Master
Thesis
[
ENTREPRENEURSHIP IN OLDER AGE
]
[Studying the relationship between traits and capabilities of entrepreneurs and age]
1
Summary
The unprecedented population aging out there today will also affect entrepreneurship. It is assumed that age has an inverted U-shaped relationship with. It is also assumed that a long-term relationship exists between the stage of economic development and the ‘equilibrium’ level of business ownership. When combining these two premises one can conclude that an ageing population will results in lower levels of entrepreneurship, and thus in a lower level of macro-economic growth.
Governments actively try to support entrepreneurship. Often, however these policies are not based on scientific research or are opaque about their objectives and how they measured their achievements. This thesis aims to study the relation between age and entrepreneurship in order to develop ways to promote entrepreneurship more effectively by distinguishing different psychological factors, or traits and capabilities that influence the likelihood that people will exploit opportunities. In a future study, the extent to which entrepreneurial traits can be learned can be discussed. Together these studies will hopefully make it possible that entrepreneurship is promoted more effectively in an aging population.
A systematic literature review (SLR) will be performed to come up with hypotheses for the relation of various traits with age. These hypotheses will be tested quantitavely using SPSS with the help of a dataset provided by the company Entrepeneur Consultancy BV owned by Martijn Driessen. This company provides a service called the E-scan; a tool for self-reflection for entrepreneurs and those who wish to start a business. The E-scan is a 76-item questionnaire designed to operationalize ten traits and capabilities of entrepreneurs identified by Driessen (2005).
It was found that there was proof for 5 of the 10 hypotheses. For H1 (there is an inverted shaped relationship between need for achievement and age), H2 (there is an inverted U-shaped relationship between need for autonomy and age) and H4 (there is a positive relationship between social orientation and age) support was found. For H3 (there is an inverted U-shaped relationship between need for power and age) and H8 (there is no relationship between creativity and age) partial support was found. For H5 (there is a negative relationship between self-efficacy and age), H6 (there is a negative relation between endurance and age), H7 (there is an inverted U-shaped relationship between market awareness and age), H9 (there is a negative relation between flexibility and age) and H10 (there is an inverted U-shaped relationship between risk-taking propensity and age) no support was found.
2
people to become entrepreneurs. Creativity and flexibility displayed no relation with age. This however does not mean that these traits cannot be learned. Future research has to determine whether these traits might be learnable. However, this is not necessarily related to the subject of aging.
The first recommendation of this study is that governments should adapt their support services so they can also serve the needs of older (potential) entrepreneurs. They should stimulate those traits that need extra attention. For risk-taking and endurance the results appeared to contradict previous research. Therefore it is difficult to recommend sets of actions on this basis. For need for achievement, need for autonomy, need for power and market awareness no publications were found in the SLR on which hypothesis could be based. Future research might want to study these traits and their relationship with age. Finally, it was found that the gap between entrepreneurial traits and the field of psychology should be bridged.
3
Content
1. Introduction 4
2. Theoretical Background 6
2.1 Entrepreneurship and age 6
2.2 Competence Theory 8
2.3 Trait Theory 10
2.4 Need for achievement 10
2.5 Need for autonomy 11
2.6 Need for power 12
2.7 Social Orientation 13 2.8 Self-efficacy 14 2.9 Endurance 15 2.10 Market awareness 15 2.11 Creativity 16 2.12 Flexibility 17 2.13 Risk-taking propensity 18 2.14 Extraversion 19 2.15 Research Gap 20
2.16 Systematic Literature Review 20
2.17 Traits and Age 24
3 Method 30 3.1 Research Design 30 3.2 Research Sample 30 3.3 Measures 30 3.4 Data Analysis 31 4 Results 32 4.1 Descriptive Statistics 32
4.2 Need for achievement 35
4.3 Need for autonomy 35
4.4 Need for power 36
4.5 Social orientation 37 4.6 Self-efficacy 38 4.7 Endurance 39 4.8 Market awareness 40 4.9 Creativity 41 4.10 Flexibility 42 4.11 Risk-taking propensity 43
4.12 70 year and older 44
5 Conclusion 45
5.1 Discussion 46
5.2 Recommendations 47
5.3 Limitations 48
4
1. Introduction
The population ageing that is out there today is unprecedented in the history of humanity (United Nations, 2009). In the Netherlands this process will double in speed in the period 2011-2015 compared to 2006-2010 (CBS, 2010). In absolute terms this means that during the next five years the number of ’65-plussers’ will increase with half a million. The effects of this trend are hard to foresee but will surely have implications for all facets of human life.
The economic and social impact of population ageing can be viewed as both an opportunity and a threat (United Nations, 1999). On the one hand, socio-demographic changes are an important source of opportunities as they transfer information about allocating resources more productively, create the potential for scale economies, and can cause changes in demand (Shane, 2003). More elderly people means demand will shift for certain products and other products might be developed specifically for this group. Also, more demand means economies of scale might be more easily achieved.
On the other hand, an aging workforce implies a lot of knowledge might be lost, labour shortages might occur and productivity might drop (Strack et al., 2008). Also, fewer workers for each retired person means premiums will have to be raised, which will increase the pressure on the economy (Audretsch and Thurik, 2004). The recent revival of the retirement age discussion in the Netherlands is a clear example of this.
What is also apparent is that due to the population aging a larger part of potential entrepreneurs will be of significant age. These people might have different personalities and face other difficulties than younger people. On the other hand, they might also possess different qualities than younger people do, and have more life experience.
It is assumed that age has an inverted U-shaped relationship with entrepreneurship as it incorporates the positive effect of experience, which increases with age, and the negative effects of opportunity cost and uncertainty premiums, which also increase with age (Bates, 1995; Bönte et al., 2009; Shane, 2003). It is also assumed that a long-term relationship exists between the stage of economic development and the ‘equilibrium’ level of business ownership (Audretsch et al., 2002; Carree et al., 2002; 2007). This suggests that countries where the business ownership rate does not equal the equilibrium rate suffer from a lower rate of macro-economic growth. When combining these two premises one can conclude that an ageing population will results in lower levels of entrepreneurship, and thus in a lower level of macro-economic growth.
5
relationship between age and entrepreneurship should also be studied more extensively in order to supply governments with the right tools to promote entrepreneurship.
This thesis aims to study the relation between age and entrepreneurship in order to develop ways to promote entrepreneurship more effectively. One way to approach the subject of entrepreneurship is to distinguish different psychological factors, or traits and capabilities that influence the likelihood that people will exploit opportunities (Shane, 2003). In order to do so competence theory will be used to investigate the traits and capabilities that make up the competence entrepreneurship and their relationship with age. In a future study, the extent to which entrepreneurial traits can be learned can be discussed. Together these studies will hopefully make it possible that entrepreneurship is promoted more effectively in an aging population. The main research question of this thesis is:
What is the relationship between age and the traits and capabilities that constitute the competence of entrepreneurship?
6
2. Theoretical Background
The origin of the word ‘entrepreneur’ lies in seventeenth-century France, where an entrepreneur was someone who undertook a commissioned commercial project. There are many definitions of an entrepreneur, but any one definition is likely to result in a mismatch with what we expect an entrepreneur to be. Generally there are three directions in defining what an entrepreneur is: (1) the entrepreneur as a manager performing certain tasks, (2) the entrepreneur as an agent of economic change having certain effects on economic systems and (3) the entrepreneur as an individual in terms of their psychology. If the personality and managerial characteristics of entrepreneurs are to be examined then a strict definition of who is an entrepreneur in terms of economic function is required. It cannot be in psychological terms and/or managerial characteristics as this would make the theory self-fulfilling (Wickham, 2006).
Often there is discussion about whether someone who owns a business is an entrepreneur. Scholars differentiate between the routinely aspects and the dynamic aspects of entrepreneurship (Baumol. 1986; Schumpeter, 1934). The dynamic aspects involve change and innovation while the static aspects involve running a business. Here it is argued that entrepreneurs are agents of economic change. Thus, entrepreneurship should also be a process involving change (Carland et al., 1984). A person preserving the status quo is therefore not an entrepreneur. As such, some business owners are not defined as entrepreneurs, while some who do not own a business might be defined as such. Following Schumpeter (1934), an entrepreneur will therefore be defined as an individual whose function it is to carry out new combinations of means of production.
Together these individuals cause value to be created and are changing the equilibrium state of the economy (or disequilibrium; however the emphasis is on the changes they make). This makes it clear that innovation is an essential aspect of entrepreneurship. Also it is important that (economic) value is created for the action to be entrepreneurial. Entrepreneurship can therefore be seen as the act of being entrepreneurial or an entrepreneur. As such, this definition also has to be in economic terms. Following Driessen (2005), the definition of entrepreneurship of Molian and Leleux (1996) will be used:
“At the heart of entrepreneurship is the notion of action arising out of the pursuit of opportunity, as a result of which value is created. The entrepreneur starts with the opportunity and then seeks the resources to
exploit it.”
2.1 Entrepreneurship and age
7
entrepreneurship as it incorporates the positive effect of experience, which increases with age, and the negative effects of opportunity cost and uncertainty premiums, which also increase with age (Bönte et al., 2009; Shane, 2003). It is also assumed that this curvilinear relationship exists for the successfulness of business and age (Bates, 1990; 1995; Bates and Servon, 2000). Figure 1 below displays this relation.
Figure 1. The relation between entrepreneurship and age
There are several reasons why there is a curvilinear relationship between age and exploiting entrepreneurial opportunities. On some traits young people score higher. For example, adolescents are fairly unbiased, energetic, at their peak of physical power (Ryan et al., 2000), and their textbook knowledge is current (Bönte et al., 2009). Also, there is evidence that the ability to process fresh knowledge and reason logically decreases with age (Ruth and Birren, 1985). Most important, the opportunity cost for younger people is lower due to lower income (Lévesque and Minniti, 2006), and their uncertainty is not so high because there time horizons are longer than those of older people (Bönte et al., 2009). Other abilities have yet to develop. For example, adolescents have little or no work experience (Kaufman and Horn, 1996), and lack credibility (Freeman, 1982).
This theory has received consistent empirical support. One set of studies found evidence for this relationship by predicting self-employment with US census data (Borjas and Bronars, 1989; Boyd, 1990; Long, 1982). The same results were obtained using other data sets (Bates, 1995; Sanders and Nee, 1996). Also, age was found to have a U-shaped relationship with the likelihood of venture failure (Bates, 1990; 1995; Bates an Servon, 2000; Taylor, 1996), and an inverted U-shaped relation with the growth of new ventures (Reynolds and White, 1997), and profitability (Borjas and Bronars, 1989; Taylor, 1996).
The fact that entrepreneurship changes with age makes it clear why government policy should not be uniform in approaching (potential) entrepreneurs. In a society in which the elderly take up an increasing percentage of the population, understanding this group becomes more important. Governments have always had the problem of lacking appropriate and up-to-date information. Researching the factors that make up the competence
8
entrepreneurship may be an important source of information for better understanding how to promote entrepreneurship at different age groups.
2.2 Competence Theory
There are many ways to discuss the subject of entrepreneurship. Roughly these can be divided into a market based view and a resource based view (McGee et al., 2005). On the one hand, neo-classical economics, Austrian school economics, heterogeneous demand theory, differential advantage theory and industrial organisation theory describe what goes on inside markets and why (Wickham, 2006). On the other hand, resource-based theory and competence-based theory question these approaches because they do not consider what goes on inside a firm (Penrose, 1959). These last approaches look at internal aspects of the firm and also allow individuals to be studied.
The central claims of the resource-based theory are that: (a) resources are not inputs but collectively provide services that support production (resource bundles), (b) different firms have different resources (resource heterogeneity), and (c) there is some difficulty in transferring resources between firms (resource immobility) (Penrose, 1959). Competence theory has its roots in the Austrian and the evolutionary literature (Adaman et al., 2002). It shares the epistemological standpoint of the tacit nature of knowledge with the Austrian school (Hayek, 1949). From the evolutionary theory, the competence theory takes the concept of economic development and learning (Nelson and Winter, 1982; Penrose, 1959). This causes competence theory to place less emphasis on resource inimitability (as resource-based theory does) and more on the dynamic replenishment of quickly erodible advantages (Wickham, 2006). It focuses on staying ahead instead of getting ahead (Prahalad and Hamel, 1990).
Here it becomes clear why competence theory is important to entrepreneurship; competence theory emphasizes forces of change, innovation and learning. Innovation is a central concept of entrepreneurship when markets are viewed as being in equilibrium (Schumpeter, 1934) but also when markets are viewed as being in disequilibrium (Kirzner, 1973). It is through the exploitation of opportunities that individuals become entrepreneurial and have an effect on markets (Shane, 2003).
9
(2005) is defensible according to various authors, because only a small proportion of individual differences in entrepreneurship are captured by relatively stable and general psychological constructs (Bandura, 1982; Baum and Locke, 2004; Lans et al., 2008; Rauch and Frese, 2007a).
In order to investigate the personality of the entrepreneur Driessen (2005) uses the competence theory. In essence, a competence is a construct and therefore not measurable. However, the factors that make up the construct are measurable. Following Lathi (1999), a competence is defined as a collection of knowledge, capabilities, characteristics and attitudes. This also makes clear why the definition of entrepreneurship given above had to be an economical one; competence theory combines motives and traits (or characteristics) from the personality approach (Rauch and Frese, 2007b) with knowledge and skills (or capabilities) from the behavioural approach (Gartner, 1988; Shane and Venkatamaran, 2000).
One weakness of competence theory is that it creates a rather abstract atomised description of competence, and ignores context (Sandberg, 2000). For example, need for autonomy might be put into practice differently in an individualistic, Western culture, than in a Chinese, collectivist and authority-oriented culture (Lans et al., 2008). Recent approaches, therefore, take a more interpretive approach concerning competence to provide a more socially constructed and integrated view of competencies (Boreham, 2006; Markman, 2007). Also, when a competence profile is derived in this way this can be viewed as ‘sheet music’, indicating the notes, dynamics, phrases and melody of entrepreneurial competence (Bolden and Gosling, 2006). However the arrangement, playing, venue, performers, acoustics, improvisations and influence of previous performances are not studied. By focusing only on the ‘sheets’ of the music, tacit or implicit competencies might be easily overlooked (Lans et al., 2008).
Driessen (2005) concluded from the literature review in his PhD thesis that the competence entrepreneurship consists of the factors shown in table 1. Driessen’s (2005) dissertation focused on the characteristics (or traits) and capabilities. Knowledge was left out because this could be more easily measured in an individual conversation. The same goes for external motivations. Internal motivations were considered as they overlap with the characteristics. Regarding capabilities; only the three capabilities important for the early phase were considered as these are more applicable to entrepreneurial ventures. This leaves the characteristics and the capabilities important in the early phase. The thinking styles were considered by Driessen (2005). However, the dataset only provides relative figures regarding thinking styles (for example you are more a pioneer than you are an expert). Thus, the dataset does not provide any absolute figures about thinking styles and therefore these will not be considered in this research.
Knowledge Motivation
10
Environment Autonomy Unemployment
People Achievement Gap in the market
Production Power Interest in subject
Finances Certainty of clients
Capabilities Characteristics Company life cycle Achievement Thinking styles: Mature phase: Early phase: Autonomy Pioneer
Manage Market orientation Power Salesperson
Motivate Creativity Affiliation Manager
Organize/plan Flexibility Effectiveness Expert
Financial adm. Endurance
Taking risks
Table 1 Entrepreneurial competence
2.3 Trait Theory
The personality approach is one of the classical and early approaches to entrepreneurship (Rauch and Frese, 2007a). It is also one of the most controversial and has been criticized with the following arguments (Aldrich and Wiedenmayer, 1993; Brockhaus and Horwitz, 1985; Gartner, 1988; Low and MacMillan; 1988): entrepreneurship asks for too varied a set of behaviours to be related to specific personality traits, the correlation coefficient of any trait is too low, and environmental aspects are not taken into account.
However, over time, a revival of personality research has emerged. There is now the consensus that there is substantial evidence for the validity of personality research and certain personality variables that are important for organizational behaviour (Barrick and Mount, 1991). This became possible because of a number of solutions to the challenges of trait theory were proposed. Some of the most important are mentioned.
First, traits need to be sampled across different situations and occasions and can then predict reasonably well a class of behaviours. However, they are not able to predict individual acts (Epstein and O’Brien, 1985). Second, taking situational parameters into account increases the predictive power of personality traits (Magnusson and Endler, 1977). Third, proximal and distal variables should be differentiated to make personality research more transparent (Kanfer, 1992). Fourth, expectancies, beliefs, affects, goals and values should also be considered to explain individual differences (Bandura, 1999).
2.4 Need for achievement
11
exploit entrepreneurial opportunities (McClelland, 1961; Shane et al., 2003). It is the prospect of achievement that drives the entrepreneur. Money is important primarily in measuring the achievement.
2.4.1 Logic
There are several reasons why people who score high on need for achievement are more likely to exploit entrepreneurial opportunities (Shane, 2003). First, solving novel and ill-specified problems, as is the case with entrepreneurial opportunities, requires the willingness to solve such problems and meet challenges, a characteristic of people with a high score in need for achievement (Harper, 1996). Second, exploiting opportunities involves goal setting and planning and information gathering. This is also a characteristic of achievement-oriented people (Miner, 2000). Third, need for achievement generates the drive to make a significant effort and stay goal-directed despite obstacles, setbacks and failures. These situations inevitably occur under uncertainty and incomplete information (Wu, 1989).
2.4.2 Proof
This theory has received consistent empirical support (Carter and Jones-Evans, 2006; Shane, 2003). When compared to the general population, entrepreneurs score higher on need for achievement (Begley and Boyd, 1986; Caird, 1991). Entrepreneurs have also been found to score higher on need for achievement than managers (Bellu, 1988; Miner et al., 1989; Stewart and Roth, 2007). A meta-analysis by Collins et al. (2004), investigating 63 need for achievement studies, found that that need for achievement significantly differentiated entrepreneurs from the general population. Also Johnson (1990) reviewed 23 studies on need for achievement and concluded that need for achievement differentiated entrepreneurs from other members of society.
2.5 Need for autonomy
12 2.5.1 Logic
There are several reasons why people who score high on need for autonomy are more likely to exploit entrepreneurial opportunities (Shane et al., 2003). First, the entrepreneur takes responsibility for an opportunity that did not exist before. This implies they often go against the status quo, or do what others perceive as foolish or even impossible. Therefore they have to be independent thinkers (Locke and Baum, 2007). Second, entrepreneurs are in the end responsible for their own results, whether they have achieved them or not. Third, desire for autonomy was found to be the most common reason to pursue a business opportunity (Boswell, 1973; Cromie, 1987; Roberts and Wainer, 1971). Similarly, Hisrich (1985) found that a prime reason why (female) firm founders pursue entrepreneurial careers is because they desire independence.
2.5.2 Proof
This theory has received consistent empirical support (Shane, 2003). When compared to the general population, entrepreneurs score higher on need for autonomy (Aldridge, 1997; Caird, 1991; Hornaday and Aboud, 1971). Entrepreneurs have also been found to score higher on need for autonomy than managers (Cromie and O’Donaghue, 1992). A meta-analysis by Rauch and Frese (2007b), investigating 11 need for autonomy studies, found that need for autonomy was significantly correlated with entrepreneurial behaviour.
2.6 Need for power
Need for power describes a person’s imperative to be in charge (McClelland, 1961; Murray, 1938). It is the need to influence others (Timmons and Spinelli, 2007). According to McClelland (1961), there are two kinds of needs for power; (1) personal power is the motive for power expressed through a desire for authority and control over others and (2) social power is the motive to exercise power for the benefit of others (McClelland, 1975). Entrepreneurs are said to get moderate scores when the need for power is measured, as opposed to managers who score high on need for power (Peay and Dyer, 1989; Winter, 1973).
2.6.1 Logic
13
(Hisrich, 1990). Also, it is suggested that a stage model for entrepeneurs and their attitudes might be a better way to examine entrepreneurs’ need for power by using their experience and the stage of development of the organization (Churchill, 1983; Yukl, 1989).
2.6.2 Proof
This theory has received some empirical support. While McClelland (1961) argued entrepreneurs had to be high in need for power for their organizations to be successful, Schrage (1965) showed that entrepreneurs had low scores for need for power. Studies performed by Roberts (1968) and Wainer and Rubin (1969), questioning these results, showed that the highest performing R&D companies were led by entrepreneurs scoring moderate on need for power. Hornaday and Bunker (1970) confirmed these results.
2.7 Social orientation
An entrepreneur’s need for affiliation, or her social orientation, is the need to attain an affiliation goal; the goal to build a relationship and feel a sense of involvement and belonging within a social group (McClelland, 1961; Timmons and Spinelli, 2007). Social orientation is also related to agreeableness (Shane, 2003). People with high levels of need for affiliation spend a significant part of their time socializing. Entrepreneurship is said to have a negative relation with need for affiliation (McClelland, 1975).
2.7.1 Logic
There are several reasons why people who score low on social orientation are more likely to exploit entrepreneurial opportunities. First off, in order to separate more valuable information from less valuable, an entrepreneur has to have a critical approach to information. This approach is enhanced by a sceptical and distrustful nature. This causes entrepreneurs to score lower on friendliness and social conformity (Shane, 2003). Another reason why the need to affiliate might be counterproductive for entrepreneurship is that it may lead to social ‘approval seeking’, which is not normally associated with risk-taking (McClelland, 1965). Here it also becomes clear how social orientation is related to the trait agreeableness (Shane, 2003).
2.7.2 Proof
14
(Hornaday and Aboud, 1971). When asked, entrepreneurs rate a low need for affiliation as an important aspect of their personality (Hornaday and Bunker, 1971). Entrepreneurs have also been found to be less trusting (Brodsky 1993; Wooten et al., 1999).
2.8 Self-efficacy
The term self-efficacy is derived from Bandura's (1977) social learning theory and refers to the belief in one’s own ability to perform a certain task effectively (Bandura, 1997; Rauch and Frese, 2007a). Self-efficacy can be split into general and task specific self-confidence (Locke and Baum, 2007). Thus, one may feel able to handle life’s challenges, but this is different from being confident about raising $5,000,000 venture capital for example. Generalized self-efficacy is also understood as locus of control (Carter and Jones-Evans, 2006). People who score higher on self-efficacy are more likely to exploit entrepreneurial opportunities than people who score low on self-efficacy (Knight, 1921; Shane, 2003).
2.8.1 Logic
There are several reasons why people who score high on self-efficacy are more likely to exploit entrepreneurial opportunities (Rauch and Frese, 2007a). First off, people scoring higher on self-efficacy are more likely to persevere when problems arise (Bandura, 1982). They also take more personal initiative (Speier and Frese, 1997). Third, they have higher hopes of success and therefore take a long-term perspective (Heckhausen and Schulz, 1995). Finally, they actively search for information which leads to better knowledge (Ashford and Tsui, 1998). These attributes are said to be important for entrepreneurial process because these situations are often characterized by ambiguity where effort, persistence and planning are important (Shane et al., 2003).
2.8.2 Proof
15
2.9 Endurance
Tenacity, also called endurance, is the perceived ability to overcome adverse circumstances (Markman et al., 2005). It is goal-directed energy over time (Shane et al., 2003). Related to endurance is the concept of ‘Type A’ behaviour (O’Gorman and Cunningham, 1997). People possessing Type A behaviour, as opposed to Type B behaviour, are able to maintain a high level of energy and interest for their product despite setbacks (Wee et al., 1994). People who score higher on endurance are more likely to exploit entrepreneurial opportunities than people who score low on endurance (Bellu, 1988; Mescon and Montanari, 1981).
2.9.1 Logic
There are several reasons why people who score high on endurance are more likely to exploit entrepreneurial opportunities. First off, endurance helps entrepreneurs overcome setbacks in their business (Brockner and Guare, 1983; McGrath, 1999). Secondly, perseverant people discover ways to overcome constraints or change them, which is where the creative or innovative aspect of entrepreneurship comes in (Bandura, 1997).
2.9.2 Proof
This theory has received some empirical support. When compared to the general population, entrepreneurs score higher on endurance (Markman et al. 2005). Entrepreneurs have also been found to score higher on endurance than managers (Mescon and Montanari, 1981). When asked, entrepreneurs rate endurance as an important aspect of their personality (Hornaday and Bunker, 1970). When ‘Type A behaviour’ was under investigation it appeared entrepreneurs received higher scores than the general public (Babb and Babb, 1992; Boyd, 1984). Also founders received higher scores than non-founders (Begley and Boyd, 1987).
2.10 Market awareness
16
score higher on market awareness are more likely to exploit entrepreneurial opportunities than people who score low on market awareness (Schrage, 1965).
2.10.1 Logic
There are several reasons why people who score high on market awareness are more likely to exploit entrepreneurial opportunities. First off, if a person cannot spot market needs which are not being met, or not sees a way to offer a product more efficiently, she is not an entrepreneur (Shane, 2003). Secondly, even if an opportunity is spotted the entrepreneur does not know if significant demand exists, and is therefore dependent upon the market (Amit et al., 1990a;b). This makes entrepreneurship a process involving market awareness (Kuratko, 2008).
2.10.2 Proof
This theory has received some empirical support. What should be kept in mind here is that a lot of literature defines entrepreneurship in such a way that it automatically involves spotting customer needs, and being sensitive to what the market demands. Founders tend to start businesses in industries in which they were previously employed (Aldrich, 1999; Johnson and Cathcart, 1979). This allows them to use their industry experience, thereby making it easier to find needs not being fulfilled. Also, there appears to be a positive relationship between market orientation and the performance of entrepreneurial firms (Brettel et al., 2006; Nasution, 2011; Schrage, 1965).
2.11 Creativity
Although various definitions exist, authors seem to have reached some agreement in that creativity involves the production of novel, useful products (Mumford, 2003). Schumpeter was the first to define successful entrepreneurs as those that discover opportunities that others do not see (Schumpeter, 1934). Innovativeness is closely related to creativity and the terms are often used interchangeably in an entrepreneurship context (Bellu, 1988; Robinson et al., 1991). People who score higher on creativity are more likely to exploit entrepreneurial opportunities than people who score low on self-efficacy (Shane, 2003; Wu, 1989).
2.11.1 Logic
17
1989). There are several sources of uncertainty where entrepreneurs can show their creativity (Amit et al., 1990a; b). Technical uncertainty implies the entrepreneur does not know whether the product will work, and if it can be produced at a cost lower to the price at which it will be sold. Market uncertainty implies the entrepreneur does not know whether demand exists or how much. Competitive uncertainty implies the entrepreneur does not know whether she is able to appropriate the profits from exploiting the opportunity. This is where entrepreneurial opportunities differ from optimizing scarce resources within existing parameters (Gaglio and Katz, 2000).
2.11.2 Proof
There seems to be some research to support this proposition (Shane, 2003). When compared to the general population, entrepreneurs score higher on creativity (Caird, 1991; Cromie and O’Donoghue, 1992). Entrepreneurs have also been found to score higher on creativity than managers (Bellu, 1988; Robinson et al., 1991). Similar results were obtained when being innovative was measured in place of creativity (Hull et al., 1980). It also appears that creativity allows some entrepreneurs to discover more opportunities and identify which are the most valuable (Tullar, 2001; Utsch and Rauch, 2000).
2.12 Flexibility
Flexibility is often defined as the capacity to respond and adapt to change as well as inflict change on others (Golden and Powell, 2000; Rundh, 2010). Flexibility can be examined by looking at dimensions such as temporal, range (foreseeable and unforeseeable changes), intention (related to locus of control) and focus (internal or external) (Driessen, 2005; Golden and Powell, 2000). Related to this issue is the concept of tolerance for ambiguity. As entrepreneurs continually face uncertainty, those better able to handle these ambiguous situations will be so because they more easily adapt to the situation.
2.12.1 Logic
18
exists or how much. Competitive uncertainty implies the entrepreneur does not know whether she is able to appropriate the profits from exploiting the opportunity.
2.12.2 Proof
This theory has received some empirical support. In their meta-analysis, Rauch and Frese (2007b) found a strong correlation between flexibility and entrepreneurship. Starr and MacMillan found that entrepreneurs often minimize commitment to a particular course by investing only in assets that can be redeployed (1990). Also, Roberts found that for this reason many technology firms begin as consulting organizations to avoid investing in fixed assets (1991). Recent insights into effectuation seem to support this idea of low commitment, whereby all options are kept open (Sarasvathy, 2001). When tolerance for ambiguity was the concept that was investigated, mixed support was found (Shane et al., 2003). A meta-analysis by Sexton and Bowman (1986), investigating 4 tolerance for ambiguity studies, found that tolerance for ambiguity was significantly correlated with entrepreneurial behaviour. Others, however, found no significant difference in tolerance for ambiguity between founders and nonfounders (Babb and Babb, 1992) or between founders and managers (Begley, 1995).
2.13 Risk Taking propensity
Risk taking propensity measures the willingness of people to engage in risky action (McClelland, 1961; Shane, 2003). In the entrepreneurship literature, risk taking propensity is defined as the willingness to take moderate risks (Atkinson, 1957; Begley, 1995). People who score higher on risk taking propensity are more likely to exploit entrepreneurial opportunities than people who score low on risk taking propensity (Shane, 2003).
2.13.1 Logic
19 2.13.2 Proof
This theory has received consistent empirical support (Shane, 2003). When compared to the general population, entrepreneurs score higher on risk-taking propensity (Caird, 1991). Entrepreneurs have also been found to score higher on risk-taking propensity than managers (Begley, 1995; Begley and Boyd, 1987; Cromie and O’Donaghue, 1992; Stewart et al., 1999). A meta-analysis By Rauch and Frese (2007b), investigating 18 risk-taking studies, found that that risk-taking propensity was significantly correlated with entrepreneurial behaviour. The same results were obtained by the meta-analysis of Stewart and Roth (2001).
2.14 Extraversion
Although the trait extraversion is not included in the dataset of the E-scan it is still considered here. This is because there does seem to be substantial research that verifies the relationship between extraversion and entrepreneurship. There is a general consensus that five broad domains capture much of the variability in normal personality traits (John and Srivastava, 1999). These are called the Big Five personality traits and are extraversion, neuroticism, openness, agreeableness and conscientiousness. Literature discusses agreeableness and extraversion as important for entrepreneurs (Shane, 2003). Agreeableness will not be dealt with separately as this trait is related to social orientation. However, extraversion will be discussed here. Extraversion is an aspect of personality that incorporates the attributes of sociability, assertiveness, activeness, ambition, initiative, impetuousness, expressiveness, gregariousness, talkativeness, surgency and exhibitionism (Barrick and Mount, 1991; Lucas and Donnellan, 2009). People who score higher on extraversion are more likely to exploit entrepreneurial opportunities than people who score low on extraversion (Shane, 2003).
2.14.1 Logic
20
to lie in the concept extraversion which is made up of a lot of different terms. For example, Helson and Kwan (2000) argued that a lot of research had overlooked the fact that there are two components to extraversion; social dominance and social vitality. On the one hand, social dominance reflects such traits as dominance, independence, and self-confidence, especially in social contexts. On the other hand, social vitality corresponds more closely to sociability, positive affect, gregariousness and energy level (Roberts et al., 2006). Therefore it seems that while entrepreneurship is negatively related to social orientation (as discussed before) and probably also social vitality, the social dominance component of extraversion causes the relationship between extraversion and entrepreneurship to be positive.
2.14.2 Proof
This theory has received consistent empirical support (Shane, 2003). When compared to the general population, entrepreneurs score higher on extraversion (Burke et al., 2000; Wooten et al., 1999; Roberts, 1991). Sexton and Bowman (1984) found entrepreneurship students scored higher on extraversion than other students. Also, firm founders were found to score higher on extraversion than non-founders (Babb and Babb, 1992).
2.15 Research gap
This thesis will investigate the relation between the 11 aforementioned traits and age. This will be a first step in the direction of studying how older entrepreneurs might be supported. Thus, the research question is formulated in the following way:
What is the relationship between age and the traits and capabilities that constitute the competence of entrepreneurship?
All the traits and capabilities will be studied individually to come up with hypotheses. In the next paragraph the method for doing this will be described.
2.16 Systematic Literature Review
21
it can provide information about the effects of some phenomenon across a wide range of settings (Kitchenham and Charters, 2007).
2.16.1 Research questions
Although variations in guidelines for a systematic literature review exist, they are broadly agreeing on the major stages of the process: planning the review, conducting the review and reporting the review (Brereton et al., 2007; Kitchenham and Charters, 2007). The planning phase mainly consists of the development of a review protocol. This includes the research questions, the search strategy, the study selection criteria, the quality assessment, the data collection and the data analysis. These parts will all be described below. The main research question for the systematic literature review is the same as the main research question for this thesis. This question can be divided by investigating each of the traits or capabilties’ relationship with age individually.
2.16.2 Search strategy
The search strategy includes using the Academic Search Premier, Business Source Premier and PsycINFO databases to search key words noted in the ‘search terms’ section. Academic Search Premier is a multi-disciplinary database providing full text for more than 4,600 journals, including full text for nearly 3,900 peer-reviewed titles. PDF backfiles to 1975 or further are available for well over one hundred journals, and searchable cited references are provided for more than 1,000 titles. Business Source Premier is the industry’s most used business research database, providing full text for more than 2,300 journals, including full text for more than 1,100 peer-reviewed titles. This database provides full text back to 1886, and searchable cited references back to 1998. PsycINFO is the American Psychological Association’s (APA) renowned resource for abstracts of scholarly journal articles, book chapters, books, and dissertations, and is the largest resource devoted to peer-reviewed literature in behavioral science and mental health. The titles, abstracts and key words of the journal articles were searched using the following search terms and Boolean search phrases:
(“need for achievement” or “need for autonomy” or “need for power” or “need for affiliation” or “social orientation” or “self-efficacy” or “tenacity” or “endurance” or “market orientation” or “creativity” or “flexibility” or “tolerance for ambiguity” or “risk taking” or “extraversion”)
AND (“age” or “ageing” or “aging”)
22
Once the potentially relevant primary studies have been obtained, they need to be assessed for their actual relevance. This process involves three steps: (1) exclusion studies on the basis of their titles, (2) exclusion of papers on the basis of their abstracts, (3) exclusion of studies on the basis of their full text. Subsequently, all the references of the identified papers will be examined in the same way.
2.16.4 Quality assessment
Only articles published after January 1st 2001, and before December 31st 2010 were considered. This focuses the systematic review on the most recent articles from a period which can be searched again (including 2011 would make it difficult to copy the study as the study took place in the year 2011). It was decided that in the second iteration, references from before 2001 were also considered because the number of results up to that stage was not very high. Only publications in the English language were considered in this review. No further quality criteria were applied to the publications. The fact that all publications were found in established databases and were peer-reviewed served as enough confidence for the quality of the publications.
2.16.5 Data extraction and analysis
The data extraction stage involved the extraction of some key details from the studies included in the systematic literature review. Two kinds of data were extracted from the studies: (1) demographics such as author(s), year of publication, journal and source name; and (2) the relationship of the factor(s) with age. The data synthesis phase of this review aims at addressing the research questions posed at the beginning of the review. The results of the analysis can be found in the separate paragraphs describing all the competencies (2.16.1-2.16.11). Table 1 below shows the number of papers excluded in each stage when read from left to right.
Iteration Initial number of papers Stage of exclusion Number of papers excluded Number of papers remaining
1 14372 (from database) Title 14225 147
Abstract 88 59
Full-text 13 46
2 2426 (references from papers Title 2372 54
found after iteration 1) Abstract 38 16
Full-text 3 13
Final number of papers 46 + 13 = 59
Table 1 Number of papers excluded in each iteration and stage.
23
found. These are need for achievement, need for autonomy, need for power and market orientation. A ut ho r( s) : Yea r of p ub lic at io n: So ur ce : N ee d f or a ch ie ve m ent N ee d f or a ut on om y N ee d f or p owe r So ci al or ie nt at io n Se lf-ef fic ac y En dur an ce M ar ket a wa re ne ss Cr ea ti vi ty Flexib ili ty R isk T aki ng Pr op en si ty Ex tr av er si on
Albion et al. 2005 Australian Journal of Psychology X
Artistico et al. 2003 Psychology and Aging X
Ashman et al. 2003 North American Journal of Psychology X
Bellante and Green* 2003 Review of Financial Economics X
Berry and West* 1993 International Journal of Behvaioral Development X
Binnewies et al. 2008 Journal of Managerial Psychology X
Blanchard-Fields 2009 Restorative Neurology and Neuroscience X
Burnett et al. 2010 Cognitive Development X
Caprara et al. 2003 Europeaan Psychologist X
Cauffman et al. 2010 Developmental Psychology X
Chasseigne et al. 2002 The American Journal of Psychology X
Chen and Ma 2009 Educational Gerontology X
Chou et al. 2007 Psychology and Aging X
Coudin and
Alexopoulos 2010 Aging & Mental Health X
Crone et al. 2008 Development and Psychopathology X
Deakin et al. 2004 Journal of the International Neuropsychological Society X
Dommes et al. 2010 Psychological Reports X
Donnellan and Lucas 2008 Psychology and Aging X
Figner et al. 2009 Journal of Experimental Psychology X
Fung and Ng* 2001 Psychology and Aging X
Furnham and
Nederstrom 2010 Personality and Individual Differences X
Galenson 2009 Journal of Applied Psychology X
Heckhausen and
Schulz* 1995 Psychological Review X
Helson et al.* 2002 Journal of Personality and Social Psychology X
Helson et al.* 2002 Journal of Research in Personality X
Jianakoplos and
Bernasek 2006 Southern Economic Journal X
Jopp and Rott 2006 Psychology and Aging X
Kanfer and
Ackerman* 2004 Academy of Management Review X
Kozbelt 2008 Psychology of Aesthetics, Creativity, and the Arts X
Lachman* 1986 Psychology and Aging X
Lucas and Donnellan 2009 Developmental Psychology X
McCrae et al.* 1987 Psychology and Aging X
McCrae et al.* 1999 Developmental Psychology X
McCrae et al. 2004 European Journal of Psychology X
Ng and Feldman 2008 Journal of Applied Psychology X
Niessen et al. 2009 Journal of Managerial Psychology X
Rai 2008 Journal of Services Research X
Rantanan et al. 2007 Scandinavian Journal of Psychology X
Reed 2005 International Journal of Aging & Human Development X
Reed et al. 2005 Journal of Managerial Issues X
Reese 2001 International Journal of Behavioral Development X
Roberts et al. 2006 Psychological Bulletin X
Ruth and Birren* 1985 International Journal of Behavioral Development X Scollon and Diener 2006 Journal of Personality and Social Psychology X
Serra et al. 2008 Experimental Aging Research X
Shimonaka 2007 Japanese Journal of Educational Psychology X
Simons 2002 Dissertation X
Srivastava et al.* 2003 Journal of Personality and Social Psychology X
Steinberg 2010 Developmental Psychology X
Stroebe 2010 American Psychologist X
Verworn 2009 Creativity and Innovation Management X
Vroom and Pahl* 1971 Journal of Applied Psychology X
Wang 2009 Evolution and Human Behavior X
24
Wells and Esopenko 2008 Educational Gerontology X X
West and Thorn 2001 Experimental Aging Research X
West and Yassuda 2004 The Journals of Gerontology Series B X Windsor and Anstey 2008 Aging, Neuropsychology, and Cognition X
Zamarian et al. 2008 Neuropsychology X
*= publications from second iteration
Table 2 Demographics of the selected publications.
2.17 Traits and Age
2.17.1 Need for achievement and age
There were no studies found that discuss the relationship between need for achievement and age. Therefore it was decided that the hypothesis would be based on the relationship of entrepreneurship with age. Age is assumed to have an inverted U-shaped relationship with entrepreneurship. Thus the following hypothesis is proposed:
H1: There is an inverted U-shaped relationship between need for achievement and age.
2.17.2 Need for autonomy and age
There were no studies found that discuss the relationship between need for autonomy and age. Therefore it was decided that the hypothesis would be based on the relationship of entrepreneurship with age. Age is assumed to have an inverted U-shaped relationship with entrepreneurship. Thus the following hypothesis is proposed:
H2: There is an inverted U-shaped relationship between need for autonomy and age.
2.17.3 Need for power and age
There were no studies found that discuss the relationship between need for power and age. Therefore it was decided that the hypothesis would be based on the relationship of entrepreneurship with age. Age is assumed to have an inverted U-shaped relationship with entrepreneurship. However entrepreneurs are said to score moderately on need for power. Therefore it should be kept in mind that it is not expected that the top of the inverted U-shaped relation will be very high. Thus the following hypothesis is proposed:
H3: There is an inverted U-shaped relationship between need for power and age.
25
There was 1 study found that discusses the relationship between social orientation and age. Fung and Ng (2001) found that older adults (60-90 years) in Taiwan and China were more likely than younger adults (18-30 years) to value social contacts. The motivation is that due to the inevitable time constraint imposed by mortality, their social goals change, causing them to limit social contacts to those with whom they are emotionally close. Thus the following hypothesis is proposed:
H4: There is a positive relationship between social orientation and age.
2.17.5 Self-efficacy and age
26
H5: There is a negative relationship between self-efficacy and age.
2.17.6 Endurance and age
There were 2 studies found that discuss the relationship between endurance and age. Both studies found a negative relation with age. Wells and Esopenko (2008) found age-related declines in persistence. These results concerned memory tests. In a review of empirical studies, Berry and West (1993) found that self-efficacy was related to persistence at various ages. As self-efficacy declines with age (as hypothesised in the previous paragraph), a conclusion could be that persistence does as well. Thus the following hypothesis is proposed:
H6: There is a negative relationship between endurance and age.
2.17.7 Market awareness and age
There were no studies found that discuss the relationship between market awareness and age. Therefore it was decided that the hypothesis would be based on the relationship of entrepreneurship with age. Age is assumed to have an inverted U-shaped relationship with entrepreneurship. Thus the following hypothesis is proposed:
H7: There is an inverted U-shaped relationship between market awareness and age.
2.17.8 Creativity and age
27
measured quantitatively did decline with age, while quality did not. This indicates a developmental shift in creativity throughout the adult years. Stroebe (2010) found that the decline in scholarly productivity has been absent in recent studies, as opposed to early research. Verworn (2009) found that the quantity and the quality of ideas submitted to a suggestion system in German companies did not change with age. However, this study did not discuss the motivation of employees or their job satisfaction. Binnewies et al. (2008) found that age was positively related to idea creativity under high job control and negatively related to idea creativity under conditions of low job control. Regarding, entrepreneurs it thus appears their idea creativity would be positively related to age, although at later ages self-efficacy does seem to decrease (as discussed earlier). Galenson (2009) found there are two fundamentally different approaches to innovation; experimental innovators work by trial and error and arrive at their major contributions later in life, conceptual innovators make sudden breakthrough usually at early age. This can be related to Schumpeterian and Kirznerian entrepreneurs (Shane, 2003). Reed (2005) found that artists do not share the view that there creativity decreases. This contradicts the findings of Ng and Feldman (2008). Reese et al. (2001) found there was an inverted U-shaped relation between age and different measures of divergent thinking. As such it can be hypothesised that creativity does not decline with age, although quantitatively it might. Thus the following hypothesis is proposed:
H8: Age does not have an effect on creativity.
2.17.9 Flexibility and age
There were 6 studies found that discuss the relationship between flexibility and age. Most studies found a negative relation with age. Chasseigne et al. (2002) found older adults (40-50 years) have more difficulty with being flexible than younger adults (18-25 years). However, this concerned learning multiplicative combination rules and was therefore rather specific. Dommes et al. (2010) found younger participants (22-25 years) showed more spontaneous flexibility whereas the older participant (55-65 years) only showed reactive flexibility. Their study concerned world wide web search strategies. Jopp and Rott (2006) could not find age differences regarding flexibility. However, their study discussed centenarians. Wecker et al. (2005) found decreases in flexibility with age even when age-related changes in skills were disregarded. Niessen et al. (2010) found organizational change negatively affected job performance of older workers. This was negatively mediated by job experience. Blanchard-Fields (2009) found that in everyday problem solving older adults remained flexible and were well able to regulate their emotions while reducing cognitive costs. However, these situations are common and do not deal with new events. Thus the following hypothesis is proposed:
28 2.17.10 Risk-taking propensity and age
There were 16 studies found that discuss the relationship between risk-taking propensity and age. Most studies found an inverted U-shaped relation with age. Ashman et al. (2003) found there were no age differences between younger (18-35 years) and older adults (61-85 years). However this study missed out on important data on what happens with risk taking in the years between these age groups. Bellante and Green (2004) found that elderly (more than 65 years) were more risk averse in their investment portfolio then were younger people. Jianakoplos and Bernasek (2006) also found that risk taking in investment portfolios decreases with age. Also, they found age differences in survey respondents’ stated willingness to take risk, which was also found to decrease with age. Rai (2008) found younger entrepreneurs did not fill in his feasibility survey from which he concluded they were more confident and therefore took more risk. He also found younger entrepreneurs took more risk in terms of debt-equity ratio. His method seems to be somewhat flawed. Burnett et al. (2010) found risk taking increased up to 14,38 years. Using a probabilistic gambling task, adolescents were tested. Chen and Ma (2009) also found young adults (19-23 years) were more likely to choose a more risky scenario as were older adults (62-87 years), but, again, this study does not examine risk between 24 and 61 years. Cauffman et al. (2010) found that adolescents (10-17 years) were more risky than adults (18-30 years), due to their lower levels of avoidance behaviour and higher levels of approach behaviour. Chou et al. (2007) found younger subjects (18-25 years) scored higher on risk taking than older adults (60-78 years), although positive moods were found to upset this difference. Again it was found that the years in between were not dealt with. Coudin and Alexopoulos (2010) found negative stereotyping of older adults reduced their risk levels suggesting that the mere activation of negative stereotypes can have broad and deterious effects on older individuals. Crone et al. (2008) also showed risk taking decreases during adolescence and that adolescents take more risks when it concerns them, than when it concerns others. Deakin et al. (2004) also found that risk taking decreased with age. Figner et al. (2009) showed risk taking was at its highest during adolescence after which it slowly declined. The same curvilinear relationship was found by Steinberg (2010), when examining individuals between the ages of 10 and 30. Heightened vulnerability to risk-taking in middle adolescence may be due to the combination of relatively higher inclinations to seek rewards and still maturing capacities for self-control according to Steinberg (2010). Vroom and Pahl (1971) found a negative relationship between age and risk taking among managers. However, there study is rather dated. Wang et al. (2009) found older respondents showed lower risk propensity. More specifically, Zamarian et al. (2008) found aging effects could only be found for situations involving uncertainty, as opposed to risk. Thus the following hypothesis is proposed:
29 2.17.11 Extraversion and age
30
3. Method
3.1 Research Design
This thesis is based on quantitative data derived from fully structured questionnaires conducted by the Entrepreneur Consultancy BV. This company, which is owned and managed by Martijn Driessen, provides a service called the E-scan; a tool for self-reflection for entrepreneurs and those who wish to start a business (Driessen and Zwart, 2006). It is also used by the Rabobank, a Dutch cooperative bank, for investment decisions. Participants can take the questionnaire online (http://www.entrepreneurscan.co.uk/), or are required to take it when they ask for an investment from Rabobank or other companies.
3.2 Research Sample
The study sample consists of 46066 filled in questionnaires from the period 2006-2011. All these questionnaires were filled in at Rabobank and other companies to investigate the personality of the people who requested an investment, or via the website of E-scan. Only the ones that contained a birthdate were considered in this research. The average age of all participants was 32, 7 years (SD = 11.4 years). There was a higher percentage of men (57,8 %) than women (42,2 %).
3.3 Measures
31
3.4 Data analysis
32
4. Results
This chapter presents the results of the statistical analyses performed. First the descriptive statistics will be discussed. Also, the Pearson correlations will be discussed. The second part of this chapter will look at all of the traits and their relationship with age. The ANOVA and the graphs of all the specific traits will be discussed individually.
4.1 Descriptive findings
Table 4 shows the means, standard deviations and correlations of the main study variables. The highest mean score was found for need for achievement (M = 79,94, SD = 10,81), closely followed by creativity (M = 77,27, SD = 13,66). The two lowest mean score were for need for power (M = 59,84, SD = 13,94) and risk-taking propensity (M = 50,54, SD = 17,23). The striking low mean score of risk-taking propensity might be explained by the fact that in the entrepreneurship literature, risk taking propensity is defined as the willingness to take moderate risks (Atkinson, 1957; Begley, 1995). The low mean score of need for power might be explained by the fact that in the entrepreneurship literature entrepreneurs are said to have moderate scores on need for power (Peay and Dyer, 1989; Winter, 1973).
Figure 2 below shows the histogram of the distribution of participants across age. Most questionnaires were filled in by people in the 20-29 years age bracket. From the age of 60, hardly any questionnaires were found. The age group of 70 years and over consists of an N of only 19, which stands in stark contrast to the 16005 in the 20-29 years class. This strengthens the theory that entrepreneurship shows an inverted U-shaped relation with age (Bönte et al., 2009; Shane, 2003).
Table 4 also shows the Pearson correlations among the traits and age in 10 year groups. The analysis of the correlations indicates that all of the traits and age in 10 year groups are positively related at .01 significance level, except for the relation between need for achievement and age. The strongest positive relation was found between creativity and flexibility (.59), closely followed by the need for achievement and endurance (.58).
33
Figure 2. Age group distribution of dataset
34 N
Mean Deviation Std.
Valid Missing 1 2 3 4 5 6 7 8 9 10
Need for achievement (1) 46066 0 78,94 10,81
Need for autonomy (2) 46066 0 64,82 13,20 .37**
Need for power (3) 46066 0 59,84 13,94 .45** .34**
Social orientation (4) 46066 0 74,01 13,95 .40** .18** .45** Self-efficacy (5) 46066 0 67,94 12,22 .51** .36** .51** .56** Endurance (6) 46066 0 74,55 13,04 .58** .33** .29** .43** .54** Market awareness (7) 46066 0 71,37 13,22 .49** .25** .32** .49** .52** .54** Creativity (8) 46066 0 77,27 13,66 .47** .27** .30** .39** .45** .43** .49** Flexibility (9) 46066 0 72,44 10,18 .46** .22** .28** .45** .47** .52** .52** .59**
Risk taking propensity (10) 46066 0 50,54 17,23 .08** .08** .10** .17** .25** .09** .06** .20** .21**
Age in years (11) 45870 196 32,23 11,45 .00 .11** -.06** .12** .13** .17** .13** .17** .15** .19** **= correlation is significant at the .01 level (2-tailed)
*= correlation is significant at the .05 level (2-tailed)
35
4.2 Need for achievement and age
To test the first hypothesis, an ANOVA test was used after which the means of the different age groups were examined. In accordance with hypothesis 1, it was expected that there is an inverted U-shaped relationship between need for achievement and age. Table 5 below shows the ANOVA of the age groups and need for achievement. The table shows that the differences between the mean scores of the various age groups on the trait need for achievement are significant. This implies that the mean scores can be used to test the hypothesis.
Sum of Squares df Mean Square F Sig. Between Groups 52502,16 6 8750,36 75,63 0,00
Within Groups 5306428,79 45863 115,70
Total 5358930,95 45869
Table 5. ANOVA of need for achievement and age groups.
Figure 3 displays the mean scores of the various age groups on the trait need for achievement graphically. What becomes clear is that there is indeed an inverted U-shaped relation between age and need for achievement. However, it also appears that need for achievement stays relatively stable through the 40 - 69 years period. Therefore, the decline in need for achievement is not as strong as expected. Thus, H1 is supported.
Figure 3. Age groups and need for achievement.
4.3 Need for autonomy
To test the second hypothesis, an ANOVA test was used after which the means of the different age groups were examined. In accordance with hypothesis 2, it was expected that there is an inverted U-shaped relationship between need for autonomy and age. Table 6
36
below shows the ANOVA of the age groups and need for achievement. The table shows that the differences between the mean scores of the various age groups on the trait need for autonomy are significant. This implies that the mean scores can be used to test the hypothesis.
Sum of Squares df Mean Square F Sig. Between Groups 176029,31 6 29338,22 172,05 0,00
Within Groups 7820710,94 45863 170,52
Total 7996740,25 45869
Table 6. ANOVA of need for autonomy and age groups.
Figure 4 displays the mean scores of the various age groups on the trait need for autonomy graphically. What becomes clear is that there is indeed an inverted U-shaped relation between age and need for autonomy. The peak in the score is in the 30 -39 year age bracket. Thus, H2 is supported.
Figure 4. Age groups and need for autonomy.
4.4 Need for power
To test the third hypothesis, an ANOVA test was used after which the means of the different age groups were examined. In accordance with hypothesis 3, it was expected that there is an inverted U-shaped relationship between need for power and age. Table 7 below shows the ANOVA of the age groups and need for power. The table shows that the differences between the mean scores of the various age groups on the trait need for power are significant. This implies that the mean scores can be used to test the hypothesis.
37
Total 8919128,14 45869
Table 7. ANOVA of need for power and age groups.
Figure 5 displays the mean scores of the various age groups on the trait need for power graphically. What becomes clear is that there is an inverted U-shaped relation between age and need for autonomy but the graph is positively skewed. Scores rise from the 10 – 19 years to the 20 - 29 years period, but from there scores steadily decline. Thus, H3 is partially supported.
Figure 5. Age groups and need for power.
4.5 Social orientation
To test the fourth hypothesis, an ANOVA test was used after which the means of the different age groups were examined. In accordance with hypothesis 4, it was expected that there is a positive relationship between social orientation and age. Table 8 below shows the ANOVA of the age groups and social orientation. The table shows that the differences between the mean scores of the various age groups on the trait social orientation are significant. This implies that the mean scores can be used to test the hypothesis.
Sum of Squares df Mean Square F Sig. Between Groups 140091,13 6 23348,52 121,87 0,00
Within Groups 8787009,25 45863 191,59
Total 8927100,38 45869
Table 8. ANOVA of social orientation and age groups.
Figure 6 displays the mean scores of the various age groups on the trait social orientation graphically. What becomes clear is that there is indeed a positive relation between age and social orientation. From the age of 10 until the age of 69 scores on social orientation rise. It is only from the age of 70 that social orientation drops. Thus, H4 is supported.
