The Chaos Theory of Careers: a user's guide

Career Development Quarterly, June, 2005 by Jim E.H. Bright, Robert G.L. Pryor

The purpose of this article is to set out the key elements of the Chaos Theory of Careers. The complexity of influences on career development presents a significant challenge to traditional predictive models of career counseling. Chaos theory can provide a more appropriate description of career behavior, and the theory can be applied with clients in counseling. The authors devote particular attention to the application of attractor concepts to careers.

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The purpose of this article is to set out the key elements of the Chaos Theory of Careers and to illustrate how these fundamental concepts are particularly relevant to contemporary career development. In the process, we show how we have applied some of these concepts to counseling practice and have used a time-honored, but infrequently acknowledged, method of reasoning in an effort to illustrate how the demanding aspects of chaos theory can be communicated in user-friendly ways.

Traditional approaches to career development typically aim to understand the key attributes of the person and then match these to compatible or congruent environments (jobs). A recurring theme in the criticisms of traditional person-environment fit models by authors such as Savickas and Baker (in press); Krumboltz (1979); Mitchell, Levin, and Krumboltz (1999); Vondracek, Lerner, and Schulenberg (1986); and Lent, Brown, and Hackett (1996) is that the person-environment interaction has been characterized in trait-oriented terms (e.g., Dawis & Lofquist, 1984; Super, 1990). The relatively static nature of the terms of the interaction, person and environment, is no longer appropriate, given the complexities and change that are observed in modern careers. Arnold (2004) noted that congruence between the person and environment has been shown in several metastudies to correlate poorly (between 0.1 and 0.2) with outcome measures such as satisfaction (e.g., Assouline & Meir, 1987; Tranberg, Slane, & Ekeberg, 1993; Young, Tokar, & Subich, 1998). Arnold high-lighted the problem by observing that the concept of congruence in J. L. Holland's (1997) theory accounts for only 1% to 4% of the outcome measure variance. He proposed 14 problems with the theory, including inadequate conceptualization of the person and the environment, inadequate measurement of the environment, and the fact that job environments are increasingly demanding variety and diversity and that jobs are continually changing.

Several of vocational psychology's leading authorities (e.g., Mitchell et al., 1999; Pryor & Bright, 2003a, 2003b; Savickas & Baker, in press) have openly questioned the continuing value of traditional person-environment fit models of career choice, wondering whether they fail to capture adequately the complexities, uncertainties, and dynamic aspects of modern work. As Savickas and Baker have pointed out, "With less stable personalities and occupations, vocational psychology's basic model of person-environment fit with its goal of congruence seems less useful and less possible in today's labor market."

Career theorists are increasingly interested in approaches that characterize the individual and the environment in more complex and dynamic terms than the traditional person-environment approaches. Vondracek et al. (1986) directed attention to the multiplicity of contextual factors in career development. Mitchell et al. (1999) explored the role of unplanned events in career choice. Patton and McMahon (1999) used systems thinking to illustrate the complex interconnectedness of multivariate influences on individuals' career decision making. Savickas (1997) focused attention on individuals' capacities for change and creativity in the crafting of a career. As an extension of such thinking, we pose the question, "What conceptual framework of careers might be able to incorporate coherently such new ideas as complexity, change, and chance?"

Recently, several authors (e.g., Bloch, 1999; Drodge, 2002; Pryor & Bright, 2003a, 2003b) have begun to investigate the potential of chaos and complexity theory to explain career behavior. Chaos theory challenges traditional approaches to scientific explanation and goes to the heart of issues relating to what can be known and how it can be known. In chaos theory, two key concepts are nonlinearity and recursiveness. In linear systems, all the elements add up to make the whole, such as a credit card balance being equal to the amount of money spent plus interest and plus a monthly card fee. A nonlinear system is characterized by the elements adding up to more (or less) than the sum of the parts. For instance, the air time a song receives on the radio increases as the sales of the song propel it up the charts, which, in turn, increases the air time the song receives. In this scenario, the sales and airplay increase rapidly and nonlinearly. Of course, the final outcome sees a sharp decline in sales and airplay as the market becomes saturated and also tired of the song. This example also includes recursiveness--one variable influences another, which in turn influences the first one, and so on. Chaos theory (Gleick, 1988; Stewart, 1989) presents an account of the recursive application of several nonlinear equations to system behavior, resulting in elements of both stability and susceptibility to sudden and dramatic change at the same time. Furthermore, chaotic systems display other characteristics such as a lack of predictability at the micro level, while at the same time appearing to have a degree of stability at the macro level. In addition, their nonlinear nature means that minor events can have a disproportionate outcome on the system. Such ideas are permeating many areas of contemporary science. To cite just one example from Peacocke (2000), "[W]e know, through key developments in theoretical biology and physical biochemistry, that it is the interplay of chance and law that allows the matter of the universe to be self-creative of new forms of organization" (p. 44).