Human and social capital are personal investments, and the positive returns to an individual's career of investments into these forms of capital are well understood. Increased education and experience, human capital, as well as the structure of relations that form social capital, contribute to higher earnings and early promotions. I hypothesize that the dynamics of human and social capital can be applied to career returns less tangible than income and promotion, namely job satisfaction. I find evidence to support this and further show support for previous findings that suggest such returns are not uniform with regard to gender. Finally, I show that the returns to human and social capital are greatly affected by individual motivation.

Some people enjoy higher incomes than others do; some are promoted faster, or are leaders on more important projects. Human capital theory (e.g. Becker, 1975) explains inequalities like these by differences in individual ability resulting from different educational attainment. The theory predicts that individuals who are better educated and more experienced will enjoy higher returns for their efforts. However, although human capital (i.e. education, training, skills) is necessary to achieve success in an organization, it is useless without the social capital of opportunities in which to apply it (Burt, 1997). Social capital theory (e.g. Burt, 1992; Coleman, 1990) predicts that returns to human capital partly depend on a person’s location in the social structure of an organization. Individuals with more social capital will receive higher returns to their human capital because they are positioned to identify and develop more rewarding opportunities. Previous studies have presented argument and evidence for the positive relationship between social capital and positive evaluations (e.g. Rosenthal, 1996), faster promotions (e.g. Burt, 1992), and higher salaries (e.g. Burt, 1997). The study presented here explored the combined effect of human and social capital on a personal, non-financial return, namely job satisfaction. I find evidence to support this relationship and further show that the job satisfaction returns to human and social capital are greatly affected by individual motivation.

There have been thousands of studies of job satisfaction and other attitudes toward work and reviews of this work have been presented elsewhere (e.g., Cranny, Smith & Stone, 1992; Locke, 1976; Miller, 1980; Spector, 1997). Studies that have focused on the antecedents of job satisfaction can be classified into two major categories: those that focus on the job environment or job characteristics and those that focus on individual factors that a person brings to the job such as personality or prior experiences. Much, if not all, of this literature has looked to individual psychology to understand underlying mechanisms of job satisfaction (Pfeffer, 1991; Salancik & Pfeffer, 1977). Typically, the argument that is made is that individuals have needs or preferences, and job environments are satisfying or not depending on how well the characteristics of the job match the needs or preferences of the individuals (e.g.

Hackman & Lawler, 1971; Kalleberg, 1977). The fit between the individual and the job characteristics has also been examined extensively and has been shown to be an important influence on employee job satisfaction (e.g. Edwards, 1991; Kristof, 1996; Tsang, Rumberger and Levin, 1991; Vroom, 1964).

The social environment (e.g. patterns of relationships) in which individuals perform their job can also be linked to variance in job satisfaction. For example, some studies have examined how social contagion or peer influence can sway affective reactions to the work environment. One example of this type of approach is the social information processing model proposed by Salancik and Pfeffer (1978). This model suggests that one’s own attitudes are affected by the expressed opinions of others in the environment. Krackhardt and Porter (1985) offered an empirical example of this approach when they modeled turnover as a process that was socially influenced. These authors gathered data on friendship and interaction patterns of workers in fast food restaurants and showed that as soon as some of the friendship group began to leave, the others followed quickly. Another aspect of social structure that has been shown to affect job attitudes is the presence of co-workers in one’s social network. Hurlbert (1991) showed that social networks of co-workers serve as a social resource which have a positive affect on job satisfaction through social support.

The model proposed here explores the combined effect of individual and structural characteristics on job satisfaction by framing the study within the robust foundations of human and social capital theories.

Human capital is defined as an individual’s stock of education, experience, skills and intelligence. In general, human capital refers to an individual’s ability. According to human capital theory (Becker, 1975), education and experience develop skills that enable workers to be productive. Theories of job satisfaction suggest that an individual’s education and experience (i.e. their human capital) is positively associated with their attitudes toward their job (e.g. Gruenburg, 1980). All other things held constant, higher levels of human capital will lead to higher levels of job satisfaction.

Hypothesis 1: Individuals with higher levels of education, training and experience will recognize higher levels of job satisfaction.

Social capital refers to the wealth of an individual’s connections with others. Certain patterns of relations with others can enhance an individual’s ability to identify and develop opportunities. Whereas human capital resides within an individual, social capital describes the value of a relationship that exists between two people; it is shared equally by both and has no value without either (Burt, 1997; Coleman, 1990). Social capital theory predicts that returns to intelligence, education, and seniority depend in some part on a person's location in the social structure of their organization. While human capital refers to individual ability, social capital refers to opportunity. Individuals with more social capital get higher returns to their human capital because they are

positioned to identify and develop more rewarding opportunities. In a sense, the exchange of human capital across relations forms the substance of the social capital among individuals and others in their social network.

Thus, human capital alone enables a person to achieve some of their potential, but only within the limits and confines of a particular social setting. In a workplace setting, human capital allows a person to learn and adapt quickly to specific situations (e.g. a firm’s culture) and social capital allows the individual to adjust their social setting in a way that the full potential of their human capital can be exploited. Rather than adapt their goals to fit the context, social capital provides the individual with the opportunities to change their context to fit their goals.

How this happens can be explained by Burt’s structural hole theory (1992), which gives concrete meaning to the concept of social capital. The theory describes how social capital is a function of a person acting as a broker between two otherwise disconnected individuals. The metaphor is that the disconnected people stand on opposite sides of a hole in social structure. An individual who spans this structural hole via their relationship with each person will experience information and control benefits. Information benefits in terms of better access, timing and referrals; control benefits in that the individual who acts as the bridge between two otherwise disconnected contacts has say in whose interests are served by the bridge. Individuals with contact networks rich in structural holes are expected to know about and experience more rewarding opportunities. Empirical evidence is consistent with this prediction — individuals with networks rich in structural holes receive more positive evaluations (Rosenthal, 1996; Burt, Jannotta, and Mahoney, 1998; cf., Krackhardt and Stern, 1988; Fernandez and Gould, 1994), earlier promotions (Burt, 1992; Sparrowe and Popielarz, 1995; Gabbay, 1996; Podolny and Baron, 1997), and higher compensation (Burt, 1997; Burt, Hogarth, and Michaud, 1998).

Based on Burt’s (1992) evidence of the returns to contact networks rich in structural holes, I argue that an individual’s ability to convert the capabilities of their human capital into high job satisfaction is contingent upon their social capital. Contact networks rich in structural holes provide the individual with opportunities to exploit their human capital more effectively in order to achieve higher levels of satisfaction.

Hypothesis 2:Individuals with contact networks rich in structural holes will have greater opportunity to leverage their human capital and will therefore experience higher levels of job satisfaction.

People are continuously surrounded by opportunities (as a function of their social surroundings) and the characteristics of the jobs they hold are the outcome of the process of identification, selection, and conversion of such opportunities. The importance of social capital on the variance of job satisfaction can be traced to two specific job characteristics inherent in the opportunities available to people: challenge and meaning. Herzberg (1968) argues that "the only way to motivate the employee is

to give him challenging work in which he can assume responsibility." Viktor Frankl (1984) suggests that motivation reflects people’s search for meaning and that job satisfaction may reflect the degree to which people have found meaning in their work. Regardless of their amount of human capital, a person will not be able to achieve the optimal meaning they are capable of experiencing or maximize the challenges they are capable of handling if they are not able to discriminate and choose from the opportunities that surround them. Knowledge about and/or access to these opportunities is enhanced or inhibited by the individual’s amount of social capital. Burt (1992, p.275) recognizes that the rate of conversion, or exploitation, of the opportunities available to an individual through their social capital is dependent upon their motivation, but does not test this link.

Studies of job satisfaction have shown that motivation is a critical component linking job characteristics to satisfaction (Hackman & Lawler, 1971; Gruenberg, 1980; Rose, 1994) by arguing that motivators are embedded in tasks and activities. Surprisingly, none of these studies treated motivation as an individual characteristic. The present study treated motivation as an important explanatory factor linking one's level of job satisfaction to one's human capital potential and social capital opportunities.

Hypothesis 3: Individuals with higher levels of motivation will convert their human capital potential and social capital opportunities into higher levels of job satisfaction.

Measures and Methods

The data describe employees at a real estate management company. Respondents filled out sociometric and job satisfaction/motivation questionnaires in the course of structured group interviews with the researcher. In all cases, participation was voluntary, and respondents were assured that their responses would be kept confidential. A total of 53 completed questionnaires were collected (87% response rate; see Table 1 for variable means, standard deviations and correlations).

Three variables were used to measure human capital: education, number of hours in work-related training in the last year, and an experience index constructed by averaging age and number of work years (alpha reliability of 0.93). Respondents had an average of approximately 24 years of experience and 30 hours of training in the last year with no significant differences between managers and non-managers. Most of the respondents (70%) had a 4-year college degree or graduate education, 15% had a high school degree and 15% had a 2-year college degree.

On the sociometric questionnaire, respondents were asked to name (1)"who are the four or five people with whom you discussed matters important to you?" (2)"who are the three people you have been with most often for informal social activities such as going out to lunch, dinner, drinks, films, visiting one another’s homes, and so on?" (3) "who is your immediate supervisor?" (4) "of all the people working for the firm, who are your most valued work contacts in the sense that they have contributed most to your professional growth?" (5) "who are the three or four people you would name to your replacement as essential sources of buy-in for initiatives coming out of your office?" (6) "who is your single most important contact in the firm?" (7) "who among the people working for the firm has made it most difficult for you to carry out your job responsibilities?" (8) "if you decided to find a job with another firm doing the same kind of work you do in your firm, who are the two or three people with whom you would most likely discuss and evaluate your job options?" For each cited contact, respondents were asked about the contact’s relations with the other cited contacts, contact age, gender, authority relation with the respondent, and whether the contact was a coworker, friend or family. The respondents’ network measures were calculated using only co-worker contacts (friends and family were not included). The calculation was done in this way to obtain an accurate measure of the respondent’s at-work social capital and to eliminate family and friend related social capital from the analysis. The cited work contacts vary from a total of 2 up to 15, with an average of 6.7 contacts.

Respondents were also asked to describe the strength of relationships. The respondent’s relation with each contact was sorted into one of four categories: especially close, close, less close, or distant. Respondents indicated the relationship among their contacts by indicating whether each pair was especially close, distant, or somewhere between distant and especially close. From this, the strength of relation between each pair of contacts (including the respondent) was estimated. This measure is symmetric for each pair of relations and varies from a minimum of 0 (distant relation) up to 1 (close relation)¹.

Social capital was measured in terms of network constraint. Network constraint measures the extent to which the structure of a person’s social network prevents them from accessing or exploiting the opportunities that may surround them, or, whether or not their network is rich in structural holes. An individual is constrained by a) a small number of contacts in his/her network, b) the extent to which network contacts are closely related to and dependent on one another, and c) the degree to which (s)he concentrates time on any one contact in the network. By examining the degree of constraint in an individual’s network, networks are viewed as a social resource which affect job satisfaction through access to opportunities. Constraint ranges from a minimum of zero to a maximum of one² (Burt, 1992). Average constraint in the present sample was 0.51.

For the motivation variable, an index (alpha reliability of 0.77) was constructed by averaging the respondent’s answers to the following three questions: I am motivated to do my job because of (1) the responsibility/impact I have; (2) the rewards/recognition I get from others at work; and (3) the ability to overcome challenges/difficulty in my job. Responses were based on a 4-point scale where 1=Never true, 2=Sometimes true, 3=Often true, and 4=Always true. Average motivation for all respondents was 3.21.

Previous research on the returns to social capital has shown that the returns to social capital are not uniform (Burt 1997; 1998). Individuals who are outsiders in a given social context must supplement their own social capital by borrowing it from insiders by way of a hierarchical network. I include variables in the present analysis to test if this is also the case with job satisfaction returns to social capital. Two dummy variables are included: one for managers (manager=1) and another for gender (female=1). Two interaction variables are also included: manager x constraint, and gender x constraint. The control variables will show whether there is a baseline difference between the groups, the interaction variables will show if there is a slope difference. There were 26 managers, 27 non-managers, 18 men and 35 women in the sample of 53 respondents. However, it is important to note that there was an imbalance of men in managerial roles in the sample; 83% of the men were managers whereas only 30% of the women were managers³.

Variable means, standard deviations and the correlation matrix is reported in Table 1. The correlations provide some preliminary support for the positive relationship between job satisfaction and experience as well as job satisfaction and motivation (correlations of 0.438 and 0.508 respectively). Furthermore, the correlations highlight significant differences between men and women and managers and non-managers. Specifically, managers are more likely to be male, better educated, more motivated and more satisfied with their job.

Hypothesis 1 predicted a positive relationship between job satisfaction and education, experience and hours training. As shown in Table 2, Model I, job satisfaction increases with experience (3.5 t-test), but the relationship with education and hours training is irrelevant. Still, reports of job satisfaction are higher for employees with more human capital – as indicated by experience.

I expected the effect of social capital (specifically, network constraint) to be negative. Model II tests this hypothesis directly. Although the sign of the reported effect is in the predicted direction, the result is not significant (t = -0.68, p = .49). There are two possible explanations for this insignificant result: 1) the effect of social and human capital on job satisfaction is evident only if motivation is added to the model; and/or 2) there are baseline or slope differences between the different groups in the sample that are watering down this effect. I tested each of these explanations and included the results below.

Table 2

Predictors of Job Satisfaction^a