ArticlePDF Available

The Role of a Vivid and Challenging Personal Vision in Goal Hierarchies


Abstract and Figures

This study examines personal vision and its role in human motivation. It examines the concept of personal vision within goal hierarchies, describes the elements that constitute goal hierarchies, and examines the effect of students' compelling personal vision on the quality of proximal goals. Asking participants to describe their expected or compelling personal vision did not influence the difficulty and vividness of such vision. Instead, individual differences overrode the manipulations with some students conceptualizing a more challenging and vivid personal vision compared with others. Students who naturally set a challenging and vivid personal vision also set more difficult and specific college goals. Students who conceptualized a vivid personal vision were more committed to their semester goals.
Content may be subject to copyright.
The Journal of Psychology, 2010, 144(3), 221–242
Copyright C
2010 Taylor & Francis Group, LLC
The Role of a Vivid and Challenging
Personal Vision in Goal Hierarchies
EADA, Barcelona, Spain
Missouri State University
Ameren Services Corporation
ABSTRACT. This study examines personal vision and its role in human motivation. It
examines the concept of personal vision within goal hierarchies, describes the elements
that constitute goal hierarchies, and examines the effect of students’ compelling personal
vision on the quality of proximal goals. Asking participants to describe their expected or
compelling personal vision did not influence the difficulty and vividness of such vision.
Instead, individual differences overrode the manipulations with some students conceptu-
alizing a more challenging and vivid personal vision compared to others. Students who
naturally set a challenging and vivid personal vision also set more difficult and specific
college goals. Students who conceptualized a vivid personal vision were more committed
to their semester goals.
Keywords: aspirations, compelling, goal hierarchies, goals, personal vision
BANDURA (1997) ARGUED THAT PEOPLE POSSESS multiple systems of
goals, hierarchically arranged from proximal goals to extreme distal goals. With
respect to goal hierarchies, he argued that distal goals (i.e., higher order goals) and
proximal goals serve different motivational functions. Proximal goals regulate im-
mediate motivation and action, which provide ongoing feedback and a sense of per-
sonal mastery. In contrast, distal goals define desired and enduring aspirations that
A version of this article was presented at the Society for Industrial Organizational Psychol-
ogy 2002 Congress, Toronto, Ontario, Canada. The authors thank Edwin Locke and Kevin
Williams for providing comments on earlier versions of this article.
Address correspondence to Aline D. Masuda, EADA, C/Arag´
o 204, Barcelona, Spain
CP 08011; (e-mail).
222 The Journal of Psychology
attract individuals toward meaningful destinations. Bandura’s (p. 136) argument
that proximal goals “subserve broader goals that reflect matters of personal impor-
tance and value” is consistent with his notion of logically connected goal systems.
Despite theorists’ general recognition that both distal and proximal goals drive
motivated behavior (e.g., Carver & Sheier, 1981; Cropanzano, Citera, & Howes,
1995; Donovan & Williams, 2000; Kernan & Lord, 1990; Ohbuchi & Tedeschi,
1997), few studies have examined the role of meaningful distal goals within
goal hierarchies. Instead, most goal-setting studies have examined the role of
quantitative task goals on performance (Locke & Latham, 1990). Understanding
the relationships of higher order goals with proximal goals and clarifying the
differences among goal constructs is essential to advancing goal theory. Hence, the
current study examines the effect of higher order goals on goal-setting processes.
Based on Bandura’s (1997) social cognitive theory, we define higher order goals
as personal vision and argue that the primary role of a personal vision is to instill
purpose to move towards a meaningful destination. We further argue that personal
vision influences motivation indirectly via the setting of proximal task goals. We
draw from goal-setting theory (Locke & Latham, 1990) to identify the content of a
compelling personal vision. A compelling personal vision is vivid and challenging
and stimulates the setting of and commitment to difficult and specific proximal
A Description of Goal Hierarchies
Research has shown that goal hierarchies play a fundamental role on human
motivation (Bandura, 1997; Locke & Latham, 1990). Central to the concept of
goal hierarchies is the property of goal proximity, which defines how far goals
are conceptualized into the future. At least three levels of goals exist within goal
hierarchies: peak goals, distal goals, and task goals. Peak goals are the most
distal outcome a person can imagine in any life domain (e.g., family, professional,
social). An example of one’s peak goal may be “I will own my own law practice
within 10 years of graduating from law school.” Individuals may have peak goals
in different life domains (e.g., family or work domain).
A set of distal goals can be subordinate to peak goals. For instance, “graduating
from law school, becoming a lawyer, and gaining name recognition” may be
conceived by an individual as necessary for owning his or her own law practice
in the future. Distal and proximal goal distinctions are relative; that is, a distal
goal (e.g., gain admittance to college) may subsume relatively long-term yet more
proximal goals (e.g., graduate from college). Hence, the proximal goal distinction
is not absolute and relies on another goal’s providing the temporal context. The
interconnected conglomeration of peak goals and distal goals (i.e., higher order
goals) are referred to in this study as personal vision.
Subservient to distal goals are task goals, which, when active, direct and
sustain immediate self-regulatory processes. Task goals are proximal goals that
Masuda, Kane, Shoptaugh, & Minor 223
“generate self satisfaction from personal accomplishments that operates on its
own reward during the pursuit of higher level goals” (Bandura, 1997, p. 136).
Task goals serve two functions. First, task goals stimulate the search for or use
of strategies needed to accomplish distal goals (Locke & Latham, 1990). Second,
task goals provide a standard for evaluating the effectiveness related to the strategy
used or the effort allocated to pursue such goals. For example, a task goal might
be defined as “getting an ‘A’ on my next political science exam.” Once defined,
task goals may promote the development of study strategies (e.g., reading the text
and knowing all term definitions), time management strategies (e.g., not going
out on Friday night), and effort allocation (e.g., spending more time studying
political science instead of math). Both effort and strategies can be anchored to a
specific task goal. Thus, progress toward task-goal attainment provides feedback
that permits self-regulation. That is, based on the nature of feedback to task-goal
discrepancies, one may choose to regulate effort, change strategies, change levels
of goal difficulty, or give up pursuing goals (Bandura, 1997; Carver & Sheier, 1981;
Williams, Donovan, & Dodge, 2000). Most research on goal setting investigates
task goals (Locke & Latham, 1990).
It is important to distinguish task goals and strategies. The former defines
what is to be accomplished, and the later defines how it is to be accomplished
(Wood & Bandura, 1989). Hence, strategies do not define future outcomes, but
rather they define behavioral or cognitive activities that, if employed, lead to the
attainment of such outcomes.
In defining components of goal hierarchies, distinguishing between values
and goals is also important. Schwartz has blurred the distinction between values
and goals, by not only defining values as “goals, varying in importance that
serve as guiding principles in people’s lives” (1994, p. 21), but also asserting
that values are more abstract “cognitive representations of motivation in the form
of goals” (Roccas, Sagiv, Schwartz, & Knafo, 2002, p. 793). In this article, we
adopt Roskeach’s distinction between goals and values that describes value as
defined principles of conduct, which involves judgment of worth or goodness
(Roskeach, 1973). Adopting this view puts forth values and goals as related but
distinct constructs. Specifically, values are more abstract cognitions and guiding
personal principles that influence the setting of personal goals. According to our
framework, personal values not only tend to be embedded in higher order goals,
but also may guide the goal-setter’s cognition and action as one pursues one’s
goals (e.g., “I will not entertain cheating as a viable option for attaining my ‘A’ on
my political science exam”). Last, although we acknowledge the importance of
needs in motivation, it is not within the scope of this article to investigate the effect
of values (or needs) on proximal goals; instead, we focus on the arrangement of
goals that constitutes a person’s personal vision.
Hence, based on the definition of constructs within goal hierarchies, we argue
that personal vision is more likely to reflect the set of personal values compared
to task goals or strategies. Figure 1 illustrates one’s complete hierarchical goal
224 The Journal of Psychology
FIGURE 1. The model of personal vision within hierarchical goal structures.
Personal Vision is defined as the group of Distal goals and Peak Goals repre-
sented above the dotted line.
structure and the distinctions among strategies, task goals, distal goals, peak goals,
values, and personal vision.
The Importance of Personal Vision
Despite the scarce empirical attention given to personal higher order goals
(Roberts & Robins, 2000), many theorists have agreed that higher order goals play
a substantial role in human motivated activity (Bandura, 1997; Cropanzano, James,
& Citera, 1993; Kanfer, 1990; Locke & Latham, 1990, 2002). For example, con-
structing long-term goals has appeared in (a) various literatures including those of
social cognitive theory (Bandura), personality theories (Cropanzano et al., 1993),
and goal theory (Locke & Latham, 1990); and (b) descriptions of companies’
organizational vision (Larwood, Falbe, Krieger, & Miesing, 1995). According
to Bandura’s social cognitive theory, possible futures and proximal goals that
aid in future goal attainments are key elements of human motivation. Peak and
distal goals that compose one’s personal vision direct, motivate, and sustain self-
regulated activity, effort, and planning (Bandura). In a similar vein, Cropanzano
et al. (1993) explained that higher order goals define relatively abstract values
and self-identities that guide one’s activities and plans. Cropanzano et al.’s (1993)
characterization of higher order goals is analogous to the concept of personal vi-
sion in that personal vision defines values and for this reason influences personal
Masuda, Kane, Shoptaugh, & Minor 225
Empirical evidence supports the content of higher order goals as related
to lower level goals. For example, Schepers and Beach (1998) found that high
discrepancy between one’s ideal future and one’s expected future led to revisions
in participant’s current goal-planning activities. Specifically, people who perceived
a high discrepancy between their ideal and expected futures changed their proximal
goals so that such goals facilitate the attainment of their idealized future.
The importance of distal goals is also emphasized in the literature on vision-
ary leadership. In this literature, a leader’s vision for organizations shares traits
with the concept of personal vision (Kirkpatrick, Locke, & Latham, 1996). Like
personal vision, a leader’s vision reflects values, and its enactment depends upon
subordinate goal systems in an organization. For example, Collins and Porras
(1991) defined organizational vision as composted of (a) a system of fundamental
motivation assumptions, principles, values, and tenets (i.e., guiding philosophy)
and (b) goals that convey a sense of concreteness (i.e., tangible images). In ad-
dition, theories of organizational change (e.g., Lawsen & Shen, 1998) emphasize
the utility of a unifying organizational vision for aligning subordinate organiza-
tional goals. In fact, Kirkpatrick and Locke (1996) showed the importance of a
leader’s vision when motivating employees to set their goals. Specifically, those
researchers found that participants who were told by leaders about their organiza-
tional vision set more difficult and specific goals compared with participants who
were not made aware of an organizational vision.
Despite personal vision’s important role in motivated activity, there have been
few empirical studies examining the content of one’s personal vision and how it in-
fluences proximal goal setting. The research examining the effectiveness of vision
has been limited to leadership vision and its effects on employees (Kirkpatrick
& Locke, 1996) and goal setting (Locke & Latham, 1990). Hence, we borrowed
from this literature and identified qualities of a compelling personal vision that
will most likely lead to the setting of effective proximal goals.
Compelling Personal Vision
A challenging personal vision should motivate the setting of more difficult
and specific proximal goals. According to goal-setting theory (Locke & Latham,
1990), motivated effort stems from anticipated satisfaction linked to attaining a
difficult goal. In fact, more than 400 field and laboratory studies have shown that
people who set difficult and specific task goals are likely to perform better in a task
than those who set vague or do-your-best goals (Locke & Latham, 1990). Further,
social cognitive theory stresses the importance of both discrepancy production
and reduction in explaining motivated activity (Bandura, 1997), and control the-
ory suggests that the goal-to-reality discrepancy produced by a challenging goal
generates effort (e.g., Scheier & Carver, 1985).
226 The Journal of Psychology
Research on organizational vision has also shown that challenge is an im-
portant attribute of an effective organizational vision (Baum et al. 1998; Conger
& Kanungo, 1987; Kirkpatrick, Locke & Latham, 1996; Nanus, 1992). Simi-
lar to goals and organizational vision, personal vision may become challenging
when it is difficult to attain compared to the vision of an average person (Baum,
Kirkpatrick, & Locke, 1998; Conger & Kanungo, 1987; Kirkpatrick et al., 1996;
Nanus, 1992). A challenging vision will serve an energizing function by stimulat-
ing effort and persistence. In addition, a challenging personal vision will increase
the discrepancy between one’s current situation and future state, thus motivating
action to reduce such discrepancy. People’s willingness to increase effort and per-
sistence should be evident in the content of their proximal goals. Hence, we argue
that just as one’s goals may lead to higher performance if they are specific and dif-
ficult, one’s personal vision may be more effective if it contains similar attributes.
An effective personal vision, however, will not directly influence performance;
instead, it should indirectly relate with performance by stimulating the setting of
difficult and specific proximal goals and by facilitating commitment to such goals.
Hypothesis 1 (H1): Challenge reflected in one’s personal-vision statement will
predict commitment to proximal task goals.
As previously stated, specific goals improve effort more than do vague or
do-your-best goals (Locke & Latham, 1990). Although higher order goals are
more likely to be abstract than task goals (Cropanzano et al., 1993), one’s personal
vision should be more compelling if it is high on imagery. A personal vision high
on imagery defines in detail a clear and vivid picture of one’s desired future (Bass,
1985; Baum et al., 1998; Kirkpatrick et al., 1996; Thoms & Blasko, 1999). By
clearly defining one’s desired future, a personal vision should better direct one’s
attention and effort to relevant tasks that facilitate movement toward that vision.
Hence, those who clearly know what they want in their future are more likely to
set specific task goals that will lead to such a future.
A vivid personal vision may also reflect stronger, clear, and well-established
values. Research has shown that values are related with commitment to projects.
For example, Lydon (1996) found that the degree to which personal projects
affirmed peoples’ core values predicted participants’ willingness to commit to
their projects, especially when participants perceived these projects as stressful
and difficult. In his study, Lydon examined students’ commitment to an 8-week
volunteer work project. Results revealed that students were more committed to the
volunteer project if they reported that the project affirmed their personal values.
The findings were more robust when students perceived the project as difficult and
Because a vivid personal vision provides a clear picture of a future and reflects
well-established values, people who conceptualize a vivid personal vision will be
Masuda, Kane, Shoptaugh, & Minor 227
more committed to their proximal goals and will be more likely to set specific
proximal task goals.
H2: The imagery contained in one’s conceptualized vision statement will predict
the specificity of subordinate personal goals.
H3: The imagery contained in one’s conceptualized vision statement will predict
subordinate goal commitment.
Proximal Goals and Student Achievement
Consistent to Locke and Latham’s (1990) goal-setting theory, we expected
to find that students who set difficult and specific proximal goals would likely
achieve a higher semester grade point average (GPA) compared to those who
set easy and vague goals. Because in the current research, we employed novel
methodology for evaluating the goal difficulty of student’s freely reported goals
(i.e., rater’s judgments of freely reported goal), replicating an often cited goal-
setting principle in this research was important for establishing the validity of our
qualitative measure of goal difficulty.
H4: Difficulty and specificity semester goals will predict student achievement.
Undergraduate students from a university in the Midwest United States were
recruited from undergraduate psychology courses and participated in this study for
course credit. The sample consisted of 180 participants: Of them, 95 (51.4%) were
freshman, 48 (25.9%) were sophomores, 25 (13.5%) were juniors, and 8 (4.3%)
were seniors. The sample also consisted of 53 men (29.4%) and 124 women (68%).
This study was part of a broader study on personality and goals, and two
data collection periods were conducted in accordance with the ethical guidelines
put forth by the American Psychological Association and the University Human
Subjects Review for the protection of human research participants. Phase 1 took
place in a classroom with all students present. Students arrived and were given
a questionnaire with the study measures and informed consent. They read and
signed the inform consent letter and completed the questionnaire that measured
personality variables. A group of 50 participants in Phase 1 were randomly as-
signed to a repeated measures compelling vision condition, where they were asked
to report their visions during Phase 1.
In Phase 2 of the experiment, conducted approximately 3 weeks after Phase 1,
the same participants returned to complete the manipulations. Specifically, we
228 The Journal of Psychology
randomly assigned 50 students to the control condition, 51 to the descriptive
condition, and 49 to the compelling personal vision condition. Last, participants
who were assigned to the repeated measures vision condition during Phase 1 were
assigned to the same condition during Phase 2. However, of the 50 participants
assigned to this manipulation, only 29 participants returned for Phase 2 of the
study. The following were the instructions for each manipulation and the amount
of subjects included per condition.
Compelling Personal Vision (49 Participants)
Instructions for the condition of compelling personal vision were:
A compelling personal vision is a unique and ideal image of the future. Today, we
will ask you to write an optimistic portrayal of your professional future. Please
visualize the most compelling vision you can. Through visualization create a
picture of what you want most in your professional life. After visualizing your
ideal future, please describe your personal vision below. Here are some tips to
think about while you write your personal vision: Challenge yourself, be specific,
think positively. After you finished writing about your professional vision, please
complete the following questionnaire.
After participants wrote their vision, instructions directed participants to set
personal semester and proximal goals.
Descriptive Personal Vision (51 Participants)
Instructions for the condition of descriptive personal vision were:
In the space provided below, we ask that you fully describe what you believe
your professional future will look like. After you finished writing about your
professional vision, please complete the following questionnaire.
After participants wrote their vision, instructions directed participants to write
personal semester and proximal goals.
Repeated Measure Compelling Vision (29 Participants)
The instructions given in the condition of repeated measure compelling vi-
sion were similar to the instructions in the compelling vision condition. After
participants wrote their visions, instructions directed participants to write per-
sonal semester and proximal goals.
Control Condition (50 Participants)
In the control condition, participants were first given instructions to set per-
sonal semester and proximal goals. After participants wrote their personal goals,
they were only asked to report a descriptive vision:
In the space provided below, we ask that you fully describe what you believe your
professional future will look like.
Masuda, Kane, Shoptaugh, & Minor 229
Personal Vision
Operationally, personal vision was defined as statements reported by partic-
ipants when asked to report their professional future. All participants wrote their
personal vision, and these statements were measured for the attributes of challenge
and imagery. Specifically, three raters rated the vision statements according to def-
initions of challenge and imagery. Each rater practiced rating a sample of vision
statements that contained extremes of each attribute. These vision statements were
used as prototypes when rating the remaining vision statements. Each dimension
was scored along an 8-point scale from 0 (“attribute absent”) to 7 (“attribute was
present at a higher level”). If participants indicated, by checking a box on the
questionnaire, that they did not have a vision, then they received a rating of 0. This
method of rating has been successfully implemented when rating organizational
vision (Baum et al., 1998) and has yielded respectable reliabilities. In our study,
interrater reliability was intraclass correlation coefficient (ICC) =.93 for chal-
lenging and ICC =.87 for imagery. Imagery and challenge were highly correlated,
r=.81. Examples of challenging and imagery ratings are the following.
An example of a vivid (i.e., high on imagery) personal vision (7) is:
My vision of my professional life entails a number of areasin my life. I would like to
work abroad in diplomatic outpost of the United States. I would particularly enjoy
working in the political arena of the State Department. In the future, I visualize
myself speaking a number of foreign languages, such as French, Chinese, and
German. I hope to travel the world and absorb the “culture” of the UK, France,
Italy, Japan, and China. I hope to continue my passion for art and music. I will
be the guy that goes to a cafe in France on a crowed business street to drink
wine and enjoy life. I see myself participating in high adventure sports such as
mountain climbing, and kickboxing.
An example of low vivid personal vision (0) is:
I hope to choose a major that I will enjoy and find a job where I can support
myself as well as my family with my earnings.
An example of a high challenging personal vision (7) is:
In the most compelling portrayal of my professional future I see myself in the
NFL. I see myself making millions and being wealthy enough to where I can
walk away from my job when I please to do. I see myself making it to numerous
pro bowls and playoffs.
An example of low challenging personal vision (0) is:
230 The Journal of Psychology
Academic Free-Set Goals
Students reported semester and college academic goals by writing responses
to the question “List academic goals you have set for yourself to accomplish by
the end of the semester.” This method allows the quality of student’s goals to vary.
Examples of academic goals were “Not procrastinate,” “Attend all classes,” “Get
As,” and “Get an internship.” Students were asked to list only goals set prior to
completion of the survey and were given the option to place a check mark beside
the statement “I have not set semester goals.” Space was provided for students
to list as many goals as they wished to report. Participants were asked to report
college goals in the same manner.
Goal Specificity
Goal specificity was assessed based on Locke, Chah, Harrison, and Lust-
garten’s (1989) definition that goal specificity is evident by the range and clarity
of outcomes that potentially satisfy goal accomplishment. Trained raters assessed
the goal specificity on a scale ranging from 1 (“extremely low clarity with wide
range of outcomes”) to 7 (“goal defines a concrete single outcome that defines
goal attainment, the outcome satisfying goal attainment is easily envisioned, and
behaviors required for attainment are clear”). The present goal specificity assess-
ment was devised and successfully implemented when rating goal specificity in
athletic settings (Kane, Baltes, & Moss, 2001). Raters considered two character-
istics when determining the level of goal specificity: (a) the clarity of behavior
and the range of possible outcomes that satisfy goal attainment and (b) whether
additional information could be (reasonably) reported to further reduce the range
of outcomes that satisfy goal attainment. Raters initially rated a sample of approx-
imately 50 goals from each level and discussed inconsistencies in rating. When
acceptable reliability was attained on the sample goals, the raters proceeded to rate
all goals. Interrater reliability for semester goals was ICC =.82 and for college
goals was ICC =.91 .
Goal Difficulty
Trained raters assessed goal difficulty on 7-alternative scale ranging from 1
(“not difficult”) to 7 (“very difficult”). They used a norm-referenced approach to
assessment because goal difficulty judgments were referenced against the aca-
demically average student. The validity of norm-referenced assessment has been
supported across a broad range of settings (Wright, 1990) and in rater’s assess-
ments of free-set goals (Kane, Loughran, Shoptaugh, Nelson, & Reichard, 2002).
Researchers first individually rated a sample of goals. Anchors were established
based on commonly reported goals for which raters consistently agreed. For exam-
ple, a goal received a rating of 1 if it was determined that it was easily attained by
anyone, even those who have below average academic ability, and included goals
such as “attend class” or “find a major.” When acceptable reliability was attained
Masuda, Kane, Shoptaugh, & Minor 231
on the sample goals, the raters proceeded to rate all goals. Interrater reliability for
semester goal difficulty was ICC =.85 and for college goal difficulty was ICC =
Goal Commitment
Goal commitment was assessed by responses to four items attached to each
goal statement reported by the participant. Items were generated according to
conceptualizations of goal commitment that include willingness to put forth effort,
unwillingness to lower one’s goal, and goal importance (Locke & Latham, 1990).
For each goal reported, participants responded to each item on a 7-alternative scale
ranging from 1 (“Strongly agree”) to 7 (“Strongly disagree”). Internal consistency
reliability was α=.77 for semester goal commitment and α=.79 for college
goal commitment.
Participants reported age, gender, ACT scores, class year, and major.
Student’s reported cumulative GPA was used to assess prior academic achieve-
ment, and their achieved GPA reported at the end of the semester was used to assess
student achievement.
Manipulation Check
To test whether our manipulations had an effect on the quality of personal
vision statements, we conducted an analysis of variance using conditions as inde-
pendent variables and challenge rated in the visions as dependent measure. Results
of the manipulations did not reveal effects on the quality of personal vision. There
were no significant differences between mean ratings on the amount of challenge
across conditions, F(3, 173) =.51, p>.05: compelling personal vision (M=
3.47, SD =2.12), descriptive vision (M=3.63, SD =1.22), and control (M=
3.81, SD =1.07) conditions. For this reason, we used the ratings of challenge and
vividness done in all vision statements written by individuals across conditions as
independent variables. Specifically, we rated the amount of challenge or imagery
contained in each vision statement and used the composite of these ratings to
test our hypothesis within participants. For the repeated measures condition, we
analyzed the vision statements described during Phase 2.
These analyses are consistent with analyses done in previous studies of self-
regulation in the examination of the relationships among distal and proximal goals
(e.g., Kane et al., 2001), the relationship between assigned goal level and personal
232 The Journal of Psychology
goal levels (e.g., Early & Lituchy, 1991), and relationships between goals, self-
efficacy, and achievement (e.g., Wood, Bandura, & Bailey, 1990).
Hypothesis Testing
Descriptive statistics and interrater reliability are shown in Table 1. Table 2
reports correlations among predictors and criteria for key study variables.
Students set a range of 1–11 goals. To test the hypotheses, we used two depen-
dent measures of goal difficulty. First, we averaged the difficulty and specificity of
semester and college goals across all goals reported by students. Second, we used
the most difficult college and semester goals reported by students as dependent
variables in our analysis. This analysis is consistent with previous analyses of
free-set goals (e.g., Kane et al., 2002).
TABLE 1. Descriptive Statistics
Category & Variable N Range M SD r
Gender 177 1–2 1.69 0.46
Age 177 17–50 20.54 4.75 —
Class year 180 1–4 1.69 0.45 —
Declared major 180 0–2 0.45 —
Self-reported ACT 141 17–33 23.83.12 —
Number of goals 180 0–11 3.17 1.64 —
Goal difficulty
Average semester goal 176 1.73–6.17 3.49 0.92 .85a
Average college goal 174 1.22–6.33 3.45 0.97 .91a
Most college goals 174 1.33–7.00 4.36 1.2.91a
Most semester goal 175 1.33–6.33 4.44 0.93 .85a
Goal specificity
Averaged semester 175 1.17–5.67 3.14 0.98 .82a
Averaged college 172 1.20–6.00 3.16 0.96 .91a
Goal commitment
Semester goal 173 3.25–7.00 5.92 0.85 .77b
College goal 171 2.50–7.00 6.18 0.88 .79b
Personal vision
Imagery 175 0.00 –7.00 3.11 1.77 .87a
Challenging vision 177 0.00–5.78 3.25 1.39 .93a
Prior student achievement 163 1.57–4.00 3.14 3.1NA
Student achievement 138 0.69–4.00 0.66 0.7—
Note. ACT =scores in college entrance exam.
aIntraclass correlation coefficient based on three raters.
bCronbach’s alpha was reported for individual member sale responses.
Masuda, Kane, Shoptaugh, & Minor 233
TABLE 2. Correlations Among Study Variables
Variable 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18
1. Gender 1
2. ACT score .03 1
3. Age .02 –.04 1
4. Class year .00 –.06 .31∗∗ 1
5. Number of goals .27∗∗ .02 .10 –.04 1
6. Major undeclared .01 –.13 –.02 .17.04 1
7. Most difficult
.13 .29∗∗ .03 .17.07 –.191
8. Most difficult college .09 .18.10 .16.01 –.18.48∗∗ 1
9. Difficult semester .12 .18.06 .18.33∗∗ .15 .62∗∗ .33∗∗ 1
10. Specificity semester .07 .03 –.01 .16.26∗∗ .18.45∗∗ .30∗∗ .69∗∗ 1
11. Difficult college .04 .10 –.06 .23∗∗ .25∗∗ .18.40∗∗ .80∗∗ .46∗∗ .41∗∗ 1
12. Specificity college .02 .11 .06 .26∗∗ .26∗∗ .21∗∗ .36∗∗ .63∗∗ .40∗∗ .47∗∗ .76∗∗ 1
13. Semester commitment .16.05 –.05 .06 –.01 –.03 .02 .13 .12 .10 .15.201
14. College commitment .15 –.05 –.06 .05 .09 –.01 .05 .14 .13 .09 .12 .14 .73∗∗ 1
15. Imagery .01 .12 –.03 .12 .08 –.13 .17.27∗∗ .11 .02 .29∗∗ .22∗∗ .15 .00 1
16. Challenge .06 .18.04 .09 .02 –.06 .22∗∗ .32∗∗ .15 .06 .33∗∗ .31∗∗ .15.03 .81∗∗ 1
17. Prior GPA .03 –.02 .16.10 .11 .06 –.04 –.06 –.10 –.05 –.05 –.02 –.09 –.08 –.01 –.02 1
18. Student achievement .08 –.02 .01 –.04 –.08 .08 .05 –.07 –.02 –.07 .01 –.07 –.10 .00 –.11 –.03 .62∗∗ 1
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18
Note.ACT=scores in college entrance exam.
p<.05. ∗∗ p<.01.
234 The Journal of Psychology
Four regression analyses were conducted. The first two regressions predicted
semester goal difficulty. Results showed that prior achievement uniquely con-
tributed to the prediction of the most difficult semester goal (ß =.43, p<.01) and
the averaged semester goal difficulty (ß =.24, p<.01), but challenging personal
vision did not add uniquely to the prediction of the semester goal difficult (ß =
.03, ns) or the most difficult semester goal (ß =.04, ns). (See Table 3.)
The third and fourth regression analyses predicted college goal difficulty.
Results indicated that challenging vision and covariates contributed 24% of the
variance in the prediction of college goal difficulty (R2=.24), F(4, 150) =11.32,
p<.01, with challenging vision (ß =.25, p<.01), total number of goals (ß =
–.24, p<.01), and prior GPA (ß =.16, p <.01) contributing uniquely. Last,
covariates and challenging personal vision accounted for 19% of the variance in
most difficult college goals (R2=.19), F(3, 168) =9.23, p<.01. In that analysis,
only challenging vision (ß =.21, p<.01) and prior GPA (ß =.24, p<.01)
contributed uniquely to the prediction. In general, challenging vision predicted
college goal difficulty but not semester goal difficulty. (See Table 3.)
According to H1, challenging personal vision would predict goal commit-
ment. We tested this hypothesis by entering challenging vision and covariate (i.e.,
gender) in one block to predict semester and college goal commitments. Chal-
lenging personal vision and gender contributed 7% of the variance in predicting
semester goal commitment (R2=.07), F(2, 164) =6.81, p<.01, with challenging
vision (ß =.21, p<.01) and gender (ß =.20, p<.01) (i.e., men coded as 0 and
women coded as 1) contributing uniquely. In the second regression, challenging
personal vision and gender only marginally predicted college goal commitment
(R2=.03), F(2, 167) =2.63, p=.05, with only gender contributing uniquely
=.17, p<.01). Hence, H1 was partially supported, with challenging vision
predicting semester goal commitment but not college goal commitment.
H2 stated that the imagery contained in one’s vision statement would be posi-
tively associated with the specificity of proximal task goals. Results showed that a
vivid personal vision and covariates contributed 11% of the variance in predicting
the mean specificity for semester goals (R2=.11), F(4, 150) =4.44, p<.01.
However, in that analysis, only number of goals reported by students (ß =–.24,
p>.01) and prior GPA (ß =.16, p>.05) contributed uniquely. In analysis
predicting college goal specificity, imagery and covariates contributed signifi-
cantly (R2=.24), F(4, 148) =11.17, p<.01, with imagery vision (ß =.27,
p>.01), class year (ß =.17, p>.05), and total number of goals (ß =–.23,
p>.01) contributing uniquely. Hence, H2 was partially supported; a vivid
personal vision predicted college goal specificity but did not predict semester
H3 stated that the imagery component of personal vision would predict goal
commitment. Results showed that imagery and gender contributed 7% of the
variance in predicting semester goal commitment (R2=.070, F(2, 165) =6.63,
p<.01, with imagery vision (ß =.20, p<.01) and gender (ß =.19, p<.01)
Masuda, Kane, Shoptaugh, & Minor 235
TABLE 3. Regression Analysis: Challenge Vision as Predictors of Goal Difficulty
Semester goal difficulty College goal difficulty
Variable MßMostß MßMostß
Number of goals –.29∗∗ .13 –.24∗∗
Class year .13 .09 .20∗∗
ACT .09 .20∗∗ — .13
Declared major –.01
Challenging vision .03 .04 .25∗∗ .21∗∗
Prior GPA .24∗∗ .43∗∗ .16∗∗ .24∗∗
R2=.20 R2=.14 R2=.24 R2=.19
F(5, 152) =7.70∗∗ F(5, 151) =14.91∗∗ F(4, 150) =11.32∗∗ F(4, 168) =9.23∗∗
Note. ACT =scores in college entrance exam.
p<.05. ∗∗p<.01.
236 The Journal of Psychology
TABLE 4. Regression Analysis: Imagery Vision as Predictors of Goal Specificity and Goal Commitment
Mgoal specificity Goal commitment
Variable Semester College Semester College
Predictors set ß ß ß ß
Number of goals –.24∗∗ –.23∗∗ NA NA
Class year 0.14 .19∗∗ NA NA
Gender NA NA .19∗∗ .22∗∗
Imagery vision 0.02 .27∗∗ .20∗∗ .08
Prior GPA .16.17NA NA
R2 =.11 R2=.24 R2=.07 R2 =.05
F(4, 150) =4.44∗∗ F(4, 148) =11.17∗∗ F(2, 165) =6.63∗∗ F(2, 163) =4.54
Note. For the variable of gender, men were coded as 1, and women were coded as 2.
p<.05. ∗∗p<.01.
Masuda, Kane, Shoptaugh, & Minor 237
contributing uniquely. In the second regression, imagery and gender did not predict
college goal commitment. Hence, H3 was partially supported with vivid vision
predicting semester goal commitment but not college goal commitment.
Lastly, H4 stated that the difficulty and specificity of subordinate goals would
predict student achievement. Because difficulty and specificity of goals were
highly related, we only tested the effects of goal difficulty on student achievement.
Consistent with goal-setting theory, difficult goals predicted student achievement.
Results showed that the most difficult semester goal and prior GPA predicted 39%
of the variance in student semester GPA (R2=.39), F(2, 108) =34.45, p<
.01, with prior GPA (ß =.53, p<.01) and most difficult semester goal (ß =.16,
p<.05) predicting uniquely. A similar regression analysis was conducted using
average semester goal difficulty and prior GPA as independent variables. Results
showed that both variables predicted 38% of the variance in student GPA (R2=
.38), F(2, 109) =33.98, p<.01, with prior GPA (ß =.59, p<.01) and averaged
difficult semester goal predicting uniquely (ß =.11, p=.05).
While goal hierarchies and meaningful distal goals occupy an important place
in motivational theories of self-regulation, the empirical study of such goal hierar-
chies has been rarely broached. A prime theoretical purpose of the present project
was to examine connections among goals in hierarchical structures and achieve-
ment. Bandura (1997) offered that higher order goals in hierarchical structures
provide meaning to the attainment of subordinate task goals. In support of this
assertion, we found that the attributes of one’s personal vision predicted students’
commitment to their semester goals. Specifically, the extent to which a student’s
personal vision is challenging and vivid positively related with his or her attach-
ment to semester task goals, unwillingness to lower these goals, and intended
effort to attain these goals. Note that challenge and specificity inherent to col-
lege goals were unrelated to semester goal commitment, providing evidence that
commitment to proximal goals is most potently affected by goals that are high in
one’s goal structure. This finding implied that the role of higher order goals in
motivational systems is different from the role of task goals.
Also theoretically relevant, findings indicated that challenge inherent in higher
order goals associated positively with challenge at a subordinate level of the
hierarchy. That is, one’s personal vision affected college goal difficulty, and college
goal difficulty was associated with the difficulty inherent to semester goals. Similar
pattern was found with the vividness and specificity of goals. These findings
provide support for Bandura’s (1997) contention that people possess logically
connected goal systems. However, a lack of relationship between the qualities
of one’s vision and semester goal difficulty indicates that college goals did not
mediate effects of personal vision on semester goals. Possibly, factors not measured
in our research influence the effects of goals atop goal structures on proximal
238 The Journal of Psychology
goals. A logical moderator is the perceived relevance of semester goals to the
advancement towards one’s personal vision. If the attainment of semester goals,
for instance, was unrelated to the realization of one’s personal vision, then it
would not be reasonable to expect a connection between the challenge contained
in one’s vision with the difficulty of semester goals. The perceived relevance of
subordinate goals to one’s personal vision might also strengthen the relationship
between the qualities of one’s vision and proximal goal commitment.
Although previous studies have investigated the effects of distal and prox-
imal goals (e.g., Donovan & Williams, 2003; Latham & Seijts, 1999, 2001) on
motivated behavior, our study was the first to examine the nature of people’s ex-
tremely distal aspirations (i.e., personal vision) in relation to subordinate goals.
While we were unable to manipulate the content of personal vision, we observed
variation in the content of personal vision reported across individuals. Students
who described a challenging and vivid personal vision were naturally more likely
to set difficult and specific college goals. That is, individuals who had a clear idea
of where they want to be in 10 years and who were also ambitious were more
likely to challenge themselves by setting difficult and specific college goals. These
findings may suggest that compelling personal visions are difficult to craft and
that individual differences are likely to relate with ones ability to craft a com-
pelling personal vision. Studies exploring antecedents of personal visions may be
Clearly defining and differentiating goal concepts within goal hierarchies is
important so that we can better understand their role in human motivated activity.
The current study suggests that personal vision and goals should serve different
functions relative to motivated activity. Our findings encourage further studies ex-
amining the role of commitment across different levels of goals within hierarchies
to predict achievement. For example, it would be interesting to explore whether
commitment to one’s personal vision is more important in the self-regulation pro-
cess than commitment to task goals. The principle of equifinality comes to mind
in that there are many different ways to reach an end. A study done by Donovan
and Williams (2003) on goal revisions of athletes showed that athletes tended to
revise proximal goals while keeping the level of difficulty of distal goals constant.
Thus, we can speculate whether commitment to personal vision may lead to higher
performance compared to commitment to proximal goals. Future studies examin-
ing the relationships among motivational variables such as goal commitment and
self-efficacy at different levels of goal hierarchies may advance our knowledge of
self-regulated activity.
The limitations of the present study must be acknowledged. Our attempt to
manipulate the quality of one’s personal vision failed. As such, we cannot assume
that a challenging and vivid image caused the setting of difficult and specific
goals. It is also plausible that the content of proximal goals influenced the degree
Masuda, Kane, Shoptaugh, & Minor 239
of challenge or image inherent in one’s personal vision. For example, Weldon
and Yun’s (2000) study revealed that a team of nurses with both proximal and
distal goals performed better and tended to set more difficult long-term goals
compared to those who had distal goals only. Also, it is equally possible that the
relationship between proximal goals and personal vision is one of reciprocity, such
that influencing either the top or bottom of the hierarchy will lead to changes in
self-regulation. For example, a person who sets difficult proximal goals related to
a subject (e.g., getting an “A” in biology) and who succeeds may develop a more
vivid and challenging vision related to sciences (e.g., getting a Ph.D. in biology).
In this example, proximal goal setting and attainment influenced the vividness and
difficulty of a vision. Future studies exploring this relationship by using stronger
manipulations or longitudinal designs would be highly desirable. These studies
may provide insight on how individuals develop their aspirations and ambitions.
Further, because our sample consisted of undergraduate psychology students,
one should also be cautious when generalizing these results to other settings.
In business settings, the quality of one’s personal vision may vary according to
tenure, age, and job position. For example, workers may be less optimistic and
more realistic regarding their professional future based on their experiences.
Understanding the importance of personal vision in motivation may be of
utility to understand how individuals develop their career paths and their visions.
For example, career counselors may be more equipped to help students to plan
their career paths by understanding how individuals develop ambition and craft
a vivid personal vision. The fact that vividness was important for semester goal
commitment may be indicative of the importance of defining one’s values and
learning about one’s priorities early in life.
Examining personal visions can also be useful when selecting employees for
managerial positions. Personal goals are commonly used as criteria for selection,
whereas applicants are asked to report their professional goals and often their
professional future (i.e., selection interview, assessment center). For example,
Howard and Bray (1988) found that the level of career aspiration was the single best
predictor of career progress in the 25-year longitudinal study of AT&T managers.
Because of the importance of personal vision for managerial success, training
recruiters to identify compelling personal visions may be of utility when selecting
potential managers.
Last, this article should encourage further studies to examine the content of
personal vision in goal hierarchies related to personality characteristics such as
ability, personality, and values. That is, which personality variables could explain
differences in people’s ability to conceptualize their personal future? Understand-
ing differences in people’s ability to craft a vivid vision of their future may proof
240 The Journal of Psychology
to be useful in training career counselors, coaches, or mentors on the best way to
help others to clarify and conceptualize their career paths.
Aline D. Masuda is a professor at EADA in Barcelona, Spain. Her research interests
are work motivation and self-regulation, the work–family interface, and organizational
attitudes and cross-cultural management. Thomas D. Kane is a professor of psychology
at Missouri State University in Springfield, Missouri, USA. His current research interests
are team dynamics, motivation in work and sport, and leadership. Carol F. Shoptaugh is
a professor of psychology at Missouri State University in Springfield, Missouri, USA. Her
current research interests are work motivation, workplace health and safety, and integrity.
Katherine A. Minor is a senior supply chain coordinator at Ameren Services Corporation.
Her interests include organizational change management and the human factors associated
with large-scale enterprise system implementation and change.
Bandura, A. (1997). Self-efficacy: The exercise of control. New York: Freeman.
Bass, B. M. (1985). Leadership and performance beyond expectations. New York: Free
Baum, J. R., Kirkpatrick, S. A., & Locke, E. A. (1998). A longitudinal study of the relation
of vision and vision communication to venture growth in entrepreneurial firms. Journal
of Applied Psychology,83, 43–54.
Carver, C. S., & Scheier, M. F. (1981). Attention and self-regulation: A control-theory
approach to human behavior. New York: Springer-Verlag.
Collins, J. C., & Porras, J. I. (1991). Organizational vision and visionary organizations.
California Management Review,35, 30–52.
Conger, J. A., & Kanungo, N. R. (1987). Toward a behavioral theory of charismatic
leadership in organizational settings. Academy of Management Review,12(4), 637–647.
Cropanzano, R. S., Citera, M. A., & Howes, J. A. (1995). A goal hierarchy approach to
plan revision. Motivation and Emotion,19, 77–95.
Cropanzano, R. S., James, D., & Citera, M. A. (1993). A goal hierarchy model of person-
ality, motivation and leadership. In L. L. Cummings & B. M. Staw (Eds.), Research in
organizational behavior (pp. 267–322). Greenwich, CT: JAI.
Donovan, J. J., & Williams, K. J. (2000, April). The impact of goal hierarchies, progress,
and anticipated emotions on goal revision. Paper presented at 2001 annual meeting of
SIOP, New Orleans, LA.
Donovan, J. J., & Williams, K. J. (2003). Missing the mark: Effects of time and causal
attributions on goal revision in response to goal-performance discrepancies. Journal of
Applied Psychology,88, 379–390.
Early, P. C., & Lituchy, T. R. (1991). Delineating goal and efficacy effects: A test of three
models. Journal of Applied Psychology,76, 81–98.
Howard, A., & Bray, D. (1988). Managerial lives in transition: Advancing age and changing
time. New York: Guilford.
Kane, T. D., Baltes, T. R., & Moss, M. C. (2001). Causes and consequences of free-set goals:
An investigation of athletic self-regulation. Journal of Sport and Exercise Psychology,
23, 55–76.
Masuda, Kane, Shoptaugh, & Minor 241
Kane, T. D., Loughran, J. E., Shoptaugh, C. F., Nelson, A., & Reichard, R. (2002, April).
Assessing three measures of free-set goal difficulty. Poster presented at the annual meeting
of the Society of Industrial/Organizational Psychology, Toronto, Canada.
Kanfer, R. (1990). Motivation theory and industrial organizational psychology. In L. M.
Hough & M. D. Dunnette (Eds.), Handbook of industrial organizational psychology:
Vol. 1. (2nd ed., pp. 75–170). Palo Alto, CA: Consulting Psychologist Press.
Kernan, M. C., & Lord, R. C. (1990). Effects of valence, expectancies, and goal performance
discrepancy in single and multiple goal environments. Journal of Applied Psychology,
75, 194–203.
Kirkpatrick, S. A., & Locke, E. A. (1996). Direct and indirect effects of three core charis-
matic leadership components on performance and attitudes. Journal of Applied Psychol-
ogy,81(1), 36–51.
Kirkpatrick, S. A., Locke, E. A., & Latham, G. P. (1996). Implementing the vision: How is
it done? Polish Psychological Bulletin,27(2), 93–106.
Larwood, L., Falbe, C. M., Krieger, M. P., & Miesing, P. (1995). Structure and meaning of
organizational vision. Academy of Management Journal,38(3), 740–769.
Latham, G. P., & Seijts, G. S. (1999). The effects of proximal and distal goals on performance
on a moderately complex task. Journal of Organizational Behavior,20, 421–429.
Latham, G. P., & Seijts, G. S. (2001). The effects of distal learning, outcome and proximal
goals on a moderately complex task. Journal of Organizational Behavior,22, 291–
Lawson, R. B., & Shen, Z. (1998). Organizational psychology: Foundations and applica-
tions. New York: Oxford University Press.
Locke, E. A., Chah, D., Harrison, S., & Lustgarten, N. (1989). Separating the effects of goal
specificity and goal level. Organizational Behavior and Human Decision Processes,43,
Locke, E. A., & Latham, G. P. (1990). A theory of goal setting and task performance. Upper
Saddle River, NJ: Prentice Hall.
Locke, E. A., & Latham, G. P. (2002) Building a practically useful theory of goal setting
and task motivation: A 35-year odyssey. American Psychologist,57, 705–717.
Lydon, J. (1996). Toward a theory of commitment. In C. Seligman, J. M. Olson, & M. P.
Zanna (Eds.), The psychology of values (pp. 191–214). Mahwah, NJ: Erlbaum.
Nanus, B. (1992). Visionary leadership. San Francisco: Jossey-Bass.
Ohbuchi, K. I., & Tedeschi, J. T. (1997). Multiple goals and tactical behaviors in social
conflicts. Journal of Applied Social Psychology,27, 2177–2199.
Roberts, B. W., & Robins R. W. (2000). Broad dispositions, broad aspirations: The in-
tersection of personality traits and major life goals. Personality and Social Psychology
Bulletin,26, 1284–1296.
Roccas, S., Sagiv, L., Schwartz, S. H., & Knafo, A. (2002). The big five personality factor
and personal values. Personality and Social Psychology Bulletin,28, 789–801.
Roskeach, M. (1973). The nature of human values. New York: Free Press.
Scheier, M. F., & Carver, C. S. (1985). Optimism, coping, and health: Assessment
and implications of generalized outcome expectancies. Health Psychology,4, 219–
Schepers, D. H., & Beach, L. R. (1998). An image theory view of worker motivation. In
L. R. Beach (Ed.), Image theory: Theoretical and empirical foundations (pp. 125–131).
Mahwah, NJ: Erlbaum.
Schwartz, S. H. (1994). Are there universal aspects in the structure and contents of human
values? Journal of Social Issues,50, 19–45.
Thoms, P., & Blasko, D. (1999). Preliminary validation of a visionary ability scale. Psy-
chological Reports,85, 105–113.
242 The Journal of Psychology
Weldon, E., & Yun, S. (2000). The effects of proximal and distal goals on goal level,
strategy development, and group performance. Journal of Applied Behavioral Science,
36, 336–344.
Williams, J. K., Donovan, J. J., Dodge, T. L. (2000). Self-regulation of performance: Goal
establishment and goal revision processes in athletes. Human Performance,13, 159–180.
Wood, R., & Bandura, A. (1989). Social cognitive theory of organizational management.
Academy of Management Review,10, 361–384.
Wood, R. E., Bandura, A., & Bailey, T. (1990). Mechanisms governing organizational
performance in complex decision-making environments. Organizational Behavior and
Human Decision Processes,46, 181–201.
Wright, P. M. (1990). Operationalization of goal difficulty as a moderator of the goal
difficulty performance relationship. Journal of Applied Psychology,3, 227–234.
Original manuscript received April 23, 2009
Final version accepted October 4, 2009
... Empirical research indicates that persons who establish compelling personal visions are more likely to set specific and personally relevant goals (Masuda et al., 2010). ...
... Correspondingly, persons who set specific and meaningful goals are more likely to achieve their stated outcomes when compared to persons who set vague goals (Locke & Latham, 2002;Vincent et al., 2004). Consequently, a personal vision appears to play an integral role in motivation and the achievement of meaningful life goals (Masuda et al., 2010). ...
Student affairs practitioners have essential roles to play in assisting students in concretising a sense of hope. However, more research is needed to explore the role of hope amongst university students during the first-year experience. This article reports on a mixed methods study that explored hope in the context of the first-year experience. The quantitative phase of the study explored the relationships between hope, flourishing, psychological distress, and academic achievement amongst a sample of 296 first-year South African university students (mean age = 20.70, SD = 1.30, female = 63%). Statistical analyses revealed significant relationships between the constructs assessed. Students who reported high scores on hope also obtained higher academic marks compared to participants who reported lower scores on the same construct. The qualitative phase of the study explored differences inconceptions of hope between participants (N = 28, age-range 18-22) who reported high versus low scores on a quantitative measure of hope. Two qualitative themes emerged, namely the trichotomy of hope, and hope-based generalised resistance resources. The findings indicate that students who present with high levels of hope may be more inclined to pursue academic goals and experience a sense of well-being. Implications for student support are discussed, and the importance of promoting realistic hope amid the first-year experience is highlighted.
... Finally, task goals are proximal or more immediate, and are often employed as achievable benchmarks in the quest to work toward distal or peak goals. All goals within this hierarchy have been shown to play a role on human motivation (Bandura, 1997;Locke & Latham, 1994;Masuda, Kane, Shoptaugh, & Minor, 2010). ...
... Academic library employees are thinking about their top goal in terms of a broader scheme, and chunking their overarching goals into smaller, more manageable pieces. This strategy, whether the study participants realize they are utilizing it or not, aligns with goal theory, which suggests that task-oriented, or proximal goals, can be used in the process of working toward distal or even peak goals (Locke & Latham, 1994;Masuda, Kane, Shoptaugh, & Minor, 2010). ...
Full-text available
Studies indicate correlations between personal goal-setting behaviors, performance and attitude in professional roles. An online study was developed and conducted in 2016 with academic library employees to better understand the goal-setting behavior of library employees in a particular context, via setting New Year’s resolutions, which is defined as "a decision to do something or to behave in a certain manner". Results show that nearly half (49.6 percent) of all respondents set New Year’s resolutions in 2016. Goals related to health and fitness topped the list of goals that were set, followed by occupational goals. Of those who felt unclear about their purpose in life, 57 percent felt they were somewhat to very likely able to accomplish their top goals. Comparatively, 82 percent of those who had a clear sense of purpose in life felt the same.
... MDT is more of a personal characteristic approach; some people have a high achievement motive and some less so. The achievement motive can be linked with personal vision, Masuda et al. ( Masuda et al. 2010) explored the link between having a challenging and vivid personal vision and the self setting of good goals. They found that those who do have a strong vision tend to have good goals and be motivated by them. ...
Full-text available
In the economical context of tight labor markets, “the great resignation” and “the battle for talent” and within the philosophical zeitgeist based on utilitarian and existential beliefs, we explore the value of work, that is, the value experienced by the employee. We follow a cross disciplinary approach integrating both recent and not so recent insights in organizational and behavioral psychology in an economic model of cardinal utility. The extensive literature review led to the conceptually clustering of the types of needs that are addressed, material needs, social needs, and identity related needs. We distance ourselves from a needs satisfaction perspective following the economic assumption of non satiation. We develop the subsequent utility categories: material utility, social utility, and transformational utility. The theory and the random utility model created is a cross disciplinary integration effort. A survey is created and validated following DeVellis (2016) scale development method. The study confirms, via the methods of factor analysis and structural equation modeling (SEM) at least 3 and possibly 4 dimensions of job utility. Further refinement of the scale with SEM leads to the compact and robust Simple Present Job Utility Scale supporting the three factor model. Post-hoc we look for mediators and moderators in the effects of job utility on job satisfaction and turnover intention, we find that all but material utility are mediated by job satisfaction in their relationship to turnover intentions. We did not find evidence of the utility factors moderating each other's relationships to the behavioral outcomes looked at. This together with the limitations outlined from the study form the segway into our recommendations for future research. Special attention is paid to the ethical implementation of the study and the broader impact the development of models for data-driven HR practices have on society, equality, privacy and justice.
... What should be carefully considered by an implementing financial institution is the importance and complexity of the goal: clients should be assisted in setting meaningful goals as part of a vision. Indeed, studies maintain that perceiving the objective as significant will boost the commitment (Locke & Latham, 2006;Masuda, Kane, Shoptaugh, & Minor, 2010). Meanwhile, the goal chosen should be reasonably challenging. ...
Full-text available
We studied the effects of a pilot project that strengthened savings incentive mechanisms. The project was established by The Small Enterprise Foundation (SEF), a leading microfinance institution based in South Africa. The program introduced a savings stimulus in the form of a Goal Card: clients subscribing to this (non-coercive) tool were required to identify a savings goal and to commit to regular payments to reach it. The experiment had a quasi-natural approach as it was implemented by SEF in non-randomly selected locations. Difference-in-differences estimates show improved savings habits among those of the foundation’s customers who were involved in the program, compared to the counterfactual that are identified using propensity score matching. The effect of the program manifested in its second semester, suggesting a persistent change of habits but a slow accumulation of savings. We conclude that asking microcredit customers to identify a savings goal and commit to a regular savings amount to achieve it is a promising savings incentive mechanism.
... In educational research, personal vision has been linked to goal-setting theory. Students who naturally have a challenging and vivid personal vision also set more specific and challenging college goals and dedicate themselves more to their goals (Masuda et al., 2010). Under TBP, students' intentions to pursue a career could originate from their personal vision of the career goal that they want to achieve. ...
In modern software development, communication is one of the key success factors in software project development and team performance. However, software engineering (SE) students and educators may not have fully considered its significance in comparison to technical skills. The objective of the study was to determine the influence of communication self-efficacy and factors related to the theory of planned behavior (TPB) on the intention to pursue a career in software development. A survey was used to collect data from senior SE students at six universities in Thailand. The partial least squares – structural equation model (PLSSEM) was used to analyze the data. The findings indicate that attitudes toward software development careers and communication self-efficacy for software development had a positive influence on the students’ intention to pursue a career in software development. This study is the first attempt to investigate how communication self-efficacy in software development affects intention to work in a software development career. Educators can use the findings to improve curricula to foster students’ communication self-efficacy and encourage them to pursue a software development career.
... On the other hand, individuals with high self-enhancement values are more likely to seek opportunities to exercise their ambition, power, and social recognition, to obtain resources (and to have control over them) and to be achievementmotivated. These Schwartz's broad motivational goals in turn, may influence in a funneling process an aligned and more specific set of goals directly related to actions (Masuda, Kane, Shoptaugh, & Minor, 2010). For example, searching for autonomy and power may translate in specific goals such as starting up a company, working for oneself, no longer reporting to a boss, creating a prototype, developing a minimum viable product, having a first customer, and/or obtaining capital. ...
Full-text available
Although individual values have been scarcely studied in the entrepreneurship literature, existing research provides evidence that they are relevant for understanding entrepreneurial behavior. Values, however, do not necessarily influence action in a direct way. Instead, they may indirectly predict behavior via more proximal psychological processes. We build upon previous research in entrepreneurship values using Schwartz (1992) individual-values theory and Frese’s (2007) entrepreneurial action theory, and propose a theoretical model in which individual values have an indirect effect on entrepreneurial behavior through a series of four ulterior cognitive processes: Goal setting and intentions, mapping of information about the environment, planning and monitoring of the execution, and feedback processing. In doing so we integrate the theory of individual values with entrepreneurial cognition research. Despite their complementarity, these two theoretical approaches have not been studied together before. In this way, we offer new insights on the way individual values can explain entrepreneurial action. Based on these two lines of research we additionally propose a research agenda.
... What should be carefully considered by the implementing financial institution is the goal's importance and complexity: clients should be assisted in setting meaningful goals part of a vision. In fact, studies conclude that having your own vision affects your drive (Masuda, Kane, Shoptaugh, & Minor, 2010) and that perceiving the objective as significant will boost the commitment (Locke & Latham, 2006). At the same time, the goal chosen should be fairly challenging: Locke and Latham (2006) conclude that task complexity, defined as an inverse measure of the likelihood of task achievement, is related to the individual's performance: assigning tough goals may not be productive. ...
INTRODUCTION: The term 'human praxis' has been referred to in an array of theoretical frameworks: philosophy, institutional change, education, and critical theory. Broadly, human praxis denotes human agency towards personal and collective transformation in the wake of various kinds of constrictions, regardless of external interventions. If occupational therapy can understand the mechanisms of human praxis, it could be used as a potential therapeutic tool leading to the improvement of health and well-being within communities at large METHOD: Eight individuals actively living human praxis participated in semi-structured interviews. Purposive sampling, and eligibility criteria based on a description of human praxis synthesized from literature, were employed. Six researchers independently performed a manual qualitative thematic analysis of the transcribed interviews, which served as method triangulation FINDINGS: Data analysis revealed that human praxis exists as a dynamic, and recursive two-phase process, consisting of initiators (Theme I), and continuous enablers (Theme II). In addition, seven categories (constituents) emerged from each of the two themes CONCLUSION: Human praxis can be applied in the conscious facilitation of the interdependence between the various constituents such as the individual and the collective, personal and ongoing shared responsibility, and between conditions of constraint and resilience toward self-determination and growth Keywords: wound management, hand therapy, occupational therapy, International Classification of Functioning, Disability and Health.
The study aims to address the following research questions: Does Peer Collaboration-Based Learning motivate HTU students to perform better in their oral ability tests as compared with Traditional Teacher-Centered Learning? Do HTU students prefer Peer Collaboration-Based Learning to Traditional Teacher-Centered Learning in terms of the learning style in the classroom? Is there any significant difference between Peer Collaboration-Based Learning and Traditional Teacher-Centered Learning in terms of HTU students’ performance on oral communication ability tests in the two different classrooms? Data collected from a survey of HTU students at National Kaohsiung University of Hospitality and Tourism consisted of an effective sample of 100. The study employed the statistical models, including T-test, ANCOVA, and Pearson Correlation, to perform the analyses. The following are the findings: First, students became more interested in and held more positive attitude toward PCBL than those in the traditional lecture instruction in MICE courses and classroom activities. Second, PCBL had greater effects on the students’ motivation toward learning English and could be better than TTCL in terms of the enhancement of students’ positive learning motivation. Third, the overall experimental group obtained striking improvement in their oral communication in MICE activities after the PCBL, in contrast to the control group that had no effects in their English oral achievement under the traditional teaching method. The results indicate some pedagogical implications based on students’ learning preferences and teachers’ teaching approaches and skills. Peer Collaboration-Based Learning, as Cooperative Learning, can help teachers enhance students’ oral communication ability in the circle of MICE. Most studies focused on the advantages of cooperative language learning in enhancing students’ reading comprehension and writing ability inside the classroom. However, little research explored the relation between the Cooperative Learning and traditional language teaching based on the improvement of students’ listening and speaking abilities. The present study investigates the effect the Peer Collaboration-Based Learning on enhancing HTU Students' English oral communication proficiency exclusively. The finding justified the value of the benefits of Peer Collaboration-Based Learning in helping students enhance their oral communication ability and their performance in the field of MICE in Taiwan.
Full-text available
This paper presents a theory of potentially universal aspects in the content of human values. Ten types of values are distinguished by their motivational goals. The theory also postulates a structure of relations among the value types, based on the conflicts and compatibilities experienced when pursuing them. This structure permits one to relate systems of value priorities, as an integrated whole, to other variables. A new values instrument, based on the theory and suitable for cross-cultural research, is described. Evidence relevant for assessing the theory, from 97 samples in 44 countries, is summarized. Relations of this approach to Rokeach's work on values and to other theories and research on value dimensions are discussed. Application of the approach to social issues is exemplified in the domains of politics and intergroup relations.
Full-text available
This research examined free-set goals (FS goals) reported by wrestling camp participants. FS goals are goals as stated by those who are simply asked to report personal goals within a defined context. Because goal content is free to vary and is defined by the athletes themselves, it is argued that FS goals underlie self-regulation in sport. Preseason, season, and long-term FS goals reported by wrestlers were coded for difficulty and specificity. Predictors and outcomes drawn from goal theory research were related to FS goals set for the upcoming season. Prior performance experiences predicted FS season goals, and FS season goals predicted performance outcomes collected after the wrestling season. Unique to goal theory, FS goal specificity was as strongly related to performance as was FS goal difficulty. Findings are discussed in relation to athletes' self-regulation.
Full-text available
Chief executives in one national and three regional samples participated in a study of the content and structure of their organizational visions. Executives clustered in three groups distinguished by differing orientations to derived factors. Cluster membership was found to be related to the rapidity of firm change, the amount of control the executives exercised over firms, and other variables. Vision showed a multifaceted structure, with factors for vision formulation, implementation, and innovative realism being most prominent. No differences in vision were found with respect to region or firm size, but the responses of executives differed from those obtained in an earlier study of business school deans.
This article presents a framework for understanding organizational vision. “Vision” is a term frequently used by academics and practicing managers, but there has been a scarcity of clear concepts and useful tools—in short, the absence of a coherent conceptual framework. This article develops a framework that removes the fuzziness surrounding the topic of vision yet at the same time preserves the magic—the spark—that is an essential quality of vision. © 1991, The Regents of the University of California. All rights reserved.
Conference Paper
The effect of a proximal plus a distal goal was investigated relative to setting only a distal goal or urging participants to do their best. Young adults (N = 39) were paid on a piece rate basis to make toys. An analysis of variance revealed that the amount of money earned by the participants who were urged to 'do your best' was significantly greater than the amount of money earned by the participants who were assigned a distal goal. However, the amount of money earned by the participants who were assigned proximal goals, in addition to a distal goal, was significantly greater than the amount of money earned by the participants in the 'do your best' condition. The correlation between perceived self-efficacy and the amount of money earned was 0.45 (p < 0.01). Perceived self-efficacy significantly increased only for those participants in the proximal plus distal goal condition. Proximal goals, through self-efficacy and performance feedback, appear to have focused attention on task appropriate strategies. The results suggest an informational explanation of proximal goals as opposed to a motivational one through goal commitment. Implications of these findings for mentoring and training are discussed. Copyright (C) 1999 John Wiley & Sons, Ltd.
Examined the research studies cumulated in recent quantitative reviews of the relationship between goal difficulty and performance to determine how goal difficulty has been operationalized. 4 categories (assigned goal level, self-set goal level, performance improvement, and difficulty perceptions) of operationalization were discovered, and the operationalization of goal difficulty was tested as a moderator of the relationship between goal difficulty and performance
Leadership experts define organizational vision as an individual's positive vivid cognitive image of an organization, e.g., success, size, employees, strategic direction, in the future. This concept infers that different people may have varying ability to create this image. This paper describes the preliminary validation of a scale designed ro measure an individual's visioning ability. Factor analysis and tests of reliability and of content, construct, and concurrent validity suggest that this visioning ability scale is a valid and reliable measure of an individual's visioning ability.
This article presents a framework for understanding organizational vision. "Vision" is a term frequently used by academics and practicing managers, but there has been a scarcity of clear concepts and useful tools—in short, the absence of a coherent conceptual framework. This article develops a framework that removes the fuzziness surrounding the topic of vision yet at the same time preserves the magic—the spark— that is an essential quality of vision.