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Human Resource Management, July–August 2016, Vol. 55, No. 4. Pp. 697–719

© 2015 Wiley Periodicals, Inc.

Published online in Wiley Online Library (wileyonlinelibrary.com).

DOI:10.1002/hrm.21740

Correspondence to: Sanghee Park, Assistant Professor, School of Management and Labor Relations, Rutgers,

The State University of New Jersey, Piscataway, NJ, 08854, Phone: (848) 445-1051, Fax: (732) 445-2830,

E-mail: [email protected]

EVALUATING FORM AND

FUNCTIONALITY OF

PAY-FOR-PERFORMANCE PLANS:

THE RELATIVE INCENTIVE

AND SORTING EFFECTS OF MERIT

PAY, BONUSES, AND LONG-TERM

INCENTIVES

S A N G H E E P A R K A N D M I C H A E L C . S T U R M A N

Using two-year longitudinal data from a large sample of US employees from a

service-related organization, the present study investigates the relative effects of

three forms of pay-for-performance (PFP) plans on employees’ job performance

(incentive effects) and voluntary turnover (sorting effects). The study differenti-

ates between three forms of pay: merit pay, individual-based bonuses, and long-

term incentives. By defi nition, these PFP plans have different structural elements

that distinguish them from each other (i.e., pay plan form) and different charac-

teristics (functionality), such as the degree to which pay and performance are

linked and the size of the rewards, which can vary both within and across plan

types. Our results provide evidence that merit raises have larger incentive and

sorting effects than bonuses and long-term incentives in multi-PFP plan environ-

ments where the three PFP plans are operating simultaneously. Only merit pay

has both incentive and sorting effects among the three PFP plans. The implica-

tions for the PFP-related theory, as well as for the design and implementation of

PFP plans, are discussed. © 2015 Wiley  Periodicals, Inc.

Keywords: pay-for-performance plans, incentive effect, sorting effect,
compensation

698 HUMAN RESOURCE MANAGEMENT, JULY–AUGUST 2016

Human Resource Management DOI: 10.1002/hrm

Even with a

substantial body of

research discussing

the effects of

particular PFP

interventions, PFP

research has typically

failed to consider the

complex, multiplan

environments

in which many

organizations invest

and many employees

face.

examinations of individual PFP plans. Most stud-
ies examine a single form of PFP at a time, par-
ticularly in laboratory studies (e.g., Bandiera,
Barankay, & Rasul, 2007; Cadsby et al., 2007;
Eisenberger, Rhoades, & Cameron, 1999; Kwong
& Wong, 2014), but also in organizational settings
(e.g., Banker, Lee, Potter, & Srinivasan, 1996, 2001;
Dunford, Boudreau, & Boswell, 2005; Eisenberger
et al., 1999; Pearce et al., 1985; Schaubroeck, Shaw,
Duffy, & Mitra, 2008). Other work provides only
broad overviews of PFP plans’ effects, such as in
strategic HR management research that typically
asks general questions about the extent to which
employees are covered by PFP (e.g., Bhattacharya,
Gibson, & Doty, 2005; Delery & Doty, 1996;
Gerhart & Milkovich, 1992; Toh, Morgeson, &
Campion, 2008; Wright, Gardner, Moynihan, &
Allen, 2005). This previous work has certainly
been valuable for providing information on the
nature of PFP effects; however, the generalizability
of theory and findings from single-plan focal stud-
ies to multiplan environments is questionable.

Many companies use multiple types of PFP
simultaneously (Cohen, 2011; Gerhart & Fang,
2014; Gerhart et al., 2009; Rynes et al., 2005). A
2010 WorldatWork Survey showed that 92 percent
of companies use merit raises, 80 percent provide
some form of individual-based variable pay pro-
gram (not including sales commissions or merit
raises), and 57 percent use some sort of perfor-
mance-sharing plan. The same survey conducted
in 2012 (WorldatWork, 2012) showed this to be an
increasing trend, with 95 percent offering merit
pay, 84 percent with some form of individual-
based variable pay program, and 58 percent using
some form of performance sharing. While these
surveys do not explicitly report the number of dif-
ferent incentive plans covering the same employ-
ees, mathematically, we can extrapolate that at
least three-quarters of companies use at least two
forms of PFP, and over one quarter are simultane-
ously using three different PFP plans. Despite this
prevalent complexity, though, there is minimal
research considering the relative effectiveness of
different PFP plans.

Studying PFP explicitly within the more com-
plex environment of multiple PFP plans is critical
to gain a better understanding of the relative effec-
tiveness of different PFP forms. This study makes
several contributions to our understanding of the
effectiveness of PFP. First, this study considers
multiple PFP plans simultaneously in multi-PFP
plan environments. As previously noted, most
prior PFP research has considered a single PFP
plan at a time, with it either being explicitly on a
single plan, or unstated or unexplored if other PFP
plans were operating simultaneously. It is unclear

T
heory and empirical evidence indicate
that, in general, pay-for-performance (PFP)
plans have positive effects on employee
job performance (e.g., Gerhart & Fang,
2014; Gerhart & Rynes, 2003; Jenkins,

Mitra, Gupta, & Shaw, 1998; Lawler, 1971; Zenger,
1992). A common component of compensation
systems, PFP plans are referred to as “pay that
varies with some measure of individual or orga-
nizational performance” (Milkovich, Newman,
& Gerhart, 2013, p. 335). Theory attributes the
influences of PFP plans to two broad sets of effects:
incentive effects and sorting effects (Cadsby, Song,
& Tapon, 2007; Gerhart & Fang, 2014; Gerhart &
Milkovich, 1992; Gerhart & Rynes, 2003; Gerhart,
Rynes, & Fulmer, 2009; Rynes, Gerhart, & Parks,

2005). Incentive effects represent
the influence of PFP plans through
employee motivation, based on the
premise that PFP plans can increase
employee motivation and, hence,
employee performance. Sorting
effects alter the composition of the
workforce, in that PFP plans can
affect the quality of workers who
apply for jobs (Lazear, 1986; Rynes
et al., 2005) and the performance
level of those leaving the organiza-
tion (Salamin & Hom, 2005; Shaw
& Gupta, 2007; Trevor, Gerhart, &
Boudreau, 1997). While there are
still some examples of ineffective
PFP plans (e.g., Beer & Cannon,
2004; Kahn & Sherer, 1990; Lawler,
2000; Pearce, Stevenson, & Perry,
1985; Pfeffer, 1998), the prepon-
derance of evidence shows that
PFP plans have positive effects (cf.,
Gerhart & Fang, 2014; Gerhart et
al., 2009). Yet, even with a substan-
tial body of research discussing the
effects of particular PFP interven-

tions, PFP research has typically failed to consider
the complex, multiplan environments in which
many organizations invest and many employees
face (Gerhart et al., 2009; Rynes et al., 2005). This
lack of consideration of more multifaceted envi-
ronments presents a theoretical gap for under-
standing and testing how relevant PFP theories
apply in more complex environments, and a
practical gap for organizations needing to predict
the sort of effects they should expect from their
multiplan environments.

While the literature on PFP plans is quite
extensive (for reviews, see Gerhart & Fang, 2014;
Gerhart et al., 2009; Guthrie, 2007; Rynes et al.,
2005), prior PFP research is largely based on specific

Human Resource Management DOI: 10.1002/hrm

EVALUATING FORM AND FUNCTIONALITY OF PAY-FOR-PERFORMANCE PLANS 699

What makes the study

of compensation

systems complex is

that some aspects

of PFP plans are

different by definition

(e.g., the reward

is permanent, a

one-time payment,

or will take time

before the reward is

vested), while other

characteristics can

vary both within and

across plan types

(e.g., the strength

of the relationship

between performance

and rewards, the

award size).

should differ in terms of both their incentive
and sorting effects (Gerhart et al., 2009). What
makes the study of compensation systems com-
plex is that some aspects of PFP plans are differ-
ent by definition (e.g., the reward is permanent,
a one-time payment, or will take time before the
reward is vested), while other characteristics can
vary both within and across plan types (e.g., the
strength of the relationship between performance
and rewards, the award size). While prior use of
theories regarding a single type of plan has typi-
cally yielded general predictions
that PFP plans should have posi-
tive effects, such a holistic approach
misses important characteristics of
PFP plans and has questionable (or
at least untested) generalizability to
considering the simultaneous effects
of multiple PFP plans. Based on pay
plans’ mechanisms, we can differ-
entiate between pay form and func-
tionality, which can vary depending
on different pay practices, thus
delineating where hypotheses can
be created based on the type of PFP
being provided (i.e., pay plan defi-
nition, or form) and those based on
the specific characteristics of the PFP
plan (i.e., pay plan functionality).

What’s in a Name Anyhow: The
Effect of Different Pay Forms

PFP plans come in a variety of forms,
both in terms of the level of the per-
formance metric (e.g., individual,
team, unit) and the type of award
it provides (e.g., recognition, non-
monetary awards, lump-sum cash
awards, long-term incentives [LTIs],
and permanent pay increases). It is
beyond the scope of any one study
to contrast every potential PFP plan,
and so we begin to address the
noted gap in compensation research
by considering three increasingly
common PFP plans: merit pay, indi-
vidual-based annual performance
bonuses, and LTIs. The first two of these are indi-
vidually based and rewarded; the third is awarded
to an individual and the size of the award depends
in part on individual performance, but ultimately
the value of the award depends on the overall
market performance of the organization and vest-
ing requirements.

Merit pay is a form of reward in which individ-
uals receive permanent pay increases (i.e., raises)
as a function of their individual performance

whether the predictions for individual PFP plans
would generalize when it is explicitly known that
other PFP plans are in operation. Furthermore, by
applying PFP-related theories to the context of
multiple PFP plans, we are examining a previously
unexplored set of processes. It is not immediately
evident what the effects of one PFP plan would be
after controlling for the effects of other PFP plans,
especially if the plans have related effects. This
study extends PFP theories to consider the context
of multiple PFP environments, where a portfolio
of PFP plans cover employees.

Second, we contribute to the compensation lit-
erature by considering a gap between research and
practice. Practically, we inform managers about
how different PFP plans should be combined to
increase employee performance in their organi-
zations. It is clear that organizations are invest-
ing significant sums of money into multiple PFP
forms (WorldatWork, 2010, 2012). With a sizable
and growing number of employees being covered
by two or more PFP plans, the lack of research on
the relative effectiveness of such plans represents
a notable gap in applicable research knowledge.
While many argue that practitioners should take
an evidence-based approach to management pol-
icy (e.g., Rousseau, 2006; Rousseau & McCarthy,
2007), the lack of research addressing this spe-
cific situation represents another notable discon-
nect between research and practice (e.g., Cascio
& Aguinis, 2008; Rynes, Giluk, & Brown, 2007),
a particular problem in the area of compensation
(Deadrick & Gibson, 2007; Rynes et al., 2007).

The purpose of this article is to apply existing
PFP-relevant theory to differentiate between the
effects of multiple PFP plans implemented simul-
taneously. We propose that a structural approach
to understanding PFP plans can be used to form
predictions on the relative effectiveness of dif-
ferent PFP plans for both incentive effects and
sorting effects. By considering the specific char-
acteristics of PFP plans, we can build theory to
predict not just the general (directional) effects of
PFP plans, but the relative effectiveness of plans.
Furthermore, we can extend theory to the purpose
of considering the simultaneous effects of multi-
ple PFP plans.

A Structural Approach to Compensation
Plans

Multiple types of PFP plans are often used through
a combination of individual-based rewards (e.g.,
merit pay, lump-sum bonuses, and individual
incentives) and/or group-based rewards (e.g.,
gain sharing, profit sharing) (Gerhart et al., 2009;
Milkovich et al., 2013). Every pay form has advan-
tages and disadvantages, and these programs

700 HUMAN RESOURCE MANAGEMENT, JULY–AUGUST 2016

Human Resource Management DOI: 10.1002/hrm

A pay plan’s name

reveals information

about its award,

but simply calling

something a PFP plan

does not necessarily

mean it links pay with

performance.

it links pay with performance. A number of theo-
ries suggest that the strength of the PFP link will
lead to beneficial incentive and sorting effects
(Lambert, Larcker, & Weigelt, 1993); thus, the
degree to which pay and performance are linked is
a critical characteristic of any PFP plan (Milkovich
et al., 2013; Zenger, 1992).

Expectancy theory proposes that employees
make rational decisions based on the character-
istics of the incentives they are facing (Bartol &
Durham, 2000; Fusilier, Ganster, & Middlemist,
1984; Vroom, 1964), hence, positing that, all else
being equal, motivation will be stronger if there is
a stronger link between performance and rewards
(Bartol & Durham, 2000; Bonner & Sprinkle, 2002;
Kahn & Sherer, 1990; Lawler, 1971). Thus, finan-
cial rewards that are strongly tied to individual
performance increase employees’ effort, and this
increased effort is supposed to lead to increases
in performance (Bonner & Sprinkle, 2002; Lawler,
1971). Similarly, agency theory predicts that if per-
formance can be monitored and tied to awards,
then the rewards system can improve individual
performance (Bartol & Locke, 2000; Eisenhardt,
1989). Agency theory also posits that a strong PFP
plan can help solve the risk-sharing problem that
organizations often experience in agency relation-
ships by leading people who are highly risk-averse
and less productive to leave their jobs (Cadsby
et al., 2007; Eisenhardt, 1989). Tournament the-
ory suggests that employees compete for higher
rewards, and so a stronger link between perfor-
mance and rewards should be associated with
greater effort to achieve the higher awards (Becker
& Huselid, 1992). At the same time, the competi-
tion among individuals attracts high performers
but increases voluntary turnover of poor perform-
ers (Bloom & Michel, 2002; Shaw & Gupta, 2007).
Even though some have argued that equity the-
ory is counter to PFP, it has been recognized that
equity does not mean equality (Brown, Sturman,
& Simmering, 2003; Trevor, Reilly, & Gerhart,
2012). To maintain equity across employees, it
is necessary to link pay and performance so that
individuals’ ratios of performance to rewards are
maintained across performance levels.

To understand the potentially different
effects of PFP plans, we must, therefore, specifi-
cally examine the strengths of the associations
between performance and rewards. Research has
provided examples of widely disparate relation-
ships between pay and performance under nomi-
nal PFP plans. For example, research has shown
varying relationships between raises and perfor-
mance under merit plans (e.g., Harris, Gilbreath,
& Sunday, 1998; Kahn & Sherer, 1990; Markham,
1988). Similarly, some research has examined

ratings (Heneman & Werner, 2005). The pay plan
is usually based on an individual’s performance,
assessed by an employee performance appraisal
(Rynes et al., 2005; Schwab & Olson, 1990). Merit
pay shares elements of both variable pay and fixed
pay. It is variable in that the pay raise depends
on individual performance, and thus new raises
must be re-earned each year. It is fixed, though,
in that any given merit raise increases base pay,
and thus regardless of future performance levels,
that new base pay will continue to be received
even if performance changes (barring employee
termination).

Bonus pay is a monetary reward given in addi-
tion to employees’ fixed compensation (Milkovich
et al., 2013). Bonuses are ostensibly based on indi-
vidual performance but do not increase employ-
ees’ base pay (Sturman & Short, 2000). This type
of pay plan has been widely used in organizations
to motivate employees’ performance, and surveys
report that the popularity of bonus pay is increas-

ing (cf. Sturman & Short, 2000;
WorldatWork, 2012). Individual-
based performance bonuses are
attractive from the company’s per-
spective because the one-time cash
rewards link pay to performance
but do not increase fixed labor costs
(Sturman & Short, 2000).

LTIs are rewards linked to a
firm’s long-term growth as well as
employee retention (Rousseau &
Ho, 2000), generally in the form of
cash or stocks (Moynihan, 2013).
LTIs allow a link between pay and
performance, and like bonuses
must be re-earned each year. Their

rewards, however, are not immediate. Employees
must wait until such awards are vested before their
value can be used. While companies have histori-
cally offered LTIs mostly to executives, many firms
have begun applying LTI plans to nonexecutive
employees (Core & Guay, 2001; National Center
for Employee Ownership, 2012; Oyer & Schaefer,
2005). LTI plans are also PFP plans because the
award itself may be a function of individual per-
formance, and the value of the incentives change
based on the performance of the organization.
This helps tie employee rewards to overall orga-
nizational performance, although such PFP is no
longer solely linked to individual performance.

Getting What You Pay For: The Link Between
Pay and Performance

As reviewed earlier, a pay plan’s name reveals
information about its award, but simply calling
something a PFP plan does not necessarily mean

Human Resource Management DOI: 10.1002/hrm

EVALUATING FORM AND FUNCTIONALITY OF PAY-FOR-PERFORMANCE PLANS 701

When we

consider the plans

simultaneously, the

situation is more

complex. We cannot

simply assume that

the incentive effects

from all three plans

combine linearly,

because their effects

are not independent.

multiple pay plans, one must therefore consider
the independent effects of each pay plan. That is,
we must ask: what is the effect of a given PFP plan
after controlling for the effects of the other PFP
plans that are present? For example, to know the
effect of merit pay in a multi-PFP environment,
we must look at the relationship between merit
pay and performance after controlling for the
relationships between pay and performance from
the other PFP plans. This represents the incen-
tive effects uniquely attributable to the particu-
lar PFP plan. Stated in more statistical terms, this
means we are looking at the partialed effects of
each pay form: the relationship between pay and
performance for a given pay form after control-
ling for the effects of the relationship between pay
and performance for all other pay forms. When
considering multiple PFP plans simultaneously,
we only expect a given PFP plan to
have an effect if the plan still has a
relationship with performance after
controlling for the relationships
from the other pay forms. Hence,
we predict:

Hypothesis 1: When considering the
incentive effects of multiple pay plans
simultaneously, the strength of the
connection between individual perfor-
mance and associated rewards, after
separating the PFP effects (i.e., control-
ling for effects) associated with other
pay plans, will be positively related to
future employee performance.

Relative Effects of PFP Plans,

Considered Simultaneously

Prior research has paid little atten-
tion to the valence (i.e., the attractiveness of
rewards) of the monetary awards across PFP plans
(cf. Gerhart, Minkoff, & Olsen, 1995). Yet with
the multiple pay forms that are the focus of this
study—merit pay, bonuses, and LTIs—one cannot
assume that valences are equal. Individuals should
value rewards differently due to their particular
characteristics. With unequal valences, the incen-
tive effects of different pay plans should likewise
be unequal.

The theories reviewed earlier have essentially
the same key takeaway: that more is better. As
has been most typically applied, that “more” has
been considered within the context of a single pay
form; yet, the same basic concept would seem to
apply if there are multiple pay forms. Expectancy
theory would predict that if one is covered by mul-
tiple pay plans, and assuming the plans operated

bonus plans that have only a modest correlation
between performance evaluations and bonuses
(e.g., r = .15 in Mizruchi, Stearns, & Fleischer,
2011), where others have shown stronger rela-
tionships (e.g., r = .42 in Salamin & Hom, 2005).
Research on LTI has been more limited. One
exception (Cappelli & Conyon, 2011) examined
how stock incentives relate to employees’ future
job performance. In the study, all employees at
the same administrative level received the same
amount of shares with the same vesting require-
ments. The results showed that higher profits
led individual employees to better performance.
This research shows that LTIs can influence indi-
vidual employee performance, but more research
is noted to understand how strong this effect is,
particularly in relation to other PFP options.

In this study, we consider complex envi-
ronments where more than a single PFP form
is provided. First, we look at incentive effects of
multiple PFP plans that have been implemented
simultaneously.

Incentive Effects of Pay-for-Performance

Incentive Effects of PFP Plans, Considered

Simultaneously

The fundamental premise behind PFP plans is that
by tying pay to higher performance levels, such
plans will motivate higher performance. All else
equal, and based most directly on expectancy and
tournament theory, stronger connections should
be associated with greater performance gains. The
context of a multiple PFP environment, though,
presents an untested theoretical question. In field
settings, it is often unclear if a specific PFP plan
under consideration was the sole PFP plan or if
other PFP plans might have been in place. The
theory, though, is quite general in its proposi-
tions, suggesting that if a given PFP plan creates
a link between performance and pay, it should be
associated with improved individual performance.
While prior findings predicted that each form of
PFP should be related to higher performance lev-
els, this has been framed when considering a com-
parison to a null effect (e.g., Banker et al., 1996,
2001; Lazear, 2000; Pearce et al., 1985) or relative
to the other plans (Kahn & Sherer, 1990; Nyberg,
Pieper, & Trevor, 2013).

When we consider the plans simultaneously,
the situation is more complex. We cannot simply
assume that the incentive effects from all three
plans combine linearly, because their effects are
not independent. Particularly, if we are consider-
ing how pay is tied to performance, the way in
which pay and performance are linked may essen-
tially overlap across plans. When considering

702 HUMAN RESOURCE MANAGEMENT, JULY–AUGUST 2016

Human Resource Management DOI: 10.1002/hrm

idea that a permanent increase has greater valence
than a one-time payment, or from a tournament
theory perspective stemming from a raise consti-
tuting a larger pay differential than a bonus, on
a unit-per-unit basis (e.g., a $1 raise versus a $1
bonus), the incentive effect for merit pay should
be greater than the incentive effect for bonuses.

LTIs represent one-time payments; however,
while bonuses are immediate payments, LTIs are
not. LTIs require a vesting period (cf. Dunford,
Oler, & Boudreau, 2008) and so are not immedi-
ately liquid. Stock awards are also more risky, as
the value of the award can fluctuate with time and
even become zero (Hull, 2012). As noted earlier,
all else being equal, individuals typically prefer
immediate rewards to delayed rewards (e.g., Green
& Myerson, 2004). In addition, the liquidity of
cash bonuses causes such rewards, on a dollar-per-
dollar basis, to have a greater present value than
a comparably sized stock award. Together, these
characteristics indicate a lower valence for LTIs
than both raises and bonuses. As our focus is on
predicting individual-level outcomes, we predict:

Hypothesis 2: If the separated PFP relationship (i.e.,
the effects for each plan, after controlling for the PFP
effects of the other plans) for each plan has effects (is
greater than zero), the incentive effect for merit pay on
individual job performance should be greater than the
incentive effect for bonuses, which should be greater
than the incentive effect for LTI.

However, if the PFP relationship for any pay
form is zero after controlling for the effects of the
other pay plans, then regardless of the pay form,
the effect of that PFP relationship should be unre-
lated to performance. Thus, we predict:

Hypothesis 3: For any plan type where the separated
PFP relationship (i.e., the effect of the plan, after con-
trolling for the PFP effects of the other plans) has no
effects (is not signifi cantly different from zero), the
incentive effect of the connection between pay and per-
formance for that plan on individual job performance
should be zero.

Sorting Effects of Pay-for-Performance

Sorting Effects of PFP Plans, Considered

Simultaneously

In addition to incentive effects, PFP plans can
play an important role in attracting and retaining
highly productive employees (Bartol & Durham,
2000; Gerhart & Fang, 2014). Research has shown
that the relationship between performance and
turnover is curvilinear, such that high perform-
ers and low performers are most likely to leave

independently (i.e., each relationship between
pay and performance effect was independent of
the other PFP relationships) and the valences for
those pay plans were equal (i.e., the rewards from
each plan were valued equally), the motivational
effects from multiple pay plans should be cumula-
tive. For considering multiple pay plans, however,
such simplifications are unlikely. This is due to
two fundamental issues that must be considered
to form hypotheses regarding multiple pay forms:
the different levels of valence across plans, and
the nonindependence of PFP relationships across
plans.

While there certainly may be individual differ-
ences with regard to pay preferences and valence
(Mitchell & Mickel, 1999), all else being equal,
a larger reward should be perceived more posi-
tively than a smaller reward. Similarly, individu-
als’ preferences for rewards are a function of delay
(i.e., immediate versus delayed rewards) and risk.
According to decision-making literature, future
uncertain rewards are less valued than immediate
assured rewards (Green & Myerson, 2004; Steel &
König, 2006). Immediate rewards should be per-
ceived more positively than a future reward of
the same amount. Likewise, a guaranteed reward
should be perceived more positively than a risky
reward. Steel and König (2006) addressed that
individuals are more likely to value immediate but
smaller rewards than large but distant ones when
they need to choose some behaviors that lead
to rewards. Indeed, people tend to undervalue
future events. Thus, the three pay plan types we
are examining—merit pay, bonuses, and LTIs—
clearly differ with regard to their value, immedi-
acy, and risk. The objective characteristics of the
rewards can, depending on individual differences,
be interpreted as the attractiveness of the rewards
(valence).

A key characteristic of merit pay is that it per-
manently increases employees’ base pay. Although
new merit raises have to be re-earned each year,
once a raise is given, the individual will continue
to receive that reward as long as the individual
remains with the organization. This characteristic
differentiates merit pay from the other forms of
PFP that we discuss. Bonuses are one-time pay-
ments, and thus do not change an individual’s
level of base pay (Sturman & Short, 2000). As a
one-time payment, the economic value of a bonus
is always less than that of a raise for any person
staying beyond one year. Due to the characteristics
of merit pay, the permanent increase from merit
pay has a greater lifetime value than the one-time
rewards granted by other pay plans (Shaw, Duffy,
Mitra, Lockhart, & Bowler, 2003). Whether from
an expectancy theory perspective based on the

Human Resource Management DOI: 10.1002/hrm

EVALUATING FORM AND FUNCTIONALITY OF PAY-FOR-PERFORMANCE PLANS 703

Each PFP plan will

have an effect on

reducing employee

voluntary turnover

when considered

simultaneously

because, to the

extent that each

plan links pay and

performance, each

plan is reinforcing the

equity relationship

that high outputs

(performance) are

tied to high inputs

(rewards).

high performers (Allen & Griffeth, 2001; Salamin
& Hom, 2005; Schwab, 1991; Trevor et al., 1997;
Williams, 1999). The degree of this contingency
should moderate the relationship between per-
formance and desirability of movement. This
prediction held in instances when raises (Trevor
et al., 1997) and bonuses (Salamin & Hom, 2005)
were related to performance, but not when raises
were unrelated to performance (Salamin & Hom,
2005). Thus, we expect that PFP, no matter what
the form, should help reduce the probability of
high-performer turnover, but also that the nature
of the reward (raise, bonus, or LTI) makes relative
differences in PFP effectiveness. It is again more
complex to consider multiple plans
operating simultaneously.

The way PFP influences turn-
over is based on the supposition
that it moderates the relationship
between performance and the desir-
ability of turnover (Allen & Griffeth,
2001). This is based more on theo-
ries of equity and fairness than
expectancy. As such, partialing out
the relationship between pay and
performance should not necessar-
ily have the same effect on turnover
as it does on performance. We still
expect that each PFP plan will have
an effect on reducing employee
voluntary turnover when consid-
ered simultaneously because, to
the extent that each plan links pay
and performance, each plan is rein-
forcing the equity relationship that
high outputs (performance) are tied
to high inputs (rewards).

The enduring nature of merit
pay indicates a potentially strong
sorting effect. Because a raise has a
permanent effect on base pay, once
it is earned in a given year, it will
be repeatedly earned, even if perfor-
mance declines. Furthermore, current raises can
lead to more future value because raises are com-
pounded. That is, as raises are typically expressed
as a percent of salary (Milkovich et al., 2013), a
raise creates more value for future raises. It may
also make future bonuses and LTI larger if they
are based on the size of the individual’s salary.
Thus, in comparison to a one-time bonus or LTI, a
raise should have the greatest potential for retain-
ing employees in contrast to a comparably sized
bonus or LTI. We, therefore, predict:

Hypothesis 4: When considering merit pay, bonuses,
and LTI plans simultaneously, the PFP for merit pay

an organization (Salamin & Hom, 2005; Sturman,
Shao, & Katz, 2012; Trevor et al., 1997). A higher
PFP relationship, however, should decrease high-
performer turnover because the high reward con-
tingency leads to lower desirability of movement
(e.g., Allen & Griffeth, 2001; Jackofsky, Ferris, &
Breckenridge, 1986; Trevor et al., 1997).

Empirical research specifically into how differ-
ent forms of PFP influence sorting effects, though,
is limited (Gerhart et al., 2009). Trevor et al.
(1997) looked at mean salary growth over a four-
year period. They found that higher salary growth
reduced the overall likelihood of turnover and the
turnover of high performers. Similarly, Salamin
and Hom (2005) looked at individuals’ mean pay
increase and latest bonus as moderators of the
performance-turnover relationship. They found
that bonuses reduced the probability of turn-
over. In contrast to Trevor et al. (1997), though,
Salamin and Hom (2005) found that raises had no
significant effect on how performance related to
turnover.

Both Trevor et al. (1997) and Salamin and Hom
(2005) considered how pay influences the effect of
performance on turnover; they did not, however,
specifically consider how strongly pay and perfor-
mance were linked. In Trevor et al. (1997), the cor-
relation between performance and average salary
growth was 0.30. In Salamin and Hom (2005), the
correlation between the mean pay increase and
performance was only 0.05, whereas the correla-
tion between performance and the latest bonus
was 0.42. Thus, the discrepant results associated
with pay increases between these two studies may
be due to the different strengths of the connection
between pay and performance (Zenger, 1992). In
both studies, when there was a higher correlation
between pay and performance (i.e., .30 or .42),
the pay system did improve retention of high
performers.

Research on LTI is more limited. Some research
on executive compensation has shown that stock
awards and other LTI are associated with reduced
turnover (e.g., Batt & Colvin, 2011; Mehran &
Yermack, 1996). Other research has examined
how repricing underwater stock options influ-
ences turnover (e.g., Carter & Lynch, 2004; Daily,
Certo, & Dalton, 2002; Dunford et al., 2005). No
research has yet addressed if LTI affects the perfor-
mance-turnover relationship.

Research also has yet to specifically exam-
ine the degree to which a PFP link for multiple
types of pay forms influences individual turn-
over. Relevant theory, however, can provide some
insights into the nature of the sorting effects
that we might expect. Tying pay to performance
should reduce the desirability of turnover for

704 HUMAN RESOURCE MANAGEMENT, JULY–AUGUST 2016

Human Resource Management DOI: 10.1002/hrm

bonuses actually had a positive effect on intent-
to-turnover. Thus, because bonuses seemingly
can create both incentives and disincentives for
turnover when considered simultaneously with
other PFP plans, we have no a priori hypotheses
regarding their effects when considered in con-
junction with merit raises and LTI.

Method

Sample

The data for this study were obtained from a large
service-related company that was a subsidiary of a
larger, diversified publicly traded American corpo-
ration. The company that is the focus of our study
offers broad-based business services to companies
in the global travel industry, providing technol-
ogy and support to global travel companies and
managing technology related to online travel.
The business, thus, focuses on issues of technol-
ogy and pricing, but has positions in account sales
and service, accounting, customer training and
support, finance, human resources, legal, mar-
keting and communications, and product and
technology development. The company provided
data on performance ratings, gender, organization
tenure, salary, and percentage of three financial
rewards (merit pay, bonuses, and LTIs) associated
with 2001 and 2002. We only examined employ-
ees who had performance ratings in 2001, did not
leave involuntarily in 2002, and were eligible for
all three forms of compensation. This resulted in
an original potential sample of 900 employees
from 17 locations in the United States. All posi-
tions were white collar, exempt, full time, and
required a college degree. The most common job
titles were developer, senior developer, systems
engineer, travel supervisor, account manager, and
project manager.

It should also be noted that the references to
the calendar year are not entirely precise in that
they refer to the relevant time period and not
the date of the award or decision. Performance
reviews in a given year are intended to reflect the
individual’s performance for that calendar year (so
the 2001 performance rating is designed to cap-
ture performance during the 2001 year but was
determined in early 2002). Compensation awards
associated with a given year reflect the award
of each type given for that year. Thus, the 2001
bonus is actually awarded in 2002, but is awarded
to the individual for service over the 2001 year.
Similarly, the 2001 raise is awarded in early 2002,
as is the 2001 LTI. We refer to 2001 rewards to
represent the awards associated with 2001 perfor-
mance. Note that 2001 salary, though, was the sal-
ary at the beginning of 2001.

will negatively moderate the performance-turnover
relationship.

While we again predict the strongest effect for
merit pay, the sorting effects of bonuses versus LTI
should differ from their incentive effects. A key
purpose of deferring compensation is to foster
employee retention (e.g., Core & Guay, 2001; Jones
& Kato, 1995; Oyer & Schaefer, 2005). Providing
LTI increases the cost of turnover for employees
because leaving the organization requires them to
forfeit any rewards that are not vested. Thus, we
predict:

Hypothesis 5: When considering merit pay, bonuses,
and LTI plans simultaneously, the PFP for LTI
will negatively moderate the performance-turnover
relationship.

Relative Effects of PFP Plans, Considered

Simultaneously

Both merit pay and LTI, by increasing the cost of
turnover, should reduce the likelihood of high-
performance turnover. Yet because a merit pay
award has greater value than an equally sized LTI
award, we again expect merit pay to have a stron-
ger effect. We, therefore, predict:

Hypothesis 6: When considering merit pay, bonuses,
and LTI plans simultaneously, the effect of PFP on the
performance-turnover relationship will be stronger (i.e.,
more negative) for merit pay than for LTI.

The nature of bonuses, though, makes their
effects less clear. This is because bonuses have
characteristics that both decrease the desirabil-
ity of movement but increase the ease of move-
ment. By having a connection between pay and
performance, bonuses will increase equity and
fairness perceptions of high performers, thus
decreasing the desirability of movement. At the
same time, the large monetary influx from a
large bonus may actually increase the individ-
ual’s ease of movement. This can occur because
either (1) the monetary reserves make leav-
ing one job and finding another more feasible,
or (2) if the individual had an intent to leave,
was a high performer, and was expecting a large
bonus, it would be most logical to wait for the
bonus before leaving the position. Consistent
with this, Sturman and Short (2000) showed
that bonus satisfaction was negatively related to
intent to turnover when not considering other
aspects of pay satisfaction or other attitudes;
however, after controlling for the other pay
satisfaction dimensions (including for raises),

Human Resource Management DOI: 10.1002/hrm

EVALUATING FORM AND FUNCTIONALITY OF PAY-FOR-PERFORMANCE PLANS 705

“turn into” actual shares of the company’s real
stock. In other words, when granted, the restricted
stock had no immediately realizable monetary
value (although it was expressed as such, based
on the number of shares and its current price).
The company used a five-year gradual vesting
schedule, with 20 percent of the stocks becoming
vested each year (and the value of that award con-
stituting income). Once vested, the award had the
same market value as any other share of common
stock from the organization. Over the span of this
study, the value of company stock did vary, but
increased an average of 1.08 percent per month.
Employees of the company were educated about
the financial rewards system via intranet, written
communication, and training workshops.

Measures

Employee Job Performance

Employee job performance ratings from 2001 and
2002 were used as independent and dependent
variables. The ratings used a 4-point scale: signifi-
cantly exceeds expectations, exceeds expectations,
meets expectations, and is below expectations.
The ratings were transformed to indicator vari-
ables from 1 (lowest performance) to 4 (highest
performance). The company used “management
by objectives” to create performance ratings, and
significant time was allocated by the organization
for these purposes.

For predicting turnover, we needed to exam-
ine potential nonlinear effects of performance
(Salamin & Hom, 2005; Sturman et al., 2012;
Trevor et al., 1997). For these analyses, we con-
sidered both a linear effect, computed as a mean-
centered measure of 2001 performance, and a
quadratic effect. Because we wanted to specifi-
cally differentiate between linear and nonlinear
effects, we needed to ensure that the two terms
were orthogonal. Although mean-centering (cf.
Aiken & West, 1991) is common and can reduce
the correlation between linear and squared terms,
it does not yield orthogonal terms. Indeed, in
this case, mean centering would still result in the
linear and quadratic terms being correlated 0.21.
We, therefore, used residual centering (Lance,
1988). That is, we regressed the squared term on
the linear term and used the residual to represent
the quadratic effect. This residual is uncorrelated
with the linear term but captures the nonlinearity
associated with the squared term (Lance, 1988).
Residual centering has been shown to be effective
in cases like this one, in which (1) the main and
quadratic effects are correlated, (2) sample sizes
are moderate to large, and (3) decomposition of
the effects is desired (Lance, 1988).

To provide an estimate of the PFP relation-
ships for each employee (as will be explained in
greater detail below), we calculated the relation-
ship that existed between 2001 performance and
each resultant form of compensation for 2001
performance under each supervisor. Thus, we
eliminated all individuals in the sample who did
not have the same supervisor in both 2001 and
2002 and (for the purposes of being able to com-
pute PFP relationships for each supervisor, as we
will explain below) all employees under supervi-
sors who did not have at least three subordinates.
This resulted in a sample of 720 employees under
88 supervisors. Supervisors had an average of 8.1
subordinates (SD = 7.58; range = 3 – 59). For pre-
dicting 2002 performance, we eliminated subjects
who left the organization (and thus did not have
2002 performance ratings), resulting in a sample
of 635 employees (also under 88 supervisors).

Organizational Compensation System

The organization provided guidance to supervi-
sors regarding the allocation of compensation,
but supervisors had discretion in the allocation
decisions. This is a typical approach used by many
organizations for their PFP plans (cf. WorldatWork,
2012). For merit pay, a range of percent pay
increases were specified for each performance rat-
ing category. Supervisors had discretion regarding
what the specific raise should be within this range.

The company paid bonuses, which reflected
the judgment of the supervisor based on the indi-
vidual’s performance rating and the individual’s
position. Each position had a bonus target, based
on its degree of responsibility. Organizational per-
formance affected the amount of total rewards that
would be distributed, a decision made by execu-
tives within the organization (not in our sample).
Supervisors were given a budget with which to
allocate rewards to their subordinates. They were
instructed to use the bonus target and individual
performance to guide their decisions, but had dis-
cretion with regard to how actual distributions were
made. Managers did not have complete discretion,
though, in that all pay decisions were ultimately
approved by the human resources department.

The distribution of LTI was based on both orga-
nizational performance (which determined the
budget for this award) and individual job perfor-
mance, although the dollar value of actual awards
was also affected by the performance of the com-
pany’s stock. Each year, the company distributed
restricted stock units to their employees based on
individual performance and criticality of employ-
ees’ job positions. At the time of the award, the
restricted stock had no real market value. Rather,
these stock grants would, at a future vesting date,

706 HUMAN RESOURCE MANAGEMENT, JULY–AUGUST 2016

Human Resource Management DOI: 10.1002/hrm

This approach to measuring PFP, while new,
has a number of advantages. Most notably, it
directly assesses the simple and straightforward
relationship that exists between pay and perfor-
mance for each pay form, which matches the
measure to the theoretical premise better than
other PFP measures have done. Note also that this
approach does not require us to assume that indi-
viduals know what others get paid. If a supervi-
sor has a strong PFP relationship, a low performer
will see a low reward and a high performer will
see a higher reward (which is similar to what a
ratio score would yield). If the supervisor has no
relationship between pay and performance, this
measure will yield a zero as opposed to a ratio
score what would yield a high value for a low
performer and low value for a high performer.
Although individuals may or may not know what
others receive, people are likely aware of what
typical awards are, either in the company overall
or in the economy. A measure of slope (which is
what our measure is), thus, does not suffer from as
much random variance that can occur with ratio
scores, even without necessarily assuming that
individuals know the performance and rewards
of their peers. It should also be noted that this
metric has very practical benefits. As an objective
measure of PFP, it captures the actual relationship
that exists between pay and performance, which
is something that can be influenced by organiza-
tional policy. It is also a measure that companies
can calculate using archival data, and thus allows
organizations to critically evaluate their current
PFP plans.

Voluntary Turnover

Voluntary turnover included departures from
the company during 2002. One concern in turn-
over research is that some previous research has
failed to distinguish between voluntary turn-
over and involuntary turnover (Gardner, Wright,
& Moynihan, 2011; Gerhart, 1990; Wright &
Cropanzano, 1998). Fortunately, the company
provided specific information that distinguished
between voluntary and involuntary turnover.
Thus, we considered only voluntary turnover. In
the sample, 85 (12 percent) of the 720 employ-
ees voluntarily left the company. We used a “0” to
indicate that an employee stayed with the com-
pany and a “1” to indicate voluntary turnover
(although it was treated in most analyses as a cat-
egorical variable).

Control Variables

Because this study examined the effect of finan-
cial rewards on employees’ future performance,
previous performance (i.e., 2001 job performance

Measuring the Pay-for-Performance

Relationships

To test our hypotheses, we needed a measure of
the link between pay and performance for the
three compensation plans. Prior compensation
research has examined this by looking at the
reward received (e.g., the change in pay or total
compensation) divided by the performance score
(e.g., a given dollar change in shareholder value
or firm return) (e.g., Hall & Knox, 2004; Hayes,
2004) or by calculating the derivative of pay
with respect to performance (e.g., Kahn & Sherer,
1990). The former approach is not ideal for our
study, as it is simply an individual’s ratio and does
not directly capture a relationship between pay
and performance. It is unclear if effects from such
ratios are due to the numerator, denominator, or
the hypothesized combination of the two. It also
does not capture if indeed there is a pattern of pay
and performance effects across individuals (which
is what PFP plans are purported to have). The
approach of calculating a derivative (e.g., Kahn
& Sherer, 1990) more directly assesses if there is
a relationship between performance and pay, but
the approach is based on looking at effects asso-
ciated with interactions with performance scores
(because if there is a straightforward relationship
between pay and performance, this becomes a
constant that is equal across subjects). We wanted
to more directly assess exactly how pay and per-
formance are related to each other within groups
that should share a similar effect. To estimate this
relationship for each employee, we examined the
strength of the link between pay and performance
under each supervisor.

For each supervisor (as noted above, with at
least three subordinates), we computed the three
regression coefficients that estimated the relation-
ships between 2001 performance and the three
forms of 2001 rewards. For each supervisor and
pay form, the percent reward was regressed on the
employee performance rating. Rewards were pre-
sented as percentage points (so 1 = 1 percent), and
the raw rating metric (1–4) was used as the inde-
pendent variable. For each pay form, we thus ran
88 regressions. This yielded 88 B coefficients associ-
ated with each of the three PFP relationships, which
we labeled PFP-Merit, PFP-Bonus, and PFP-LTI.

It should be noted that, for subsequent analy-
ses, our PFP metrics were not independent. That
is, individual observations of PFP were not fully
independent because employees under the same
supervisor operated under the same PFP relation-
ship. We thus needed to use multilevel modeling
(Raudenbush & Bryk, 2002) when considering the
PFP effects of the various plans.

Human Resource Management DOI: 10.1002/hrm

EVALUATING FORM AND FUNCTIONALITY OF PAY-FOR-PERFORMANCE PLANS 707

relative effects of different PFP plans, our depen-
dent variable was 2002 job performance. The level
1 model we used was:

Perf
2002

= B
00

+ B
1
*Perf

2001
+ B

2
*Gender

+ B
3
*Tenure + B

4
*ln(Salary

2001
)

+ B
5
*Merit percent + B

6
*Bonus percent

+ B
7
*LTI percent + ε [1]

In this model, the intercept (B
00

) was modeled
as a random effect.

The second level of analyses varied depend-
ing on what type of PFP plans we tested. As noted
earlier, we first examine each PFP plan separately.
The purpose of this test is to examine if prior PFP
research conducted on a single plan generalizes to
a situation where one is examining a single plan
within a multi-PFP context. While these models
are not used to test our hypotheses, it is impor-
tant to see if prior research (in which we do not
know whether a plan was operating in a multi-PFP
plan environment) is consistent with a purposely
underspecified model (i.e., when we examine a
single PFP plan at a time, but we do know that
the plan is operating in a multi-PFP plan environ-
ment). For these models, the PFP effect for each
pay form was entered as the sole level 2 variable.
So, to test the effect of merit pay (Model 2a), the
level 2 equation was

B
00

= G
00

+ G
01

*PFP-Merit + ξ [2a]

whereas to test the effect of bonus pay (Model 2b),
the level-2 equation was

B
00

= G
00

+ G
01

* PFP-Bonus + ξ [2b]

and to test the effect of LTI (Model 2c), the level 2
equation was

B
00

= G
00

+ G
01

* PFP-LTI + ξ [2c]

This study’s hypotheses consider the role of
multiple PFP plans operating simultaneously. To
test our hypotheses related to incentive effects of
all three plans simultaneously (Model 3), the level
2 equation was as follows:

B
00

= G
00

+ G
01

*PFP-Merit + G
02

*PFP-Bonus
+ G

03
*PFP-LTI + ξ [3]

Sorting Effects

For assessing sorting effects, because turnover is
a dichotomous variable, we used the Bernoulli
model in HLM. Thus, our analyses are multilevel
but analogous to logistic regression (Raudenbush

rating) was used as a control variable. Using prior
performance as a control variable helps par-
tial out the effects of stable characteristics that
caused employees’ performance (Sturman, 2003;
Sturman, Cheramie, & Cashen, 2005) and unmea-
sured effects that are attributable to omitted fac-
tors (e.g., ability, job knowledge, motivation levels,
or opportunities to perform) that might affect per-
formance and pay (Kahn & Sherer, 1990; Sturman,
2007). While performance ratings certainly are not
perfect measures (Viswesvaran, Ones, & Schmidt,
1996), its inclusion does help address the alterna-
tive explanation that high performers get rewarded
but also remain high performers. We want to know
what effect PFP has beyond knowing that, in gen-
eral, past performance is the best predictor of
future performance (Sturman et al., 2005).

Organization tenure was used as a control
variable because it could interfere with test-
ing the main effects of the different characteris-
tics of financial rewards on future performance
(Sturman, 2003). Gender differences have been
considered a potentially important factor caus-
ing pay differences (Milkovich et al., 2013), and
so were also controlled for (with men coded as 0,
and women coded as 1). Additionally, salary from
2001 was controlled in this study, as was the level
of the most recent raise, bonus, and LTI. Because
the salary data was skewed, we used a log transfor-
mation to reduce the leverage of high values. The
raise, bonus, and LTI were expressed as a percent
of salary (before log transformation).

Analyses

Before we tested our hypotheses, we wanted to
replicate prior findings and thus see if our sam-
ple provides similar results to prior research. Our
analyses are conducted in a series of steps. First,
we create a baseline model without PFP variables,
to serve as a point of reference (Model 1). We then
run a series of models in which we consider a
single pay plan at a time. This allows us to repli-
cate prior research that has examined a single pay
plan at a time but did not consider if other PFP
plans were in effect. Thus, we run a model exam-
ining merit pay (Model 2a), bonuses (Model 2b),
and LTIs (Model 2c). Then, we test our hypotheses
with the model that includes all three plans simul-
taneously (Model 3).

Incentive Effects

In all of our models, because individuals were
nested within supervisors, we used hierarchical
linear modeling (Raudenbush & Bryk, 2002) using
the HLM7 statistical package (Raudenbush, Bryk,
Cheong, Congdon, & du Toit, 2011). To test the
incentive effects of independent PFP plans and

708 HUMAN RESOURCE MANAGEMENT, JULY–AUGUST 2016

Human Resource Management DOI: 10.1002/hrm

by Gerhart and Fang (2014). The mean PFP rela-
tionship for merit pay was 0.62 (SD = 0.14) and
ranged from 0 to 0.95; for bonuses, the mean was
0.73 (SD = 1.9) and ranged from –1.1 to 10.5; and
for LTI, the mean was 0.57 (SD = 1.48) and ranged
from 0.02 to 9.2. This means, for example, a one-
point increase in performance was associated
with, on average, a 0.62 percentage point higher
raise. The average raise for a high performer (4)
is thus 1.86 percentage points higher than that
for low performer (1). For some supervisors, larger
bonuses were actually granted to lower perform-
ers, as evidenced by a minimum PFP-Bonus value
of –1.1. However, as noted, the average relation-
ship was 0.73.

There are also some strong correlations among
the PFP variables and the pay amount percent vari-
ables. For example, the relationship between PFP-
Bonus and PFP-LTI was strong (r = .73), showing
that managers are fairly consistent in how they
distribute bonuses and LTI. Of course, although
a high correlation, it still indicates that nearly
half the variance between these variables is unex-
plained, and thus there clearly are differences in
how managers allocate awards.

Variance components for all models are pre-
sented in Tables III and IV. For both the prediction
of 2002 job performance and voluntary turnover,
the analyses revealed significant level 2 variance
(p < .05) for the intercepts in the random-inter-
cepts models.

Replicating Previous Findings

Independent Incentive Effects

Models 2a, 2b, and 2c in Table III present the
results of the HLM analyses, which examine a sin-
gle pay plan at a time. These results are consistent
with existing theory and prior empirical work.
Note that these are not nested models, not fully
comparable, and thus not used for our hypothesis
tests. The purpose of these models is to illustrate
what the results would look like if a researcher
were examining a single PFP plan at a time in a
multi-PFP environment. The results show that
the strength of a PFP plan’s connection between
individual performance and rewards is positively
related to future employee performance when
considering a single PFP plan at a time. As shown
in Models 2a, 2b, and 2c (for merit pay, bonuses,
and LTI, respectively), all three PFP relationships
were significantly related to future performance
(all at p < .001).

Independent Sorting Effects

Table IV presents the analyses predicting 2002 vol-
untary turnover, and specifically how the strength

& Bryk, 2002). For our test of independent sorting
effects, our level 1 model was as follows:

Prob(turnover) = B
00

+ B
10

*Perf
2001

+ B
20

*Perf2
2001

+ B

3
*Gender + B

4
*Tenure

+ B
5
*ln(Salary

2001
) + B

6
*Merit

percent + B
7
*Bonus percent

+ B
8
*LTI percent + ε [4]

For this model, the intercept and the effects of
performance could potentially vary across super-
visors, as these coefficients could be affected by
the degree of PFP resulting from each supervisor’s
decisions. Testing revealed, though, that there was
only significant level 2 variance for the intercept
term; for B

10
and B

20
, the variance component was

not significant (at p > .50). Thus, only the inter-
cept was modeled as a random effect. Nonetheless,
for all three of these coefficients, the level 2 equa-
tions were equivalent to Equations 2a, 2b, and 2c
above, with the key differences being that (1) there
are three equations, with the dependent variables
being B

00
, B

10
, and B

20
, and (2) there was no level

2 error term in the equations predicting B
10

and
B

20
. Thus, to test the hypotheses related to sorting

effects, the level 2 equations were as follows:

B
00

= G
00

+ G
01

*PFP-Merit + G
02

*PFP-Bonus
+ G

03
*PFP-LTI + ξ [5a]

B
10

= G
00

+ G
01

*PFP-Merit + G
02

*PFP-Bonus
+ G

03
*PFP-LTI [5b]

B
20

= G
00

+ G
01

*PFP-Merit + G
02

*PFP-Bonus
+ G

03
*PFP-LTI [5c]

Results

Summary statistics are presented in Tables I and
II. Table I presents the summary statistics for the
portion of the sample (N = 635) used in the analy-
ses predicting job performance; Table II presents
the summary statistics for the sample used in the
prediction of turnover (N = 720). Note that the
means of merit percent, bonus percent, and LTI
percent (shown in Table II) were 3.08 percent,
7.02 percent, and 1.19 percent, respectively. Thus,
the average additional compensation received by
employees was 11.29 percent, although only 3.08
percent was an increase in base pay.

For merit pay, across the four performance rat-
ings, the average pay increases were 1.9 percent
(below expectations), 2.8 percent (average perfor-
mance), 3.3 percent (exceeding expectations), and
4.6 percent (far exceeding expectations). These
levels are similar to the average merit increases in
these or similar performance categories reported

Human Resource Management DOI: 10.1002/hrm

EVALUATING FORM AND FUNCTIONALITY OF PAY-FOR-PERFORMANCE PLANS 709

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Human Resource Management DOI: 10.1002/hrm

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Human Resource Management DOI: 10.1002/hrm

EVALUATING FORM AND FUNCTIONALITY OF PAY-FOR-PERFORMANCE PLANS 711

Trevor et al., 1997; specifically, the probability of
turnover was, on average 52 percent, 14 percent, 7
percent, and 16 percent for performance scores 1
to 4, respectively). Adding the PFP variables to the
second level of analysis was likewise consistent
with prior research.

The results also show that the strength of
each plan’s PFP link negatively moderated the
performance-turnover relationship. As with the
replication of the incentive effects, this pertained
to considering individual PFP plans separately. As

of the various PFP links influence the perfor-
mance-turnover relationship. Again, these results
show that our sample produces results consistent
with prior research.

A model with no level 2 variables (Model 1
in Table IV) showed that performance had the
expected negative linear effect (G

10
= –.54; p < .05)

and positive nonlinear effect (G
20

= .71; p < .001),
thus replicating the predicted inverted U-shape
relationship between performance and turnover
(Salamin & Hom, 2005; Sturman et al., 2012;

T A B L E I I I Separate and Partialed Effects of PFP Plans

Variable Model 1 Model 2a Model 2b Model 2c Model 3

For Intercept (Random Effect)

Intercept –3.06 –2.38 –2.48 –2.84 –2.93

(.68)*** (.62)*** (.71)*** (.65)*** (.62)***

PFP-Merit 10.98 88.22

(28.16)*** (28.94)**

PFP-Bonus 8.09 8.09

(1.86)*** (4.81)*

PFP-LTI 8.63 –2.06

(2.31)*** (5.84)

2001 Performance .14 .15 .14 .14 .15

(.048)** (.048)** (.047)** (.048)*** (.048)**

Gender .0087 .0034 –.0093 –.0051 –.012

(.034) (.031) (.034) (.034) (.032)

Tenure –.0034 –.0027 –.0021 –.0026 –.0017

(.0027) (.0026) (.0026) (.0027) (.0025)

Ln (2001 Salary) .34 .33 .29 .32 .28

(.067)*** (.064)*** (.060)*** (.064)*** (.057)***

Merit pay (%) 61.61 57.35 57.98

(5.71)*** (6.62)*** (6.60)***

Bonus Pay (%) –.54 –1.07 –1.27

(.95) (.65) (.94)

LTI (%) .082 –1.22 –.47

(1.01) (.96) (.93)

Fit Statistics

Model Likelihood –341.50 –325.60 –331.17 –333.53 –315.73

Sigma2 .1490 .1473 .1478 .1477 .1464

% LV 1 Var 68% 69% 69% 69% 69%

Explained

Random Effects .0319*** .0229*** .0255*** .0291*** .0196***

Variance Component

Percent Variance 79% 95% 95% 94% 96%

Component Explained

Notes: N (level 1) = 635; N (level 2) = 88. *p < .05; **p < .01; ***p < .001. For the null model, Sigma2 = .4693. For the random intercepts

model, likelihood = –624.98, Sigma2 = .3510 (25% explained), the random effects variance component = .1458 (signifi cant at p < .001), and

ICC(1) = .31.

712 HUMAN RESOURCE MANAGEMENT, JULY–AUGUST 2016

Human Resource Management DOI: 10.1002/hrm

T A B L E I V Prediction of Turnover

Variable Model 1 Model 2a Model 2b Model 2c Model 3

For Intercept (Random Effect)
Intercept –1.45 –3.42 –1.90 –5.70 –2.00

(4.82) (4.31) (4.70) (4.63) (5.51)

PFP-Merit –262.34 –227.10

(143.36)* (115.77)*

PFP-Bonus –2.77 92.21

(13.92) (26.40)***

PFP-LTI –76.05 –242.17

(50.27)† (78.77)**

2001 Performance (linear)

Intercept –.54 –.73 –.53 –1.14 –2.05

(.27)* (.27)** (.19)** (.48)** (.59)***

PFP-Merit –823.81 –793.07

(223.88)*** (185.76)***

PFP-Bonus –30.33 21.29

(16.30)* (27.15)

PFP-LTI –162.77 –298.61

(88.55)* (123.49)**

2001 Performance (Quadratic)

Intercept .71 .64 .60 .20 –.083

(.25)** (.22)** (.21)** (.33) (.41)

PFP-Merit –497.56 –332.38

(241.34)* (253.46)†

PFP-Bonus –31.67 38.69

(18.93)* (43.14)

PFP-LTI –120.65 –222.78

(53.87)* (86.00)**

Gender .25 .27 .32 .39 .34

(.25) (.27) (.27) (.27) (.31)

Tenure –.088 –.086 –.094 –.098 –.095

(.020)*** (.021)*** (.022)*** (.022)*** (.023)***

Ln (2001 Salary) .023 .20 .070 .39 .020

(.43) (.39) (.43) (.42) (.49)

Merit pay (%) 11.38 31.21 23.55

(28.49) (23.10) (23.16)

Bonus Pay (%) 7.51 2.70 –1.50

(5.56) (3.69) (6.39)

LTI (%) –10.23 4.44 8.67

(8.92) (6.31) (10.72)

Fit Statistics

Model Likelihood

Sigma2 .0944 .0912 .0939 .0938 .0916

% LV–1 Var 10% 13% 11% 11% 13%

Explained

Random Effects .3406 .3606 .3872 .4063 .1877

Variance Component

Percent Variance 17% 12% 5% 1% 54%

Component Explained

Notes: N (level 1) = 720; N (level 2) = 88. †p < .10; *p < .05; **p < .01; ***p < .001. For the purpose of reporting level 1 variance explained in

the turnover model, as no level 1 sigma is given for a dichotomous outcome, the table reports the sigma2 for a normal (continuous) outcome

variable. All other turnover analyses are based on the more appropriate Bernoulli outcome model.

Human Resource Management DOI: 10.1002/hrm

EVALUATING FORM AND FUNCTIONALITY OF PAY-FOR-PERFORMANCE PLANS 713

shown in Models 2a, 2b, and 2c of Table III, if we
were studying any single pay plan at a time that was
operating in a multi-PFP environment, the effects
of the PFP relationships all had negative effects on
the linear and/or quadratic performance variables
(all at p < .05), thus indicating that a stronger PFP
relationship was associated with a lower probabil-
ity of turnover as performance increased. So, as
with incentive effects, were this a study about a
single PFP plan, we would have yielded conclu-
sions similar to prior research about PFP plans.

Tests of Relative Incentive Effects
(Hypotheses 1–3)

Tests of our hypotheses regarding relative incen-
tive effects are shown in Table III, supporting
our hypotheses. The three hypotheses pertained
to considering all three plans simultaneously.
Testing these hypotheses involved considering the
separated effects of each plan’s PFP relationship.
This is important because the PFP relationships for
the three pay practices are correlated, with a par-
ticularly high correlation between PFP for bonuses
and PFP for LTI.

We first computed the partial correlation for
each of the three PFP variables on 2001 perfor-
mance (i.e., the correlation between each PFP vari-
able and 2001 performance with the effects of the
other two PFP variables separated out). We found
that, while the raw correlation of each PFP rela-
tionship was significantly related to performance,
the partial correlation coefficient for merit pay
was largest (r

My.B,L
= .16), followed by a smaller but

still significant effect for bonuses (r
By.M,L

= .09), and
no significant relationship for LTI (r

Ly.M,B
= –.04).

Hypothesis 1 predicted that when consider-
ing the incentive effects of multiple pay plans
simultaneously, the strength of the connection
between individual performance and associated
rewards, after separating out the PFP relationship
associated with other PFP plans, would be posi-
tively related to future employee performance.
Therefore, we expected a positive effect in our full
model from merit pay and bonuses, but no effect
for LTI. Model 3 in Table III indeed supports this.
The effect for PFP-Merit was significant (B = 88.22,
p < .01), as is the effect for PFP-Bonus (B = 8.09,
p < .05); the effect of LTI was nonsignificant (B =
–2.06, p = .73).

Hypothesis 2 predicted that for each plan with
separate significant PFP relationships, the effect
for merit pay would be greater than the effect for
bonuses, which again was supported (p < .01).
Because PFP-LTI had no separated effect (i.e., the
partial correlation coefficient was not significant),
Hypothesis 2 did not pertain to it. Hypothesis
3 predicted that, for any plan type where the

separated PFP relationship was zero, which is true
here for LTI, the effect of the connection between
pay and performance for that plan should be zero.
Indeed, as noted above, the effect of PFP-LTI is
nonsignificant (p = .73).

Tests of Relative Sorting Effects
(Hypotheses 4–6)

The second half of our hypotheses considered
the relative sorting effects of PFP plans, and spe-
cifically how the strength of the various PFP links
would influence the performance-turnover rela-
tionship. Model 3 in Table IV shows the analyses
predicting 2002 voluntary turnover and our tests
of Hypotheses 4 through 6.

The three hypotheses considered the effects
of all three PFP plans when analyzed together.
Hypothesis 4 predicted that, when considering
merit pay, bonuses, and LTI plans simultaneously,
the PFP relationship for merit pay would nega-
tively moderate the performance-turnover rela-
tionship. This was supported by a negative effect
of PFP-Merit on the linear effect of performance
(p < .001) and a marginally non-significant effect
on the quadratic terms (p = .095). Hypothesis
5 predicted that, when considering merit pay,
bonuses, and LTI plans simultaneously, the PFP
relationship for LTI would negatively moderate
the performance-turnover relationship, which
was supported by both significant effects on the
linear (p < .01) and quadratic terms (p < .001).
Finally, Hypothesis 6 predicted that when consid-
ering merit pay, bonuses, and LTI plans simulta-
neously, the effect of PFP on turnover would be
stronger (i.e., more negative) for merit pay than
for LTI. This was supported by the negative effect
of PFP-Merit being significantly more negative
than the effect for LTI on the linear performance
term (p < .05). The effect on the quadratic term
was more negative as predicted, although the dif-
ference did not approach statistical significance
(p = .35).

As noted earlier, we had no a priori predictions
regarding the effect of bonuses when considered
simultaneously with merit pay and LTI. Our analy-
ses revealed that, in the analysis with all three PFP
effects, bonuses increased the overall probability
of turnover through its significant positive effect
on the intercept (p < .001; note that merit pay and
LTI had significant negative effects). Bonuses had
no effect on either the linear or quadratic perfor-
mance terms.

Discussion

Prior work on PFP has generally shown positive
incentive and sorting effects, yet this work has
not explicitly considered what effects we should

714 HUMAN RESOURCE MANAGEMENT, JULY–AUGUST 2016

Human Resource Management DOI: 10.1002/hrm

The general findings

of incentive and

sorting effects

do hold when

considering PFP

plans independently,

even when other PFP

plans are operating

but are not controlled

for in the analyses.

do indeed support the applicability of expectancy
theory for making such predictions. In the rep-
lication, the results show that merit pay is more
valuable than a bonus or LTI on a dollar-per-dollar
basis, and indeed it has stronger incentive and
sorting effects.

Third, we expanded on prior theory to con-
sider the implications of multiple pay plans
being implemented simultaneously. While some
prior work has analyzed situations with multi-
ple pay plans (Kahn & Sherer, 1990; Salamin &
Hom, 2005), both of those studies had one pay
plan where rewards were unrelated to perfor-
mance; additionally, these studies did not explic-
itly consider how multiple pay plans operating
simultaneously might be different from plans’
independent effects. We specifically predicted
and supported that considering partialed effects
is important for incentive effects, while not so
for sorting effects.

Our study thus provides a theoretically consis-
tent explanation for the mixed results previously
observed for merit pay. The effectiveness of merit
pay has been repeatedly questioned (Gerhart et
al., 2009; Gerhart & Rynes, 2003; Heneman &
Werner, 2005). A key concern is that differences in
awards between the best and the worst performers
are often not large (Gomez-Mejia & Balkin, 1989);
others have shown examples where there is actu-
ally no relationship between pay and performance
in a nominal merit pay plan (e.g., Kahn & Sherer,
1990). These concerns, though, are not completely
generalizable to all implementations of merit pay.
Rather, when viewed through the lens of expec-
tancy theory, they suggest that the merit plans
are often poorly implemented because they fail to
generate a PFP link. Our findings provide a better
understanding of the mechanisms that PFP plans
should have so as to yield the desired results. Our
results show that it is an overgeneralization to sug-
gest there is a single positive effect for any type of
PFP plan. Instead, PFP plan effectiveness depends
on how strongly pay and performance are linked.

Furthermore, the practical effects of any
pay plan will also depend on the budget for the
awards, for without resources it is difficult to cre-
ate a plan with a strong PFP link. Thus, while our
results showed that merit pay has the strongest
effects on performance and turnover in multi-PFP
environments, if an organization fails to create a
link between raises and performance, even if they
call it a merit plan, we would not expect merit pay
to be an effective tool.

Our study is also one of the few studies to
examine the effect of LTIs on individual employ-
ees. When considered independently, PFP for LTIs
was related to increased performance; however,

expect from PFP plans when employees are per-
forming in a multiple PFP plan environment.
Considering how different PFP plans operate in
the same environment requires us to consider the
relative relationships we should expect from PFP
plans, thus requiring us to add to our theoretical
precision (Edwards & Berry, 2010). It also requires
us to consider how the relevant theory is appli-
cable to partialed effects—the sorts of effects we
expect for one PFP plan when controlling for the
effects of other PFP plans. Our findings show that
prior PFP research, which has generally focused on
a single plan at a time, generalizes to more com-
plex environments. Furthermore, the predictions
of the relative effectiveness of PFP plans from
theory generally hold, and, hence, the expansion
of theory to multiplan environments does have
some external validity.

This study provides three general forms of
theoretical contributions. The first is
the replication and confirmation of
the generalizability of prior research.
Our results show that prior PFP
research—be it on a single-PFP plan
or in multi-PFP plan environments
but with the other plans not consid-
ered—replicates and generalizes to
multi-PFP plan environments. The
general findings of incentive and
sorting effects do hold when consid-
ering PFP plans independently, even
when other PFP plans are operat-
ing but are not controlled for in the
analyses.

Second, our results provide a
test of the theoretical precision of
theories that have been related to
PFP plans. Because of the differ-

ent sorts of rewards associated with different PFP
plans, expectancy theory in particular would pre-
dict different effects. Expectancy theory remains
one of the dominant decision-making theories
(Vancouver, Weinhardt, & Schmidt, 2010), and
continues to play an important role in its own
right (Cadsby et al., 2007; Gerhart et al., 2009;
Kepes, Delery, & Gupta, 2009) in addition to being
incorporated into more sophisticated current
theories of motivation (e.g., Schmidt & DeShon,
2007; Steel & König, 2006; Vancouver et al., 2010).
While the internal validity of expectancy theory
has generally been supported (i.e. general posi-
tive effects found for expectancy, valence, or the
interaction; see Van Eerde & Thierry, 1996), there
is far less research testing the external validity of
the theory (its ability to make accurate predictions
in new contexts) or if its tenets hold for predicting
the relative effects of expectancy or valence. We

Human Resource Management DOI: 10.1002/hrm

EVALUATING FORM AND FUNCTIONALITY OF PAY-FOR-PERFORMANCE PLANS 715

Future theoretical

development relevant

to PFP plans requires

attention to both

content (i.e., the

characteristics of

the plan) and context

(i.e., examining a plan

in light of other PFP

plans that may be in

place).

motivation; rather, the predictions were based
on approximations of the relationships between
pay and performance and from the characteris-
tics of the plans and supervisory decisions. While
this is not the first study to estimate PFP relation-
ships mathematically (e.g., Kahn & Sherer, 1990;
Salamin & Hom, 2005; Trevor et al., 1997), it is not
a direct test of the internal validity of the related
theories. It would certainly be valuable to see how
individuals perceive the sort of PFP linkages in
which they are operating. While our use of theory
and supported hypotheses provide evidence of the
external validity of relevant theory, and particu-
larly expectancy theory, our article does not con-
tribute to testing of the theories’ internal validity.

Our single context also limits the generaliz-
ability of our findings. Other forms of PFP and
other simultaneous combinations of PFP plans
should be examined to provide
greater precision in our understand-
ing of the effectiveness of compen-
sation plans. There are many other
types of PFP plans, and even more
potential PFP portfolios. Because
organizations are more likely to use
“hybrid plans” than independent
pay plans (Gerhart, 2000; Gerhart &
Fang, 2014; Gomez-Mejia & Balkin,
1992; Gomez-Mejia, Berrone, &
Franco-Santos, 2010; Milkovich et
al., 2013), understanding how the
characteristics of multiple PFP plans
simultaneously affect performance
and voluntary turnover is crucial
for organizations to design effective
compensation systems.

There are also limitations to the
nature of our data. Unaddressed in
this article, there may exist inter-
actions between PFP relationships. It is also pos-
sible that pay systems have effects beyond one
year. In our analyses, we examine the effect of
pay outcomes on performance or turnover in the
subsequent year. It is possible, for example, that
long-term incentives, may have effects that occur
in subsequent years, or the strength of effects
may change over time. It is beyond the scope of
our study, in addition to the capabilities of our
data, to consider the potential multiyear effects
of hybrid pay systems, and thus our results may
not be fully capturing the set of effects associated
with these plans.

In short, our article represents a single case
of a multi-PFP environment, and more research
on more and different plans is needed. While
performing such research will obviously require
significant industry-academic cooperation to

in this context, the link between pay and perfor-
mance after partialing out the links with the other
pay plans was not significant. This limited the
potential incentive effect of LTI when considered
in conjunction with the other PFP plans, although
it still had a sorting effect. Further research on LTIs
would be useful, as our results show that, in gen-
eral, the effectiveness of a compensation plan is a
function of its characteristics. We only examined
a single LTI plan in this article; other plans may
vary in terms of their vesting requirements and
the specific reward granted, and thus can be more
complex (Moynihan, 2013).

Motivational theories have strongly sup-
ported the underlying mechanisms of PFP plans
regarding the extent to which financial rewards
can motivate employees to higher performance
and the desirable behaviors that organizations
expect. Situations have become, for both organi-
zations and employees, more multifaceted due to
organizations providing more complex compen-
sation system environments and employees being
covered by multiple PFP plans. Future compensa-
tion research needs to consider more carefully the
effectiveness of PFPs. Indeed, each PFP has a dif-
ferent form and set of characteristics, and all of
the different combinations of multiple PFPs that
organizations provide will have relative effects on
various important outcomes. This creates more
complex decision making and motivational pro-
cesses that need greater research attention.

Overall, a key theoretical contribution from
this paper is our demonstration of the potential
and utility associated with developing greater
theoretical precision (Edwards & Berry, 2010).
Simply calling a plan PFP is insufficient; and
while general directional effects are valid, theory
can be extended to predict the relative effective-
ness of PFP plans. Future theoretical development
relevant to PFP plans requires attention to both
content (i.e., the characteristics of the plan) and
context (i.e., examining a plan in light of other
PFP plans that may be in place).

Limitations

This article has a number of advantages over pre-
vious PFP studies. We used longitudinal data con-
trolling for prior performance to examine both
the incentive and sorting effects of PFP plans. The
study also considered the different effects of the
characteristics of multiple PFP plans simultane-
ously. Like all research, though, this study is not
without limitations, and it is important to point
out the key issues that threaten the potential gen-
eralizability of our findings.

From a theoretical perspective, this study
did not directly assess individual perceptions of

716 HUMAN RESOURCE MANAGEMENT, JULY–AUGUST 2016

Human Resource Management DOI: 10.1002/hrm

Companies may

want to avoid raises

because of the

increase to fixed

labor costs, but our

findings show that

minimizing merit

pay means giving

up a powerful PFP

tool. Raises had

larger effects than

bonuses and LTI, and

only raises had both

incentive and sorting

effects.

and rewards, and adjust policy as necessary to
ensure stronger links. Most companies using PFP
have individual performance data (WorldatWork,
2012). A related contribution of our study is our
demonstration on how companies can use HR
data to see how strongly their plans link pay and
performance, and thus change policy based on
using their HR data.

Third, our results raise interesting questions
about the use of bonuses. While bonuses consid-
ered independently did have positive incentive
and sorting effects, after controlling for the effects
of other PFP plans, there was actually a positive
effect on turnover. This is consistent with the
finding by Sturman and Short (2000), who found
a positive effect of bonus satisfaction on turnover
intentions after controlling for satisfaction with
other pay dimensions. Organizations may ben-
efit by using their available data to make similar
tests in their own organizations to see if their pay
plans, and bonuses in particular, are having unin-
tended consequences (Pfeffer, 1998).

Finally, this study emphasizes the importance
of the relative effectiveness of different types of
PFP plans in multi-PFP plan environment. It is
very common today for organizations to provide
their employees with more than one type of PFP.
As many organizations are focusing more on PFP
plans, implementing a single or multiple PFP
plan(s) is not a differentiator among organiza-
tions. With the results of our study, organizations
must identify the complexity of pay environ-
ments and distinguish between forms and charac-
teristics of different PFP plans and across PFP plan
types to better understand how these factors influ-
ence employees’ motivation and decision-making
processes.

provide the sort of data needed to conduct such
tests, there is great practical and theoretical value
that could be provided by such work.

Implications for Practice

Given the prevalence of mul-
tiple PFP plan environments, our
research into the effects of multi-
ple PFP plans operating simultane-
ously has important implications
for practice. First, we show that
employees do, on average, respond
rationally to incentives. Companies
may want to avoid raises because
of the increase to fixed labor costs,
but our findings show that mini-
mizing merit pay means giving
up a powerful PFP tool. Raises had
larger effects than bonuses and LTI,
and only raises had both incentive
and sorting effects. Our findings do
show that companies can use other
pay forms to get the same effects as
raises, but it would require stronger
PFP links and larger rewards. The
trade-off between higher one-time
costs versus greater fixed labor costs
thus becomes a cost-benefit decision
(cf. Sturman, Trevor, Boudreau, &
Gerhart, 2003).

Second, our study shows that
companies can apply PFP-related
theory to the design of PFP plans,

and thus take advantage of evidence-based
management (e.g., Rousseau, 2006; Rousseau &
McCarthy, 2007). Companies can specifically
look at the degree to which managers link pay

SANGHEE PARK is an assistant professor of human resource management in Rutgers
University’s School of Management and Labor Relations. She received her PhD in human

resources from the Hotel School at Cornell University. Her primary research interests are on

the infl uence of compensation systems, particularly looking at the intersection of pay and

motivation, and the dynamics of the multiple dyadic relationships within multiple hierarchies

in organization. Her research has been published in the Journal of Applied Psychology.

MICHAEL C. STURMAN (PhD, Cornell University) is the Kenneth and Marjorie Blanchard
Professor of Human Resources, and the associate dean for faculty development at Cornell

University’s School of Hotel Administration. There, he teaches courses on human resource

management and compensation. His research focuses on the prediction of individual job

performance over time and the infl uence of compensation systems. His work is published

in journals such as the Journal of Applied Psychology, Academy of Management Journal,

Personnel Psychology, and Journal of Management. Michael is also a Senior Professional of

Human Resources as certifi ed by the Society for Human Resource Management.

Human Resource Management DOI: 10.1002/hrm

EVALUATING FORM AND FUNCTIONALITY OF PAY-FOR-PERFORMANCE PLANS 717

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