Category Archives: Job Performance

Time for Teamwork: When Aspects of Collectivism are Most Beneficial

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Topic: Goals, Job Performance, Teams
Publication: Journal of Applied Psychology (March, 2011)
Article: The power of “we”: effects of psychological collectivism on team
performance over time
Authors: Erich C. Dierdorff, Suzanne T. Bell, and James A. Belohlav
Reviewed By: Allison B. Siminovsky

Collectivism, in essence, is the orientation of a group’s members toward a similar set of goals and for their mutual wellbeing as a team.  A group composed of collectivistic members should be more cooperative and will likely show a higher degree of citizenship behavior amongst its team members.  However, can certain aspects of collectivism be damaging?  The authors of this study set out to determine the interplay of psychological collectivism and team performance over the course of time.

The authors measured a number of different aspects of collectivism in group members during various points in group formation and attempted to link this information to the group’s performance.  For example, they found that preference, the collectivistic aspect involving interest in aligning with other group members, was beneficial to groups at initial formation.  On the other hand, the aspect of reliance, or assuming that other members will take on as much responsibility as you will, can be damaging to a newly formed group.  Group members need time to get to know one another on the interpersonal level and diving too quickly into responsibility assumptions can damage new relationships.

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Does Being Proactive in Your Job Positively Relate to Your Performance, Satisfaction, and Commitment? Yes, Yes, and Yes!

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Topic:  Job Performance, Organizational Commitment
Publication: Journal of Occupational and Organizational Psychology (JUNE 2010)
Article:Employee proactivity in organizations: A comparative meta-analysis of emergent proactive constructs
Authors: Jeffrey P. Thomas, Daniel S. Whitman, and Chockalingam Viswesvaran
Reviewed by: Mary Alice Crowe-Taylor

Given the dynamic nature of the work environment, being proactive has become necessary for today’s leaders and managers. What does that mean? More specifically, what is Employee Proactivity and what does it lead to? Measuring Employee Proactivity has varied from measuring “proactive personality”, which is considered a steady, natural propensity to direct or control circumstances and dynamically provoke change, to measuring “voice” which measures the tendency to constructively discuss change. Two other ways of measuring it are the self-explanatory variables “personal initiative” and “taking charge”.

In this study, using meta-analysis, these authors analyzed 103 data sets totaling 32,967 participants and empirically determined the relationships between these types of measures of Employee Proactivity and job performance, job satisfaction, organizational commitment as well as: “the big five” personality traits; social networking ability; work experience; age; and general mental ability.

Whew! What a lot of variables! Well, the good news is that the authors were very comprehensive and exacting in their analysis. Employee Proactivity, measured as “proactive personality”, ”taking personal initiative” and “taking charge”, positively correlated with both subjective and objective job performance.

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What Does Organizational Tenure Really Buy You?

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Topic: Citizenship Behaviors, Counter-Productive Work Behavior, Job Performance

Publication: Journal
of Management (SEP)

Article: Organizational tenure and job performance

Authors: T.W.H.
Ng and D.C. Feldman

Reviewed By: Benjamin Granger


Ladder Success  It is
often intuited that employees who remain in an organization longer gain more
knowledge of their job and the organization and thus perform at a higher level
than employees with less tenure. 
Indeed, it’s no secret that organizational tenure is common factor
considered in administrative decisions such as offering promotions and awarding
raises and other fringe benefits (e.g., pensions, vacation days).  For many of us, anecdotal evidence
probably confirms the assumption that as tenure within the organization
increases, so does performance. 
But what does the research say? 

In a recent
meta-analysis of the relationship between organizational tenure and job
performance, Ng and Feldman (2010) combined data from 350 studies which
included nearly 250,000 research participants.  Not surprisingly, the authors expected that organizational
tenure would be favorably related to various forms of job performance.  Their findings generally confirmed that
organizational tenure is favorably
associated with performance.  However,
the relationships between tenure and performance was quite weak overall. 

While
there was modest positive association between organizational tenure and task
performance and organizational citizenship behaviors, the benefit of tenure
appears to drop as tenure increases.

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Emotional Intelligence: A tangled web of definitions, predictors, outcomes, and models

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Topic: Emotional Intelligence, Job Performance, Leadership

Publication: Industrial and Organizational Psychology: Perspectives on Science and Practice

Article: Emotional Intelligence: Toward Clarification of a Concept

Author: C. Cherniss

Selected commentary authors: Kaplan, Cortina, and Ruark (2010); Antonakis, J. & Dietz, J. (2010)

Reviewed by: Samantha Paustian-Underdahl

 

Images Emotional Intelligence (EI) has been one of the most popular topics studied throughout the history of I/O psychology. Given its popularity, it has been defined and measured in several different ways throughout time, leading to some confusion and controversy in the field. Cherniss (2010) argues that despite these multiple definitions and models, most researchers generally agree on what EI is: ‘‘the ability to perceive and express emotion, assimilate emotion in thought, understand and reason with emotion, and regulate emotion in the self and others’’ (Mayer, Salovey, & Caruso, 2000, p. 396). Despite a common definition, some researchers model EI in different ways, with some arguing that EI is a kind of intelligence, meaning it is a set of related abilities like reasoning, problem-solving, and the processing of information (Mayer, Caruso, & Salovey, 1999) while others describe EI as a set of competencies or Emotional and Social Competencies (ESC), which are competencies that are clearly linked to EI (i.e., the perception, expression, understanding, and regulation of emotion in oneself and others). Cherniss (2010, p. 116) believes that there will always be a gray area around EI, however there he proposes one view of EI that encompasses multiple perspectives, “

that the core EI abilities, such as emotional perception, provide the foundation for emotional and social competencies such as ‘‘influence’’ or ‘‘stress tolerance.’’

 

Another concern amongst scholars is the validity of EI measures. Cherniss (2010) proposes that measures of EI can be divided into different categories: ability tests, self-report measures, and alternative measures. Amongst these categories of tests, Cherniss believes the MSCEIT (an ability test) has the strongest support for content validity and reliability, the Schutte’s self-report emotional intelligence test (SREIT) has high reliability (amongst self report tests), and multi-rater or “360” assessments are a promising alternative to these self-report and ability measures. While some of the EI tests are supported in the literature, there are several limitations including weak discriminant and divergent validity. Thus, Cherniss (2010) believes that new measures should be developed that take into account the context in which they will be used. Cherniss proposes that researchers and practitioners should consider more ecologically valid, behavior-based assessment strategies such as assessment centers, event-based interviews, and role-plays.

 

Finally, Cherniss (2010) discusses complications related to outcomes of EI and ESC. Recent research suggests that EI is positively associated with job performance. One study found a correlation of .43 between company rank and EI, and a correlation of .35 between merit salary increase percentage and EI as measured by the MSCEIT in a group of analysts and clerical employees (Lopes, Grewal, Kadis, Gall, & Salovey, 2006). However, Cherniss (2010) believes that, in many situations, certain ESCs may be stronger predictors of performance than EI. Further, social context is likely to moderate the relationship between EI or ESC and outcomes.

 

Selected Commentaries:

Kaplan, Cortina, and Ruark (2010) commend Cherniss for beginning to “disentangle the jumble” of models and definitions of EI. However, these authors criticize the general approach that has been taken by most IO psychologists in studying EI. They believe that much of the focus of EI, up to this point, has been on its predictive value, regardless of the outcomes it may or may not predict. They suggest a practical approach to studying EI by following an outcome-driven strategy. Instead of trying to determine ‘‘how well EI predicts,’’ a more useful strategy for organizational researchers will be to start with the outcome of interest and then work backwards to identify those particular socioemotional constructs that predict specific dimensions of that outcome. Their approach is outlined below:

 

Step 1: Carefully identify organizational phenomena and outcomes in which emotions and emotionally relevant processing are most relevant and impactful (like supportive leadership, participative decision making, etc).

 

Step 2: Explicitly define and map out the dimensionality of that outcome. Researchers of EI should (a) make distinctions among the particular components of EI, (b) make distinctions among the specific types or dimensions of the outcome domain, and (c) consider the moderating role of contextual factors.

 

Step 3: Identify the predictor variables that are most likely to explain or account for the specific dimensions of the outcome of interest. Kaplan et al (2010) agree with Cherniss who argued that focusing on any one definition or conceptualization of EI, to the exclusion of other important socioemotional variables, is likely to result in a failure to appropriately capturing all relevant predictors, thereby resulting in a less than optimal prediction of organizational outcomes.

 

Antonakis and Dietz (2010) agree with Cherniss that emotions are important for many organizational phenomena, however, they disagree with Cherniss regarding the incremental validity (or lack thereof) of EI and ESC over and above IQ (general intelligence) and personality tests. Antonakis and Dietz (2010) also raise concerns regarding Cherniss’s take on EI and ESCs:

 

They believe that there are important conceptual problems in both the definition of ESC and the distinction of ESC from EI, (b) that Cherniss’s interpretation of neuroscience findings as supporting the constructs of EI and ESC is outdated, and (c) that his interpretation of the famous marshmallow experiment as indicating the existence of ESCs is flawed.

 

In summary, Antonakis and Dietz (2010) generally believe that there is not considerable support for many of Cherniss’s arguments about EI. They feel that the only way EI research can move forward successfully would be to commit firmly to the ability definition of EI (e.g, Mayer, Caruso, & Salovey, 2000) and its consequences—then there is no need to include ESCs as they may unnecessarily complicate our understanding of EI.

 

Focal article:

Cherniss, C. (2010). Emotional intelligence: Toward clarification of a concept. Industrial and Organizational Psychology: Perspectives on Science and Practice, 3, 110–126.

Commentaries:

Antonakis, J.& Dietz, J. (2010). Emotional Intelligence: On Definitions, Neuroscience, and Marshmallows, Industrial and Organizational Psychology: Perspectives on Science and Practice, 3, 165-170.

Kaplan, S., Cortina, J. & Ruark, G. (2010). Oops. . . . We Did It Again: Industrial Organizational’s Focus on Emotional Intelligence Instead of on Its Relationships to Work Outcomes. Industrial and Organizational Psychology: Perspectives on Science and Practice, 3, 171–177.

 

Citations:

Lopes, P. N., Grewal, D., Kadis, J., Gall, M., & Salovey, P. (2006). Evidence that emotional intelligence is related to job performance and affect and attitudes at work. Psichothema, 18, 132–138.

Mayer, J. D., Caruso, D. R., & Salovey, P. (1999). Emotional intelligence meets traditional standards for an intelligence. Intelligence, 27, 267–298.

Mayer, J. D., Salovey, P., & Caruso, D. R. (2000). Models of emotional intelligence. In R.J. Sternberg (Ed.), Handbook of intelligence (2nd ed., pp. 396–420). New York: Cambridge University Press.

 

What Makes for a Successful Employee and Why?

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Topic: Job Performance, Personality
Publication: Journal of Occupational and Organizational Psychology (MAR 2010)
Article: Human capital and objective indicators of career success: The mediating effects of cognitive ability and conscientiousness
Authors: T.W.H. Ng and D.C. Feldman
Reviewed By: Benjamin Granger

Career success is important for determining an employee’s well-being, life satisfaction, and can also contribute to organizational success.  While it is well known that an employee’s level of education and work experience influences his/her career success, Ng and Feldman suggest that why this relationship exists is unclear.

According to Ng and Feldman, education and work experience are indicators of an employee’s human capital (i.e., competencies possessed by employees that positively influence performance).  Such indicators of human capital signal to organizations that employees/job applicants posses valued competencies and will likely be successful on the job.

In a recent meta-analysis, Ng and Feldman argue that education can actually increase employees’cognitive ability which in turn enhances job performance. They argue further that work experience and attaining a high level of formal education leads employees to develop better work habits (i.e., become more conscientious) which is also a well known predictor of job performance.

Ng and Feldman’s results suggest that these indicators of human capital directly and positively influence objective indicators of employee career success (salaries and promotions).  However, investments in human capital development also appear to increase employee cognitive ability and conscientiousness and thus affect career success indirectly as well.

Caution: While Ng and Feldman argue that education and work experience lead to cognitive ability and conscientiousness, the opposite could also be the case.  This would suggest that smarter and more conscientious people seek out more education and tend to stay with their organizations longer which is also quite plausible and probably true to some degree.

These results lend support to the common practice of screening job applicants based on their education and work experiences prior to testing and/or interviewing.  This initial step can save significant time and money and can effectively screen out applicants that do not possess the human capital necessary for successful job performance.  Ng and Feldman also suggest that organizations make “tradeoffs” between work experience and education since applicants who attend school longer have fewer opportunities to gain work experience.  Weeding out applicants with high levels of education because they do not possess certain work experiences may be cutting applicants who DO possess the necessary human capital for good performance.

Ng, T. W. H., & Feldman, D. C. (2010). human capital and objective indicators of career success: the mediating effects of cognitive ability and conscientiousness . Journal of Occupation and Organizational Psychology, 83, 207-235.

Why Work Group Satisfaction Matters

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Topic: Employee Satisfaction, Job Performance, Teams
Publication: Personnel Psychology (SPRING 2010)
Article: Satisfaction, citizenship behaviors, and performance in work units: A meta-analysis of collective construct relations
Authors: D.S. Whitman, D.L. van Rooy, and C. Viswesvaran
Reviewed By: Benjamin Granger

The happy worker is the productive worker, right?  Not necessarily.  Indeed, much of the past research on job satisfaction (which is extensive, to say the least) suggests that at the individual employee level, job satisfaction and performance are weakly related.  This finding, however, tends to go against common sense.  Doesn’t it seem reasonable to believe that employees who are satisfied at work perform better than those who are not as satisfied or dissatisfied at work?  It apparently does to many researchers and thus the search for clarification continues.

A recent meta-analysis by Whitman, van Rooy and Viswesvaran (2010) suggests that while the relationship between satisfaction and performance may be weak at the individual level, satisfaction may still be important for predicting performance when measured at the work group/unit level.  In other words, Whitman et al. hypothesized that work units with more satisfied employees may tend to outperform work units with less satisfied employees. It is important to mention that work unit-level satisfaction represents an aggregate of the group members’ levels of job satisfaction.  That is, every group member plays an important role in determining the satisfaction level of the work unit.

As the authors also note, there are a number of performance indicators (i.e., productivity, customer satisfaction, withdrawal behaviors, Organizational Citizenship Behaviors (OCBs)) that can be meaningfully measured at the work unit level.

Whitman et al.’s results suggest that job satisfaction at the work unit level is, in fact, important for predicting a variety of performance indicators.  And importantly, the relationships tend to be stronger than those found in past research measuring these outcomes at the individual employee level.  Specifically, work units with satisfied employees are more productive, engage in more OCBs, and receive higher customer satisfaction ratings than work groups with less satisfied group members. Moreover, satisfied work units have lower rates of turnover and absenteeism.

So while the satisfied employee may not necessarily be the productive employee, the satisfied work group does seem to be the more productive unit!

Whitman, D.S., van Rooy, D.L., & Viswesvaran, C. (2010). Satisfaction, citizenship behaviors, and performance in work units: A meta-analysis of collective construct relations. Personnel Psychology, 63, 41-81.

Predicting Job Performance with Implicit Words Games?

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Topic: Personality, Measurement, Job Performance
Publication: Personnel Psychology (SPRING 2010)
Article: We (sometimes) know not how we feel: Predicting job performance with an implicit measure of trait affectivity
Authors: R.E. Johnson, A.L. Tolentino, O.B., Rodopman, and E. Cho
Reviewed By: Benjamin Granger

In the world of emotions, trait affect refers to the predisposition some people have to generally experience positive or negative emotions.

Trait affect is often broken up into Negative Affect (NA) and Positive Affect (PA). While high levels of NA are associated with negative emotions such as fear and anxiety, high levels of PA are associated with positive emotions such as excitement and joy.  It should not come as a surprise that PA tends to relate favorably to work performance whereas the opposite is true for NA.

Recently, Johnson, Tolentino, Rodopman, and Cho (2010) suggested that because trait affect (e.g., PA & NA) operates outside of employees’ conscious awareness, it is more appropriate to measure it at the unconscious or implicit level.  This is in stark contrast to the self-report, explicit measurement of trait affect that is typically used when explicitly asking people to rate the extent to which they feel certain emotions across many different situations.

But how in the heck would you measure trait affect implicitly?  Johnson et al. used a word completion task that presented word fragments to employees for which they were required to complete to create a meaningful English word.  The following are actual examples of word fragments used by Johnson and colleagues:

F E _ _ (NA = FEAR, or neutral = FEEL, FEED) S M _ _ _ (PA = SMILE, or neutral = SMART, SMOKE)

A person’s level of trait NA and PA were determined by the relative amount of NA-related and PA-related word fragments completed by employees, respectively.  But, don’t worry if you are a bit skeptical; this is not exactly your everyday personnel survey!

Nevertheless, Johnson and colleagues conducted two independent pilot studies that supported the validity of their word fragment approach. Ultimately, Johnson and colleagues demonstrated that implicit measures of trait affect are important predictors of task performance, organizational citizenship behaviors (OCBs) and counterproductive work behaviors (CWBs), even more so than the conscious/explicit measures that we are more accustomed to. Johnson et al.’s study highlights an interesting way to measure employees’ predispositions to experience positive and negative emotions.

Moreover, while employees can easily misrepresent themselves on explicit personality measures, this is likely not possible for implicit measures.

Johnson, R.E., Tolentino, A.L., Rodopman, O.B., & Cho, E. (2010). We (sometimes) know not how we feel: Predicting job performance with an implicit measure of trait affectivity. Personnel Psychology, 63 (1), 197-219.

 

Can Personality Lead to Better Performance?

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Topic: Motivation, Personality, Job Performance
Publication: Personality and Individual Differences (MAR 2009)
Article: Using a two-factor theory of achievement motivation to examine performance-based outcomes and self-regulatory processes.
Authors: Story, P.A., Hart, J.W., Stasson, M.F., & Mahoney, J.M.
Reviewed By: Samantha Paustian-Underdahl

Have you ever wondered why some employees seem to find it easier to achieve their organizational goals than others? Current research proposes that theories of achievement motivation can explain some of  these employee differences. Achievement motivation refers to the tendency to set and work toward personal goals and/or standards (Cassidy & Lynn, 1989). It can be broken down into two motivational factors: intrinsic achievement motivation (IAM) and extrinsic achievement motivation (EAM) (Ryan & Deci, 2000). While researchers agree that achievement motivation is a complicated concept, many disagree about how it differs amongst employees.

Researchers debate how individuals who are intrinsically or extrinsically motivated may differ in their self-regulation and in their need for learning. In the current study, Story, Hart, Stasson, and Mahoney (2009) examined 340 college students in order to look into these two issues. They found that IAM scores were positively related with scores on the Need for Cognition scale. Thus, greater levels of intrinsic motivation were associated with a higher need for cognition.

It seems that employees who are  intrinsically motivated may be more interested in mastering skills and learning new material than in simply meeting a goal or competing with coworkers. On the other hand, EAM was not significantly related to need for cognition. The authors believe that rather than being motivated by learning, extrinsically motivated employees may be motivated by competition and external rewards.

The authors also found that IAM was positively related to frequency of self-regulation, showing that those with higher levels of intrinsic motivation reported higher levels of self-regulation. However, there was no significant correlation between EAM and frequency of self regulation.  Extrinsically motivated employees may need a greater push from management (e.g., rewards, deadlines, regulation) in order to successfully reach their goals.

The take-away here is that depending on the type of motivation an employee has, and the kinds of organizational policies and practices in place, an employee may find it more or less difficult to work towards achieving their goals. Intrinsically motivated employees will naturally be compelled to learn and master organizational skills and tasks. They will probably not be motivated by deadlines or external rewards. On the other hand, extrinsically motivated employees are more likely to succeed in competitive environments in which they have deadlines and are closely regulated by supervisors. Intrinsically motivated employees however, may be more successful in environments where they can independently regulate their goal-attainment strategies.

Story, P.A., Hart, J.W., Stasson, M.F., & Mahoney, J.M. (2009). Using a two-factor theory of achievement motivation to examine performance-based outcomes and self-regulatory processes. Personality and Individual Differences, 46, 391-395.

SJTs: They’re Not Perfect, but Gosh Darn it they Work!

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Topic: Selection
Publication: Human Performance ( JAN 2010)
Article: Contextual effects on SJT responses: An examination of construct validity and mean differences across applicant and incumbent contexts
Authors: W.I. MacKenzie, R.E. Ployhart, J.A. Weekley, and C. Ehlers
Reviewed By: Benjamin Granger

A situational judgment test (SJT) is a commonly used employee selection tool which presents job applicants with realistic work situations. Job applicants are required to choose from several response options, which range in their effectiveness (as rated by subject matter experts).  While SJTs tend to predict future job performance rather well, there is still debate as to what SJTs actually measure (SJTs correlate with and likely measure cognitive ability, personality, job knowledge, and experience simultaneously) and how they operate in different contexts (e.g., job applicants vs. incumbents).

To further investigate the validity of SJTs, MacKenzie et al. (2010) addressed a few major issues common in SJT research. For example, much of the existing research on SJTs relies on samples of job incumbents.  However, SJTs are most frequently used in new employee selection and the authors speculate that the knowledge, skills, and abilities of incumbents may differ significantly from that of job applicants.  In other words, SJTs may operate differently for job incumbents and applicants.

Impressively, MacKenzie et al. collected SJT data from applicant and incumbent samples from six different organizations, arriving at a total sample of over 40,000 people. Because the SJTs were  tailored to the individual organizations using them, six different SJTs were employed. However, all six were similarly designed (Each situation was accompanied by five response options and participants chose the “best” and “worst” responses).

For all six organizations, job incumbents tended to have higher SJT scores than applicants. More importantly, the findings suggest that SJTs do function differently for job applicants and incumbents.  For all six organizations, cognitive ability was more strongly related to SJT scores for job incumbents than for applicants.

MacKenzie et al.’s findings suggest that practitioners should take care when interpreting the results of SJT research conducted on job incumbents, especially if the SJTs are intended for use in new employees in selection settings.  Nevertheless, SJTs enhance our ability to make predictions about future job performance and are even known to reduce adverse impact against racial minorities, which is a common by product of using pure cognitive ability tests in selection.

MacKenzie, W.I., Ployhart, R.E., Weekley, J.A., & Ehlers, C. (2010). Contextual effects on SJT responses: An examination of construct validity and mean differences across applicant and incumbent contexts. Human Performance, 23(1), 1-21.MacKenz

Do Optimistic Predictions Lead to Quicker Completion Times?

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Topic: Goals, Job Performance, Judgment
Publication: Organizational Behavior and Human Decision Processes (JAN 2010)
Article: Finishing on time: When do predictions influence completion times?
Authors: R. Buehler, J. Peetz, and D. Griffin
Reviewed By: Benjamin Granger

Past research has shown that human beings often underestimate the amount of time necessary for task completion (“I can finish this project by…”). This optimistic bias has been consistently demonstrated in many work-related settings and most of the research has focused on why this happens. However, a recent series of studies by Buehler, Peetz and Griffin (2010) investigated whether optimistic prediction times have the ability to improve actual completion times and if so, for what kinds of tasks?

Buehler et al. found that optimistic completion time predictions can have a positive impact on actual completion times, but it depends largely on the type of task/project. For instance, the effect of optimistic predictions on completion times appears to be more favorable when tasks can be completed in a single session (e.g., short computer tutorial, writing a memo) vs. when tasks require multiple steps to be completed at different time points (e.g., launching an employee engagement survey, filing a federal tax return – ugh!).

Interestingly, Buehler et al. also found that the tendency to underestimate completion times was more prevalent for tasks that require multiple sessions.

Ultimately, Buehler et al. concluded that optimistic completion time predictions can be useful for tasks/projects that require one shot. However, optimistic completion time predictions appear to have little power for tasks that require multiple sessions over multiple time points. Additionally, although predictions don’t always have a positive impact on completion times, they do to have a positive influence on task/project start times. Thus, Buehler and colleagues conclude that completion time predictions initiate action early on, but apparently lose their power over time, especially for longer tasks/projects that require many sessions or steps.

Buehler, R., Peetz, J., & Griffin, D. (2010). Finishing on time: When do predictions influence completion times? Organizational Behavior and Human Decision Processes, 111, 23-32.