ArticlePDF AvailableLiterature Review

Evaluating the Effectiveness of Performance Management: A 30-Year Integrative Conceptual Review

January 2019
Journal of Applied Psychology 104(7)

January 2019
104(7)

Authors:

City University of Hong Kong

This integrative conceptual review is based on a critical need in the area of performance management (PM), where there remain important unanswered questions about the effectiveness of PM that affect both research and practice. In response, we create a theoretically grounded, comprehensive, and integrative model for understanding and measuring PM effectiveness, comprising multiple categories of evaluative criteria and the underlying mechanisms that link them. We then review more than 30 years (1984 -2018) of empirical PM research vis-à-vis this model, leading to conclusions about what the literature has studied and what we do and do not know about PM effectiveness as a result. The final section of this article further elucidates the key "value chains" or mediational paths that explain how and why PM can add value to organizations, framed around three pressing questions with both theoretical and practical importance (How do individual-level outcomes of PM emerge to become unit-level outcomes? How essential are positive reactions to the overall effectiveness of PM? and What is the value of a performance rating?). This discussion culminates in specific propositions for future research and implications for practice.

Frequency of Criteria Across All PM Studies

…

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INTEGRATIVE CONCEPTUAL REVIEW

Evaluating the Effectiveness of Performance Management:

A 30-Year Integrative Conceptual Review

Deidra J. Schleicher

Texas A&M University Heidi M. Baumann

Bradley University

David W. Sullivan and Junhyok Yim

Texas A&M University

This integrative conceptual review is based on a critical need in the area of performance management

(PM), where there remain important unanswered questions about the effectiveness of PM that affect both

research and practice. In response, we create a theoretically grounded, comprehensive, and integrative

model for understanding and measuring PM effectiveness, comprising multiple categories of evaluative

criteria and the underlying mechanisms that link them. We then review more than 30 years (1984–2018)

of empirical PM research vis-a

`-vis this model, leading to conclusions about what the literature has studied

and what we do and do not know about PM effectiveness as a result. The final section of this article

further elucidates the key “value chains” or mediational paths that explain how and why PM can add

value to organizations, framed around three pressing questions with both theoretical and practical

importance (How do individual-level outcomes of PM emerge to become unit-level outcomes? How

essential are positive reactions to the overall effectiveness of PM? and What is the value of a performance

rating?). This discussion culminates in specific propositions for future research and implications for

practice.

Keywords: performance management, performance appraisal, evaluation, integrative conceptual review

Despite the popularity of performance appraisal (PA) and per-

formance management (PM) in both research and practice, there is

a great deal yet to know about the effectiveness of these practices.

Consider, for example, the following observations.

These systems constitute a ‘human resource management paradox and

their effectiveness an elusive goal’ (Taylor, Tracy, Renard, Harrison,

& Carroll, 1995). (Nurse, 2005, p. 1178)

The formula for effective [PM] remains elusive. (Pulakos & O’Leary,

2011, p. 146)

There is no shortage of recommendations in the practitioner literature

about what makes for effective PM systems....Theproblem is that

few studies support the many claims about the actual contributions of

various practices to the overall effectiveness of PM systems. (Haines

& St-Onge, 2012, p. 1171)

It is not clear that [PM] will lead to more effective organizations....

Identifying how (if at all) the quality and the nature of performance

appraisal programs contribute to the health and success of organizations

is a critical priority. (DeNisi & Murphy, 2017, p. 429)

The lack of clear and compelling evidence for the effectiveness

of PM (defined as “a continuous process of identifying, measuring,

and developing the performance of individuals and teams and

aligning performance with the strategic goals of the organization,”

Aguinis, 2013, p. 2) has given rise to recent debates about whether

or not formal PM is even necessary (e.g., Adler et al., 2016;Pulakos

& O’Leary, 2011). Addressing these sorts of issues, as well as making

informed judgments about PM research and practice in general, re-

quires a fuller articulation of the evaluative space of PM than avail-

able in the extant literature. This is the primary purpose of this article,

which identifies a particularly pressing need based on our extensive

review of the PM literature: a theoretically grounded, comprehensive,

and integrative framework for PM effectiveness.

We thank, and agree with, a reviewer who pointed out that this issue

within PM is actually a more specific instance of an issue that has been

around a long time: the “criterion problem” (see Austin & Villanova, 1992).

This article was published Online First January 24, 2019.

Deidra J. Schleicher, Department of Management, Texas A&M Univer-

sity; Heidi M. Baumann, Department of Management and Leadership,

Bradley University; David W. Sullivan and Junhyok Yim, Department of

Management, Texas A&M University.

We wish to express our sincere appreciation to Murray Barrick, Wendy

Boswell, and Matt Call for their very helpful comments on earlier versions

of this article.

Correspondence concerning this article should be addressed to Deidra J.

Schleicher, who is now at Ivy College of Business, Iowa State University,

2167 Union Drive, Ames, IA 50011-2027. E-mail: deidra@iastate.edu

This document is copyrighted by the American Psychological Association or one of its allied publishers.

This article is intended solely for the personal use of the individual user and is not to be disseminated broadly.

Journal of Applied Psychology

0021-9010/19/$12.00 http://dx.doi.org/10.1037/apl0000368

851

The need for such a framework is highlighted by recent discus-

sions within practice. For example, Pulakos and O’Leary (2011,p.

154) ask whether PM systems “provide a sufficient return to justify

their use.” Related, there has been a push to simplify PM by

streamlining its “low value” aspects (see Effron & Ort, 2010; and

Buckingham & Goodall’s, 2015 discussion of Deloitte’s changes

in this regard). More generally, Lawler and McDermott (2003)

find “little research data to establish the impact of the many

practices recommended in the writings on PM” (p. 50). One key

challenge is that there are myriad ways to define what terms like

“return,” “value,” and “impact” mean in this context. Indeed,

different research streams historically have argued (implicitly or

explicitly) for different evaluative foci. For example, an ability-

based or cognitive perspective on PA privileges the rating task and

argues for an emphasis on psychometric criteria (e.g., Cardy &

Dobbins, 1994); a motivational view privileges PM as a vehicle for

improving employee performance and argues that “the proper

focus...istochange employee behavior on the job” (DeNisi &

Pritchard, 2006); and strategic views privilege unit-level outcomes

and argue for firm performance as the ultimate criterion (DeNisi &

Smith, 2014).

Importantly, our review of the PM literature reveals no previous

attempts to systematically and comprehensively map (let alone

integrate) the full evaluative criterion space of PM implied by

these disparate research streams. This is likely one of the key

contributors to some of the issues noted above. Specifically, our

review suggests that cumulative and actionable knowledge about

PM effectiveness has been significantly hindered by lack of atten-

tion to articulating and studying the multiple types of PM evalu-

ative criteria, how they interrelate (e.g., how do more proximal

criteria such as reactions accumulate to create value for the orga-

nization?), and how they are differentially relevant for different

questions. Both empirical research and conceptual models histor-

ically have focused on a disappointingly small number of PM

criteria (e.g., rating errors and accuracy, ratee reactions; Cardy &

Dobbins, 1994;Levy & Williams, 2004; see Table 1, which

provides a summary of earlier work). There exist very few models

of how multiple types of PM criteria are likely to interrelate, and

no such models that are comprehensive. In response, as part of this

integrative conceptual review, we created a comprehensive theo-

retical model for the criteria underlying PM effectiveness. This

model combines empirical and theoretical work in multiple areas

to identify the types of criteria that have been—or should be—

used to evaluate the effectiveness of PM.

The creation of this comprehensive model and subsequent re-

view of the literature vis-a

`-vis this model are our primary contri-

butions, representing a significant step forward compared to prior

work in several ways. We integrate PM effectiveness criteria

relevant to both research and practice, a longstanding need in this

area (Bretz, Milkovich, & Read, 1992;Ilgen, Barnes-Farrell, &

McKellin, 1993). Moreover, although we incorporate extant mod-

els, we go beyond these to add concepts from other literatures

critical for understanding the mechanisms underlying PM effec-

tiveness. Specifically, PM literature to date has either (a) had a

very micro focus, not attempting to link individual criteria like

rating quality or reactions to unit-level constructs (see earlier

review by Levy & Williams, 2004); or (b) has adopted an exclu-

sively macro focus (e.g., DeNisi & Smith’s, 2014 discussion of

PM and firm performance). In contrast we argue that progress in

understanding PM effectiveness requires incorporation of both

micro and macro constructs as well as specification of the pro-

cesses that link them (Ployhart & Moliterno, 2011). Doing so

allows us to articulate how the various criteria are interrelated,

including a mapping of the key mediational paths (or what we term

“value chains”) underlying PM effectiveness.

This model (see Figure 1) in turn has several important impli-

cations for both research and practice. First, regarding implications

for PA/PM researchers specifically, our review uses this model to

distill cumulative knowledge from the empirical PM literature, in

terms of what aspects of PM exert the biggest influence on which

evaluative criteria. This allows us to synthesize what is currently

known about the effectiveness of PM while simultaneously iden-

tifying a number of limitations in the extant literature, which in

turn provides an important foundation for charting a specific and

fruitful course for future research. Second, regarding implications

for practice, the distilled knowledge from our review concisely

identifies which aspects of PM make the biggest difference for

specific evaluative criteria. This enables organizations interested in

a particular outcome (e.g., improving employees’ reactions to PM)

to understand what levers are likely to be most impactful in that

goal. Our model and review of relationships among criteria also

help organizations identify the more proximal criteria that lead to

more distal outcomes. It is often the latter (e.g., firm performance)

in which organizations are most interested, but identifying a direct

link between these and PM can be very difficult, given the many

alternative explanations.

Third, regarding implications for literatures beyond PA/PM, we

contribute to the strategic human resources (HR) literature, which

has emphasized the importance of better understanding the “black

box” linking HR practices to organizational performance (Becker

& Huselid, 2006;Messersmith, Patel, Lepak, & Gould-Williams,

2011, or what macro researchers would label the “microfounda-

tions” of organizational performance, Coff & Kryscynski, 2011).

Our comprehensive model that incorporates both micro and macro

evaluative criteria and specifies their interrelationships helps shed

light here. Finally, in articulating how PM affects both proximal

and more distal criteria and emerges from individual to unit-level

phenomena, we contribute to important multilevel work in the area

of human capital (Ployhart & Moliterno, 2011;Ployhart, Nyberg,

Reilly, & Maltarich, 2014). Ployhart and Moliterno (2011) note

that “one of the most promising avenues for future research will be

linking specific HR practices to human capital emergence” (p.

145), and our model depicts multiple ways in which PM specifi-

cally can affect such emergence.

In the sections that follow, we first explain the scope of this

review, followed by a description of how our model of PM

evaluative criteria was created, how we used it as a framework for

systematically reviewing and coding more than 30 years of em-

pirical PM work, and the meaning of each component. Then we

synthesize the empirical PM research via this model (including

criteria interrelationships), drawing conclusions about what the

literature has studied and what we do and do not know about PM

effectiveness as a result. The final section of our article further

elucidates the key value chains or mediational paths that explain

how and why PM processes can add value to organizations. Dis-

cussion of these specific mediational paths is organized around

several pressing questions with both theoretical and practical im-

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852 SCHLEICHER, BAUMANN, SULLIVAN, AND YIM

Table 1

Extant Models of PA/PM Effectiveness

Authors and year Journal Scope Approach Years reviewed Criterion constructs

examined Relevant model components

Cardy and Dobbins (1994) Book PA Theoretical model Unspecified • Rater errors

• Rating accuracy

• Qualitative aspects

• MGR learning (Rating quality)

• EE and MGR reactions

(Satisfaction and cognitive)

Cawley, Keeping, and Levy

(1998) Journal of Applied

Psychology PA Meta-analysis 1967–1998 • EE reactions • EE reactions (All)

• EE learning (Motivational)

Keeping and Levy (2000) Journal of Applied

Psychology PA Literature review and

single empirical

study

All extant appraisal reactions

research • EE reactions • EE reactions (All)

den Hartog, Boselie, and

Paauwe (2004) Applied Psychology: An

International Review PM Theoretical model Unspecified • EE perceptions and

attitudes

• EE behavior and

performance

• Organizational

performance

• EE reactions (All)

• EE transfer (Task performance)

• Unit-level financial

performance

Levy and Williams (2004) Journal of Management PA Literature review 1995–2003 • Rater errors and

biases

• Rating accuracy

• Appraisal reactions

• MGR learning (Rating quality)

• EE and MGR reactions (All)

• EE learning (Motivational)

DeNisi and Pritchard (2006) Management and

Organization Review PA and

PM Theoretical model Unspecified • EE performance

improvement

• Agreement between

evaluators

• Fairness in

evaluation

procedures

• Consistency across

ratees/time

• Distributive justice

• EE transfer (Task performance)

• MGR learning (Rating quality)

• EE reactions (Fairness)

Pichler (2012) Human Resource

Management PA Meta-analysis All extant appraisal reactions

research • Ratee reactions • EE reactions (All)

Kinicki, Jacobson, Peterson, and

Prussia (2013) Personnel Psychology PM Literature review and

scale development Unspecified • MGR performance

management behavior • MGR learning (Skills-based)

• MGR transfer (Quality of

decisions made about EEs)

DeNisi and Smith (2014) Academy of Management

Annals PA and

PM Literature review and

theoretical model Unspecified • Firm-level

performance • Unit-level financial

performance

DeNisi and Murphy (2017) Journal of Applied

Psychology PA and

PM Literature review 1917–2015 (Focus on 1970–

2000 and on JAP articles) • Rater errors and

biases

• Rating accuracy

• Ratee and rater

reactions

• EE performance

improvement

• Firm-level

performance

•MGR learning (Rating quality)

• EE and MGR reactions (All)

• EE transfer (Task performance)

• Unit-level financial

performance

Note. Italicized text represents constructs that were proposed as independent variables in the original source, but are categorized in the current model as criterion constructs. EE ⫽employee; MGR ⫽

manager; PM ⫽performance management; PA ⫽performance appraisal.

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853

EFFECTIVENESS OF PERFORMANCE MANAGEMENT

portance, culminating in specific propositions for future research

and implications for practice.

The Scope of This PM Review

There are several aspects related to scope that we would like to

clarify. To start, our review focuses on PM. Whereas PA is

generally understood to be a discrete, formal, organizationally

sanctioned event, usually occurring just once or twice a year, PM

is seen as a broader set of ongoing activities aimed at managing

employee performance (DeNisi & Murphy, 2017;DeNisi &

Pritchard, 2006;Williams, 1997). In other words, PA can be

thought of as a subset of PM (see also Levy, Tseng, Rosen, &

Lueke, 2017). We use the terms PA and PM somewhat inter-

changeably when referring to the body of literature only. The

scope of our review (which is PM) necessarily includes work in

both PA and PM, and to create a comprehensive evaluative model,

it is necessary to include both the traditionally narrower practices

of PA (constituting a longer and more voluminous tradition in the

empirical literature) as well as the broader set of activities consid-

ered more recently to be part of PM. Thus, we discuss both in the

ensuing review of the literature, which spans the last 30⫹years of

work in PA/PM (1984–2018).

Our review is also not a “general” review of PM but instead is

more specifically focused on the evaluative criteria of PM. This

addresses what we see as a particularly important need in the

literature (as articulated above); it also makes this review substan-

tively unique from others in the literature (see Table 1), including

the very recent literature. For example, DeNisi and Murphy

(2017), in the Centennial Issue of Journal of Applied Psychology

(JAP), summarize PA/PM research published in JAP specifically,

during the “heyday” of PA research (1970–2000), in eight areas:

rating scale formats, criteria for evaluating ratings (primarily rating

quality and rater and ratee reactions, see Table 1), PA training,

reactions to appraisal, purpose of rating, rating sources, demo-

graphic differences in ratings, and cognitive processes in PA.

Another review on the topic of PM was recently published in the

Journal of Management (Schleicher et al., 2018). Whereas the

current review can be thought of as comprehensively articulating

what is known about the outcomes or dependent variables (“DVs”)

of PA and PM, Schleicher et al. (2018) focus squarely on the

independent variables (“IVs”) of PM, categorizing all of the com-

ponents of PM systems to help shed light on what the most

relevant “moving pieces” are of PM practices and systems. Im-

portantly, neither of these two recent reviews, nor any that came

before them, have explicitly and comprehensively focused on the

evaluative criteria of PM, as the current review does.

Finally, it is admittedly difficult to discuss the “DVs” of PM

without also referencing the “IVs,” as it is useful to summarize

which aspects of PM are particularly influential in affecting the

various evaluative criteria. Schleicher et al. (2018) take a systems-

based approach to understanding the various IVs of PM. Because

their taxonomy is the most recent and most comprehensive ap-

This timeframe seemed appropriate given that DeNisi and Murphy

(2017) identified the year 2000 as the end of the “heyday” of PA research.

Our timeframe of 1984–2018 brings us to the most recent research and also

allows for a nearly even split (17–18 years on either side) regarding the

ending of this heyday.

Affective

Cognitive

Utility

Satisfaction

PM-related Reactions

Cognitive

Attitudinal/

Motivational

Skills-based

PM-related Learning

•Job attitudes

•Fairness/justice perceptions

•Organizational attraction

•Motivation

•Empowerment

•Well-being

•Work Affect

•Creativity

•Performance (OCB, task)

•Counterproductive behavior

•Withdrawal

•Specific KSAOs

Transfer

Human Capital

Resources

•Labor Productivity

•Production

quality/quantity

•Organizational

innovation

•Safety Performance

•Corporate Social

Responsibility

•Turnover rates

•Absenteeism

•Grievances

Operational Outcomes

Employee Manager

Cognitive

Attitudinal/

Motivational

Skills-based

Rating quality

•Quality of relationship with

employees

•Quality of decisions made

about employees

•General mgrl effectiveness

•Climate, culture, and

leadership

•Trust in management

•Organizational learning

and knowledge sharing

•Team cohesion, trust,

and collaboration

•Quality of human

capital decisions

Affective

Cognitive

Utility

Satisfaction

Unit-level

•Skills/abilities/potential

capabilities

•Motivation capabilities

Emergence Enablers

Financial Outcomes

•ROI, ROA

•Sales growth

•Firm growth

•Market

Competitiveness

PM System Components

PM-related Reactions PM-related Learning

Transfer

Figure 1. Model of evaluative criteria underlying performance management (PM) effectiveness.

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854 SCHLEICHER, BAUMANN, SULLIVAN, AND YIM

proach to date of the IVs of PM—and also because we built our

DV model with the assumption that PM in organizations is a

system—we adopt their IV framework for facilitating our synthe-

sis of the empirical research, as we discuss in that later section.

Creation and Overview of Our Model of PM

Evaluative Criteria

In creating our model, we took an iterative (inductive-deductive-

inductive) approach. First, we reviewed the last 30⫹years of work

in PA/PM, including empirical and conceptual articles in both the

research and practice, and micro and macro literatures, to uncover

the types of evaluative criteria being measured and discussed. By

“criteria,” we mean the categories of constructs used to measure

the effectiveness of PM (see Kirkpatrick, 1987). We wanted our

model to be explicitly comprehensive with regard to (a) the content

existing in the variety of (narrower) evaluative frameworks in the

extant literature; (b) criteria of interest to both research and prac-

tice; and (c) both micro and macro constructs. Regarding (a), we

incorporated definitions of PA effectiveness by Cardy and Dob-

bins (1994),Keeping and Levy (2000), and Levy and Williams

(2004) and frameworks from other authors (e.g., den Hartog,

Boselie, & Paauwe, 2004;DeNisi & Smith, 2014;Toegel &

Conger, 2003). Table 1 provides a summary of this prior (and

notably narrower) work. Regarding (b), we know from long-

standing discussions of the “research-practice gap” in PA that

researchers and practitioners tend to be interested in different

criteria (Banks & Murphy, 1985;Bretz et al., 1992). For example,

while issues of validity and other psychometrics are focal evalu-

ative criteria in research, issues of acceptability to users are key in

practice. Wanting to reflect both sides of this “gap,” we explicitly

incorporated criteria important to research and practice. Regarding

(c), a comprehensive and generative model also must incorporate

both “micro” and “macro” criteria, as full understanding can only

come by examining both what PM can do to and for individuals as

well as what it can do to and for organizations. Although extant

writing in PM (and certainly PA) has had a decidedly more micro

feel (notable exceptions include Bhave & Brutus, 2011;DeNisi &

Smith, 2014), the evaluation of PM is inherently multilevel. In

fact, we would argue that this is likely more true for PM than for

other areas of HR, given the integral role of the manager in PM

(den Hartog et al., 2004). PM processes and policies affect

organization-level outcomes not only through employees (“ratees”

in traditional PA research) but also through the actions and atti-

tudes of managers (“raters” in traditional PA research). For this

reason, our model maps the evaluative criteria at both employee/

ratee and manager/rater levels as well as how these individual-

level constructs aggregate and emerge to affect unit-level out-

comes (see Figure 1).

Second, we identified models and theories from other literatures

that would be useful for classifying all the criteria uncovered in the

previous step, suggesting additional relevant criteria, and perhaps

most important, understanding how all of these criteria might

interrelate in theoretically meaningful ways. Thus, our model

includes both criteria measured in the extant PM literature as well

as those that are not currently measured but are theoretically

relevant. The latter may denote mechanisms that explain how some

criteria link to other more distal criteria. We believe these are

important to identify, given the goals of a more comprehensive

model, which include understanding how PM results in effective-

ness. For this deductive phase we relied in particular on work in

the training evaluation area, including Kirkpatrick’s (1987) taxon-

omy, Alliger, Tannenbaum, Bennett, Traver, and Shotland’s

(1997) model of the relations among training criteria, and the

Kraiger, Ford, and Salas (1993) model of cognitive, skill-based,

and affective learning criteria; and theories within strategic HR,

including the ability-motivation-opportunity (AMO) framework

(Becker & Huselid, 1998;Delery & Shaw, 2001;Jiang, Takeuchi,

& Lepak, 2013) and multilevel work on the construct of human

capital resources and the emergence process (Ployhart & Mo-

literno, 2011;Ployhart et al., 2014).

Third, we then systematically coded all criterion variables found

in the empirical PM literature, identified through a search that used

Business Source Ultimate and PsycINFO for the years 1984–2018

and the terms performance management, performance appraisal,

and performance evaluation. After removing all irrelevant articles,

there were a total of 488 empirical PM articles (544 separate

studies, with 768 instances of criteria across all studies). We coded

each study vis-a

`-vis the components of our model and also re-

corded findings and methodological details. This final step ensured

completeness of the model and also gave us important summative

information about what the literature is and is not investigating with

regard to evaluative criteria and what we know about PM as a result.

The resulting model is depicted in Figure 1, with each component

explained below. Here we discuss linkages between components at a

general level, to establish the relevance of various components; in the

final section of the article we articulate these links in greater detail and

explicate specific propositions.

PM-Related Reactions

Because PM practices first affect employees’ perceptions (den

Hartog et al., 2004), reactions are the first component of our model

(see Figure 1). This refers to how employees and managers feel or

think about the overall PM system and/or its specific aspects (e.g.,

rating, the appraisal interview, a feedback meeting); for employ-

ees, this would include managers as a target of reactions, given

they are enactors of these processes. Theoretically, reactions play

an important role as they can relate to learning (Alliger, Tannen-

baum, Bennett, Traver, & Shotland, 1997;Kirkpatrick, 1987), and

they have been found to be important in the social exchange

between PM partners (i.e., managers and employees; Masterson,

Lewis, Goldman, & Taylor, 2000;Pichler, 2012), suggesting they

may be related to attitudes and behaviors as well.

Although the majority of PM research has focused on reactions

of employees (especially ratees), reactions of managers are also

key to understanding PM. Because such practices “are facilitated

and implemented by direct supervisors or front-line managers”

(den Hartog et al., 2004, p. 565), their reactions are critical in any

model of PM effectiveness. In addition, there is evidence that

raters’ attitudes and beliefs about PM are related to their rating

behavior and that these PM-specific reactions are stronger predic-

tors of such behavior than are general job or organizational atti-

tudes (Tziner, Murphy, Cleveland, & Roberts-Thompson, 2001).

Although the structure of this category (see next paragraph) par-

From here on out we use the more general terms of employees and

managers, respectively.

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855

EFFECTIVENESS OF PERFORMANCE MANAGEMENT

allels that of employee reactions, manager reactions likely have

different implications for downstream criteria (and operate through

different mediators) than employee reactions (Seiden & Sowa,

2011), as we develop later.

Like Alliger et al.’s (1997) augmentation of Kirkpatrick’s tax-

onomy, our model distinguishes between affective, cognitive, and

utility reactions to PM; we also add satisfaction as a subcategory

to capture overall evaluations of PM (Keeping & Levy, 2000).

Affective reactions refer to how the employee or manager feels

about the PM event or system and include discomfort, frustration,

anxiety/stress, or other emotional reactions to PM (e.g., David,

2013;Smith, Harrington, & Houghton, 2000). Cognitive reactions

refer to how the employee or manager thinks about the PM event

or system and include perceived justice or fairness, perceived

acceptability or appropriateness, and perceived accuracy of the

evaluation (e.g., Erdogan, 2002;Erdogan, Kraimer, & Liden,

2001;Hedge & Teachout, 2000). Utility reactions more directly

ask about the perceived usefulness or value of the PM event or

system (e.g., Burke, 1996;Keaveny, Inderrieden, & Allen, 1987;

Nathan, Mohrman, & Milliman, 1991). Satisfaction reactions are

typically measured as a general evaluation of the PM system or

event (Cawley, Keeping, & Levy, 1998). Although satisfaction can

be affective or cognitive (see Schleicher, Smith, Casper, Watt, &

Greguras, 2015;Schleicher, Watt, & Greguras, 2004), many reac-

tions in the PM literature measure more general satisfaction and

cannot be cleanly categorized as just affective/cognitive. Thus, we

retained overall satisfaction as a subcategory. Keeping and Levy

(2000) found that PA reactions (e.g., satisfaction, utility) are best

modeled as distinct constructs that are related to one another

through a higher-order factor. Moreover, we know from the train-

ing evaluation literature that affective versus cognitive versus

utility-based reactions can have differential effects on other criteria

(Alliger et al., 1997). Thus, we believe it is important to differen-

tiate reactions in this way in our model. Finally, we found in our

review that what the PM literature sometimes casually refers to as

reactions (e.g., “buy-in,” acceptance, or commitment to the PM

system) may be more accurately classified as learning, as de-

scribed in the next section.

PM-Related Learning

We argue that multifaceted learning, by both employees and

managers, is an expected outcome of PM, yet one that has never

been fully articulated in extant models (see Table 1). The training

literature describes learning as “the extent to which trainees have

acquired relevant principles, facts, or skills” (Kraiger, Ford, &

Salas, 1993, p. 311), and the learning components of our model

reflect what employees and managers may have gained—in terms

of proximal PM-related knowledge, skills, attitudes, and motiva-

tion—as a result of PM. This necessarily includes both learning

things about PM itself (e.g., for employees, awareness of devel-

opment opportunities; for managers, awareness of what behaviors

comprise effective feedback meetings or effective note-taking) as well

as learning things about oneself (e.g., increased self-awareness re-

garding strengths and areas for improvement). By “proximal,” we

mean that the learning occurred as a direct result of participating in

a PM task (e.g., the employee’s increased awareness of and greater

intent to engage in development opportunities after participating in

a formal performance evaluation; Boswell & Boudreau, 2002)oris

in reference to the PM aspects themselves (e.g., managers’ in-

creased understanding of what goes into effective feedback and

beliefs about its importance); they are also often measured in close

proximity to the PM event.

To build out this component, we rely on Kraiger et al.’s (1993)

multidimensional model of learning criteria and differentiate be-

tween cognitive, skills-based, and attitudinal/motivational learning

(see Figure 1). Cognitive PM-related learning includes knowledge

(declarative, procedural, and tacit), knowledge organization, or cog-

nitive strategies resulting from participation in PM. Skills-based learn-

ing represents behavioral changes related to skill compilation and

skill automaticity resulting from PM (e.g., effective note-taking,

Mero, Guidice, & Brownlee, 2007; employee feedback-seeking,

Moss, Valenzi, & Taggart, 2003). Attitudinal/motivational PM-

related learning includes attitudinal changes and motivational ten-

dencies resulting from PM. These are attitudes about PM specif-

ically, formed by participation in the PM system, not job attitudes

more generally; and motivation for PM tasks (e.g., acceptance and

commitment of goals set during PM; buy-in or acceptance of the

PM system as a whole), not general motivation related to one’s

job. As Kraiger et al. (1993) have noted “an emphasis on behav-

ioral or cognitive measurement at the expense of attitudinal or

motivational measurement provides an incomplete profile of learn-

ing” (p. 318). In addition, its inclusion in both their model and in

ours reflects the fact that training programs and PM systems in

organizations go beyond impacting knowledge and skills to also

act as “powerful socialization agent[s]” (p. 319), indoctrinating

employees and managers to the importance of various aspects of

the training content or PM systems. For example, in the PM

literature, attitudinal/motivational learning variables include agree-

ment with the theories of performance espoused by the organiza-

tion (which increases as a result of rater training, Schleicher &

Day, 1998) and rater self-efficacy (Tziner et al., 2001) for man-

agers; and intentions to engage in future development (Boswell &

Boudreau, 2002) and acceptance of and commitment to goals

discussed in the feedback meeting (Tziner & Kopelman, 1988) for

employees.

Learning criteria involve PM-related knowledge, skills, atti-

tudes, and motivations that employees and especially managers

need to “do PM well” and that should theoretically improve as a

result of experience with PM (e.g., understanding what good

performance is, learning to more constructively receive feedback,

felt accountability for PM, avoidance of intentional distortion).

This is an important component of the model because the extent to

which managers do PM well is likely to directly affect employees’

reactions to PM (Jawahar, 2010;Waung & Jones, 2005), setting

off the evaluative chain in the bottom row of our model. It has been

suggested that managers who do such things well should also

produce employees who are more engaged and motivated (Lady-

shewsky, 2010). Unfortunately, these manager learning criteria

have been largely ignored in the extant PM literature, with one

major exception. Related to this exception, we categorize the

quality of ratings under this category because, like the other

constructs included here, rating quality represents tangible and

proximal manifestations of managers’ knowledge, skills, abilities,

and motivations gained from the PM process. This psychometric

subcategory of learning includes the extent to which ratings are

free from errors and biases, are reliable and valid, and are accurate

(Aguinis, 2013;Cardy & Dobbins, 1994).

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856 SCHLEICHER, BAUMANN, SULLIVAN, AND YIM

It is important to differentiate learning from reactions in under-

standing PM effectiveness. Reactions capture the PM event or

system as experienced by the employee or manager but are not

direct measures of what one may have learned as a result of the PM

experience (Kraiger et al., 1993). It is notable, and surprising to us,

that prior discussions of PM effectiveness have not explicitly

focused on these learning criteria (for employees or managers).

Such criteria seem especially important given recent trends fo-

cused on more developmental approaches to PM (e.g., “feed-

forward” interviews, Kluger & Nir, 2010; strengths-based evalu-

ation, Bouskila-Yam & Kluger, 2011). Cappelli and Tavis (2016),

for example, describe the recent PM revolution as a shift “from

accountability to learning” (p. 2), and Buckingham and Goodall

(2015) describe the focus of Deloitte’s new system as “constant

learning” (p. 42). Without effectiveness measures focused on prox-

imal PM-related learning, it may be unclear whether (and how)

these new development-focused systems have achieved their goals.

Thus, we include PM-related learning as an important evaluative

criterion, positioned between reactions and transfer in our model.

Employee Transfer

The employee transfer component of our model includes em-

ployee attitudes, behaviors, and outcomes that may be affected by

elements of PM but which extend beyond the PM context, in

referent (i.e., they refer to the job or organization more broadly)

and/or timing of measurement. This component would not include

employees’ attitudes about PM specifically or behaviors that are

confined to the PM context primarily (these would be classified as

employee reactions or learning). Instead this component includes

criteria that suggest that the effects of PM may “transfer” back to

the job. In Kirkpatrick’s (1976,1987) model, transfer was largely

equated with behavior and performance and defined as “using

learned principles and techniques on the job” (Alliger & Janak,

1989, p. 331). Because we are not talking about the effective-

ness of just training but rather the outcomes of multifaceted PM

systems, we use transfer in a broader sense, to include perfor-

mance and other behaviors (e.g., withdrawal) but also attitudi-

nal and motivational constructs (e.g., job attitudes, justice). Yet

similar to Kirkpatrick’s initial meaning, this component repre-

sents the question of whether the effects of PM transfer beyond

the immediate PM context (e.g., formal review meeting) back to

the “job” to impact employee behaviors and attitudes more

broadly. Unlike subsequent components, which are at the unit-

level, Transfer criteria reside at the individual level (conceptu-

ally and empirically).

There is a heavy focus on “transfer” criteria in the training

literature (see, e.g., Baldwin & Ford, 1988;Ford & Weissbein,

1997), and the constructs in this category here are undoubtedly

among the most frequently studied and important outcomes in

organizational behavior and I/O psychology in general. Yet his-

torically they have been less studied as explicit outcomes of PM.

For example, in extant conceptual models (see Table 1), only task

performance is referred to and in only a few examples (den Hartog

et al., 2004;DeNisi & Murphy, 2017;DeNisi & Pritchard, 2006).

In the empirical PM literature, however, examination of these

criteria has more than doubled in recent, compared with older,

research (i.e., there were 47 instances before 2000, compared with

121 post-2000). This is welcome empirical progress, as these

criteria play an important role theoretically in the various value

chains of PM, as we develop later.

Manager Transfer

Like employee transfer, the manager transfer component in-

cludes criteria that extend beyond the PM context to the manager’s

role in the organization more generally. Given the longstanding

emphasis on interpersonal and decision-making activities in man-

agerial work (Mintzberg, 1971), this component includes both

relational and decision-making constructs. PM has been discussed

as a critical tool that serves as a basis for making effective

decisions about human resources (Cardy & Dobbins, 1994), mak-

ing managers’ effectiveness in this regard an important evaluative

criterion. The manager–employee relationship is also clearly rel-

evant and has been noted as essential for increasing PM effective-

ness (Pulakos & O’Leary, 2011). We agree wholeheartedly but

argue here that these relationships can themselves be impacted by

aspects of PM and thus should be studied as a DV in PM research,

not just as an IV. In short, the manager transfer component

concerns the extent to which PM changes how managers do their

job (or at least employees’ perceptions of this, Kacmar, Wayne, &

Wright, 1996), and it includes the quality of relationships formed

with employees, the quality of decisions managers make about

employees, and other indicators of general managerial effective-

ness.

These transfer criteria would likely be affected by the learning

managers amass as a result of aspects of PM (relational criteria

specifically could also be impacted by employees’ reactions to

PM). In turn, these improved aspects of managerial effectiveness

impact employees’ attitudes and behaviors (see Figure 1). We also

argue that manager transfer criteria exert an important influence on

unit-level criteria (discussed in the following sections). Specifi-

cally, the quality of managers’ relationships with employees ag-

gregate into several important emergence enablers such as climate

and trust in management. And the quality of decisions managers

make about employees aggregate into the quality of unit-level

human capital decisions, which determines the unit’s ability to

“leverage” the human capital available (see Lakshman, 2014).

Unit-Level Human Capital Resources

In our model, employee transfer constructs knowledge, skills,

abilities,and other characteristics (KSAOs, attitudes, and behav-

iors) aggregate to become unit-level human capital resources

(HCRs; Ployhart & Moliterno, 2011;Ployhart et al., 2014), and it

In our discussion of unit-level criteria further below, we rely on

Ployhart et al.’s (2014) recent theorizing about the construct of human

capital resources. Our transfer criteria require some clarification vis-a

`-vis

that theorizing. Ployhart et al. (2014) exclude constructs like attitudes,

satisfaction, and motivation from their discussion of KSAOs (the essential

building blocks of human capital resources), because they view such

characteristics as being situationally specific and induced. Setting aside

evidence that such characteristics can in fact be stable (e.g., Staw & Ross,

1985), we argue that these other characteristics of employees (i.e., atti-

tudes, motivation), especially when emergent at unit levels, do have eco-

nomic relevance for organizations (see e.g., Barrick, Thurgood, Smith, &

Courtright’s, 2015, and Harter, Schmidt, & Hayes’, 2002 work on em-

ployee engagement). For that reason, we include a comprehensive set of

criteria under employee transfer (see Figure 1).

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857

EFFECTIVENESS OF PERFORMANCE MANAGEMENT

is these HCRs that can influence firm operational and financial

performance (see Figure 1).

Borrowing from the AMO frame-

work popular within strategic HR, these unit-level HCRs are

organized into the following two categories in our model: skills/

abilities/potential, and motivational capabilities. Based in the view

that employees’ ability (A), motivation (M), and opportunity (O)

to perform are key determinants of performance, the AMO model

posits that HR systems relate to firm performance through their

influence on these three elements (e.g., Becker & Huselid, 1998;

Delery & Shaw, 2001;Jiang, Lepak, Hu, & Baer, 2012;Lepak,

Liao, Chung, & Harden, 2006).

For example, HR practices (in-

cluding PM) might affect unit-level abilities or skills such as

adaptability, creativity, or potential (our skills/abilities/potential

category); and/or motivational capabilities, such as collective en-

gagement (Barrick, Thurgood, Smith, & Courtright, 2015) and

unit-level employee commitment and empowerment (Messersmith

et al., 2011). These unit-level capabilities (or HCRs), in turn, lead

to operational outcomes (see Figure 1).

Yet employee variables do not automatically become unit-level

HCRs. As Bliese (2000) notes “the main difference between a

lower-level and an aggregate-level variable...isthat the aggre-

gate variable contains higher-level contextual influences that are

not captured by the lower-level construct” (p. 369). In other words,

transfer variables and unit-level HCRs are only partially isomor-

phic, as they have different antecedents (Ployhart & Moliterno,

2011; and supported by our empirical review).

Related, Ployhart,

Nyberg, Reilly, and Maltarich (2014) distinguish between human

capital and human capital resources, defining the latter as unit-

level capacities that are accessible for unit-relevant purposes.

Thus, in our model we depict unit-level HCRs as resulting from

employee transfer variables yet moderated by accessibility-related

contextual factors. As the next section describes, our emergence

enablers category captures these key moderating influences.

Emergence Enablers

Central to the question of how unit-level HCRs are created from

individual-level criteria is the process of “emergence” (Ployhart &

Moliterno, 2011). Emergent phenomena “originate in the cogni-

tion, affect, behaviors, or other characteristics of individuals, [are]

amplified by their interactions, and manifest as higher-level, col-

lective phenomen[a]” (Kozlowski & Klein, 2000, p. 55). Thus, the

microfoundations of unit performance are not only employee

KSAOs but also the social and psychological mechanisms that

constitute this emergence enabling process (Li, Wang, van Jaars-

veld, Lee, & Ma, 2018;Ployhart & Moliterno, 2011). Our model

captures this important element, depicting emergence enablers as a

key moderator between employee transfer and unit-level HCRs (as

well as a direct determinant of HCRs and operational outcomes;

see Figure 1). Thus, to the extent that PM alters these emergence

enablers, it necessarily would result in the emergence of different

kinds of HCRs (Ployhart & Moliterno, 2011).

Three categories of emergence enablers were identified by Ploy-

hart and Moliterno (2011): behavioral processes (coordination,

communication, and regulatory processes that affect the interde-

pendence of employees, Kozlowski & Ilgen, 2006); cognitive

mechanisms (unit climate, memory, and learning, Hinsz, Tindale,

& Vollrath, 1997); and affective psychological states (the emo-

tional bonds that tie unit members together, such as cohesion and

trust). Using this conceptual framework, along with the empirical

PM literature, we identified the following unit-level outcomes of

PM that could be classified as emergence enablers (see Figure 1):

climate, culture, and leadership (per Rentsch, 1990, perceptions of

unit leadership is part of climate); trust in management; unit

learning and knowledge/information sharing; and team cohesion,

trust, and collaboration. We add an additional category of emer-

gence enablers, based on the role of managers in PM: the unit-level

quality of human capital decisions made. This is an aggregate of

the manager transfer criterion, quality of decisions made about

employees, and at the unit level we argue that it serves an impor-

tant enabling function for unit-level HCRs. As Ployhart et al.

(2014) have noted, human capital has to be sufficiently available

to the unit to be considered a resource; and the quality of human

capital decisions made determines the extent to which the unit can

actually leverage the potential HCRs (see Lakshman, 2014). Our

model argues that the quality of decisions made at the unit level,

through affecting the availability of human capital, is an important

moderator of the link between employee transfer criteria and

unit-level HCRs.

Unit-Level Operational and Financial Outcomes

Finally, our model includes organization-level performance and

separates this into operational and financial outcomes (see Figure

1). This follows the lead from research in strategic HR, which has

argued (although not always found) that operational outcomes are

more closely aligned with the improved employee capabilities

resulting from HR practices and therefore more strongly related to

such practices than are financial outcomes (Combs, Liu, Hall, &

Ketchen, 2006;Dyer & Reeves, 1995). Following researchers in

strategic HR, we identified the following unit-level operational

outcomes in the empirical PM literature (see Figure 1): labor

productivity, product quality, innovation, safety performance, cor-

porate social responsibility, turnover rates, absenteeism, and griev-

ances.

Per the strategic HR literature, these outcomes result in

Taking our lead from Ployhart and Moliterno (2011), we use the more

generic “unit” terminology; as these authors note, “by defining the level of

theory generically at the ‘unit level,’ [human capital] can exist at the group,

department, store, or firm level of analysis, with the relevant aggregation

of individual level KSAOs measured at the level that is theoretically and

empirically relevant” (p. 144).

Following Jiang et al. (2012), we exclude opportunity capabilities from

our model. As these authors note, ability and motivational capabilities are

the two most important mediating paths. In addition, there were no empir-

ical PM articles examining unit-level opportunity capabilities.

The various ways in which HCRs combine from individual constructs

(e.g., composition vs. compilation models) is outside the scope of our

model/article. This is discussed in Ployhart et al. (2014), and the interested

reader is referred there.

Some strategic HR research has used a category of organization per-

formance referred to as “HRM outcomes,” which includes unit-level con-

structs such as employee commitment, competence, quality, and turnover

(e.g., Beer, Spector, Lawrence, Mills, & Walton, 1984;Guest, 1987,1997;

Zheng et al., 2006). However, to us this seems to be a somewhat unclear

mix of HCRs and operational outcomes. Ployhart et al. (2014) note that

HCRs are “capacities for action, but they are not the action itself. There-

fore, studies that define human capital in terms of employee performance

behaviors are not studying HCRs but rather the results or outcomes of such

resources” (p. 390). Thus, we classify human capital capacities under

resources but human capital outcomes (such as unit-level performance,

productivity, turnover, etc.) as operational outcomes.

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858 SCHLEICHER, BAUMANN, SULLIVAN, AND YIM

part from unit-level HCRs (Daley, 1986;Kim, Atwater, Patel, &

Smither, 2016;Zheng, Morrison, & O’Neill, 2006). Regarding

financial outcomes, there are many ways to operationalize firm

financial performance (see Batt, 2002;Goh & Anderson, 2007),

but those examined in the PM literature have included return on

investment (ROI), return on assets (ROA), sales growth, firm

growth, and market competitiveness.

Here we want to clarify the meaning of the horizontal ar-

rangement of our model. That it ends with organizational out-

comes does not signify that these are the “ultimate criteria.”

Although some have argued that the overall purpose of PM is to

improve firm performance (e.g., DeNisi & Smith, 2014;DeNisi

& Sonesh, 2011), we argue that what is most relevant depends

on the goals of the PM system and the specific effectiveness

questions being asked (addressed in the final section of our

article). Thus, the positioning of organizational performance at

the end of our model should not be taken to imply its overar-

ching importance. Rather, our model is generally organized

from left to right in causal-logical sequence, from more micro

criteria to more macro criteria, which is the generally estab-

lished causal direction in training evaluation (Kirkpatrick,

1987) and multilevel research (Ostroff & Bowen, 2000), and

allows us to map the emergence process (Ployhart & Moliterno,

2011). It is possible that, over time, there could be reciprocal

relationships among components of the model; for example,

improved financial performance might lead an organization to

invest more into the PM system (see den Hartog et al., 2004).

However, this is distinct from the causal sequence linking more

proximal evaluative criteria to more distal evaluative criteria

(the focus of our model) and is therefore not discussed here.

Synthesis of Empirical PM Research

Vis-a`-Vis the Model

This section summarizes conclusions from our systematic and

comprehensive review of the empirical PM research from 1984–

2018 vis-a

`-vis the components of our evaluative criteria model.

Table 2 provides the frequencies of studies in each criterion

category, organized by timeframe; Table 3 provides a description

of specific variables examined, by criterion category. Rather than

reviewing this research in detail criterion by criterion (which

Appendix A does, provided for the interested reader), our discus-

sion here is organized along several broader themes we identified

in this empirical literature. The first section provides descriptive

information on how frequently various criteria are studied in the

PM literature and, based on our theoretical model, a discussion of

what else we should be examining as a result. The second section

summarizes what this empirical research suggests are the aspects

of PM that most impact its effectiveness. The third section reviews

empirical evidence for the criterion–criterion relationships impli-

cated in our model. Finally, the fourth section identifies method-

ological trends and limitations in this research and associated

recommendations for improvement. Each of these sections con-

tains some suggestions for future research based on the explicit

focus of the section. The final major section of the article goes

beyond these research suggestions to develop specific research

propositions tied to the longer value chains believed to underlie

PM effectiveness.

Differential Empirical Emphasis Across PM Criteria

and Time

An overall observation from our review is that there has been

unequal empirical attention across criteria (and across time). Table

2lists frequencies for each criterion category, organized by time-

frame; several trends are apparent here. First, employee reactions

(see Appendix A, section Ia) have become the most widely studied

outcome in the PM literature (more frequent even than rating

quality). Such research exploded following Murphy and Cleve-

land’s (1995, p. 310) claim that reactions were “neglected criteria”

in the PM literature and their inclusion in Cardy and Dobbins

(1994) model of PA effectiveness, and our review suggests that

this strong focus on reactions has continued post-2000. However,

managers’ reactions to PM (see Appendix A, section Ib) have

been studied much less often (only 16% of all reactions variables),

and this focus has in fact declined post-2000. Research suggests

that managers’ reactions to PM tend to differ substantially from

employees’ reactions (Manshor & Kamalanabhan, 2000;Taylor,

Pettijohn, & Pettijohn, 1999), perhaps due to differences in knowl-

edge of the PM system (Williams & Levy, 2000); and both play

important and distinct roles in our theoretical model. Thus, future

research should focus substantially more on manager reactions to

PM.

Second, empirical focus on employee transfer criteria in PM

(see Appendix A, section IV) has significantly increased post-2000

and in fact is essentially tied with employee reactions as the most

commonly studied criterion in the more recent literature. Our

review suggests transfer includes more than just task performance

(indeed, job attitudes were actually studied as often as perfor-

mance; see Table 2). Given that these constructs create the foun-

dation for unit-level HCRs (Ployhart & Moliterno, 2011;Ployhart

et al., 2014), this is a positive trend for understanding PM effec-

tiveness. At the same time, there are criteria we conceptualized as

part of employee transfer that have been studied infrequently,

including counterproductive behavior (cf., Tziner, Fein, Sharoni,

Bar-Hen, & Nord, 2010), employee creativity (cf., Jiang, Wang, &

Zhao, 2012), organizational attraction (cf., Blume, Rubin, & Bald-

win, 2013;Maas & Torres-González, 2011), and employee well-

being (e.g., burnout, stress, self-esteem, safety behaviors; cf.,

Culig, Dickinson, Lindstrom-Hazel, & Austin, 2008;Gabris &

Ihrke, 2001;Johnson & Helgeson, 2002;Milanowski, 2005). More

research should be directed to each of these transfer criteria and

also specific KSAOs, which are not typically examined as out-

comes of PM but which, per our conceptual model, have clear

relevance for unit-level HCRs.

Third, our review suggests a different story for learning criteria.

Regarding employee learning specifically (see Appendix A, sec-

tion II), there has been much less emphasis on this relative to

There are a number of moderators believed to affect the strength of the

relationship between unit-level HCRs and various measures of organiza-

tional performance (some argue, for example, that HCRs must be firm-

specific to result in improved organizational performance; Barney &

Wright, 1998). In the interest of space and parsimony, because these have

been reviewed in detail in other places (see e.g., Mahoney & Kor, 2015)

and because we view the primary contribution of our model not in what is

mapped out to the right of unit-level HCRs but rather how PM leads up to

unit-level HCRs, these moderators are outside the scope of our model and

review. Theoretically, they should not be unique to the PM context.

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859

EFFECTIVENESS OF PERFORMANCE MANAGEMENT

employee reactions or transfer (although the emphasis on em-

ployee learning has at least not declined post-2000). The sparse

empirical focus is at odds with the theoretical importance of

employee learning for subsequent attitudes, motivation and per-

formance (per our model). Indeed, such learning criteria have been

found to completely mediate the relationship between reactions to

performance feedback and one’s behavioral responses to it (Kin-

icki, Prussia, Wu, & McKee-Ryan, 2004). Regarding manager

learning specifically (see Appendix A, section III), although this

criterion appears to be frequently studied (see Table 2), that is

almost entirely a function of a continued disproportionate empha-

sis on rating quality specifically (which has remained post-2000).

As a field we know significantly less about other aspects of

managers’ learning from PM. For example, rater self-efficacy has

emerged as an important construct in the literature, and in our

model it is categorized as a manager learning criterion. Yet most

of the extant research in this area has considered it primarily as an

individual difference that predicts other aspects of PM. We suggest

the need for more research—such as Tziner and Kopelman (2002)

and Wood and Marshall (2008)—that examines the PM system

Table 2

Frequency of Criteria Across All PM Studies

Criterion category

Across all studies 1984–2000 2001–2018

ⴱ

⫽768) (n⫽334) (n⫽434)

Count Percent Count Percent Count Percent

Employee 454 59.11 178 53.29 276 63.59

Reactions 230 29.95 106 31.74 124 28.57

Cognitive 106 13.80 52 15.57 54 12.44

Satisfaction 69 8.98 37 11.08 32 7.37

Utility 39 5.08 13 3.89 26 5.99

Affective 16 2.08 4 1.20 12 2.76

Learning 56 7.29 25 7.49 31 7.14

Cognitive 12 1.56 6 1.80 6 1.38

Skills-based 16 2.08 7 2.10 9 2.07

Attitudinal/motivational 28 3.65 12 3.59 16 3.69

Transfer 168 21.88 47 14.07 121 27.88

Job attitudes 57 7.42 19 5.69 38 8.76

Performance 57 7.42 17 5.09 40 9.22

Withdrawal 20 2.60 4 1.20 16 3.69

Fairness/justice 11 1.43 2 .60 9 2.07

Motivation 13 1.69 5 1.50 8 1.84

CWBs 1 .13 — — 1 .23

Employee creativity 2 .26 — — 2 .46

Organizational attraction 2 .26 — — 2 .46

Employee well-being 5 .65 — — 5 1.15

Manager 241 31.38 130 38.92 111 25.58

Reactions 45 5.86 24 7.19 21 4.84

Cognitive 17 2.21 10 2.99 7 1.61

Satisfaction 14 1.82 9 2.69 5 1.15

Utility 7 .91 — — 7 1.61

Affective 7 .91 5 1.50 2 .46

Learning 167 21.74 90 26.95 77 17.74

Cognitive 9 1.17 4 1.20 5 1.15

Skills-based 32 4.17 19 5.69 13 3.00

Attitudinal/motivational 7 .91 3 .90 4 .92

Rating quality 119 15.49 64 19.16 55 12.67

Transfer 29 3.78 16 4.79 13 3.00

Quality of relationships with

employees 20 2.60 12 3.59 8 1.84

Quality of decisions made for

employees 8 1.04 3 .90 5 1.15

Managerial effectiveness 1 .13 1 .30 — —

Emergence enablers 52 6.77 21 6.29 31 7.14

Climate and culture 31 4.04 10 2.99 21 4.84

Knowledge sharing 4 .52 2 .60 2 .46

Team cohesion/trust and collaboration 12 1.56 8 2.40 4 .92

Quality of human capital decisions 5 .65 1 .30 4 .92

Affect/mood ——————

Unit-level 21 2.73 5 1.50 16 3.69

Human capital resources 2 .26 — — 2 .46

Operational outcomes 5 .65 1 .30 4 .92

Financial outcomes 14 1.82 4 1.20 10 2.30

ⴱ

n(and count) refers to the number of instances of each criterion, across studies. These numbers are more than the 544 studies included due to some studies

measuring multiple performance management (PM) criteria. Percentages reflect column totals for each of the three time periods.

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860 SCHLEICHER, BAUMANN, SULLIVAN, AND YIM

Table 3

Summary of Empirical PM Research by Component

Model components

and subcategories Variables and sample research

PM reactions

Manager

Cognitive Fairness/justice (Williams & Levy, 2000)

Satisfaction Appraisal satisfaction (Williams & Levy, 2000)

Utility Utility of feedback (Erdemli, Sümer, & Bilgiç, 2007)

Affective Discomfort with PA (Saffie-Robertson & Brutus, 2014)

Employee

Cognitive Perceived fairness/justice (Taylor, Tracy, Renard, Harrison, & Carroll, 1995)

Perceived accuracy (Kinicki, Prussia, Wu, & McKee-Ryan, 2004)

Acceptance of PM (Hedge & Teachout, 2000)

Perceived quality of feedback (Anseel, Lievens, & Schollaert, 2009)

Satisfaction Satisfaction with PM (Nathan, Mohrman, & Milliman, 1991)

Utility Perceived utility of feedback (Elicker, Levy, & Hall, 2006)

Utility of PA (Payne, Horner, Boswell, Schroeder, & Stine-Cheyne, 2009)

Affective Discomfort with PA (Spence & Wood, 2007)

Negative and positive emotions (David, 2013)

PM learning

Manager

Cognitive Idiosyncratic performance standards (Schleicher & Day, 1998)

Performance schema accuracy (Gorman & Rentsch, 2009)

Understanding employee strength/weakness (Selden, Sherrier, & Wooters, 2012)

Managerial knowledge of PA (Davis & Mount, 1984)

Memory strength (Martell & Leavitt, 2002)

Understanding one’s contribution to unit objectives (Mabey, 2001)

Skills-based Effectiveness in completing PA forms (Davis & Mount, 1984)

Taking better notes (Mero, Motowidlo, & Anna, 2003)

Behavioral specificity in evaluation comments (Macan et al., 2011)

Performance information recall ability (DeNisi & Peters, 1996)

Effectiveness of supervisor appraisal behavior (Eberhardt & Pooyan, 1988)

Attitudinal/motivational Agreement with org. performance theories (Schleicher & Day, 1998)

PA self-efficacy (Tziner, Murphy, Cleveland, & Roberts-Thompson, 2001;Wood & Marshall, 2008)

Self-serving motives (Goerke, Möller, Schulz-Hardt, Napiersky, & Frey, 2004)

Rating quality Error, biases, and accuracy (Cardy & Dobbins, 1994)

Reliability and validity criteria (Aguinis, 2013)

Employee

Cognitive Awareness of development opportunities (Boswell & Boudreau, 2002)

Task thoughts (Harackiewicz, Abrahams, & Wageman, 1987)

Self-awareness (Morgan, Cannan, & Cullinane, 2005)

Role clarity (Prince & Lawler, 1986)

Perceived benefits of development (Linderbaum & Levy, 2010)

Skills-based Way in which employees do their work (Morgan et al., 2005)

Feedback sharing between peers (Wang, 2007)

Feedback seeking (Linderbaum & Levy, 2010)

Attitudinal/motivational Desire to participate in PA (Langan-Fox, Waycott, Morizzi, & McDonald, 1998)

View of how the PM system aids in performance (Harris, 1988)

Motivation to improve (Harackiewicz et al., 1987)

Intended future use of development (Boswell & Boudreau, 2002)

Goal clarity, acceptance, and commitment (Tziner & Kopelman, 1988)

Self-efficacy (Bartol, Durham, & Poon, 2001)

Intentions to change behavior (Johnson & Helgeson, 2002)

Transfer

Manager

Quality of relationship with employees Trust in manager (Korsgaard, Roberson, & Rymph, 1998)

Supervisor liking/satisfaction (Kacmar, Wayne, & Wright, 1996)

LMX (Dahling, Chau, & O’Malley, 2012)

Quality of the coaching relationship (Gregory & Levy, 2012)

Perceived supervisor support (Armstrong-Stassen & Schlosser, 2010)

Employee-supervisor working relationship (McBriarty, 1988)

Confidence in collaborating with manager (Tjosvold & Halco, 1992)

Cooperation with supervisor (Taylor & Pierce, 1999)

Quality of decisions made about employees Quality of decisions on job assignment/resource utilization (McBriarty, 1988)

Accuracy of personnel decisions (Jawahar, 2001)

Managerial effectiveness Perceptions of supervisor effectiveness (Burke, 1996)

Employee

Job attitudes Job satisfaction (Lam, Schaubroeck, & Aryee, 2002;Nathan et al., 1991)

Organizational commitment (Lam et al., 2002;Pearce & Porter, 1986)(table continues)

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EFFECTIVENESS OF PERFORMANCE MANAGEMENT

Table 3 (continued)

Model components

and subcategories Variables and sample research

Perceived organizational support (Masterson, Lewis, Goldman, & Taylor, 2000)

Job embeddedness (Bambacas & Kulik, 2013)

Role ambiguity (Youngcourt, Leiva, & Jones, 2007)

Performance Overall performance (Klein & Snell, 1994)

Task performance (Nathan et al., 1991;Prince & Lawler, 1986)

OCB (Findley, Giles, & Mossholder, 2000;Masterson et al., 2000;Norris-Watts & Levy, 2004)

Withdrawal Intention to turnover (Brown, Hyatt, & Benson, 2010)

Intention to remain (Taylor et al., 1995)

Turnover (Milanowski, 2005)

Fairness/justice Procedural justice (Lam et al., 2002;Masterson et al., 2000)

Distributive justice (Cheng, 2014;Lam et al., 2002)

Interactional justice (Linna et al., 2012;Masterson et al., 2000)

Motivation Intrinsic/extrinsic motivation (Sundgren, Selart, Ingelgård, & Bengtson, 2005)

Employee engagement (Gruman & Saks, 2011)

Motivation to work hard (Tjosvold & Halco, 1992)

Motivation to improve (Taylor et al., 1995)

Effort on the job (Taylor & Pierce, 1999)

CWBs Deviant behavior (Tziner, Fein, Sharoni, Bar-Hen, & Nord, 2010)

Employee creativity Employee creativity (Jiang, Wang, & Zhao, 2012)

Organizational attraction Organizational attractiveness (Blume, Rubin, & Baldwin, 2013)

Employee well-being Burnout (Gabris & Ihrke, 2001)

Stress (Milanowski, 2005)

Self-esteem (Johnson & Helgeson, 2002)

Safety behaviors (Culig, Dickinson, Lindstrom-Hazel, & Austin, 2008)

Emergence enablers

Climate and culture Office morale (Burke, 1996)

Unit-level satisfaction (Daley, 1986;Mullin & Sherman, 1993)

Support culture (Mamatoglu, 2008)

Perceived psychological contract fulfillment (Raeder, Knorr, & Hilb, 2012)

Ethical climate (Guerci, Radaelli, Siletti, Cirella, & Rami Shani, 2015)

Creative climate (Sundgren et al., 2005)

Knowledge and information sharing Communication atmosphere of the unit (Mamatoglu, 2008)

Knowledge sharing of R&D employees (Liu & Liu, 2011)

Knowledge management effectiveness (Tan & Nasurdin, 2011)

Organizational learning (Wang, Tseng, Yen, & Huang, 2011)

Team cohesion trust, and collaboration Team cohesion (McBriarty, 1988;Rowland, 2013)

Trust for top management (Mayer & Davis, 1999)

Quality of human capital decisions Effectiveness for influencing performance (Lawler, 2003)

Effectiveness for differentiating top/poor performer (Lawler, 2003)

Human capital (Unit-level)

Employee skill/abilities/potential capabilities Adaptability/flexibility (Mullin & Sherman, 1993)

Performance potential of workforce (Scullen, Bergey, & Aiman-Smith, 2005)

Workforce quality (Giumetti, Schroeder, & Switzer, 2015)

Employee’s knowledge about how work and strategy aligns (Ayers, 2013)

Employee motivation Employee motivation (Roberts, 1995)

Capabilities Staff commitment (Rao, 2007)

Operational outcomes

Labor productivity Labor productivity (Roberts, 1995;Kim, Atwater, Patel, & Smither, 2016)

Productive quality or quantity Attainment of quality (Waite, Newman, & Krzystofiak, 1994)

Production (Zheng, Morrison, & O’Neill, 2006)

Production quality (Lee, Lee, & Wu, 2010)

Organizational innovation Administrative/process/product innovation (Tan & Nasurdin, 2011)

Administrative/technological innovation (Jiang et al., 2012)

Safety performance Safety behavior (Laitinen & Ruohomäki, 1996)

Number and rate of occupational injuries/accidents (Reber & Wallin, 1994)

CSR Perceived CSR (Daley, 1986)

Collective turnover Turnover rate (Batt, 2002)

Absenteeism Absenteeism (Roberts, 1995)

Others Perceived organizational performance (Daley, 1986;Rodwell & Teo, 2008)

Financial outcomes

ROI ROI (Goh & Anderson, 2007)

Firm growth Sales growth (Batt, 2002)

Competitiveness Market competitiveness (Zheng et al., 2006)

Note. PM ⫽performance management; PA ⫽performance appraisal; OCB ⫽organizational citizenship behavior; LMX ⫽leader-member exchange;

ROI ⫽return-on-investment; CSR ⫽corporate social responsibility.

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862 SCHLEICHER, BAUMANN, SULLIVAN, AND YIM

antecedents of rater self-efficacy, to understand how aspects of PM

can actually build such PM-related self-efficacy in managers.

More generally, the importance of these types of learning out-

comes will only increase over time, given the move toward more

development-focused PM.

Fourth, the empirical emphasis on manager transfer (see Ap-

pendix A, section V)—which is not widespread overall—has

unfortunately declined somewhat post-2000 (see Table 2). Espe-

cially needed is additional work on the quality of managers’

employee-related decisions and how this is impacted by aspects of

PM. This serves as an important building block for unit-level

HCRs, yet we found only a few studies examining this criterion.

Especially important will be longitudinal designs that capture the

implications of PM changes (e.g., eliminating ratings, Adler et al.,

2016) on managers’ decisions. The assumption is that improved

PM processes increase the quality of HR decisions, but this is

largely an untested assumption in the literature.

Fifth, unit-level criteria (see Appendix A, sections VI., VII., and

VIII) have not been as frequently studied overall as the other

criteria, but fortunately this focus has increased post-2000 (see

Table 2). This trend is especially notable for operational and

financial measures of firm performance, and it may largely be due

to strategic HR researchers beginning to focus on PM. Regardless,

it is a positive trend for understanding the overall effectiveness of

PM. At the same time, future research needs to examine other

relevant aspects of organizational performance that have received

less attention (see Appendix A, section VIII). For example, griev-

ances are listed in our model of operational outcomes (and likely

are significantly impacted by the type of PM system; see Payne &

Mendoza, 2017), but we could find no empirical research in this

area. Future unit-level PM research also needs to focus on addi-

tional emergence enablers (see Appendix A, section VII). Our

model specifies the quality of human capital decisions made as

critical in this regard (as it affects the unit’s ability to leverage

human capital and thus both should determine the amount of HCRs

available as well as moderate the link between individual-level

human capital and unit-level human capital), yet we found only

one study in this area.

The Most Impactful Aspects of PM

The previous section reviewed the prevalence of the criteria

themselves in the empirical literature. This section concerns the

question of what aspects of PM (i.e., the IVs) are most impactful

for PM effectiveness based on this literature, and our overall

observation is that the answer appears to vary across the types of

evaluative criteria (see Appendix A for details). As noted in the

introduction, to synthesize these findings we rely on Schleicher et

al.’s (2018) systems-based taxonomy of the IVs of PM, which

identifies the following six main components of PM systems: tasks

(the activities involved in PM, including setting performance ex-

pectations, observing performance, integrating performance infor-

mation, rendering a formal performance evaluation, generating and

delivering performance feedback, the formal performance review

meeting, and performance coaching); inputs (e.g., environmental

context, strategy); individuals (characteristics of the people in-

volved in the PM tasks, especially employees and managers);

formal processes (formal procedures for how the PM tasks are

conducted; the PM methods and approaches); informal processes

(unwritten or implicit elements that emerge over time, e.g., infor-

mal feedback norms); and outputs (e.g., performance ratings, feed-

back generated, creation of a development plan, career planning,

administrative recommendations).

Our empirical review shows that employee reactions (see Ap-

pendix A, section Ia) are most influenced by informal processes,

with research suggesting pretty clearly that more positive cognitive

and utility reactions (as well as greater satisfaction) result when

employees participate in the PM process, when they have knowl-

edge about how the process works, and when they believe their

supervisors are unbiased and fair. In fact, it appears that percep-

tions of fairness and accuracy in PM may depend as much on trust

in the supervisor as on characteristics of the PM process itself (e.g.,

Fulk, Brief, & Barr, 1985). On the other hand, our review suggests

that manager reactions (see Appendix A, section Ib) are more

influenced by formal processes, include rating approach (e.g., Dale

et al., 2013;Schleicher, Bull, & Green, 2009), as well as by

managers’ individual factors (e.g., previous PM experience, per-

sonality).

For employee learning criteria (see Appendix A, section II),

both informal processes (e.g., delivery of feedback) and formal

processes (e.g., type of evaluation) are important for motivational

and skills-based learning. For manager learning criteria (see Ap-

pendix A, section III), formal processes appear most impactful,

especially rater training. In fact, this focus characterizes the bulk of

research in this area, and more work is needed on other aspects of

PM likely to result in significant learning for managers, such as the

experience of rating or the feedback session with employees. There

is also some evidence that individual factors play a role here, but

that is generally confined to effects on rating quality criteria.

For employee transfer (see Appendix A, section IV), overall the

research suggests that the effects of PM can in fact transfer beyond

the immediate PM context, to affect more general employee atti-

tudes and behaviors. Yet what PM aspects are most impactful in

this regard varies a bit across specific transfer criteria. For exam-

ple, turnover intentions (see Appendix A., section IVc) are partic-

ularly impacted by due process elements of PM (implicating both

formal and informal processes) and the reactions that accompany

them. Both formal and informal processes are also important for

fairness/justice perceptions (see Appendix A, section IVe). Yet for

employee motivation (see Appendix A, section IVd), it appears to

be the task components of goal-setting and feedback (components

of more developmentally oriented PM systems) that appear most

impactful, not specific processes (formal or informal) within these

tasks. For manager transfer (especially the quality of relationship

with employees, see Appendix A., section Va), our review again

shows that both informal and formal PM processes can impact

these relationships, either positively or negatively.

Finally, for unit-level criteria, the IV is usually the PM system

(as opposed to components or processes of PM), especially given

that such investigations are often conducted by strategic HR re-

searchers. For example, the research on HCRs (see Appendix A,

section VI) shows that PM systems (and FDRS systems specifi-

cally) can impact both ability-based and motivation-based HCRs

(sometimes positively and sometimes negatively). Research has

shown that emergence enablers too (see Appendix A, section VII)

can result from the implementation of new PM systems and the

general type of PM system (“high quality” PM, Searle & Ball,

2003). There is a clear need for future research to try to link more

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863

EFFECTIVENESS OF PERFORMANCE MANAGEMENT

specific processes or other components within PM systems to

unit-level criteria. Related, we have observed in our review that the

strategic HR research, especially that examining PM as part of HR

bundles, tends to take a very simplistic approach to the measure-

ment of PM systems (e.g., the percentage of employees who

receive a formal PA). We believe strongly that a fuller understand-

ing of the relationship between PM and firm performance requires

a much more nuanced approach to measuring the PM construct.

For example, the fact that research has been equivocal on the link

between PM and creativity (e.g., Zhou & Shalley, 2003) can be

explained by the strong likelihood that this relationship is deter-

mined not by the existence of PM, but rather by the type of PM.

Relationships Among Evaluative Criteria

Unfortunately, our review revealed insufficient empirical re-

search exploring any of the longer mediational relationships in our

model of evaluative criteria (per Figure 1); consequently, these are

discussed at primarily a theoretical level in the final section of our

article, which lays out specific propositions for some key value

chains implicated in our model. However, there is research that has

reported bivariate relationships among our evaluative criteria (of-

ten as incidental, as opposed to focal, results). We coded such

relationships as part of our comprehensive review and then com-

puted the average sample-weighted correlation for any criterion–

criterion relationships with at least two samples. Figure 2 reports

these correlations linking the evaluative criteria in our model, and

Appendix B describes these findings in more detail. For the most

part these results show sizable positive relationships between

adjacent criteria and support the theoretical linkages between

model components previously discussed. Although some of these

estimates are based on a small number of samples, and many of

them are likely inflated from same-source/-method data, we still

feel reporting these criterion–criterion estimates is useful for this

review, particularly in terms of providing some preliminary evi-

dence to serve as a foundation for the value chains discussed in the

final section.

How We Study PM Criteria

In this final section of observations from our empirical review,

we discuss several needed improvements in how we study PM

effectiveness, including the measurement and conceptualization of

criteria; the use of stronger designs and field contexts; and the

simultaneous examination of employees and managers. Future

research will need to improve in each of these areas in order to

advance cumulative knowledge of PM effectiveness.

Measuring and conceptualizing criteria. From our empiri-

cal review we conclude that greater care must be taken in both the

conceptualization and measurement of specific evaluative criteria.

We highlight two examples here. First, our review revealed that

the distinction between reactions and learning is not always clearly

articulated in the PM literature. For example, a closer examination

of an article purporting to measure feedback reactions (Johnson &

Helgeson, 2002) shows that three distinct “reactions” variables

were measured: agreement with the feedback, changes in self-

esteem, and intentions to change behavior. Whereas the first is

categorized as reactions in our model, the second and third would

be considered learning. Similarly, Tziner, Latham, Price, and Hac-

coun (1996) examined a “usefulness for employee development”

criterion by measuring employee satisfaction (a reactions criterion)

as well as goal perception and the quality of goals set (both

learning criteria in our model). These distinct types of criteria are

likely to behave differently, a possibility supported by the different

PM-Related

Reactions PM-Related

Learning

Manager

Transfer

Human Capital

Resources

Operational

Outcomes

Employee Manager

Unit-level

Emergence

Enablers

Financial

Outcomes

r=.29 (k=24)

r=.23 (k=9) r=.38 (k=9)

r=.14 (k=7) r=.53 (k=3)

r=.30 (k=2)

r=.51 (k=3)

r=.37 (k=4)

1 3

PM-Related

Reactions PM-Related

Learning

Employee

Transfer

Figure 2. Average bivariate correlations between criterion categories.

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864 SCHLEICHER, BAUMANN, SULLIVAN, AND YIM

results across variables in these two studies. We would encourage

future researchers to avoid using more generic “reactions” labels

for variables conceptually closer to learning criteria (including

“buy-in” or commitment to the PM system). This advice is par-

ticularly important in light of the criterion–criterion relationships

reported in Figure 2. These show relationships between reactions

and learning of r⫽.23 and .14 only (for employees and managers,

respectively), suggesting these are clearly distinct (albeit related)

constructs. These results also show employee learning has a some-

what stronger relationship with employee transfer than does em-

ployee reactions, again affirming the need to accurately indicate

whether one is measuring reactions or learning.

Second, our review also revealed a need to more clearly con-

ceptualize and operationalize types of firm performance as an

outcome of PM. We found a number of articles that examined

aspects of organizational performance that could not be clearly

categorized (see Appendix A, section VIII). Although almost all of

these studies show a positive impact of PM on organizational

performance, these types of measures and the related methods

seem problematic for drawing clear conclusions. In particular,

perceptions of organizational effectiveness (e.g., from HR execu-

tives or managers) are suspect as measures of actual effectiveness.

Using stronger research designs and contexts. There were a

number of PM studies using relatively weak methods. This may

explain why some criteria showed more equivocal results, such as

with employee transfer (see Appendix A, section IV). Much of the

research on transfer criteria was characterized by weaker designs

(including common method issues, especially with job attitudes

and fairness as transfer outcomes). We would also argue that

transfer criteria, by definition, should probably not be studied in

the lab (e.g., Holbrook, 1999).

Other criteria with an overreliance on lab research were learning

and managerial transfer. A lot of the research on cognitive learning

outcomes for employees has been conducted in the lab; such

findings should be replicated in field studies, as our review sug-

gests that effects are often smaller in these settings (e.g., Boswell

& Boudreau, 2002;Morgan, Cannan, & Cullinane, 2005;Tjosvold

& Halco, 1992). For managerial learning, over 50% of cognitive

learning research (and almost 50% of skills-based learning re-

search) has been conducted in the lab with students; thus, many of

the results discussed in Appendix A (section III) need to be

replicated with managers in organizational settings who may ex-

perience greater cognitive load and additional constraints and thus

different learning processes. Even in the lab, increased attentional

demands meant to emulate actual work settings have been found to

affect results (e.g., Martell, 1991); this is likely even more pro-

nounced with managers in the field. Finally, nearly one third of the

quality of relationship studies (under managerial transfer) were

conducted in the lab, which is concerning because this then typi-

cally represents a hypothetical (i.e., “paper people”) or extremely

short-term (formed within hours or minutes) relationship. As such,

it is unclear whether these findings would generalize to complex

workplace relationships.

Learning criteria were also prone to common-method issues

(cross-sectional, single-source designs), especially cognitive learn-

ing and its relation to employee transfer (attitudinal/motivational

learning research was much more likely to employ time-lagged or

experimental designs than other learning). In addition, the vast

majority of skills-based learning research employs self-report for

this outcome; this is contrasted with the approach in the training

literature, where skills-based learning often relies on observation

by others (Kraiger et al., 1993). Incorporating others’ reports of

employees’ PM learning will be important for future research in

this area. With regard to manager learning, we found it interesting

that research on rating quality (often as a result of rater training)

was actually more likely than other forms of PM-related learning

to use time-lagged, longitudinal, or quasi-experimental designs.

Unfortunately, most of the field research on other aspects of

manager learning relied on single-source, cross sectional surveys.

These methodological issues for learning criteria need to be

strengthened in future research. However, the most glaring issues

of weak methodologies involved the unit-level criteria, where

many of the studies use cross-sectional, single-source surveys.

Simultaneously examining employees and managers. A fi-

nal need for future research is to measure both employee and

manager criteria within the same study. Failure to do so was a

primary limitation observed in the reactions literature in particular.

For the quality of relationships as a PM criterion, although both

employees (e.g., Dahling, Chau, & O’Malley, 2012;Taylor &

Pierce, 1999) and managers (e.g., Taylor et al., 1995) have been

used across studies as sources for measuring such quality, no

single study has collected these relational criteria from both per-

spectives. This is problematic because the same PM factor (e.g.,

more frequent negative feedback) may differentially impact the

manager-employee relationship, depending on perspective. Similar

concerns have been cited in other manager–employee dyadic

research (e.g., Matta, Scott, Koopman, & Conlon, 2015). PM

research should also broaden to examine the reactions and behav-

iors of managers who are also ratees/employees of their own

supervisors (Langan-Fox, Bell, McDonald, & Morizzi, 1996). We

know that managers’ experiences as recipients of PM can affect

their reactions and behavior while executing PM (see Latham,

Budworth, Yanar, & Whyte, 2008), and we need additional re-

search on such role duality.

An Agenda for PM Effectiveness Research and

Practice: Understanding Key Value Chains

The previous sections suggest that although a lot of research has

examined the impact of PM on separate evaluative criteria, there

has been very little explicit focus on how the multiple criteria are

interrelated and link together to form the “value chains” of PM.

Thus, in this final section of our integrative review, we explicitly

consider the longer value chains underlying PM effectiveness. This

is not meant to be exhaustive with regard to all possible linkages

in our model. Rather we organize our discussion of specific link-

ages around three questions with particular import for theory and

practice: (a) How do individual-level outcomes of PM emerge to

become unit-level outcomes? (b) How essential are positive reac-

tions to the overall effectiveness of PM? and (c) What is the value

of a performance rating? For each question we identify several

propositions (listed in Table 4) that could and should be tested in

future research and discuss the implications for the practice of PM

in organizations (summarized in Table 5). As such, this section

serves to illustrate how our model might be used productively by

both researchers and practitioners to make grounded hypotheses

about the PM value chains.

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EFFECTIVENESS OF PERFORMANCE MANAGEMENT

How Do Individual-Level Outcomes of PM Emerge to

Become Unit-Level Outcomes?

The link between PM systems and firm performance has been

severely underspecified (empirically and conceptually) in the re-

search literature (DeNisi & Smith, 2014). Our model can help shed

light on this link and in turn also meaningfully contribute to the

broader strategic HR literature, which has long been interested in

better understanding the mediational processes (the so-called

“black box”) linking HR practices with organizational perfor-

mance (Becker & Huselid, 2006;Messersmith et al., 2011). We

discuss two aspects of these mediational processes here: the rela-

tionship between individuals and unit-level HCRs, and the role of

emergence enablers.

Individuals and unit-level HCRs. Like others (e.g., Daley,

1986;Kim et al., 2016;Zheng et al., 2006), we suggest that

organizational performance is a function of unit-level HCRs, in

this case HCRs that eventually emerge from aspects of PM pro-

cesses. Ployhart and colleagues (Ployhart & Moliterno, 2011;

Ployhart et al., 2014) argue that unit-level human capital has its

origins in the full range of individual KSAOs. Unique to our model

is the observation and acknowledgment that this full range of

individual KSAOs includes both PM-specific KSAOs (those cri-

teria in our learning category, such as increased self-awareness and

increased feedback-seeking) as well as broader job and organiza-

tionally relevant constructs (captured in our transfer category,

including job attitudes, motivation, and performance). We argue

that the impact of PM on unit-level HCRs operates through both

types of criteria. Thus, our first proposition (see Table 4) recog-

nizes the dual nature of the individual source underlying unit-level

HCRs. This line of thinking suggests that PM may positively

impact unit-level outcomes even if it does not improve employee

performance. This is interesting given the frequent assertion that

such improvement is the ultimate goal (e.g., DeNisi & Pritchard,

2006) and “has been the major focus” of PM (DeNisi & Smith,

2014, p. 133). Future research should empirically address this

possibility.

Future research should also examine whether performance im-

provement (individual and/or unit levels) with PM is due to in-

creases in competencies and skills or primarily to attitudinal or

motivational effects. AMO researchers have suggested that the

effects of PA on performance are primarily through motivation,

and have consistently categorized PA as a motivation-enhancing

HR practice as opposed to an ability/skills-enhancing HR practice

(e.g., Chuang & Liao, 2010;Delery & Doty, 1996;Gong, Law,

Chang, & Xin, 2009). Yet our review actually shows greater

research support for the impact of PM on ability-based unit-level

Table 4

Specific Propositions Underlying the PM Value Chains

How do individual-level outcomes of PM emerge to become unit-level outcomes?

Proposition 1: Both employee transfer and employee learning criteria can become unit-level HCRs. Effects of learning criteria on unit-level human

capital may be partially mediated by transfer criteria but are unlikely to be fully mediated.

Proposition 2: PM is likely to lead to organizational performance outcomes via both ability-based unit-level HCRs and motivation-based unit-level

HCRs.

Proposition 3: Emergence enablers are an important moderator between employee learning and transfer criteria, and unit-level HCRs. When

emergence enablers are nonexistent or weak, these individual criteria are less likely to emerge as unit-level HCRs.

Proposition 4: The relationship between PM and organizational performance is mediated by (a) an “individual path,” whereby employee criteria

(learning and transfer) mediate this relationship, and this link is moderated by emergence enablers; and by (b) an “emergence path,” whereby

emergence enablers mediate this relationship.

Proposition 5: Manager transfer criteria are related to unit-level HCRs in multiple ways, including (a) via the impact on employee transfer (for both

relationship and decision effectiveness criteria); (b) via the emergence enabler of unit-level quality of human capital decisions made (for manager

decision effectiveness criteria); and (c) via other emergence enablers such as climate and trust in management (for manager relationship

effectiveness criteria).

How essential are positive reactions to the overall effectiveness of PM?

Proposition 6: The relationship between employee reactions and unit-level criteria is mediated by (a) employee learning, (b) employee transfer, and

Proposition 7: Employee reactions should predict employee learning, with moderately-sized positive relationships.

Proposition 8: Employee learning outcomes are likely to at least partially mediate the relationship between employee reactions and employee

transfer criteria.

Proposition 9: It is unlikely that positive employee reactions to PM are essential (i.e., a necessary condition) for learning.

Proposition 10: Employee reactions should be moderately and positively related to employee transfer. These relationships are likely to be stronger

for job attitudes and employee well-being than they are for performance and other behaviors.

Proposition 11: It is unlikely that employee reactions are essential (i.e., a necessary condition) for employee transfer.

Proposition 12: Relationships between employee reactions and other criteria are likely to vary based on the nature of the reactions (affective vs.

cognitive vs. utility). Relationships with transfer are likely to be strongest for utility and fairness (cognitive) reactions. Fairness may be more

important than utility reactions for turnover intentions specifically.

Proposition 13: Managers’ PM-related learning is likely to be more strongly related to manager transfer and unit-level criteria than are managers’

reactions. The effects of managers’ reactions on transfer and unit-level criteria are likely to be mediated by managers’ PM-related learning.

What is the value of a performance rating?

Proposition 14: Engaging in the rating process can have a positive impact on managers’ PM-related learning.

Proposition 15: Eliminating performance ratings will increase the strength of the relationship between managers’ PM-related learning and other

criteria

Proposition 16: The quality of human capital decisions (an emergence enabler) is likely to be lower in the absence of performance ratings, thus

weakening the relationship between employee transfer criteria and unit-level HCRs and negatively impacting unit-level HCRs directly.

Note. PM ⫽performance management; HCR ⫽human capital resources.

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866 SCHLEICHER, BAUMANN, SULLIVAN, AND YIM

Table 5

Key Practical Implications of Our Review

Organizations must first identify the relevant criteria for evaluating PM based on their objectives.

• There is no “ultimate criterion” for evaluating PM.

• The most relevant criteria depend on the objectives of the PM system and the specific effectiveness questions being asked. Objectives should be

based on an organization’s strategy and key stakeholders and tied to the various purposes of PM (e.g., administrative, developmental).

• For example:

Xan emphasis on employees as stakeholders would suggest a focus on well-being outcomes (employee transfer) as criteria, whereas an emphasis

on top management as stakeholders (or a push to establish clear financial returns from investment in PM) would suggest a focus on

organizational performance outcomes; and

Xmore developmental approaches to and purposes for PM would suggest a greater emphasis on learning criteria.

Organizations must measure more than one criterion category in evaluating their PM systems.

• Regardless of objectives for the PM system, it is unlikely that a single component in our evaluative model can provide a complete evaluation

picture for organizations.

• This is especially true given the equifinality inherent in overall PM effectiveness.

• With interest in more distal criteria (e.g., organizational performance), measuring more proximal (intermediary) criteria becomes essential for both

understanding how the distal criteria did (or did not) manifest and ruling out alternative explanations for changes in such distal outcomes.

Organizations must measure more than one dimension within a criterion category in evaluating PM.

• Similar to the above, it is very unlikely that a single reactions, or learning, or transfer measure, for example, can provide a complete picture for

organizations of the impact of PM on that criterion category.

• With reactions, for example, measures need to go beyond basic satisfaction; fairness (cognitive) and utility-based reactions in particular appear

quite impactful and should be included.

• The dimensions measured should also include a focus on specific referents (e.g., the feedback meeting, the manager’s role in this), not just the

PM system overall, as data on specific referents are more helpful for improving the system.

Organizations must collect evaluation data from multiple sources.

• In particular, both employees and managers should be included in evaluation of PM (and, because their perspectives vary, data should be coded

for source). This is especially important in measuring reactions, where managers have been significantly ignored relative to employees.

• Data from multiple sources is also key for learning criteria, where too often the emphasis has been on self-report. A complete view of learning

must include observation by others.

Organizational interventions aimed at improving PM should focus on different levers based on the relevant criteria of interest.

• Our review shows that the aspects of PM that exert the biggest influence differ across the evaluative criteria. For example:

Xemployee reactions are particularly influenced by informal processes (e.g., employee participation in PA, trust in supervisor);

Xmanager reactions are particularly influenced by formal processes (e.g., rating approach);

Xemployee turnover intentions are particularly impacted by due process elements (perceived fairness), not perceived value of PM; and

Xemployee motivation is particularly impacted by provision of goal-setting and feedback.

• Organizations should use this information to choose the levers likely to be most impactful in improving criteria of interest.

Organizations should focus substantially more on learning criteria in evaluating PM systems.

• Learning criteria represent the greatest untapped potential in evaluating PM. This criterion category (for both employees and managers) involves

more than just rating quality, and it serves as a key mediator in our model, linking to more distal criteria. For example:

Xwhat employees learn from PM (especially in terms of attitudinal and motivational learning) can transfer into improved attitudes and

performance back on the job; and

Xmanagers’ PM-related learning can impact both employees’ attitudes and performance as well as the quality of decisions managers make. In

fact, our review suggests it may be more important that managers “do PM well” (learning) than that they react positively to PM.

• The importance of learning outcomes in general will only increase over time, given the move towards more development-focused PM.

Organizations should rethink what reactions criteria mean and how they should be managed.

• Organizations appear singularly focused on employee reactions to PM, which are often negative (and cited as a reason for change). Yet our review shows

that positive reactions, although relevant, are just one of many criteria of interest and are not, in fact, essential for PM effectiveness.

• Rather than focusing heavily on maximizing positive reactions, organizations might focus on helping employees work through negative reactions

to PM. Companies and employees might learn to reframe negative reactions as okay, as long as learning occurs.

Organizations need to focus more on manager transfer variables, especially quality of decisions.

• Another criterion category underutilized in PM evaluation is manager transfer, especially the quality of decisions made.

• These manager transfer variables play multiple important roles in the relationship between PM and unit-level outcomes (e.g., firm performance)

and therefore should be measured by organizations interested in such outcomes.

• Organizations should measure how PM design choices (especially changes in design) help (or hinder) managers in making better quality decisions

about employees (e.g., who should be promoted). The assumption is that improved PM processes increase the quality of HR decisions, but this

is largely untested because of the neglect of this criterion.

Organizations need to focus more on emergence enablers in evaluating their PM systems.

• Emergence enablers (especially culture, climate, and trust in management) should be included in organizations’ evaluation of their PM systems

(especially for those organizations concerned about the PM-organizational performance link), for two reasons:

Xwhen these emergence enablers are nonexistent or weak, individual criteria are less likely to emerge as unit-level HCRs and thus unlikely to

translate into organizational performance; and

XPM processes themselves can directly affect these emergence enablers, either positively or negatively, which in turn can directly impact

organizational performance (as well as weaken or strengthen the above link).

Note. PM ⫽performance management.

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EFFECTIVENESS OF PERFORMANCE MANAGEMENT

HCRs than on motivation-based HCRs (see Appendix A, section

VI). More importantly, we believe this motivation-enhancing cat-

egorization is too simplistic for understanding the complex ways

that PM may impact both individuals and organizations, and we

would call for future research to empirically test some of these

various paths. In particular it would be interesting to examine the

relative importance of ability- versus motivation-based HCRs in

explaining the PM-organizational performance link (see Proposi-

tion 2 in Table 4).

Emergence enablers. Emergence enablers are a critical mod-

erator of the link between employee constructs and unit-level

human capital; quite simply, they enable individual-level con-

structs to become unit-level phenomena. When emergence en-

ablers are nonexistent or weak, any individual criteria would be

less likely to emerge as unit-level HCRs (see Proposition 3, Table

4). We argue here that emergence enablers actually play multiple

important roles in understanding the longer chains of how PM

impacts organizational performance.

First, PM can affect organizational performance through its

impact on employee learning and transfer (as shown in our re-

view). The effect of these criteria on unit-level HCRs would then

be moderated by emergence enablers. Second, our review also

suggests that PM can affect emergence enablers directly (e.g.,

climate, coordination, trust in leadership), positively or negatively.

Taken together these two points mean that PM essentially influ-

ences both the IV (employee learning or transfer) and the moder-

ator (emergence enablers) in the overall employee to unit-level

HCR relationship. Third, there is evidence that emergence enablers

can themselves directly affect unit-level HCRs and related opera-

tional outcomes. For example, without sufficient cohesion (an

emergence enabler), members can begin to question their involve-

ment in the unit and withdraw from it (Ployhart & Moliterno,

2011), thus negatively affecting motivation-related HCRs and out-

comes such as absenteeism and turnover. In addition, Evans and

Davis (2005) have noted that positive changes in social structure

(an emergence enabler) increase organizational flexibility and ef-

ficiency, which are key to operational outcomes. Thus, as Ployhart

and Moliterno (2011) have suggested, to the extent that PM alters

the way that unit members interact behaviorally, cognitively, and

affectively, this necessarily would result in the emergence of

different kinds of HCRs. We argue this is true in the context of PM

both because these emergence enablers moderate the impact of

employee criteria on unit-level HCRs and because they are

directly linked to other unit-level phenomena (see Proposition 4

in Table 4).

Also unique to our article is a consideration of the role of

managers in this emergence process. In our model, manager trans-

fer criteria (which reflect the effectiveness of managers as man-

agers) impact unit-level HCRs in multiple ways. First, improved

managerial effectiveness can positively impact employees’ atti-

tudes and behaviors (employee transfer), the effect of which would

then proceed via the relationships outlined above. Second, the

quality of decisions that managers make about employees (which

is a manager transfer criterion) should significantly impact the

unit-level HCRs. This is because quality of decisions made by

managers would aggregate to the quality of unit-level human

capital decisions made (depicted as an emergence enabler in our

model), which in turn determines the unit’s ability to “leverage”

the human capital available and turn it into a resource (Lakshman,

2014). Third, the quality of managers’ relationships with employ-

ees (another manager transfer criterion), which our empirical re-

view suggests is significantly impacted by PM processes, would

aggregate at the unit-level into important emergence enablers such

as climate and trust in management. In turn, these emergence

enablers both moderate the relationship between employee criteria

and unit-level HCRs and directly impact other unit-level outcomes,

as specified above (see Figure 1). Thus, we argue that manager

transfer criteria (in terms of both the quality of relationships with

employees and the quality of decisions made about employees)

play multiple important roles in the relationship between PM and

unit-level outcomes (see Proposition 5 in Table 4). This is some-

thing that should be explicitly tested in future research.

We are aware of no other research that has attempted to artic-

ulate the impact of specific HR practices (as we do here for PM)

on the emergence enabling process (see Ployhart & Moliterno,

2011 on the general need for this), and we believe the specific

propositions here offer important directions for future research on

PM effectiveness. These arguments also have meaningful impli-

cations for practice (see Table 5). Organizations are likely to be

particularly interested in the impact of PM on organizational

performance, yet “80–90% of HR professionals consider that their

PM system does not improve organizational performance” (Haines

& St-Onge, 2012, p. 1158). We suspect it is unlikely that most HR

professionals have the data to support this link one way or the

other, as establishing it can be very complex. The difficulty of

linking aspects of operational PM systems to very distal outcomes

while ruling out other possible explanations for the effects (i.e.,

threats to validity, Cook & Campbell, 1979) requires thoughtful

consideration of the underlying intermediary processes. We be-

lieve that our articulation of some of these processes can be useful

in practice, suggesting that organizations should measure the fol-

lowing outcomes of PM in order to understand whether and how

PM is resulting in improved organizational performance: em-

ployee PM-related learning, employee transfer (at least some

ability/skill- and some motivational-related criteria), managerial

decision-making and relationship quality, and culture and climate

constructs.

How Essential Are Positive Reactions to the Overall

Effectiveness of PM?

Reports from the popular press suggest that employees and

managers alike downright detest their PM systems. As Levy,

Tseng, Rosen, and Lueke (2017, p. 156) recently noted “...you

can do a simple Google search and tap into the uproar.” For their

part, organizations appear very sensitive to these negative reac-

tions, often citing them as reasons for modifications to their PM

systems (see Corporate Leadership Council, 2012). Our review of

the research (see Appendix A, section i) suggests that negative

reactions are, in fact, quite prevalent. For example, reports of

procedural injustice are frequent, and affective reactions to PM are

quite negative, especially as a result of negative feedback, and

even when perceived importance is quite high. Given the extent of

negative reactions, it is critical to understand how such reactions

relate to other PM effectiveness criteria. In this section we inte-

grate the research findings with our overall model to break down

what has been a widespread assumption in the research literature

(and perhaps in practice as well, judging from organizations’

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868 SCHLEICHER, BAUMANN, SULLIVAN, AND YIM

actions): that positive reactions are essential to the effectiveness of

PM. For example, Murphy and Cleveland (1995) stated in 1995

that “reaction criteria are almost always relevant, and an unfavor-

able reaction may doom the most carefully constructed appraisal

system” (p. 314), and this was later reiterated by Keeping and

Levy (2000) in their review of PA reactions. We examine this

assumption here in a more detailed manner, explicating through

what paths reactions might exert their influence on more distal

criteria and also describing paths that likely accrue value without

necessitating positive reactions. We consider this first for em-

ployee reactions and then for manager reactions.

Employee reactions. Some strong statements have been made

about the importance of employee reactions in the effectiveness of

PM. For example:

The effectiveness of appraisal and feedback depends substantially on

the extent to which ratees accept the appraisal system. (Tziner et al.,

1996, p. 177, emphasis added)

With dissatisfaction and feelings of unfairness in process and inequity

in evaluations, any appraisal system will be doomed to failure.(Cardy

& Dobbins, 1994, p. 54, emphasis added)

The empirical evidence and our model suggest that employee

reactions are likely to relate to unit-level effectiveness in multiple

ways (i.e., via multiple paths in our model, including through

employee learning, employee transfer, and manager transfer; see

Proposition 6 in Table 4 and below). At the same time, the

equifinality inherent in our model also suggests little reason to

believe that any PM system is “doomed to failure” without positive

employee reactions.

Within employee-level criteria, there is likely to be a positive

relationship between employee reactions to PM and both employee

learning from aspects of PM and employee transfer criteria. Such

relationships have certainly been suggested and found in the train-

ing evaluation literature (Alliger et al., 1997;Kirkpatrick, 1987),

and our empirical results confirm this. First, as Figure 2 shows, PM

research suggests a moderately positive relationship (r⫽.23)

between employee reactions and learning (especially motivation to

improve as a result of the PM). It is also likely that these learning

criteria mediate the relationship between reactions and behavioral

responses to PM. Such a prediction is in-line both with arguments

in the training evaluation literature and with PM-specific empirical

findings by Kinicki, Prussia, Wu, and McKee-Ryan (2004), who

found that such constructs completely mediated the relationship

between reactions to feedback and behavioral responses to it. At

the same time, our review suggests that the employee reactions–

learning relationship is not so strong as to suggest that positive

reactions are a necessity for learning. In addition, it appears that

some positive reactions (i.e., believing that PM is distributively

fair) can actually reduce some learning outcomes such as self-

efficacy for improvement (e.g., Taylor, Masterson, Renard, &

Tracy, 1998). Table 4 summarizes the above arguments into prop-

ositions (Propositions 7, 8, and 9) that should be further tested with

empirical work.

Second, our review also shows a moderate positive relationship

between employee reactions and transfer (r⫽.29, see Figure 2).

This estimate is mainly based on relationships between reactions

and job attitudes such as job satisfaction and organizational com-

mitment (subject to method bias). It is less clear from the empirical

PM research how employee reactions impact employee perfor-

mance and other behavioral outcomes. It is also unknown whether

the magnitude of these reactions–transfer relationships would hold

if one accounted for employee learning, given its likely mediating

role (see above). We do believe, however, that employee reactions

would likely be relevant for transfer constructs related to employee

well-being, a category we proposed as part of our model but one

with relatively little empirical research in the PM literature. We

would encourage future research to examine each of these proba-

ble relationships (see Propositions 10 and 11 in Table 4).

Finally, based on both our review as well as work in other areas,

we argue that the relationship between employee reactions and

other criteria is likely to depend on the nature of the reactions. For

example, our model draws a distinction between affective, cogni-

tive, and utility-based reactions; these various types of reactions

have been shown in different contexts to have differential effects

on other criteria (Alliger et al., 1997). In particular, utility reac-

tions may exhibit stronger relationships with performance and

other behavioral outcomes than other types of reactions (Alliger et

al., 1997, “What we think is useful may correlate with what we

use,” p. 352). Yet our review also suggests there are likely to be

particularly strong effects for fairness reactions (a cognitive reac-

tion in our model), including due process perceptions, especially in

terms of relationships with transfer criteria such as turnover inten-

tions. In fact, several pieces of evidence converge to suggest it is

in fact the “due process” and perceived fairness aspects of PM, as

opposed to perceived value created by the PM system, that drive

relationships with employee turnover intentions specifically (see

Burke, 1996;Poon, 2004;Si & Li, 2012, all in Appendix B). These

arguments are summarized in Proposition 12 in Table 4; they

suggest that future research (as well as practitioners interested in

evaluating PM) should jointly examine multiple types of reactions

to better understand their relevance. The same could be said for

referent of reactions: system, specific events or aspects of PM, or

the person (e.g., the manager implementing PM). Our model is

meant to apply to all such referents of reactions, but we know little

about whether the referent matters for the relationship with down-

stream criteria and would encourage future work on this. From a

practical perspective we would strongly encourage organizations

to measure reactions to specific aspects of PM, rather than the

overall system, as the former provides better information for

making improvements (see Table 5).

Manager reactions. Both the practice and scholarly literatures

have suggested that the effectiveness of PM depends greatly on

managers. For example, den Hartog, Boselie, and Paauwe (2004)

noted that “Most PM practices...arefacilitated and implemented by

direct supervisors or front-line managers. Therefore, the behavior of

line managers will mediate the effect of (most) practices on employee

perception (and behavior)” (p. 565), and “Without managers’ support

and cooperation, it is unlikely that employees can experience fairness

in organizational HR systems” (p. 568). We agree that the role of

managers in PM is paramount and we strongly encourage additional

research that highlights this. But does this mean that positive reactions

by managers are necessary for PM to have value and/or to affect other

criteria? Although our model and empirical review suggest there are

multiple ways in which manager reactions can relate to other criteria

(see Figures 1 and 2), the empirical results suggest quite modest

relationships (with the exception of manager reactions to manager

transfer, but this was based on only two studies published together in

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EFFECTIVENESS OF PERFORMANCE MANAGEMENT

a single article and subject to common method variance, see Appen-

dix B).

We believe, based on both our review and theoretical model, that it

may be more important that managers “do PM well” (captured by

manager learning criteria) than that they react positively to PM (see

Proposition 13 in Table 4). Although learning criteria have not been

previously explicitly discussed in PM and there needs to be substan-

tially more empirical attention paid to this, some indirect evidence

exists for this link via a validation study of the Performance Manage-

ment Behavior Questionnaire (Kinicki, Jacobson, Peterson, & Prussia,

2013). Five dimensions of this scale represent manager PM-related

learning, and across multiple samples all five were linked to reports of

managers’ general effectiveness, a key aspect of manager transfer.

This suggests that managers’ PM-related learning is likely a critical

criterion in the value chain of PM, as does our empirical review of

criterion–criterion relationships (see Figure 2), which shows that

managers’ PM-related learning actually demonstrates stronger rela-

tionships with employee transfer outcomes (a cross-level effect) than

does employee learning (a within-level effect).

The arguments presented here about employee and manager reac-

tions suggest first that organizations should acknowledge and under-

stand the equifinality present in the value chain(s) leading from PM to

organizational performance and not overemphasize the role of reac-

tions in an effective PM system (by, e.g., scrapping a PM system

because of negative reactions to it, as has been reported). Reactions

should of course be measured, but they are simply one of many

relevant criteria. In addition, rather than focusing so heavily on

maximizing positive reactions, organizations might focus on helping

employees work through negative reactions (especially short-term

negative affective reactions that appear unavoidable in the face of

negative feedback). Companies and employees might learn to even

reframe negative reactions as okay, as long as learning occurs. More-

over, when reactions are measured, it should be from the perspective

of both employees and managers within the PM system, and organi-

zations are well-advised to code survey responses for this status, given

that the two sets of reactions tend to differ and differentially affect

other criteria in the value chain. Also, a variety of types of reactions

measures (i.e., affective, cognitive, utility-based) should be included;

fairness (cognitive) and utility-based reactions in particular appear

quite impactful and might receive extra attention.

What Is the Value of a Performance Rating?

PM practice has seen major changes in recent years, and one of the

most salient has been eliminating annual performance ratings. Com-

panies ranging from the technology sector to professional service

firms to manufacturing are eliminating their formal performance

ratings (Cappelli & Tavis, 2016), and this trend has resulted in a

heated debate that spans practice and research (“The pros and cons of

retaining performance ratings were the subject of a lively, standing-

room-only debate at the 2015 Society for Industrial and Organiza-

tional Psychology conference in Philadelphia,” Adler et al., 2016,p.

222). This is an area where practice has far outpaced research, and

there is unfortunately very little empirical work examining what the

impact of such a practice might be. Yet because the discourse sur-

rounding the benefits and disadvantages of eliminating ratings impli-

cates many of the components in our criterion model, it would seem

that our model and corresponding review may have something to say

about this debate.

Justifications for the elimination of performance ratings within PM

have included negative reactions from employees and managers to

this component (the necessity of which was addressed in the prior

section), as well as extensive evidence that performance ratings are

never as reliable or valid as we would like them to be (see Adler et al.,

2016), criteria categorized as manager learning in our model. Adler et

al. (2016) go on to conclude that no previous review “leads to the

conclusion that performance rating is particularly successful either as

a tool for accurately measuring employee performance or as a com-

ponent of a broader program of [PM]” (p. 223). After our own very

comprehensive review of the literature, we simply do not see any

sufficient empirical basis for deciding whether or not performance

rating adds value to PM systems, especially given the limited ways in

which value has been operationalized in prior PM research. We can,

however, through our model identify a few paths through which

performance ratings might add value (see Propositions 14–16 in

Table 4), possibilities that should be empirically studied in future

research and in practice, in order to better inform this debate.

First is the likely possibility that managers can learn from the

process of rating performance. Engaging in this could build managers’

PM-related skills and knowledge (as suggested indirectly by Kinicki

et al., 2013;Longenecker, Liverpool, & Wilson, 1988;Spence &

Keeping, 2011). We have previously established this criterion as quite

important (if empirically understudied) in the value chain of PM, as it

impacts both managerial transfer (the quality of decisions made about

employees and relationships with employees) and employee transfer.

Interestingly, if performance rating is removed from a PM system, it

may make the other criteria under manager learning even more

important. This is because it is “naïve to think that, relieved of the

burden of ratings and without the ‘crutch’ of a structured feedback

tool, managers will somehow overcome this weakness and consis-

tently engage in positive and impactful conversations. Indeed, one

important mechanism for assuring that quality ongoing performance

conversations occur...isbysetting goals as well as evaluating and

rewarding managers for how effectively they manage the perfor-

mance of their own subordinates” (Adler et al., 2016, p. 239).

Second, the existence of performance ratings seems important for

making decisions about human capital (an important manager transfer

criterion and unit-level criterion as well). Adler et al. (2016) them-

selves admit the heavy reliance of decisions on performance ratings

(e.g., “It is fair to say that tens if not hundreds of billions of dollars in

compensation and rewards are riding on the backs of performance

ratings,” p. 223). Thus, in the absence of performance ratings, it is

unclear how (well) such decisions might be made, thus diminishing an

important emergence enabler (and moderator) in our model (see

Figure 1). Future research should specifically test what happens to the

quality of human capital decisions in the absence of formal ratings.

Finally, the relevance of the psychometric quality of ratings (an

important focus in this debate) can also be framed in terms of our

model. As suggested throughout this review, there is a great deal of

“mediational equifinality” in the value chains of PM (i.e., multiple

mediational paths for the more proximal evaluative criteria). This is

contrasted with claims sometimes made in the PM literature. For

example, DeNisi and Smith (2014) note that the only way rating

accuracy matters is if it affects employee motivation for improvement,

via perceived fairness. But the causal chain is likely more complicated

than this; accuracy could also positively impact things like develop-

mental or training assignments, job tasks, or relocation based on poor

fit, all of which could impact performance improvement, via the

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870 SCHLEICHER, BAUMANN, SULLIVAN, AND YIM

quality of decisions made about employees. Our model and review

serve to make this equifinality explicit, and we would encourage

future research that examines competing mediational mechanisms

such as these.

Conclusions

This review sets forth a theoretically grounded, comprehensive,

and integrative model for understanding and measuring PM effective-

ness. In using this model as a framework for reviewing and synthe-

sizing the empirical research in PM, we find that although there has

been a great deal of empirical work on the relationship between

aspects of PM and each evaluative criterion considered separately,

very little work has examined the longer “value chains” of PM. This

represents an important opportunity for future work. We believe that

this model and review (including the propositions we develop) can be

very helpful for advancing both research and practice in PM, moving

the field from more simplistic questions like “Is PM effective?” and

“What is the ultimate criterion for PM?” to more nuanced and fruitful

inquiries regarding how PM creates value and for whom.

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878 SCHLEICHER, BAUMANN, SULLIVAN, AND YIM

Appendix A

Detailed Summary of Empirical Research on Each Criterion Category

I. PM-Related Reactions

a. Employee reactions. The empirical PM literature has ex-

amined 230 variables classified as employee reactions across 166

studies. Cognitive reactions are most prevalent (46%), followed by

satisfaction (30%), utility (17%), and affective (7%) employee

reactions. Of the 94 studies examining cognitive reactions, per-

ceived fairness/justice (especially procedural justice) has been

most prevalent (41%; see Clarke, Harcourt, & Flynn, 2013, for a

particularly good discussion of justice and PA), followed by per-

ceived accuracy (15%; e.g., Kinicki et al., 2004;Selvarajan &

Cloninger, 2012) and acceptance of PM (9%; e.g., Hedge &

Teachout, 2000;Morgan et al., 2005). Perceived quality of feed-

back has also been studied (e.g., Anseel, Lievens, & Schollaert,

2009;Payne, Horner, Boswell, Schroeder, & Stine-Cheyne, 2009).

Typically, fairness reactions have been studied with regard to the

overall PM system (e.g., Whiting, Kline, & Sulsky, 2008) but have

also been examined with regard to more specific aspects of PM,

such as ratings (Inderrieden, Allen, & Keaveny, 2004), participa-

tion in the PA (Evans & McShane, 1988), and formal processes

(Taylor et al., 1998). Research also suggests that interactional

injustice in PM is much less common than procedural injustice,

which is frequently reported (Narcisse & Harcourt, 2008). More

generally, positive cognitive employee reactions and greater sat-

isfaction result when employees participate in the PM process

(e.g., Keaveny et al., 1987;Nathan et al., 1991;Prince & Lawler,

1986), when they have knowledge about how the process works,

and when they believe their supervisors are unbiased. In fact, as

Fulk et al. (1985) have suggested, perceptions of fairness and

accuracy in PM may depend as heavily on the level of trust in the

supervisor–employee relationship as on characteristics of the PM

process itself (see also Dusterhoff, Cunningham, & MacGregor,

2014;Russell & Goode, 1988).

Of the 40 studies examining employee utility reactions to PM,

the majority focused on evaluating the effectiveness of feedback

(Catano, Darr, & Campbell, 2007;Elicker, Levy, & Hall, 2006;

Tuytens & Devos, 2012) and overall usefulness of PA (Balfour,

1992;Payne et al., 2009;Seiden & Sowa, 2011). Research in this

area shows that employees report greater utility of PM when they

participate in the PM process (Keaveny et al., 1987;Prince &

Lawler, 1986) and when 360 evaluations are used (Mamatoglu,

2008); there is some evidence that negative feedback is not viewed

as useful by employees (Brett & Atwater, 2001). Affective reac-

tions of employees have been examined in 26 studies and generally

fall into one of two categories: discomfort with the PA (also

common among raters), and emotional (positive or negative) re-

sponses to aspects of PM. Some research has suggested that

negative affective reactions to PM are common across employees,

even when perceived importance might be high (Spence & Wood,

2007). The most common finding is that negative feedback is

associated with negative affective reactions (emotions such as

anger, frustration, discouragement; Atwater & Brett, 2006;Bel-

schak & Den Hartog, 2009;David, 2013;Podsakoff & Farh,

1989). Interestingly, however, positive feedback does not appear to

result in positive affective reactions, but rather in an absence of

negative affective reactions (Brett & Atwater, 2001). Thus, it

remains unclear whether there are any aspects of PM that could

actually result in positive affective reactions, or whether the ab-

sence of negative reactions is the best that one can hope for.

b. Manager reactions. Our review suggests that the manager

reactions literature has not developed as extensively as employee

reactions, as there has been much less empirical focus on the

former. Specifically, we found 45 variables (across 32 studies) that

could be classified as manager reactions (just 16% of all the

empirical reactions articles). Similar to employee reactions, the

most frequently researched manager reactions have been cognitive

reactions (38%, especially fairness/justice), followed by satisfac-

tion reactions (31%). Unique from employee reactions, however,

was a sizable number of studies on discomfort with PA (an

affective reaction, which accounted in general for 16% of manager

reactions studies). Utility reactions comprised 16%. This research

indicates that the following aspects are important determinants of

managers’ PM reactions: type of feedback (e.g., Erdemli, Sümer,

& Bilgiç, 2007;Mabey, 2001;Redman & Mathews, 1995), rating

approach (FDRS, Schleicher et al., 2009; graphic rating scales,

Dale et al., 2013), general comfort with PM processes or the

system (Villanova, Bernardin, Dahmus, & Sims, 1993), previous

PM experience (Brutus, Fletcher, & Baldry, 2009;Smith et al.,

2000), and personality and leadership qualities of the manager

(Waldman & Atwater, 2001;Wexley & Youtz, 1985).

II. PM-Related Learning (Employees)

Our review revealed 56 studies examining variables that could

be categorized as employee learning, with attitudinal/motivational

learning being most frequent (50%), followed by skills-based

(29%) and cognitive (21%) learning. Unlike the reactions cate-

gory, there are several idiosyncratic operationalizations compris-

ing this criterion category, as detailed below.

a. Cognitive learning. Per Kraiger et al. (1993), we delineate

cognitive PM-related learning as knowledge (declarative, proce-

dural, and tacit; e.g., awareness of development opportunities,

Boswell & Boudreau, 2002), knowledge organization (e.g., task

thoughts, Harackiewicz, Abrahams, & Wageman, 1987), and cog-

nitive strategies (e.g., self-awareness, Morgan et al., 2005) result-

ing from participation in PM processes. We found 13 such vari-

ables (in 11 studies) in the PM literature. This research suggests

(Appendices continue)

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EFFECTIVENESS OF PERFORMANCE MANAGEMENT

that cognitive learning outcomes result from the type of evaluation

(amount of task-based thoughts increased with a task-focused, as

compared with normative-focused, evaluation; Harackiewicz et al.,

1987; and value-focused thinking increased with dialogue-based,

as compared with control-based, evaluation; Sundgren, Selart,

Ingelgård, & Bengtson, 2005). They also result from involvement

with and participation in the appraisal meeting (which increased

perceived learning and role clarity; Greller & Jackson, 1997;

Prince & Lawler, 1986).

b. Skills-based learning. Employees can also learn PM-

related skills in response to the PM system, and many of the

studies in this category (13 variables across nine studies) focused

on skills-based learning surrounding feedback. Outcomes exam-

ined in this regard include how employees do their work, which

can change as a result of 360 feedback (Morgan et al., 2005);

feedback sharing between peers, which increased with a new PM

system entailing regular observation and feedback (Wang, 2007),

and feedback seeking, which increased as a result of PM in

employees higher on feedback orientation (Dahling et al., 2012;

Linderbaum & Levy, 2010), self-esteem, and fear of negative

evaluation (Moss et al., 2003), and decreased when receiving an

evaluation inconsistent with previous feedback (Greller & Jackson,

1997).

c. Attitudinal/motivational learning. The vast majority of

the research on employee attitudinal/motivational learning out-

comes (28 variables across 26 studies) has examined motivational

learning, with only a couple studies focusing on attitudinal learn-

ing as an outcome of PM. This research suggests that employees’

PM-related motivation (i.e., concern about one’s performance

level and motivation and effort to improve) can improve with (a)

the use of performance-contingent rewards (Harackiewicz et al.,

1987); (b) managers who set cooperative (vs. competitive) goals

(Tjosvold & Halco, 1992), have power (Fedor, Davis, Maslyn, &

Mathieson, 2001;Wexley & Snell, 1987), and have credibility as

a feedback source (Kinicki et al., 2004); (c) perceived voice in the

PA session (Elicker et al., 2006); and (d) a feedback-rich (Kinicki

et al., 2004) and PA-supportive (Langan-Fox, Waycott, Morizzi, &

McDonald, 1998) organizational environment. Research has also

found greater intentions to use feedback and to engage in related

development opportunities when it comes from a credible source

(Bannister, 1986) and for employees with a higher feedback ori-

entation (Linderbaum & Levy, 2010). Other research has focused

on motivational learning outcomes specifically related to aspects

of goals or goal-setting and self-efficacy or other expectancy

beliefs. For example, the implementation of PM can increase the

number of goals employees plan to achieve (Pollack, Fleming, &

Sulzer-Azaroff, 1994); and a behavorial observation scale (BOS)

rating format can result in higher levels of goal clarity, goal

acceptance, and goal commitment as compared with a Graphic

Rating Scale format (Tziner, 1999;Tziner, Prince, & Murphy,

1997) and a behaviorally anchored rating scale (BARS) format

(Tziner et al., 1996). Self-efficacy and related expectancy-based

beliefs also can be impacted by rating format, with greater effica-

cy/expectancy with a process-focused as opposed to results only

focused performance evaluation (Lam & Schaubroeck, 1999) and

with a five-category as opposed to a three-category rating system.

The presence of higher quality feedback also impacts these effi-

cacy/expectancy beliefs (Northcraft, Schmidt, & Ashford, 2011).

A final theme in this research is the examination of individual

factors as determinants (or especially as moderators) of motiva-

tional learning outcomes of PM. Research has found, for example,

that higher core self-evaluations were associated with greater goal

commitment following the PA discussion (Kamer & Annen,

2010); that high achievers were more concerned with their perfor-

mance improvement following feedback (Harackiewicz et al.,

1987); that women reported greater intentions to change behavior

based on evaluation (Johnson & Helgeson, 2002); and that women,

under subjective but not objective evaluation, expect more positive

evaluation outcomes as the probability of evaluation by a female

manager increases (Maas & Torres-González, 2011).

III. PM-Related Learning (Manager)

Of the four types of manager PM-related learning criteria found

in our review, rating quality has received the most attention (71%),

followed by skills-based (19%), cognitive (5%), and attitudinal/

motivational (4%) learning. Similar to employee learning, the

manager learning variables are quite idiosyncratic.

a. Cognitive learning. In the vast majority of studies exam-

ining manager PM-related cognitive learning, such learning was

examined as an outcome of formal PM processes, particularly rater

training. Specifically, frame of reference (FOR) training has been

found to relate to the holding of less idiosyncratic performance

standards (Schleicher & Day, 1998) as well as to greater declara-

tive knowledge and performance schema accuracy (Gorman &

Rentsch, 2009). Managers in “whole brain training,” a newer form

of rater training, showed better understanding of their employees’

strengths and weaknesses (as reported by employees, Seiden &

Sowa, 2011). Another study found computer training to be effec-

tive in increasing managerial knowledge of PA (Davis & Mount,

1984). Outside of training, it has also been found that using groups

(as opposed to individuals) to rate can increase rater memory

strength and use of neutral decision criteria (Martell & Leavitt,

2002); and managers’ participation in a 360-feedback program can

result in greater understanding of one’s contribution to unit objec-

tives (Mabey, 2001).

b. Skills-based learning. After rating quality, this learning

category has received the most attention in empirical PM research.

Skills-based learning variables assessed in the literature include

effectiveness in completing PA forms (which improved with train-

ing, Davis & Mount, 1984); effective note-taking and attention to

relevant subordinate performance (which resulted from rater ac-

countability and ultimately improved decision accuracy; Mero,

Motowidlo, & Anna, 2003); behavioral specificity in PA evalua-

tion comments (which was higher for raters who had previously

(Appendices continue)

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880 SCHLEICHER, BAUMANN, SULLIVAN, AND YIM

participated in an assessment center; Macan et al., 2011); perfor-

mance information recall ability (which was improved from a

structured diary intervention and ultimately led to higher quality

ratings; DeNisi & Peters, 1996); engaging in less intentional rating

distortion (after implementation of a new due process PA system;

Taylor et al., 1995); and effectiveness of supervisors’ appraisal

behaviors (as rated by employees, after implementation of a new

behaviorally based, pay-for-performance system; Eberhardt &

Pooyan, 1988). Finally, in addition to being influenced by a variety

of PM system factors, manager skills-based learning demonstrated

important relationships with rating quality (e.g., DeNisi & Peters,

1996;Favero & Ilgen, 1989;Mero et al., 2007).

c. Attitudinal/motivational learning. Attitudinal and motiva-

tional manager learning variables, like cognitive learning, are often

linked to rater training. For example, frame of reference training

results in higher levels of agreement with organizational perfor-

mance theories (Schleicher & Day, 1998), and amount of training

relates positively to raters’ PA self-efficacy (Wood & Marshall,

2008). Participation in a 360-feedback program is associated with

perceived opportunity and satisfaction with PM changes (Mabey,

2001).

d. Rating quality. Our review shows that the emphasis on

rating quality as an outcome in PM research, although still sub-

stantial, has declined somewhat over time (see Table 2). Rating

quality criteria examined include errors (36%), accuracy (35%),

bias (14%), validity (9%), and reliability (6%). This research has

examined rating quality as an outcome of both formal (e.g., rating

scale format, Gomez-Mejia, 1988; training, Wood & Marshall,

2008) and informal (e.g., exposure to anchoring information, Thor-

steinson, Breier, Atwell, Hamilton, & Privette, 2008) processes, as

well as individual differences (e.g., agreeableness, Randall &

Sharples, 2012). Other learning variables also predict rating qual-

ity, including cognitive (e.g., less idiosyncratic performance stan-

dards, Schleicher & Day, 1998; performance schema, Gorman &

Rentsch, 2009) and skills-based (e.g., note-taking, Mero et al.,

2007) learning criteria.

IV. Employee Transfer

The empirical PM literature has examined 168 variables classi-

fied as employee transfer criteria. The most numerous of these

have been job attitudes (34%) and performance (34%), followed

by withdrawal (12%), motivation (8%), and fairness/justice (7%).

a. Job attitudes. The most frequently studied job attitude

outcomes of PM are job satisfaction and organizational commit-

ment, examined in 26 and 27 studies, respectively. Other job

attitudes studied much more infrequently include perceived orga-

nizational support (Armstrong-Stassen & Schlosser, 2010;Gavino,

Wayne, & Erdogan, 2012;Jacobs, Belschak, & den Hartog, 2014;

Masterson et al., 2000), job embeddedness (Bambacas & Kulik,

2013), and role ambiguity (Youngcourt, Leiva, & Jones, 2007).

This research suggests that the following aspects of the PM pro-

cess (formal and informal) can influence employee job satisfac-

tion: the content of the review meeting (e.g., Nathan et al., 1991);

the type of criteria used in the PA (e.g., Pettijohn, Pettijohn, &

d=Amico, 2001); whether goal setting (e.g., Bipp & Kleingeld,

2011), feedback (e.g., Lam, Yik, & Schaubroeck, 2002), and an

explanation for the PA (e.g., Rahman, 2006) are included as part of

PM; the existence of political motives in PA (e.g., Poon, 2004);

and the extent to which the supervisor and subordinate agree on the

ratings (e.g., Szell & Henderson, 1997). Research suggests that

organizational commitment is similarly influenced by the provi-

sion of goal setting (e.g., Taylor & Pierce, 1999); feedback (Lam,

Schaubroeck, & Aryee, 2002;Pearce & Porter, 1986;Tang, Bald-

win, & Frost, 1997); developmental PA more generally (Young-

court et al., 2007) and “high-commitment” PM practices (Farndale

& Kelliher, 2013); fair treatment by one’s supervisor in the PA

(Farndale, Hope-Hailey, & Kelliher, 2011); and supervisor/subor-

dinate agreement on ratings (Szell & Henderson, 1997).

The research summarized above would seem to suggest a clear

link between elements of PM and employees’ job attitudes. Yet

much of this research is plagued by common method concerns

(single source cross-sectional surveys), and research using stronger

designs has often concluded a lack of effect of PM on these more

distal job attitudes. For example, using quasi-experimental de-

signs, Eberhardt and Pooyan (1988),Korsgaard, Roberson, and

Rymph (1998), and Taylor et al. (1998) all failed to find an effect

of PM on job attitudes. Taylor and Pierce (1999), which utilized a

stronger longitudinal design, found an effect of PM practices on

organizational commitment but not on job satisfaction. Thus, it

appears that the stronger the design, the less the evidence for a link

between PM and these job attitudes. An exception to this is Mabey

(2001), which utilized a matched sample of nonparticipants and

found that participating in a 360-degree program leads to more

positive attitudes about the organization.

b. Performance. The other most frequently studied employee

transfer construct is performance (34% of employee transfer arti-

cles), operationalized most often as overall performance (20 arti-

cles), organizational citizenship behavior (OCB; 14 articles), and

task performance (11 articles); counterproductive behavior (three

articles) and career success (two articles) have also been examined.

There is quite a bit of evidence that employee performance is

related to PM, including the implementation of new or different

PM systems (e.g., Pampino, MacDonald, Mullin, & Wilder, 2003;

Stumpf, Doh, & Tymon, 2010) as well as specific elements of PM.

For example, research suggests that overall and task performance

are positively related to the implementation of goal setting (e.g.,

Klein & Snell, 1994;Pollack et al., 1994), feedback (e.g., Pollack

et al., 1994;Wang, 2007), and more developmentally oriented PA

programs (e.g., Tharenou, 1995). More discussion and participa-

tion in the PA interview is also associated with higher employee

performance (e.g., Nathan et al., 1991;Prince & Lawler, 1986).

Regarding different approaches to PA, higher employee perfor-

mance has been found to result from BOS rating formats compared

with graphic rating scale formats (Tziner, 1999), with greater as

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EFFECTIVENESS OF PERFORMANCE MANAGEMENT

compared with less rating segmentation (Bartol, Durham, & Poon,

2001), and with process- as opposed to results-oriented feedback

(Lam & Schaubroeck, 1999). The manager’s role in PM is also

important, with research showing that the types of goals set with

one’s supervisor (cooperative vs. competitive, Tjosvold & Halco,

1992), the type of power employed by one’s supervisor in the PA

context (Wexley & Snell, 1987), and perceived interactional jus-

tice within the PA setting (Masterson et al., 2000;Thurston &

McNall, 2010) are all positively related to employee performance.

Increased OCBs are similarly positively related to these same

elements of PA process (e.g., Findley, Giles, & Mossholder, 2000;

Masterson et al., 2000;Norris-Watts & Levy, 2004;Si & Li, 2012;

Zheng, Zhang, & Li, 2012). The most common moderators exam-

ined involve the feedback component of PM, showing that perfor-

mance is most likely to improve when feedback is more frequent

(Bhave, 2014;Kuvaas, 2011;Pampino et al., 2003), timely and

specific (e.g., Northcraft et al., 2011), when reflection accompa-

nies it (e.g., Anseel et al., 2009), and with greater self-awareness

(e.g., Korsgaard & Roberson, 1995). Unlike with job attitudes,

much (but certainly not all) of the research examining the link

between PM and employee performance has avoided common

method issues, with 15 of these studies measuring performance

using managers as the source. Despite the generally consistent

evidence that performance can and does improve as a result of

multiple aspects of PM, there also is a handful of studies failing to

find such effects (see Erdemli et al., 2007;Milanowski, 2005;

Shen, D’Netto, & Tang, 2010).

c. Withdrawal. Of the 20 withdrawal-related variables stud-

ied in PM, the vast majority (17) have been operationalized as

intention to turnover versus remain; actual turnover has been

studied in one article (Milanowski, 2005, no effect found), and

another article measured withdrawal as neglect, or putting in less

effort (Si & Li, 2012). It has been suggested that “a high-quality

PA system deters turnover (Peterson, 2004;Brown, Hyatt, &

Benson, 2010) [and] a low-quality PA system increases intentions

to leave (Brown et al., 2010)” (Bambacas & Kulik, 2013, p. 1936).

There does appear to be some evidence of this, especially if

“high-quality” is defined in terms of due process. The empirical

research shows, specifically, that employee turnover intentions are

positively related to the use of computer aided performance mon-

itoring (Chalykoff & Kochan, 1989; although for some employees

this can be mitigated by attention to feedback and other aspects of

the PA process) and to employees receiving negative as opposed to

positive feedback (Lam et al., 2002, although these effects gener-

ally did not last beyond 3 months). Conversely, employees are

more likely to express intentions to remain with the organization

under due-process PA systems (Bambacas & Kulik, 2013;Taylor

et al., 1998) and, related, when they have high procedurally just

perceptions of PA (Juhdi, Pa’wan, & Hansaram, 2013;Masterson

et al., 2000) and greater satisfaction with PA (Kuvaas, 2006;

Tymon, Stumpf, & Doh, 2010;Whiting & Kline, 2007), although

much of this research is plagued by common method issues.

d. Motivation. Motivational criteria are the last category of

employee transfer that has been studied with some regularity (8%

of employee transfer research). Most commonly studied has been

intrinsic motivation (four articles), including engagement (Gruman

& Saks, 2011 provide a conceptual model that identifies key

drivers of employee engagement at each stage of PM, but there has

been little empirical testing of these ideas). The empirical PM

research offers the following conclusions. First, the goal-setting

and feedback components of PM, not surprisingly, are particularly

important for employee motivation; research has found that coop-

erative (vs. competitive) goals lead to greater motivation to work

hard (Tjosvold & Halco, 1992), that having high quality goals (i.e.,

specific and observable) varies across rating scale format (BOS vs.

graphic rating scale vs. BARS; Tziner et al., 1996), and that higher

quality (more timely and more specific) feedback on tasks leads to

greater resource allocation on those same tasks (Northcraft et al.,

2011). Second, greater intrinsic motivation results from PM that

utilizes a more dialogue-based evaluation from the manager

(Sundgren et al., 2005) and is more developmental in nature

(Kuvaas, 2007), and when employees assess the aspects of PM

(e.g., goal setting, evaluation, feedback) more positively (Juhdi et

al., 2013;Kuvaas, 2006;Tymon et al., 2010). Some research has

also failed to find a link between PM and motivation criteria:

Taylor et al. (1998) found no relationship between due process PA

and motivation to improve, and Taylor and Pierce (1999) found

that the introduction of a new PM system did not increase effort.

Together, this research suggests that there is likely not a straight-

forward relationship between PM and motivation; rather, the type

of PM processes in place are likely to determine the type of

motivation resulting (e.g., intrinsic vs. extrinsic, Sundgren et al.,

2005).

e. Fairness/justice. Although fairness perceptions regarding

PM itself are frequently studied (as discussed under Reactions, see

section I in this Appendix), less frequently examined has been the

impact of PM on more generalized fairness/justice perceptions

(just 7% of the empirical work on employee transfer). Variables

examined include overall justice (three articles), procedural justice

(four articles), distributive justice (two articles), and interactional

justice (three articles). This research has found more positive

perceptions of justice/fairness are associated with the provision of

feedback (but only among high performers, Lam et al., 2002);

perceived usefulness of the PA process (Linna et al., 2012); and

the implementation of PA for administrative purposes (Cheng,

2014), including reward allocation (Day, Holladay, Johnson, &

Barron, 2014). In terms of moderators, Linna et al. (2012) discov-

ered an interesting and potentially important finding: during neg-

ative changes in work life, employees’ experienced usefulness of

the PA feedback interview was especially important in helping

prevent the deterioration of justice perceptions.

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882 SCHLEICHER, BAUMANN, SULLIVAN, AND YIM

V. Manager Transfer

Twenty-nine manager transfer variables have been examined

across 26 studies. The focus has mostly been on quality of rela-

tionships (69%), with less research (28%) on quality of decisions

made about employees. One study examined perceived supervisor

effectiveness more generally (Burke, 1996), finding a positive

relationship with employee beliefs that they had received an ac-

curate and fair evaluation.

a. Quality of relationships with employees. Aspects of the

PM system can alter the manager–employee relationship in vari-

ous ways, and research has operationalized managers’ relationships

with employees in terms of trust in the manager (four studies),

supervisor liking/satisfaction (one study), leader-member exchange

(LMX; two studies), perceived supervisor support (two studies), gen-

eral supervisor-subordinate working relationship (five studies),

and the quality of the coaching relationship (two studies). This

research shows that managers report better working relationships

with employees after using a due process PA system (Taylor et al.,

1995) and that employee feedback orientation positively relates to

both LMX (Dahling et al., 2012) and the quality of the employee–

supervisor coaching relationship (Gregory & Levy, 2012). The

quality of the employee–supervisor coaching relationship results

from effective communication and the facilitation of development

by the supervisor (Gregory & Levy, 2011). Conversely, the

supervisor–subordinate relationship can degrade under certain PM

conditions, including forced distribution PM systems (McBriarty,

1988). Research has also examined more specific aspects of a

manager’s relationship with employees, including trust in the

manager (which is related to employees expressing noninstrumen-

tal voice and being assertive in the PA interview; Korsgaard, 1996;

Korsgaard et al., 1998); employee confidence in future collabora-

tion with his or her manager (related to the manager establishing

cooperative as opposed to competitive goals with the employee,

Tjosvold & Halco, 1992); liking of one’s supervisor (related to

supervisors’ impression management and provision of feedback;

Kacmar et al., 1996); and satisfaction and cooperation with one’s

supervisor (which increased with the implementation of a new PM

system including merit-based pay, but only for low performers,

Taylor & Pierce, 1999).

b. Quality of decisions made about employees. Despite the

important implications for downstream criteria such as the emer-

gence of unit-level HCRs, very little empirical research (four

studies) has examined the quality of decisions made about em-

ployees as an outcome of PM. Research has found that the imple-

mentation of a forced distribution PM system actually decreased

the quality of managers’ decisions relating to job assignments and

resource utilization (McBriarty, 1988), and that the accuracy of

employee-related decisions by managers was not related to their

attitudes about appraisal but was related to their self-monitoring

personality (Jawahar, 2001). More research should examine the

degree to which PM actually provides useful information for

making other HR decisions (see Roberts, 1995).

VI. Unit-Level Human Capital Resources

Our review uncovered only nine studies that have empirically

examined unit-level HCRs as an outcome of PM. There is a

distinction in multilevel scholarship between the level of theory

and the level of measurement (Kozlowski & Klein, 2000), and it is

important to note that our categorizations here are based on the

level of theory, not measurement. Nonetheless, all but one of these

nine studies (Mulligan & Bull Schaefer, 2011, a simulation at the

employee level) measured this variable at the organization level.

Six studies examined skills/abilities/potential capabilities, in-

cluding adaptability/flexibility (Mullin & Sherman, 1993); perfor-

mance potential of the workforce (“the average potential of an

organization’s workforce to perform on the job,” Mulligan & Bull

Schaefer, 2011;Scullen, Bergey, & Aiman-Smith, 2005); work-

force quality (Giumetti, Schroeder, & Switzer, 2015) and staff

competency (Zheng et al., 2006); and employees’ knowledge

about how their work relates to the organization’s strategy (Ayers,

2013). This research shows that each of these “ability” unit-level

HCRs can be impacted by PM. Interestingly, three of the studies in

this category are about FDRS specifically (and are simulations;

Giumetti et al., 2015;Mulligan & Bull Schaefer, 2011;Scullen et

al., 2005). These results suggest that improvement in workforce

potential and quality as a result of FDRS should be most noticeable

over the first few years (Giumetti et al., 2015;Scullen et al., 2005),

except for the findings of Mulligan and Bull Schaefer (2011),

which suggested that temporary use of FDRS may do more harm

than good in terms of workforce performance potential.

Three articles examined motivational capabilities. In the context

of municipal PM systems, Roberts (1995) found that most respon-

dents agreed that the PM system had a positive effect on employee

motivation. Zheng et al. (2006) found positive effects of PA on

staff commitment (per Pfeffer, 1998 and Youndt, Snell, Dean, &

Lepak, 1996, commitment is classified as motivational), which

mediated the relationship with firm performance. On the other

hand, McBriarty (1988) found that a forced distribution system in

the Air Force had a negative effect on motivation at the organiza-

tion level, arguing that such systems focused “an inordinate

amount of attention on the basic human concerns about survival,

security, and ego maintenance at the expense of the higher order

‘motivators’ of more productive organizational behavior” (p. 428).

We uncovered no empirical studies examining the relationship

between PM and unit-level opportunity capabilities. Some (e.g.,

Combs et al., 2006) have suggested that climate is part of the

opportunity part of the AMO framework, and there are studies

looking at the impact of PM on climate. However, following

Ployhart and Moliterno (2011), we categorize climate as an emer-

gence enabler as opposed to a HCR and therefore review this in the

next section.

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EFFECTIVENESS OF PERFORMANCE MANAGEMENT

VII. Emergence Enablers

There is evidence that PM can affect an organization’s climate,

culture, and perceptions of leadership, all of which are important

emergence enablers in our model. Eleven studies have examined

aspects of climate as outcomes of PM, operationalized as office

morale (Burke, 1996), group- or organization-level satisfaction

(Daley, 1986;Mullin & Sherman, 1993), a “support” dimension of

organizational culture (Mamatoglu, 2008), perceived psychologi-

cal contract fulfillment (Raeder, Knorr, & Hilb, 2012), six dimen-

sions of organizational climate (Kaya, Koc, & Topcu, 2010), and

ethical organizational climate (Guerci, Radaelli, Siletti, Cirella, &

Rami Shani, 2015). One study examined how PM affects the

creativity culture of an organization (Sundgren et al., 2005), and

one study examined the relationship between PM and strong

positive perceptions of leadership (Lakshman, 2014), also consid-

ered an aspect of climate (Rentsch, 1990). This research suggests

that climate, culture, and leadership can be influenced by the

implementation of new systems as well as different types of PM

systems. For example, in a longitudinal study, Mamatoglu (2008)

found that a new 360-feedback system positively impacted em-

ployees’ perceptions of a support and achievement culture; and

Raeder et al. (2012) found that PA related to perceived psy-

chological contract fulfillment, but only in the presence of

performance-based pay (a tangible consequence). Sundgren et al.

(2005) found that dialogue- versus control-based PA systems had

a stronger impact on the organization’s creativity culture; and

Guerci et al. (2015) found that the use of performance goals and

behavior-based evaluations is linked to egoistic, rather than ethi-

cal, climates. Another emergence enabler—trust in management—

was examined in one study. Mayer and Davis (1999) found that the

implementation of a more acceptable PA system increased trust for

top management, and that this relationship was mediated by the

three factors of trustworthiness: ability, benevolence, and integrity.

The unit’s ability to learn via the sharing of knowledge and

information is part of cognitive emergence enabling states (reflect-

ing the unit’s ability to acquire, absorb, and transfer information)

and has been examined as an outcome of aspects of PM in four

studies. Operationalizations of this include the communication

atmosphere of the unit (Mamatoglu, 2008), the knowledge sharing

of R&D employees (Liu & Liu, 2011), knowledge management

effectiveness (Tan & Nasurdin, 2011, which served as a mediator

between PA and organization-level innovation), and organizational

learning (Wang, Tseng, Yen, & Huang, 2011). This research has

suggested that these emergence enabling states can be impacted by

high quality PA practices in general (Liu & Liu, 2011;Tan &

Nasurdin, 2011;Wang et al., 2011) and the implementation of a

360-feedback system specifically (Mamatoglu, 2008).

A fourth category of emergence enablers concerns team cohe-

sion, trust, and collaboration. Findings across four articles suggest

that these elements can definitely be affected by the type of PM

system, either positively or negatively. For example, in three

laboratory experiments, Song, Sommer, and Hartman (1998)

showed that modifying PA to include intergroup behavior explic-

itly (and an external supervisor as evaluator) led to more helping

behavior and more positive attitudes toward cooperating; and

Wang (2007) found that a new approach to evaluating teachers that

relied on additional interaction, classroom observation, and feed-

back significantly increased the frequency of teacher collaboration

and peer feedback. Conversely, some forms of PM can have

negative effects on team cohesion and team effectiveness, includ-

ing forced distribution systems (McBriarty, 1988) and those based

on individual contributions and rewards and otherwise incongruent

with a teamwork culture (Rowland, 2013). Finally, we conceptu-

alize the unit-level quality of human capital decisions as another

important emergence enabler. We found only one article examin-

ing this. Lawler (2003) evaluated the organization-level effective-

ness of the PM systems of 55 Fortune 500 companies on two

factors: effectiveness for influencing performance (the right kind

of performance) and effectiveness for differentiating between top

and poor performers/talent. Their results show that PM systems

were more effective on these two criteria when there is a connec-

tion between the results of PM and the reward system of the

organization.

VIII. Firm Performance

The articles we review here are those where the effects of PM

specifically (not just bundled HR practices) on organization per-

formance could be isolated. We found 16 such studies that exam-

ined operational outcomes (almost all of which were conducted at

the organization level) and four articles that examined financial

outcomes. Overall this research shows that PM can indeed have a

positive impact on organizational outcomes, both operational (es-

pecially turnover) and financial performance.

a. Operational outcomes. Operational outcomes examined

include labor productivity (Roberts, 1995 found that the majority

of respondents believed their PA system had a positive effect on

employee productivity) and production quality or quantity (which

has been found to be positively related to the existence of PA,

Zheng et al., 2006, and Lee, Lee, & Wu, 2010; as well as more

related to “progressive” than “traditional” PA approaches, where

the former includes more informal and multiple rating source

approaches, Waite, Newman, & Krzystofiak, 1994). Organiza-

tional innovation is another operational outcome, and two studies

have examined its relationship to PM. Tan and Nasurdin (2011)

found PA practices had a positive effect on administrative inno-

vation but not on product or process innovation (and knowledge

management effectiveness mediated this relationship). Jiang et al.

(2012) found evidence for the link between PA and both admin-

istrative and technological innovation, but this was not mediated

by creativity as it was for other HR practices. Two studies exam-

ining improved safety performance as an outcome suggested PM

can be very effective in this regard. Laitinen and Ruohomäki

(1996) found a new PM approach oriented around safety behavior

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884 SCHLEICHER, BAUMANN, SULLIVAN, AND YIM

(including weekly graphic feedback) at building construction sites

in Finland significantly improved safety, and Reber and Wallin

(1994) found a PM program around safety behavior in offshore

oilfield diving significantly reduced OSHA-recordable occupa-

tional injuries and accidents. Research has also examined the

impact of PM on turnover (six articles) and/or absenteeism (two

articles) at the organization level, suggesting that turnover can be

reduced by PA practices in general (Galang, 2004;Zheng et al.,

2006) and other “high involvement” practices such as electronic

performance monitoring (Batt, 2002). These same articles also

suggest that turnover at least partially mediates the relationship

between these practices and financial performance. In addition, a

survey about PA systems in municipal governments showed that

the majority of respondents perceive the systems to be effective at

retaining good employees, but they were judged as less effectives

for controlling absenteeism (Roberts, 1995). On the other hand,

Peretz and Fried (2012) found, in an organization-level study

across 21 countries, that congruence between societal cultural

practices and the characteristics of PA practices (i.e., formality,

focus on development, multiple sources of raters, and percentage

of EEs evaluated) affects absenteeism and turnover, but there was

greater support for absenteeism than for turnover.

b. Financial outcomes. Our review identified four articles

that examined the link between PM and aspects of firm financial

performance (all measured at the organization level). Zheng et al.

(2006) operationalized firm performance as increased sales, mar-

ket competitiveness, and expected growth (all measured via inter-

view responses), and found that a sound PA system generated

better “HRM outcomes” (e.g., turnover, commitment, compe-

tency) which, in turn, contributed positively to financial perfor-

mance. Yang and Klaas (2011) measured financial performance as

the ratio of operating profit to assets (which represents how effec-

tively firm assets are utilized in achieving profitability) and found

that pay dispersion was less negatively related to firm financial

performance when the organization invests more in performance

evaluation and feedback. Sales growth was measured in Batt

(2002) and was found to be positively impacted by the PM practice

of electronic performance monitoring (among other high involve-

ment HR practices), as mediated by turnover. Finally, Goh and

Anderson (2007) examined the return-on-investment (ROI) of a

PM learning curriculum, which outlined how managers were sup-

posed to improve the performance of their people and how em-

ployees were expected to take responsibility for their own devel-

opment. The ROI was based on five impact factors (personal

productivity, team efficiency, improved quality, increased net

sales, and reduced cost) and was found to be 122%.

c. Other outcomes. We also found a number of empirical

articles that examined aspects of organizational performance that

could not be clearly categorized under the above categories. Some

of these examined the impact of PM on more general (or undif-

ferentiated) aspects of organizational performance (e.g., Irs &

Türk, 2012, found that the PA system positively impacted school

performance on a number of performance indicators). Several

others examined subjective ratings of perceived organizational

performance. For example, in Daley (1986), Iowa public employ-

ees reported on the extent to which the “organization is effective in

accomplishing its objectives” as a result of PM. In Rodwell and

Teo (2008), managing directors were asked to evaluate their or-

ganizations’ performance as compared with similar organizations

and relative to market competitors over the past 3 years (these

performance indicators were positively related to the adoption of

PA practices). In Raeder et al. (2012), participants were asked to

assess the performance of their organizations compared with oth-

ers in the sector on six items: service quality, productivity, prof-

itability, product to market time, rate of innovation, and stock

market performance. In Galang (2004), respondents were asked

how accurately each of the following described their respective

companies on a 5-point scale: produces high quality goods, has a

promising future, manages its people well, is flexible enough to

change, has high quality people, has a strong unified culture, is

very effective overall, has a very satisfied workforce, has a very

productive workforce, and is seen as a leader in industry (PA

practices were strongly related to these performance ratings).

(Appendices continue)

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EFFECTIVENESS OF PERFORMANCE MANAGEMENT

Appendix B

Empirical Estimates of Criterion–Criterion Relationships

This appendix empirically summarizes the research reporting

bivariate relationships among our evaluative criteria. We com-

puted the average sample-weighted correlation for any criterion–

criterion relationships with at least two samples (see also Figure 2).

Where possible, we report these average correlations separately by

subcategories of criteria; where that is not possible, we acknowl-

edge that (along with generally small numbers of samples) as a

limitation in interpreting these results.

Employee Reactions ¡Employee Learning

In the training evaluation literature there is an assumption of

(and empirical evidence for) a positive link between reactions and

learning (see Alliger et al., 1997). We found several PM articles

(nine samples across nine articles) that included these empirical

relationships, revealing a positive relationship between employee

reactions and employee learning (average r⫽.23). In these

relationships, employee reactions most commonly (60% of the

time) focused on fairness reactions; also examined were emotional

reactions, satisfaction with PM, and perceived accuracy and use-

fulness. Learning was most commonly measured as motivation to

improve (in four studies; for just these studies, average r⫽.35).

Unfortunately, in several studies reactions and learning were mea-

sured via the same source at the same time. Overall this research

suggests that employee reactions to PM relate positively to em-

ployee learning from aspects of PM (especially motivation to

improve). However, in the case of justice reactions this relation-

ship appears a bit more complicated. For example, Selvarajan and

Cloninger (2012) observed that PM-related motivational learning

can improve with perceived procedural and interactional fairness,

but not with perceived distributive fairness. Taylor et al. (1998)

actually reported a moderately negative relationship between dis-

tributive justice of PM and learning outcomes such as self-efficacy

for skill improvement and goals for improved future performance.

Employee Reactions ¡Employee Transfer

One reason employee reactions to PM matter is that positive

reactions can “transfer” to important criteria on the job, including

improved job attitudes, views of one’s supervisor, and aspects of

performance (Korsgaard et al., 1998;Youngcourt et al., 2007).

Reactions are also thought important in the social exchange be-

tween PM partners (i.e., managers and employees, Pichler, 2012),

suggesting they may relate in important ways to general attitudes

and behaviors on the job. These were in fact the relationships most

frequently examined in our review, with 24 samples across 23

articles examining relationships between employee reactions and

employee transfer. The average rwas .29. Employee reactions

most commonly focused on justice and other cognitive reactions

(65% of studies); and the most common employee transfer vari-

ables were organizational commitment (where r⫽.35) and job

satisfaction (where r⫽.37). Several of these studies were again

prone to same method bias, thus potentially inflating these rela-

tionships. In addition, it is unknown whether the magnitude of

these direct relationships would hold if one accounted for em-

ployee learning (a potential mediator; see following section). In-

terestingly, several studies in this area converged to suggest that

perceived fairness of PM, as opposed to perceived value of the

PM, drives employee turnover intentions specifically. For exam-

ple, Burke (1996) found that employee intent to quit was (nega-

tively) related to due process and perceived fairness of PA, but not

to the meaningfulness of the personal development plan created.

Related, Si and Li (2012) found that the extent to which PA is

developmentally useful was negatively related to employee neglect

but not to exit (i.e., turnover intentions). As further support for the

importance of due process and fairness on turnover, Poon (2004)

found that if employees believe ratings were manipulated because

of raters’ personal bias and intent to punish employees, this leads

to greater turnover intentions; but there is no effect on turnover

intentions when employees believe ratings were manipulated for

motivational purposes. This is interesting because in both cases the

ratings were intentionally manipulated (thereby ostensibly de-

creasing the utility of the ratings and the PM system), but manip-

ulation for motivational purposes presumably is seen as more fair

than manipulation for personal bias or intent to punish, and fair-

ness appears to trump utility in driving turnover intentions.

Employee Learning ¡Employee Transfer

In models of training evaluation, it is learning that is the most

proximal determinant of transfer (Alliger et al., 1997;Kraiger et

al., 1993). In the context of PM, this suggests that it is what

employees learn from the PM experience that affects their overall

attitudes and behaviors back on the job, and our review does reveal

some empirical evidence of this. We found nine studies reporting

this relationship, with an average rof .38 (interestingly this rela-

tionship did not vary based on whether the data were same- or

different-source, r⫽.38 vs. .39, respectively). For the attitudinal

and motivational subcategory of learning (k⫽7), the relationship

was even larger (average r⫽.45), for multiple subcategories of

transfer (e.g., for job attitudes, r⫽.46; for performance r⫽.44).

These estimates suggest that what employees learn from the PM

experience (especially in terms of attitudinal and motivational

learning) can indeed transfer into improved attitudes and perfor-

mance back on the job.

(Appendices continue)

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886 SCHLEICHER, BAUMANN, SULLIVAN, AND YIM

Manager Reactions ¡Manager Learning

Just as employees’ reactions to PM should positively relate to

learning from PM, so should managers’ reactions. Our review

showed that manager reactions are positively (albeit weakly) re-

lated to manager learning (r⫽.14). This estimate is based on

seven distinct samples reported in three different articles. Manager

reactions variables included satisfaction, fairness, difficulty, and

discomfort; manager learning variables were limited to rating

quality and distortion.

Manager Reactions ¡Manager Transfer

Our review showed manager reactions are also positively related

to manager transfer (r⫽.30). But this estimate is based on only

two studies published together in a single article on managers’

reactions to the implementation of a procedurally just PM system

(Taylor et al., 1998). Specifically, managers’ satisfaction with the

appraisal system related positively to a favorable working relation-

ship with their employees. However, in both samples, the two

variables were reported by managers at the same point in time,

likely inflating the magnitude of the relationship.

Manager Learning ¡Manager Transfer

Our review showed manager learning was positively and

strongly related to manager transfer (r⫽.53). This overall positive

estimate is based on three studies. One study showed a very strong

positive relationship (Gregory & Levy, 2012), but two of these

studies (from the same article referenced in the previous section;

Taylor et al., 1998) actually had a negative relationship (average

r⫽⫺.10). The latter examined managers’ self-reported distortion

of appraisals and found that more distortion (coded as less learning

here) related positively to working relationships with their employ-

ees. Manager learning is likely to be positively related to the

quality of decisions subcategory of manager transfer, but as these

results show, it might negatively impact the quality of relationships

with employees (especially given that greater learning may imply

lower ratings).

Manager Learning ¡Employee Transfer

We also found three articles that reported relationships between

aspects of manager learning about PM and employee transfer,

showing a positive relationship (average r⫽.51). In particular,

managers’ learning with regard to providing feedback through the

year and discussing past and future performance in the PA inter-

view ultimately related to employee job satisfaction (Inderrieden et

al., 2004); and managers’ learning in terms of interactive behaviors

that help employees convert tacit knowledge to explicit knowledge

and managers’ performance enhancement strategies both related

positively to subordinate performance (Lakshman, 2014).

Predictors of Unit-Level Outcomes

There were a handful of studies that reported relationships

between employee- or manager-level criteria from our model and

unit-level criteria. Unfortunately, for only one criterion category

(employee transfer, k⫽4) was there a sufficient number of

samples to aggregate. The average rhere was .37, but this was

marked by a bimodal distribution, with two effect sizes in the r⫽

.60 range (the link between employee transfer variables and orga-

nizational climate and innovation) and two in the r⫽.06–.10

range (for the link between employee transfer and bottom-line

measures of organizational performance). This pattern suggests,

not surprisingly, that employee transfer criteria are more strongly

related to the more proximal unit-level criteria of emergence

enablers and operational outcomes than they are the more distal

bottom-line measures of organizational performance.

Received May 15, 2016

Revision received September 19, 2018

Accepted October 2, 2018 䡲

This document is copyrighted by the American Psychological Association or one of its allied publishers.

This article is intended solely for the personal use of the individual user and is not to be disseminated broadly.

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