Many studies have found that the self-employed are more satisfied with their jobs than are wage and salary earners (for example, Duffy and Stevenson 1984; Hornaday and Vesper 1982; Katz 1993; Naughton 1987a, 1987b). However, all of this research has implicitly assumed that the self-employed are a homogeneous group. In reality, this is not the case the types of workers covered by the self-employed label include professional consultants, small family business owners, farmers, independent tradespersons, labor-only contractors, artists, and workers trying to make a living in self-employment who would otherwise be unemployed. We therefore might expect job satisfaction to vary markedly among different sub-groups of the self-employed. This article provides a partial test of this hypothesis. In particular, data from a survey of a representative sample of the Australian workforce are used to test for significant differences in reported job satisfaction between wage and salary earners, self-employed contractors, and other self-employed workers.
The focus on self-employed contractors can be justified on at least two grounds. First, it is widely believed that the prevalence of self-employed contractors in the labor force in industrialized countries has increased markedly during the last decade or so (McGregor and Sproull 1991; Pfeffer and Baron 1988). While hard data with which to establish this proposition are not available, it is clear that in virtually all OECD (Organization for Economic Cooperation and Development) countries, employers are moving away from the traditional pattern of full-time, permanent, waged work and instead, in their search for increased flexibility, are offering individuals a wide variety of working arrangements. Although most obvious here are permanent part-time work and temporary employment, contract employment is generally thought to have risen also in response to the same sorts of demands (Belous 1989; BAchtemann and Quack 1989; Davis-Blake and Uzzi 1993; McGregor and Sproull 1991).
Second, it is often claimed that many contract work arrangements involve a relationship between contractor and the hiring organization which differs little from the typical employer-employee relationship. That is, similar to an employee, the contractor is heavily dependent on the hiring organization for his or her income or livelihood and, moreover, has relatively little autonomy or control over working conditions. Thus independence one of the major advantages of self-employment is missing. At the same time, these contractors continue to bear all the risks associated with self-employment, such as poor job security and the absence of benefits typically available to employees. Self-employed contractors such as these have variously been referred to in the literature as the "fake self-employed" (Kuhl 1990), "bogus contractors" (Dombois and Osterland 1987) and "surrogate" employees (Burgess 1991). We have chosen to label them as "dependent contractors," thus emphasizing both the tendency for such workers to be counted among self-employed contractors and their dependence on the service recipient for on-going work and income. It is expected that such workers would be unlikely to be more satisfied with their jobs than employees working in otherwise comparable jobs. Indeed, we might expect far greater dissatisfaction.
The approach adopted in the article is as follows. After introducing the data and methods of analyses, results from bivariate analyses are presented. Then results of a regression model of job satisfaction are detailed. The model includes controls for employment status (that is, self-employed contractors, other self-employed workers, and employees) alongside controls for other personal and industry characteristics. The analysis is then repeated after separately distinguishing "independent contractors" from "dependent contractors." The importance of the results is discussed in the conclusions.
Data and Methods
The data used in this article were collected by the Australian Bureau of Statistics (ABS) as part of its May 1994 Population Survey Monitor (PSM). …