Chopping and Changing: Demographic, Bright and Dark Side Trait Correlates of Job Changes


The aim of this study was to explore personality correlates of those who frequently change, as opposed to remain for longer periods, in their jobs. Over 6000 adult managers (Mean Age 43.83 years) attending an assessment centre completed a battery of tests including a normal, “bright side” personality trait measure (NEO-PI-R); a “dark side”, sub-clinical personality disorders measure (HDS). They also recorded how many jobs they had held over their life-time (Mean 7.01). Correlational analyses showed those who had more jobs were strongly associated with age as well as low Neuroticism, high Extraversion, and Conscientiousness, as well as being Cautious, Dutiful, Mischievous and Imaginative. Regressions showed the higher-order, “dark side” factor “Moving Against Others” was associated with more job changes. There appears to be no other studies in this area either by differential and social psychologists or sociologists. Limitations of this essentially pilot study are noted.

Share and Cite:

Furnham, A. (2020) Chopping and Changing: Demographic, Bright and Dark Side Trait Correlates of Job Changes. Psychology, 11, 204-216. doi: 10.4236/psych.2020.111014.

1. Introduction

This study looks primarily at those personality traits that relate to people changing jobs. People change jobs both within and between organisations for many reasons: they are promoted, sacked, and leave voluntarily. Their personality circumstances might change, encouraging moving geographically. Sometimes the organisation fails requiring that staff have to find another job. Some people seem job dissatisfied, unfulfilled and unhappy and change frequently to try to find a better job fit which is aim of much vocational guidance ( Furnham, 2005) while others seen as “high flyers” may be promoted frequently so accumulating wide experience ( Teodorescu, Furnham, & Macrae, 2017). Sometimes job holders are primarily responsible for the move (as in resignation) while on other occasions these decisions are primarily made by others such as a boss making a promotion decision. Inevitably a person can refuse a job change and ask for a move whether is it is vertical or horizontal, suggesting a fairly strong voluntary aspect to job moves.

Some organisations have a policy of moving people around and up the organisation to give them a fuller understanding of the culture and processes involved, while others allow both specialists and generalists to stay in similar jobs for long periods of time ( Furnham & Palaiou, 2017). Whatever the reason for the job change it is possible that a wide variety of experiences gives a person a broader perspective on work and leadership and thus makes them more likely to be able to take on more senior roles. Thus, it may be hypothesized that more able people are offered a wider variety of job roles to test their potential or that they choose to broaden their skills through experience. Similarly, it may be hypothesised that people with a particular personality profile choose to, or not to change jobs frequently, to increase their sense of well being and/or occupational success ( Furnham, 2018).

This study focuses on individual differences in job changes, an area much neglected in the literature. There are a very limited number of theories in this area. It is self-evident that there are individual differences in job attraction and choice ( Bipp & Demerouti, 2014). This is the central concern of vocational psychology, though is mainly concerned with person-job rather than person-organisation fit. The central question is what individual difference factors are relevant to the person-job attraction situation.

Schneider (1987) proposed a theory based on three concepts: Attraction: People are differentially attracted to careers as a function of their own interests and personality. That is, they search out potential jobs and employers as a function of “fit”. Selection: Organizations then select people who they think have the abilities, personality and motivation to be successful at the job in their organisation. Thus, organizations end up choosing people who share many common characteristics and hence become more and more heterogeneous. Attrition: This occurs when people do not fit the organisation and leave it. One could add another stage called Socialisation which suggests that once people have been selected they get taught “what to think” and “how to behave” ( Furnham & Palaiou, 2017).

People are attracted to certain jobs and may or may not be well informed about the nature of the job. Consequently, applicants may be attracted to jobs like acting without any real knowledge of the industry or their particular abilities. After a person applies to a particular job/organisation that (s)he is attracted to, (s)he goes through a selection process which is aimed at getting people who would “thrive” in that work. Inevitably, selection processes differ considerably between organisations. The theory suggests that candidates for jobs do some sort of matching where they consider their “personal assets” in terms of abilities, preference and values; and then to what extent the organisation and the job requires those assets.

People often spontaneously apply for various different jobs at the same time based on “convenience” of place and time as well as salary. Nevertheless, the theory is very popular because it has valid points and makes good sense. Moreover, it has been tested in a variety of contexts ( Baron, Franklin, & Hmieleski, 2013).

In this study, we are looking at personality correlates of job changes; both “normal” bright-side traits and sub-clinical, personality disorder dark-side traits.

1.1. Bright Side Measures

There is a big literature onnormal personality trait correlates of job selection, satisfaction and productivity (Furnham, 2008, 2017). Although the literature on “fit” considers how person-job fit leads to an individual staying in a job, there is very little literature on personality correlates of job changing. There is however a literature on attraction, selection and fit. Swider, Zimmerman, Charlier, & Pierotti (2015) investigated the relation between applicant characteristics such as applicant ability, personality and experience and surface-level characteristics such as race, age and gender with applicant attraction. They noted: “… applicants high in Conscientiousness, Extraversion, work experience, and Emotional Stability as well as low in ability would be wise to recognize that they are more likely to be predisposed to feeling attracted to organizations, which may prevent them from eliminating alternatives and processing to a more narrow set of options as recruiting comes to a close … Our study, highlighting the independent influence of the “person”, indicates that there is value in applicants preparing for the recruitment process by recognizing the influence of their own individual differences on the recruitment process rather than just the organization” (p. 80).

It is possible to speculate on Big Five trait correlates of job changes based on the literature on job attraction ( Furnham & Palaiou, 2017). Neuroticism would be negatively correlated with change as people with low scores and the ability to cope with stress are tested with more challenging jobs. Extraversion would be positively associated with job (and many other lifestyle) changes as extraverts crave excitement. Conscientiousness would be positively correlated with change because conscientious people are ambitious and highly valued in organisations and more likely offered more job moves.

1.2. Dark Side Measures

Whilst there are a host of studies on management failure ( Newton, Khanna, & Thompson, 2008) there are also studies that suggest that some personality disorders, like Narcissistic Personality Disorder, may be at times be positively associated with leadership success ( Board & Fritzon, 2005; Bollaert & Petit, 2010). On the other hand, some personality disorders are associated with being systematically sacked from organisations ( Furnham, 2015).

This study used the Hogan “dark side” measure, now extensively used in organisational research and practice, to measure dysfunctional personality in the “normal population” ( De Fruyt et al., 2009; Furnham & Crump, 2005). This measure has been used in various studies to investigate dysfunctional behaviour at work ( Carson, Shanock, Heggestad, Andrew, Pugh, & Walter, 2012; Zibarras, Port, & Woods, 2008). The HDS focuses only on the core construct of each disorder from a dimensional perspective ( Hogan & Hogan, 2001: p. 41). Various relatively studies have used the HDS and have shown it to be a robust, reliable and valid instrument ( De Fruyt et al., 2009; Rolland & De Fruyt, 2003; Khoo & Burch, 2008). Various factor analytic studies of the HDS have yielded three factors rather different from the above ( Furnham & Trickey, 2011). These three clusters have also been described as Moving Against People (Bold, Mischievous, Colourful, Imaginative), Moving Toward People (Diligent, Dutiful), and Moving Away From (Excitable, Cautious, Skeptical, Reserved, Leisurely) others ( Hogan, Hogan, & Warrenfeltz, 2007).

The idea that dark side traits maybe beneficial in certain occupations has been observed by many writers ( Furnham, 2010; Hogan, 2007; Kets de Vries, 2006) particularly those using clinical case studies. Whilst some disorders are rarely associated with success in any jobs (Borderline, Avoidant, Dependent) others have been implicated as potentially beneficial (Bold, Mischievous, Diligent). It has been suggested that while some disorders appear to help in getting certain jobs they are also related to failure and sacking, and therefore high job turnover.

It was hypothesised that those scoring high on the Moving Against factor (Bold, Mischievous, Colourful and Imaginative) would have more job changes partly as a function of these dark side characteristics being paradoxically associated with management success ( Furnham, 2010).

Inevitably the older people are the more opportunities they have had to move jobs in their working lives. Thus, in all the analyses we control for age.

2. Method

2.1. Participants

There were a total of 7083 participants of whom 5568 were males and 1515 females. Their mean age was 40.07 years (SD = 7.76). They were employed in mainly large British organisations in the public and private sector, including banking and finance, pharmaceutical, engineering and law. Of these 4365 (3563 males) had been promoted to manager and 3119 (2618 males) promoted to senior manager.

2.2. Measures

1) NEO Personality Inventory form S (NEO-PI-R; Costa & McCrae, 1985)

The NEO Personality Inventory is based upon the five-factor model of trait personality. Each single factor/domain consists of six primary factors/facets which can be summed to form a total domain score. Thus the measure has five domain scores and thirty facet scores which allows for a finer grained analysis of the data. The inventory is composed of 240 self-descriptive statements to which respondents use a five-point scale in Likert format anchored by strongly agree and strongly disagree. The manual provides impressive evidence of both reliability and validity.

2) Hogan Development Survey ( Hogan, Hogan, & Warrenfeltz, 2007)

The HDS was explicitly based on the DSM Axis II personality disorder descriptions, but it was not developed for the assessment of all the DSM disorders. The HDS focuses only on the core construct of each disorder from a dimensional perspective ( Hogan & Hogan, 2001: p. 41). An overview of the item selection guidelines can be found in Hogan & Hogan (2001). The survey includes 154 items, scored for 11 scales, each grouping 14 items. The measure also has a social desirability scale.

3) Job Changes

Participants were asked to provide a detailed CV. Consultants who interviewed and tested each applicant, counted the number of different jobs, with different job titles that each person had. They were particularly interested in measuring breadth of thinking, and this variable—total number of jobs prior to current job—was used to investigate the hypothesis that leaders who have done more jobs and have more varied experience are likely to have developed greater breadth of thinking. They included those with a change in level (vertical move) and those with a change in responsibility (horizontal move). It also included moves to other organisations. Unfortunately, the data was collected in a way not to differentiate changes within and between organisations. Where possible this was checked during an interview with the candidate. The average was just over 7 times.

2.3. Procedure

Participants were required to attend a Middle Management Assessment Centre, run by a major British, psychological consultancy, over a 10 year period where they completed the questionnaires. The data was logged anonymously on an SPSS file. The assessment was primarily aimed at determining the suitability of each manager for promotion, but it was also used for developmental processes. Each manager was given full feedback on their results from all the tests that they completed including how he/she related to the test norms as well as his/her colleagues. They agreed that the anonymised data could be used for research. A number of papers have resulted from this large and rich data set ( Furnham et al., 2013).

3. Results

3.1. Correlations

Table 1 shows the correlations between all the measures. Inevitably the largest

correlation was between age (birth year) and number of jobs. Males also changed jobs more frequently partly because they were in the job market longer. The “bright side” five factors showed that Conscientious, Stable, Extraverts had had more job changes. The “dark side” factors indicated that those who were Cautious and Diligent had fewer changes while those who were Mischievous and Colourful had more job changes.

The 11 dark side variables were subjected to a Varimax Rotated factor analysis. (See Table 2) The result was a three factor solution identical to that reported in the manual as well other studies using different data sets ( Furnham & Trickey, 2011; Furnham, Trickey, & Hyde, 2012). There were three factors that accounted for 24.67%, 18.07% and 10.67% of the variance respectively. The first was labelled Moving Against Others, the second factor was labelled Moving Away from Others and the was labelled Moving Toward Others. Three factor scores were then used in further analyses.

3.2. Regressions

Bright Side: A series of regressions were run with number of jobs as the criterion score and the Big Five as predictors after sex, age and social desirability was entered in the first block.

Table 3 shows the regression for the Big Five Domain traits. The five traits were not significant. Thereafter, five regressions were run with the six facets of each of the Big Five traits as predictor variables. The regression for Neuroticism was significant (F (9, 3876) = 50.55, p < 0.001; AdjR2 = 0.10. Two facets were significant: N5 (Impulsiveness) (Beta = 0.06, t = 3.82, p < 0.001) and N6 (Vulnerability) (Beta = −0.07, t = 3.07, p < 0.01). Thus, less vulnerable but more impulsive people were likely to have experienced job changes. The regression for

Table 2. Results from the factor analysis.

Extraversion was significant (F (9, 3876) = 49.51, p < 0.001; AdjR2 = 0.10). One facet was significant: E3 (Assertiveness) (Beta = 0.07, t = 3.82, p < 0.001). Assertive people have more job changes. The regression for Openness was significant (F (9, 3876) = 52.19, p < 0.001; AdjR2 = 0.10. Three facets were significant: 02 (Aesthetics) (Beta = −0.07, t = 3.69, p < 0.001), 03 (Feelings) (Beta = 0.05, t = 2.84 p < 0.01) and 04 (Actions) (Beta = 0.07, t = 4.27 p < 0.001). Those people less interested in aesthetics but more interested in their how and others feelings and actions had had more jobs.

The regression for Agreeableness was also significant (F (9, 3876) = 48.99, p < 0.001; AdjR2 = 0.10). Three facets were significant: A2 (Straightforwardness) (Beta = −0.05, t = 2.53, p < 0.01), A5 (Modesty) (Beta = −0.04, t = 2.10 p < 0.05) and A6 (Tender Minded) (Beta = −0.06, t = 3.29, p < 0.001). Less modest, tender-minded and straightforward people had had more jobs.

Finally, the regression for Conscientiouness was significant (F (9, 3876) = 50.72, p < 0.001; AdjR2 = 0.10. Two facets were significant: C4 (Achievement Striving) (Beta = 0.08, t = 4.33 p < 0.001), and C6 (Deliberation) (Beta = −0.06, t = 3.24 p < 0.001). Those who were more achievement oriented but less deliberate had had more jobs.

Dark Side: Similar regressions were run (See Table 4). The Moving Against

Table 3. Regressions with the Job Changes as the criterion scale and demographics and the bright side variables as the predictor scales.

F (8, 3891) = 53.57, p < 0.001, Adj R2 = 0.10. ***p < 0.001 **p < 0.01 *p < 0.05.

Table 4. Regressions with the Job Changes as the criterion scale and demographics and the Bright Side Variables as the predictor scales.

F (6, 6269) = 71.54, p < 0.001, Adj R2 = 0.11. ***p < 0.001; **p < 0.01; *p < 0.05.

Others factor was a significant correlate indicating a higher score was associated with more jobs. A second regression was run this time using all eleven dark side factors. This was significant (F (14, 3886) = 31.64, p < 0.001, AdjR2 = 0.10). Only two had significant Beta’s: Mischievous (Beta = −0.08; t = 3.10, p < 0.001) and Imaginative (Beta = 0.04, t = 1.99, p < 0.05). More imaginative (Schizotypal) but less anti-social people had had more jobs.

4. Discussion

In this study we were interested primarily in correlates of job changes. Some changes are. for individuals, completely voluntary such as resigning from one organisation to go to another while other are completely out of personal control such as being sacked or where a job is made redundant. Next the type of job, organisation and sector may have a big influence on the number of jobs a person has. Thus, if one works in a small organisation, with a flat structure in a steady market, job changes (i.e. promotion, side-ways moves) will be comparatively unlikely while if one works in a big, hierarchical and expanding organisation, job changes will be more likely

The results of this study showed first, as could be suspected, the power of demographic variables on job changes Females had fewer jobs than males which could be explained by numerous factors including “taking time out” for child rearing or “the glass ceiling”. Age was expectedly by far the largest correlate simply because older people were at work longer and had therefore many more opportunities to change jobs.

The results from the correlations and regressions showed most, but predictable, results for the “bright side” Big Five personality traits. Neurotics, particularly those high on Vulnerability changed jobs less frequently no doubt because of all the worry and adaptation to change that is required. Extraverts, particularly those high on Assertiveness changed jobs more often possibly because of their ability to speak-up, be noticed and ask for promotion. It was the Achievement-Striving factor in Conscientiousness that most accounted for the significant correlation. However, overall the Domain five factors did not contribute incremental variance over the demographic factors. Indeed, the size of the correlations shown in Table 1 indicate how comparatively little variance the bright side personality factors accounted for in job changes.

The results from the “dark side” personality disorders indicated three positive (Mischievous, Imaginative and Colourful) positive and two negative (Cautious and Dutiful) correlates of job changes. The anti-social, possibly selfish, individual, with quirky ideas and emotional displays, may get more noticed by others and promoted. Equally the quiet, retiring, dutiful individual is equally unlikely to be noticed or to put themselves forward for change.

Perhaps the most important results are shown in Table 4 which shows the regression for the three “higher order” dark side factors. The Moving Against Others was significant. In other studies this factor has shown to be, paradoxically, related to a range of issues like promotion

( Furnham, Crump, & Ritchie, 2013) and being rated as having managerial potential ( Furnham, Trickey, & Hyde, 2012). One explanation lies the fact that those with high Moving Against Others are more likely to be noticed (possibly for promotion or sacking) as well as being somewhat manipulative of others. This factor did not account for a great deal of the variance but indicated promising areas for future research.

According to Horney (1945, 1950) who coined the term, the Moving Away From Others factor has various clear characteristics: The need for power; the ability to bend wills and achieve control over others—while most persons seek strength, the neurotic may be desperate for it. The need to exploit others; to get the better of them. To become manipulative, fostering the belief that people are there simply to be used. The need for social recognition; prestige and limelight. The need for personal admiration; for both inner and outer qualities—to be valued.

Given these characteristics it is perhaps no surprise that the factor is associated with job changes initiated both by the employee and the employer.

The sample in this study was both a source of strength and weakness because it was heterogeneous in terms of organisation. Had we used one organisation we could have been much clearer about the exact definitions and explanation of job change but that would have restricted the size of the sample and the generalisability of the results across different organisations. Inevitably differences may have occurred in the precise definition of job change, though by far the most common, was promotion or resignation to work elsewhere. Further, we had no indication of the participants’ education and training, or varied work experience which may have contributed significantly to their promotion. We also did not have any appraisal or performance data to indicate whether the organisation thought that they were effective as managers. Moreover, the correlations between the bright and dark side personality variables does not rule out the possibility of third factors. Thus, Extraverts maybe better networkers and Conscientious people more astute in choosing projects that succeed and therefore lead to promotion

This paper had various limitations. The main criterion variable, job changes, includes vertical moves and horizontal moves added together in a single index. The kinds of personality traits that may predict vertical moves (e.g., promotions) are likely to be those that are associated with exemplary performance, whereas the traits that may predict horizontal moves (moving to another company or another job in the company) may include those that are associated with difficulties in getting along with others. The results would be much more interpretable if there were one criterion (and score) for number of vertical moves and another for number of horizontal moves as well as movements between as well as within organisations. In that scenario one would still want to statistically control for age, or perhaps use indices like number of vertical moves per year of employment and number of horizontal moves per year of employment. But, there would still be a problem in distinguishing between horizontal moves that were initiated by the candidate and may actually be vertical moves, and horizontal moves that were initiated by the employer as a result of unsatisfactory performance (or other problems) attributed to the participant. We confirmed with the consultants that most moves however were positive in the sense that employees volunteered for or were offered different jobs to further their experience. Nevertheless, the reason for, and type of move may be as important as the number of moves made.

It would also be desirable to have data on individuals such as their job motivation, education level and speciality. Also, where they live has clearly an impact on the job market. Taking into account these factors one question central to this paper is which and how much personality factors add incremental validity over and above demographics, abilities and motivation.

5. Conclusion

Over their working lives, some people appear to have had many more jobs than others. In this study, we found older more than younger, and male rather than female workers, had more jobs. There was also some evidence of personality differences: Conscientious, Extraverts had changed jobs more often but Neurotics less often. Also, those who were Cautious and Diligent had fewer changes while those who were Mischievous and Colourful had more job changes. As noted above research in this area is difficult because there are so many factors that influence job changes.

Conflicts of Interest

The authors declare no conflicts of interest.


[1] Baron, R. A., Franklin, R. J., & Hmieleski, K. M. (2013). Why Entrepreneurs Often Experience Low, Not High, Levels of Stress. The Joint Effects of Selection and Psychological Capital. Journal of Management, 42, 742-768.
[2] Bipp, T., & Demerouti, E. (2014). Which Employees Craft Their Jobs and How? Basic Dimensions of Personality and Employees’ Job Crafting Behaviour. Journal of Occupational and Organizational Psychology, 88, 631-655.
[3] Board, B. J., & Fritzon, K. (2005). Disordered Personalities at Work. Psychology, Crime & Law, 11, 17-32.
[4] Bollaert, H., & Petit, V. (2010). Beyond the Dark Side of Executive Psychology: Current Research and New Directions. European Management Journal, 28, 362-376.
[5] Carson, M., Shanock, L., Heggestad, E., Andrew, A., Pugh, S., & Walter, M. (2012). The Relationship between Dysfunctional Interpersonal Tendencies, Derailment Potential Behavior, and Turnover. Journal of Business and Psychology, 27, 291-304.
[6] Costa, P., & McCrae, R. (1985). The NEO Personality Inventory Manual. Odessa, FL: Psychological Assessment Resources.
[7] De Fruyt, F., De Clercq, B., Milley, J., Rolland, J. P., Jung, S. C., Taris, R., Furnham, A., & Hiel, A. (2009). Assessing Personality at Risk in Personnel Selection and Development. European Journal of Personality, 23, 51-69.
[8] Furnham, A. (2005). The Psychology of Behaviour at Work. Hove: Psychologist Press.
[9] Furnham, A. (2010). The Elephant in the Boardroom: The Psychology of Leadership Derailment. Bracknell: Palgrave MacMillan.
[10] Furnham, A. (2015). Backstabbers and Bullies. London: Bloomsbury Publishing.
[11] Furnham, A. (2018). Personality and Occupational Success. In V. Zeigler-Hill, & T. K. Shackelford (Eds.), The SAGE Handbook of Personality and Individual Differences (pp. 537-551). New York: Sage.
[12] Furnham, A., & Crump, J. (2005). Personality Traits, Types and Disorders. European Journal of Personality, 19, 167-184.
[13] Furnham, A., & Palaiou, K. (2017). Applicant Attraction to Organizations and Job Choice. In J. Passmore, E. Salas, C. Semedo, & H. Goodstein (Eds.), The Wiley Blackwell Handbook of the Psychology of Recruitment, Selection and Team Dynamics (pp. 74-86). Chichester: Wiley.
[14] Furnham, A., & Trickey, G. (2011). Sex Differences and Dark Side Traits. Personality and Individual Differences, 50, 517-522.
[15] Furnham, A., Crump, J., & Ritchie, W. (2013). What It Takes: Ability, Demographic, Bright and Dark Side Trait Correlates of Years to Promotion. Personality and Individual Differences, 55, 952-956.
[16] Furnham, A., Trickey, G., & Hyde, G. (2012). Bright Aspects to Dark Side Traits: Dark Side Traits Associated with Work Success. Personality and Individual Differences, 52, 908-913.
[17] Hogan, R. (2007). Personality and the Fate of Organizations. Mahwah, NJ: Lawrence Erlbaum.
[18] Hogan, R., & Hogan, J. (2001). Assessing Leadership: A View from the Dark Side. International Journal of Selection and Assessment, 9, 40-51.
[19] Hogan, R., Hogan, J., & Warrenfeltz, R. (2007) The Hogan Guide. Tulsa, OK: Hogan Press.
[20] Horney, K. (1945). Our Inner Conflicts. New York: Norton.
[21] Horney, K. (1950). Neurosis and Human Growth. New York: Norton.
[22] Kets de Vries, N. (2006). The Leader on the Couch. New York: Jossey Bass.
[23] Khoo, H., & Burch, G. (2008). The “Dark Side” of Leadership Personality and Transformational Leadership. Personality and Individual Differences, 44, 86-97.
[24] Newton, N. A., Khanna, C., & Thompson, J. (2008). Workplace Failure: Mastering the Last Taboo. Consulting Psychology Journal: Practice and Research, 60, 227-245.
[25] Rolland, J. P., & De Fruyt, F. (2003). The Validity of FFM Personality Dimensions and Maladaptive Traits to Predict Negative Affect at Work. European Journal of Personality, 17, 101-121.
[26] Schneider, B. (1987). The People Make the Place. Personnel Psychology, 40, 437-453.
[27] Swider, B. W., Zimmerman, R. D., Charlier, S. D., & Pierotti, A. J. (2015). Deep-Level and Surface-Level Individual Differences and Applicant Attraction to Organizations: A Meta-Analysis. Journal of Vocational Behaviour, 88, 73-88.
[28] Teodorescu, A., Furnham, A., & Macrae, I. (2017). Trait Correlates of Success at Work. International Journal of Selection and Assessment, 25, 36-42.
[29] Zibarras, L., Port, R., & Woods, S. (2008). Innovation and the “Dark Side” of Personality. Journal of Creative Behavior, 42, 201-215.

Copyright © 2023 by authors and Scientific Research Publishing Inc.

Creative Commons License

This work and the related PDF file are licensed under a Creative Commons Attribution 4.0 International License.