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Personnel Selection
Chapter · April 2017
DOI: 10.1093/acrefore/9780190236557.013.8
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Summary and Keywords
Personnel selection is one of the most critical processes in the study of human work
behavior because it determines the efficacy of many other issues of human resource
management (e.g., training, productivity, and culture). From this perspective, personnel
selection is a process of decision-making, and its main objective is to predict the future
performance of potential employees. In order to achieve this objective, personnel
selection identifies the individual requirements of job performance and uses a variety of
assessment procedures, including cognitive ability tests, personality inventories,
interviews, job knowledge tests, situational judgment tests, job experience, work sample
tests, assessment centers, biodata, and reference checks. Using the best combination of
predictors, currently, scientific personnel selection is capable of predicting and
explaining over 60% of job performance variance based on individual differences.
Keywords: personnel selection, validity, job performance, contextual performance, counterproductive behavior at
work, cognitive test, personality, assessment centers, applicant reactions, combining predictors
Personnel selection is one of the most critical processes in the study of human work
behavior because it determines the efficacy of many other issues of human resource
management (Guion, 1998; Salgado, Viswesvaran, & Ones, 2001). Personnel selection is
used by organizations to decide which of the applicants for a job is the most appropriate
for a particular position. In this sense, it is a decision-making process about the suitability
of the candidates (Salgado & Moscoso, 2008).
As a scientific discipline, it began around 1900, when the principles and methods of
psychology were applied to personnel decisions in Europe and the United States
(Salgado, Anderson, & Hülsheger, 2010; Vinchur & Koppes Bryan, 2012). To this regard, as
Vinchur and Koppes Bryan (2012) noted, the advances in the area are intimately tied to the
advances in assessment and measurement procedures and in statistical developments.
This applied process requires carrying out several steps. First, an analysis of the job must
be done in order to ascertain the specific characteristics of the position (e.g., tasks and
Personnel Selection
Jesús F. Salgado
Subject: Industrial and Organizational Psychology Online Publication Date: Mar 2017
DOI: 10.1093/acrefore/9780190236557.013.8
Oxford Research Encyclopedia of Psychology
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duties). The second step involves identifying the specific individual requirements (e.g.,
cognitive abilities, job knowledge, skills, personality, experience, and other
characteristics) needed for carrying out efficiently specified tasks and duties. This
information is typically obtained through job analysis (García-Izquierdo, Díaz-Vilela, &
Moscoso, 2015; Pearlman & Sanchez, 2010; Sanchez & Levine, 2012). Sometimes, these
individual characteristics are called competencies (e.g., Schippman et al., 2000). The third
step determines the degree to which candidates meet the individual requirements
identified in step 2. In other words, candidates are evaluated using a variety of
assessment procedures (e.g., cognitive test, job knowledge test, interview, assessment
center, among others) to estimate their proficiency in requirements. Finally, the data
collected can be used to predict future organizational behavior (e.g., job performance,
training proficiency, turnover, promotions, career success, leadership potential, and
many others). These organizational behaviors are typically named criteria. Therefore,
personnel selection is a predictive process consisting of two kinds of variables: (a)
predictors, that is, the assessment procedures; and (b) criteria, that is, the employee’s
behavior and the outcomes the organization seeks to obtain.
Nevertheless, we should not overlook that candidates also make decisions, that is,
together with the organizational perspective, the candidate perspective must also be
considered (e.g., the applicant perceptions and reactions), regarding the hiring process
(Anderson, Born, & Cunningham-Snell, 2001; Anderson, Salgado, & Hülsheger, 2010).
This article reviews and summarizes the research literature on personnel selection and is
organized into four main sections. The first section examines the different approaches to
personnel selection. The second section reviews the most relevant assessment
procedures according to their psychometric properties. Consequently, in the second
section, the validity of cognitive ability tests, personality inventories, interviews, job
knowledge tests, work sample tests, assessment centers, and other procedures are
summarized. The third section reviews applicant perceptions and reactions. The fourth
section presents the issue of combining data from different predictors (i.e., multiple
prediction, incremental validity) to optimize efficacy. Finally, conclusions are provided.
Performance Measurement and Approaches to
Personnel Selection
What is to be predicted? What behaviors and outcomes are relevant for organizations and
candidates? Based on what we know currently about the procedures used in hiring
decisions, these are probably the most crucial questions for an effective personnel
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selection process. These two questions underscore the issue of performance
measurement on the one hand, and the perspectives on the selection process on the
other.
For a century, it was believed that the aim of personnel selection was to predict overall
job performance and that overall job performance was a single entity, whether assessed
using a single global dimension or as a composite of multiple dimensions (Salgado, 2015;
Schmidt, Hunter, & Ones, 1992). However, today we know that some assessment
procedures can predict some performance-related behaviors and outcomes (e.g., task
performance) very efficiently but they are poor predictors of other performance-related
behaviors (e.g., contextual performance, counterproductive work behaviors, leadership
potential, and so on). Thus, the first step in personnel selection is to determine the
performance criteria for the future employees.
There is currently a large consensus among researchers that the job performance domain
includes at least three main subdomains: task proficiency, contextual (citizenship)
performance, and counterproductive performance. Task performance is defined as the
proficiency with which employees perform core technical activities that are relevant for
the job (Borman, Bryant, & Dorio, 2010). Task performance can be subdivided into
individual performance and work-team performance. Contextual performance (also called
citizenship performance) relates to the contributions of the employee to the
organizational, social, and psychological environment to help to accomplish
organizational goals (Borman et al., 2001; Dorsey, Cortina, & Luchman, 2010; Hoffman &
Dilchert, 2012). Empirical evidence has shown that there is some degree of
interrelationship among the three subdomains (Conway, 1996). Contextual performance
has been subdivided into two narrower dimensions: interpersonal performance and job
dedication (Van Scotter & Motowidlo, 1996). Counterproductive performance has been
defined as any intentional behavior of an employee viewed by the organization as
contrary to its legitimate interests (Sackett & De Vore, 2001, p. 145). Two further
subdimensions of counterproductive performance have been identified, that is, a
subdimension related to interpersonal counterproductive behaviors, for example, abusive
supervision, aggression, bullying; and a subdimension related to organizational
counterproductive behaviors, for example, hurts, voluntary absenteeism, low effort
(Hoffman & Dilchert, 2012; Rotundo & Spector, 2010). There is also meta-analytic evidence
that, after controlling for halo error and reliability, there is a general factor in job
performance rating (Viswesvaran, Schmidt, & Ones, 2005). This factor explained 60% of
the total variance. With regard to the interrater reliability of job performance ratings, .52
is the average value found in independent meta-analytic studies for overall job
performance (Salgado, IN PRESS; Salgado et al., 2003B; Salgado & Moscoso, 1996;
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Viswesvaran, Ones, & Schmidt, 1996). Figure 1 represents the performance domain and its
dimensions and subdimensions.
In addition to criterion, a
further issue to be
appraised refers to the
theoretical traditions
related to personnel
selection. Several authors
have identified two main
perspectives in personnel
selection (Anderson,
Lievens, van Dam, & Ryan,
2004; Anderson, Salgado,
Schinkel, & Cunningham-Snell, 2008; Schuler, 1993). The first perspective is the
predictivist, which in essence aims to establish the person-job fit. According to this
perspective, selection procedures are predictors of future job performance, and
candidates are seen as “subjects” to selection procedures. The second perspective is
constructivist, emphasizing that candidates, as well as organizations, make decisions in
personnel selection. According to Anderson and his colleagues, the constructivist
perspective sees selection as an opportunity for information exchange and to explore if a
future working relationship would be viable. Therefore, from the constructivist
perspective, personnel selection focuses not only on ensuring person-job fit but also
person-organization fit and team-organization fit. In this context, person-organization fit
is conceptualized as the adjustment between the candidate’s values and the
organizational values and culture, whereas person-team fit is conceptualized as the
adjustment between the candidate’s competencies, attitudes, and abilities, and the
immediate working environment of the group. The constructivist perspective is closely
related to the Attraction-Selection-Attrition (ASA) paradigm (Schneider, 1987; Schneider,
Goldstein, & Smith, 1995). According to the ASA paradigm, “the people make the place.”
This means that the attributes of employees (e.g., abilities and personality) are the most
relevant factors of job performance and that candidates are differentially attracted to
jobs. On their part, organizations try to select employees they see compatible with
organizational culture and climate and that can be compatible for a number of different
jobs. Over time, employees who do not fit in well are more likely to leave. The
consequence of this process is a homogenization of employees’ characteristics who work
at the organization.
Click to view larger
Figure 1. Dimensional Structure of Job Performance
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Personnel Selection Procedures
Regardless of which selection approach is used, that is, the predictivist or the
constructivist perspective, the appropriateness of the hiring decision will depend upon
the criterion-related validity of assessment procedures used for making decisions. As for
recent estimates on the criterion-related validity of the procedures most commonly used
in practice, the following sections will report the validity estimates provided for the most
robust studies of validity generalization, based on the psychometric meta-analysis
methods of Hunter and Schmidt (2004; Schmidt & Hunter, 2014). In all likelihood,
psychometric meta-analysis has been the most significant methodological development in
work and organizational psychology and in personnel selection for the last 40 years.
Psychometric meta-analysis can be defined as a quantitative integration of multiple
research results that correct measurement error, sampling error, and several other
artifactual errors, providing the most robust estimate of the operational validity of
selection procedures.
Several comprehensive reviews of the validity of personnel procedures have been
published in the last 15 years (e.g., Salgado & Moscoso, 2008; Salgado, Viswesvaran, &
Ones, 2001; Schmidt & Hunter, 1998). The current review will focus on the procedures most
commonly used in practice, and on the most recent criterion-related validity evidence.
Selection procedures can be classified by two types: procedures for assessing constructs
and procedures that are assessment methods (Hunter & Hunter, 1984). The main
difference between a construct and an assessment method resides in the fact that the
latter consists in grouping several constructs or measures. In other words, an assessment
method is an aggregate of other variables. More recently, assessment procedures have
been classified in terms of reflective measures and formative measures (Edwards &
Bagozzi, 2000). The first type of measures includes the procedures for assessing constructs
(e.g., cognitive test, job experience, and personality inventories), and the second type of
measures are the assessment methods (e.g., interviews, situational judgment tests, and
assessment centers). Using Hunter and Hunter’s (1984) and Edwards and Bagozzi’s (2000)
classifications as the basis for subdividing the different procedures, the criterion-related
validity of the personnel procedures is presented in two subsections.
Criterion-Related Validity of Reflective-Assessment (Constructs)
Procedures
The findings of the meta-analyses are summarized in Table 1, which shows the estimate of
operative validity for the most common reflective procedures used in personnel selection
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for predicting overall job performance. It should be noted that the operative validity was
estimated using the correlation between a predictor and a criterion after correction of
artifactual errors. Typically, the observed correlation is corrected for measurement error
in the criterion measure, and range restriction in the predictor.
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Table 1. Operational validity estimates of reflective-assessment procedures
Criterion Procedure Validity
Overall Job Performance General Cognitive Ability .62
Numerical Ability .52
Spatial Ability .51
Perceptual Ability .52
Verbal Ability .38
Memory .56
Conscientiousness .39
Emotional Stability .20
Extroversion .12
Openness .22
Agreeableness .16
Job Experience .25
Task Performance General Cognitive Ability .62
Conscientiousness .25
Emotional Stability .08
Extroversion .09
Openness .12
Agreeableness .10
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Job Experience .25
Contextual Performance General Cognitive Ability .24
Conscientiousness .32
Emotional Stability .16
Extroversion .22
Openness .03
Agreeableness .18
Overall Counterproductive Work Behavior General Cognitive Ability −.02
Conscientiousness −.34
Emotional Stability −.15
Extroversion −.14
Openness .02
Agreeableness −.33
General and Specific Cognitive Ability Tests
General cognitive ability (GCA) can be defined as the capacity of a person to learn some
material rapidly and accurately in optimal conditions of instruction. Therefore, less time
taken and greater accuracy reflect greater GCA. There are several structural models of
cognitive ability, most of them consisting of a general cognitive ability and several
specific cognitive abilities (see Salgado, IN PRESS, for a comprehensive review). Among the
specific cognitive abilities most frequently used in personnel selection we find abstract
reasoning, spatial-mechanical reasoning, verbal reasoning, numerical reasoning,
perceptual ability, and memory; but there are many other specific abilities. For example,
the taxonomy of Fleishman and Reilly (1992) included inductive and deductive reasoning,
verbal fluency, selective attention, and vigilance, among others.
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Research on the criterion-related validity of cognitive ability measures in personnel
selection is divided in two main approaches (see Salgado, IN PRESS; Schmitt, 2014, for
exhaustive reviews). One approach contends that specific cognitive abilities do not add
validity beyond the validity of GCA. In contrast, the other approach sustains that specific
cognitive abilities can show incremental validity beyond GCA (e.g., Lang et al., 2010).
The meta-analytic findings across the globe obtained over the last 35 years have
demonstrated that (1) CGA tests or a combination of several specific cognitive ability
tests are the most valid predictor of overall job performance for all types of occupations
(Hunter, Schmidt, & Le, 2006; Salgado et al., 2003A; Schmidt, Oh, & Le, 2006), and that .62 is
the best estimate of operational validity; (2) The sizes of the estimates of criterion-related
operational validity are similar across countries (Salgado, IN PRESS; Salgado & Anderson,
2003); (3) Job complexity is an important moderator of the validity of cognitive ability tests
(Hunter & Hunter, 1984; Hunter et al., 2006; Salgado et al., 2003A; Schmidt et al., 2006); (4)
Specific cognitive tests are also valid predictors of overall performance, but their validity
is smaller than the GCA validity (Salgado et al., 2003B); (5) Cognitive tests are the most
valid predictors of task performance, but they are less valid for predicting contextual
performance, and they are not valid predictors of counterproductive work behavior
(Gonzalez-Mule et al., 2014); (6) Cognitive tests show evidence of ethnic differences but
they do not produce differential prediction (Berry et al., 2014).
Personality Inventories
The recent advances in the domain of personality at work have been largely due to the
use of a construct-oriented approach in which the Five Factor Model of personality has
become the preferred model for Work and Organizational Psychology researchers (Hough
& Ones, 2001). The seminal work by Barrick and Mount (1991), Hough (1992), and Tett et al.
(1991) was crucial for demonstrating that personality dimensions were relevant predictors
of overall job performance and, on the basis of this pioneering research, many studies
were conducted in the following years. Furthermore, many surveys conducted around the
world since the1950s have shown that practitioners typically included personality
measures in the personnel selection processes.
In the last 25 years, many hundreds of primary studies and dozens of meta-analyses have
examined the validity of personality measures as predictors in personnel selection. The
FFM proved to be a successful taxonomy for classifying the various measures included in
validity studies, and we now have a better understanding of the validity of the Big Five.
Based on the best meta-analytical data available, the following conclusions can be drawn:
(1) The taxonomy of the personality traits derived from the FFM has proved to be a very
useful framework for organizing the various single measures and is now accepted as the
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paradigm in the field. The use of this taxonomy allowed personnel selection researchers
to adequately respond to the concerns of Ghiselli (1966; Schmitt et al., 1984), Guion and
Gottier (1965), and Schmitt et al. (1984) regarding the lack of a widely accepted personality
model; (2) Conscientiousness is the best personality predictor of job performance and
counterproductive behaviors, and it has shown validity generalization across samples,
occupations, and countries. Operational validity of conscientiousness was found to be .39
when a quasi-ipsative forced-choice format was used (Salgado, Anderson, & Tauriz, 2015;
Salgado & Tauriz, 2014); (3) Emotional stability was the second most relevant personality
predictor of job performance and counterproductive work behaviors, (4)
Conscientiousness, emotional stability, and agreeableness are the most valid predictors
of overall counterproductive behaviors, interpersonally oriented counterproductive
behaviors, and organizationally oriented counterproductive behaviors (Berry et al.,
2007); (5) Conscientiousness, emotional stability, and agreeableness showed incremental
validity over GCA for predicting overall job performance (Salgado & De Fruyt, 2006); (6)
The format of the personality inventory is an important moderator of the criterion-related
validity of the Big Five dimensions, so that the validity increases dramatically when quasiipsative
forced-choice formats are used (Salgado, Anderson, & Tauriz, 2015; Salgado &
Tauriz, 2014); and (7) The facets of the Big Five do not show evidence of criterion-related
validity for predicting job performance when the validity of the factor is residualized
(Salgado et al., 2015; Salgado, Moscoso, & Berges, 2013).
With regard to the criterion-oriented personality scales (COPS), meta-analyses have
shown they were predictors of job performance and counterproductive behaviors. The
most researched COPS were integrity tests. Technically, these are compounds (i.e.,
formative procedures), but they are included here as they include personality constructs
only. The validity of personality-based integrity tests has been estimated at .37 for
predicting job performance, and .42 for overall counterproductive behaviors (Ones,
Viswesvaran, & Schmidt, 1993). The nomological net of these measures suggests
hypotheses for explaining why they predict job performance and counterproductivity.
Integrity tests have been found to mainly consist of conscientiousness, emotional
stability, and agreeableness (Ones et al., 1993; Ones & Viswesvaran, 2001). Thus, the joint
effect of these three basic personality dimensions explains the large validity of this
personality measure.
The conclusions of the cumulated research is that the Big Five personality dimensions are
important variables for predicting and explaining overall job performance, task
performance, contextual performance, and counterproductive work behaviors (see Judge
et al., 2013; and Salgado, Moscoso, & Anderson, 2013, for a review), and that personality
inventories measure variables that are not assessed by other selection methods, and
hence provide unique and non-overlapping variance for explaining the criterion space.
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Consequently, practitioners in personnel selection can confidently use them for making
personnel decisions.
Job Experience
In the practice of personnel selection, job experience is usually conceptualized as the
number of years of experience on the same or similar job (McDaniel, Schmidt, & Hunter,
1988). Therefore, the length of service is used as a proxy of the experience on the job.
Notwithstanding, this measure conveys no information on past performance of the job
(Schmidt & Hunter, 1998).
Schmidt and Hunter (1998) indicated that the average operational validity of job
experience was .25. In another meta-analysis, Schmidt, Hunter, and Outerbridge (1986)
found a nonlinear relationship between job experience and job performance. Job
performance increased linearly up to five years of job experience, and after that, the
relationship became increasingly horizontal. When the amount of job experience was five
years or less, the operational validity was .33 for predicting supervisory ratings of job
performance (Schmidt et al., 1986).
Criterion-Related Validity of Formative-Assessment (Methods)
Procedures
The findings of the meta-analyses for the most common formative measures used in
personnel selection are shown in Table 2, which includes the operational validity of three
types of employment interviews, work sample test, job knowledge test, situational
judgment test, assessment center, biodata, and reference checks.
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Table 2. Operational validity estimates of formative-assessment procedures
Criterion Procedure Validity
Overall Job Performance Behavioral Structured Interview .62
Conventional Structured Interview .37
Unstructured Employment Interview .20
Work Sample Test .33
Job Knowledge Tests .45
Situational Judgment Test .26
Assessment Center .37
Biodata .33
Reference Check .26
Employment Interview
In numerous surveys across many countries, the interview showed to be the most
extensively used procedure for personnel selection (Salgado et al., 2001). These surveys
show that practically all candidates must get through at least one interview during the
hiring process. For this reason, the employment interview can be considered the foremost
standard formative-assessment procedure.
Since 1984, a number of meta-analyses have examined both criterion-oriented validity as
well as construct validity evidence in the selection interview. Prior to 1984, several
narrative reviews on the empirical data regarding the reliability and validity of the
interview concluded that the employment interview was unreliable and that its validity
was practically zero (see Moscoso, 2000). The first meta-analysis of the criterion-related
validity of the interview (Hunter & Hunter, 1984) agreed with this conclusion and showed
that validity was very small (operational validity of .14). This raised the paradox that the
most commonly used procedure for predicting applicant’s job performance was incapable
of predicting it.
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However, research conducted during the last 25 years has shown that the selection
interview was not a single and unitary method. Employment interviews have been
classified using a twofold scheme of the structure and content of the questions (Salgado
& Moscoso, 2002). These authors found three main types of interviews: unstructured
interviews, conventional structured interviews, and behavioral structured interviews
(other classifications were suggested by Huffcut, Roth, & McDaniel, 1996; and McDaniel et
al., 1994). Unstructured interviews have no fixed format regarding the content of the
questions and the assessment of the answers. Conventional structured interviews ask the
same questions to the candidates and can rate the answers using the same form. The
majority of the questions of unstructured and conventional interviews focus on attitudes
and opinions (Janz, Hellervik, & Gilmore, 1986). The behavioral structured interview is a
category of interview that poses the following characteristics (Salgado & Moscoso, 2006):
(a) The questions are based on a job analysis, using typically the critical incident
technique; (b) The job analysis also serves to identifying the main job dimensions that
should be assessed with the interview; (c) The same questions are asked to all the
candidates; (d) The same procedure is used for all candidates; (e) In many cases, the
candidate answers are assessed using behavioral anchoring rating scales (BARS); (f) The
interviewer is previously trained in this technique; (g) The decision is made only when all
the candidates have been interviewed.
A meta-analysis of the nomological network of structured interviews found that
conventional structured interviews appeared to be mainly measuring general cognitive
ability and personality variables, that is, they focus on the intrinsic variables of the
applicants(Salgado & Moscoso, 2002). With regard to behavioral structured interviews,
these authors found that this type of interview mainly assessed job knowledge and job
experience. Consequently, this interview type seems to be concentrated on finding out
whether the applicant would perform well in the job.
Several meta-analyses have reported the criterion-related validity of employment
interviews (e.g., Huffcut & Arthur, 1994; McDaniel et al., 1994; Salgado, Gorriti, & Moscoso,
2007; Wiesner & Cronshaw, 1988). A meta-analysis of behavioral structured interviews
found an operational validity of .62 (Salgado & Moscoso, 2006). In comparison,
conventional structured interviews showed an operational validity of .35, and the
operational validity of the unstructured interviews was .20 (Huffcut, Roth, & McDaniel,
1996).
Work Sample Tests
Work sample tests can be defined as hands-on simulations of part or all of the job content
(Schmidt & Hunter, 1998). Work samples have been used extensively for selecting skilled
workers, but they have the limitation that they can only be used with candidates who
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already know the job. In other words, candidates do not need to be trained as they have
experience on the job.
The largest meta-analysis ever carried out on the criterion-related validity of work sample
tests for predicting job performance found operational validity was .33 (Roth, Bobko, &
McFarland, 2005). Roth and colleagues (2005) also examined the correlation between
general cognitive ability and work sample tests and found a correlation of .38, which
agrees with the correlation reported in a previous meta-analysis by Schmidt, Hunter, and
Outerbridge (1986).
Job Knowledge Test and Situational Judgment Test
As the term indicates, job knowledge tests are procedures for examining the extent to
which the candidate possesses the knowledge required for a particular job. This category
of tests can include at least two types of procedures: job knowledge tests and situational
judgment tests. Like the work sample tests, job knowledge tests can be used only for
experienced candidates (Schmidt & Hunter, 1998).
With regard to the operational validity of job knowledge tests, Hunter and Hunter (1984)
reported a coefficient of .48 for predicting overall job performance. For situational
judgment tests, McDaniel and colleagues (2001) reported an initial estimate of .34 for
predicting job performance; and, more recently, in a second and more comprehensive
meta-analysis McDaniel and his colleagues (2007) reported an operational validity of .26.
With regard to the correlation between job knowledge tests and GCA, Schmidt, Hunter,
and Outerbridge (1986) found a correlation of .48. In the case of the situational judgment
test, McDaniel et al. (2007) reported a correlation of .32 with GCA.
Assessment Centers
The assessment center method is a kind of job simulation that consists of a set of
different exercises aimed at assessing several job dimensions (e.g., problem solving,
interpersonal behavior, influence and persuasion, and so on). Another important
characteristic of the assessment center method is that different raters assess the
candidates. The assessment center can also include some traditional procedures such as
cognitive ability tests, personality inventories, and interviews, together with less
traditional procedures such as role-playing exercises, group discussion exercises, and inbasket
tests. This last procedure is probably the most frequent exercise of an assessment
center. It consists in presenting applicants with a set of memos, letters, telephone
messages, and so on, similar to those they would have to deal with in the actual job. The
individuals are asked to organize all this information, as they would be in the real job
situation.
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Several meta-analyses have been conducted to find the operational validity of overall
assessment ratings as well the operational validity of the ratings of the dimensions. The
seminal meta-analysis conducted by Gaugler et al. (1987) found an operational validity of .
36 for predicting job performance when an overall assessment rating (OAR) was used.
Twenty years later, Hermelin, Lievens, and Robertson (2007) found an operational validity
of .28. Recently, the operational validity of most of the standard exercises of assessment
centers, including oral presentations, in-basket tests, case analysis, leaderless group
discussions, and role play was found to range from .18 to .26 (Hoffman et al., 2015). Based
on these operational validities and in the intercorrelations among the exercises, the best
estimate of the operational validity of the OAR seems to be the score reported by Gaugler
et al. (1987).
Biodata
The biodata form consists of biographical data questions about the job and life
experiences of each candidate. These questions have been chosen because of their
correlation with job performance. Therefore, biodata are criterion-oriented procedures
that are empirically derived. In this sense, the construction of a biodata form is similar,
for instance, to the method used for the development of the main scales of the MMPI
(e.g., hysteria; psychopathy). Biodata forms can include questions such as early
experiences in the candidate’s first job, in high school, in college, in hobbies, and other
pursuits; but due to antidiscrimination legislation, they exclude questions about race,
age, marital status, and other forbidden issues in many countries (Schmidt & Hunter,
1998).
A meta-analysis carried out by Rothstein and her colleagues (1990) showed an operational
validity of .35 for predicting overall job performance and that the correlation with GCA is
moderately large, around .50. This last correlation suggests that biodata indirectly reflect
GCA, similarly as conventional structured interviews do.
Reference Check
This assessment method is used at the end of the selection process. Typically, it involves
collecting information on a candidate from previous employers. The literature reviews
suggest that reference checks are used similarly for high and low complexity jobs, and
that there are no significant differences related to the size of the company (ChamorroPremuzic
& Furnham, 2010; Lado, 2012). In the practice of personnel selection, both
reference check content and structure show a remarkable variety (Chamorro-Premuzic &
Furnham, 2010).
With regard to the operational validity of reference checks, Hunter and Hunter (1984)
found a coefficient of .26 for predicting overall job performance. Recently, the meta-
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analysis of Lado (2012) found reference checks correlated.25 with general cognitive ability
and .17 with job experience.
Applicant Perceptions and Reactions to
Selection Procedures
Research conducted since 1990 suggests that candidates have preferences regarding the
procedures used for making personnel decisions, and that such preferences can have
important consequences for organizational practices of personnel selection (Viswesvaran
& Ones, 2004). This research stems from two parallel lines. A first research line based on
the selection fairness model of Gilliland (1993; Steiner & Gilliland, 1996). This model
distinguishes between procedural justice and distributive justice. Procedural justice
refers to the fairness of the personnel selection processes. Distributive justice refers to
the fairness of the selection decisions. Related to Gilliland’s fairness selection model is
Schuler’s (1993) social validity perspective that consists of four different aspects related to
applicant perceptions of the selection process. These aspects are (a) Informativeness,
defined as the degree of information provided to the applicant and perceived as useful;
(b) Participation, that is, the degree to which applicants perceive they have a chance to
participate and present themselves properly; (c) Transparency, that is, the extent to
which the procedures used are transparent; and (d) Feedback, defined as the availability
and extent of feedback provided by the organization to the applicants, independently of
their success in the selection process.
A meta-analysis carried out by Anderson, Salgado, and Hülsheger (2010) examined
applicant perceptions and reactions using studies conducted in 17 countries spread
worldwide through Europe, North America, Asia, and Africa. With small exceptions,
interviews, work sample tests, and resumes were the procedures perceived most
favorably. Cognitive tests, personality inventories, and references were also perceived
quite favorably. Finally, personal contacts and graphology were perceived unfavorably.
Anderson and colleagues (2010) also examined the relation between applicant reactions
and the operational validity of the selection procedures. They found large correlations
(over .60) between the operational validity of the procedures and the perceptions of
favorability, scientific evidence, face validity, and opportunity to perform.
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Multiple Prediction of Job Performance Based
on the Most Valid Procedures
Based on the validity of the different selection procedures and their interrelationships,
the largest correlation can be estimated by combining a set of instruments. In the present
case, the validity of selection processes consisting of two or three procedures for
predicting several performance criteria was estimated, including overall, one task, and
contextual performance, and overall interpersonal and organizational counterproductive
work behaviors.
In the case of overall job performance and task performance, as general cognitive ability
was the reflective predictor with the largest validity, it was the variable combined with a
second predictor or with two additional predictors. In the case of contextual performance
and counterproductive work behaviors, conscientiousness was the initial predictor to be
supplemented with a second or a third predictor. The results of the two-variable
prediction appear in Table 3, while those corresponding to the combinations of three
predictors can be seen in Table 4.
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Table 3. Best combinations of two procedures for predicting several occupational
criteria
Criterion Predictor Combination R R Square
Overall—Job Performance GCA + BSI .
77
.60
Task—Performance GCA + C .
68
.46
Contextual Performance C + GCA .
41
.17
Overall—Counterproductive Work
Behavior
C + ES .
52
.27
Interpersonal—Counterproductive
Work Behavior
A + ES .
50
.25
Organizational—Counterproductive
Work Behavior
C + A .
39
.16
Notes: GCA= general cognitive ability; BSI= behavioral structured interview; C=
conscientiousness; EX= extroversion; A= agreeableness; ES= emotional stability.
With reference to overall job performance and task performance criteria, the best
combination of two predictors was achieved using a GCA test supplemented with a
behavioral structured interview (R=.77). The next best combination was a GCA test
supplemented with a measure of the personality factor of conscientiousness (R=.74) or
integrity test (R=.74). The third best option was the combination of GCA with a measure
of job experience (R=.67). From here on, the contribution of the potential supplement
predictors was relatively scant. For example, if a test of a specific cognitive ability (e.g.,
numerical reasoning) supplemented the GCA test, the second test increased GCA validity
only slightly by .02. In the case of task performance, the results were similar.
For predicting contextual performance, the best combination of two predictors was a
conscientiousness measure supplemented with a GCA test (R=.41). For the criterion of
overall counterproductive work behaviors (OV-CWB), the best option was combining a
measure of conscientiousness with a measure of emotional stability (R=.52). For
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interpersonal counterproductive behavior (I-CWB), the best combination was a measure
of agreeableness supplemented with a measure of emotional stability (R=.50). Finally, for
the criterion of organizational counterproductive work behavior (O-CWB), the best
combination was conscientiousness supplemented by agreeableness (R=.39).
Table 4. Best combinations of three procedures for predicting several occupational
criteria
Criterion Predictor Combination R R Square
Overall—Job Performance GCA + BSI + C .
84
.71
Contextual Performance C + GCA + EX .
47
.22
Overall—Counterproductive Work
Behavior
C + A + ES .
45
.20
Interpersonal—Counterproductive
Work Behavior
A + ES + C .
52
.27
Organizational—Counterproductive
Work Behavior
C + A + ES .
40
.16
Notes: GCA= general cognitive ability; BSI= behavioral structured interview; C=
conscientiousness; EX= extroversion; A= agreeableness; ES= emotional stability.
As shown in Table 4, there were two optimum combinations offering similar results when
a combination of three procedures was used for predicting overall job performance. The
best combination consists of a GCA test supplemented with a behavioral structured
interview plus a conscientiousness inventory (R=.84). The second best combination was a
GCA test supplemented with a behavioral interview and a job knowledge test. These two
combinations had very good predictive outcomes. The choice of using one of the
combinations or the other could be based on non-psychometric criteria, for instance, the
costs of the instruments, the number of candidates, time available, and so on.
With regard to contextual performance, the best combination of three predictors was
combining a conscientiousness measure supplemented by a GCA test, and an
extroversion measure (R=.47). For innovative performance, the best combination was
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using a job knowledge test, plus a measure of openness, and a measure of emotional
stability. For the criterion of overall CWB, the best predictive option was a personalitybased
compound of conscientiousness, agreeableness, and emotional stability (R=.45).
For predicting interpersonal CWB, the optimum combination of three predictors was
agreeableness, emotional stability, and conscientiousness (R=.52). Finally, for the
criterion of organizational CWB, the best combination was conscientiousness, plus
agreeableness, and emotional stability (R=.40).
Ethnic Group Differences and Biased
Prediction
A relevant issue regarding the use of personnel selection procedures is whether they
produce ethnic group differences and whether these differences can produce biased
predictions. This issue is especially relevant regarding to cognitive tests and personality
measures but also it is important for all personnel selection procedures. Schmitt (2014)
concluded his review of this issue pointing out that the usual conclusion for at least the
last two decades was that that the tests did not produce biased predictions for women
and members of minority groups. The statistic Cohen’s d is the effect size index used to
establish whether there are subgroup differences. This effect size is computed by
subtracting the minority group mean (e.g., Asian, African American, and Hispanics) from
the majority group mean (typically, White) and dividing the difference by the pooled
within-group standard deviation of the scores (Schmidt & Hunter, 2014).
In the last 20 years, it has been well documented that cognitive tests showed ethnic
subgroup differences. This effect was found particularly in the United States (Berry et al.,
2014; Berry & Zhao, 2014; Hough, Oswald, & Ployhart, 2001; Schmitt, Clause, & Pulakos, 1996;
but it was also found in other countries such as The Netherlands (De Meijer et al., 2006;
teNijenhuis & van der Flier, 1997), South Africa (Kriek & Dowdeswell, 2009), Sweden (Kvist
& Gustafsson, 2008), and New Zealand (Guenole, Englert, & Taylor, 2003). In their review of
this topic, Bobko and Roth (2013) updated the main findings on the Black-White subgroup
differences. According to Bobko and Roth (2013), general cognitive ability tests show d =.
72 for moderate complexity jobs and d= .86 for low complexity jobs. In the case of work
sample tests, Bobko and Roth suggested an average d = .73. For situational judgment
tests, these researchers suggested a weighted average d = .38. For biodata, the average
d is .39 and for assessment centers, d is .56. Personality measures presented the lowest d
values, with .04 for integrity tests and -.09 for conscientiousness. Finally, Bobko and Roth
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suggested that the Black-White differences range from .31 to .46 for structured
interviews.
In the context of the ethnic group differences and biased prediction, it is important to
distinguish between differential validity and differential prediction. On one hand,
differential validity focuses on subgroup differences in the correlation between a
selection procedure and an organizational outcome (e.g., job performance, productivity,
salaries, satisfaction, and so on) as evidence of subgroup differences in procedureoutcome
relationships. On the other hand, differential prediction focuses on subgroup
differences in procedure-criterion unstandardized regression equations as evidence
regarding to subgroup differences in procedure-criterion relationships. Recently, several
articles reviewed the issue of differential validity and differential prediction (Berry et al.,
2014; Berry & Zhao, 2014; Mattern & Patterson, 2013). After controlling for range restriction,
Berry et al. (2014) found evidence of a small degree of differential validity in a cognitive
test battery. More specifically, Berry et al. (2014) found that the average validity was
smaller for Hispanics and African Americans than for Whites and Asians. With regard to
differential prediction, empirical research carried out by Berry and Zhao (2014) and
Mattern and Patterson (2013) agreed that cognitive ability tests overpredicted African
American job performance. In other words, these researchers concluded that cognitive
ability tests scores are not predictively biased against African American candidates in the
employment setting, which is consistent with the conclusions of Schmitt (2014) mentioned
above.
General Conclusion
In recent years, substantial progress in research and practice on personnel selection has
been made around the world and many of the limitations that previously affected the field
have been overcome. Currently, practitioners involved in personnel selection have a large
number of valid assessment procedures and have access to a great deal of research that
enables them to use the most appropriate set of instruments for their specific needs.
Thus, the job of the practitioners has been strongly endorsed and their role in
organizations is increasingly acknowledged and valued.
This article summarizes the operational validity of the 19 most common selection
procedures used in current practice. The operational validity of each procedure was
determined and the best combinations of pairs or triads of procedures were established.
The best combinations were derived on the basis of the respective operational multiple
correlation for predicting job performance criteria. Current state-of-the-art in personnel
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selection is capable of predicting these criteria and explaining over 60% of job
performance variance based on individual differences. Future rises in the explained
variance will be probably based on the development of new assessment technologies and
on the development of new theoretical approaches for occupational situations.
Further Reading
Anderson, N., Ones, D. S., Sinangil, H. K., & Viswesvaran, C. (Eds.). (2001). Handbook of
industrial, work, and organizational psychology. London: SAGE.
Evers, A., Anderson, N., & Voskuijl, O. (Eds.). (2005). Handbook of personnel selection.
Oxford: Blackwell.
Farr, J. L., & Tippins, N. (Eds.). (2010). Handbook of employee selection. New York:
Routledge.
Le, H., & Schmidt, F. L. (2006).Correcting for indirect range restriction in meta-analysis:
Testing a new analytic procedure. Psychological Methods, 11(4), 416–438.
Morgeson, F. P., Campion, M. A., Dipboye, R. L., Hollenbeck, J. R., Murphy, K., &
Schmitt, N. (2007). Reconsidering the use of personality tests in personnel contexts.
Personnel Psychology, 60(3), 683–729.
Outz, J. L. (Ed.). (2010). Adverse impact. Implications for organizational staffing and high
stakes selection. New York: Routledge.
Salgado, J. F. (2003). Predicting job performance using FFM and non-FFM personality
measures. Journal of Occupational and Organizational Psychology, 76(3), 323–346.
Schmitt, N. (Ed.). (2012). The Oxford handbook of personnel assessment and selection.
Oxford: Oxford University Press.
Society for Industrial and Organizational Psychology. (2003). Principles for validation and
use of the personnel selection procedures. Bowling Green, OH: Author.
Tett, R. P., & Christiansen, N. D. (Eds.). (2013). Handbook of personality at work. New
York: Routledge.
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Jesús F. Salgado
University of Santiago de Compostela
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