assets, a situation that would contribute to economic growth and employment (Orjuela, 2006), as well as supporting the reduction of barriers perceived as relevant in innovative self-perceived entrepreneurs. These proposals are consistent with the findings of Haider, Asad and Aziz (2015) who point out that it is necessary to adapt the training of micro-entrepreneurs according to their characteristics, and that these proposals could be implemented in micro-ventures from other South American countries with comparable levels of economic development, such as Brazil, Colombia and Mexico, which Morgan Stanley Capital International (n.d.) considers emerging nations.


The results recognize a relationship between variables. However, it is not possible to estimate if changes in age, training, and marital status affect the innovative self-concept and, with it, the intention to develop new entrepreneurial initiatives and the perception of barriers. To detect changes over time it is necessary to consider experimental or longitudinal research designs. Another limitation is that the research does not include interview analysis, focus groups or other qualitative techniques to recognize underlying causes of the differences found in quantitative analysis. Despite these limitations, I estimate that the information obtained could contribute to direct public policies or guide corporate social responsibility initiatives of private companies, which seek to strengthen micro-enterprises and reduce barriers for their development.


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Gustavo Alfonso Barrera Verdugo (1)

Universidad Tecnologica de Chile INACAP, Santiago, Chile (1)

Author Profile

Gustavo Alfonso Barrera Verdugo

Universidad Tecnologica de Chile INACAP, Direccion de Postgrados, Avenida del Valle Norte, 819, Piso 5, Huechuraba, Santiago, Region Metropolitana, 8580702, Chile. E-mail address:

Received 17 July 2017; received in revised form 2 January 2018; accepted 13 March 2018; first published online 23 April 2018.

Editor's note. Hilka Vier Machado served as Action Editor for this article.
Table 1
Entrepreneurial Variables Related to Innovative Self-concept

                            Answer alternatives

Age                             Open answer
Gender                        1=Man, 0=Woman
Primary or lower education      Yes=1, No=0
Secondary education             Yes=1, No=0
Tertiary education              Yes=1, No=0
Participation in training       Yes=1, No=0
Married                         Yes=1, No=0
Single                          Yes=1, No=0
Cohabitant                      Yes=1, No=0
Divorced                        Yes=1, No=0
Separated/annulled              Yes=1, No=0
Widower                         Yes=1, No=0

Note. Source: Variables are extracted from Fourth
Micro-Entrepreneurship Survey by Ministerio de Economia, Fomento y
Turismo. (n.d.). Cuarta encuesta de microemprendimiento de Chile
(EME4). Retrieved June, 2017, from

Table 2
Variables and Measurement Scales Incorporated in Chi-squared Analysis

Barriers to entrepreneurship                   Measurement
development                                       range

Lack of customers
Lack of supplies
Lack of financing
Lack of skilled workers                       Most important
High cost of hiring new employees                factor.
High cost of regulations or legal norms      Dichotomous: yes
                                                   / no
High cost of regulations or legal norms
High tax rate
Uncertainty about the state of the
Do not believe that there are factors that
impede the growth of business                Dichotomous: yes
Intends to invest or buy assets in the next        / no
12 months

Barriers to entrepreneurship                  Entrepreneur
development                                  self-perception

Lack of customers
Lack of supplies
Lack of financing
Lack of skilled workers
High cost of hiring new employees
High cost of regulations or legal norms

High cost of regulations or legal norms        Innovative
High tax rate                                 self-concept
Uncertainty about the state of the
Do not believe that there are factors that
impede the growth of business
Intends to invest or buy assets in the next
12 months

Barriers to entrepreneurship                   Entrepreneur
development                                  self-perception

Lack of customers
Lack of supplies
Lack of financing
Lack of skilled workers
High cost of hiring new employees
High cost of regulations or legal norms      Do you consider
High cost of regulations or legal norms        innovative?
High tax rate                                Dichotomous: yes
Uncertainty about the state of the                 / no
Do not believe that there are factors that
impede the growth of business
Intends to invest or buy assets in the next
12 months

Table 3
Logistic Regression Models

                    n=5836                    n=5836
           Prob > [chi.sup.2]=0.000  Prob > [chi.sup.2]=0.000
           Odds ratio    P>|z|        Odds ratio    P>|z|

Gender       0.844     0.023 (**)       0.837     0.017 (**)
Age          0.978     0.000 (***)      0.977     0.000 (***)
Primary      0.817     0.013 (**)
Secondary    0.961     0.697            1.117     0.261
Tertiary                                1.265     0.010 (**)
Divorced     2.157     0.022 (**)       2.184     0.019 (**)
Cohabitant   1.188     0.087 (*)        1.199     0.071 (*)
Constant    17.967     0.000           16.352     0.000

           Prob > [chi.sup.2]=0.000
             Odds ratio   P>|z|

Gender         0.876     0.078 (*)
Age            0.977     0.000 (***)
Training       1.664     0.000 (***)
Divorced       2.211     0.018 (**)
Cohabitant     1.192     0.081 (*)
Constant      15.547     0.000

Note. Author's elaboration.
(*)p <.10, (**) p < .05, (***) p < .001.

Table 4
Chi-squared Tests, Differences of Innovative Self-concept by

                                  Innovative self-concept
Characteristics                   Self-perceived     Self-perceived
of the micro-entrepreneur         As an innovator =  As an innovator =
                                       No                 Yes

                           Woman        328               1831
Gender                      Man         667               3010
Primary or lower            No          603                392
education                   Yes        3353               1488
Secondary                   No          836                159
education                   Yes        4069                772
Tertiary education          No          800                195
                            Yes        3602               1232
Training                    No          844                151
                            Yes        3667               1174
Married                     No          474                521
                            Yes        2486               2355
Single                      No          803                192
                            Yes        4702               1134
Divorced                    No          985                 10
                            Yes        4735                106
Cohabitant                  No          853                142
                            Yes        3951                890
Separated/annulled          No          917                 78
                            Yes        4476                365
Widower                     No          943                 52
                            Yes        4658                235
Age                                      54.63              50.07

Characteristics            Pr [Chi.sup.2]
of the micro-entrepreneur        /F              Conclusion

                                0.004           Greater with
Gender                          (***)           female gender
Primary or lower                0.000           Smaller with
education                       (***)         Primary education
Secondary                                    Without significant
education                       0.979            difference
Tertiary education              0.000           Greater with
                                (***)        Tertiary education
Training                        0.000              Greater
                                (***)           with training
Married                         0.033            Smaller in
                                (**)               Married
Single                          0.906        Without significant
Divorced                        0.015            Greater in
                                (**)              Divorced
Cohabitant                      0.002              Greater
                                (**)            in cohabiting
Separated/annulled              0.745        Without significant
Widower                         0.035            Greater in
                                (**)              Divorced
Age                             0.000         Smaller age with
average                         (***)      innovative self-concept

Note. Author's elaboration.
(*) p <.10, (**) p < .05, (***) p < .001.

Table 5
Chi-squared Tests, Barriers to Entrepreneurship by Innovative

                                            Innovative self-concept
                                        Self-perceived  Self-perceived
                                            as an       as an innovator=
                                              No             Yes

                                   No         800            4264
Do not believe that there are
factors that impede the growth of
their business                     Yes        195             577

                                   No         698             264
Want to buy assets or invest in
the next 12 months                 Yes       2394            2242

                                   Pr [Chi.sup.2]

                                                     Smaller in
Do not believe that there are          (***)       entrepreneurs
factors that impede the growth of                       with
their business                          0.00         innovative
                                                     Greater in
Want to buy assets or invest in        (***)       entrepreneurs
the next 12 months                      0.00            with

Note. Author's elaboration.
(*) p <.10, (**) p < .05, (***) p < .001.

Table 6
Chi-squared Tests, Types of Barriers to Entrepreneurship by Innovative

                                   Innovative self-concept
Most important barrier         Self-perceived as  Self-perceived as
for the development of          an innovator =    an innovator =
micro-enterprise                     No                Yes

                          No        674                3593
Lack of customers         Yes       321                1248

                          No        832                3467

Lack of financing         Yes       163                1374
                          No        946                4521
Lack of supplies          Yes        49                 320

                          No        976                4686
Lack of                   Yes        19                 155
trained workers           Yes        17                 106
                          No        978                4735
High cost of hiring
new employees
                          No        974                4722
High cost of regulations
Or legal rules            Yes        21                 119
                          No        962                4703
High tax rate
                          Yes        33                 138
Uncertainty about         No        937                4482
the state of the economy  Yes        58                 359

Most important barrier
for the development of    Pr [Chi.sup.2]        Conclusion

                               (***)             Minor with
Lack of customers              0.000      innovative self-concept

                               (***)             Major with
                                          innovative self-concept
Lack of financing              0.000
                               (**)              Major with
Lack of supplies               0.047      innovative self-concept

                                                 Major with
Lack of                        (**)       innovative self-concept
trained workers                0.029
High cost of hiring            0.336            significant
new employees                                    difference
High cost of regulations       0.514            significant
Or legal rules                                   difference
High tax rate                  0.427            significant
Uncertainty about               (*)              Minor with
the state of the economy       0.077      innovative self-concept

Note. Author's elaboration.
(*) p <.10, (**) p < .05, (***) p < .001.
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Title Annotation:Chile
Author:Verdugo, Gustavo Alfonso Barrera; Machado, Hilka Vier
Publication:BAR - Brazilian Administration Review
Article Type:Report
Geographic Code:3CHIL
Date:Apr 1, 2018
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