Building a Practically Useful Theory of Goal Setting
and Task Motivation
A 35-Year Odyssey
Edwin A. Locke University of Maryland
Gary P. Latham University of Toronto
The authors summarize 35 years of empirical research on
goal-setting theory. They describe the core ﬁndings of the
theory, the mechanisms by which goals operate, modera-
tors of goal effects, the relation of goals and satisfaction,
and the role of goals as mediators of incentives. The
external validity and practical signiﬁcance of goal-setting
theory are explained, and new directions in goal-setting
research are discussed. The relationships of goal setting to
other theories are described as are the theory’s limitations.
n the 1950s and 1960s, the study of motivation in
North American psychology was not considered a re-
spectable pursuit. The ﬁeld was dominated by behav-
iorists, and “motivation” was argued by them to lie outside
the person in the form of reinforcers and punishers. When
internal mechanisms were acknowledged, as in drive re-
duction theory, it was said that they were primarily
McClelland, a nonbehaviorist, argued for the exis-
tence of internal motives, such as need for achievement, but
these were asserted to be subconscious (McClelland, At-
kinson, Clark, & Lowell, 1953) and hence measurable only
by projective tests. Behaviorists, drive reductionists, and
advocates of subconscious motives all agreed that intro-
spection was not a valid method of understanding human
motivation. This ruled out the possibility of studying the
conscious regulation of action.
An exception to the anticonsciousness zeitgeist was
the work of Ryan. Anticipating the cognitive revolution in
psychology, Ryan (1970) argued that “it seems a simple
fact that human behavior is affected by conscious purposes,
plans, intentions, tasks and the like” (p. 18). For Ryan,
these, which he called ﬁrst-level explanatory concepts,
were the immediate motivational causes of most human
Lewin and his colleagues (e.g., Lewin, Dembo, Fest-
inger, & Sears, 1944) studied conscious goals, or levels of
aspiration, years prior to Ryan’s work. However, they
treated levels of aspiration as a dependent rather than an
independent variable. Mace (1935), a British investigator
who was perhaps less inﬂuenced than others by American
behaviorism, was the ﬁrst to examine the effects of differ-
ent types of goals on task performance. His work was
largely ignored, however, except for a citation in Ryan’s
classic text with Smith on industrial psychology (Ryan &
Goal-setting theory was formulated inductively
largely on the basis of our empirical research conducted
over nearly four decades. It is based on Ryan’s (1970)
premise that conscious goals affect action. A goal is the
object or aim of an action, for example, to attain a speciﬁc
standard of proﬁciency, usually within a speciﬁed time
limit. As industrial–organizational psychologists, our pri-
mary interest has been to predict, explain, and inﬂuence
performance on organizational or work-related tasks. Thus,
we focused on the relationship between conscious perfor-
mance goals and level of task performance rather than on
discrete intentions to take speciﬁc actions (e.g., to apply to
graduate school, to get a medical examination). The latter
type of intention has been studied extensively by social
psychologists, such as Fishbein and Ajzen (1975).
The ﬁrst issue we addressed was the relationship of goal
difﬁculty to performance. Atkinson (1958), a student of
McClelland, had shown that task difﬁculty, measured as
probability of task success, was related to performance in a
curvilinear, inverse function. The highest level of effort
occurred when the task was moderately difﬁcult, and the
lowest levels occurred when the task was either very easy
or very hard. Atkinson did not measure personal perfor-
mance goals or goal difﬁculty. Moreover, his task-difﬁculty
ﬁndings have not been replicated when task performance
Editor’s note. Denise C. Park served as action editor for this article.
Author’s note. Edwin A. Locke, R. H. Smith School of Business, Uni-
versity of Maryland; Gary P. Latham, Joseph L. Rotman School of
Business, University of Toronto, Toronto, Ontario, Canada.
This article is based in part on Edwin A. Locke’s G. Stanley Hall
lectures at the annual meetings of the American Psychological Associa-
tion in 1999 and of the Southeastern Psychological Association in 2000.
It is also based on Gary P. Latham’s presidential address to the Canadian
Psychological Association in 2001 and on his invited address to the
American Psychological Society in 2001.
Correspondence concerning this article should be addressed to Edwin
A. Locke, 32122 Canyon Ridge Drive, Westlake Village, CA 91361.
Copyright 2002 by the American Psychological Association, Inc. 0003-066X/02/$5.00
Vol. 57, No. 9, 705–717 DOI: 10.1037//0003-066X.57.9.705
goals were measured.
We found a positive, linear function
in that the highest or most difﬁcult goals produced the
highest levels of effort and performance. Goal difﬁculty
effect sizes (d) in meta-analyses ranged from .52 to .82
(Locke & Latham, 1990). Performance leveled off or de-
creased only when the limits of ability were reached or
when commitment to a highly difﬁcult goal lapsed (Erez &
We also compared the effect of speciﬁc, difﬁcult goals
to a commonly used exhortation in organizational settings,
namely, to do one’s best. We found that speciﬁc, difﬁcult
goals consistently led to higher performance than urging
people to do their best. The effect sizes in meta-analyses
ranged from .42 to .80 (Locke & Latham, 1990). In short,
when people are asked to do their best, they do not do so.
This is because do-your-best goals have no external refer-
ent and thus are deﬁned idiosyncratically. This allows for a
wide range of acceptable performance levels, which is not
the case when a goal level is speciﬁed. Goal speciﬁcity in
itself does not necessarily lead to high performance be-
cause speciﬁc goals vary in difﬁculty. However, insofar as
performance is fully controllable, goal speciﬁcity does re-
duce variation in performance by reducing the ambiguity
about what is to be attained (Locke, Chah, Harrison, &
Lustgarten, 1989). Goal studies have also compared the
effects of learning versus performance goals and proximal
versus distal goals. These results are discussed below in
relation to the moderating effects of task complexity.
Expectancy and Social–Cognitive
Goal-setting theory appears to contradict Vroom’s (1964)
valence–instrumentality–expectancy theory, which states
that the force to act is a multiplicative combination of
valence (anticipated satisfaction), instrumentality (the be-
lief that performance will lead to rewards), and expectancy
(the belief that effort will lead to the performance needed to
attain the rewards). Other factors being equal, expectancy
is said to be linearly and positively related to performance.
However, because difﬁcult goals are harder to attain than
easy goals, expectancy of goal success would presumably
be negatively related to performance.
The apparent contradiction between the two theories is
resolved by distinguishing expectancy within versus ex-
pectancy between goal conditions. Locke, Motowidlo, and
Bobko (1986) found that when goal level is held constant,
which is implicitly assumed by valence–instrumentality–
expectancy theory, higher expectancies lead to higher lev-
els of performance. Across goal levels, lower expectancies,
associated with higher goal levels, are associated with
This within–between distinction is not an issue in
social–cognitive theory (Bandura, 1986, 1997). Self-
efﬁcacy (task-speciﬁc conﬁdence) is measured by getting
efﬁcacy ratings across a whole range of possible perfor-
mance outcomes rather than from a single outcome (Locke
et al., 1986). The concept of self-efﬁcacy is important in
goal-setting theory in several ways. When goals are self-
set, people with high self-efﬁcacy set higher goals than do
people with lower self-efﬁcacy. They also are more com-
mitted to assigned goals, ﬁnd and use better task strategies
to attain the goals, and respond more positively to negative
feedback than do people with low self-efﬁcacy (Locke &
Latham, 1990; Seijts & B. W. Latham, 2001). These issues
are addressed further below.
Goals affect performance through four mechanisms. First,
goals serve a directive function; they direct attention and
effort toward goal-relevant activities and away from goal-
irrelevant activities. This effect occurs both cognitively and
behaviorally. For example, Rothkopf and Billington (1979)
found that students with speciﬁc learning goals paid atten-
tion to and learned goal-relevant prose passages better than
goal-irrelevant passages. Locke and Bryan (1969) observed
that people who were given feedback about multiple as-
pects of their performance on an automobile-driving task
improved their performance on the dimensions for which
they had goals but not on other dimensions.
Second, goals have an energizing function. High goals
lead to greater effort than low goals. This has been shown
with tasks that (a) directly entail physical effort, such as the
ergometer (Bandura & Cervone, 1983); (b) entail repeated
performance of simple cognitive tasks, such as addition; (c)
include measurements of subjective effort (Bryan & Locke,
Task and goal difﬁculty are not synonymous and can be measured
separately. An example of a difﬁcult task would be solving a complex
anagram or a student pilot landing a plane. The term performance goal, as
we use it, refers to the score one attains on the task (e.g., how many
anagrams solved in three minutes or the proﬁciency level one attains in
practice landings). A learning goal refers to the number of ideas or
strategies one acquires or develops to accomplish the task effectively.
706 September 2002
1967a); and (d) include physiological indicators of effort
Third, goals affect persistence. When participants are
allowed to control the time they spend on a task, hard goals
prolong effort (LaPorte & Nath, 1976). There is often,
however, a trade-off in work between time and intensity of
effort. Faced with a difﬁcult goal, it is possible to work
faster and more intensely for a short period or to work more
slowly and less intensely for a long period. Tight deadlines
lead to a more rapid work pace than loose deadlines in the
laboratory (Bryan & Locke, 1967b) as well as in the ﬁeld
(Latham & Locke, 1975).
Fourth, goals affect action indirectly by leading to the
arousal, discovery, and/or use of task-relevant knowledge
and strategies (Wood & Locke, 1990). It is a virtual axiom
that all action is the result of cognition and motivation, but
these elements can interact in complex ways. Below is a
summary of what has been found in goal-setting research:
1. When confronted with task goals, people automat-
ically use the knowledge and skills they have already
acquired that are relevant to goal attainment. For example,
if the goal involves cutting logs, loggers use their knowl-
edge of logging without the need for additional conscious
planning in their choice to exert effort and persist until the
goal is attained (Latham & Kinne, 1974).
2. If the path to the goal is not a matter of using
automatized skills, people draw from a repertoire of skills
that they have used previously in related contexts, and they
apply them to the present situation. For example, Latham
and Baldes (1975) found that truck drivers who were as-
signed the goal of increasing the weight of their truck loads
made modiﬁcations to their trucks so that they could better
estimate truck weight before driving to the weighing
3. If the task for which a goal is assigned is new to
people, they will engage in deliberate planning to develop
strategies that will enable them to attain their goals (Smith,
Locke, & Barry, 1990).
4. People with high self-efﬁcacy are more likely than
those with low self-efﬁcacy to develop effective task strat-
egies (Latham, Winters, & Locke, 1994; Wood & Bandura,
1989). There may be a time lag between assignment of the
goal and the effects of the goal on performance, as people
search for appropriate strategies (Smith et al., 1990).
5. When people are confronted with a task that is
complex for them, urging them to do their best sometimes
leads to better strategies (Earley, Connolly, & Ekegren,
1989) than setting a speciﬁc difﬁcult performance goal.
This is because a performance goal can make people so
anxious to succeed that they scramble to discover strategies
in an unsystematic way and fail to learn what is effective.
This can create evaluative pressure and performance anx-
iety. The antidote is to set speciﬁc challenging learning
goals, such as to discover a certain number of different
strategies to master the task (Seijts & G. P. Latham, 2001;
Winters & Latham, 1996).
6. When people are trained in the proper strategies,
those given speciﬁc high-performance goals are more
likely to use those strategies than people given other types
of goals; hence, their performance improves (Earley &
Perry, 1987). However, if the strategy used by the person is
inappropriate, then a difﬁcult performance-outcome goal
leads to worse performance than an easy goal (Audia,
Locke, & Smith, 2000; Earley & Perry, 1987). For a
detailed discussion of the relation of task goals and knowl-
edge, see Locke (2000).
The goal–performance relationship is strongest when peo-
ple are committed to their goals. Seijts and Latham (2000a)
found goal commitment questionnaires to have high reli-
ability and validity. Commitment is most important and
relevant when goals are difﬁcult (Klein, Wesson, Hollen-
beck, & Alge, 1999). This is because goals that are difﬁcult
for people require high effort and are associated with lower
chances of success than easy goals (Erez & Zidon, 1984).
Two key categories of factors facilitating goal com-
mitment are (a) factors that make goal attainment important
to people, including the importance of the outcomes that
they expect as a result of working to attain a goal, and (b)
their belief that they can attain the goal (self-efﬁcacy).
Importance. There are many ways to convince
people that goal attainment is important. Making a public
commitment to the goal enhances commitment, presum-
ably because it makes one’s actions a matter of integrity in
one’s own eyes and in those of others (Hollenbeck, Wil-
liams, & Klein, 1989). Goal commitment can also be
enhanced by leaders communicating an inspiring vision
and behaving supportively. In ﬁeld settings (e.g., Ronan,
Latham, & Kinne, 1973) and laboratory settings (e.g.,
Latham & Saari, 1979b), the supervisor’s legitimate au-
thority to assign goals creates demand characteristics.
An alternative to assigning goals is to allow subordi-
nates to participate in setting them. The theory is that this
would make goals more important to the person because
one would, at least in part, own the goals. A series of
studies by Latham and his colleagues revealed that, when
goal difﬁculty is held constant, performances of those with
participatively set versus assigned goals do not differ sig-
niﬁcantly (e.g., Dossett, Latham, & Mitchell, 1979; Latham
& Marshall, 1982; Latham & Saari, 1979a, 1979b; Latham
& Steele, 1983). Erez and her colleagues (Erez, 1986; Erez,
Earley, & Hulin, 1985; Erez & Kanfer, 1983), however,
reached the opposite conclusion.
Working collaboratively, with Locke as mediator,
Latham and Erez explored reasons for their contradictory
ﬁndings. They found that from a motivational perspective,
an assigned goal is as effective as one that is set participa-
tively provided that the purpose or rationale for the goal is
given. However, if the goal is assigned tersely (e.g., “Do
this...”) without explanation, it leads to performance that
is signiﬁcantly lower than for a participatively set goal
(Latham, Erez, & Locke, 1988). Meta-analyses of the ef-
fects of participation in decision making on performance,
for those studies that measured performance objectively,
yielded an effect size of only .11 (Wagner & Gooding,
Subsequently, Locke, Alavi, and Wagner (1997)
found that the primary beneﬁt of participation in decision
making is cognitive rather than motivational in that it
stimulates information exchange. For example, Latham et
al. (1994) found that with goal difﬁculty level controlled,
participation in goal setting had no beneﬁcial effect on
performance. However, people who participated with oth-
ers in formulating task strategies performed signiﬁcantly
better and had higher self-efﬁcacy than those who did not
participate in formulating strategies.
Monetary incentives are one practical outcome that
can be used to enhance goal commitment. However, there
are important contingency factors. The ﬁrst is the amount
of the incentive; more money gains more commitment.
Second, goals and incentive type interact. When the goal is
very difﬁcult, paying people only if they reach the goal
(i.e., a task-and-bonus system) can hurt performance. Once
people see that they are not getting the reward, their per-
sonal goal and their self-efﬁcacy drop and, consequently,
so does their performance. This drop does not occur if the
goal is moderately difﬁcult or if people are given a difﬁcult
goal and are paid for performance (e.g., piece rate) rather
than goal attainment (Latham & Kinne, 1974; Latham &
Yukl, 1975; T. Lee, Locke, & Phan, 1997).
Latham (2001) developed an empathy box to help
managers identify nonﬁnancial outcomes that employees
expected as a result of committing to or rejecting a speciﬁc
difﬁcult goal. In a study where the goal was to reduce theft,
when self-efﬁcacy regarding honest behavior was high,
actions taken to change outcome expectancies led to a
signiﬁcant decrease in stolen material (Latham, 2001).
Self-efficacy. As noted, self-efﬁcacy enhances
goal commitment. Leaders can raise the self-efﬁcacy of
their subordinates (a) by ensuring adequate training to
increase mastery that provides success experiences, (b) by
role modeling or ﬁnding models with whom the person can
identify, and (c) through persuasive communication that
expresses conﬁdence that the person can attain the goal
(Bandura, 1997; White & Locke, 2000). The latter may
involve giving subordinates information about strategies
that facilitate goal attainment. Transformational leaders
raise the efﬁcacy of employees through inspiring messages
to and cognitive stimulation of subordinates (Bass, 1985).
For goals to be effective, people need summary feedback
that reveals progress in relation to their goals. If they do not
know how they are doing, it is difﬁcult or impossible for
them to adjust the level or direction of their effort or to
adjust their performance strategies to match what the goal
requires. If the goal is to cut down 30 trees in a day, people
have no way to tell if they are on target unless they know
how many trees have been cut. When people ﬁnd they are
below target, they normally increase their effort (Matsui,
Okada, & Inoshita, 1983) or try a new strategy. Summary
feedback is a moderator of goal effects in that the combi-
nation of goals plus feedback is more effective than goals
alone (Bandura & Cervone, 1983; Becker, 1978; Erez,
1977; Strang, Lawrence, & Fowler, 1978).
Control theory (Carver & Scheier, 1981) also empha-
sizes the importance of goal setting and feedback for mo-
tivation. The assumptions that underlie control theory,
however, are questionable (Locke, 1991a, 1994; Locke &
Latham, 1990). In essence, the theory is based on a ma-
chine model derived from cybernetic engineering (Powers,
1978). The source of motivation is asserted to be a negative
feedback loop (such as that characterizing a thermostat)
that eliminates goal–performance discrepancies. The natu-
ral state of the organism is, by implication, one of motion-
lessness or rest.
Control theory is in effect a mechanistic version of
Hull’s drive reduction theory, which was abandoned de-
cades ago. However, machines do not possess internal
motivational states and do not have goals of their own.
Their “goals” are those of the machine’s builders. Further-
more, discrepancy reduction is a consequence rather than a
cause of goal-directed behavior. As Bandura (1989) stated,
goal setting is ﬁrst and foremost a discrepancy-creating
process. Motivation requires feed-forward control in addi-
tion to feedback. After people attain the goal they have
been pursuing, they generally set a higher goal for them-
selves. This adoption of higher goals creates rather than
reduces motivation discrepancies to be mastered. “Self
motivation thus involves a dual cyclic process of disequili-
bratory discrepancy production followed by equilibratory
reduction” (Bandura, 1989, p. 38).
A third moderator of goal effects is task complexity. As the
complexity of the task increases and higher level skills and
708 September 2002
strategies have yet to become automatized, goal effects are
dependent on the ability to discover appropriate task strat-
egies. Because people vary greatly in their ability to do this,
the effect size for goal setting is smaller on complex than
on simple tasks. Meta-analyses (Wood, Mento, & Locke,
1987) have revealed goal difﬁculty effect sizes (d)of.48
for the most complex tasks versus .67 for the least complex
tasks. For speciﬁc difﬁcult goals versus a goal to do one’s
best, the effect size was .41 for the most complex tasks
versus .77 for the least complex tasks.
Because people use a greater variety of strategies on
tasks that are complex than on tasks that are easy, measures
of task strategy often correlate more highly with perfor-
mance than do measures of goal difﬁculty (Chesney &
Locke, 1991). In addition, there are often goal–strategy
interactions, with goal effects strongest when effective
strategies are used (Durham, Knight, & Locke, 1997).
R. Kanfer and Ackerman (1989) found that in an air
trafﬁc controller simulation (a highly complex task), hav-
ing a performance-outcome goal actually interfered with
acquiring the knowledge necessary to perform the task.
People performed better when they were asked to do their
best. However, Winters and Latham (1996) showed that the
fault was with the type of goal that had been set rather than
with the theory. They found that when a speciﬁc difﬁcult
learning goal rather than a performance goal was set,
consistent with goal-setting theory, high goals led to sig-
niﬁcantly higher performance on a complex task than did
the general goal of urging people do their best.
Another factor that may facilitate performance on
new, complex tasks is the use of proximal goals. Latham
and Seijts (1999), using a business game, found that do-
your-best goals were more effective than distal goals, but
when proximal outcome goals were set in addition to the
distal outcome goal, self-efﬁcacy and proﬁts were signiﬁ-
cantly higher than in the do-your-best condition or in the
condition where only a distal outcome goal had been set. In
dynamic situations, it is important to actively search for
feedback and react quickly to it to attain the goal (Frese &
Zapf, 1994). As Dorner (1991) noted, performance errors
on a dynamic task are often due to deﬁcient decomposition
of a distal goal into proximal goals. Proximal goals can
increase what Frese and Zapf (1994) called error manage-
ment. Proximal feedback regarding errors can yield infor-
mation for people about whether their picture of reality is
aligned with what is required to attain their goal.
Personal Goals as Mediators of
What Locke (1991b) called the motivation hub, meaning
where the action is, consists of personal goals, including
goal commitment, and self-efﬁcacy. These variables are
often, though not invariably, the most immediate, con-
scious motivational determinants of action. As such, they
can mediate the effects of external incentives.
For example, assigned goal effects are mediated by
personal or self-set goals that people choose in response to
the assignment, as well as by self-efﬁcacy. The relation-
ships among assigned goal difﬁculty, self-set goal difﬁ-
culty, self-efﬁcacy, and performance are shown in Figure 1.
Observe that assigning a challenging goal alone raises
self-efﬁcacy because this is an implicit expression of con-
ﬁdence by a leader that the employee can attain the goal.
The correlation between self-set goals and self-efﬁcacy is
higher when no goals are assigned.
The mediating effect of self-set goals and self-efﬁcacy
on monetary incentive effects was noted earlier (T. Lee et
al., 1997). However, not all incentive studies have found a
mediating effect. Wood, Atkins, and Bright (1999) showed
that incentive effects were mediated by instrumentality or
outcome expectancies rather than by goals and efﬁcacy.
Also, when summary feedback is provided without any
goals, the feedback effects are mediated by the goals that
are set in response to the feedback (Locke & Bryan, 1968).
Bandura and Cervone (1986) found that both goals and
self-efﬁcacy mediated feedback effects. Self-efﬁcacy is
especially critical when negative summary feedback is
given because the person’s level of self-efﬁcacy following
such feedback determines whether subsequent goals are
raised or lowered.
As noted earlier, the beneﬁts of participation in deci-
sion making are primarily cognitive rather than motiva-
tional. However, Latham and Yukl (1976) and Latham,
Mitchell, and Dossett (1978) found that employees who
were allowed to participate in setting goals set higher goals
and had higher performance than those who were assigned
goals by the supervisor. The higher the goals, the higher the
performance. Finally, Kirkpatrick and Locke (1996) found
that goals and self-efﬁcacy mediated the effect of visionary
leadership on employee performance.
Goals are, at the same time, an object or outcome to aim for
and a standard for judging satisfaction. To say that one is
trying to attain a goal of X means that one will not be
satisﬁed unless one attains X. Thus, goals serve as the
inﬂection point or reference standard for satisfaction versus
dissatisfaction (Mento, Locke, & Klein, 1992). For any
given trial, exceeding the goal provides increasing satisfac-
tion as the positive discrepancy grows, and not reaching the
goal creates increasing dissatisfaction as the negative dis-
Relationships Among Assigned Goals, Self-Set Goals,
Self-Efficacy, and Performance
Note. Adapted from A Theory of Goal Setting and Task Performance (p. 72),
by E. A. Locke and G. P. Latham, 1990, Englewood Cliffs, NJ: Prentice Hall.
Copyright 1990 by Prentice Hall. Reprinted with permission.
crepancy grows. Across trials, the more goal successes one
has, the higher one’s total satisfaction.
There is a paradox here, however. How can people who
produce the most, those with difﬁcult goals, be the least
satisﬁed? The answer is implicit in the question. People with
high goals produce more because they are dissatisﬁed with
less. The bar for their satisfaction is set at a high level. This is
why they are motivated to do more than those with easy goals.
But why would people be motivated to set high goals?
People can expect many psychological and practical out-
comes from setting and attaining those goals. For example,
undergraduate business students reported four beneﬁcial
outcomes that they expected as a result of having a grade
point average of A versus B versus C (Mento et al., 1992).
These outcomes were pride in performance; academic out-
comes, such as admission into graduate school or receiving
a scholarship; future beneﬁts, such as an excellent job offer
or a high starting salary; and life beneﬁts, such as career
success. At the same time, expected satisfaction with per-
formance showed the opposite pattern. The highest degree
of anticipated satisfaction, averaged across all grade out-
comes, was for students with a goal of C, and the lowest
was for students with a goal of earning an A. The relation-
ships found by Mento et al. (1992) are shown in Figure 2.
Setting speciﬁc challenging goals is also a means of en-
hancing task interest (Locke & Bryan, 1967) and of helping
people to discover the pleasurable aspects of an activity
(Harackiewicz, Manderlink, & Sansone, 1984).
Achievement Valence and Instrumentality Functions for Grade Goals or Outcomes
Note. From “Relationship of Goal Level to Valence and Instrumentality,” by A. Mento, E. Locke, and H. Klein, 1992, Journal of Applied Psychology, 77, p. 401.
Copyright 1992 by the American Psychological Association.
710 September 2002
Productivity and Cost Improvement
Numerous studies have shown that setting a speciﬁc difﬁ-
cult goal leads to signiﬁcant increases in employee produc-
tivity (Locke & Latham, 1984). For example, loggers cut
more trees (Latham & Kinne, 1974; Latham & Yukl,
1975), and unionized truck drivers increased the logs
loaded on their trucks from 60% to 90% of the legal
allowable weight (see Figure 3) as a result of assigned
goals. The drivers saved the company $250,000 in 9
months (Latham & Baldes, 1975). A subsequent study
saved $2.7 million dollars in 18 weeks by assigning union-
ized drivers the goal of increasing their number of daily
trips to the mill (Latham & Saari, 1982). Word-processing
operators with speciﬁc high goals increased their perfor-
mance regardless of whether the goal was assigned or set
participatively (Latham & Yukl, 1976). In a survey of
companies from Dun’s Business Rankings, Terpstra and
Rozell (1994) found a signiﬁcant correlation between goal
setting and organizational proﬁtability.
Engineers and scientists who set goals for their scores on a
behavioral index of their performance had higher subse-
quent performance than those who were urged to do their
best (Latham et al., 1978). Unionized telecommunications
employees had high performance and high satisfaction with
the performance appraisal process when speciﬁc high goals
were set. Moreover, self-efﬁcacy correlated positively with
subsequent performance (Brown & Latham, 2000a). As
was the case with the engineers and scientists, the higher
the goal, the higher and more positive the performance
Latham, Saari, Pursell, and Campion (1980) developed the
situational interview to assess an applicant prior to employ-
ment. In brief, applicants are presented with situations,
based on a job analysis. Each question contains a dilemma
that assesses an applicant’s goals or intentions for what he
or she would do when confronted by these situations.
Meta-analyses have shown that the situational interview
Effect of Goal Setting on Percentage of Legal Net Weight Achieved by Logging Truck Drivers
Note. From “The ‘Practical Significance’ of Locke’s Theory of Goal Setting,” by G. P. Latham and J. Baldes, 1975, Journal of Applied Psychology, 60, p. 123.
Copyright 1975 by the American Psychological Association.
has high criterion-related validity (e.g., Huffcutt & Arthur,
1994; Latham & Sue-Chan, 1999). McDaniel, Whetzel,
Schmidt, and Maurer (1994) concluded that the mean cri-
terion-related validity of the situational interview is higher
than that of all other selection interviews.
Self-Regulation at Work
A key variable in self-regulation is goal setting. Job atten-
dance is a prerequisite of job performance. Consequently,
Frayne and Latham (1987) adapted F. H. Kanfer’s (1970,
1996) methodology for the development of a training pro-
gram to teach unionized state government employees ways
to overcome obstacles they perceived to coming to work.
The training in self-regulation taught those employees to
set speciﬁc high goals for attendance, to monitor ways in
which their environment facilitated or hindered attainment
of their goal, and to identify and administer rewards for
making goal progress, as well as punishments for failing to
make progress toward goal attainment.
Not only did this training in self-management enable
these employees to cope effectively with personal and
social obstacles to their job attendance but, consistent with
social–cognitive theory (Bandura, 1986, 1997), it increased
their self-efﬁcacy because they could exercise inﬂuence
over their behavior. Increases in self-efﬁcacy correlated
signiﬁcantly with subsequent increases in job attendance.
Moreover, the job attendance of the people who were
taught these self-management skills was signiﬁcantly
higher than that of the control group three months after the
training had taken place.
In a follow-up study, Latham and Frayne (1989) found
that the increase in self-efﬁcacy and the increase in job
attendance were maintained over a nine-month period.
Then, the control group was provided with the same train-
ing in self-regulation skills as the original experimental
group. Three months later, their job attendance and self-
efﬁcacy regarding job attendance increased to the same
level as that of the original experimental group. Similarly,
Brown and Latham (2000b) studied the team-playing be-
havior of master’s-level business students in their respec-
tive study groups. Those students who set speciﬁc high
goals regarding their evaluation by peers and who received
training in verbal self-guidance regarding goal attainment
had higher team-playing skills than those who did not set
Mental practice is symbolic guided rehearsal of a task
in the absence of any physical involvement (Richardson,
1967). Using Richardson’s (1967) methodology, mental
practice in which goal setting was either implicit or explicit
was investigated by Morin and Latham (2000) as a transfer-
of-training intervention to improve the communication
skills of supervisors interacting with the union. Six months
later, self-efﬁcacy was signiﬁcantly higher for the supervi-
sors who had received training in mental practice and goal
setting than for those in the control group. Self-efﬁcacy
correlated signiﬁcantly with goal commitment and commu-
nication skills on the job.
Finally, goal-setting research led to the development
of the high-performance cycle (Latham, Locke, & Fassina,
2002; Locke & Latham, 1990). The high-performance cy-
cle explains how high goals lead to high performance,
which in turn leads to rewards, such as recognition and
promotion. Rewards result in high satisfaction as well as
high self-efﬁcacy regarding perceived ability to meet future
challenges through the setting of even higher goals. This
cycle explains the lack of a direct connection between job
satisfaction and subsequent productivity, an issue that has
long puzzled psychologists (e.g., Hersey, 1932; Kornhauser
& Sharp, 1932). In the high-performance cycle, high sat-
isfaction is the result, not the cause, of high performance
when rewards are commensurate with performance. The
subsequent effect of satisfaction on action is therefore
indirect rather than direct. Job satisfaction leads to perfor-
mance only if it fosters organizational commitment, only if
this commitment is to speciﬁc and challenging goals, and
only if the moderator variables discussed in this article are
taken into account. Goal setting also has been applied
successfully to nonwork domains, such as sports (Lerner &
Locke, 1995) and health management (Gauggel, 1999). It is
applicable to any self-regulated activity.
New Directions and Limitations
In organizational settings, the organization’s goal and the
goal of the individual manager are sometimes in conﬂict.
For example, working to attain the organization’s goals
could be detrimental to the monetary bonus of a manager if
managers are rewarded more for the performance of the
people they lead than for the performance of the overall
organization. Goal conﬂict undermines performance if it
motivates incompatible action tendencies (Locke, Smith,
Erez, & Schaffer, 1994). Seijts and Latham (2000b) found
that when speciﬁc, difﬁcult goals of the person are aligned
with the group’s goal of maximizing performance, the
group’s performance is enhanced. Without such alignment,
personal goals have a detrimental effect on a group’s
Learning and Performance Goals
We noted earlier that on tasks that are complex for people,
learning goals can be superior to performance goals. How-
ever, there have been almost no studies examining the use
of both together. Intriguing ﬁndings have been obtained by
Harackiewicz, Barron, Carter, Lehto, and Elliott (1997)
with college students. Performance goals improved grades
but did not affect interest, whereas learning goals enhanced
interest in the class but did not affect grades. The perfor-
mance effect is contrary to Dweck’s (e.g., Dweck & Leg-
gett, 1988) assertion that performance goals have a delete-
rious effect on a wide range of educationally relevant
Goals and Risk
Organizations must take risks to remain competitive in the
marketplace. Prospect theory (Kahneman & Tversky,
1979) emphasizes reference points, as does goal theory, but
it does not incorporate the concept of aspiration level.
712 September 2002
Knight, Durham, and Locke (2001) found that difﬁcult
performance goals increased the riskiness of the strategies
participants chose to use in a computer game and improved
performance. Obviously, higher risk strategies sometimes
lead to worse performance outcomes than lower risk ones,
and the conditions under which better or worse outcomes
occur need to be studied further.
Two related issues are involved here. First, do goals, along
with self-efﬁcacy, mediate personality effects? It must
be noted here that there is some doubt about the meaning
of personality test scores (Bandura, 1986, 1997). If a
trait measure refers only to past behavior, then trait–
performance correlations involve predicting current behav-
ior from past behavior. Traits, in this case, would predict
but not explain behavior. If, however, traits are viewed,
explicitly or implicitly, as reﬂecting, in some form, under-
lying motives, then they would constitute an explanation.
Regardless of one’s opinion on this issue, a number of
studies have found that goals, along with self-efﬁcacy,
mediate the effect of personality measures on work perfor-
mance (see Locke, 2001, for a summary). For example,
Matsui, Okada, and Kakuyama (1982) found that the rela-
tionship between achievement motivation (measured with a
questionnaire) and performance disappeared when the dif-
ﬁculty level of self-set goals was controlled. Barrick,
Mount, and Strauss (1993) found that the effects of con-
scientiousness on sales performance were partially medi-
ated by goals and goal commitment. VandeWalle, Cron,
and Slocum (2001) found that goals and self-efﬁcacy me-
diated the effect of a person’s goal orientation on student
The second issue involved is whether goals are better
predictors of action than traits. If goals mediate personality
effects, then the former should predict better than the latter.
Adler and Weiss (1988), in their review of the goal-setting
literature, argued that a performance goal is a strong vari-
able that masks personality differences. Yukl and Latham
(1978) found that goals predicted performance and satis-
faction better than a measure of need for achievement.
Dweck and her colleagues (Dweck, 1986; Dweck & Leg-
gett, 1988; Elliott & Dweck, 1988) found that two person-
ality traits characterized children in the classroom. Those
with a desire to acquire knowledge and skills—that is,
those with a learning goal orientation (LGO)—performed
better on school-related subjects than whose focus was
primarily on attaining a performance outcome such as a
grade or score—that is, those with a performance goal
orientation (PGO). In industrial/organizational psychology,
PGO has been measured as a desire not for challenging
goals but rather for certain or easy success that results in
praise (Button, Mathieu, & Zajac, 1996)—a focus that goal
theory predicts would be associated with low performance.
Thus, it would be an LGO rather than a PGO that would be
more likely to lead people to undertake challenges, thus
leading to high performance, as was found by VandeWalle
et al. (2001). As noted, the latter study found LGO effects
to be fully mediated by goals.
Seijts and B. W. Latham (2001) conducted a study to
determine whether a learning goal too is a strong variable.
They found that individuals who have a high PGO but are
given a speciﬁc, difﬁcult learning goal perform as well as
those with a learning goal who have an LGO. In short,
assigned goals neutralize goal orientation effects.
Further evidence that the setting of a high goal creates
a strong situation was obtained by Harackiewicz and Elliott
(1998). Using a pinball machine, they found that, regard-
less of whether a person scored high or low on need for
achievement (as measured by a self-report questionnaire), a
speciﬁc high-performance goal that was accompanied by a
rationale or purpose that emphasized a PGO resulted in a
higher level of intrinsic motivation (e.g., continued perfor-
mance during free time) than a performance goal that
emphasized an LGO. In the absence of a statement of
purpose, a speciﬁc high-performance goal that emphasized
an LGO resulted in the highest level of intrinsic interest in
Goals and Subconscious Motivation
Because we had studied conscious goals and McClelland et
al. (1953) had asserted that achievement motivation was
subconscious, McClelland collaborated with Locke and
others to see if there was a relationship between these two
concepts. The results, involving entrepreneurs in the print-
ing business, showed that need for achievement, measured
by the Thematic Apperception Test (TAT; a projective
test), had no concurrent or longitudinal relationship with a
ﬁrm’s performance and no relationship to entrepreneur-set
goals. However, goal effects were highly signiﬁcant in both
cases (Tracy, Locke, & Renard, 1999).
Howard and Bray (1988) collected TAT data in a
25-year study of managers at AT&T. Collaborating with
McClelland, they constructed a pattern score for leaders’
motives from the TAT. This score combined need for
power, power inhibition, and need for afﬁliation (weighted
negatively). Howard also possessed unscored TAT proto-
cols that she subsequently added to the data set. In addition,
she made scoring adjustments, after consulting with Mc-
Clelland about recent reﬁnements in the procedure, for
calculating leader motive pattern. In the reanalysis, the
leader motive pattern was not signiﬁcantly related to man-
agers’ number of promotions. However, managers’ ambi-
tion was a signiﬁcant motivational predictor of number of
promotions over the 25-year period. Howard (personal
communication) noted that the core item in the ambition
factor was a single interview question: “How many levels
up do you want to go?” This was the managers’ conscious
goal for number of promotions. Managers’ motive patterns
and their promotion goals were unrelated.
Two tentative conclusions may be drawn from
Howard and Bray’s (1988) results. First, even over a long
period, Ryan’s (1970) ﬁrst-level explanation of motivation,
namely, conscious goal setting, may be more reliably and
directly tied to action than are second-level explanations
(e.g., motives). Second, the conscious and subconscious
aspects of achievement motivation are unrelated.
Despite the above results, there can be no doubt that
the subconscious is a storehouse of knowledge and values
beyond that which is in focal awareness at any given time
(Murphy, 2001). People can take action without being fully
aware of what is motivating them or what stored knowl-
edge is affecting their choices. The lack of focus on the
subconscious is a limitation of goal-setting theory. In the
19th century, the Wurzburg school (Ach, Watt, Kulpe, and
others)—a school that inﬂuenced Lewin—showed that as-
signed goals (they used the term tasks) could affect action
at a later time without people being aware of it. Research is
now needed on the effect of the subconscious on goals and
on the ways in which goals arouse and affect subconscious
knowledge. As an initial step in this direction, Wegge and
Dibbelt (2000) found that hard goals automatically en-
hanced the speed of information processing.
Goal-setting theory states that, irrespective of the sub-
conscious, conscious motivation affects performance and
job satisfaction. This is especially true for people who
choose to be purposeful and proactive (Binswanger, 1991).
As Bandura (1997) noted, people have the power to ac-
tively control their lives through purposeful thought; this
includes the power to program and reprogram their sub-
conscious, to choose their own goals, to pull out from the
subconscious what is relevant to their purpose and to ignore
what is not, and to guide their actions based on what they
want to accomplish.
The essential elements of goal-setting theory, along with
the high-performance cycle model, are summarized in
Figure 4. Goal-setting theory is fully consistent with
social–cognitive theory in that both acknowledge the im-
portance of conscious goals and self-efﬁcacy. The two
theories differ in emphasis and scope. The focus of goal-
setting theory is on the core properties of an effective goal.
These properties are as follows: speciﬁcity and difﬁculty
level; goal effects at the individual, group, and organization
levels; the proper use of learning versus performance goals;
mediators of goal effects; the moderators of goal effects;
the role of goals as mediators of other incentives; and the
effect of goal source (e.g., assigned vs. self-set vs. partici-
Goal-setting theory is not limited to but focuses pri-
marily on motivation in work settings. Social–cognitive
theory and the research that underlies it are primarily
focused on self-efﬁcacy, its measurement, its causes, and
its consequences at the individual, group, and societal
levels in numerous domains of functioning. Social–cogni-
tive theory also discusses the effects of and processes
underlying modeling, cognitive development, moral judg-
ment, language development, and physiological arousal.
Despite these differences, the two theories agree about
what is considered important in performance motivation. A
detailed discussion of the relationship of goal theory to
other work motivation theories is presented in Locke
The effects of goal setting are very reliable. Failures to
replicate them are usually due to errors, such as not match-
ing the goal to the performance measure, not providing
feedback, not getting goal commitment, not measuring the
person’s personal (self-set) goals, not conveying task
knowledge, setting a performance goal when a speciﬁc
high-learning goal is required, not setting proximal goals
when the environment is characterized by uncertainty, or
not including a sufﬁcient range of goal difﬁculty levels (see
Locke & Latham, 1990, chapter 2).
A key issue involved in theory building is that of
generalization. With goal-setting theory, speciﬁc difﬁcult
goals have been shown to increase performance on well
over 100 different tasks involving more than 40,000 par-
ticipants in at least eight countries working in laboratory,
simulation, and ﬁeld settings. The dependent variables have
included quantity, quality, time spent, costs, job behavior
measures, and more. The time spans have ranged from 1
minute to 25 years. The effects are applicable not only to
the individual but to groups (O’Leary-Kelly, Martocchio,
& Frink, 1994), organizational units (Rogers & Hunter,
1991), and entire organizations (Baum, Locke, & Smith,
2001). The effects have been found using experimental,
quasi-experimental, and correlational designs. Effects have
been obtained whether the goals are assigned, self-set, or
set participatively. In short, goal-setting theory is among
the most valid and practical theories of employee motiva-
tion in organizational psychology (C. Lee & Earley, 1992;
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