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Personality Predictors and Job Performance
Personality Predictors and Job Performance
Alex Larson
San Diego State University
PSY 497 – Dr. Conte

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Personality Predictors and Job Performance
One of the most important and relevant topics in industrial and organizational psychology
is job performance. Job performance is not as simple as many would assume and is much more
than just outputs and numbers. In reality, job performance starts with a complex network of
determinants and predictors, one of the most famous and well recognized being the “Five Factor
Model.” The five traits, “openness to experience,” “conscientiousness,” “extraversion,”
“agreeableness,” and “neuroticism,” have been used as the key personality predictors for job
performance (McCrae & John, 1992), but how effective are these predictors? Are the
correlations between these and job performance strong enough to be conclusive, or are there
better and more effective ways to evaluate personality predictors of job performance in the
workplace? What else is able to help accurately predict job performance? Analysis of recently
published, peer-reviewed articles gives an insightful look to help answer these questions and
helps provide direction for future research.
Some articles with relevant information have reoccurring and underlying themes to them
such as gender, and Gonzales-Mulé, DeGeest, Kiersch, and Mount (2013) specifically categorize
and analyze gender differences for predictors of job performance. Workplace aggression for both
men and women is the target of their work (Gonzales-Mulé, DeGeest, Kiersch, & Mount, 2013),
and with good reason after Pearson and Porath (2005) found that one in eight people who
recently resigned left as a result of aggression and disrespect. Two-hundred and twelve
participants with entry-level positions were selected from a human resources management class
for the study, and personality measures, pleasantness, calmness, and interpersonal
counterproductive work behaviors were measured through a survey and tested for both men and
women (Gonzales-Mulé, DeGeest, Kiersch, & Mount, 2013). Through statistically significant
evidence, they found females to be more agreeable, pleasant, and calm, while males were more

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Personality Predictors and Job Performance
emotionally stable but also showed higher levels of interpersonal workplace counterproductive
work behaviors (Gonzales-Mulé, DeGeest, Kiersch, & Mount, 2013). More evidence reveals
men have a higher probability of acting aggressively in the workplace (Gonzales-Mulé, DeGeest,
Kiersch, & Mount, 2013), a result which supports Darwin’s Sexual Selection Theory, where
males must fight and compete for mates of the opposite sex in a process known as intra-sexual
selection (Mota, 2010), and Social Role Theory, which questions women’s role in the workplace
due to their lack of aggression compared to males (Dulin, 2007). The researchers also found that
pleasantness and calmness have more validity than the Five Factor Model when predicting
interpersonal counterproductive work behaviors, and emotional stability, agreeableness, and
pleasantness all differ based on gender alone when predicting counterproductive work behaviors
and aggression (Gonzales-Mulé, DeGeest, Kiersch, & Mount, 2013). This is just one finding
suggesting that the Five Factor Model may not be the best predictor of job performance, and
future research has already been proposed to examine pleasantness and calmness more closely as
predictors compared to Five Factor Model specifically, and to also research other forms of
workplace aggression, such as direct aggression compared to gossip or rumors Gonzales-Mulé,
DeGeest, Kiersch, & Mount, (2013).
Another theme found in literature is race, specifically black and white differences for
predictors of job performance (Bobko & Roth, 2013). Bobko and Roth analyze the level of
validity of standardized subgroup differences as predictors (2013), as well as adverse impact, a
legal issue regarding discrimination of protected groups in the workplace (Hough & Ployhart,
2001). They do this by reviewing previously published literature on differences in personnel
selection test scores, and overall differences and pre-assumptions made due to race (Bobko &
Roth, 2013). They have found that inaccurate estimates of black and white standardized

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subgroup differences may be the cause of adverse impact in the workplace, and subgroup
differences fluctuate depending on what skills and abilities are targeted by certain tests (Bobko &
Roth, 2013). This means that overall job performance could be affected simply by how the
personalities of potential employees are evaluated during the selection process, as the differences
between white and black employees increase when certain tests target cognitive abilities, as
opposed to a decrease when targeting social skills. Bobko and Roth have concluded differences
between groups may not be as large as predicted sometimes and may not be as small as predicted
other times, and certain tests have commonly made the wrong assumption when it comes to these
differences (2013). Some factors may seem miniscule and irrelevant in the big picture, but when
it comes down to it, even the smallest factor if overlooked can be the cause of something major
such as adverse impact in the workplace. Different tests targeting specific personality predictors
such as the “Big Five” separate employees right off the bat, and the larger difference leads to
potential adverse impact, which can decrease motivation and performance for those being
affected by it (Bobko & Roth, 2013). It is unclear if race is a predictor of performance in the
workplace, but race is clearly a factor, especially if it is making a difference as early on as the
hiring process. Personality tests and other forms of evaluation need to make sure they are not
causing this separation and unnecessarily skewed data, because if one’s personality is to be a true
predictor of performance, then it can’t be swayed by miscalculations and race before the
selection process is even finished.
One last theme has to do with one’s rank, and whether a managerial position influences
performance compared to an entry-level or more basic position in the organization (Huang,
Zabel, & Palmer, 2014). Due to changing technologies, economies, and business structures
(Huang, Zabel, & Palmer, 2014), adaptation is key for both employees and organizations to

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succeed (Bhattacharya, Gibson, & Doty, 2005), and “Big Five” predictors relate to adaptive
performance just as with other types of performance (Huang, Zabel, & Palmer, 2014). Their
experiment focuses on emotional stability and extraversion, but Huang, Zabel, and Palmer touch
on all five factors in their work. Openness to experience could be advantageous to adaptation in
the workplace as it leads to a variety of innovative ideas to help solve problems (Nettle, 2006),
agreeableness is an important aspect of interacting with others in the workplace but really
depends on the environment (Nettle, 2006), and conscientiousness helps long-term planning and
striving towards one’s goals as it can be linked to one’s drive and determination (Denissen &
Penke, 2008). Extraversion enables one to boldly seek rewards but really depends on the
environment (Nettle, 2006), and the ability to remain emotionally stable regardless of what
comes a worker’s way is needed in “fight or flight” situations. An organization would much
rather select someone who is able to stand their ground and “fight” for their organization (Nettle,
2006). Huang, Zabel, and Palmer took 18 managerial samples and 53 employee samples from a
total population of 7,535 from a range of work fields and conducted a meta-analysis examining
extraversion and neuroticism. After running the tests, their conclusions fell in line with previous
research as emotional stability and extraversion proved to enhance one’s adaptive performance,
and both are stronger in managers rather than employees (Huang, Zabel, & Palmer, 2014). This
ambition and drive to be proactive and successful, while also keeping calm, helps one see
changes approaching, react accordingly, and seize opportunities (Pulakos, Arad, Donovan, &
Plamondon, 2000). The business world is very competitive, but organizations can give
themselves the upper hand by selecting managers and employees who exhibit these qualities.
Managers have more chances to show their proactive potential, and being able to adapt quickly
and without fear can lead to overall success for the company (Huang, Zabel, & Palmer, 2014).

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Thanks to their research, future studies can be made in regards to other personality traits outside
of the “Big Five,” and also how well personality traits are able to predict cognitive abilities and
its relation to adaptive performance in the workplace.
Huang, Zabel, and Palmer’s work not only revealed personality traits for successful
managers, but also for employees who are truly ambitious and have a desire to propel the
company and themselves upward (2014). This proactive personality has also been researched by
Bakker, Tims, and Derks in order to see how well it is able to predict work engagement and job
performance (2012). Proactive personality is the willful manipulation of one’s situation in order
to create beneficial change in one’s surroundings (Buss, 1987), predicts organizational
citizenship behaviors (Greguras & Diefendorff, 2010), and boosts overall effectiveness as a
result of positive attitude (Crant, 2000). A manager is not always around to motivate, assist, and
encourage each individual employee, so it is up to that employee to do it for themselves. This
proactive behavior should increase work engagement and job performance, and Bakker, Tims,
and Derks investigated through data analysis (2012). They selected 95 dyads for a total of 190
subjects from organizations in the Netherlands and conducted an online questionnaire through
email where those selected first rated themselves and then their counterparts afterwards. Results
revealed proactive personality as well as work engagement to be predictors of job performance,
as employees who exhibit these qualities are more resourceful and rise to meet the demands of
the organization (Bakker, Tims, & Derks, 2012). Crafting one’s job will lead to enhanced work
engagement and this engagement will then predict better performance, something which can help
an organization’s human resource management and organizational development in the future
(Bakker, Schaufeli, Leiter, & Taris, 2008). Although Bakker, Tim, and Derks’s study
successfully helped explain the positive correlation between proactive personality and job

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performance (2012), they also revealed and that there may be a better predictor of job
performance than personality traits such as the Five Factor Model. It is not necessarily one’s
personality, but the actions as a result from their personality which determine performance
because personality predictors mean nothing until the employee acts proactively (Daniels, 2006).
Overall proactive personality and the resulting actions account for more than the “Big Five” is
able to when job performance is truly broken down to its simplest and smallest factors (Crant &
Bateman, 2000). All of these aspects are intertwined together and result in better, more accurate
predictions of job performance, but the research has exposed weakness in the “Big Five.”
Although some of the previous articles have shown a slightly better predictor than the
“Big Five,” its validity still holds strong from countless prior studies. It has proven to predict job
performance for employees and managers, but what about those at the very top of the
organization? Colbert, Barrick, and Bradley examine top management team personality and
leadership as predictors of organizational financial performance and effectiveness (2014).
Decisions to lead an organization are not made by one individual, but rather an entire team of
executives (Hambrick, 2007), and their personalities will have influence on these decisions and
outcomes. However, they chose to analyze the CEO and TMT separately to first find the
individual influence of both and then combine the results for the overall team (Colbert, Barrick,
& Bradley, 2014). A final sample of 94 CEO’s and 507 TMT members was collected from
United States’ credit unions and the National Credit Union Administration, and “Big Five”
personality traits were self-rated on a five-point scale by the individuals. Performance was
measured through financial ratios one year later, and a path analysis was conducted to see the
correlation. Data and statistics show conscientiousness, emotional stability, and openness to
experience, for both the CEO and overall team, to help predict greater performance financially

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Personality Predictors and Job Performance
(Colbert, Barrick, & Bradley, 2014). If a company’s overall goal is to profit, then this finding is
extremely important and reveal what is necessary for a CEO and TMT to be effective leaders.
This transformational leadership encompasses these traits and helps teams plan more effectively,
work more vigorously, and endure through adversity (Colbert, Barrick, & Bradley, 2014).
Conscientiousness, emotional stability, and openness to experience can be categorized as task-
oriented, while extraversion and agreeableness can be categorized as interpersonally-oriented
(DeRue, Wellman, Nahrgang, & Humphrey, 2011). The task-oriented traits result as the most
influential predictors (Colbert, Barrick, & Bradley, 2014), as conscientiousness and emotional
stability directly relate to both organizational performance and commitment at almost any level
of occupation for both individuals and teams (Barrick, Mount, & Judge, 2011), and openness to
experience helps boost one’s own leadership effectiveness as well as team performance (Judge,
Bono, Ilies, Gerhardt, 2002). Colbert, Barrick, and Bradley’s work has laid a foundation for
future research in both individual and team efforts, possibly to uncover mediators and
moderators of performance, and to also investigate negative individual influence from executives
on an organization if the rest of the team exhibits the positive personality traits discussed above
(2014). But, for now, they have reconfirmed aspects of the Five Factor Model as strong
predictors of performance in the workplace.
While Colbert, Barrick, and Bradley’s research resulted in some of the “Big Five” as
more influential and predictive than others (2014), Judge, Rodell, Klinger, Simon, and Crawford
specifically designed their research to break down and analyze each of the “Big Five” traits in
order to try to help solve the debate between broad or faceted measures of each trait as better
predictors of performance in the workplace (2013). The generally accepted and most popular
structure of the traits is the six-facet NEO approach, where each trait is broken down into six

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facets to better describe the trait (Costa & McCrae, 1992). Two issues fueling the debate are the
“bandwidth fidelity dilemma,” which compares and contrasts “multidimensional but unreliable”
and “reliable but unidimensional” aspects of predictor-criterion validity (Cronbach & Gleser,
1965) and the discussion over “construct correspondence,” which theoretically presumes specific
motives should best predict specific behaviors and broad motives should best predict broad
behaviors (Harrison, Newman, & Roth, 2006). However, neither of these issues have really
helped solve the debate surrounding these different perspectives on broad and narrow traits.
Something which is relevant though is DeYoung, Quilty, and Peterson’s contribution to the
literature by presenting a 10-facet structure of the “Big Five” (2007). Rather than six facets per
trait, they proposed each could be simplified into two, with “industriousness and orderliness” for
“conscientiousness,” “compassion and politeness” for “agreeableness,” “volatility and
withdrawal” for “neuroticism,” “intellect and aesthetic openness” for “openness to experience,”
and “enthusiasm and assertiveness” for “extraversion” (DeYoung, Quilty, & Peterson, 2007).
Judge, Rodell, Klinger, Simon, and Crawford’s goal (2013) was to replicate DeYoung, Quilty,
and Peterson’s work (2007), create a 6-2-1 framework, and use meta-analysis of the data to
determine the best predictors of overall, task, and contextual performance (Judge, Rodell,
Klinger, Simon, & Crawford 2013). They assessed the correlation between narrow traits to job
performance and broad traits to job performance independently using Costa and McCrae’s
framework of thirty total facets (1992) and then treated these with factor analyses to produce just
ten factors like DeYoung, Quilty, and Peterson (2007), and combined both the previous research
and their own meta-analysis to produce their results. After testing 1,176 correlations from 410
independent samples, Judge, Rodell, Klinger, Simon, and Crawford concluded lower order traits
do help predict work performance, and shifting from broad to narrow traits helped increase

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predictive power (2013). Their results were not necessarily congruent with “correspondence
perspective” and “bandwidth-fidelity,” and results did also indicate broad traits are better
predictors of overall job performance, so they are supportive of wideband, faceted interpretations
of the “Big Five” (Judge, Rodell, Klinger, Simon, & Crawford 2013). These discoveries have
made an impact but researchers are still nowhere near solving the debate, because the debate
itself is the main problem; In order to get closer to understanding predictors of job performance,
researchers must look at both narrow and broad traits as predictors and look at the big picture
rather than debating over which is more important. These researchers accomplished this in their
6-2-1 framework technique and have shown this hierarchical approach to be a better
representation of criterion-related validity (Judge, Rodell, Klinger, Simon, & Crawford, 2013).
Future research implies looking at the conditions through even more broadly or narrowly, as
these researchers have revealed it is all about perspective when examining the “Big Five.”
The research above looked at this data as a big picture, and in the big picture of
personality predictors of job performance, results must be extensive over time and generalizable
to help predict performance in the future. One way of doing this was the research of Minbashian,
Earl, and Bright, who looked into personality predictors and their correlation to performance
trajectories and rates of deceleration (2013). These types of longitudinal studies have uncovered
a pattern and a curve for job performance, as it tends to rise at first but will eventually plateau
and then fall as time progresses (Hofmann, Jacobs, & Baratta, 1993). Just as time affects job
performance, so do individual differences between workers (Hofmann, Jacobs, & Baratta, 1993).
Openness to experience from the Five Factor Model helps predict these individual differences,
and individuals with high openness to experience have a higher probability of increasing
performance over time due to their desire to gain more knowledge and skill (Costa & McCrae,

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1992). To test openness to experience as a predictor, the researchers sampled 129 recent
graduates who had recently been hired directly by a large, professional company in Australia
(Minbasian, Earl, & Bright, 2013). After working at the company for six months, the employees
filled out the Congruence Personality Scale-2 (CPS-2; Pryor & Taylor, 2000) to assess their
levels of each personality trait, and then the company supervisor assessed their performance on a
1-5 scale over the course of the next four years where 494 performance ratings were given in
total (Minbasian, Earl, & Bright, 2013). Through use of hierarchical linear modeling to interpret
the results, Minbasian, Earl, and Bright found the average time of performance plateau followed
by deceleration to be roughly 2.93 years for the average employee, and when including openness
to experience, those with low ratings declined around 2.72 years while those with high ratings
did not decline until around 3.34 years. This finding suggests openness to experience to be a
significant predictor of job performance over time, as it is able to extend performance and
prolong deceleration. Future research could include looking into all of the other personality
factors in the model and also mediators such as learning orientations and regulatory goals
(Minbasian, Earl, & Bright, 2013). Learning orientation is one’s motivation and drive to learn
and master tasks in the long run (Harris, Mowen, & Brown, 2005), and workers strive for and
focus on promotion through regulatory goals (Vaughn, Bautmann, & Klemann, 2008).
Understanding these concepts could help researchers understand what helps maintain drive to
keep acquiring knowledge and what helps workers strive for promotions. This data was only
collected over a period of four years and there was still a significant difference between those
rated high versus low on openness to experience (Minbasian, Earl, & Bright, 2013), so if the
findings are generalizable and can be expanded upon, this could help predict performance on a
larger, more important scale relating to one’s career. If one can last longer before decelerating,

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they may be able to acquire more knowledge and achieve higher levels of status through
promotion.
One of these individuals of high status is Laszlo Block, the senior vice president of
people operations at Google. In his closing plenary speech at the 2016 Society for Industrial and
Organizational Psychology Annual Conference in Anaheim, California, Block was astounded by
the current research and findings of industrial and organizational psychologists on a global level,
and encouraged everyone to keep advancing and moving forward with their research. Current
studies are paving the way for the science to grow and are helping correlate psychological
findings and areas of interest such as the “Big Five” personality predictors with business-
applicable outcomes such as job performance. Future research includes looking into other human
qualities and attributes as alternatives for the Five Factor Model (Gonzales-Mulé, DeGeest,
Kiersch, & Mount, 2013), separating hard facts from assumptions, and analyzing cognitive
abilities and their relationships with job performance (Huang, Zabel, & Palmer, 2014). Other
areas of interest include taking a step back to see both sides of broad and narrow trait views
(Judge, Rodell, Klinger, Simon, & Crawford, 2013), comparing individual and team levels of
predictors and performance (Colbert, Barrick, & Bradley, 2014), and recognizing personality
predictors from the Five Factor Model and uncovering what causes and drives them (Minbasian,
Earl, & Bright, 2013). Some studies have supported aspects of the “Big Five” such as with
Huang, Zabel, and Palmer, as well as Colbert, Barrick, and Bradley, through their successful
meta-analyses of traits to confirm them as accurate predictors of adaptive and financial
performance (2014). The Five Factor Model has to be open to different interpretations and
perspectives to fully understand it (Judge, Rodell, Klinger, Simon, & Crawford, 2013), and
another area which showed success was analyzing performance in the long run to show some

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traits as key predictors for one’s career (Minbasian, Earl, & Bright, 2013). On the other hand,
some aspects have been contrasted due to findings of other, more valid predictors of performance
(Gonzales-Mulé, DeGeest, Kiersch, & Mount, 2013), inaccurate measures and assumptions when
assessing the “Big Five” (Bobko & Roth, 2013), and it may not be the factors of personality but
rather the actions of personality as better predictors of job performance (Daniels, 2006). Because
there have been so many studies on these topics and so many different sides and views as a
result, there is no conclusive stance on whether or not the Five Factor Model is the best method
of predicting performance. However, as long as innovative thinking and research continues, the
workplace can eventually get closer to fully understanding personality predictors of job
performance.

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