We tested the longstanding belief that performance is a function of the interaction between cognitive ability and motivation. Using raw data or values obtained from primary study authors as input (k ...= 40 to 55; N = 8,507 to 11,283), we used meta-analysis to assess the strength and consistency of the multiplicative effects of ability and motivation on performance. A triangulation of evidence based on several types of analyses revealed that the effects of ability and motivation on performance are additive rather than multiplicative. For example, the additive effects of ability and motivation accounted for about 91% of the explained variance in job performance, whereas the ability-motivation interaction accounted for only about 9% of the explained variance. In addition, when there was an interaction, it did not consistently reflect the predicted form (i.e., a stronger ability-performance relation when motivation is higher). Other key findings include that ability was relatively more important to training performance and to performance on work-related tasks in laboratory studies, whereas ability and motivation were similarly important to job performance. In addition, statelike measures of motivation were better predictors of performance than were traitlike measures. These findings have implications for theories about predictors of performance, state versus trait motivation, and maximal versus typical performance. They also have implications for talent management practices concerned with human capital acquisition and the prediction of employee performance.
Drawing on the attraction-selection-attrition perspective, strategic human resource management (SHRM) scholarship, and recent human capital research, this study explores organization-level emergence ...of personality (i.e., personality-based human capital resources) and its direct, interactive, and (conditional) indirect effects on organization-level outcomes based on data from 6,709 managers across 71 firms. Results indicate that organization-level mean emotional stability, extraversion, and conscientiousness are positively related to organization-level managerial job satisfaction and labor productivity but not to financial performance. Furthermore, organization-level mean and variance in emotional stability interact to predict all three organization-level outcomes, and organization-level mean and variance in extraversion interact to predict firm financial performance. Specifically, the positive effects of organization-level mean emotional stability and extraversion are stronger when organization-level variance in these traits is lower. Finally, organization-level mean emotional stability, extraversion, and conscientiousness are all positively related to firm financial performance indirectly via labor productivity, and the indirect effects are more positive when organization-level variance in those personality traits is lower. Overall, the findings suggest that personality-based human capital resources demonstrate tangible effects on organization-level outcomes. Theoretical and practical implications of these findings are discussed along with study limitations and future research directions.
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Past research has not adequately considered the importance of interconnected human capital resources. Drawing on the resource-based view, we propose a dynamic model in which changes in generic human ...capital (personality and cognitive ability) lead to changes in unit-specific human capital (advanced training and experience), which in turn lead to changes in unit service performance behavior and effectiveness. We examined 238 units in a restaurant chain using data from different sources spanning ten quarters. The hypothesized causal sequence among the constructs was supported. These findings advance resource-based scholarship and highlight the value of understanding the relationships among human capital resources.
This article reviews 100 years of research on individual differences and their measurement, with a focus on research published in the Journal of Applied Psychology. We focus on 3 major individual ...differences domains: (a) knowledge, skill, and ability, including both the cognitive and physical domains; (b) personality, including integrity, emotional intelligence, stable motivational attributes (e.g., achievement motivation, core self-evaluations), and creativity; and (c) vocational interests. For each domain, we describe the evolution of the domain across the years and highlight major theoretical, empirical, and methodological developments, including relationships between individual differences and variables such as job performance, job satisfaction, and career development. We conclude by discussing future directions for individual differences research. Trends in the literature include a growing focus on substantive issues rather than on the measurement of individual differences, a differentiation between constructs and measurement methods, and the use of innovative ways of assessing individual differences, such as simulations, other-reports, and implicit measures.
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Leader-centric views of leadership tend to regard followers as passive recipients of leaders' influences. As such, researchers often control for follower characteristics (e.g., age, gender, ...organizational tenure) when examining relations between leadership behaviors and other variables. However, reversing-the-lens theory suggests that followers' characteristics represent substantive factors that may affect how they perceive their leaders or how leaders behave toward different followers. We conducted two studies to investigate this possibility. In Study 1, we meta-analyzed data from 479 primary studies (N = 172,494) and found meaningful relations between follower individual differences (e.g., gender, personality) and ratings of their leaders' behaviors (e.g., transformational leadership, abusive supervision). In Study 2, we conducted a primary study to estimate the extent to which actual leader behaviors or differences in follower perceptions of those behaviors account for these relations. Results suggest that follower perceptions and measurement error explain almost the same or more variance in follower ratings than do actual leader behaviors. In addition, other findings imply that relations between some follower characteristics (e.g., gender, neuroticism) and leadership ratings are likely to be due to perceptual differences associated with these follower characteristics. However, actual leader behaviors also appear to play a role, such that leaders tend to behave differently toward followers who possess high or low levels of certain characteristics (e.g., agreeableness). Taken together, this two-study investigation provides evidence that follower individual differences are related to ratings of leader behaviors and, thus, deserve more attention within leadership theory and research.
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Work effort has been a key concept in management theories and research for more than a century. Maintaining and increasing employee effort also is a persistent concern to managers. The goal of the ...present conceptual and meta-analytic review was to increase clarity and consensus regarding what effort is and how to measure it. First, we reviewed conceptualizations of effort and provided an integrated definition that views effort as a direct outcome of motivation that captures (a) what employees work on, (b) how hard they work, and (c) how long they persist in that work. Second, we identified four main ways researchers have operationalized effort and meta-analytically studied the effects of each operationalization on effort–job performance relationships. For example, measures that assessed multiple dimensions of effort (ρ = .37) tended to relate more strongly to performance than measures that focused on only one dimension (e.g., effort intensity) or on effort more generally (ρ = .18 to .29). Third, we developed and meta-analytically tested a nomological network to gain a better understanding of effort's antecedents (e.g., intrinsic motivation, ρ = .46; performance orientation, ρ = .12) and outcomes (e.g., job performance, ρ = .34; exhaustion, ρ = .04) as well as constructs that appear to overlap with effort (e.g., work engagement, ρ = .48; grit, ρ = .51). Finally, on the basis of our conceptual and meta-analytic reviews, we delineated an agenda for future research on this central, yet often misunderstood, construct.
Social media (SM) pervades our society. One rapidly growing application of SM is its use in personnel decision making. Organizations are increasingly searching SM (e.g., Facebook) to gather ...information about potential employees. In this article, we suggest that organizational practice has outpaced the scientific study of SM assessments in an area that has important consequences for individuals (e.g., being selected for work), organizations (e.g., successfully predicting job performance or withdrawal), and society (e.g., consequent adverse impact/diversity). We draw on theory and research from various literatures to advance a research agenda that addresses this gap between practice and research. Overall, we believe this is a somewhat rare moment in the human resources literature when a new class of selection methods arrives on the scene, and we urge researchers to help understand the implications of using SM assessments for personnel decisions.
Recent reports suggest that an increasing number of organizations are using information from social media platforms such as Facebook.com to screen job applicants. Unfortunately, empirical research ...concerning the potential implications of this practice is extremely limited. We address the use of social media for selection by examining how recruiter ratings of Facebook profiles fare with respect to two important criteria on which selection procedures are evaluated: criterion-related validity and subgroup differences (which can lead to adverse impact). We captured Facebook profiles of college students who were applying for full-time jobs, and recruiters from various organizations reviewed the profiles and provided evaluations. We then followed up with applicants in their new jobs. Recruiter ratings of applicants’ Facebook information were unrelated to supervisor ratings of job performance (rs = −.13 to –.04), turnover intentions (rs = −.05 to .00), and actual turnover (rs = −.01 to .01). In addition, Facebook ratings did not contribute to the prediction of these criteria beyond more traditional predictors, including cognitive ability, self-efficacy, and personality. Furthermore, there was evidence of subgroup difference in Facebook ratings that tended to favor female and White applicants. The overall results suggest that organizations should be very cautious about using social media information such as Facebook to assess job applicants.
A common belief among researchers is that vocational interests have limited value for personnel selection. However, no comprehensive quantitative summaries of interests validity research have been ...conducted to substantiate claims for or against the use of interests. To help address this gap, we conducted a meta-analysis of relations between interests and employee performance and turnover using data from 74 studies and 141 independent samples. Overall validity estimates (corrected for measurement error in the criterion but not for range restriction) for single interest scales were .14 for job performance, .26 for training performance, -.19 for turnover intentions, and -.15 for actual turnover. Several factors appeared to moderate interest-criterion relations. For example, validity estimates were larger when interests were theoretically relevant to the work performed in the target job. The type of interest scale also moderated validity, such that corrected validities were larger for scales designed to assess interests relevant to a particular job or vocation (e.g., .23 for job performance) than for scales designed to assess a single, job-relevant realistic, investigative, artistic, social, enterprising, or conventional (i.e., RIASEC) interest (.10) or a basic interest (.11). Finally, validity estimates were largest when studies used multiple interests for prediction, either by using a single job or vocation focused scale (which tend to tap multiple interests) or by using a regression-weighted composite of several RIASEC or basic interest scales. Overall, the results suggest that vocational interests may hold more promise for predicting employee performance and turnover than researchers may have thought.
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Meta-analysis has become a well-accepted method for synthesizing empirical research about a given phenomenon. Many meta-analyses focus on synthesizing correlations across primary studies, but some ...primary studies do not report correlations. Peterson and Brown (2005) suggested that researchers could use standardized regression weights (i.e., beta coefficients) to impute missing correlations. Indeed, their beta estimation procedures (BEPs) have been used in meta-analyses in a wide variety of fields. In this study, the authors evaluated the accuracy of BEPs in meta-analysis. We first examined how use of BEPs might affect results from a published meta-analysis. We then developed a series of Monte Carlo simulations that systematically compared the use of existing correlations (that were not missing) to data sets that incorporated BEPs (that impute missing correlations from corresponding beta coefficients). These simulations estimated ρ̄ (mean population correlation) and SDρ (true standard deviation) across a variety of meta-analytic conditions. Results from both the existing meta-analysis and the Monte Carlo simulations revealed that BEPs were associated with potentially large biases when estimating ρ̄ and even larger biases when estimating SDρ. Using only existing correlations often substantially outperformed use of BEPs and virtually never performed worse than BEPs. Overall, the authors urge a return to the standard practice of using only existing correlations in meta-analysis.
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