Measuring Career Orientations in the Era of the Boundaryless Career

Abstract

Schein proposed his career anchor construct more than 40 years ago. The purpose of our research is to use current career theory perspectives to reconceptualize and develop a measure that is grounded in the career anchor framework but better reflects the boundaryless nature of careers today. We conducted two studies in which we develop and validate a measure of career orientation by examining its internal structure (Study 1) and external validity within a nomological network of conceptually related variables (Study 2). Results suggest that career orientation is best represented by a six-dimension factor structure: entrepreneurial creativity, security, managerial competence, lifestyle, technical competence, and service to a cause. Five of the six factors that emerged were correlated as expected with proactive personality, ambition, career self-management behaviors, mentoring relationships, and workplace attitudes, providing support for our conceptualization and measure of career orientation. The implications for both theory and practice are discussed.

Keywords

career anchor career orientation boundaryless career protean career

Career scholars have observed that rapid changes in global trade, technology, organizational design, and workforce diversity over the last two decades have led to changes in the employee–organization relationship and the erosion of the traditional organization-based career (Arthur & Rousseau, 1996; Sullivan & Baruch, 2009). Classically, careers unfolded within the framework of a stable organizational structure with a clear linear progression up an organization’s hierarchy (Levinson, 1978; Sullivan & Baruch, 2009; Super, 1957). Within the traditional organizational career, the opportunities and constraints of one’s organization—job titles, pay grades, functional role hierarchies—acted as an external guide for one’s career. Success could be judged, both by the employee and by others, in terms of these external indicators. In the last several decades, with the decline in the traditional career, novel perspectives on how careers are approached by individuals and organizations have emerged. Two such perspectives include the boundaryless career as described by Arthur (1994) and protean career as described by Hall (1996).

Unlike the traditional career that is conceived and can unfold in a single organizational setting, the boundaryless career is a multifaceted phenomenon that can involve and transcend various boundaries both physically and psychologically (Arthur & Rousseau, 1996; Briscoe & Hall, 2006). In a boundaryless career, individuals can no longer rely on organizational promotions and internal career paths, and they are less likely to stay within a single “bounded” career path or organization (Arthur & Rousseau, 1996). Instead, individuals’ careers may cross many boundaries, as they move across work roles, organizations, occupations, and even forms of employment during their career. The implication for individuals is that they need to be “protean”—that is, versatile, mutable, and adaptable to the changing circumstances of their unfolding career (Briscoe & Hall, 2006; Briscoe, Hall, & Frautschy DeMuth, 2006).

According to Briscoe, Hall, and Frautschy DeMuth (2006, the protean career attitude is defined by two dimensions. The values driven dimension suggests that the individual’s internal values provide both guidance and measures of success for the individual’s career, while the self-directed dimension provides the ability to be adaptive in terms of both performance and learning opportunities. As such, the person’s career is based on the needs and goals of the whole person, and success is judged in terms of the person’s own internal, subjective criteria (Hall, 1996; Sullivan & Baruch, 2009). An individual with a protean career attitude needs to be resilient—ready, willing and able to adapt to changing career circumstances in the boundaryless career era.

In short, what these two perspectives suggest is that companies may no longer be able to offer upward, linear career mobility to motivate and retain individuals, and thus, understanding what motivates individuals’ career choices is important to retaining top performers and engaged employees. One framework that could help organizations better understand career choices is Schein’s career anchors (Schein, 1978, 1990). A career anchor identifies an individual’s career self-concept based on one’s attitudes and values, self-perceived talents and abilities, and career motives and needs (Schein, 1978, 1990). Because of its focus on internal values and needs, the career anchor framework can be useful for understanding the important drivers of individuals’ career choices in today’s boundaryless career. Yet, the career anchor framework was originally developed over 40 years ago when careers were more traditional. Thus, the potential of the career anchor concept has not been fully utilized because of certain outdated assumptions of the original construct as well as the limited empirical verification of career anchor measures (Feldman & Bolino, 1996; Igbaria & Baroudi, 1993). Thus, it is time to revisit and update the career anchor framework and measure.

The purpose of the current study is to reconceptualize this theoretical construct and develop a measure reflecting these theoretical revisions. To avoid confusion with Schein’s original career anchor framework, we will refer to our revised construct and measure as career orientations. We define career orientations as the features of work that define one’s career goals reflecting the individual’s self-concept regarding his or her self-perceived values, interests, experiences, skills, and abilities. Career orientations reflect the notion that internal values and self-direction are the drivers of career decisions in the protean and boundaryless career era. This is consistent with other scholars studying vocational behavior who have recognized the importance of individuals’ abilities, needs, and values to issues such as occupational choice (Holland, 1959), work adjustment (Dawis & Lofquist, 1984), and career development (Super, 1980). Thus, we contribute to the line of research that has examined how individual differences relate to career choices and decisions.

Specifically, by developing and validating a measure of career orientations, we contribute to the careers literature in three ways. First, we reconceptualize the career anchors framework so that its theoretical assumptions are more consistent with today’s boundaryless careers. Our main argument is that people tend to no longer remain with a single organization for long periods of time and similarly do not guide their careers based on a single career anchor. Instead, individuals are guided by multiple orientations and the set of orientations may change over their careers. Second, our study makes an empirical contribution to the careers literature by offering an updated, valid scale to measure career orientations. By allowing for the possibility of individuals having multiple career orientations at a time, as opposed to maintaining just one career anchor, and recognizing that individuals may need to shift the significance of their career orientation throughout their careers, our updated scale is better able to capture the realities of today’s boundaryless career. This revision will allow future researchers to further examine how career orientations impact individuals’ work attitudes, behaviors, and career decisions. Third, our updated scale offers a practical contribution by providing a measure that can enhance practitioner’s understanding of what motivates individuals’ career choices and work behaviors. We first theoretically develop our career orientations construct and then develop and validate our measure across two studies.

From Career Anchor to Career Orientation

Schein defined a career anchor as the individual’s overall career self-concept that consists of focal individuals’ attitudes and values, self-perceived talents and abilities, and most importantly, motives and needs as they pertain to one’s career (Schein, 1978, 1987, 1990, 2006). By defining priorities and values, career anchors provide individuals with a particular orientation toward work that guides how they approach their careers. Schein’s early work on career anchors, based on in-depth interview data, posited a typology of five distinct career anchors: (1) technical/functional competence, (2) managerial competence, (3) security and stability, (4) autonomy and independence, and (5) entrepreneurial creativity (Schein, 1978). Subsequent work by Schein (1987, 1990) proposed three additional career anchors: (6) service and dedication to a cause, (7) pure challenge, and (8) lifestyle.

In formulating the concept of the career anchor, Schein sought to develop an understanding of how individuals establish for themselves a source of direction and coherence in their careers. A principal assumption underlying Schein’s model is that individuals have only one true career anchor and do not have multiple anchors. He argues that, even in the face of difficult choices, a career anchor is the one element in a person’s self-concept that one would be unwilling to give up (Schein, 1990). However, the assertion that individuals hold only one dominant anchor may be an artifact of methods that forced respondents to choose only one anchor (Schein, 1978, 1987, 1990). As Feldman and Bolino (1996) note, “On a purely statistical level, arbitrarily adding extra points to higher ranking items (as Schein does) forces a distinction which does not exist in the raw data” (p. 105). In contrast, studies that have used Likert scaling techniques to measure respondents’ agreement with each of the scale items (e.g., Danzinger, Rachman-Moore, & Valency, 2008) have found that the anchors correlate in ways that suggest individuals may identify with multiple anchors. Overall, the empirical research does not support Schein’s assumption that individuals hold only one true anchor. Another vital assumption of Schein’s anchor model holds that fundamentally, career anchors do not change. More specifically, Schein (1990) suggests that as individuals mature, their future career choices stabilize along with their career anchor. Schein (2006) further argues that career anchors are built on job experiences and the feedback one receives regarding one’s competencies, motives, and values. As such, the career anchor is viewed as a stabilizing force in providing coherence to career decisions and in guiding future career directions. Because the empirical studies testing Schein’s career anchor framework have all been cross-sectional surveys or interview studies, it is unknown whether Schein is correct in assuming that career anchors are a stabilizing force. In fact, Schein (1990) acknowledges that although there is evidence on the side of stability, the empirical evidence is inconclusive.

In terms of measurement, researchers have primarily relied on Schein’s (1990) 40-item career anchor inventory scale to measure career anchors despite there being little evidence for the scale’s psychometric properties. One problem is that Schein’s career anchor scale has shown reliabilities below .70 for some of the dimensions (e.g., technical/functional, creativity; Danziger, Rachman-Moore, & Valency, 2008). More importantly, there have been inconsistent results in the number of factors represented by the scale (Feldman & Bolino, 1996). For example, studies reporting exploratory factor analyses of the 40-item scale have revealed a 4-factor solution (Nordvik, 1996), a 9-factor solution (Danziger et al., 2008; Marshal & Bonner, 2003; Petroni, 2000), and an 11-factor solution (Igbaria, Greenhaus, & Parasuraman, 1991).

Based on the discussion above, one can conclude that a number of the basic aspects of the career anchor concept are still questioned: How many anchors exist? Can an individual hold more than one anchor? Is one’s career anchor stable over time? We address these questions through our conceptual development of career orientations. First, in terms of the number of distinct orientations that may be relevant to describing work features, we believe this is an empirical question worth investigating. In general, we believe Schein’s eight anchors defined in terms of abilities, needs and interests, and values, include the important features of work that may be important to individuals as they navigate career choices in a boundaryless career environment. However, the number of possible dimensions that can comprise career orientations remains an empirical question.

Second, in terms of the number of anchors that may be salient to an individual at a given point in time, our career orientation construct is more in line with what previous scholars have suggested, and as such more reflective of current career perspectives. Although Schein argued that each person has a single career anchor that is more important than any other anchor, Feldman and Bolino (1996) argue that individuals can have multiple career anchors of differing intensity and that the significance of any one anchor may change over time as a result of new experiences and challenges. Our approach to the career orientation construct and measure reflects this view. Specifically, we expect individuals to be able to rate themselves highly on more than one career orientation at a time. Shifting the significance of one’s career orientation, as opposed to maintaining just one career anchor, may be necessary in order to adapt to environmental changes. In this regard, Feldman and Bolino also describe two important observations regarding Schein’s career anchors: (a) Although Schein suggests that all career anchors are composed of self-perceived abilities, needs, and values, Feldman and Bolino (1996) note that each career anchor appears to be composed of primarily one of these underlying psychological constructs. (b) They also suggest that, because different career anchors may be different types of psychological constructs, it is possible for an individual to rate themselves highly on more than one of them at the same time. This suggests that in today’s protean and boundaryless career environment, it makes more sense for people to have multiple career orientations as opposed to just one career anchor.

Third, regarding the stability of any one career orientation, our conceptualization of career orientation allows for the possibility of changes in an individual’s values and needs as a result of new career paths that are driven and managed by the individual, not the organization. According to Gubler, Arnold, and Coombs (2014), people who have a protean career orientation develop their own idea of what makes up a successful career and take appropriate action to adapt to a changing environment. Schein argued that the (single) career anchor develops after several years of experience and then does not change. In contrast, we believe individuals identify with certain career orientations early in their career based on their early work experiences, personal values, and perhaps parental values. Individuals may continue to feel that some orientations are important throughout their careers, but other orientations may become more or less important over time based on significant career or life experiences, such as being fired from a job or having children. It may be that orientations are stable in the short term but change over longer time periods. The changes in the work environment over the past few decades require individuals to be more “protean”—that is, versatile, mutable, and adaptable to the changing circumstances they encounter. As such, it is imperative that contemporary measures used to inform career research reflect the current landscape of careers today. In sum, although our definition of career orientation shares conceptual similarities to the career anchor concept in terms of focusing on perceived skills, the needs important to one’s career, and internal values we differ in terms of the multidimensional nature of the distinct orientations and the stability of orientations over time.

Study 1

The purpose of Study 1 was to develop a measure of career orientations following the scale development process outlined by Hinkin (1998). Our approach involved five steps: (1) generate items; (2) administer a questionnaire to assess psychometric properties of the new items; (3) perform exploratory factor analysis for initial item reduction; (4) perform confirmatory factor analysis (CFA) of retained items with an independent sample; (5) provide construct validity evidence through convergent, discriminant, and criterion-related validity. We completed Steps 1–3 and part of Step 5 (convergent/discriminant construct validity) in Study 1. Step 4 and the criterion-related validity of Step 5 are completed in Study 2.

We initially developed scale items to capture the eight orientations identified by Schein’s career anchor framework (1990). These eight orientations included technical/functional competence—the value for and desire to become an expert in one’s chosen occupation; managerial competence—the value for and desire to become a general manager and rise to organizational levels with significant profit/loss responsibilities; autonomy—the value for and desire to have freedom and independence in one’s job; security and stability—the value for and desire to have financial and job security; entrepreneurial creativity—the value and drive to create new ventures, develop new products or services, or build new organizations (this definition includes corporate intrapreneurship); pure challenge—the value for and desire to work on difficult problems and having to overcome obstacles; service and dedication to a cause—the value for and desire to improve the world in some way that fits a specific value; and lifestyle—the value for and desire to have flexibility to integrate and manage one’s life and work issues as necessary. Our first objective was to explore the validity of these eight career orientations.

Research Question 1: Does the career orientation construct comprise the following 8 dimensions: technical/functional, managerial, autonomy, security/stability, entrepreneurial creativity, pure challenge, service and dedication to a cause, and lifestyle?

It is important to note here that previous empirical evidence (Nordvik, 1991) suggests that career anchors are correlated with each other to varying degrees. Based on Schein’s definitions and Nordvik’s findings, Feldman and Bolino (1996) proposed an octagonal model in an effort to reconcile and determine the underlying patterns of career anchor types. Their octagonal circumplex model suggested that some career orientations were fairly similar to each other, while others were quite orthogonal such that individual who scores highly on one orientation is likely to score higher (or lower) on another. Although we see the virtue in the proposed circumplex structure in which certain orientations are expected to occur together, we work from the more modest proposition that the orientations are positively (or negatively) correlated with each other. Because specific hypotheses would depend on which orientations emerge from our examination of Question 1, we do not offer formal hypotheses. But, in general, we expect the correlations to be consistent with the circumplex model of Feldman and Bolino (1996). In particular, we expect managerial competence to be positively related to entrepreneurial creativity; security to be negatively related to entrepreneurial creativity; and security/stability, service, and dedication to a cause, and lifestyle to be positively related. Our approach therefore builds on the conceptual work done by Feldman and Bolino (1996) by empirically examining their propositions concerning the relationships among the career anchor dimensions.

Method and Results

Step 1: Item generation

We first deductively generated an initial set of 120 items to measure the eight career orientations. For each dimension, we developed items reflecting the content domain based on Schein’s (1990) definition of the related career anchor. In doing so, we ensured items tapped into either one’s values, self-perceived abilities, or motives and needs, the core aspects of a career anchor (Schein, 1990). Our initial set of items included a few scale items developed by Premarajan (2001). Content validity of the items was assessed by four PhD students who were asked to independently assign each item to one of the eight career orientations based on Schein’s definitions and as reported above. Items that were assigned to the same orientation by three of the four academics were retained for further analysis. From this initial content validity procedure, we retained 60 scale items for the next stage of scale development.

Step 2: Questionnaire administration

The 60 items generated in Step 1 were administered to 271 working upper-class undergraduate and part-time MBA students at a large, public Midwestern university. Although they were mostly business majors, the students take positions in a wide variety of occupations and industries upon graduation. For example, according to the College’s placement services, recent graduates’ jobs ranged across financial services, sciences, media/entertainment, sports/leisure, health care, and government industries. Respondents were asked to indicate the extent to which they agreed that each statement represents their own values and motives with respect to work. Items were scaled from 1 = Strongly Disagree to 7 = Strongly Agree. Participation was voluntary, anonymous, and did not affect students’ course grades. We received completed surveys from 207 of the students (33% of which were MBA students) for a 76% response rate.

Step 3: Exploratory factor analysis and initial item reduction

We followed a two-stage process to refine the 60 scale items. First, because we had a priori factors based on theory, following Hinkin’s (1998) recommendations, we examined interitem correlations among the sets of items designed to measure each a priori factor (e.g., all items intended to measure managerial career orientation). Items that correlated less than .40 with all of the other scale items for that dimension were eliminated from the exploratory factor analysis in order to remove items producing error and unreliability (Hinkin, 1998). This resulted in 9 items being eliminated.

As a second stage, we conducted a series of exploratory principal axis factor analyses to determine the number of factors actually represented by our scale items. Because our intention was to develop a scale in which the scale items measuring each dimension “are reasonably independent of one another, an orthogonal rotation is recommended for this analysis” (Hinkin, 1998, p. 112). Thus, we used varimax rotation. Our initial analysis of the 51 remaining items resulted in 12 factors with eigenvalues greater than 1, explaining 70% of the total variance. To produce a set of more interpretable factors, we eliminated 18 items that loaded on more than one factor at or above .40 (4 items), did not load above .40 on any factor (8 items), or loaded above .40 on a factor with only 1 other item (6 items; the last three factors were each composed of only 2 items and explained less than 2% of the variance). We reanalyzed the reduced item pool (33 items) again using principal axis factor analysis and varimax rotation. This resulted in a six-factor solution with eigenvalues greater than 1.0, explaining 67% of the cumulative variance. Each of the six factors clearly corresponded to six of the proposed career orientation (anchor) dimensions and none of the 33 items cross loaded on more than one factor. In order to reduce the overall scale length, we retained the 5 highest loading items for five of the factors and retained all 4 items for the sixth factor. A principal axis analysis on the final set of 29 items was performed (see Table 1 for results).

Table 1.

Exploratory Factor Analysis Results of the Career Orientation Scale From Study 1.

	Factor^a
Career Orientation Scale Item	1	2	3	4	5	6
I am very good at developing innovative new procedures, products, or services.	.88
I find work most interesting when I am working on the development of a new product, service, or work process.	.78
I enjoy work that involves building or creating something that is entirely new.	.78
One of my greatest strengths is developing, creating, and launching new products or services.	.77
I have the kinds of skills and abilities required to be a successful entrepreneur.	.62
Employment security is important to me.		.88
It is important that my organization provides me with job security.		.86
I would value working at an organization that offers long-term job security.		.79
Financial security is important to me.		.67
Organizations should strive to provide job security for their employees.		.59
It is important to me to have a job that helps society in some way.			.88
Contributing positively to society through work is important to me.			.83
It is important to me to have a job that is compatible with my desire to improve the world.			.80
I will feel successful in my career only if I am making a real contribution to the welfare of society.			.78
It is important to me that I have a job that provides “family-friendly” benefits so that I can balance my work and home life.				.82
Balancing my work and personal needs is important to me.				.72
An ideal organization to me is one that allows employees the time they need to be with their families.				.68
My career must provide me with good work-life balance.				.67
It is important that I work for an organization that values family/personal life.				.66
I would like a position with a great deal of managerial responsibility.					.77
I have the skills and abilities to eventually rise to a high managerial level.					.72
I would like to manage an entire organizational division or profit-center someday.					.71
I have the kind of skills and abilities that make one an effective general manager.					.66
I have the dedication required to rise to a high managerial level.					.59
I would pursue a position that would allow me to become more proficient in my technical/functional specialty.						.78
I prefer work that challenges my technical or specialized skills and abilities.						.74
I prefer having a job in which I can fully utilize my technical/functional expertise.						.72
If given the choice, I would prefer an advancement that allows me to continue to use my specialized technical skills.						.69
I enjoy work that allows me to learn something new in my area of specialization.						.51
Eigenvalue for each factor	6.09	4.82	3.72	2.28	1.76	1.48
Variance Explained by each Factor	21.00	16.63	12.81	7.85	6.06	5.12
Total Variance Explained						69.48

Note. N = 207.

^aFactor 1 = entrepreneurial creativity orientation; Factor 2 = security orientation; Factor 3 = service to a cause orientation; Factor 4 = lifestyle orientation; Factor 5 = managerial orientation; Factor 6 = technical/functional orientation.

The six components to emerge from these analyses were clearly interpretable as the following career orientation: entrepreneurial creativity (α = .90), security (α = .89), service to a cause (α = .91), lifestyle (α = .85), managerial (α = .85), and technical/functional (α = .84). All items intended to measure the “pure challenge” and “autonomy” orientations were eliminated due to factor loadings above .40 on multiple factors in the initial factor analysis. The correlations among the dimensions appear in Table 2. Of the 15 correlations, 8 are statistically significant with the strongest correlation between managerial orientation and entrepreneurial creativity (r = .44, p < .01). None of the dimensions are significantly, negatively correlated. Step 4 (confirmatory factor analysis with independent sample) will be done in Study 2.

Table 2.

Descriptive Statistics and Correlations Among Our Career Orientation Dimensions and Schein’s Career Anchors.

Study 1 Sample
Variable	Mean	SD	1	2	3	4	5	6	7	8	9	10	11	12	13	14
1. Entrepreneurial creativity orientation	4.90	1.20	(.90)
2. Security orientation	5.66	.98	−.09	(.89)
3. Lifestyle orientation	5.85	.83	.00	.37**	(.85)
4. Technical/functional orientation	5.39	.86	.12	.32**	.26**	(.84)
5. Managerial orientation	5.52	.92	.44**	.19**	.07	.23**	(.85)
6. Service to a cause orientation	4.66	1.27	.31**	−.05	.28**	.09	.02	(.91)
7. Schein entrepreneurial	4.67	1.19	.69**	−.06	−.06	−.04	.26**	.27**	(.80)
8. Schein security	4.66	1.05	−.18*	.76**	.31**	.16*	.14*	−.06	−.15*	(.80)
9. Schein lifestyle	5.39	.79	−.03	.25**	.66**	.04	.01	.19**	.03	.28**	(.57)
10. Schein technical	4.90	.72	.21**	.22**	.10	.47**	.24**	.16*	.14*	.27**	.07	(.41)
11. Schein managerial	4.28	.84	.32**	.15*	.00	−.05	.55**	.05	.30**	.15*	−.00	.19**	(.56)
12. Schein service to cause	4.73	1.03	.30**	−.07	.27**	.10	.07	.82**	.30**	−.03	.24**	.28**	.15*	(.78)
13. Schein autonomy	4.95	.90	.36**	−.25**	.04	−.13	.07	.35**	.47**	−.31**	.11	.09	.20**	.31**	(.71)
14 Schein pure challenge	4.90	.87	.42**	−.13	.08	.21**	.38**	.34**	.42**	−.19**	.01	.37**	.31**	.45**	.24**	(.72)

Note. N = 207. Coefficient αs estimating reliabilities are in parentheses along the diagonal.

*p < .05. **p < .01.

Step 5: Discriminant and convergent construct validity

Convergent validity can be assessed by correlating our new scale with measures designed to assess similar constructs; discriminant validity is demonstrated if our new measure does not correlate with dissimilar measures (Hinkin, 1998). In our case, Schein’s (1990) 40-item scale designed to measure his career anchors is an alternative measure to our career orientation scale. We therefore had included Schein’s 40-item career anchor scale in our questionnaire that was completed by the Study 1 sample. Per Schein’s (1990) instructions, we averaged the 5 items designed to measure each of the eight career anchors to compute scale scores for each anchor. Reliabilities for Schein’s original eight scales are entrepreneurial creativity (α = .80), security (α = .80), lifestyle (α = .57), technical/functional competence (α = .41), managerial competence (α = .56), service and dedication to a cause (α = .78), autonomy (α = .71), and pure challenge (α = .72).

Convergent validity is demonstrated when the correlations between measures of similar constructs (e.g., managerial orientation and managerial anchor) using different methods (e.g., our new career orientation measure versus Schein’s career anchor scale) are sufficiently large and significantly different from zero (Campbell & Fiske, 1959; Hinkin, 1998). Examination of the correlations of this monotrait–heteromethod diagonal revealed that all of these correlations were large and statistically significant (r ranged from .47 to .82, average r = .66, p < .01). Correlations among our career orientation dimensions and Schein’s career anchors are reported in Table 2.

Discriminant validity is demonstrated when three conditions are met. First, correlations between measures of the same construct with different methods (monotrait–heteromethod) should be greater than correlations between different constructs with different methods (heterotrait–heteromethod). For example, the correlation between our managerial career orientation and Schein’s managerial career anchor should be greater than the correlation between our managerial career orientation and all of the other career anchors measured with Schein’s scale. As noted above, in our sample, all correlations of the monotrait–heteromethod diagonal exceeded .47. The largest correlation in the heterotrait–heteromethod matrix (directly below the monotrait–heteromethod diagonal in Table 2) was r = .32, which was between our entrepreneurial orientation and Schein’s managerial anchor. Thus, the first condition was met. Second, correlations between the same construct using different methods (monotrait–heteromethod) should be larger than correlations between different constructs measured with the same measure (heterotrait–monomethod; e.g., the correlations for our managerial career orientation with all other career orientation dimensions). As noted above, in our sample, all correlations in the monotrait–heteromethod diagonal exceeded .47. The largest correlation in the heterotrait–monomethod matrix (correlations among our career orientation dimensions) was r = .44, which was between managerial orientation and entrepreneurial orientation. Thus, the second condition was also met. Third, similar patterns of correlations should exist in the heterotrait–monomethod matrix and within the heterotrait–heteromethod matrix. In our sample, the heterotrait–monomethod correlations ranged from r = −.09 between security and entrepreneurial orientation to r = +.44 between managerial and entrepreneurial orientations. The heterotrait–heteromethod correlations ranged from r = −.18 between Schein’s security anchor and our entrepreneurial orientation to r = .32 between Schein’s managerial anchor and our entrepreneurial orientation. In addition, comparing the 15 correlations across the two matrices, 14 of the correlations are in the same direction and the majority are of a similar magnitude. Thus, the patterns of correlations within the two matrices are quite similar and meet the third condition. In sum, our new career orientation measure demonstrated good convergent and discriminant validity in relation to Schein’s career anchor scale.

Finally, we examined the correlations among the six career orientations measured with our new scale (see Table 2). Consistent with Feldman and Bolino’s (1996) circumplex model, we found that managerial and entrepreneurial orientations were significantly correlated (r = .44, p < .01), service to a cause and lifestyle orientation were significantly correlated (r = .28, p < .01), and technical and security orientations were significantly correlated (r = .32, p < .01). Also consistent with Feldman and Bolino’s circumplex model, security and entrepreneurial were not related, and managerial and service orientations were not related.

Discussion

Through the scale development process followed in Study 1, we developed a 29-item scale to measure six career orientations: entrepreneurial orientation, security, lifestyle, technical/functional, managerial, and service to a cause (all scales composed of 5 items except for service to a cause, which is composed of 4). The results demonstrate that our new career orientation scale, relative to Schein’s 40-item career anchor scale (Schein, 1990), had good convergent and discriminant validity, yet was rigorously developed to ensure content validity, independent factors, and scale items with strong internal consistency. Our findings contribute to theoretical development of the career anchor concept in two ways.

First, our results demonstrate that not all of the eight orientations identified by Schein emerged. In particular, items designed to tap two of the career anchors—autonomy and pure challenge—did not surface as their own unitary dimensions. One conclusion might be to regard these anchors as unimportant or irrelevant to career orientation. However, examination of the items that were dropped renders this conclusion unlikely in our judgment. Many of these items were eliminated due to the fact that they loaded on several dimensions of our scale. Similarly, the correlations in Table 2, show that Schein’s autonomy and pure challenge scales significantly correlated with three and four, respectively, of our career orientation dimensions. Thus, it may be that these items tap psychological processes or drives that underlie several of the career orientations identified by the principal axis analysis. For example, challenge may underlie an individual’s desire for managerial competence, entrepreneurial achievements, technical/functional competence, or fulfillment of service to a cause. This view is consistent with Mainiero and Sullivan’s (2005) kaleidoscope career model in which one’s desire for challenge is considered to be one of three motivators that underlie individuals’ career decision making to varying degrees throughout their career. Future research is necessary to determine whether autonomy and pure challenge should be considered as underlying motives that explain individuals’ career orientations.

A second theoretical contribution is finding that the six career orientation dimensions behave as continuous variables, with a normal distribution of individuals over the range of each dimension, rather than a bimodal distribution as suggested by a typological approach. Further, the mostly weak to moderately positive correlations among the dimensions suggest that an individual’s score on one dimension does not determine his or her score on any of the other dimensions. Thus, as Feldman and Bolino (1996) argue, it appears that individuals can hold multiple career orientations of differing intensity at the same time.

A limitation of Study 1 is that the student sample from a single US university limits the generalizability of the findings. Although students were working at least part time and the university from which the sample is drawn is culturally diverse, we do not know if our findings generalize to individuals more advanced in their careers or in other countries. We address the career stage limitation in Study 2 by using a sample with a diverse age range.

Study 2

In Study 2, we conducted a CFA of our career orientation scale using an independent sample (Step 4 of the scale development process) and examined criterion and discriminant construct validity (Step 5). Because this second study was conducted in a single manufacturing organization, we and our contact person in the organization did not feel the service to a cause orientation was relevant to this sample. We therefore did not include this orientation in Study 2. To assess criterion and discriminant validity, a number of variables that we theoretically expected to be related to certain career orientation dimensions, but not others, are examined. This includes two individual difference variables that have been shown to be relevant to the protean career construct: proactive personality (Seibert, Kraimer, & Crant, 2001) and desire for upward mobility (London, 1983). We also included two variables related to an employee’s career development: career self-management and mentoring received. In addition, we examined how two work attitudes (willingness to relocate and continuance commitment) and five work behaviors (organizational tenure, innovative performance, promotability, managerial competence, and technical competence) may be differentially related to career orientation. We developed hypotheses for how each of these variables are expected to be related to the career orientation dimensions only if there was theoretical justification for a significant relationship. However, we conducted a robust test of the nomological network by including all five career orientations in the test of the hypotheses, enabling us to test convergent and discriminant validity for the career orientation dimensions.

Hypotheses

Entrepreneurial Creativity Career Orientation

Individuals high in entrepreneurial orientation are principally motivated by the need to create something that is entirely their own project and enjoy moving from project to project to escape boredom (Feldman & Bolino, 1996; Schein, 1978, 1990). We therefore expect that individuals high in entrepreneurial orientation are more likely to be high in proactive personality. Proactive personality is defined as the disposition to take initiative in a broad range of situations and environments and has been shown to be related to entrepreneurial behaviors (Crant, 2000). In addition, entrepreneurial creativity should be related to behaviors that show initiative at work, such as engaging in career self-management. Activities associated with career self-management include seeking feedback, engaging in career planning, and proactively finding ways to develop one’s skills (Sturges, Guest, Conway, & Davey, 2002). Finally, we also expect that individuals with an entrepreneurial creativity orientation engage in more innovative behaviors at work since such individuals perceive themselves to be creative.

Hypothesis 1: Entrepreneurial creativity orientation is positively related to proactive personality, career self-management, and supervisor ratings of innovative performance behaviors.

Security Career Orientation

Individuals high on the security orientation value employment and financial security from an organization. We expect security to be associated with an unwillingness to relocate for the organization. Individuals who value security may not want to risk the “known” benefits of their current position for the “unknown” of another position even one that might offer a higher level opportunity or more developmental experience (Feldman & Bolino, 1996; Schein, 1978, 1990). Essentially, individuals with a high security orientation are likely to be risk avoiders and would view relocating as a potentially risky job decision.

Hypothesis 2a: Security career orientation is negatively related to willingness to relocate.

On the other hand, we would expect individuals high on security orientation to be stable employees who are highly committed to their organization (Schein, 2006). These individuals view stability as a means to maintaining their financial security. Thus, high-security-oriented individuals may feel they need to stay with the organization. Leaving the organization would represent a loss of accrued benefits and rewards that come with organizational tenure. This type of commitment to an organization has been referred to as continuance commitment (Meyer, Allen, & Smith, 1993). Based on the notion of attitude–behavior consistency, the knowledge and skills individuals acquire during their tenure plays a role in keeping their behavior, including job employment, consistent (Fabrigar, Petty, Smith, & Crites, 2006).

Hypothesis 2b: Security orientation is positively related to continuance commitment and organizational tenure.

Lifestyle Career Orientation

Individuals with a high lifestyle career orientation strive for situations that allow for the integration of family, personal, and career concerns and opportunities for self-development (Petroni, 2000). Moreover, consideration of a spouse’s attitude toward a move, the impact the move has on a spouse’s career, and concerns about moving children all can affect a person’s willingness to relocate a family (Eby & Russell, 2000). Often, this means that the individual will not easily relocate his or her family for the purposes of career advancement.

Hypothesis 3: Lifestyle career orientation is negatively related to willingness to relocate.

Managerial Career Orientation

Individuals who score highly on the managerial career orientation are motivated to have primary profit and loss responsibility and be in higher managerial levels. These individuals desire the power and achievement potential that top positions can offer (Tan & Quek, 2001). We therefore expect that they will report a desire for upward mobility and a willingness to relocate in order to achieve higher level positions. Individuals with a managerial orientation are also energized by the opportunity to analyze and solve problems under conditions of incomplete information and ambiguity and look forward to responsibility for the productivity of the organization (Feldman & Bolino, 1996; Schein, 1978, 1990). These types of challenging managerial tasks require individuals to take initiative and responsibility for developing their skills to succeed in these situations. We therefore argue that a managerial orientation is associated with proactive personality and career self-management behaviors. We also expect that individuals with a managerial orientation seek to learn from senior managers and be perceived by senior managers as worthy of mentoring. Finally, because promotions are, at least partly, based on job performance (Lyness & Thompson, 2000), we contend that individuals with managerial orientations are motivated to perform well, especially on managerial tasks, and, thus, are also perceived as more worthy of promotion.

Hypothesis 4: Managerial career orientation is positively related to proactive personality, desire for upward mobility, career self-management, mentoring received, willingness to relocate, and supervisors’ assessments of managerial competence and promotability.

Technical/Functional Career Orientation

Individuals scoring high on technical/functional career orientation value the opportunity to continue to develop their skills in their area of expertise and to apply those skills to increasingly challenging and complex problems. They are principally energized by the content of the work itself and prefer advancement only in their technical or functional area of proficiency (Feldman & Bolino, 1996; Schein, 1978, 1990). Individuals with this orientation seek opportunities to exercise their technical skills, and their identity is tied to a job that allows them to enhance these skills (Petroni, 2000). This type of individual is essential for organizations that both implement and maintain technical infrastructures and processes (Marshall & Bonner, 2003). Enhancing their technical/functional skills through continued training and development initiatives coupled with viable promotion opportunities will help retain the intellectual capital attained by these individuals (Marshall & Bonner, 2003). Arguably, because these individuals prefer advancement in their areas of proficiency and seek opportunities to apply their skill set to increasingly challenging problems (Tan & Quek, 2001), they desire upward mobility within an organization.

Hypothesis 5: Technical/functional career orientation is positively correlated with supervisors’ assessments of technical competence and desire for upward mobility.

Method

Sample and Procedures

Surveys were mailed to the homes of 512 exempt-level employees (those not legally entitled to overtime pay) who worked in a Fortune 500 manufacturing company and, in a separate mailing, to the homes of their corresponding supervisors. Employees were randomly chosen from the organization’s U.S. facilities and represented all major functions at the corporate level (e.g., production, research and development, marketing, accounting), as well as plant management, and sales and service personnel. A human resources representative within the company provided us with the home addresses for employees and their supervisors. Surveys were assigned code numbers so that we could match employee and supervisor surveys upon return. Employees and supervisors were assured confidentiality and were instructed to complete the survey and return it directly to the authors in the postage-paid envelope provided. The original survey was followed by a postcard reminder 1 week later and another complete survey packet to nonrespondents 3 weeks after that.

A total of 290 employees (56.6% response rate) and 326 supervisors completed the surveys (these data were collected as part of a larger study and were used in Kraimer, Seibert, Wayne, Liden, & Bravo, 2011). Of those, there were 208 matched employee–supervisor pairs with complete data for an effective overall response rate of 41%. The average age of employee respondents was 45 years, 66% were male, 77% were married, and 93% were White. Eight percent held a high school diploma as their highest degree, 25% held an associate’s degree, 41% held a bachelor’s degree, and 26% held a master’s or higher degree.

Measures—Self-report

All scales were measured on a scale from 1 (strongly disagree) to 7 (strongly agree) unless otherwise noted.

Career orientation

The 25 items for the corresponding five factors developed in Study 1 were used in this study (see Table 1). Reliabilities in the current sample were acceptable across all orientations: entrepreneurial creativity (α = .83), security (α = .87), lifestyle (α = .90), technical/functional (α = .83), and managerial (α = .90).

Proactive personality

We used Seibert, Crant, and Kraimer’s (1999) 10-item proactive personality scale. An example item is “If I see something I don’t like, I fix it” (α = .87).

Desire for upward mobility

We used 3 items from Wayne, Liden, Kraimer, and Graf (1999) to assess employees’ desire for upward mobility. An example item is “I am not interested in moving from my present job to a higher-level position” (reverse scored; α = .83).

Career self-management

Nine items selected from Sturges, Guest, Conway, and Davey (2002) and Tharenou and Terry (1998) assessed career self-management. Respondents indicated on a scale from 1 (not at all) to 5 (a very large extent), to what extent they had engaged in certain career management activities. An example item is “I have engaged in career path planning” (α = .86).

Mentoring received

Mentoring was assessed using Dreher and Ash’s (1990) 8-item career mentoring scale. Respondents indicated on a scale from 1 (not at all) to 5 (a very large extent), to what extent an influential, more experienced manager has engaged in certain activities to help them develop their careers within the organization. An example item is “Encouraged you to prepare for advancement” (α = .92).

Willingness to relocate

A 3-item version of Eby and Russell’s (2000) scale was used to assess willingness to relocate. An example item is “I am not willing to relocate for any reason” (reverse scored; α = .82).

Continuance commitment

Continuance organizational commitment was assessed with 6 items from Meyer, Allen, and Smith’s (1993) measure. An example item is “It would be very hard for me to leave my organization right now, even if I wanted to” (α = .79).

Organizational tenure

Respondents reported how many years and months they have been working for the current organization; we report organizational tenure in terms of years.

Measures From Supervisor

All scales were measured on a scale from 1 (strongly disagree) to 7 (strongly agree) unless otherwise noted.

Innovative performance

The four innovation items from Welbourne, Johnson, and Erez’s (1998) role-based performance scale were used to assess innovative performance. Supervisors rated employees on a scale from 1 (needs much improvement) to 5 (excellent) on dimensions of their performance. An example item is “Works to implement new ideas” (α = .61).

Promotability

We used 4 items from Wayne et al. (1999) to assess employees’ promotability. An example item is “If I had to select a successor for my position, it would be this employee” (α = .90).

Managerial competence

Three items developed for this study assessed employees’ managerial competence. An example item is “This employee has what it takes to be an effective manager in this organization” (α = .96).

Technical Competence

Three items developed for this study assessed employees’ technical competence. An example item is “(this employee) is an expert in his/her technical or functional area” (α = .93).

Analyses and Results

To complete the scale development process (Hinkin, 1998), we present results of a CFA (Step 4) and regression analyses testing the hypotheses for criterion-related convergent validity (Step 5).

Step 4: CFA

To test the quality of the five-factor structure of the 25-item career orientation scale, we conducted a CFA using LISREL 8.80. This analysis is based on responses from 287 employees who provided complete data on the career orientation scales. We specified five, correlated, latent factors with scale items loading only on their respective factor. The results indicated acceptable fit for this five-factor model (χ² = 687.26, df = 265, p < .01; CFI = .95; NFI = .92; SRMR = .07; RMSEA = .07). The five-factor model fits significantly better than a model in which all correlations among the latent factors were set equal to 1 (analogous to a one-factor model; Δχ² = +189.40, Δdf = 10, p < .01; CFI = .92; NFI = .89; SRMR = .34; RMSEA = .09) and better than all of the possible four-factor models, in which two factors were allowed to be perfectly correlated (all Δχ² = +26.02, Δdf = 1, p < .05). In the five-factor model, all scale items had statistically significant lambda estimates to their respective factors (p < .01).

Step 5: Criterion-related construct validity

Means, standard deviations, and intercorrelations among the study variables are reported in Table 3. The correlations among some of the career orientation dimensions were again statistically significant. We therefore used multiple regression analyses including all five career orientation variables to test the unique effects of each of the hypothesized career orientation dimensions on the outcome variables. The results of the multiple regressions are reported in Tables 4 and 5.

Table 3.

Descriptive Statistics, Correlations, and Reliability Coefficients for Study 2 Sample.

Variables	Mean	SD	1	2	3	4	5	6	7	8	9	10	11	12	13	14	15	16
1. Entrepreneurial orientation	5.48	.94	(.83)
2. Security orientation	6.09	.81	.12	(.87)
3. Lifestyle orientation	5.95	.95	.20**	.57**	(.90)
4. Technical/functional orientation	5.96	.78	.35**	.50**	.45**	(.83)
5. Managerial orientation	5.31	1.26	.41**	−.01	.08	.05	(.90)
6. Proactive personality	5.63	.68	.51**	.05	.15*	.16*	.56**	(.87)
7. Desire for upward mobility	4.82	1.52	.29**	−.13	−.04	.07	.59**	.35**	(.83)
8. Career self-management	3.11	.80	.43**	−.08	−.01	.08	.50**	.38**	.40**	(.86)
9. Mentoring received	2.66	.91	.21**	.01	.14*	.10	.29**	.18**	.14*	.37**	(.92)
10. Willingness to relocate	3.79	1.67	−.09	−.19**	−.18**	−.03	.25**	.12	.40**	.16*	.11	(.82)
11. Continuance commitment	3.96	1.34	−.10	.29**	.10	.13	−.24*	−.09	−.25**	−.27**	−.25**	−.27**	(.79)
12. Organizational tenure (years)	13.07	10.06	−.08	.07	−.03	−.10	−.18**	−.07**	−.29**	−.16*	−.11	−.10	.30**
13. Innovative performance	3.77	.79	.24**	−.03	.06	.12	.18**	.19**	.16**	.21**	.29**	.11	−.16*	−.04	(.61)
14. Promotability	4.43	1.80	.16*	−.05	.11	.36	.30**	.16*	.30**	.29**	.34**	.16*	−.27**	−.19**	.60**	(.90)
15. Managerial competence	4.80	1.70	.15*	−.07	.03	.01	.37**	.20**	.24**	.26**	.33**	.17*	−.20**	−.02	.59**	.81**	(.96)
16. Technical competence	5.57	1.35	.23**	−.04	−.11	.07	.14*	.07	.16*	.27**	.20**	.09	−.10	−.01	.54**	.50**	.59**	(.93)

Note. N = 208. Coefficient αs estimating reliabilities are in parentheses along the diagonal.

*p < .05. **p < .01.

Table 4.

Regression Results for Individual Differences and Career Development Outcomes.

Predictor Variable	Proactive Personality	Desire for Upward Mobility	Mentoring Received	Career Self-Management
Entrepreneurial orientation	.32**	.05	.08	.29**
Security orientation	−.01	−.15*	−.09	−.09
Lifestyle orientation	.06	−.08	.14	−.08
Managerial orientation	.42**	.58**	.24**	.39**
Technical/functional orientation	.00	.14*	.05	.05
R ²	.41	.39	.11	.33
Adjusted R ²	.40	.38	.09	.32
ANOVA F	28.19**	26.01**	5.05**	20.18**

Note. N = 208. Standardized regression coefficients (β) are reported. ANOVA = analysis of variance.

*p < .05. **p < .01.

Table 5.

Regression Results for Work Attitudes and Behaviors.

Predictor Variables	Willingness to Relocate	Continuance Commitment	Organizational Tenure	Innovative Performance^a	Promotability^a	Managerial Competence^a	Technical Competence^a
Entrepreneurial orientation	−.14	−.05	.04	.18*	.03	−.01	.22**
Security orientation	−.15	.31**	.18*	−.13	−.16	−.12	.01
Lifestyle orientation	−.17*	−.05	−.05	.05	.17*	.06	−.20*
Managerial orientation	.31**	−.22**	−.18**	.09	.27**	.36**	.06
Technical orientation	.14	.03	−.18*	.09	.02	.03	.07
R ²	.13	.15	.06	.08	.11	.15	.09
Adjusted R ²	.11	.13	.04	.06	.09	.12	.07
ANOVA F	6.19**	6.94**	2.74*	3.52**	5.21**	6.88**	3.86**

Note. N = 208. Standardized regression coefficients (β) are reported. ANOVA = analysis of variance.

^aWork behavior was assessed by supervisor.

*p < .05. **p < .01.

Entrepreneurial creativity career orientation

The regression analyses indicated that the β weight for entrepreneurial career orientation was positive and statistically significant, predicting proactive personality (see Table 4), career self-management (see Table 4), and supervisor’s ratings of innovative performance (see Table 5). Thus, Hypothesis 1 was fully supported. Although not hypothesized, entrepreneurial orientation also positively related to supervisor’s ratings of technical competence (see Table 5).

Security career orientation

Per Table 5, the regression coefficient for security orientation predicting willingness to relocate was not statistically significant. However, the β weight for security orientation was positive and statistically significant in the equations predicting continuance commitment and organizational tenure. This supports Hypothesis 2b but not 2a.

Lifestyle career orientation

As shown in Table 5, the β weight for lifestyle career orientation was negative and statistically significant in the equation predicting willingness to relocate. This provides support for Hypothesis 3. Unexpectedly, it also positively related to supervisor’s assessments of promotability and negatively related to technical competence ratings.

Managerial career orientation

The β weight for managerial career orientation was statistically significant and positive in the equations predicting proactive personality, desire for upward mobility, mentoring received, career self-management, willingness to relocate, promotability, and managerial competence (see Tables 4 and 5). Thus, Hypothesis 4 was fully supported. Although not hypothesized, managerial career orientation was also negatively related to continuance commitment and organizational tenure.

Technical/functional career orientation

As can be seen in Table 5, the technical career orientation did not significantly predict supervisor’s assessments of technical competence, but it was positively related to desire for upward mobility (see Table 4). Thus, we found partial support for Hypothesis 5. Technical career orientation was also significantly, negatively related to organizational tenure.

General Discussion

In Study 1, we developed scale items to correspond to Schein’s eight career anchors. Following a rigorous scale development process, the resulting factor structure suggested that these items best represent six dimensions of career orientation: entrepreneurial creativity, security, managerial, lifestyle, technical/functional, and service to a cause. Our results suggest that these are continuous rather than typological variables and that individuals may indicate that more than one of these career orientation dimensions are salient at the same time. We did not find support for the notion that autonomy and pure challenge are unique anchors that define career orientation. Instead, individuals identifying with several different career orientations seem to value autonomy and job challenge. It may also be that autonomy and job challenge are secondary orientations that become subsumed by one or more of the other six orientations. For example, some basic level of autonomy may be necessary but not sufficient to achieve lifestyle balance or entrepreneurial creativity in one’s career. We believe future research focused on these variables within their own domain may prove fruitful.

In Study 2, we found theoretical support for Schein’s definitions of five of the career orientations by showing that they mostly correlated as expected with proactive personality, career self-management behaviors, mentoring by senior colleagues, and attitudes toward one’s organization and work. In particular, strong support was found for our hypothesized relationships for entrepreneurial career orientation, lifestyle career orientation, and managerial career orientation. At the same time, a few unexpected relationships emerged in our sample. Overall, our results provide empirical evidence for our reconceptualization of the career orientation construct and suggest some avenues for future refinement.

Theoretical Implications

Using Schein’s career anchor framework as a theoretical foundation for our research, we developed and validated a multidimensional measure of career orientation. By doing so, we address the need to empirically verify a measure of career orientations that has both sound psychometric properties and reflects the changes that have occurred in how employees view their careers. Such a measure will enable researchers to utilize an instrument that captures a current perspective of the internal career needs of today’s employee. We hope that our career orientation scale will revitalize research on individual’s internal career goals and values. Indeed, our findings for each of the dimensions offer theoretical insights and future research opportunities.

The managerial career orientation dimension had the most consistent support across all of the hypothesized relationships. In particular, we found that a managerial career orientation positively related to nine of the criterion variables demonstrating its relevance to a wide variety of employee attitudes and behaviors, at least within a large organizational setting. Although seven of these relationships were hypothesized, we also unexpectedly found that managerial orientation negatively related to continuance commitment and organizational tenure, suggesting that such individuals may more readily move organizations in order to attain higher managerial positions. As one of Schein’s original anchors, our scale to measure managerial career orientation appears to exhibit considerable criterion validity.

The entrepreneurial creativity career orientation also appears to be robust as we found support for all three relationships hypothesized. A significant but unexpected relationship also emerged with supervisor ratings of technical competence. In retrospect, this makes considerable sense. It is likely that one would need relatively high competence in one’s technical knowledge in order to initiate worthwhile innovations. If we compare the entrepreneurial orientation with the managerial orientation, we find a great deal of overlap in the criterion variables to which each is related. It appears that the main difference between these two dimensions of career orientation is the desire for upward movement within the organization in the managerial orientation versus the desire to create new products, services, or processes for the entrepreneurial orientation. Future research is needed to further examine how entrepreneurial orientation differs from a managerial orientation in terms of career paths and work style choices. For example, this career orientation might be used to predict who will be most effective in new product start-up operations or who might leave the organization to become an entrepreneur.

The technical/functional career orientations dimension, which was also included in Schein’s original set, showed few significant relationships to the other variables in our study: technical/functional orientation positively related to desire for upward mobility and negatively related to organizational tenure. Nonetheless, these relationships seem to make sense. Because individuals with a technical/functional orientation prefer advancement in their areas of expertise and seek to apply their skill set to increasingly challenging problems, they desire upward mobility within an organization in order to achieve this, even if this movement is along a technical rather than managerial career track. Research has indeed demonstrated that employees with specialized skills are less willing to accept downward movement (Noe, Steffy, & Barber, 1988). It therefore stands to reason that as individuals are in the process of enhancing their technical/functional skills, they are doing so with the idea that such activity will lead to upward movement as opposed to remaining stagnant or moving downward.

Regarding our finding that technical/functional career orientation negatively related to tenure, it may be that only newer employees in the organization we studied continue to hold this career orientation and they either change their orientation or leave the organization over time. In fact, research suggests that as tenure in an organization increases, employees achieve a better understanding of the way technical work is accomplished (Zenger & Lawrence, 1989). Accordingly, it seems reasonable to suggest that as employee tenure increased in our sample, the orientation toward attaining and/or enhancing technical skills diminished as a result of the level of comfort they felt with their positions. Perhaps those individuals with more tenure are closer to having achieved their career goals, and as a result, do not feel the need to enhance their technical/functional skills any further. Future research will have to examine these relationships more closely if these contentions are to be substantiated.

As expected, security career orientation was positively related to organizational tenure and continuance commitment. Individuals who self-identify with a desire for job and financial security appear to be more stable employees. It is also interesting to note that individuals high on security orientation were not any more or less likely to indicate a willingness to relocate. Perhaps such individuals are willing to relocate in order to remain employed with the same organization, rather than risk employment stability by refusing a transfer or stay where they are geographically and search for another job. Overall, this career orientation is associated with behaviors and outcomes identified by Schein.

People higher on the lifestyle orientation were however less willing to relocate. It is likely such individuals consider their family’s interests and desires as equally important if not more important when it comes to making company requested relocation decisions. We feel it is worth noting here that, although not hypothesized, we also found that lifestyle orientation was negatively related to supervisors’ assessments of technical competence, yet positively related to promotability assessments. We found this a bit paradoxical and suggest that future research further investigate the relations among individuals’ desire for work/life balance, technical competence, and promotion potential within organizations.

Practical Implications

From a practical standpoint, the multidimensional nature of the career orientation construct developed here offers some implications for the workplace that may help to keep protean employees committed to their current organization. Specifically, an understanding of the dimensions and scales identified here can help employers better support their employees’ career goals. We recommend that organizations assess the career orientation of each of their employees and use this information in career development sessions. Individuals who are high on entrepreneurial orientation will desire opportunities to develop new products and services. It is important that these individuals be given the opportunity to work on projects that enable them to fulfill these internal career needs. Not only will this likely enhance employee satisfaction but will benefit the organization, as entrepreneurial orientation was significantly related to innovative performance. In contrast, rather than focusing on innovative projects that may involve risk in terms of whether they will be successful, individuals high on security orientation may value core positions that are less likely to involve risk. These individuals are also less likely to desire upward mobility. Consequently, career plans for these individuals could be comprised of lateral positions perhaps within the same department and thus involving less change and risk.

Our finding that employees with a lifestyle orientation are less willing to relocate suggests that development plans that consist of internal career opportunities that do not require relocation are more likely to retain these employees and at the same time help them have satisfying careers. The large number of significant relationships for managerial orientation provides several implications for career development plans for individuals high on this orientation. Individuals high on managerial orientation are proactive, willing to relocate, have mentors, and engage in career self-management. They also have a strong desire for upward mobility. At the same time, these individuals are high on managerial competence and have less commitment and tenure in their organizations. The implication is that these individuals are more likely to leave for career opportunities in other organizations if their career needs are unmet. Thus, for individuals with high managerial orientation, it is important that organizations have clear development plans and monitor closely the extent to which these plans are realized to avoid losing these individuals. Finally, individuals high on technical orientation also have a strong desire for upward mobility but prefer to remain in a technical career path. This supports many organizations’ career ladders that provide for both technical and managerial career paths.

Another practical use of our career orientation measure is in assisting individuals in identifying organizations with career opportunities that are in alignment with their career orientations. The ability to self-assess one’s career orientations may be especially valuable for individuals starting their careers. For example, individuals who are high on service and dedication to a cause may be advised to seek out employers whereby there is a fit between their orientation and the organization’s mission. In contrast, individuals high on managerial orientation may desire employers who promote from within and have a strong management development system. Career development systems that are in alignment with employees’ career orientations are likely to be associated with high employee career satisfaction and commitment.

Strengths and Limitations

One strength of this research is that we followed recommended scale development processes (e.g., Hinkin, 1998) in developing our career orientation scale using two separate samples to identify and then confirm the factor structure. The two studies together provide strong empirical support for our multidimensional model of career orientation. Another strength of this research is that our career orientation scale was grounded in a strong theoretical framework provided by a rich career anchor literature. The main limitation of the current study was that our analyses relied on cross-sectional, correlational data. Thus, we cannot draw conclusions about the causal directions underlying our findings. A second limitation of this research is that the mostly Caucasian sample from a single U.S. organization in Study 2 limits generalizability of these findings. A third limitation is that the sample used in Study 2 to externally validate the measure included only exempt-level employees of a large manufacturing organization. This may have resulted in a disproportionate emphasis on the managerial orientation and it precluded us from validating the service to a cause orientation in Study 2. We note that, because the career orientations are independent dimensions, this limitation does not negate the validity of the findings for the other five dimensions we uncovered. We encourage future research to further validate our career orientation constructs in a more diverse sample where service to a cause may be deemed more relevant.

Conclusion

Traditional theories of careers that were based on the predictability and stability of job security within a single organization or industry have given way to fresh and innovative ways of examining careers in this new work context (Sullivan & Baruch, 2009). Contemporary career theories, including the boundaryless and protean career concepts, are more representative of today’s ever changing work environment. Missing until recently has been the rigorous empirical research that can inform and support this growing area of inquiry (Briscoe & Hall, 2006; Briscoe et al., 2006). We addressed this empirical gap by developing and validating a scale to measure career orientations. Although the career orientation concept is not a new one, it seemed appropriate at this time to offer an updated valid scale that can extend this framework so that its theoretical assumptions are more consistent with today’s boundaryless careers. We hope our research and resulting scale will encourage future research to continue to investigate how individuals’ career orientations impact work attitudes, behaviors, and career decisions.

Footnotes

Authors’ Note

The data used in this study were collected as part of a larger project that was funded by the University of Illinois’ Center for Human Resource Management (CHRM). The conclusions are those of the authors and do not necessarily represent CHRM.

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) received no financial support for the research, authorship, and/or publication of this article.

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