Opportunity Motivation and Growth Aspirations of Mexican Entrepreneurs: The Moderating Role of the Household Income

Abstract

Framed in the Theory of Planned Behavior, this work analyzes the entrepreneurial growth aspirations in efficiency-driven economies and examines the interaction effect of household income on the relationship between opportunity entrepreneurship and entrepreneurial growth aspirations. We propose a growth aspirations model using GEM (Global Entrepreneurship Monitor) data, with two explanatory variables: increased wealth and independence, and a moderating variable (household income). Hypotheses were validated with the use of hierarchical regression, and we find that that opportunity motivation is positively related to the entrepreneurial intention to expand entrepreneurial business activities. A second interesting finding of this study is that the independent effects model infers that growth aspirations are significantly related to household income.

1. Introduction

Traditionally, the entrepreneurial aspiration for growth has focused, among other factors, on how business growth is affected by Information and Communication Technologies (ICT)-based strategies, mainly through the application of e-commerce and ERP [1,2], ownership [3,4], offshore outsourcing [5,6], entrepreneurial education [7], innovation [8], and political connections [9,10]. Training, networking, and trust have a positive effect on growth aspiration, and entrepreneurs use these practices in response to institutional deficiencies (inadequate educational systems, inefficient courts, and other formal institutions) [11]. Growth-aspiring entrepreneurs benefit simultaneously from strong government (in the sense of property rights enforcement), and smaller government, but are constrained by corruption [12] This study contributes to the existing academic literature by theoretically examining the interaction effect of household income on the relationship between opportunity-based entrepreneurial motivations and business growth aspirations. We propose a model for growth aspirations with two explanatory variables: wealth increase and independent motivation, and a moderating variable, namely, household income, which has a positive impact on the motivation for growth.

Motivation is a necessary condition for achieving growth [13] and takes place under limited volitional control [12]. Actions based on motivation are dependent on the perceived outcomes, abilities, and opportunities associated with the intended behavior [14,15,16,17]. We use the Theory of Planned Behavior in our study to determine entrepreneurship, as this theory is based on studying how entrepreneurial beliefs are defined by both subjective norms related to other people’s expectations, and a perceived behavioral control linked to people’s perceptions of their ability to perform a given behavior. In this sense, the Theory of Planned Behavior has been successful in predicting responses under limited volitional control [15,17,18].

Regarding motivations, people are primarily guided by opportunity entrepreneurship to increase wealth, and to achieve independence, recognition, and social status. Opportunity motives are also referred to as pull motives. Regarding economic wealth, it is the most critical factor affecting entrepreneurial growth preferences [19]. The desire for financial independence is the second most cited pull factor in starting a business [20,21,22,23]. However, individuals may also be factor-driven by necessity, especially seen when there is a threat of unemployment, which forces people into self-employment [24]. Necessity motives are also referred to push reasons, as a considerable number of startups are being created out of necessity. Besides, growing a firm is a much more a committed act than establishing a new firm; thus, the Theory of Planned Behavior is better suited to explain growth aspirations rather than creation of startups.

Liquidity constraints are an essential element to disable entrepreneurs to carry out their business opportunities [25,26]. Therefore, securing funding may be necessary for achieving goal growth. As most entrepreneurs provide a substantial percentage of start-up capital, the household income is closely connected to financing startups. Access to personal wealth is a crucial barrier to entrepreneurial activity, and a lack of personal wealth typically restricts the scale of entrepreneurial activity engaged by the individual [27]. Family characteristics imply the emergence of new firms, opportunity recognition, startup decisions, and resource mobilization [28]. Financial resources in the family are of great importance on entrepreneurial intentions [29]. Thus, high-income households are abler to finance firms and the necessary resources for business growth.

In sum, opportunity-based motivation and household income are important determinants for growth aspirations, and thus, they have been targeted by several studies. Both have strong theoretical backgrounds and have obtained empirical support as predictors of growth aspirations. However, they have generally been studied separately and only rarely together in the same study. Household income may indirectly affect the attitudes, intentions, and behaviors to become entrepreneurs [30]. Entrepreneurs coming from high-income households place a higher demand for the quality of entrepreneurial opportunities. High-income households provide fertile environments for accessing high-quality opportunities because the social connectivity associated with financial wealth enables individuals from high-income households to see more entrepreneurial opportunities for growth [31]. Thus, the effect of opportunity-rooted motivations on entrepreneurial growth aspirations is moderated by higher household income. This work addresses this gap related to the entrepreneurial ambitions for business growth.

We outline in Section 2 the most relevant theories related to these issues, and we set several testable hypotheses. Section 3 describes the data and methodology. Section 4 shows the results that are discussed in Section 5. We end with conclusions.

2. Theoretical Background and Hypotheses

2.1. The Theory of Planned Behavior and Entrepreneurial Growth Aspirations

Entrepreneurial growth aspirations have been the subject of different labels and measures [32] to examine the entrepreneurial willingness for growth [19,33,34], where entrepreneurial culture has an important role to play. Willingness and entrepreneurial efforts measured by entrepreneurial intentions or aspirations [35,36,37] strengthen business growth. Notably, the term ‘ambitious entrepreneurship’ studies the quality of the entrepreneurial activity, which refers to entrepreneurial initiatives and behaviors capable of boosting their firms along the lifespan of the company [38,39].

There is a wide range of factors influencing individual decisions to become a growth-oriented entrepreneur, including: entrepreneurial demographic characteristics (gender, age), wealth, household income, current working status, individual human capital (education, working experience), own perceptions towards entrepreneurship (opportunities recognition, fear of failure, entrepreneurial skills, and abilities), motivations (opportunity or necessity-driven entrepreneurship), and some institutional and macroeconomic factors, such as property rights, government activity, financial capital availability, inflation rate, and country risk [40,41,42]. The combination of these factors explains why entrepreneurs vary their intentions considerably for business growth [35,38], also showing a complicated relationship between growth intentions and firm growth [13] because economic, social, and psychological variables come together in the business creation process.

Business development is a prevalent dimension when researchers empirically capture entrepreneurial growth aspirations. Motivational theories provide a plausible explanation for the differences in growth rates between firms and are built on the premise that motivation affects behavioral choice, business longevity, and organizational effort. Thus, the psychological construct of motivation is essential, especially in research on entrepreneurship. Different entrepreneurial behaviors and abilities have important effects on the entrepreneurial process [43], especially on firm growth [14]. Both microenterprises and SMEs, and the importance of owners’ or managers’ willingness to grow is likely to be relatively more significant than in large firms [43]. However, not all entrepreneurs are willing to make their business grow since they may expect some consequences of growth to be negative and in conflict with their goals [24].

The motivation for growth affects how SME managers make their choice to expand the firm, the willingness to sustain this decision over time, and the level of effort in the endeavor [14]. Motivation has to be relatively stable over time to affect firm growth. Managers working in SMEs are motivated generally to expand their firms during short periods to prioritize other goals and behaviors later. As a result, the motivation for growth is discontinuous [14,15].

The strength of the relationship between motivation and behavior is affected by the individual degree of volitional control, that is, the ability to act on will [14]. The expansion of a firm is an example of a business behavior under limited voluntary control, as firms only grow when managers develop suitable strategies for growth, especially in international markets [44].

A new firm’s growth may be under some volitional control, but it is unlikely to be under total volitional control [17]. The combination of environmental constraints, low skills, and insufficient task comprehension diminishes behavioral motivation [14]. Therefore, managerial motivation has a positive effect on business growth, but this effect cannot be expected to be very large, as behavior is under limited volitional control, and the task of expanding a business can be regarded as complex and fuzzy [12], because it is a joint function of motivation and individual ability [15].

The Theory of Planned Behavior [15] considers limited volitional control. This well-established and validated psychological theory explains and predicts specific actions in particular contexts [17], and is regularly applied to different topics related to entrepreneurship. The Theory of Planned Behavior is an extension to the Theory of Reasoned Action complemented with aspects of individual abilities, thus incorporating behaviors defined by limited volitional control. As expected, this theory outperforms the Theory of Reasoned Action in situations of limited volitional control [45].

The core of the Theory of Planned Behavior is the role of intentions that captures motivational factors to influence behavior as an indication of how people are willing to act, and how much effort they plan to exert to behave [17]. Generally, stronger behavioral intentions carry better performance [15] to distinguish between the attitude towards business growth, the degree others consider growth to be remarkable (subjective norm), and the belief entrepreneurs can achieve firm growth (perceived behavioral control). Together, they determine the entrepreneurial intention to pursue firm growth. Generally, a distinction can be made between what entrepreneurs want and what is possible to achieve, given some individual and environmental constraints guided by individual abilities, skills, and opportunities to make grow the firm.

According to the Theory of Planned Behavior, startups are volitional new businesses established to exploit business opportunities to create extrinsic and intrinsic benefits for entrepreneurs, only if they are oriented for business growth [46]. As a result, motivation has a positive effect on growth aspirations, but the effect is limited because firms’ growth is under limited volitional control.

2.2. Opportunity Motives and Entrepreneurial Growth Aspirations

A second theory for the analysis of entrepreneurial growth ambition is the Push-Pull Theory of Entrepreneurship [47,48,49]. Push factors are personal or external factors driven by necessity entrepreneurship [50], and pull factors are those that draw people to start businesses – such as seeing opportunity entrepreneurship [51]. In general, pull factors are found to be more prevalent than push factors [52,53], especially in developing countries, as the push-pull framework of entrepreneurship focuses on an integrative analysis of forced (push) and voluntary (pull) factors that influence entrepreneurship [54].

Startup creation follows the combination of a dynamic pull effect when entrepreneurs consider startups as their mere source of profit and a dynamic push effect when startups generate social change [55]. To avoid this conflict, organizational wealth is needed. We define corporate wealth as the existence of financial surplus and cash-flow generation in an organization. A cash-flow generation is stronger when the competitive advantages generated in innovative enterprises guided by pull, push or mixed processes are organized as clusters [56].

Generally, people guided by necessity entrepreneurship have lower aspirational levels than entrepreneurs conducted by opportunity entrepreneurship [51], because entrepreneurs based on necessity are more likely to have limited access to human capital, financial capital, technology, and other resources [55]. Therefore, their potential for generating jobs is expected to be constrained. Necessity entrepreneurs are pushed by unemployment situations or dissatisfaction with their previous posts. For necessity-motivated entrepreneurs, their daily economic survival will depend strongly on the survival of their businesses, which may negatively affect the aspirations they have with their firm [55].

In comparison, opportunity entrepreneurs are viewed as individuals who start a business to pursue market opportunities and have usually prepared their entry into self-employment on a more solid basis to start their firms in areas of particular expertise. These factors lead to a longer survival rate and higher business growth, as top growth entrepreneurs are more often found to be motivated by business opportunities and firm growth [57].

In our work, we are interested in investigating the extent to which opportunity motives drive entrepreneurial growth ambition. We analyze the two most important types of start-up motivations identified in the literature: (a) increased wealth motivation, which involves reasons that describe the entrepreneurial intention to earn money and achieve financial security [22], and (b) the motivation for independence to explain that financial expectations and increased independence are positively related to aspirations for growth [33]. Stimulated by a new panel survey focused on nascent entrepreneurs, the PSED (Panel Study of Entrepreneurial Dynamics) database also explores the mechanisms behind growth aspirations [19,35,58,59]. In particular, they link growth expectations with complementary determinants, such as social and financial capital [60], household income [58], and wealth-attainment motivation [19], as there is a positive relationship between wealth-motivated entrepreneurs and high growth jobs [55]. Hence, if entrepreneurs choose wealth, they expect a positive correlation for their aspiration to grow. As a result, hypothesis 1 can be drawn as follows:

H1: 

Increasing wealth motivation augments entrepreneurial growth aspirations.

Independence describes the entrepreneurial desire for freedom, control, and flexibility in the use of one’s time [61,62,63]. A key motivating factor in the decision to follow an entrepreneurial career is a desire for independence and control over one´s working life [21,64]. Independence may be understood as the individual’s intention to start a new venture that is primarily expected to make independent entrepreneurs while providing income and EBITDA (earnings before interests, taxes, depreciation, and amortization) capable of achieving the financial aspirations of the firm, although it allows for managers with incentives to overinvest in capital and to acquire excessive debt [65]. When digital transformations accompany innovations, they enhance value creation in products and services offered in the market to create digital dividends and foster entrepreneurship [66].

Startups created for entrepreneurial independence give rise to a relatively broad category needed to include the goal of analyzing different entrepreneurial lifestyles to pursue some entrepreneurial preferred leisure activities, hobbies, and avocations [24]. The motivation for independence leads the individual to try harder because every effort generates a direct personal benefit, which leads to the generation of new opportunities to grow. Different lifestyle firms provide their owners with the opportunity to follow a particular lifestyle while earning a living [67]. We argue that entrepreneurs endowed with a strong sense of independence are motivated to expand their firms. Hence, if entrepreneurs choose greater independence, we also expect a positive relationship for their aspiration to grow. As a result, hypothesis 2 can be drawn as follows:

H2: 

Entrepreneurial independence increases entrepreneurial growth aspirations.

2.3. The Moderating Role of Household Income

Individuals coming from high-income families may be interested in more lucrative business opportunities than low-income individuals, as entrepreneurs endowed with enormous financial wealth will intend to achieve a higher standard of living [68]. Higher socioeconomic wealth provides more considerable financial resources, which allow entrepreneurs to undertake larger size venturing before using external sources of funding. Besides, the opportunity cost of being a nascent entrepreneur measured by the household income has a positive effect on growth aspirations [61], especially in high-income groups, where high expectation entrepreneurial activity is overrepresented [58]. Household income was shown to be a particularly strong predictor emphasizing the importance of financial assets and social capital for entrepreneurial growth expectations [42].

However, if no or only low levels of resources are available, growth is difficult to achieve regardless of whether motivation exists. The Theory of Planned Behavior has been successful in predicting behaviors under limited volitional control. The effect of opportunity motivations on growth aspirations is a function of the extent to which the individual can decide at will to attempt to perform the behavior, and the probability that is trying to complete the action will lead to a successful outcome. Behavioral control, in turn, is influenced by the individual’s access to resources and opportunities to exert the behavior [17,18,20]. Therefore, in predicting entrepreneurial growth aspirations, it is essential to assess the specific resources and opportunities that may affect growth.

We suggest household income may have a moderating effect on the relationship between opportunity motives and entrepreneurial growth aspirations for several reasons. First, entrepreneurial households tend to have a greater incentive than employee households to generate considerable sums of household income, both because of their need to offset substantial earnings risks and also to reduce the requirement for costly external finance [69,70]. Unlike employees with regular salary payments and some confidence in job continuity, entrepreneurs face a considerable risk that future lump sums may not accrue due to the high potential for downturns in business fortunes. Hence, the incentive to earn money and save is much stronger in entrepreneurial households than in employee households. In practice, therefore, entrepreneurs have both the means and the motive to accumulate wealth and, given the opportunity, will do so [71].

Second, household income is an essential determinant of one’s social class, so high-income households may have stronger motives to increase their financial wealth and attain independence, and they, therefore, may get to see better entrepreneurial growth opportunities. This creation of startups is stronger when entrepreneurs make use of their savings to create and grow the company from 3F (family, friends, and self-financing) schemes without relying on external financing. Third, it may be that high-income households are only better able to act on business opportunities they see by mobilizing their household wealth for the pursuit of their opportunity motivations. Fourth, high household income may also create a stronger expectation for individual autonomy, lifestyle, and freedom, the pursuit of which could then be reflected in entrepreneurial growth aspiration [72]. As a result, Hypotheses 3a and 3b can be drawn as follows,

H3a: 

Household income positively moderates the effect of increased wealth motive on entrepreneurial growth aspirations.

H3b: 

Household income positively moderates the effect of independence motive on entrepreneurial growth aspirations.

To identify the determinants that might increase the growth aspirations of new entrepreneurs, we propose and empirically test a motivation-based model of growth aspiration (Figure 1).

3. Methodology

3.1. Data and Sample

The Global Entrepreneurship Monitor (GEM) dataset provides unique information on entrepreneurs’ characteristics, ranging from standard socio-demographic characteristics to more specific entrepreneurial traits, perceptional, and attitudinal variables. We can also distinguish between the opportunity and necessity-driven entrepreneurship and high and low growth aspiration ventures. For this study, we will focus on opportunity-driven and growth-oriented entrepreneurship.

The data used in this paper were collected through the National Adult Population Survey [73]. We merged cross-sectional data from all years that the GEM project has been conducted in Mexico (2001, 2002, 2005, 2006, 2008, 2010, 2011, 2012, 2013, and 2014). The GEM data examine entrepreneurial activity while capturing the broadest possible range of business creation activities. Thus, we can distinguish between individuals who are actively involved in setting up a business (nascent), those who are currently owner-managers of a new firm (new), and those who are owner-managers of established business (established).

In this study, we selected the individuals defined as new entrepreneurs, which are those who are currently owner-managers of a business that has paid salaries, wages, or any other payments to the owners for more than three months, but not more than 42 months (814 new entrepreneurs). This category adequately serves the purpose of our study because growth aspirations refer to firms already in existence. The new firm category also provides excellent coverage of the current level of employment used in defining our dependent variable, so this leads to a valid sample of 191 new entrepreneurs.

According to the Mexican Institute of Statistics (INEGI), between 350 and 400 thousand new firms in the country are being created each year, but half-close the first year and only 10 percent will last more than five years. In 10 years, there will be a population of around 80 thousand new firms, considering that this number the optimal sample size is determined by

$$n=\frac{z^{2}pqN}{e^2\left(N-1\right)+pq{z}^2}$$

(1)

where:

n Size of the random sample

z Critical value of the standard normal for a confidence level (z = 1.96). In this study, the confidence level is 95 %

e Error (0.08)

N Annual population size (80,000)

pq Degree of heterogeneity. With absolute uncertainty (p = q = 0.5), this value maximizes.

Under the above expression, the minimum sample size required is 150 units (95% confidence level), and our final sample was 191.

3.2. Variables and Measures

3.2.1. Entrepreneurial Growth Aspirations

According to GEM, opportunity-driven entrepreneurs are those who, despite being able to obtain employment, choose instead to start their own business. An exciting but small sub-segment of opportunity-driven entrepreneurs is made up of individuals who aspire to create a growth-oriented firm. GEM’s data on growth expectations of new entrepreneurs are measured in terms of the number of jobs to be created within the next five years. This variable is continuous. As the distribution was biased, a natural logarithm of expected jobs was used.

3.2.2. Opportunity Motives

Respondents in the GEM Adult Population Survey were first asked to indicate whether they are involved in a start-up to take advantage of a business opportunity or because they have no better choices for work. When they indicate to take advantage of a business opportunity, this is considered an opportunity motive, and when they point to have no better choices for work, they are classified as necessity-motivated entrepreneurs. Next, opportunity motivated entrepreneurs were asked to indicate the most crucial motive for pursuing this opportunity, which includes the following elements: increased wealth, independence, maintain income, none of them, and do not know. Based on these questions, we use the indicators which account for the 92% incidence of the entrepreneurial motives:

(a)

Increased wealth motive: the new entrepreneurs declare that their purpose of becoming an entrepreneur was to increase their income, yes = 1.

(b)

Independence motive: the new entrepreneurs declare that their motivation to become an entrepreneur was to obtain greater independence, yes = 1.

3.2.3. Household Income

This GEM variable categorizes household income in thirdtiles according to national distribution (lowest 33%, middle 33%, top 33%). An annual income of the entire household, including the respondent, must be assured. Among new entrepreneurs, high-expectation activity occurs among individuals who belong to the highest third in the household income segment. Thus, we use a dummy variable that indicates whether the entrepreneur declares that their household income is in the upper third.

3.2.4. Controls

Several control variables are included in the analysis. Age mean-centered; Gender (Male = 1); Education (primary, secondary, postsecondary, and graduate experience); Fear of Failure (yes = 1); Current jobs (we controlled for the individual’s current number of employees to capture idiosyncratic variation in initial conditions when analyzing influences on growth expectations. Necessity (the share of entrepreneurs that indicate participation in entrepreneurial activity primarily because they have no other options for work, yes = 1); Industry structure (as a methodological control, we controlled the GEM established business ownership rate (EBO); and Year dummies, the year dummy takes the value 0 for the year 2001 and the value 1 for the years 2002, 2005, 2006, 2008, 2010, 2011, 2012, 2013 and 2014. We have chosen these years, primarily because of two main reasons: (a) the availability of GEM data in Mexico, so there is discontinuity over the years, and (b) this series of years coincides with the ruling in Mexico of the National Action Party, which led to a political change for the first time in 70 years.

The hypotheses were tested using hierarchical regression analysis. The hierarchical approach is necessary to examine whether an interaction effect exists. This fact will be the case if the interaction term gives a significant contribution over and above the individual predictor effects model [74].

4. Results and Discussion

This study takes an essential step towards an increased understanding of entrepreneurial growth aspiration. A substantial part of this paper focused on investigating the extent to which opportunity motivation and household income are related to entrepreneurial aspiration in new Mexican firms. We used the Theory of Planned Behavior as a framework from which we empirically investigated the effects of start-up motives on entrepreneurial growth aspirations and the moderating role of household income. The Theory of Planned Behavior suggests that intentions to perform behaviors of different kinds can be predicted with high accuracy from attitudes toward the behavior, subjective norms, and perceived behavioral control; and these intentions, together with perceptions of behavioral control, account for considerable variance in actual conduct [17].

New entrepreneurs with high growth aspirations should be associated with established firms with higher growth trajectories. Previous studies show a positive relationship between growth intention and firm growth [18,36,37,75,76,77,78,79]. Thus, knowledge of the determinants of growth expectations of newly founded firms has become a primary focus for researchers, policymakers, and other social enterprise organizations interested in scalable ways to drive economic development.

Table 1. Descriptive Statistics.

	Mean	Standard Deviation	Min	Max
Age mean centered	−1.7454	8.32748	−21.34	35.66
Gender	0.4800	0.501	0	1
Education	0.0900	0.293	0	1
Fear of fail	0.2400	0.429	0	1
Current Jobs	2.5490	3.581	0	69
Necessity	0.2304	0.422	0	1
GEM EBO rate	4.0317	1.029	0.40	5.80
Increased wealth motive	0.5400	0.499	0	1
Independence motive	0.3100	0.465	0	1
Household income	0.4900	0.501	0	1
Increased wealth motive x Household income	0.2400	0.429	0	1
Independence motive x Household income	0.1800	0.388	0	1

Legend: GEM (Global Entrepreneurship Monitor), EBO (Established Business Owners). Source: The authors.

shows descriptive statistics. Male entrepreneurs represent 48% of the sample, 9% have the graduate experience, 24% say they have a fear of failure, 49% belong to high households, 86% are opportunity-driven (54% have an increased wealth motive and 31% an independence motive), and 23% are necessity driven. Correlations of the indicator variables used in the model are presented in

Table 2. Correlation Matrix.

	AMC	G	E	F	N	EBO	HI	IM	IWM	CJ
AMC	1
G	−0.022	1
E	−0.080	0.181	1
F	−0.006	−0.029	−0.142	1
N	0.017	−0.024	0.036	−0.046	1
EBO	−0.024	−0.005	0.022	−0.019	−0.061	1
HI	−0.020	0.066	0.118	−0.079	−0.011	−0.080	1
IM	0.038	0.053	0.097	−0.100	−0.076	0.093	0.109	1
IWM	−0.085	0.093	0.069	0.062	0.126	−0.019	−0.065	−0.729	1
CJ	−0.049	0.171	0.170	−0.042	−0.084	0.066	0.139	−0.080	−0.020	1

Legend: AMC (Age mean-centered), G (Gender), E (Education), F (Fear of fail), N (Necessity), EBO (GEM EBO rate), HI (Household income), IM (Independence motive), IWM (Increase wealth motive), CJ (Current Jobs); Source: The authors.

. To investigate potential multicollinearity problems, we calculated variance inflation factors (VIF) for all our variables. We found no indication of multicollinearity problems since all our variables are well below the agreed level of 10. Research model results are shown in Figure 2.

As no value exceeds 0.8, the correlation matrix results show a weak degree of correlation between all the studied elements. Concerning age (column 1), calculated using the age mean-centered, the correlation matrix displays meager (< 0.10) correlation rates, which indicates that senior entrepreneurs (men and women) have a reduced incentive to start a business. With regards to gender (column 2), correlations are also low, and there are no substantial differences between the values, being education the highest correlation value (0.181), followed by current jobs (0.171), which shows that higher educational levels and current jobs both slightly increase the entrepreneurial growth ambition.

Regarding education (column 3), the highest correlation value is shown between education and current jobs (0.170), which shows a small relationship between the level of studies achieved and the jobs obtained. The fear of fail (column 4) shows a low and negative correlation with household income (-0.079), indicating that entrepreneurs slightly reduce their fear of failure when they undertake business. Regarding necessity entrepreneurship, the highest value in column 5 (0.126) shows that entrepreneurs tend to increase their economic wealth. Household income (column 7) has the strongest correlation with current jobs (0.139), which shows that family income comes primarily from the salary and wage earned in the current job. Related to the motivation for independence (column 8), the highest value (0.729) is found when independence is correlated with economic wealth, as individuals endowed with independent earnings are the only ones capable of being employed.

As seen in

Table 3. Hierarchical Regression Results of Entrepreneurial Growth Aspiration.

	Model 1	Model 2	Model 3
Control Variables
Age mean centered	−0.042	−0.094	−0.097
Male	0.268	0.121	0.120
Fear of failure	0.000	0.078	0.109
Education	0.228	−0.214	−0.153
Current Job	0.059***	0.041***	0.046***
Necessity	0.042	0.028	0.043
GEM EBO rate	−0.049	−0.005	−0.014
Predictors
Increased wealth motive (H1)		0.589***	0.336*
Independence motive (H2)		0.594***	0.297
Household income		1.758***	1.214***
Interactions
Increased wealth x household (H3a)			0.584**
Independence x household (H3b)			0.654**
Constant	2.262	0.615	0.792
N	191	191	191
F	3.928	27.358	24.925
R2	0.220	0.710	0.730

Notes: *p < 0.10; **p < 0.05; ***p < 0.01 Year dummies were included for the years 2002, 2005, 2006, 2008, 2010, 2011, 2012, 2013 and 2014. Source: The authors.

, the authors have used hierarchical regression to analyze three models formed by control variables only (model 1), control variables and predictors (model 2), and control variables, predictors, and interactions with financial capital (model 3). The control variables age, male, education, fear of failure, current jobs, necessity, GEM business owner-manager rate, and year dummies were first entered in a base model reported in Table 3, column 1. This model explains a statistically significant share of the variance of the growth aspiration-dependent variable (R² = 0.22, p < 0.001).

The predictor variables were entered in the second model: increase wealth and independence motives. The results are reported in column 2 of the table. The predictors’ effects model makes a significant contribution over and above the base model (R² = 0.71), where the change in R-squared is statistically significant (p < 0.001). Within the model, the findings suggest that both wealth and independence have a statistically significant influence on growth aspirations, but the independence results for this effect are nonsignificant (0.297), while the interaction effect is positive and significant (0.654, p < 0.01), H2 is supported for those entrepreneurs situated in the higher-income levels only. Thus, hypotheses H1a and H1b are supported.

The addition of the interaction terms in the third model gives an explanatory contribution over and above the individual predictor effects model (Column 3). Explained variance increases by 0.71 to 0.73, and the growth is statistically significant at p < 0.10. This fact suggests that interaction effects are indeed present. Examining the regression coefficients of the interaction terms, it is evident that household income positively moderates the relationship between independence and growth aspiration and the relationship between increased wealth motive and growth aspiration. Therefore, hypotheses H2a and H2b are also supported.

Even though explained variance coefficients are high, we found no outlier influencing the sample. Overall, the results of our empirical exercise support our prediction that people for whom increasing wealth is the prime motive for becoming self-employed tend to be job growth-oriented, which suggests that such a purpose is needed for these types of entrepreneurs to achieve the financial gains that they desire. We also find evidence that independence motive contributes to variation. According to our expectations, household income appears to magnify the effects that increased wealth and independence motives have on growth aspiration.

5. Conclusions

This study contributes to the existing academic literature by analyzing entrepreneurial growth aspirations in efficiency-driven economies and empirically examining the moderating effect of household income on the relationship between opportunity motivations and entrepreneurial growth aspirations. Consistent with previous findings and others’ assumptions, we found that opportunity motivation is positively related to the entrepreneur’s intention to expand their business activities. Given the relationship between the increased wealth motive and independence motives concerning aspiration rates, the results of this study also suggest that it is rewarding for policymakers to devote attention to the enhancement of aspiration levels among these entrepreneurs. In Mexico, entrepreneurship policies are already shifting their focus from seeking to increase the number of entrepreneurs to improve the quality of entrepreneurship, which is reflected in the policy focus on high growth entrepreneurship. This fact is an advantage since increased wealth and independence are the two most popular start-up motives that we take into account in our study.

Another interesting finding of this study is that the independent effects model infers that growth aspirations are significantly related to household income. When we jointly consider growth aspirations, opportunity motivations, and household income, we find that household income does indeed play a role – it magnifies the influence that motives have on growth. Given that household income provides more significant opportunities, our findings reinforce the notion from the Theory of Planned Behavior that not only is motivation necessary for behavior, but so are resources and opportunities.

Due to the importance of new firm formations to most economies, such research has important practical implications. For academics, future research should seek to explore the various ways in which policymakers can stimulate people to start their businesses to pursue material gains and or independence. For policymakers, our results suggest that promoting a higher prevalence of the increased wealth and independence motives in the population of entrepreneurs seems to be a somewhat advantageous avenue when aiming to support a higher rate of ambitious entrepreneurship. Furthermore, our results imply that they should be aware that entrepreneurs motivated to start a firm to strive for independence are likely to have a high aspiration for their business and therefore are probably the ones making a significant contribution to the country’s employment creation and economic growth.

Nevertheless, there is considerably more to learn about an entrepreneur’s growth aspiration. We have taken an important step; however, we must point out some limitations: the nature of the cross-sectional GEM dataset; even though dummies were introduced, the period of time is too long, and economic conditions may vary; the exclusion of less common motives that may influence growth aspirations; and the relative coarse-grained measurement of purposes. As future lines of research, we suggest the size of household income as the proxy variable of financial capital be strengthened by a multi-item operationalization, as well as the assessment of country culture and income level since they may stem from individual differences in opportunity-driven entrepreneurship, motives, and their combination. Finally, another line of research may be the extension of this study to other countries and to thus undertake a comparative study.