Job satisfaction (JS) is one of the most widely discussed and studied dimensions of employees’ work lives, with research dating back to the dawn of the twentieth century. Early definitions conceived of JS as a global affective or emotional reaction to one’s job. More recently, JS has been defined as comprising two distinct yet related components: an individual’s effective orientation toward the job (e.g., I enjoy my job; I look forward to going to work each day) and an individual’s cognitive evaluation of the job and how well it meets personal needs (e.g., I think that I am adequately compensated for the work I do; this job provides me with the recognition I deserve). A large number of job facets (or dimensions) have been identified as underlying these cognitive evaluations, including social aspects of the job (e.g., appreciation or recognition by the supervisor or organization); compensation and benefits; working conditions (e.g., safety); and opportunities for personal growth (e.g., promotion). Thus, many measures of JS ask specifically about these various facets.
The relevance of JS attitudes to career-development issues lies in the fact that JS is an important (arguably the most important) outcome for assessing the effectiveness of career-development activities and decisions. That is, the ultimate goal of most career-development activities is to ensure that individuals end up in careers and jobs that they find maximally satisfying. Thus, it is important to understand how JS is measured, the determinants of JS (both individual and situational), and outcomes typically associated with higher levels of JS. Each topic is reviewed in the following sections.
Measuring Job Satisfaction
There are a number of different scales and techniques available for measuring one’s level of JS. Most involve eliciting responses on a self-report questionnaire or in an interview (with the former being much more common). For example, to understand how satisfied individuals are with their jobs or with a particular aspect of their jobs (e.g., benefits), employers can ask them to complete a survey (or participate in an interview) that directly asks them the extent of their satisfaction. These scales have a number of benefits, including high reliability (i.e., consistency of responses across time and different items); face validity (i.e., they appear to measure what they are measuring, which is important for employees’ willingness to complete such measures); and practicality (i.e., questionnaires are relatively quick to complete and inexpensive to create or obtain). Limitations to this assessment method include variability in individuals’ motivation to report how they truly feel and think and their ability to accurately describe what they are feeling or thinking.
The various scales designed to measure JS can be sorted according to the following distinctions: (a) verbal versus pictorial, (b) global versus facets, and (c) cognitive versus affective (or a combination of both). With regard to the first distinction, the vast majority of JS scales ask participants to respond to a series of items on a Likert-type scale, usually ranging from very dissatisfied to very satisfied (or strongly disagree to strongly agree). However, the Faces Scale forgoes this verbal response system in favor of a series of faces depicting varying levels of satisfaction. Employees are then asked to choose the face that most closely reflects how they feel about their jobs. In general, the Faces Scale has been shown to be as good a measure of JS as scales that rely on Likert-type response formats.
Regarding the second distinction among JS scales, global (or general) measures of JS are characterized by their relatively small number of items (sometimes as few as one item) and their avoidance of asking about specific aspects of a job. Usually, global measures of JS include items such as “Overall, I am satisfied with my job” or “In general, I enjoy working here.” These types of scales offer a number of advantages, including their relative practicality (it may take only a minute or two to complete the measure) and strong relationships with multidimensional JS scales (i.e., those including several facets). JS scales that assess multiple facets of an individual’s JS are commonplace and vary widely in their length and the number of distinct facets assessed. These JS measures offer the advantage of greater specificity in the assessment of JS, which can be useful for gaining a greater understanding of employees’ satisfaction regarding specific aspects of their jobs. For example, although an employee may be generally satisfied with a job, examination of facet-level JS may reveal that he or she is dissatisfied with the supervisor, a situation that could potentially lead to performance problems or even result in the employee’s leaving the organization. Thus, both global and facet measures of JS have unique advantages and limitations that should be balanced with the purpose(s) for collecting the JS information.
The third distinction among JS scales involves that between cognitive and affective components of JS (previously defined). The vast majority of extant JS measures are more cognitive in nature, asking employees what they think about various facets of their jobs. However, a few JS measures are more affective in nature, asking employees how they feel about their jobs. Although these two types of measures do not tend to differ much in terms of their reliability or validity (i.e., their relations with other variables), recent JS research building on basic attitude theory has demonstrated the importance of measuring and considering both components of JS. That is, job incumbents have been shown to have distinct affective and cognitive perceptions of JS that may be quite different. For example, individuals may cognitively understand that for the work done, they are well compensated, yet at the same time not like the type of work they are doing (thus, a cognitively focused measure of JS might show them to be satisfied, whereas an affectively oriented measure might show the opposite). In addition, it is known that when cognitive and affective components of attitudes align, they are much more useful as indicators of subsequent behavior and attitudes (and this has recently been shown in the JS research specifically).
More recently, there have been some “new directions” in JS attitude measurement, using some techniques that are qualitatively different from verbal reports on JS scales. The first involves a more “interpretive” approach, an emphasis on employees’ reports of their JS and its important components (using the employees’ language) rather than reliance on predetermined facets of JS (using the researcher’s language). This approach involves asking employees to write unstructured accounts of satisfying and dissatisfying job experiences, and research using this approach has found that the language employees use to describe such experiences largely converges with the facets reflected in the more traditional JS scales.
Second, an interesting new methodology has developed that can be used for measuring employees’ job satisfaction, particularly its affective component. This methodology, referred to alternatively as experience sampling methods or ecological momentary assessment, allows researchers to capture momentary behaviors and psychological states in context and then track those behaviors and states over time. For example, an employee whose job satisfaction would be measured in this way would most likely receive a personal digital assistant (PDA) to carry for several days or weeks. This employee would be periodically cued throughout the day from the PDA and asked to report on his or her affective state. This very new approach to measuring JS has the advantage of being able to assess JS at a very detailed level and in “real time,” allowing for examination of changes in JS over time.
Determinants of Job Satisfaction
Given that JS is believed to be an important outcome of career-related actions, it is particularly relevant to review what factors contribute to an individual’s level of JS. These factors can be grouped into three categories: the individual, characteristics of the job and organization, and the intersection of the two.
Although it may seem intuitive that JS is primarily a function of the job, there are, in fact, a number of characteristics of individuals that, independent of the jobs they hold, will influence their general levels of JS. Among these factors are relatively stable personality traits, such as self-esteem, self-efficacy, and positive/negative affectivity, with research suggesting that people with greater self-esteem, greater self-efficacy, greater positive affectivity, and lower negative affectivity tend to report higher levels of JS. Investigation of the relationship between JS and personality traits has also focused on the five-factor model of personality, which comprises five traits: Neuroticism, Extraversion, Openness to Experience, Agreeableness, and Conscientiousness. Of these five traits, Neuroticism has the strongest relationship. Perhaps not surprisingly, this relationship shows that the more neurotic individuals are, the less likely they are to be satisfied with their jobs; thus, this is characterized as a negative relationship. Extraversion and Conscientiousness, on the other hand, are both related positively to JS; more extraverted and more conscientious employees tend to report higher JS.
From this evidence, it is clear that individuals’ perceptions of JS are reflective of not only their jobs but also who they are as people. In fact, levels of JS may even have a genetic component to them. Specifically, research based on identical twins shows that up to 30 percent of JS may be heritable, and identical twins reared apart have been shown to have very similar levels of JS as adults, even though they may hold very different jobs. In essence, research on the individual determinants of JS suggests that some people are more likely to be satisfied with their jobs regardless of their actual employment conditions (and therefore, across the career span). This is not to say, however, that employment conditions do not play any role at all, and those effects are reviewed next.
The examination of the effects of job characteristics on JS perceptions is, historically, perhaps the most studied aspect of JS. At the core of this idea is the belief that different working conditions will cause individuals to feel motivated and satisfied with their work or unmotivated and dissatisfied. Support for the doctrines of empowering workers, redesigning jobs, and building variety into task work arose from the assumption that employees would not be satisfied if they felt they were in boring and highly repetitive jobs. Decades of research in this area have reported mixed findings. In general, improving job characteristics such as autonomy, feedback, and skill variety does result in increased levels of JS. However, these relationships depend in large part on the personality of the individual employee, with some employees enjoying added flexibility and responsibility and others disliking it. This dependence on the characteristics of the individual employee brings us to perhaps the most recently and widely agreed-upon important determinant of JS: fit.
Fit between an individual and the employment situation can be conceptualized at both the job level, person-job (P-J) fit, and organizational level, person-environmental (P-E) or person-organizational (P-O) fit. Fit can be assessed in terms of demographic, personality, or values characteristics, and, in general, it is believed that persons who fit with the job and organization should experience more positive work outcomes, including higher levels of JS. For example, a highly competitive employee should be more satisfied in (a) a job that requires little cooperation and much intergroup competition and (b) an organization characterized by a highly competitive culture that rewards individual performance and tends to attract other competitive individuals. In general, research has supported these predictions regarding the important role of fit in determining JS.
Outcomes of Job Satisfaction
Over the course of nearly 100 years of research, JS has been linked to a number of important workplace outcomes, including job performance, withdrawal behaviors, burnout, and health.
Intuitively, the relationship between JS and job performance makes sense (that is, a happy worker should be a productive worker). However, the majority of research has not borne out this relationship, with studies generally finding only weak to moderate relations between JS and job performance. These findings are being continually revisited, however, with claims that (a) the older reviews of this relationship have been misinterpreted and (b) either JS or job performance has been conceptualized and/or measured in ways that do not expose this relationship. For example, recent research has shown that when JS attitudes are “strong” (i.e., an alignment between the cognitive and affective components), the relationship between JS and job performance increases significantly. Findings such as these, as well as the continued expansion of the definition of job performance to include contextual performance and organizational citizenship behaviors (i.e., employees going above and beyond the call of duty) have led to a renewed interest in understanding the role of JS in determining job performance.
In addition, it appears that the relationship between JS and job performance or career success may change somewhat over the course of an individual’s career. Careers are often identified using a three-stage approach: establishment, maintenance, and decline. During the establishment stage, there is little relationship between JS and job success, as JS can change as a person explores his or her career options (likewise, career success is generally low, but rises as the person finds the career in which they will remain). In the maintenance stage, JS and career success begin to align more closely, and both reach career high points. The decline stage is also marked with high consistency between JS and career success, with both levels slowly declining until retirement.
Withdrawal attitudes and behaviors such as commitment, absenteeism, intention to quit, and turnover have long been linked both empirically and theoretically to JS. The rationale behind these relationships is the commonsense notion that if you are dissatisfied with your job, you will (a) be less committed to your organization, (b) seek to avoid your job whenever possible (increased levels of absenteeism), and (c) possibly, if your dissatisfaction is strong enough, intend to or actually leave your job. In many models of employee turnover, JS is considered to be a primary determinant of employees’ forming the intention to quit their jobs, thus setting into motion a process that will result in their eventually leaving the organization. This is an important distinction, as research has shown that although JS is a weak predictor of actual turnover, it is a strong predictor of intention to turnover (i.e., quit). Thus, organizations interested in retaining their employees are well-advised to consider their employees’ JS.
Psychological Burnout and Health
In recent years, burnout and emotional exhaustion have been identified as important problems in the workplace, and research has shown that both stressful job conditions and employees’ low levels of JS can lead to an increased risk of burnout or emotional exhaustion (this type of research has focused almost exclusively on careers involving medical services or direct care, so additional research needs to be done on these relationships in other occupations). Interestingly, in many models of the burnout process, low JS is not by itself a direct cause of burnout; rather, it is a factor that can amplify the effects of a stressful or highly emotionally demanding job and/or workplace. In this context, therefore, low JS can be seen as an indicator of which individuals may be more susceptible to burnout. These established links between JS and burnout and experienced stress on the job become especially problematic when considered in conjunction with findings that levels of JS can “spill over” to affect general life satisfaction.
- Arvey, R. D., Bourchard, T. J. Jr., Segal, N. and Abraham, L. M. 1989. “Job Satisfaction: Environmental and Genetic Components.” Journal of Applied Psychology 74:187-192.
- Beal, D. J. and Weiss, H. M. 2003. “Methods of Ecological Momentary Assessment in Organizational Research.” Organizational Research Methods 6:440-464.
- Cytrynbaum, S. and Crites, J. O. 1989. “The Utility of Adult Development Theory in Understanding Career Adjustment Process.” Pp. 66-88 in Handbook of Career Theory, edited by M. B. Arthur, D. T. Hall and B. S. Lawrence. New York: Cambridge University Press.
- Hackman, J. R. and Oldham, G. R. 1976. “Motivation through the Design of Work: Test of a Theory.” Organizational Behavior and Human Performance 16:250-279.
- Judge, T. A., Heller, D. and Mount, M. K. 2002. “Five-factor Model of Personality and Job Satisfaction: A Meta-analysis.” Journal of Applied Psychology 87:530-541.
- Judge, T. A., Thoresen, C. J., Bono, J. E. and Patton, G. K. 2001. “The Job Satisfaction-Job Performance Relationship: A Qualitative and Quantitative Review.” Psychological Bulletin 127:376-407.
- Kristof-Brown, A. L. 1996. “Person-organization Fit: An Integrative Review of Its Conceptualizations, Measurement, and Implications.” Personnel Psychology 49:1-49.
- Schleicher, D. J., Watt, J. D. and Greguras, G. J. 2004. “Reexamining the Job Satisfaction-Performance Relationship: The Complexity of Attitudes.” Journal of Applied Psychology 89:165-177.
- Spector, P. E. 1997. Job Satisfaction: Application, Assessment, Cause, and Consequences. Thousand Oaks, CA: Sage.
- Taber, T. D. 1991. “Triangulating Job Attitudes with Interpretive and Positivist Measurement Methods.” Personnel Psychology 44:577-600.
- Weiss, H. M. 2002. “Deconstructing Job Satisfaction: Separating Evaluations, Beliefs and Affective Experiences.” Human Resource Management Review 12:173-194.