This study empirically investigates factors influencing satisfaction levels of founders of new ventures, using a representative sample of 1,107 Dutch founders. We relate entrepreneurial satisfaction (with income, psychological burden and leisure time) to firm performance, motivation and human capital. Founders with high levels of specific human capital are more satisfied with income than those with high levels of general human capital. Intrinsic motivation and that of combining responsibilities lowers stress and leads to more satisfaction with leisure time. Women are more satisfied with their income than men, even though they have a lower average monthly turnover.
Hinweise
We are grateful to both referees who helped us to improve our analysis.
1 Introduction
The majority of entrepreneurs prefer to manage a venture that is successful and that provides them with sufficient financial means to live a comfortable life. For many aspiring entrepreneurs the reality does not meet their initial expectations. In fact, failure rates among start-ups and new ventures can amount up to sixty percent within the first 5 years (Cooper et al. 1988; Phillips and Kirchoff 1989) and the average income of the self-employed is often well below that of comparable employed individuals (Hamilton 2000). Still, each year there are many individuals who start new firms, indicating that there are other (intrinsic) factors motivating people to pursue an entrepreneurial career. Several studies show that self-employed individuals are more satisfied with their jobs than employees (Benz and Frey 2008a; Blanchflower and Oswald 1998; Bradley and Roberts 2004; Hundley 2001; Katz 1993; Thompson et al. 1992).
The present study examines the factors influencing satisfaction levels among founders. Satisfaction can be seen as a key measure of individual entrepreneurial success. The utility entrepreneurs derive from their start-up venture is an important determinant of venture survival. The degree of entrepreneurial satisfaction is influenced mainly by venture performance, but may also be affected by personal characteristics, motives for start-up and venture characteristics. Existing research on job satisfaction has primarily concentrated on explaining the satisfaction of employees rather than that of entrepreneurs (Cooper and Artz 1995). We contribute to the literature in three ways.
Anzeige
First, we do not use one measure of overall entrepreneurial satisfaction, but discriminate between three different types of satisfaction. This is relevant as there are many facets of (work) satisfaction. Scarpello and Campbell (1983) argue that global measures of job satisfaction are not equivalent to the sum of the different facets. VandenHeuvel and Wooden (1997) present descriptive evidence that the self-employed are more satisfied than wage earners with their independence, but are not with their income and job security. In the present study we empirically examine the determinants of three types of satisfaction among founders, i.e., with income, with psychological well-being, and with leisure time. Satisfaction with income is particularly relevant for entrepreneurs who start a venture to earn a living or for financial success. Furthermore, an entrepreneurial career can be stressful, in particular during the start-up phase. Psychological well-being has previously been studied as an important career outcome for the self-employed (Andersson 2008; Feldman and Bolino 2000; Jamal 1997). Finally, individuals may differ in terms of their satisfaction regarding leisure time. Income and leisure time are the two traditional main sources of utility in economics (Bonke et al. 2009). Some individuals start a business to combine household and work responsibilities and have more flexible working hours. Others start a business with the aim of growing it into a multi-million enterprise, devoting long working hours to the venture, limiting the number of hours available for other (leisure) activities. High time investments in the business may also come at the expense of the family situation as it often leads to higher levels of work-family conflict (Parasuraman and Simmers 2001).
Second, we introduce new additional factors explaining entrepreneurial satisfaction, including start-up motivation, the distinction between general and specific human capital, and venture-specific controls. Start-up motives are likely to impact entrepreneurial satisfaction. Existing research has proposed various motives for new venture creation (e.g., Feldman and Bolino 2000). Individuals who start a business because of ‘negative’ (push) factors may be less satisfied than those who start because of ‘positive’ (pull) motives (Jamal 1997; Block and Koellinger 2009). In our study we use two scale measures of motivation: the relative importance of intrinsic motivation, and that of combining work and household/family responsibilities. Also, previous studies have investigated the effect of education on entrepreneurial satisfaction (VandenHeuvel and Wooden 1997; Bradley and Roberts 2004; Clark and Oswald 1996), but thus far have neglected the role of specific types of knowledge and experience. Although education has often been found to negatively affect (job) satisfaction, specific experience may enhance new venture performance and, hence, satisfaction with the newly founded firm. Furthermore, existing research explaining entrepreneurial motivation does not allow for variation between types of ventures in terms of, for example, firm size, complexity of the business environment (e.g., shop around the corner versus high-tech companies), and effort and involvement (e.g., full-time versus part-time commitment). Indeed, start-up entrepreneurs tend to have different ambition levels, which may lead to different expectations and subsequent levels of satisfaction.
A third contribution is that we examine a range of indirect effects of venture performance on satisfaction. Although earlier studies control for venture performance and/or income in explaining satisfaction (Cooper and Artz 1995; Bradley and Roberts 2004), we disentangle direct and indirect effects of performance on satisfaction. For example, level of education may have a negative direct effect on satisfaction because of high opportunity costs, while indirectly enhancing satisfaction through increased firm performance.
Although the literature on entrepreneurial satisfaction is relatively scarce, various scholars have linked ‘overoptimism’ to entrepreneurship (Kahneman and Lovallo 1993; Camerer and Lovallo 1999; Sarasvathy et al. 1998; Arabsheibani et al. 2000). Overoptimism occurs when the expectations of an individual regarding an outcome exceed the realized outcome. Satisfaction may partly be determined by the extent of overoptimism, with the disappointment of overoptimistic entrepreneurs limiting their satisfaction. In this respect, Ferrante (2009) directly connects people’s life satisfaction to a (positive) difference between expected and realized outcomes. Several explanations have been proposed for the overoptimistic nature of entrepreneurs. The heuristic of overoptimism may help entrepreneurs to cope with the information (over)load, time pressure and uncertainty of entrepreneurship and to take timely actions, e.g., developing the new venture before all relevant information is available and known (Busenitz and Barney 1997). There is the possibility of self-selection with entrepreneurship attracting a certain type of (overoptimistic) people (Forbes 2005; Åstebro et al. 2007). Overoptimism does not necessarily preclude satisfaction. Entrepreneurs may adjust their expectations ex-post and believe that the entrepreneurial experience is satisfactory despite initial unrealistic expectations.1
Anzeige
We examine the determinants of satisfaction among founders using a large representative sample of 1,107 entrepreneurs in The Netherlands who manage new ventures of less than one-year-old. The data set contains information on a wide range of personal and venture characteristics and distinguishes between three facets of satisfaction. Satisfaction with income, leisure time and psychological well-being are important indicators of the amount of ‘utility’ derived from an occupation and entrepreneurship in specific.
2 Determinants of Entrepreneurial Satisfaction
Some entrepreneurs are more satisfied with their ventures than others. In this study we link entrepreneurial satisfaction to performance and four types of factors: human capital (general and specific), start-up motivation, individual-specific and venture-specific control factors. These factors may have both a direct and indirect effect (via performance) on satisfaction. See Fig. 1. In this study we discriminate between three different types of satisfaction: with respect to income, psychological well-being and leisure time.
Fig. 1
Explaining entrepreneurial satisfaction
×
The first factor is human capital. We expect that entrepreneurs who possess higher levels of specific (or relevant) human capital at the time of start-up have more realistic expectations and, accordingly, are more likely to be content with financial performance or non-monetary utility derived from the business (e.g., psychological well-being, leisure time). The opposite will be true for high levels of general human capital, which are expected to boost the expectations of individual entrepreneurs and make it more difficult to achieve satisfaction. Second, we expect that the motivation for starting up a business will be related to individual satisfaction. Start-up motives of entrepreneurs can have important consequences for the degree of satisfaction as entrepreneurs are expected to evaluate performance by linking firm outcomes to their initial goals and expectations. In addition, we control for individual- and venture-specific characteristics. Next to direct effects on entrepreneurial satisfaction, we take into account that these factors may affect satisfaction through venture performance.
In the remainder of this section we will discuss the determinants of entrepreneurial satisfaction in more detail.
2.1 Specific and General Human Capital
Founders differ in terms of the amount of relevant human capital they require and possess. They may start in distinct business environments, requiring different types and levels of knowledge and information. Individuals who are well-informed about the possible consequences of their choices are more likely to be satisfied with the end result. A distinction is usually made between general and specific or relevant human capital, for example, discriminating between education level and experience (Becker 1993; Castanias and Helfat 2001). Education has been found to negatively affect entrepreneurial satisfaction (VandenHeuvel and Wooden 1997; Bradley and Roberts 2004; Clark and Oswald 1996). Highly educated self-confident entrepreneurs may have a hard time meeting their own high expectations and have difficulty compensating for their high opportunity costs. Indeed, Ferrante (2009) finds that higher educated people are more likely to regret forgone opportunities. Also, well-educated entrepreneurs may be more likely to overestimate their abilities to run a venture and become disappointed than entrepreneurs with lower levels of education.
It is important to distinguish between formal education and relevant (or pertinent) human capital (Bhandari and Deaves 2006), the latter which can be acquired through experience with, for example, managerial tasks and the industry. Entrepreneurs who performed related activities in their past career, can be expected to be more realistic (Fraser and Greene 2006; Cooper et al. 1988) and therefore more likely to be satisfied. Nevertheless, experience may not always enhance satisfaction. Bradley and Roberts (2004) do not find a significant effect of entrepreneurial experience on satisfaction levels of entrepreneurs. Wright et al. (1997) indicate that serial entrepreneurs are less able to recognize their own limitations than first-time entrepreneurs. In addition, Hayward et al. (2006, p. 165) claim that experienced founders may be overconfident when the nature of their venture differs from that of previous endeavors.
2.2 Start-Up Motivation
Salinas-Jiménez (2010) argue that differences in motivations have an important effect on levels of satisfaction and that moving from extrinsic to intrinsic motivation leads to greater satisfaction (with life). There are various motives for new venture creation (Gilad and Levine 1986; Feldman and Bolino 2000). In addition to the financial benefits of starting up a business, there are several non-pecuniary rewards, including the wish to be independent, the entrepreneurial challenge and the possibility of combining work and household responsibilities (Amit et al. 2001). Hamilton (2000) claims that these non-pecuniary benefits of self-employment must be substantial as the pecuniary rewards are often disappointing. Two important intrinsic start-up motives include that of being your own boss and the challenge of entrepreneurship (Feldman and Bolino 2000). Individuals who are motivated by these non-pecuniary benefits will probably be less disappointed by unexpected financial hardship or unforeseen stress and excessively long working hours. Cooper and Artz (1995) find that non-monetary goals positively relate to satisfaction. Similarly, Benz and Frey (2004, 2008b) find the greater independence and autonomy of self-employment increases job satisfaction. Finally, according to Jamal (1997, p. 55) individuals who are ‘pushed’ into self-employment because no other job was available, may experience less satisfaction. This result was recently confirmed by Block and Koellinger (2009) for German nascent entrepreneurs.
The combination of work and household responsibilities appears an important consideration at firm start-up for a substantial number of entrepreneurs, but in particular for women (Wellington 2006, p. 359). The motive of combining responsibilities may especially lead to more satisfaction with leisure time and flexibility of working hours.2 Individuals who start a business from the perspective of combining responsibilities may be better aware of and prepared for the necessary time investments in entrepreneurship.
2.3 Performance
Next to the direct effects on satisfaction, we test for indirect effects through firm performance. Firm performance is an obvious determinant of satisfaction with the venture (e.g., Cooper and Artz 1995). This is in line with the positive income effect on job satisfaction, specifically satisfaction with respect to pay (Gazioglu and Tansel 2006). An obvious example of an indirect effect through venture performance on satisfaction with income is that of general human capital. It is also sometimes claimed that women entrepreneurs financially underperform vis-à-vis their male counterparts, which could again negatively affect their satisfaction with income.
2.4 Individual-Specific Controls
Several studies have investigated the effect of socio-demographic factors such as age, family situation and gender, on job and life satisfaction. We take these factors into account when explaining entrepreneurial satisfaction. Furthermore, we incorporate the element of risk tolerance to control for differences in coping with business (mis)fortune across entrepreneurs. We include the following four individual-specific controls in the analysis:
2.4.1 Gender
There may be a gender bias in expectations regarding the performance of the newly founded venture. Several studies show that women report higher levels of job satisfaction than men do (VandenHeuvel and Wooden 1997; Clark 1997; Clark et al. 1996). Similarly, Cooper and Artz (1995) find that female entrepreneurs are, ceteris paribus, more satisfied with the business than their male counterparts. Gender differences in overconfidence appear to be highly task-dependent (Lundeberg et al. 1994) and greatest for tasks that are perceived to be masculine, such as entrepreneurship (Beyer and Bowden 1997). Gazioglu and Tansel (2006) also point out that there may be a participation effect, i.e., women are often secondary bread-winner, and may sooner opt for exit when dissatisfied.
2.4.2 Age
A U-shaped relationship between age and satisfaction has been found for both wage- and self-employed individuals (Clark et al. 1996; VandenHeuvel and Wooden 1997; Bradley and Roberts 2004; Gazioglu and Tansel 2006). Higher levels of reported job satisfaction among older workers may reflect seniority-related benefits, lower job expectations and self-selection effects. Indeed, Forbes (2005) provides evidence that overconfidence, and a subsequent higher chance of being dissatisfied, is more prevalent among younger than older entrepreneurs.3
2.4.3 Life Partner
A life partner may reduce stress related to the business by sharing problems and (s)he may earn an income that provides the entrepreneur with financial security. Clark et al. (1996) find that married employees experience higher levels of job satisfaction, in particular in terms of satisfaction with pay. Blanchflower and Oswald (1998) report a positive effect of marriage on overall happiness, which is valid for all employed individuals (wage- or self-employed).4 In addition, they find negative effects of being without a partner as is found in the case of widowed, divorced or separated individuals.
2.4.4 Risk Tolerance
Entrepreneurs on average have a higher level of risk tolerance than employees (Kihlstrom and Laffont 1979). However, even among entrepreneurs risk tolerance may vary considerably. Risk tolerant entrepreneurs may be more likely to appreciate disappointing business results as a possible side effect of the entrepreneurial adventure. Parker (2006, p. 353) argues that risk averse entrepreneurs feel pressured to work longer hours to avoid poor performance and therefore may also be less content with psychological well-being and available leisure time. Block and Koellinger (2009) present some evidence that risk tolerance is positively related to start-up satisfaction.
2.5 Venture-Specific Controls
The effect of characteristics of the newly founded business on entrepreneurial satisfaction thus far did not receive any attention in the literature. Nevertheless, it can be expected that the nature of the business affects the degree of entrepreneurial satisfaction. In the present study we discriminate between three key venture characteristics:
2.5.1 Size
Larger new ventures usually come with higher responsibility and expectations and may also involve more stress. On the other hand, large start-ups usually require more preparation and have to deal with outside supervision, e.g., by capital suppliers, thereby reducing the chance of unexpected misfortune. As measures of firm size we include the number of employees, the amount of start-up capital, and whether the business operates from the home or a separate business premises. Starting and running a business from the home may be an indicator of prudence on the part of the entrepreneur, and may affect perceived psychological stress and leisure time.
2.5.2 Complexity
Greater environmental complexity may lead to less satisfaction as the entrepreneur is confronted with multiple sources of unexpected setback. In addition, managers who introduce pioneering products tend to be more overoptimistic than those who pursue incremental innovations (Simon and Houghton 2003), diminishing subsequent entrepreneurial satisfaction. We use two measures of complexity: whether the start-up is in a high-tech sector, and whether the entrepreneur believes (s)he is able to keep up with all relevant developments.
2.5.3 Involvement
The allocation of time to various entrepreneurial tasks may vary considerably across start-ups. Entrepreneurs who are confronted with substantial time pressure may derive less satisfaction from their enterprise. This is in line with the negative effect of working hours on job satisfaction as reported by, e.g., Clark et al. (1996) and Gazioglu and Tansel (2006). We expect that entrepreneurs who are dependent upon the income out of the firm for subsistence show more commitment than ‘part-time’ entrepreneurs. Demanding side-activities may increase time pressure and stress, while the opposite holds for outsourcing of tasks.
3 Methodology
3.1 Data
We use data of a unique and detailed panel survey of the research institute EIM, which was commissioned by the Dutch Ministry of Economic Affairs. A large and representative sample was drawn of independent new ventures registered at the Chamber(s) of Commerce in the first half year of 1994 in the Netherlands. This has been the most extensive sample in terms of available information across the years of sampling. The distribution of firms was representative across sector and size class. Only main establishments were selected. The following firms were excluded: agricultural firms and companies extracting minerals, businesses that changed legal form or activity, and relocated firms. About 12,000 firms were approached by telephone of which approximately 3,000 participated in the survey. These firms received a questionnaire by mail. Of these questionnaires 1,938 were completed and returned, mainly by firms that were in existence between 6 months and 1 year. The present study uses the subset of 1,107 entrepreneurs who are either owners or owner-managers and for which information is available for all variables included in the present study.
3.2 Measuring Entrepreneurial Satisfaction
We use a single-item measure of the degree of satisfaction, asking entrepreneurs whether the outcomes of their new venture are in line with their initial expectations. Answer categories range from (1) “much worse than expected” to (5) “far better than expected”. Similar measures of self-reported satisfaction have been applied in the areas of customer satisfaction (Peterson and Wilson 1992), self-employment satisfaction (VandenHeuvel and Wooden 1997), and job satisfaction (Wanous et al. 1997). Both Wanous et al. (1997) and Scarpello and Campbell (1983) argue that a single-item measure of overall job satisfaction is preferable to a measure combining items. The present study interprets the answers as cardinal. Ferrer-i-Carbonell and Frijters (2004) show that using the measures as either cardinal or ordinal hardly affects the results of estimations of the determinants of happiness.
Our measure of satisfaction is a relative one, capturing how founders evaluate the current situation (actual experience) with what they initially expected. We consider a person who has his or her expectations on running a business (clearly) not met, met or even (clearly) exceeded as (very) unsatisfied, neutral or (very) satisfied, respectively. Recent studies on satisfaction that compare the actual situation with what could be expected, include Stutzer (2004); Senik (2009) and Boes et al. (2010). They show that the comparison of an individual's own income with that of their parents, peers or with what they earned in the past, is an important driver of subjective well-being.
The outcomes of the new venture after 1 year of operation can be expressed in terms of income, psychological burden or leisure time, which are separately measured in the survey. Correlations between the three different variables of satisfaction indicate that these are related, yet separate, constructs. The correlation coefficient is highest for the relationship between satisfaction with leisure time and that with psychological burden, and amounts to 0.352 (p < 0.01). Satisfaction with income is relatively different from that with psychological burden and leisure time as correlation coefficients amount to 0.212 (p < 0.01) and 0.075 (p < 0.05), respectively.
3.3 Independent Variables
An overview of the independent variables can be found in Table 1. The effect of general human capital on satisfaction is tested by way of two variables: Education and EntExperience. The latter variable captures general experience with entrepreneurial activity. We control for the effect of more specific entrepreneurial experience by including the job similarity variable. The effect of specific human capital is tested using the variables JobSimilarity and FinManExperience. We combine the two motivations of ‘the wish to be independent’ and ‘the challenge of starting and running a business’ into one variable: Intrinsic. This variable represents the extent to which these two main intrinsic motives play a role in the start-up decision.5 The variable Combine captures the extent to which the combination of responsibilities plays a role in the start-up decision.6Performance is measured in terms of average monthly turnover.
Table 1
Variable description
Variable name
Variable description
Mean
Std.
min
Max
Satisfaction with respect to income
Thus far, is the income you retrieved from your business in line with your expectations? [1 = much worse than expected; 2 = a bit disappointing; 3 = similar to expectations; 4 = better than expected; 5 = far better than expected]
3.16
0.87
1
5
Satisfaction with respect to psych. burden
Thus far, is the psychical burden of starting up a business in line with your expectations? [1 = much worse than expected; 2 = a bit disappointing; 3 = similar to expectations; 4 = better than expected; 5 = far better than expected]
3.24
0.87
1
5
Satisfaction with respect to leisure time
Thus far, is your (remaining) leisure time in line with your expectations? [1 = much worse than expected; 2 = a bit disappointing; 3 = similar to expectations; 4 = better than expected; 5 = far better than expected]
3.03
0.91
1
5
Performance
What is your average monthly turnover? [1 = <fl.1,000; 2 = fl.1,000–fl.2,500; 3 = fl.2,500-fl.5,000; 4 = fl.5,000–fl.10,000; 5 = fl.10,000–fl. 20,000; 6 = fl.20,000–fl.50,000; 7 = > fl.50,000-fl.100,000; 8 = >fl.100,000]a
3.18
1.91
1
8
Education
What is your highest level of education? [1 = average second. education; 2 = higher second. education; 3 = low-level vocat. training; 4 = Leerlingstelselc; 5 = mid-level vocat. training; 6 = high-level vocat. training; 7 = university]
4.39
1.85
1
7
EntExperience
Did you run a business prior to the start-up of this firm? [0 = no; 1 = yes]
0.08
0.28
0
1
JobSimilarity
To what extent are your current activities related to past work? [1 = not at all; 2 = somewhat similar; 3 = identical]
2.01
0.76
1
3
FinManExperience
Did you have experience with financial management prior to the start-up of this firm? [1 = no; 2 = a little; 3 = quite some; 4 = a lot]
2.04
0.97
1
4
Intrinsic
To what extent did intrinsic motives play a role in the start-up decision? Calculated as the importance of two intrinsic motives (wish to be your own boss; challenge) as a share of the importance of all other motivesb
0.24
0.05
0.10
0.38
Combine
To what extent did the combination of work and household responsibilities play a role in the start-up decision? Calculated as the importance of combining responsibilities as a share of the importance of all other motivesb
To what extent do you dare to take risk? [1 = very weak…5 = very strong]
3.77
0.80
1
5
Employees
How many employees do you have? (in FTEs = people who work more than 32 h per week)
0.35
1.60
0
21
Subsistence
To what extent are you dependent on the profits from your business for subsistence? [1 = not at all…4 = completely]
2.23
1.18
1
4
OtherHours
At the start of your firm, how much time did you spend on other activities? [0 = 0; 1 = 1–9; 2 = 10–19; 3 = 20–39; 4 = >40 h]
1.59
1.67
0
4
FirmStatus
What is the status of your firm? [1 = newly started firm; 2 = restart existing firm; 3 = take-over]
1.24
0.63
1
3
StartCapital
What is the total amount of start-up capital? [1 = <fl.10,000; 2 = fl.10,000–fl.25,000; 3 = fl.25,000–fl.50,000; 4 = fl.50,000–fl.100,000; 5 = fl.100,000–fl. 250,000; 6 = fl.250,000–fl.500,000; 7 = >fl.500,000]a
2.13
1.46
1
7
Outsourcing
Are certain activities within the firm contracted out? [0 = no; 1 = yes]
0.44
0.50
0
1
HomeBase
Do you run your business from the home? [0 = no; 1 = yes]
0.69
0.46
0
1
ManuCons
Do you run a business in manufacturing or construction? [0 = no; 1 = yes]d
0.12
0.33
0
1
WholeRetail
Do you run a business in wholesale or retailing? [0 = no; 1 = yes]d
0.30
0.46
0
1
KeepUp
Are you able to keep up with all relevant developments in your line of business? [1 = not really…4 = to a large extent]
3.17
0.71
1
4
Hightech
Is the sector you operate in characterized by rapid technological developments? [1 = no; 2 = somewhat; 3 = yes]
1.48
0.74
1
3
aMeasured in Dutch guilders (florin). One guilder is equivalent to 0.45 Euro
bOther motives include: (risk of) unemployment; dissatisfaction with wage job; opportunity to leave wage job with bonus or taking along customers; available own funding; grown into it; exploiting profit opportunity; earn more money than in wage employment; combine responsibilities; no other choice. The respondents could rate them as follows: 1 = not important; 2 = to some extent; 3 = very important
cHere students combine school with a minimum of 20 h work
dThe category ‘personal and business services’ is the base category
3.4 Control Variables
We include the following control variables in our analysis. The personal characteristics are measured by a gender dummy, Female, an Age variable and the square of this variable, a LifePartner dummy variable and self-reported risk attitude, RiskTolerance, respectively. The venture characteristics are the following. Employees represents the number of fulltime employees. Subsistence captures the extent to which entrepreneurs are dependent on the financial revenues from the business. OtherHours represents the time spent on side-activities (e.g., family care, hobbies, schooling). FirmStatus measures whether the firm is newly started, restarted, or a takeover of an existing business. We control for size differences across the young firms in our sample by taking into account the amount of start-up capital, StartCapital. This is a categorical variable with seven size classes, ranging from relatively small (<4,500 Euro) to substantial start-ups (>225,000 Euro). The variable Outsourcing measures the degree to which entrepreneurs contract out certain activities. HomeBase measures whether a business is run from the home or business premises. ManuCons and WholeRetail capture industry effects. We distinguish between three types of industries: ‘manufacturing and construction’ (ManuCons); ‘wholesale and retailing’ (WholeRetail) and the base category of ‘other industries’ (mainly personal services). Finally, we control for the dynamics of the business environment and required knowledge by including two variables: KeepUp, indicating the extent to which entrepreneurs are able to keep up with relevant developments in their line of business, and Hightech, capturing the degree of technological advancement in the sector.
4 Analysis and Results
The results of the OLS regression explaining satisfaction are presented in Table 2.7 The explanatory power of the models for the three types of satisfaction is limited. This is in line with relatively low R2s in previous studies explaining job satisfaction (e.g. Fuchs-Schündeln 2009; Blanchflower and Oswald 1998; Bradley and Roberts 2004). The general human capital variables Education and EntExperience have the expected negative effect on satisfaction with income. Entrepreneurial experience also seems to limit satisfaction with psychological burden. The specific human capital variables of job similarity and experience with financial management significantly increase satisfaction with income and with leisure time, respectively.
Table 2
Explaining satisfaction with income, psychological burden, leisure time
Satisfied with…
Income
Psychological burden
Leisure time
Constant
1.838***
(6.0)
2.051***
(6.4)
2.732***
(8.2)
Performance
0.144***
(7.1)
−0.036*
(−1.7)
−0.089***
(−4.1)
Education
−0.033**
(−2.3)
0.002
(0.1)
0.008
(0.5)
EntExperience
−0.157*
(−1.7)
−0.177*
(−1.8)
−0.050
(−0.5)
JobSimilarity
0.099***
(2.7)
−0.001
(−0.0)
0.024
(0.6)
FinManExperience
0.020
(0.7)
0.036
(1.3)
0.067**
(2.3)
Intrinsic
0.313
(0.6)
1.214**
(2.2)
0.572
(1.0)
Combine
1.320*
(1.7)
1.778**
(2.1)
3.047***
(3.5)
Female
0.110*
(1.7)
−0.199***
(−3.0)
−0.127*
(−1.8)
Age
−0.024
(−0.3)
0.094
(1.2)
0.006
(0.1)
Age2
0.001
(0.1)
−0.005
(−0.7)
−0.001
(−0.2)
LifePartner
0.042
(0.6)
0.040
(0.5)
0.092
(1.2)
RiskTolerance
0.080**
(2.4)
0.103***
(3.0)
0.010
(0.3)
Employees
−0.016
(−0.9)
−0.001
(−0.0)
0.010
(0.5)
Subsistence
0.035
(1.3)
−0.034
(−1.2)
0.020
(0.7)
OtherHours
0.032*
(1.8)
−0.026
(−1.4)
−0.058***
(−3.0)
FirmStatus
−0.045
(−1.0)
0.030
(0.6)
−0.157***
(−3.0)
StartCapital
−0.057**
(−2.5)
-0.031
(−1.3)
0.048*
(1.9)
Outsourcing
0.038
(0.7)
0.016
(0.3)
−0.031
(-0.5)
HomeBase
0.094
(1.4)
0.018
(0.3)
0.123*
(1.7)
ManuCons
−0.081
(−1.0)
−0.043
(−0.5)
−0.030
(−0.3)
WholeRetail
−0.239***
(−4.0)
−0.076
(−1.2)
−0.012
(−0.2)
KeepUp
0.144***
(4.0)
0.098***
(2.6)
0.028
(0.7)
Hightech
−0.056
(−1.6)
−0.024
(−0.6)
−0.065*
(−1.7)
N
1,107
1,107
1,107
R2
0.133
0.051
0.070
* Refer to significance levels of 0.10 (two-sided test)
** Refer to significance levels of 0.05 (two-sided test)
*** Refer to significance levels of 0.01 (two-sided test)
t values are presented between brackets
We find that intrinsic motives only enhance satisfaction with psychological well-being. Thus, founders appear better able to cope with stress when intrinsically motivated. We do not find a significant relationship between intrinsic motivation and satisfaction with income and leisure time. Entrepreneurs motivated by combining work and family care score higher on all three facets of satisfaction. Apparently, entrepreneurs who balance work and family care are well aware of the demands of self-employment, and benefit from having more flexible working hours. This is in line with Hamilton (2000) arguing that entrepreneurs enjoy the non-pecuniary benefits of self-employment.
Women and men clearly differ regarding satisfaction with their new venture. Women appear more satisfied with income than men, but are less content with the lack of available leisure time and the psychological demands of running a new business. The latter result is in line with previous evidence that women tend to be more vulnerable to (di)stress (Vermeulen and Mustard 2000). Neither Age nor LifePartner have an effect on satisfaction. Entrepreneurs who report high risk tolerance also indicate to be more satisfied with income and psychological burden. These entrepreneurs appear less upset when confronted with low business performance.
There are several interesting effects of the venture-specific control variables. A takeover reduces rather than enhances satisfaction with leisure time. Entrepreneurs seem to underestimate the challenges of running a business perhaps assuming that an existing business requires less time and effort than creating a new venture. Entrepreneurs who start new ventures with a sizeable amount of start-up capital are less satisfied with income even when firm performance is corrected for. Apparently, it is difficult to achieve a satisfactory rate of return on invested capital in the first year after start-up. Entrepreneurs who start wholesale and retail firms appear less content with income than entrepreneurs in other sectors. This might be related to relatively low entry barriers, and therefore higher competition, in these sectors.8 Finally, environmental complexity lowers the level of satisfaction: entrepreneurs who run high-tech firms and who have difficulty keeping up with relevant industry developments are on average less content.
Performance has a positive effect on satisfaction with income. Firm performance also has a significant effect on the two non-pecuniary types of satisfaction. Remarkably, this effect is negative, although only significant at the 10 percent level for psychological well-being. Apparently, financial success comes at a price. Table 3 shows the OLS regression results explaining firm performance.9 Six variables with significant direct effects on satisfaction with income, also significantly influence performance. These are JobSimilarity, Female, OtherHours, StartCapital, WholeRetail and KeepUp. There are also variables that only have an indirect impact on satisfaction. These are LifePartner and six venture-specific controls. Hence, for example, male entrepreneurs who have a life partner, run a larger venture, have previous relevant work experience, have few time-demanding side-activities, who outsource business tasks, and who are able to keep up with industry developments, tend to have relatively high monthly revenues. This provides support for a indirect effect of performance next to the direct effects.10
Table 3
Explaining performance (average monthly turnover)
Coefficient
t value
Constant
−0.280
(−0.6)
Education
0.015
(0.7)
EntExperience
0.039
(0.3)
JobSimilarity
0.234***
(4.3)
FinManExperience
0.060
(1.5)
Intrinsic
−0.434
(−0.6)
Combine
−1.227
(−1.0)
Female
−0.413***
(−4.3)
Age
0.024
(0.2)
Age2
−0.001
(−0.1)
LifePartner
0.496***
(4.7)
RiskTolerance
0.065
(1.3)
Employees
0.170***
(6.5)
Subsistence
0.285***
(7.4)
OtherHours
−0.168***
(−6.3)
FirmStatus
0.477***
(6.8)
StartCapital
0.384***
(11.6)
Outsourcing
0.416***
(5.3)
HomeBase
−0.260***
(−2.6)
ManuCons
0.375***
(3.0)
WholeRetail
0.292***
(3.3)
KeepUp
0.144***
(2.7)
Hightech
−0.031
(−0.6)
N
1,107
R2
0.590
* Refer to significance level of 0.10 (two-sided test)
** Refer to significance level of 0.05 (two-sided test)
*** Refer to significance level of 0.01 (two-sided test)
5 Discussion and Conclusions
This study empirically investigates factors that influence satisfaction levels of recently established entrepreneurs. We find that founders differ in terms of the degree of satisfaction with income, psychological well-being and leisure time. More specifically, founders with high levels of human capital specific to the firm are more satisfied with income than those with high levels of general human capital. Job similarity has both a direct and indirect positive effect (via business performance) on satisfaction with income. Founders who are driven by intrinsic (instead of extrinsic) motivation or who start a business to combine responsibilities, are better able to cope with stress and are more satisfied with their leisure time. This supports Hamilton’s (2000) notion that many self-employed are motivated by non-pecuniary benefits.
Women are more satisfied with their income than men, even though they have a lower average monthly turnover. Women find it more difficult to cope with stress and are less satisfied with their leisure time. Although having a life partner does not contribute to entrepreneurial satisfaction, it does have a positive effect on performance, thereby indirectly affecting satisfaction with income. Entrepreneurs reporting high risk tolerance are more satisfied with their income and are less bothered by stress. Risk tolerant entrepreneurs apparently anticipate on possible set-backs associated with starting a new venture.
Venture-specific characteristics influence entrepreneurial satisfaction mainly indirectly through performance. There is an interesting combination of effects of start-up capital on satisfaction. On the one hand, the amount of start-up capital reduces satisfaction with income directly. This can be attributed to high expectations. On the other hand, the amount of start-up capital enhances business performance, which again indirectly boosts satisfaction. These two effects appear to cancel out. Also, entrepreneurs who run firms in complex environments and lack relevant experience are prone to dissatisfaction, due to, for example, potential pitfalls, underestimation of competition, project duration and the difficulty of finding customers.
Higher firm performance per se does not lead to more happiness among founders. It does not guarantee a higher overall level of satisfaction. Firm performance (of course) increases satisfaction with income, but this comes at the price of lower satisfaction with leisure time.
We mention three limitations of our study. First, the study deals with one country, that is, the Netherlands. Second, we use cross-sectional data, which makes it difficult to test for causality. However, most independent variables are based upon items of an objective nature (facts), limiting problems of reversed causality. Third, we use self-reported data for satisfaction. This may lead to some form of cognitive dissonance, where respondents compare business outcomes to their labor market situation prior to start-up instead of taking into account their initial expectations.
Open Access
This article is distributed under the terms of the Creative Commons Attribution Noncommercial License which permits any noncommercial use, distribution, and reproduction in any medium, provided the original author(s) and source are credited.
Open AccessThis is an open access article distributed under the terms of the Creative Commons Attribution Noncommercial License (https://creativecommons.org/licenses/by-nc/2.0), which permits any noncommercial use, distribution, and reproduction in any medium, provided the original author(s) and source are credited.
Cooper and Artz (1995) find, in fact, that entrepreneurs who were initially more optimistic were more satisfied later, even when controlling for performance.
The two motives of ‘challenge of starting and running a business’ and ‘the wish to be independent’ score clearly as most often mentioned important start-up motives in our survey data. Their average scores are close to 2.5 (on a scale from 1 to 3). The two motive variables are highly correlated and, hence, they were combined into one variable.
Note that the respondents could indicate more than one start-up motive in the questionnaire. Other motives include (threat of) unemployment, dissatisfaction with the current wage job, self-employment due to an occupation (e.g. dentist), perception of a market opportunity and taking over the family business.
We also estimated an ordered logit model because of the categorical nature of the dependent variable. The estimation results are very similar to the OLS results. See also Ferrer-i-Carbonell and Frijters (2004). There are exceptions only for two control variables. Subsistence is significantly positive (p = 0.05) in the ordered logit model for satisfaction with income, while it was not significant in the OLS estimation. HomeBases is not significant in the ordered logit model for satisfaction with leisure time (p = 0.11), while it is significantly positive in the OLS model.
The year before the survey there was a substantial lowering of institutional entry requirements in the Netherlands which led to more entry (Carree and Nijkamp 2001).
We also estimated an ordered logit model because of the categorical nature of the performance variable. There is no change in the significance of the variables as compared to the OLS results.
