Breaking The Rules Aug 2015
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This chapter was originally published in the book Advances in Motivation Science,
Volume 2. The copy attached is provided by Elsevier for the author's benefit and for
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From Locke, E. A., & Latham, G. P. (2015). Breaking the Rules: A Historical
Overview of Goal-Setting Theory. In A.J. Elliot (Ed.), Advances in Motivation
Science (pp. 99–126).
ISBN: 9780128022702
Copyright © 2015 Elsevier Inc. All rights reserved.
Academic Press
Author's personal copy
CHAPTER FOUR
Contents
1. Early Development: Laying the Groundwork for Goal-Setting Theory 100
1.1 Defying Behaviorism: Locke 100
2. An Inductive Approach to Theory Building 103
3. Empirical Findings 105
3.1 Goals 105
3.2 Feedback 105
3.3 Self-set Goals 106
3.4 Expectancy and Self-efficacy 106
3.5 Commitment 107
3.6 Affect 107
4. Learning from Field Experiments: Latham 107
4.1 Assigned versus Participatively Set Goals 109
4.2 Goals and Self-management 111
5. Goal-Setting Studies by Others 111
6. The Theory: 1990 112
7. The Theory Expanded: 2013 115
8. Observations on Theory Building 118
9. Future Directions 119
10. Conclusions 120
References 121
Abstract
This paper describes the development of goal-setting theory starting from the 1960s
when Locke saw but rejected behaviorism as the dominant paradigm in psychology.
Locke began with laboratory experiments of goals while Latham pioneered field
studies of goal setting. Because goals had reliable effects, many other researchers con-
ducted goal-setting studies. This provided a large database from which the theory was
developed inductively over a 25-year period. The theory was formulated in 1990, and
research on the theory continues apace to this day; recent developments on the theory
were published in 2013. We advocate (and seek to provide a model of) the inductive
Advances in Motivation Science, Volume 2
ISSN 2215-0919 © 2015 Elsevier Inc.
http://dx.doi.org/10.1016/bs.adms.2015.05.001 All rights reserved. 99 j
Advances in Motivation Science, First Edition, 2015, 99e126
Author's personal copy
100 Edwin A. Locke and Gary P. Latham
approach to theory building, and end this article with suggested future directions for
research on goal-setting theory.
In this same time period, projective tests were popular, especially for
measuring McClelland’s (1961) need for achievement (n ach) motive. How-
ever, their relationship to action was not always reliable. Ryan suggested that
traits and motives likely affect action through their effect on conscious inten-
tions. Locke agreed with Ryan’s view that studying immediate determinants
of action was the best strategy for predicting, understanding, and influencing
motivation.
Behaviorism, as an application of its philosophy, had made major inroads
within experimental psychology, learning theory, child psychology, psycho-
therapy, institutional management, and other specialty areas. However, it
made only minor inroads within industrialeorganizational psychology
(e.g., Campbell, 1971; Nord, 1969). This may be because I-O psychologists
have always been concerned with the world of work; hence their research
did not involve rats, pigeons, dogs, or other animals. The Journal of Applied
Psychology and management journals accepted goal-setting articles even dur-
ing the heyday of behaviorism. In the mid and late 1970s, Locke (1977,
1978) wrote articles critiquing the intrusion of “Behavior Modification”
(applied behaviorism) into work settings. He argued that those studies
“smuggled” in conscious processes such as goal setting without acknowl-
edging having done so. Furthermore, behavior modification ignored find-
ings showing that feedback itself was not an automatic reinforcer of
behavior (Locke, 1978).
Latham’s experience with behaviorism differed from Locke’s. As an
undergraduate student, he entered a bastion of behaviorism in Canada, Dal-
housie University, in 1963. There he took year-long laboratory courses on
operant conditioning principles, particularly the differential effects of
different schedules of reinforcement on the response rates of rats and
pigeons. In addition, he took courses from faculty who were social psychol-
ogists, child psychologists, and neuroscientists. He was exposed to the the-
ories and research of Festinger, Lewin, and Piaget, and most of all Hebb
(1949).1
When Latham entered the doctoral program at the University of Akron,
Yukl, his advisor, was dabbling with the effect of monetary incentives
administered in a laboratory setting on different schedules of reinforcement
(Yukl, Wexley, & Seymore, 1972). Skinner’s (1953) work with animals
showed that in the early stages of learning, animals learn faster on a
1
Hebb, arguably the father of neuroscience, did his undergraduate work at Dalhousie in the 1930s.
3. EMPIRICAL FINDINGS
As noted earlier, Locke began his research on goal setting with his
doctoral dissertation, assigning various types of performance goals on labo-
ratory tasks. This worked so well that he kept going. The studies were
not done in any particular orderdit was just an issue of “trying stuff.”
The importance of “trying stuff” in science has never been properly
acknowledged. If you already believe you know what is true, you do not
need to conduct experiments. But Locke did not do exact replications.
To build a theory, you need replication with variation (Locke, 2015), as
will be explained shortly.
3.1 Goals
Do your best goals were compared to specific, challenging goals in line with
Mace’s (1935) findings. Statistical tests verified that specific, challenging
goals are a better way than vague goals to increase performance on labora-
tory tasks. Different levels of goal difficulty were studied. The more difficult
goals seemed to work better than easier goals to increase performance. Goal
effects were studied using different laboratory tasks to ensure that the effects
were not task specific. Locke found that specificity alone affects (reduces) the
variability of performance, providing the goal is attainable, that is, perfor-
mance is controllable by the individual. If a goal exceeds an individual’s abil-
ity, then variance increases and becomes simply a function of individual
differences (Locke, Chah, Harrison, & Lustgarten, 1989). That a specific,
difficult goal leads to higher performance than a vague, do your best goal
or no goal at all would become the core of goal-setting theory (e.g., Mento,
Steel, & Karren, 1987).
3.2 Feedback
The behaviorists claimed that performance feedback is a reinforcer that
affects performance automatically. In disagreement with this assertion,
Locke undertook a series of studies, as well as a literature review, to see if
conscious goals mediate feedback effects. They do (Locke & Bryan,
1968a, 1969; Locke, Cartledge, & Koeppel, 1968). Previous studies claiming
that feedback has causal effects on performance had routinely smuggled
conscious goals into their procedure, but did not bother to measure or
acknowledge them (Locke, 1980). Feedback is only information that does
not influence an individual unless it is evaluated as relevant to some goal
3.5 Commitment
A goal that one is not committed to attaining has little or no influence on
performance. Commitment is positively related to performance (Locke,
Frederick, Buckner, & Bobko, 1984; Locke & Shaw, 1984). Commitment
is most important when goals are difficult (Erez & Zidon, 1984). This is
because people have little trouble pursuing easy goals, but may not be confi-
dent in attaining high goals that require a great deal of effort. Commitment
would become a moderator in goal-setting theory.
3.6 Affect
Locke conducted a number of experiments on goals and affect. Goals are not
only outcomes to aim for, they are at the same time standards by which to
judge one’s performance. People are more satisfied when they reach their
goals than when they do not (e.g., Locke, Cartledge, & Knerr, 1970).
This is because goals are based on or tied to values, namely that which
one considers good or beneficial. In this research endeavor, there was an un-
expected finding, one in hindsight that we should have expected. While
more difficult goals lead to higher performance than easy goals, easy goals,
other things being equal, lead to higher satisfaction because there are
more successes (Mento, Locke, & Klein, 1992). This is the clue as to why
more difficult goals work better than easy goals in bringing about high per-
formance: to get satisfaction with difficult goals an individual has to do bet-
ter, that is, achieve more.
This leads to the question of why people pursue difficult goals. The
answer is that in the real world, more benefits come to those who make
progress toward the attainment of difficult goals (Mento et al., 1992).
Consider the benefits of a student studying and getting high grades in school:
it affects what career opportunities become open to that person. To become
a psychologist, a student has to get into a university and subsequently get
good grades in difficult subjects, and then get accepted into a graduate
school.
would prove effective in the workplace (e.g., Heneman & Schwab, 1972;
Hinrichs, 1970).
After graduating from Dalhousie University, Latham entered the psy-
chology department at Georgia Tech (1967e1969). There he was immersed
in what Cronbach (1957) labeled the “other” discipline in psychology,
namely, correlational methods as opposed to empirical experiments. In addi-
tion, the faculty stressed the necessity of overcoming “the criterion prob-
lem,” that is, the development and measurement of a dependent variable
with sufficient reliability to test the significance of a predictor or the effec-
tiveness of an independent variable.
Two incidents in that time period affected Latham’s academic career.
First, “the criterion problem” and the necessity of finding solutions to prob-
lems in work settings led him to learn all he could about Flanagan’s (1954)
CIT, an inductive methodology for developing a criterion with interobserver
reliability and relevance (content validity) in the workplace. Induction, as
noted earlier, became the method of choice for developing goal-setting
theory.
Second, Latham’s master’s thesis was on the development of job perfor-
mance criteria for pulpwood producers (i.e., loggers) in the southeastern
United States. The CIT revealed that a critical behavior that differentiates
an effective from an ineffective logger is the setting of a specific goal as to
the number of trees to cut in a day/week. A factor analysis of a survey
that he and his major professor conducted revealed that goal setting and
supervisory presence loaded on the only factor that contained an objective
measure of a crew’s productivity, cords per man-hour (Ronan, Latham, &
Kinne, 1973).
Upon completing his master’s thesis, Latham, was hired by the Amer-
ican Pulpwood Association where his focus was on productivity improve-
ment. Following up on the results of a factor analysis (Ronan et al., 1973),
he matched logging crews on their size, terrain, level of mechanization, and
productivity before randomly assigning them to one of two conditions,
namely, one where the crews were given a specific, challenging goal to
attain in terms of number of trees to cut down, or to a control condition
where the crews were urged to do their best to cut as many trees as possible.
The exhortation to do your best was highly relevant to the employees
because each of the crews in both conditions were paid on a piece-rate
basis: the more trees they cut down, the more money they made. Within
the very first week of this 3-month field experiment, the productivity of
the goal-setting crews soared as did job attendance (Latham & Kinne,
1974). Goal setting had provided these crews a sense of purpose, challenge,
and meaning in what had been previously perceived by them as tedious,
repetitive work.
When their wood supply was too high, logging companies restricted the
number of days they would buy logs from five to three. In a reverse of Par-
kinson’s Law (work expands to fill the time available), the pulpwood crews,
again paid on a piece-rate basis, harvested as much wood or more during
those restricted days as they did in a normal workweek. To the dismay of
the forest products companies who wanted to reduce their wood inventory,
the restricted number of days they would buy logs became a high-
performance goal for the logging crews that in turn led to a significant
increase in their effort to cut the same amount of wood in 3 days as they
typically did in 5 days (Latham & Locke, 1975). These field experiments sug-
gest that money and deadlines increase performance to the extent that peo-
ple set, and exert effort to pursue, a high goal. Effort would become a
mediator in goal-setting theory.
Would goal setting increase the productivity of loggers who are union-
ized and paid by the hour? The answer is yes. Goal attainment enabled them
to feel a sense of accomplishment. Logging truck drivers strategized ways of
increasing the load of logs they could carry without exceeding a truck’s legal
net weight (Latham & Baldes, 1975; Latham & Saari, 1982). Strategy would
become a mediator in goal-setting theory.
All of the above field experiments provided further evidence for what
would become the core of goal-setting theory: a specific, high goal increases
task performance. A question of importance for the workplace had to do
with the optimal method of setting a goal.
2
Azrin (1977) as well as Rousseau and Fried (2001) have argued that a set of factors, when considered
together, often provide a more theoretically interesting pattern than any of the variables would show
in isolation.
performance. This is only half true. Goal setting is first and foremost a pro-
cess of discrepancy creation.
Because poor conceptualization is often a cause of poor research, our first
chapter in Locke and Latham (1990) is conceptual. We formulated a clear
definition of a goal: the object or aim of an action. Aim means that people
want something that they do not yet possess. The cause of action is the idea
or desire for the state or object not present. Such a formulation cannot be
applied to inanimate matter. Again, it cannot be overemphasized that goal
setting is first a discrepancy production process and only then a discrepancy
reduction process.
Categorizing approximately 400 goal-setting studies was relatively
straightforward. Ten major categories emerged:
• Studies of main effects
• The relation of goals to expectancies and valence
• Goal mechanisms (causal mediators)
• Determinants of choice of self-set goals
• Goal commitment
• Goals and feedback
• Moderators in addition to commitment and feedback
• Goals and affect
• Applications to human resource management
• Integration: The high performance cycle
The next step involved integration within each category. For example,
there were meta-analyses of the main effects of setting a goal, cited earlier.
Furthermore, we did something that is seldom, if ever, done. We analyzed
every published failure of goal setting. In doing so, we suggested testable
hypotheses as to the reasons for a null finding, based on what we knew about
goals, as we built our theory. The reason for this analysis was the law of
contradiction. A failure had to mean either that the method was not used
properly, or that our theory was lacking in some respect.
With respect to goal commitment, we looked at how it had been
measured. Was it relevant to all goals or only certain types? As noted earlier,
another issue was resolving contradictory findings in the literature such as
the importance of employee participation in the setting of goals.
With respect to goal mediators, we were faced with integrating motiva-
tion (goals) and cognition (task knowledge or strategies). Was task know-
ledge a mediator, a moderator, or both?
With feedback, we had to differentiate between its function as a medi-
ator and its function as a moderator.
9. FUTURE DIRECTIONS
Because human action is characteristically goal-directed, there is no
specific limit to the types of actions goal setting can regulate, so long as
the individual or team has some control over the outcome. Our 2013
book gives many examples of the use of goal setting in domains other
than work tasks.
Especially important is to do more studies of the ways in which conscious
and subconscious goals work together. We believe that the conscious mind
is the active part of one’s psychological make-up, yet it can only hold about
seven disconnected items in awareness at the same time (Miller, 1956). We
believe that the conscious mind not only regulates what goes into the sub-
conscious, but it routinely affects what comes out, based on one’s purpose.
The subconscious is more passive yet it holds millions of items of informa-
tion; the subconscious is potential awareness and is activated based on pur-
pose and association. Although goal-setting studies have shown that
conscious goals and the priming of the subconscious can have independent
effects, in the end both are aspects of the individual and both are “at work”
during one’s waking life.
The issue of learning goals also needs research, including the effects of
different learning goal instructions and learning strategies. More needs to
be discovered regarding how learning and performance goals can be com-
bined and/or ordered (e.g., see Masuda, Locke, & Williams, in press).
This ties into the field of cognitive psychology in that action, broadly
speaking, is jointly glued by both cognition and motivation.
Another need is to study how goals are committed to over long time spans.
The “marshmallow studies” (Mischel, 2014) show that being able to post-
pone gratification has many beneficial effects on life success. Certainly it
should be possible to teach people to lengthen their time perspective by using
proximal (i.e., short-term goals) as a pathway to more distal/long-term goals.
The research by Travers (2013) has opened a new domain, namely, using
goals to promote self-development. What is striking about her research is
that university students who set self-development goals (combined with
mental work such as written diaries) may improve ancillary outcomes that
were not specifically listed as goals. Goal-setting theory has always stressed
the idea that goals and outcomes must be matched. Perhaps this is not neces-
sarily so. Maybe goals generalize to dependent variables in ways that have
not yet been discovered.
Today goal setting continues to lie at the core of many human resource
management applications (Latham & Arshoff, 2013). The high-performance
cycle that, as explained earlier, shows the relationship among goals, self-
efficacy, job satisfaction, organizational commitment, and job performance
has been updated and supported in an enumerative review of the literature
(Latham, Locke, & Fassina, 2002). Empirical support for the high-
performance cycle has been obtained by the U.S. Office of Personnel
Management (Selden & Brewer, 2000) and in the private sector in Italy
(Borgogni & Dello Russo, 2013).
10. CONCLUSIONS
In summary, the theory of goal setting came about as a result of
breaking three rules, namely, eschewing (1) behaviorism, (2) premature gen-
eralizations, and (3) deduction as a method for theory development. Among
the limitations of behaviorism is that it is reactive. Behavior is said to be
solely a function of its consequences. It is the environment alone that shapes
behaviors. This premise is a half-truth in that it ignores the fact that people
are capable of forethought. Thus they can think about, plan, and act upon
their environment to create a future state they desire. Goal-setting theory
provides a framework that explains how people do so.
Among the problems of overgeneralizing a theory in the absence of
empirically derived data is that doing so ignores the fact that grand theories
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