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This study introduces the use of practice employment tests during recruitment as a tool with the potential to improve outcomes for both an organization and its (potential) applicants during personnel selection. Synthesizing research on recruitment, selection, job search, adverse impact, signaling theory, and human capital theory, we propose that practice tests reduce information asymmetry regarding the nature of an organization's assessment procedures, thereby acting as short-term human capital investment opportunities. Using a large sample of potential applicants and applicants who later decided to apply for jobs within a professional occupation in a large organization, we demonstrate that (a) those who took the practice tests scored higher on the actual tests; (b) score gains between practice tests and actual tests were greater for Blacks and Hispanics when compared to Whites; (c) the practice test exhibited a self-selection effect, encouraging those with higher scores to apply; and (d) score gains between practice tests and actual tests were similar to scores observed for those retesting on the actual tests. These findings suggest practice tests may be capable of simultaneously enhancing organizational outcomes (e.g., increased quality of applicants, reduced cost of testing unqualified applicants, and reduced adverse impact) and applicant outcomes (e.g., increased human capital, increased chances of eventual employment, and reduced disappointment and wasted effort from unsuccessful application). (PsycINFO Database Record (c) 2019 APA, all rights reserved).

Research on transactive memory systems (TMS) has been conducted in a variety of teams, a range of task types and increasingly, in settings around the world. Despite this proliferation, there has been relative inattention to contextual factors that produce TMS and explain heterogeneity in the TMS to team performance relationship. TMS studies are typically conducted in homogeneous settings (i.e., teams located in a single country) and often with sources of potential variation (i.e., environmental volatility, leadership, team human capital, and diversity) in TMS development controlled. Collating these individual studies, we use meta-analytic techniques to illuminate key contextual factors that may shape TMS and influence the TMS-performance association. Using 76 empirical studies representing 6,869 sampling units, we find that the strength of the TMS to performance relationship varies, depending on features of the national cultural context-the impact of TMS is stronger in cultural contexts where power distance and in-group collectivism are higher. Our results also suggest that environmental volatility, leadership effectiveness, and team human capital are positively associated with TMS, and informational and gender diversity are negatively associated with TMS development. Our findings also indicate fruitful areas for future research specifically aimed toward disentangling the effects of environmental, team, and national cultural context on TMS and team performance. (PsycINFO Database Record (c) 2019 APA, all rights reserved).

[Correction Notice: An Erratum for this article was reported in Vol 102(5) of Journal of Applied Psychology (see record 2017-14296-001). In the article, the following headings were inadvertently set at the wrong level: Method, Participants and Procedure, Measures, Occupation specific human capital, Symbolic jobs, Relevant majors, Occupation-specific capital hotspots, Source timing, Source diagnosticity, Results, and Discussion. All versions of this article have been corrected.] This study proposes that reaching applicants through more diagnostic recruitment sources earlier in their educational development (e.g., in high school) can lead them to invest more in their occupation-specific human capital (OSHC), thereby making them higher quality candidates. Using a sample of 78,157 applicants applying for jobs within a desirable professional occupation in the public sector, results indicate that applicants who report hearing about the occupation earlier, and applicants who report hearing about the occupation through more diagnostic sources, have higher levels of OSHC upon application. Additionally, source timing and diagnosticity affect the likelihood of candidates applying for jobs symbolic of the occupation, selecting relevant majors, and attending educational institutions with top programs related to the occupation. These findings suggest a firm's recruiting efforts may influence applicants' OSHC investment strategies. (PsycINFO Database Record, ((c) 2017 APA, all rights reserved).)

[Correction Notice: An Erratum for this article was reported in Vol 101(7) of Journal of Applied Psychology (see record 2016-32115-001). In the article the affiliations for Emily D. Campion and Matthew H. Reider were originally incorrect. All versions of this article have been corrected.] Emerging advancements including the exponentially growing availability of computer-collected data and increasingly sophisticated statistical software have led to a "Big Data Movement" wherein organizations have begun attempting to use large-scale data analysis to improve their effectiveness. Yet, little is known regarding how organizations can leverage these advancements to develop more effective personnel selection procedures, especially when the data are unstructured (text-based). Drawing on literature on natural language processing, we critically examine the possibility of leveraging advances in text mining and predictive modeling computer software programs as a surrogate for human raters in a selection context. We explain how to "train" a computer program to emulate a human rater when scoring accomplishment records. We then examine the reliability of the computer's scores, provide preliminary evidence of their construct validity, demonstrate that this practice does not produce scores that disadvantage minority groups, illustrate the positive financial impact of adopting this practice in an organization (N ∼ 46,000 candidates), and discuss implementation issues. Finally, we discuss the potential implications of using computer scoring to address the adverse impact-validity dilemma. We suggest that it may provide a cost-effective means of using predictors that have comparable validity but have previously been too expensive for large-scale screening. (PsycINFO Database Record, ((c) 2016 APA, all rights reserved).)