The Role of Future Orientation and Negative Career Feedback in Career Agency and Career Success in Australian Adults

Abstract

Future orientation is crucial for young people to achieve career-developmental milestones, yet little research has examined the role of future orientation in attaining career outcomes in adult samples. Using the future orientation framework, we tested direct effects of future orientation on career agency (proactive career behaviors and work effort) and career success (perceived employability and career adaptability), indirect effects via career agency variables, and conditional effects of negative career feedback in the future orientation-career agency-career success relationships. We surveyed 285 adults (M = 38.38 years) and conducted structural equation and moderated mediation analyses. Future orientation was associated positively with work effort, proactive career behaviors, career adaptability, and perceptions of employability. Work effort and proactive career behaviors mediated the future orientation-career success relationship. The mediation via career behaviors (but not work effort) was dependent on the level of received negative career feedback. The results have theoretical and practical implications.

Keywords

future orientation career agency career success negative career feedback career adaptability perceived employability

The nature of careers has noticeably changed over the last few decades. Due to the rapid changes and advancements in technology and significant economical swings due to unprecedented circumstances (e.g., COVID-19 pandemic), people are now asked more than ever to demonstrate their ability to cope with these changes and thrive in this new world. They are expected to show a positive, future-oriented career mindset; that is, show interest in the future, set future-oriented goals, anticipate optimistic future outcomes, and invest in future-oriented planning and activities (Johnson et al., 2014; Stoddard et al., 2011). They also need to show proactivity and adaptability in their careers, as these are important agentic skills linked to effective career management and career success (Chen et al., 2020; Savickas, 1997; Savickas & Porfeli, 2012). However, what are the relationships between these concepts and the specific processes behind successful career management?

In the present study, we tested an adapted version of the integrative future orientation framework (Johnson et al., 2014), assessing career constructs important for work as it is understood today. This framework is useful because it helps to explain the relationships between future, goal-oriented mindset, behaviors, and successful outcomes and transitions, while also taking into consideration contextual factors that influence these processes. Specifically, guided by the framework, we assessed the direct and indirect relationships between future orientation, career agency (i.e., work effort and proactive career behaviors) and career success (i.e., career adaptability and perceived employability) in an adult population, and assessed the conditional effect of negative career feedback in the future orientation → career agency → career success processes. To date, the predominant focus in the area of future orientation has been on adolescent academic, personal, and career development (Seginer, 2008). Notably, there has been limited evidence testing the complex, integrative model in adult populations, despite future orientation being as pertinent to this group as it is to adolescents. As Seginer (2008) argued, it is a relevant construct for times of frequent changes and personal transitions that require preparation for what lies ahead.

Future Orientation

Thinking about the future is a characteristic feature of the human mind (Nurmi, 2005), considered vital to the successful building of a career, making important career decisions, and adapting to changes in a career path (Savickas & Porfeli, 2012; Zimbardo & Boyd, 1999). From the expectancy-value theory of motivation (Wigfield & Eccles, 2000), future orientation can be viewed as a goal-oriented tendency to focus one’s mind on the future and future valued outcomes. Some people are better able to create an image of themselves in the future, anticipate what their future holds, and think about their hopes, possibilities and the likely outcomes of these than others. They do this by reflecting on their current attitudes and behaviors and how these are related to their desired future goals and anticipated attainments (i.e., they are able to see the future consequences of their current behaviors; Cabras & Mondo, 2018). Consequently, it provides them with purpose and meaning in life (Seginer, 2008).

As a result, people with stronger future-orientation typically show a higher propensity for future-oriented exploration, goal-setting, commitment-making, and planning, and are generally more motivated and eager to implement their plan by active engagement in goal-oriented activities to attain those anticipated positive outcomes (Bandura, 2001; Cabras & Mondo, 2018; Nurmi, 1991; Seginer, 2008; Shipp et al., 2009). Research showed that future orientation is an important predictor of a wide range of outcomes, including greater academic achievement (Peetsma & van der Veen, 2011), more developed identity, including career identity (Luyckx et al., 2010; Pulkkinen & Rönkä, 1994; Strauss et al., 2012) and life satisfaction (Zhang & Howell, 2011). Future orientation is also associated with the use of adaptive self-regulatory behaviors, such as better planning and managing education, and increasing motivation, learning effort, and persistence in time of difficulties (de Bilde et al., 2011). People differ in the extent to which they are able to think and foresee their future, and, in turn, act on the anticipated events (Hejazi et al., 2013; Zimbardo & Boyd, 1999). We selected future orientation as the key individual-differences predictor of successful career outcomes.

The conceptualization of future orientation has evolved over time, from the main focus on the single, cognitive self-construed image of oneself in the future, to an increasingly more developed and multifaceted construct currently represented by numerous definitions and overlapping conceptualizations. For example, future orientation has been defined as the anticipation and evaluation of future self (Pulkkinen & Rönkä, 1994; Trommsdorff, 1983) or the image people have about themselves in the future that guides their behaviors and overall developmental course, including setting goals, plans, making commitments, and actions (Seginer, 2008). Taking the “time perspective” view, future orientation can also be defined as an allocation of attention to the future (Shipp et al., 2009) or being a dispositional “bias” toward the future characterized by a pattern of thoughts and behaviors that reflect striving for future goals and outcomes (Zimbardo & Boyd, 1999).

This brief overview of definitions highlights that future orientation comprises cognitive, motivational, and behavioral aspects. In synthesis, the cognitive aspect reflects thinking about what a person would like and dislike the future to be, but also reflects the frequency and saliency of thoughts people have about the future, and their evaluation of the value and expected attainment of those outcomes (Pulkkinen & Rönkä, 1994; Seginer, 2008; Trommsdorff, 1983). The motivational aspect is manifested in general interest in the future and purpose in life expressed as self-set goals, but also in a strong drive to invest in future-oriented thinking, and drive and confidence to face the future, pursue those set goals, and achieve growth and success (Nurmi, 1991; Seginer, 2008; Trommsdorff, 1983; Zimbardo & Boyd, 1999). The behavioral aspect of future orientation reflects people’s ability to make plans and enact actions and strategies to help them progress and attain their future goals (Nurmi, 1991; Seginer, 2008; Zimbardo & Boyd, 1999). In addition, attitudinal/affective aspects of future orientation were also proposed (Johnson et al., 2014), including an optimistic mindset that good things will happen (Scheier & Carver, 1985) and having hope, or a positive feeling and expectation that set goals will be achieved in the future as a consequence of personal agency and planning to accomplish those set goals (Snyder et al., 1991). Having a positive attitude toward the future is important, as it is likely to strengthen the value of set goals and motivate actions directed toward future outcomes.

Most recently, Johnson et al. (2014) proposed a future orientation framework where future orientation plays an important role in adolescent engagement in promotive/risk behaviors and successful transition to adulthood within the context of individual and environmental influences. Johnson et al. (2014) integrated existing definitions and conceptualizations, describing future orientation as the ability to think, set goals, plan for, and anticipate the future. In this integration, people with stronger future orientation have expectations (i.e., positive impressions and hopes for the future), aspirations (i.e., think about future possible selves, set goals and intentions for the future), and plan (i.e., ability to action out and achieve the aspirations). Research testing this framework in relation to predicting adolescent risky behaviors is growing (not reviewed here), but is yet to be confirmed with other populations and across other domains of life. From developmental and career self-management perspectives, career development does not end in adolescence (Havighurst, 1973; Lent & Brown, 2013) but continues throughout the lifespan. Thus, as future orientation is considered a powerful influence on much of human functioning (Zimbardo & Boyd, 1999), and acts across a whole range of life domains (Seginer, 2008; Trommsdorff, 1983), we adopted Johnson et al.’s (2014) framework to assess future orientation in relation to important career success outcomes. We focused on the adult population to account for the career developmental and management tasks that adults face at careers today.

Future Orientation and Career Success

Future orientation is an important dispositional factor contributing to success in the career domain. People with greater future orientation have clearer goals, have better planning skills, and stronger abilities to overcome challenges (Johnson et al., 2014). They think about the future, have positive expectations about the future, believe they have good control over future events, and generally feel more motivated—these are all important attributes for achieving career success (Savickas & Porfeli, 2012). Progress wise, future orientation creates a discrepancy between the current state of affairs and where one wants to be (Johnson et al., 2014; Locke & Latham, 1990). This is motivating for a person, in that it stimulates effort and engagement in future-directed behaviors to close this gap, and, in turn, contributes to educational and career outcomes (Johnson et al., 2014). This value and expectancy-driven self-directedness when pursuing and/or managing an important career then results in a greater perception of career success (Hall & Chandler, 2005). Previous research refers to a variety of markers of psychological career success, including life, job, and career satisfaction, continuous self-development, perceived employability, and career adaptability (Arnold & Cohen, 2008; Arthur et al., 2005; Dries et al., 2008). In our study, we operationalized career success as career adaptability and perceived employability.

Career adaptability is a central construct in career psychology (Rudolf et al., 2017) and a key competency in achieving career success and satisfactory career development (Chen et al., 2020; O’Connell et al., 2008; Savickas, 1997). It is described as the ability to manage and adjust to work-related changes, including conquering developmental tasks, dealing with work concerns and setbacks, and navigating career transitions (Savickas, 1997). Being embedded in career construction theory (Savickas & Porfeli, 2012), and consistent with the future orientation framework (Johnson et al., 2014), it is theorized that people engage in future-oriented cognitive and agentic processes (i.e., planning, goal setting, and exploration) to help them construct their career, and, ultimately, develop career adaptability (Savickas & Porfeli, 2012). Being a skill important for navigating today’s world of work and meeting the demands for being active and adaptable to realize career goals (Fugate et al., 2004) and cope effectively with career transitions (Wittekind et al., 2010), career success in adults is likely to manifest in greater career adaptability. The career-specific literature supports these claims, indicating that positive expectations for future career and career planning attitudes (i.e., career optimism) are likely to result in successful career adaptability (Rottinghaus et al., 2005). Consistent with this, research found that future orientation and planning ahead showed positive associations with career adaptability in students (Duffy, 2010; Fugate et al., 2004; Savickas & Porfeli, 2012). Future focus also emerged as the strongest and the most reliable predictor of career adaptability and its domains in a study using large samples of Australian working adults (Zacher, 2014). Thus, being an important part of life design and success (Savickas & Porfeli, 2012), we expected that future orientation would be positively associated with career adaptability.

Similarly, a positive perception of employability has become an increasingly important aspect of career success (Rothwell & Arnold, 2007; Rothwell et al., 2008). We live in a turbulent world of unstable and insecure economical markets and face more career transitions than ever before. At least in Western cultures that promote the model of “modern” careers, career responsibility now lies with individuals and their own agency to manage it (Vanhercke et al., 2014). Thus, it is crucial that people develop employability skills and strategies to help them gain and/or maintain their work. In addition, it is equally important that they develop self-confidence (subjective perception) about their ability to use these skills to manage their careers (Rothwell et al., 2008; Wittekind et al., 2010) and then act on those perceptions (Vanhercke et al., 2014).

From this individual-level (subjective) perspective, perceived employability is the perception an individual has about the possibilities of obtaining and maintaining employment (Vanhercke et al., 2014), or the ability to retain the job one has or find the job one desires (Rothwell & Arnold, 2007). As such, perceived employability is relevant to young adults who appraise their standing in the future career markets after completing their education and/or training (Gunewan et al., 2018). Likewise, it is also relevant to the middle-aged and aging workers who appraise themselves in terms of meeting the demands of rapidly changing markets and remaining competitive and re-employable (van der Heijde & van der Heijden, 2005). Perceived employability, thus, reflects people’s ability to see themselves positively in their current organization or a future career based on their evaluation of internal and external contextual factors. It involves having confidence in the knowledge and career-related skills attained through formal education, work experiences and other career-enhancing activities, as well as confidence in established professional networks. It also reflects positive perceptions of being valued in their organization and/or perception that there is a demand for those skills in the labor market (Rothwell & Arnold, 2007; Rothwell et al., 2008; Vanhercke et al., 2014). In summary, perceived employability involves people’s appraisal of their own skills, experiences, networks, personal attributes, and the knowledge of labor market (Gunawan et al., 2018).

Perceived employability can be distinguished from other subjective perspectives, namely, competence-based employability and dispositional employability. From the above review, perceived employability revolves around the evaluation of one’s position and value in the labor market. On the other hand, the focus of competence-based employability (Van der Heijden, 2002; van der Heijde & van der Heijden, 2005) is predominantly on evaluating abilities (e.g., personal flexibility), while the dispositional employability (Fugate et al., 2004) reflects the motivational aspects of employability (e.g., work and career proactivity). Vanhercke et al. (2014) proposed a theoretical model that offers insight into the processes involved in people’s evaluation of their employability. Specifically, competencies and dispositions in this model were proposed to be the person-based antecedents of perceived employability (i.e., perceived employability is the outcome of mastering competencies and proactive attitudes), with context (i.e., labor market) influencing these perceptions. Notably, while all three perspectives refer to the internal and external labor market, only the perceived employability perspective made this distinction clear, and was applied to different groups, including university students, the employed, and the unemployed (Vanhercke et al., 2014). We selected this perspective for our study, as it was more inclusive and, consistent with our hypothesized model, portrayed employability as the key career outcome of agentic personal and environmental factors (and their interactions).

Self-perceived employability and future orientation are concepts related theoretically. The future orientation framework (Johnson et al., 2014) stipulates that a stronger focus on the future is associated with positive and hopeful expectations about the future. Thus, future orientation should also be associated with career-relevant expectations, such as more positive perceptions of employability. Drawing from related literature, Wittekind et al. (2010) found that future orientated attributes, such as awareness of work-related opportunities and qualifications, and willingness to gain new skills and knowledge of the labor market, were all contributing to positive perceptions of self-perceived employability over time. Similarly, studies found that aspects of future-orientation, such as hope and optimism, predicted greater self-perceived employability in working adults (Kasler et al., 2017; Kirves et al., 2013). Last, drawing from the organizational literature on temporal focus, future focus in working adults was associated with more positive perceptions of future working conditions (e.g., autonomy, advancement, pay), and more positive attitudes toward the future (Shipp et al., 2009). Thus, we also expected to find a positive relationship between future orientation and self-perceived employability.
H1. From this review, we hypothesized that future orientation would be associated positively with career success (i.e., perceived employability and career adaptability).

Future Orientation and Career Agency

The current demand on people to manage their own careers through uncertain futures means that it is important to understand how people choose to engage in proactive career behaviors. According to social cognitive (Bandura, 2001; Lent & Brown, 2013) and goal setting (Locke & Latham, 1990) theory, people are active agents of their environment, drawing on their personal attributes and strengths to set, pursue, and manage important life goals. From these perspectives, career agency is the ability to participate in one’s own career and engage in proactive career behaviors to help direct career and educational development to reach envisioned goals. It represents the motivational factor in people’s career journey driven by future orientation (Lens et al., 2012).

Relatedly, future orientation scholars (Johnson et al., 2014; Nurmi, 2005) argued that future-oriented individuals have the right mindset that helps them engage in adaptive processes (e.g., anticipating and planning for the future, regulating effort and behaviors) to get them where they want to be. Thus, future-oriented thinking facilitates people’s development; it stimulates cognitive, motivational, and behavioral processes to help them reach anticipated outcomes. Future orientation is not only relevant to developing children and adolescents, it is a crucial attribute that stimulates career agency in adults too (Nurmi, 2005). Research supports this. Future orientation has been associated with a range of career-enhancing behaviors, including greater academic engagement (Horstmanshof & Zimitat, 2007), more career goal setting, planning and exploration (Patton et al., 2004), greater engagement in proactive career behaviors (Parker & Collins, 2009; Strauss et al., 2012), and stronger drive for success and accomplishment in a chosen career (Strauss et al., 2012). In our study, we assessed two important markers of agency aimed at managing one’s career direction and progress through uncertain times: goal-directed effort (i.e., persistence, direction, and intensity toward gaining and/or maintaining work; De Cooman et al., 2009) and proactive career behaviors (e.g., creating career opportunities, work involvement, and self-presentation; Gould & Penley, 1984).
H2. We hypothesized that future orientation would be associated positively with career agency (i.e., work effort and proactive career behaviors).

Future Orientation, Career Agency, and Career Success

Exhibiting positive personal attitudes and agency in career goal pursuit (Gould & Penley, 1984; Johnson et al., 2014), even in the face of unexpected career events, is vital to successful career development and management (Savickas & Porfeli, 2012). From the future orientation perspectives (Johnson et al., 2014; Seginer, 2008), thinking about, and envisioning oneself in, the future career should activate future-oriented processes aimed at achieving a successful overall developmental course, including making career goals and plans, increasing motivation and goal-directed effort, and engaging in proactive career behaviors directed toward meeting the outcomes one expects. Increased effort and engagement in proactive career strategies, in turn, should be associated with important career outcomes and perception of success (Gould & Penley, 1984; Hall & Chandler, 2005). These proposed relationships are consistent with Johnson et al.’s (2014) framework, which places promotive behaviors as mechanisms in the future orientation – successful development relationship. It further resonates with goal setting and self-regulation propositions that proactive career strategies directed toward cognized goals (e.g., increasing effort, creating opportunities, networking, accumulating work experience) act as driving motivational processes in goal pursuit, leading to successful career outcomes, including career adaptability and perceived employability (Bandura, 2001; Brown et al., 2006; Gould & Penley, 1984; Locke & Latham, 1990; Saks & Ashforth, 1999).

Research supports these claims. We already established the relationship between future orientation and career agency. Further, career agency showed positive association with career success, specifically, positive perceptions about employability in young, middle-career and older working adults (Praskova et al., 2015; van der Heijden, 2002), gaining employment (Strauss et al., 2012) and career adaptability (Praskova et al., 2014; Taber & Blankemeyer, 2015). While no known study investigated the indirect effects of future orientation on career success via career agency, work effort and career behaviors were found to be significant mediators between another value-driven construct, career calling, and career success in young adults (Praskova et al., 2014, 2015). From this, we hypothesized that
H3. career agency (work effort and proactive career behaviors) would be positively associated with career success (perceived employability and career adaptability), and, that

H4. career agency would mediate the future orientation–career success relationship. Specifically, future orientation would be associated positively with work effort and proactive career behaviors, which, in turn, would be associated positively with career adaptability and perceived employability.

Role of Negative Career Feedback

The future orientation framework (Johnson et al., 2014), social cognitive theory (Bandura, 2001), and goal setting theory (Locke & Latham, 1990) all propose that people are able to assert some control and agency to navigate their environment but also operate within the context of social and environmental influences. For example, Lent and Brown (2013) argued that people were more likely to engage in proactive career behaviors when their environment buoyed them, and Chen et al. (2020) noted that effectively balancing the interaction between self-driven behaviors and people’s living environment helped them develop career adaptability. Consistent with the employability process model, Vanhercke et al. (2014) also proposed that context (e.g., support for career development) interacted with personal factors (e.g., optimism) in predicting perceived employability. Thus, while people actively create their own life script, their decisions, actions, and, ultimately, their successful goal attainments are shaped by external world and environmental factors such as receiving feedback (Bandura, 2001). To date, no research embedded in the future orientation framework (Johnson et al., 2014) has assessed this person-environment interplay to achieving career success.

Feedback from a significant other (e.g., supervisor, family) in relation to one’s career and career progress has been recognized to be especially powerful influencing factor in people’s career decision-making, motivation, and career enactment (Lent & Brown, 2013), and an important moderator that has a conditional effect on goal attainment (Locke & Latham, 1990). Feedback can work to provide a person with positive reactions from important others, encouragement, and even inspiration, thus, stimulating one’s motivation to engage in career behaviors and, subsequently, achieving career success (Schuesslbauer et al., 2018). On the other hand, negative career feedback can act as a constraint to career effort and progress, and, thus, lower career success (Johnson et al., 2014).

In our study, we specifically focused on the role of negative career feedback in people’s career enactment, as receiving excessive negative feedback is more detrimental to people’s wellbeing, motivation and effort to engage in goal-related activities, and, subsequently, performance (Ilgen & Davis, 2001) than any other form of feedback. Research shows that negative feedback is associated with whole range of negative outcomes, including slower goal progress, lower career expectations, and greater career distress (Creed et al., 2015; Hu et al., 2017), as well as greater disbelief in own ability to achieve future goals, less adaptive behaviors, and withdrawal from work performance (Choi et al., 2018). Based on the review, we included negative career feedback as a moderator in our mediation model. We expected that the indirect effect of future orientation on career success via career agency would be conditional upon the level of negative career feedback received.
H5. Specifically, we expected that the indirect effect would be the strongest for people who received low level of negative career feedback, and the weakest for people with high negative career feedback.

Present Study

We embedded our study variables in the future orientation framework (Johnson et al., 2014), and adapted it to assessing future oriented processes in a career domain. In a moderated, multiple mediation model, we assessed the direct and indirect effects of future orientation on career success via career agency, and tested the conditionality of these relationships based on the level of negative career feedback one receives. To our best knowledge, no study has tested this integrative model of future orientation, although it is well suited to explain how people manage their career lives and become successful. Thus, our study was set to contribute to limited theory-driven research on future orientation that relates this construct to agency and success in a career domain. Our study also answered the call for more research into future orientation by providing all-inclusive picture of the mechanisms through which future orientation impacts outcomes, while also accounting for environmental factors that can influence the trajectory (Johnson et al., 2014; Nurmi, 1991). Lastly, our focus in this study was on adult population rather than adolescents or young adults seen in previous studies, since career development and management is a dynamic, life-long process that is relevant to people of all ages (Dietrich et al., 2012).

Method

Participants

Participants were 285 Australian adults between 18 and 83 years of age (M = 38.38 years, SD = 13.24, range = 65), with 205 (72%) being females. The majority (n = 267; 93.7%) were enrolled in a university degree at the time of data collection across a wide range of preparatory, undergraduate and postgraduate disciplines. Most of the participants were working and studying (n = 194, 68.1%), followed by those who only studied (n = 71, 24.9%), only worked (n = 14, 4.9%), or neither worked nor studied (n = 6, 2.1%). The majority of participants indicated their financial situation to be better off when compared to others (n = 119, 41.8%), with fewer reporting being about the same as others (n = 87, 30.5%), or a little or much worse off than others (n = 79, 27.7%).

Measures

For all measures, we reverse-scored all negative items and then summed the individual item scores to create scale composites. Thus, higher scores reflected higher level of that construct.

Future orientation

The 13-item future orientation subscale of the 56-item Zimbardo and Boyd (1999) Time Perspective Inventory was used to assess general future orientation. Consistent with the Johnson et al.’s (2014) framework that defines future-oriented considerations, planning, and setting/achieving goals as the key aspects of future orientation, items reflected the extent that people strive for, plan for, and achieve future goals shown through motivational, cognitive, and behavioral manifestations. Sample questions included “I keep working on difficult, uninteresting tasks if they will help me get ahead,” “Before making a decision, I weigh the cost against the benefit,” and “I complete projects on time by making steady progress.” Participants responded on a 5-point Likert-type scale (1 = very uncharacteristic, 5 = very characteristic). Zimbardo and Boyd (1999) reported adequate Cronbach’s α of .77 for the future orientation subscale and test-retest reliability of .80 with a sample of students. They demonstrated convergent validity by finding positive and strong (r > .67) correlations with existing conceptually related measures—consideration of future consequences and conscientiousness, and concurrent validity by finding positive correlations with preference for consistency and hours spent studying per week. Internal consistency coefficient for our sample was .76.

Career agency

Proactive career behaviors

The 26-item Career Strategies Inventory (Gould & Penley, 1984) was used to assess the use of seven strategies to develop one’s career, including work involvement, creating career opportunities, networking, and self-presentation. Several items were modified to suit our sample of adults, most of whom were also university students. Participants responded to a stem: “In respect to my career development, I am…” followed by a sample item “…developing expertise in areas that are critical to my career field” (modified from “developing expertise in areas that are critical to your department’s operations”), using a 6-point Likert scale (1 = strongly disagree, 6 = strongly agree). The modified versions of the scale showed a single factor and an excellent internal reliability coefficient of .91 to .93 for the total scale in samples of young adults (Perkins, 2012; Praskova et al., 2014) and demonstrated concurrent validity by finding positive correlations with career adaptability and career calling (Praskova et al., 2014). We also found a single factor and the internal consistency coefficient for our sample was .92.

Work effort

The 10-item Work Effort Scale (De Cooman et al., 2009) was used to assess three aspects of direction, intensity, and persistence. Three items were modified to suit our sample of adults (e.g., the item, “I really do my best to achieve the objectives of the organization,” was amended to, “I really do my best to achieve the objectives I set for myself”). Participants responded using a 7-point Likert-type scale (1 = fully disagree, 7 = fully agree). De Cooman et al. (2009) reported an excellent internal reliability of .90 and test-retest correlation of .72 in a sample of working adults. Scale validity for the total scale was demonstrated by finding positive correlations with performance, job satisfaction, and social desirability. Internal consistency coefficient for our sample was .90.

Career success

Self-perceived employability

The 16-item Self-Perceived Employability Scale (Rothwell & Arnold, 2007) was used to assess people’s perceptions of their value within the labor market. Items that reflected internal and external employability were modified to suit the sample of adults already working and students who were preparing for entry to graduate employment (e.g., “I could easily retrain to make myself more employable elsewhere” was amended to “I could easily retrain to make myself more employable”). Participants responded using a 7-point Likert scale (1 = strongly disagree, 7 = strongly agree). Authors reported a good Cronbach’s α of .83 for the total scale in a sample of working adults and demonstrated concurrent validity by expected positive associations with career success and professional commitment. The modified scale has been used with emerging adults and was found to be reliable (α = .91) and showing expected correlations with life satisfaction and career calling (Praskova et al., 2015). We found a single factor solution and the internal consistency coefficient for our sample was .91.

Career adaptability

The 24-item Career Adapt-Abilities Inventory - International version (Savickas & Porfeli, 2012) was used to assess career adaptability across four domains: concern, control, curiosity, and confidence. Participants responded how strongly they have developed abilities, such as “becoming curious about new opportunities” and “overcoming obstacles” on a 5-point Likert-type scale (1 = not strong, 5 = strongest). Authors reported an excellent Cronbach’s α of .92 for the total scale in a sample of university students with all items loading above .48 on the single, first-order factor. Construct validity was demonstrated by positive association with indices of career identity, such as career exploration and commitment identification in young students (Porfeli & Savickas, 2012). We found a single factor worked better than a four-factor solution, and the internal consistency coefficient for our sample was .94.

Negative career feedback

We used 12 items from the 24-item Career Goal Feedback Scale for adults (Hu et al., 2016) that assessed negative career feedback on progress, suitability, and improvements needed from external sources, with a sample question, “I am told that I am not making progress toward my career goals.” Participants responded on a 6-point Likert scale (1 = strongly disagree, 6 = strongly agree). Hu et al. (2016) demonstrated an excellent Cronbach’s α of .90 for the total scale in university students and scale validity by finding positive correlations with an existing career feedback scale and career-related stress, and negative correlation with career self-efficacy. Internal consistency coefficient for our sample was .91.

Procedure

We obtained ethical clearance from the corresponding University’s Human Research Ethics Committee (ECN-19-103) prior to commencement of this study. Through non-probability, convenience and snowball sampling strategy, we invited participants 18+ years of age to complete an anonymous online survey in Qualtrics (mobile friendly). Due to the nature of the online recruitment strategies, precise response rate could not be calculated. We sent a moderated bulk email with embedded study link to all university students and staff, and advertised the study via the second author’s social media platform. Participants were first asked to read the conditions of the study (e.g., voluntary participation allowing for withdrawal at any time without consequences) and their proceeding to the survey was taken as their consent to participate. There were no incentives for participation, although answering questions about career actions and attitudes could have encouraged self-reflection and development of positive career mindset. The survey took approximately 10 minutes to complete.

Results

Missing Data and Assumptions

We downloaded data from 342 participants to the IBM-SPSS 25. Missing value analysis revealed 16.35% of missing values with progressive dropout. While a power analysis (GPower; Faul et al., 2007) for multiple regression showed that we had 95% power to detect a medium size effect in a sample size of 129, Jackson (2001) suggests 200–400 participants for structural equation modeling. We removed 54 participants with gross missingness, leaving 288 participants with a small proportion of values (3.8%) missing completely at random (Little’s MCAR test), χ²(114) = 129.92, p = .146. We used multiple imputation tool to replace these, as it produces the least biased parameter estimates.

Exploring the data identified three influential scores with standardized residuals exceeding three standard deviations and Mahalanobis distance value exceeding the critical χ² value for p < .001. These were deleted from further analyses (N = 285). Checking age at univariate level revealed positively skewed data (z = 2.99, p > .05) with one potential outlier (an 83 year old research student). The topic of study was relevant to this participant, and he represented our sample, as 22 participants (8%) reported being ≥60 years of age. The above analyses also did not find this participant influential. Checking bivariate correlations and histograms, normal probability plots and scatter plots of residuals showed that assumptions of multiple regression analysis were met.

Data Preparation and Planned Analyses

To avoid violating the recommended ratio (5:1 to 10:1) between number of participants and number of parameters in a latent variable analysis (Bentler & Chou, 1987), and to achieve more balanced measures of the constructs that produce stable parameter estimates, we created parcels that represented the latent variables for all scales (Landis et al., 2000). After conducting exploratory factor analysis on each scale and finding all reflected a first-order scale, we sorted items by their factor loading size and allocated items to the parcels using the item-to-construct balance approach (Landis et al., 2000). We created three parcels to represent the shorter scales, four parcels to represent the 24-item career adaptability scale, and five parcels to represent the longest, 26-item career strategies scale. This approach is adequate when identifying underlying structure of items is not the primary goal of the study (Matsunaga, 2008).

We then used latent variable analysis (structural equation modeling with a maximum likelihood estimation in AMOS 25) to assess a multiple mediation model where future orientation was the predictor, career adaptability and perceived employability were the outcomes, and work effort and career behaviors were the mediators. We first assessed the measurement model to confirm the parcels reflected their latent variables, and then assessed the hypothesized, structural model using Hair et al.’s (2010) recommendations for sample of ≥250 participants and >12 observed variables. Indicators of a good fit included χ² (significant p value expected), normed χ² (χ² /df < 3.0), the comparative fit index (CFI > .92), the Tucker-Lewis index (TLI > .92), the root mean square error of approximation (RMSEA < .07), and the standardized root mean square residual (SRMR ≤ .08). We identified the most parsimonious structural model using the Akaike Information Criterion (AIC with smallest value; Byrne, 2010). To assess the moderation effect of negative career feedback in the mediation model, we conducted conditional processes analysis using ordinary least squares regression in PROCESS v3 for SPSS (Hayes, 2018).

Testing Measurement and Structural Models

The initial assessment of the measurement model with the five latent variables (without the moderator) showed good fit on some indices, χ² (125) = 333.43, p < .001, χ² /df* = 2.67, CFI = .95, TLI = .94, GFI = .88, RMSEA = .08, and SRMR = .05. Modification indices identified covariance between two sets of error terms. We allowed these to covariate as they represented parcels of the same latent variable (Cole & Maxwell, 2003). This measurement model showed superior fit, χ² (123) = 258.12, p < .001, χ² /df = 2.10, CFI = .97, TLI = .96, GFI = .91, RMSEA = .06, and SRMR = .04, and no problematic cross-loadings. Factor loadings were all significant (p < .001; range = .70–.95), and all squared multiple correlations (item reliabilities) were > .50 (r = .51–.85), supporting construct validity and reliability of the scales. All correlations among the latent variables were significant at p < .05 (r = .15–.69) and consistent with observed variable correlations (see Table 1). This confirmed that the defined latent variables would accurately represent the relationships among the variables in subsequent latent variable

Table 1.
Summary Data, Factor Loadings, Bivariate Correlations (Above Diagonal), and Latent Variable Correlations (Below Diagonal).

Variable M SD Range Factor loadings ^a 1 2 3 4 5 6 7 8 9 10

1. Future orientation 49.42 6.49 29–65 .70–.75 — .23 .42 .13* .27 −.23 .19 .03 .27 −.11

2. Career strategies 101.74 18.32 36–148 .81–.89 .30* — .28 .55 .39 −.08 −.08 .02 .01 .04

3. Work effort 60.17 7.04 37-70 .87–.91 .48* .33* — .27 .61 −.35 .23 .08 .20** −.05

4. Perceived employability 80.72 14.37 32–112 .87–.92 .15* .57* .29* — .38 −.25 −.06 .01 −.02 −.16

5. Career adaptability 89.24 15.51 49–−120 .82–.95 .32* .40* .69* .38* — −.29 .06 .00 .04 −.01

6. Career feedback 29.60 12.45 12-72 — — — — — — — −.17** −.08 −.13* .06

7. Age 38.38 13.24 18–83 — — — — — — — — −.09 .36** −.06

8. Gender — — — — — — — — — — — — −.08 .10

9. Education — — — — — — — — — — — — — −.10

10. Financial situation — — — — — — — — — — — — — —

Note. N = 285; ^a range of factor loadings (standardized regression coefficients) for observed variables representing latent variables in measurement model. p < .05; p < .01; p < .001.

The hypothesized (structural) model seen in Figure 1 showed a good fit, χ² (127) = 276.14, p < .001, χ² /df = 2.17, CFI = .96, TLI = .96, GFI = .91, RMSEA = .06, and SRMR = .08. There were significant, positive paths (p < .001) from future orientation to career behaviors and work effort, indicating that higher levels of future orientation were associated with more work effort and greater use of career behaviors (H2). There were also significant, positive paths (p < . 01) from career behaviors and work effort to perceived employability and career adaptability, indicating that greater work effort and the use of career behaviors were associated with greater career adaptability and more positive perceptions of employability (H3). Figure 1 includes the standardized coefficient.

Figure 1.
Structural multiple mediation model.

Testing for Mediation

From the above results, work effort and career strategies potentially mediated the relationship between future orientation and perceived employability/career adaptability, as we satisfied criteria for mediation (Hayes, 2018). The predictor was associated with the mediator (path a) and the mediator (after controlling for the predictor) was associated with the outcome variable (path b). We also found significant total effects (path c) with positive paths from future orientation to perceived employability (p = .01) and career adaptability (p < .001); stronger sense of future orientation was associated with greater career adaptability and perceived employability (H1). We then added these paths to the hypothesized model to assess (a) the direct effects of future orientation on the outcome variables in the presence of the mediators (path c′), and (b) the indirect effects between future orientation and the outcomes via the mediators (path ab). We requested bootstrapping, which generates standard errors and 95% bias-corrected confidence intervals (CIs; 10,000 bootstrapping samples; Preacher & Hayes, 2008). A bootstrapped CI of the indirect effect that does not contain zero indicates mediation.

Results showed that bootstrapped CIs for the indirect effects of future orientation on career adaptability (95% CI [.29, .54]) and future orientation on perceived employability (95% CI [.16, .42]) did not contain zero, indicating that future orientation – outcome relationships were mediated by the combined effect of work effort and career behaviors. Notably, the direct effects from future orientation to career adaptability (β = −.08, p = .26) and perceived employability (β = −.08, p = .17) became non-significant in the presence of the mediators. This full model had a good fit, χ² (131) = 273.06, p < .001, χ² /df = 2.84, CFI = .96, TLI = .96, GFI = .91, RMSEA = .07, and SRMR = .07, and was only marginally poorer (AIC = 365.06) than the hypothesized model (AIC = 364.14). We added the total and direct effects to Figure 1. Last, we assessed the significance of the mediation paths for each mediator. All possible mediation paths were significant (H4), as the bootstrapped CIs did not contain zero. The indirect effect of future orientation on perceived employability was mediated by career behaviors (95% CI [.21, .81]) and work effort (95% CI [.08, .25]). The effect of future orientation on career adaptability was mediated by career behaviors (95% CI [.09, .33]) and work effort (95% CI [.23, .45]).

Testing for Moderation of the Indirect Effects

To assess the moderating effect of negative career feedback, we run conditional process analyses for each outcome variable in PROCESS for SPSS (Hayes, 2018). Mediation is moderated when the moderator (W) has a non-zero weight in the function linking the effect of the predictor (X) on the outcome (Y) via the mediator/s (M). This weight (i.e., index of moderated mediation) is the product of regression coefficients taken from the full integrated model (Hayes, 2018). The test uses percentile bootstrap CIs (5,000 bootstrap samples) as a formal test of statistical inference (i.e., non-zero 95% CI), and the size and the sign of the index are used to guide interpretation of the moderated mediation (Hayes, 2018). We specified Model 7 (i.e., moderation of X → M effect by W), mean centered the products of the interaction terms, generated heteroscedasticity-consistent standard errors (HC3), conditioned effects at the 16th(low), 50th(moderate) and 84th(high) percentile values of the moderator, and reported unstandardized coefficients as recommended (Hayes, 2018).

We first checked for potential covariates by assessing correlations between the study variables and a number of personal and contextual/socio-economic factors noted in the literature as having the potential to affect career outcomes (Chen et al., 2020; Vanhercke et al., 2014). Age, gender, and education showed trivial associations with the two outcome variables and, thus, were not included in the model as covariates. Financial situation had a significant, negative correlation with perceived employability (p < .01; see Table 1), so the relevant analysis included this variable as a covariate.

The results showed that the bootstrapped indirect effect of future orientation on perceived employability (95% CI [−.025, −.003]) and career adaptability (95% CI [−.013, −.001]) through career strategies was negatively moderated by negative career feedback (H5). We can be 95% confident that the effect of future orientation on perceived employability (index = −.001; SE_boot = .002) and career adaptability (index = −.007; SE_boot = .003) via enhanced use of career behaviors increased with decreased level of negative career feedback (i.e., negative indices of moderated mediation and non-zero CIs). Probing the conditional indirect effects with simple slopes analyses supported these claims and showed that the positive effect of future orientation on perceived employability and career adaptability via career strategies were only significant for those who received moderate and low negative feedback about career progress, goal suitability, and the need for improvement (see Table 2).

Table 2.
Probing the Conditional Effects of Negative Feedback via Career Strategies (N = 285).

Future orientation ´ career feedback at value of moderator Outcome variables

Perceived employability Career adaptability

Indirect effect Boot SE Boot LLCI BootULCI Indirect effect Boot SE Boot LLCI Boot ULCI

16th percentile (W = −12.60) .42 .12 .20 .67* .21 .06 .09 .34*

50th percentile (W = −1.60) .27 .09 .11 .44* .14 .04 .06 .23*

84th percentile (W = 12.40) .09 .10 −.11 .28 .04 .05 −.06 .14

Note. * significant conditional indirect effects for the value of the moderator. Bootstrap CIs generated from 5,000 bootstrap samples. Unstandardized coefficients are reported.

Our analyses did not find indirect conditional effects through the second mediator, work effort. Negative career feedback was negatively associated with work effort, F(1,281) = 27.54, p < .001), but there was no interaction between future orientation and negative career feedback when predicting work effort, F(1,281) = 0.46, p = .50. The indices of moderated mediation when predicting perceived employability (95% CI [−.004, .002]) and career adaptability (95% CI [−.015, .008]) were also non-significant. Thus, unexpectedly, the indirect effect of future orientation on the outcome variables via work effort was not conditional upon the level of negative career feedback (H5).

Discussion

The study aim was to test an integrative model of future orientation (Johnson et al., 2014) with adults. Managing and progressing a career became increasingly more challenging at times of frequent changes and career transitions, requiring foresight of what is likely to happen in the future (Seginer, 2008). Thus, the ability to think about the future, be able to adapt to changes, be motivated to implement strategies and divert effort toward the desired goal, while also expecting positive career outcomes, are all relevant attributes for young people in training just as they are for adults in established careers. After all, career development and management is a life-long process (Dietrich et al., 2012). Thus, we contribute to the future orientation literature to date, which mainly focusses on adolescent career development and wellbeing (Johnson et al., 2014; Nurmi, 1991; Seginer, 2008), by testing the complex interplay between personal, contextual, motivational, behavioral, and career success factors in adults of varied ages. We extend the application of this model, while also answer the call for more complex, integrative future orientation research (Johnson et al., 2014; Nurmi, 1991).

Overall, findings largely support the hypothesized relations in our multivariate conditional process model. Confirming Hypothesis 1, we found that future orientation was related to career success. People who focused on the future more by aspiring and planning for their expected future life exhibited greater career adaptability and perceived employability. These findings are consistent with previous research that found that adolescents and young adults with more developed future orientation (including hope and a sense of control) reported more positive perceptions and confidence about their employability (Kasler et al., 2017), and more career adaptability (Duffy, 2010). Similar relationships were also found in working adults (Shipp et al., 2009; Zacher, 2014). Together, career adaptability and perceived employability were confirmed to be the key career success outcomes of future orientation (Rothwell & Arnold, 2007; Savickas & Porfeli, 2012) in adults.

Secondly, we confirmed Hypothesis 2 with finding that future orientation was related to career agency. Specifically, people with stronger future orientation reported greater use of proactive career behaviors aimed at development and management of their careers, such as networking, self-promoting, and exploring career opportunities, and reported putting more effort (attention, intensity, and persistence) toward their work. These findings are consistent with previous research, which found similar relationships between future orientation and drive to accomplish set career aspirations and engagement in proactive career behaviors (Parker & Collins, 2009; Strauss et al., 2012). The findings also resonate with social cognitive (Bandura, 2001) and goal setting (Locke & Latham, 1991) theory, showing that people are able to draw on their own attributes to mobilize agency, such as set, pursue, and manage important career goals. We further contribute to the future orientation literature by testing a theoretically-driven model, and confirming that the future focus is an important personal attribute for motivation, self-definition and self-regulation, stimulating active engagement in cognitive, motivational, and behavioral processes aimed at reaching desired outcomes (Johnson et al., 2014; Seginer, 2008).

Our Hypothesis 3 was supported by positive relationship found between career agency and career success. People who used more proactive career behaviors and exerted more work effort reported being more adaptable to changing and/or challenging work situations and having more positive perceptions about their employability. The findings resonate with previous research findings that young adults who engaged in proactive career strategies showed more successful career outcomes in terms of perceived and actual employability and career adaptability (Praskova et al., 2014, 2015; Strauss et al., 2012; Taber & Blankemeyer, 2015; van der Heijden, 2002). We expand this literature by finding these relationships with adults. This indicates that career outcomes and the efforts put into achieve these reflect processes that are relevant to all - young, middle-aged, and older adults.

We also assessed complex relationships between the study variables, supporting Hypothesis 4. We found that future orientation influenced career success indirectly through career agency, finding that all possible mediating paths were statistically significant. People with more future-oriented focus engaged in more behavioral and motivational processes (proactive career behaviors and work effort), and, in turn, showed greater career adaptability and perceived employability. This is consistent with previous related research, where, in young adults, behavioral, motivational, and emotional self-regulation processes were identified as important mediators that related purpose-driven and meaningful goals (i.e., career calling) with employability perceptions (Praskova et al., 2015) and career adaptability (Praskova et al., 2014). It is also consistent with theories that argue that goal-directed processes are employed to diminish goal discrepancies, and act as driving forces in the goal–outcome relationships (Locke & Latham, 1990). Being the first study using adult sample to test this theoretical framework in a career domain (Johnson et al., 2014), we provided evidence that confirms the important role of future orientation in stimulating people’s motivation and enactment of their careers, that, ultimately contributes to overall career success.

Finally, we tested whether these positive mediation processes depended on one environmental factor - negative career feedback. Our Hypothesis 5 was partially supported. We found that when people received low or medium level of negative career feedback, the stronger sense of future orientation was associated with more proactive career behaviors which, in turn, stimulated more positive perceptions of employability and career adaptability. On the other hand, for people who received high level of negative career feedback, the indirect effect became non-significant. This indicates that being subject to lower levels of negative career feedback was beneficial to the agentic enactment of proactive career behaviors, and, in turn, achieving career success, as it strengthened these processes or, at least, did not affect these processes negatively. Conversely, high exposure to negative feedback about people’s career cancelled out the positive impact future orientation had on active engagement in a career, which indicates a “suppression” effect. Not surprisingly, negative career feedback showed negative bivariate correlations with all key study variables (Table 1). The results are consistent with previous theoretically related research that found that people who received more negative feedback had less confidence about their ability to achieve goals, showed slower progress toward their goals, had lower career expectations, and used less adaptive behaviors (Choi et al., 2018; Creed et al., 2015; Hu et al., 2017).

Ultimately, negative career feedback (when received too much of it) acted as a micro-level environmental constraint in the future orientation model (Johnson et al., 2014), being consistent with claims that too much of negative feedback is likely to be harmful to people’s motivation to engage in goal-related activities (Ilgen & Davis, 2001). We assessed negative career feedback as a moderator in the first stage of our conditional process model (between future orientation and career agency) to be consistent with well-regarded social cognitive, goal setting, and career success perspectives (Bandura, 2001; Hall & Chandler, 2005; Locke & Latham, 1990). Overall, our results confirmed that people were active agents in their environment, that they drew on their strengths to facilitate this agency, but also were influenced and their actions were shaped by the world around them (Bandura, 2001; Johnson et al., 2014; Locke & Latham, 1990). Importantly, our contribution to future orientation literature is in providing greater understanding of the complex and multistage processes in which future orientation exerts its impact on important career-related processes and outcomes in a model that includes both person-related and environmental factors (Johnson et al., 2014; Nurmi, 1991).

Unexpectedly, our study did not confirm a conditional effect of negative career feedback in the mediating paths via work effort. Our measure of work effort might have been too general, and assessing career feedback in relation to effort toward specific career goal or a career task might have been more suitable and powerful to detect conditional effect in already identified strong indirect effects. In support, conditional effects are generally hard to detect in moderated models (Helm & Mark, 2012), let alone in complex, moderated mediation models. Thus, while in our study the significant conditional indirect effects via career behaviors were small, these reflect what is typically found in research (median f² = 0.002; Aguinis et al., 2005). Overall, the theory-driven hypotheses we made and the bootstrapping method we used to make inferences strengthened our results.

Study Limitations and Future Directions

In the light of the study contributions, there were limitations worth noting. Firstly, our study was cross-sectional. Thus, although our hypothesized relationships were theory-driven and the analytical approach (i.e., conditional process modeling) suggests causality (Hayes, 2018), a longitudinal study using a cross-lagged design would provide greater confidence in making causal and directional inferences. Our findings should provide more assurance to such future research. Secondly, the majority of participants were females and university students. While gender did not correlate significantly with any of the study variables, education level correlated positively with future orientation and work effort (Table 1). It is plausible that adults who currently study have higher future orientation in general, which would motivate them to enroll in the university and study as a pathway to future career enhancement and success. Thus, our findings should serve as a stepping-stone to confirming these career-relevant processes in more representative adult samples.

Future orientation, and, subsequently, goal-directed motivation and outcomes, can be affected by life experiences (e.g., family environment and beliefs about temporal focus, previous successes in obtaining goals), personal attributes (e.g., core self-evaluations, self-efficacy, and attributional style), and a range of socio-environmental factors (Johnson et al., 2014; Seginer, 2008; Shipp et al., 2009). These factors include “opportunities” (e.g., encouragement by one’s national culture or a community to attend university as the means of furthering a career opportunity, access to financial aids, and organizational culture supportive of future-oriented thinking) and “constraints” (e.g., economic downturn and lack of financial resources can act as barriers to motivation to pursue a career goal; Johnson et al., 2014). Our study contributed to this future orientation literature by providing a first step in untangling these complex processes. It would be pertinent to continue this research journey by assessing this model from different cultural viewpoints (our study was embedded in the Western cultural system that values personal development and future oriented attitudes), and testing other theory-driven self-regulatory mechanisms and personal and socio-environmental factors in the future orientation model to investigate the integrative role of these variables in developing future orientation as well as facilitating or constraining career-directed actions and, subsequently, career success. Particularly, the concept of a career shock would seem important to include in such a model, to provide insight on how disruptive and extraordinary events, such as the COVID-19 pandemic (Akkermans et al., 2020), affected (positively and negatively) people’s career and future related perceptions, motivations, actions, and, subsequently, success outcomes, either directly or in combination with personal attributes. Such research would provide further support for the proposed future orientation framework (Johnson et al., 2014) in a career domain.

Last, consistent with literature that suggests that career development and management is a life-long process (Dietrich et al., 2012) age was not associated with the self-perceived career success outcomes in our study. However, the age range of our sample was large and the purpose behind the engagement in the future orientation processes might have differed based on whether an individual was a young, middle-aged, or aging adult. Notably, in the study on employability, the aging population has been found to be subjected to age-related stereotyping, with employers assessing capabilities (and, consequently, employability) of those over 50’s lower than of those of younger people (van der Heijden, 2002). Interestingly, senior workers attributed less importance to their age than their employers did. Results further indicated that “starters” considered social recognition and developing professional and task-related skills as the key elements to enhancing their employability, while older workers perceived their employability would grow with opportunities to expand their expertise in adjacent/different fields. This literature highlights that while careers matter at any stage in adult life, the future-oriented career focus and motivation might differ according to whether an individual is preparing for their future career, setting up and maintaining their career, or is in a transition to another career or a meaningful role. Future studies could explore this in more detail.

Practical Implications and Conclusion

Our study has practical importance for people who are currently in their career and those who are transitioning to or between careers. Our findings provide support for the underlying mechanism in which future orientation facilitates motivation, career enactment, and career success. This should encourage practitioners and educators to develop targeted interventions and educational programs that focus on building healthy future orientation that takes into account the individual’s stage in their career life and their life roles (Lent & Brown, 2013). Such programs should aim to develop all aspects of future orientation as related to career development, including thinking about future career hopes, evaluating the likelihood of potential outcomes, setting intentions and career goals for the future as well as building the ability to plan and enact a course of actions to reach those set career outcomes (Johnson et al., 2014). In addition, as these motivational and goal-directed processes are influenced by feedback from the environment, just as our study confirmed, interventions to foster career agency and success should include aspects that focus on managing career feedback, and especially the negative one.

Future orientation might also be important for organizations that wish to optimize employees’ attitudes and motivation to achieve improved outcomes for their organization. Hiring future-oriented people and/or modeling future orientation in their employees is likely to lead to more progressive strategic planning and greater engagement from the employees to actively participate in future-oriented transformation of the organization to move it to envisioned position in the future (Shipp et al., 2009). In return, future-oriented employees might have positive hopes and expectancies about future rewards, opportunities, and other self-perceived career success outcomes. Thus, tailored conversations with employees that aim at adopting future-oriented “language” (Zimbardo & Boyd, 1999, p. 1285), future-oriented mindset, and future-oriented outcomes might help gain employees’ support and enhance their motivation and commitment to organizational objectives and actions.

Orientation to future is a fundamental multidimensional psychological construct that “gives people wings to soar to new heights of achievement” (Zimbardo & Boyd, 1999, p. 1285). Concluding with this powerful quote coupled with our strong evidence, we believe that the inquiry into deeper understanding of the complex processes surrounding future orientation should continue. Our study provides a theory-driven support that future orientation has positive influence on human agency and two career success outcomes of adaptability and employability, which are critical for people’s optimal existence within the context of fast going, dynamic, and future-oriented world.

Variable	M	SD	Range	Factor loadings ^a	1	2	3	4	5	6	7	8	9	10
1. Future orientation	49.42	6.49	29–65	.70–.75	—	.23**	.42**	.13*	.27**	−.23**	.19**	.03	.27**	−.11
2. Career strategies	101.74	18.32	36–148	.81–.89	.30***	—	.28**	.55**	.39**	−.08	−.08	.02	.01	.04
3. Work effort	60.17	7.04	37-70	.87–.91	.48***	.33***	—	.27**	.61**	−.35**	.23**	.08	.20**	−.05
4. Perceived employability	80.72	14.37	32–112	.87–.92	.15*	.57***	.29***	—	.38**	−.25**	−.06	.01	−.02	−.16**
5. Career adaptability	89.24	15.51	49–−120	.82–.95	.32***	.40***	.69***	.38***	—	−.29**	.06	.00	.04	−.01
6. Career feedback	29.60	12.45	12-72	—	—	—	—	—	—	—	−.17**	−.08	−.13*	.06
7. Age	38.38	13.24	18–83	—	—	—	—	—	—	—	—	−.09	.36**	−.06
8. Gender	—	—	—	—	—	—	—	—	—	—	—	—	−.08	.10
9. Education	—	—	—	—	—	—	—	—	—	—	—	—	—	−.10
10. Financial situation	—	—	—	—	—	—	—	—	—	—	—	—	—	—

Future orientation ´ career feedback at value of moderator	Outcome variables
16th percentile (W = −12.60)	.42	.12	.20	.67*	.21	.06	.09	.34*
50th percentile (W = −1.60)	.27	.09	.11	.44*	.14	.04	.06	.23*
84th percentile (W = 12.40)	.09	.10	−.11	.28	.04	.05	−.06	.14

Footnotes

Authors’ Note

Lena Johnston is now at Change Futures, Brisbane, Queensland, Australia. Email: lena.johnston@hotmail.com

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.

ORCID iD

Anna Praskova

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Future orientation ´ career feedback at value of moderator	Outcome variables
	Perceived employability				Career adaptability
	Indirect effect	Boot SE	Boot LLCI	BootULCI	Indirect effect	Boot SE	Boot LLCI	Boot ULCI
16th percentile (W = −12.60)	.42	.12	.20	.67*	.21	.06	.09	.34*
50th percentile (W = −1.60)	.27	.09	.11	.44*	.14	.04	.06	.23*
84th percentile (W = 12.40)	.09	.10	−.11	.28	.04	.05	−.06	.14