expectations and job search behavior among graduating
TRANSCRIPT
Retrospective Theses and Dissertations Iowa State University Capstones, Theses andDissertations
1995
Expectations and job search behavior amonggraduating university seniorsAnna Rebekah EricksonIowa State University
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Expectations and job search behavior among
graduating university seniors
by
Anna Rebekah Erickson
A Dissertation Submitted to the
Graduate Faculty in Partial Fulfillment of the
Requirements for the Degree of
DOCTOR OF PHILOSOPHY
Department: Psychology Major: Psychology
Approved:
SorWori
For the Major Department
Iowa State University Ames, Iowa
1995
Signature was redacted for privacy.
Signature was redacted for privacy.
Signature was redacted for privacy.
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ii
TABLE OF CONTENTS
Page
LIST OF TABLES iv
LIST OF FIGURES v
ACKNOWLEDGEMENTS vi
ABSTRACT viii
INTRODUCTION 1
REVIEW OF THE LITERATURE 7
The Effects of Expectations on Behavior 7
Expectations of Self 17
Locus of control 19
Self-efficacy 26
Expectations about the Job Market 32
Economic Psycholocfy 38
THE PRESENT STUDY 42
METHOD 44
Participants 44
Instruments 45
Career locus of control 45
Self-efficacy 46
Perceptions of the economy 48
Job search activity 49
RESULTS 53
Preliminary Analyses 53
Scale reliabilities 53
Correlations between scales 56
iii
Tests for collinearity 58
Variable means 59
Job search steps employed 64
Dates for engaging in job search steps 69
Cluster Analysis 72
First cluster 73
Second cluster 76
Third cluster 78
Fourth cluster 80
Fifth cluster 82
Sixth cluster 84
MANOVA 86
DISCUSSION 89
Attitudinal Differences Among Job Seekers 89
Behavioral Differences Among Job Seekers 92
Cluster Analysis Results 94
Directions for Future Research 99
REFERENCES 103
iv
LIST OF TABLES
Page
Table 1: Internal consistency reliability for scales (n=370). 53
Table 2: Pearson product moment correlations among variables (n=370). 57
Table 3: Variance inflation factors (VIFs). 58
Table 4: Means scores for all variables for entire sample (n=370). 60
Table 5: Participants' plans for Fall 1994. 61
Table 6: Variable means by Plans for Fall and Employment Status. 63
Table 7: Differences in job search steps utilized by students who had obtained job offers and those who had not (n=309). 67
Table 8: Differences in job search steps utilized by students who had accepted job offers and those who had not (n=309). 68
Table 9: Dates for initiating various job search steps (309). 69
Table 10: Differences in means between clusters on date of initiating job search and GPA. 88
V
LIST OF FIGURES
Page
Figure 1: Job search steps employed by participants planning to work full time in the fall (n=309). 65
Ficfure 2: Mean, Median, and Modal dates for initiating various job search steps measured in weeks before graduation (n=309). 70
Figure 3: Semi-partial plotted against number of clusters (n=309). 73
Figure 4: Variable means for first cluster (n=67). 74
Figure 5: Variable means for second cluster (n=63). 76
Figure 6: Variable means for third cluster (n=33). 78
Ficfure 7: Variable means for fourth cluster (n=62). 80
Figure 8: Variable means for fifth cluster (n=40). 82
Figure 9: Variable means for sixth cluster {n=35). 84
vi
ACKNOWLEDGEMENTS
As I complete this dissertation, I think about all the
people who made it possible. To those people I am eternally
grateful.
First I would like to thank my major professor, Dr. Paul
Muchinsky. I am very thankful for all that he has done for me
and for all he has taught me. His guidance throughout this
project has been invaluable to me. I am especially grateful
for his continued support across the miles, while I was in
Texas and he was in North Carolina. I can never repay you for
all you have given me.
I am also especially grateful to Dr. Gary Phye for all
his support and help. Dr. Phye made it possible for me to
complete my degree in the absence of a major professor while I
was away working. I cannot thank him enough for all he has
done.
Thank you to all the other members of my committee, Dr.
Andre, Dr. Borgen, Dr. Strahan, and Dr. Lorenz for all their
time and support throughout this project. And to Dr. Hanisch,
who has been a great help and support throughout my graduate
training.
Finally, I would like to thank my family. I could not
have come this far without the support and encouragement of my
parents, Kathryn and Wendell Erickson. I am also grateful for
the support I received from my mother-in-law, Judy Oilman. My
vii
sister Kirsten let me know that graduate school with children
is possible and that the outcome is worth the suffering.
Without her encouragement I may have given up during those
long years without sleep. And to all my family, thank you for
your support and encouragement.
Finally, I am most grateful to my husband and children.
I thank my husband, Mike, for all he has sacrificed for me to
return to and complete graduate school. His loving support
and encouragement have been invaluable. Mike, Jens, and
Krista have been incredibly patient and understanding
throughout the completion of this project. (I am sure that I
am one of the few parents who have preschool children who play
"dissertation.") I could not have done it without them.
viii
ABSTRACT
This study was designed to examine the effects of
expectations on the job search activity of university seniors.
Participants included 370 graduating seniors (194 male, 171
female) at Iowa State University. The questionnaire was
designed to measure attitudes toward job searching,
expectation about the job market, and job search activity.
Attitudes toward job searching was measured using the Career
Locus of Control Scale (Trice, Haire & Elliott, 1989); the Job
Search Self-Efficacy portion of the Outplacement Needs
Inventory (Kanfer & Hulin, 1985); and the Job Seeking
Confidence scale developed by the Institute for Social
Research at the University of Michigan (van Ryn & Vinokur,
1992). Expectations about the job market were measured with
the Employment Outlook segment of the Career Exploration
Survey (Stumpf, Colarelli & Hartman, 1983); and the Business
Conditions portion of the Survey of Consumers. Job search
activity was measured by asking students to indicate the onset
of job search activity, the number of job search activities
undertaken, the frequency of job search and the amount of time
spent looking for a job. Cluster analysis was used to
divide students into 6 groups based upon attitudes toward the
job search and expectations about the job market. Comparisons
were made among the 6 resulting clusters on job search
activities and GPA. Manova was performed to determining
whether the clusters differed in job search activity or
ix
ability (GPA). Results revealed that optimistic of students
began their job search earlier than pessimistic students
(p<.05) and that students with greater job seeking confidence
also tended to report higher GPAs (p<.05).
1
INTRODUCTION
The U.S. Department of Education, National Center for
Education Statistics estimates that over one million people
received bachelors degrees during the 1993-1994 academic year
(U.S. Department of Education, 1993). Although many of tbese
students had jobs upon graduation, many did not. Still others
had not even begun to look for a job until after graduation.
What determines whether a new graduate will find a job?
Qualifications such as academic performance, university
activities, employment status before graduation, and
impressive job references certainly play an important role in
determining who gets the best jobs. For example, Marshall
(1985) compared recent college graduates who had either been
successful or unsuccessful in finding a job 90 days after
graduation. She found that successful job applicants were
more likely to characterize their job references as
"impressive", were more likely to have been employed before
graduating from college and had an average grade point average
of B or better in business courses.
Other researchers have also found evidence that academic
performance influences which students will receive job offers.
For example, Campion (1978) found academic performance to be
influential in the job interview. Campion's study examined
the effects of various applicant characteristics, such as
academic major, extra curricular activities, and grade point
average, on interview impressions. Multiple regression of
2
interviewers' evaluations with applicant predictor variables
revealed that undergraduate GPA had the greatest impact of all
the predictor variables on over-all general impression and
personal liking aspects of interviewers' ratings.
Undergraduate GPA, together with membership in fraternity or
sorority, also influenced interviewers judgments of chances of
further consideration. Keenan (1979) also found academic
performance to be related to interview success, with those
with higher GPAs being more likely to succeed in the
interview.
Work related experience before graduation has also been
shown to be related to success in the job search. For
example, Keenan and Scott (1985) reported that students
holding part time jobs related to their field of study were
more likely to be called back for a second interview and were
more likely to receive a job offer following an interview,
than those without such experience. Carroll (1966) found that
business studies graduates interviewing for jobs were more
likely to be successful if they had had experience working in
an office setting.
Clearly, qualifications are an important influence in
finding a job. However, even the most qualified individuals
will not find jobs if they do not look for a job. Campus
placement counselors, in accord with the scores of job search
books published annually, often put little emphasis on
qualifications, advising job seekers that choice jobs are
3
bestowed upon those with the best job seeking skills rather
than to the most qualified individuals.
Research does support the position that the degree and
intensity of job seeking activities are important and that the
way one looks for a job may be as important as one's
qualifications for that job. For example, Wielgosz and
Carpenter (1987) reported significant differences in job
search duration depending upon the job search methods
employed. Their research demonstrated that among the
unemployed, individuals who used multiple job search methods
found jobs much more quickly than those who relied on only one
method. According to a study by Jones (1985), the
relationship between qualifications and quality of job
obtained may not be a direct relationship, but one that is
mediated by job search activities. This study revealed that
poorly qualified individuals actually made fewer applications
and displayed less adequate job seeking skills than their
better qualified classmates. Kanfer and Hulin (1985) also
found that job seeking skills play an important role in
determining who will become reemployed the soonest. Their
study of 35 former hospital employees who had been laid off,
revealed that reemployed individuals had engaged in a greater
number of search behaviors than those who remained unemployed.
The reemployed workers also possessed significantly more
confidence in their ability to find a job. Still other
research has shown that training unemployed adults in job
4
seeking skills can result in higher paying and more satisfying
jobs (Caplan, Vinokur, Price, & Van Ryn, 1989).
A number of researchers have reported that formal job
seeking methods (such as use of a college placement office,
private placement agency or executive search firm, state
employment services, and advertisements in newspapers or trade
journals) are more effective than informal sources (such as
personal contacts, and referrals from friends and relatives)
in helping students find employment (Allen & Keaveny, 1980).
Other research has indicated that informal methods are
superior (Granovetter, 1974; McKersie & Ullman, 1966; Wielgosz
& Carpenter, 1987) or at least just as good (Reid, 1972) as
formal sources. It has been suggested that differences
between studies may be the result of economic conditions
(Allen & Keaveny, 1980). When jobs are more plentiful than
qualified applicants, employers are more likely to make use of
formal channels such as campus recruiting. During these times
use of formal channels would result in shorter job search
duration. However, when applicants for jobs far out number
positions available, employers do not make use of formal
channels as heavily, causing informal channels to be more
efficient for job seekers.
Preparation for the job search is also important. Keenan
and Scott (1985) demonstrated that preparing for an interview
can impact its outcome. These researchers found that the
length of time spent reading company literature prior to an
5
interview was positively correlated with the number of second
interviews obtained and the number of job offers received.
Carroll (1966) reported the physical appearance of an
applicant during an initial interview was related to success
during the interview. Scheider and Stevens (1971) found that
individuals with specific and realistic job goals obtained
jobs more quickly than those whose goals were vague or
unrealistic.
The notion that one should put the same effort and
careful planning into finding a job that one has put into
training for that job should not surprise students. Yet
although most students would probably like to find a good job,
there are great differences in the enthusiasm with which the
task of finding a job is undertaken. Almost half of those
receiving bachelors degrees in 1991 had already begun their
job search six months before graduation (Waldrop, 1992), yet
there appears to be a great deal of variation in how
diligently this search is conducted.
What individual differences might contribute to the
variation in job search activities? Researchers exploring job
search behaviors, usually focusing on the unemployed, have
isolated a number of individual factors related to the
variability in job seeking behaviors. These include locus of
control (Friedrich, 1987; Plumly & Oliver, 1987; Trice, Haire,
& Elliott, 1989), self-esteem (Baik, Hosseini, & Priesmeyer,
1989; Ellis & Taylor, 1983), perceived social support
6
(Mallinckrodt & Fretz, 1988; Vinokur & Caplan, 1987),
attitudes toward job seeking (Jones, 1985; Latham, 1987; Ullah
& Banks, 1985; Vinokur & Caplan, 1987), attitudes toward
employment and work (Baik, Hosseini, & Priesmeyer, 1989;
Feather & O'Brien, 1987; Stumpf & Lockhart, 1987; Ullah &
Banks, 1985), length of time unemployed and number of
unsuccessful job applications (Baik, Hosseini, & Priesmeyer,
1989; Feather & O'Brien, 1987).
The present study addresses the influence of expectations
on the job search process. The expectations examined will
include expectations regarding the economy and the number of
jobs available as well as expectations regarding the ability
to obtain the jobs that are available.
7
REVIEW OF THE LITERATURE
The Effects of Expectations on Behavior
A number of theorists have proposed that expectations
influence both motivation and behavior. One of the earliest
to recognize the importance of expectations was Tolman (1932)
as he introduced a cognitive component to theories of
learning. In contrast to the behavioristic theories of
learning which prevailed at the time, Tolman proposed that
both people and animals have knowledge of goals, and
expectations regarding the outcomes of their behavior (Tolman,
1932). According to Tolman, expectations involve knowledge
about the relationships between and among stimuli and
responses. These expectations may be in response to stimuli
which were presented at some time in the past, stimuli which
are currently present or stimuli which are anticipated.
Lewin (1938), like Tolman (1932), described motivation in
terms of cognitive choices among alternatives, emphasizing the
role of individual aspirations, expectations, and affect.
Lewin agreed with the behaviorists that a person is a function
of his or her environment (P = f(E)). But he also recognized
that the environment is perceived differently by different
people and therefore the environment is also a function of the
person (E = f(P)). According to Lewin, behavior results from
an interaction between an individual and his or her
environment (B = f(P,E)). Therefore an individual's
expectations will heavily influence his or her perceptions.
8
The ideas of Tolman and Lewin laid the groundwork for a
number of theories of motivation which emphasized the roles of
expectancies and valences in determining behavior. Expectancy
theories which followed include those of Adams, Atkinson,
Edwards, Locke, Peak, and Rotter (Lawler, 1971; Weiss, 1990) .
Vroom (1964) was the first to apply these concepts
specifically to motivation toward work behavior (Lawler, 1971;
Mitchell, 1982; Muchinsky, 1993).
In his book introducing his theory of work motivation,
Vroom (1964) expressed his frustration with industrial
psychology's lack of integration of theories from other areas
of psychology and conveyed his belief in the general need for
formal theory in the field of industrial psychology:
In focusing on the motivational aspects of the
relationship between men and their work, the industrial
psychologist should be able to make use of and contribute
to the development of theories of
behavior...Unfortunately it does not appear that this
potential is being realized (Vroom, 1964, p. 4),
In introducing expectancy theory to the field of
industrial psychology, Vroom's intent was to present a theory
which integrated existing knowledge in the fields of work and
motivation. This theory was intended to explain not only
behavior in the work-place, but behavior in general. "We also
assume that there is lawfulness in the behavior of individuals
which transcends the boundaries of applied fields. It is
9
exceedingly unlikely that the behavior of persons in work
situations is governed by processes that are basically
different from behavior in other types of situations."
(Vroom, 1964, p.5-6).
According to Vroom's expectancy theory, motivation toward
an action and choices among alternatives are influenced by
various forces. The strength of these forces is determined by
three elements-, valence, expectancies, and instrumentality.
Valence is the anticipated satisfaction from the various
possible outcomes; this element is related to, but not the
same as an individual's values. Expectancies are beliefs
about the likelihood that a specific outcome will result from
a particular action. Instrumentality is an outcome-outcome
association related to whether an individual believes that a
secondary outcome will follow from the first outcome. For
example, an employer may offer some incentive for performance,
such as a pay increase or promotion. In this illustration, an
individual's expectancies would refer to his or her belief
that an increase in effort will lead to better performance.
Instrumentality would refer to the belief that better
performance will lead to a raise in pay, a promotion or
feelings of accomplishment. Valence would refer to the belief
that each specific outcome (i.e., pay, promotion, feelings of
accomplishment) would be satisfying to the individual, with
each outcome manifesting a different level of valence
depending upon the individual's values.
10
According to Vroom's theory, outcomes or incentives can
only act as performance motivators to the extent that the
individual values the proposed outcomes and perceives that
their effort will lead to those outcomes. For example, an
individual may desire to obtain a pay raise, but if that
individual does not believe an increase in effort on the job
will lead to that pay raise, motivation to perform the job
will not increase. Expectations are therefore important to
motivational force. An outcome can only work as a motivator
to the extent the individual expects effort will lead to
obtaining that outcome.
Vroom introduced expectancy theory as a model to explain
both occupational choice and work motivation, advocating
applications to both vocational and industrial psychology
(Vroom, 1964). The theory has found general support from the
numerous studies which have been conducted, especially in its
applications to predicting job or occupational choice (Kanfer,
1990; Mitchell, 1982). For example, Brooks and Betz (1990)
found that the interaction between expectancy and valence
predicted occupational choice among college students, and that
expectancy alone was as good a predictor as the product.
Arnold (1981) also found support for the interaction of
expectancy and valence predicting motivational force related
to job outcomes and job preference among undergraduates. Teas
(1981) found strong support for Vroom's traditional valence
model in predicting job preference and anticipated
11
satisfaction. Muchinsky and Taylor (1976) tested the
effectiveness of Vroom's model for occupational preference.
Using a within-subjects analysis, these researchers found
support for the application of Vroom's model to questions of
occupational choice.
Because Muchinsky and Taylor used within-subjects
analysis, they did not compare subjects with one another.
Preferences for different occupations were compared for each
person. In a within-subjects analysis, each individual serves
as a unit of analysis. Between-subjects analyses make
comparisons across individuals which vary on some independent
variable. Overall, the use of expectancy-theory to predict
between-subjects differences in effort or performance has not
been as successful as its use in making within-subjects
predictions (Mitchell, 1982; Schwab, Olian-Gottlieb, &
Heneman, 1979). For example, expectancy theory has not been
successful in predicting withdrawal behavior such as turnover
as a between-subjects variable (Birkenback & Van der Merwe,
1983; Mitra & Bhattacharyya 1983), but has been successful in
predicting within-subjects preference for retirement or
continued employment (Eran & Jacobson, 1976). Malloch and
Michael (1981) were able to predict academic performance by
examining ability (as determined by ACT scores) and
expectancy. However, valence and instrumentality constructs
did not contribute to the prediction of academic performance.
12
Use of Vroom's expectancy theory to predict effort on the
job has found varying degrees of empirical support. Orpen
(1976) found that valence for pay was more highly associated
with job performance among employees who believe that pay and
performance are highly related (high instrumentality) than
among those who perceive a weak relationship between pay and
performance (low instrumentality). Oliver (1974) found that
valence and instrumentality perceptions related to incentive
outcomes were strongly related to productivity among salesmen.
Arvey and Neel (1974) found that employee expectancies
regarding whether perfomance would lead to rewards interacted
with supervisory style to successfully predict performance
levels among engineers.
Mitchell (1974) reviewed 21 studies attempting to predict
job effort using expectancy theory, either as proposed by
Vroom or as some variation of Vroom's theory. All but two of
these studies reported some support for the theory's use in
predicting effort on the job, although the relationships were
not as strong as those found when using expectancy theories to
predict attitude or occupational choice. It may be worth
noting that Vroom's expectancy theory seems to be more
successful in predicting self reported effort than in
predicting objective or observer ratings of effort (Mitchell,
1974, 1982; Schwab, Olian-Gottlieb, & Heneman, 1979). For
example, expectancy theory has successfully predicted self
ratings of effort for work performed by engineers (Kopelman &
13
Thompson, 1976) and academic effort among college students
(Muchinsky, 1977) .
Although Vroom's theory is the best know expectancy
theory within the fields of industrial and organizational
psychology, it is only one of a large family of theories of
human motivation which recognize the influence of expectations
and values on behavior (Lawler,1971; Feather, 1982). These
basic concepts have been also utilized in theories of
Achievement Motivation (Atkinson, 1957), Social Learning
(Rotter, 1954), and Attribution Theory (Weiner, 1982).
For example, Rotter (1954) developed his Social Learning
Theory in an attempt to integrate reinforcement theories and
cognitive theories of behavior (Rotter, 1982) . According to
Rotter's social learning theory, the relationship between
reinforcement and behavior is mediated by expectancy of the
occurrence of reinforcement in a specific situation and the
value of that reinforcement in the situation. These
expectancies are based in part upon past learning. Social
learning theory takes into account that the behavior varies as
the situation does but also that there is transituational
generality in behavior. "Expectancies in each situation are
determined not only by specific experiences in that situation,
but also to some varying extent, by experiences in other
situations that the individual perceives as similar" (Rotter,
1982, p. 243) . An interaction between the person and his or
her environment creates explicit and implicit cues.
14
establishing what Rotter called a psychological situation.
Expectancies for behavior-reinforcement sequences and for
reinforcement-reinforcement sequences are determined by these
cues. Reinforcements can act to strengthen expectancies that
a particular behavior will be followed by reinforcement in the
future.
Expectations regarding the probability of reinforcement
are also important in McClelland and Atkinson's Theory of
Achievement Motivation (Atkinson, 1957, 1964; McClelland,
Atkinson, Clark, & Lowell, 1953). According to the theory, an
individual's motivation to engage in a specific behavior is
determined by (l) the person's motive to achieve success, (2)
the person's beliefs about the probability of success, and (3)
the incentive value of success for any particular task. These
three variables combine in a multiplicative relationship to
influence the tendency to achieve success (T^ = M^ X Pg X 1^) .
This theory assumes that the motive to achieve success is a
personality trait which remains fairly stable across
situations. It also assumes that there is a direct, negative
relationship between the individual's subjective beliefs about
the probability of success for a given task and the incentive
value of success for that task (such that = 1 - Pg) . In
other words, the lower the probability of success, the more
valuable success becomes to the individual.
Because of the relationship between the variables, the
theory of achievement motivation predicts that people with a
15
high need for achievement (motive to achieve success) will
prefer tasks of moderate difficulty, since this would maximize
the Ig X PB relationship, which in turn would maximize the
tendency to achieve success (since = Mg X X Ig) . However,
certain individuals may also possess a motive to avoid
failure, which can cause these people to avoid taking action,
choose very easy or very difficult alternatives, or purposely
engage in activities which would inhibit their performance
(Atkinson, 1964; Berglas & Jones, 1978; Horner, 1972; Mahone,
1960) .
Feather (1982, 1992) developed his expectancy-value
theory in an attempt to delineate the relationship betweer
expectations, values and actions. According to Feather an
individual's values and needs generate valences toward
specific events and potential outcomes. Valences, according
to Feather, are the affective meanings associated with a
situation. Synonymous with the terminology used by Lewin and
Vroom, positive valence represents a general subjective
attractiveness of an event or object, while negative valence
denotes adversiveness toward an event or object. Valences
interact with expectations in determining or influencing
actions.
This expectancy-value theory as described by Feather
(1982, 1992) has been successful applied to the prediction of
job-seeking behaviors. Feather and O'Brien (1987) tested this
expectancy-value theory's capacity to explain individual
16
differences in job seeking behavior among 320 young unemployed
men and women in Australia. These researchers measured
expectation of finding a job with a factor they called
'control-optimism'. Their measure of 'control-optimism' was
generated via factor analysis of a number of job-seeking and
unemployment related items. It included items measuring
unemployment helplessness ("How helpless do you feel about
your unemployment?"), nob confidence ("How confident are you
about finding the job you really want in the near future?" and
"How confident are you about finding any kind of job at all in
the near future?"), stability of unemployment ("In the future,
if your unemployment continues, will the cause of unemployment
still be present?") and personal uncontrollability of
unemployment ("Can you do anything to change the cause of your
unemployment?"). Job valence was measured through another
scale created through the same factor analysis. This scale
included items measuring iob need ("How much do you feel you
need a job?"), unemployment disappointment ("When you think
about being unemployed, or the possibility of being
unemployed, how does it make you feel?"), and unemployment
depression ("How depressed do you feel about your
unemployment?").
Job seeking behavior was measured with a single item
asking "How frequently do you look for a job?" for which
respondents were asked to choose 'not looking for a job',
'when I feel like it', 'monthly', 'every couple days', or
17
'daily'. Conducting a path analysis, these researchers found
that job valence was related to job seeking behavior, but
control-optimism was not. Control-optimism tended to be more
closely related to the length of time unemployed. The authors
suggest that the failure to obtain the hypothesized relation
between control-optimism and job-seeking behavior may have
been due to deficiency in the dependent variable, including
the fact that the dependent variable was measured using a
single item. The authors also refer to a possible inadequacy
in their measure of expectation, comprising measures of
optimism and control.
Expectations of Self
One type of expectation which strongly influences our
behavior involves our expectations about ourselves. Most
cognitive based theories in psychology recognize that the way
we view ourselves effects the way we behave. Some of the
strongest assertions regarding the effects of self-
expectations on behavior are made by theorist in the social
learning theory tradition. Social learning theorists such as
Bandura (1977b) and Rotter (1954) added a cognitive component
to traditional behavioristic, stimulus-response theories of
learning. These theorists emphasized the importance of
intervening cognitive variables such as expectations in
explaining how reinforcers may or may not influence our
behavior.
18
One of the fundamental principles of social learning
theory is that "cognitive processes play a role in the
acquisition and retention of new behavior patterns" (Bandura,
1977a, p. 192), According to these theories, cognitive
components, such as expectations and values may influence or
modify the effects of reinforcement on behavior. With
concepts and terminology similar to Vroom's (1964) expectancy
theory, Rotter (1975) explains that social learning theory
specifies three major determinants of behavior potential: (1)
the expectancy for reinforcement to follow behavior; (2) the
value of the reinforcement; and (3) the psychological
situation. Thus, our expectations for ourselves, our
abilities, and our control over our environment have
substantial impact on the behaviors and activities we choose
to perform.
Two important constructs dealing with an individual's
expectations for reinforcement have emerged from the social
learning theories of behavior. Locus of control deals with
the person's beliefs about the causal nature of the behavior-
outcome sequence (Rotter, 1966); while self-efficacy refers to
an individual's beliefs about whether he or she is able to
perform the behaviors required to produce a reinforcing
outcome (Bandura, 1977b). Each of these constructs has been
shown to be related to job search activities.
19
Locus of control
Julian Rotter first introduced the concept of locus of
control in the tnid-1950's, within the framework of social
learning theory. Behavioral theories of learning suggest that
our actions are effected by our past history of reinforcement.
Behaviors which have been reinforced are more likely to be
performed again; while behaviors which have not been
reinforced or have been punished, will decrease in frequency.
However, Rotter (1966, 1982) proposed that the effects of
reinforcement on learning are mediated by the individual's
beliefs about the causal relationship between his or her
actions and the outcome of those actions. If a person
perceives that reinforcement was caused by something he or she
did, learning will result and the individual will be more
likely to perform the behavior again in the future. However,
if the individual believes that the outcome was caused by
factors out of his or her control, learning (in the forro of
changed behavior) is less likely to occur.
In its simplest form, our basic hypothesis is that
if a person perceives a reinforcement as contingent
upon his own behavior, then the occurrence of either
a positive or negative reinforcement will strengthen
or weaken potential for that behavior to recur in
the same or similar situation. If he sees the
reinforcement as being outside his own control or
not contingent, that is depending upon chance, fate,
20
powerful others, or unpredictable, then the
preceding behavior is less likely to be strengthened
or weakened. Not only will there be a difference of
degree but also a difference, in some instances, in
the nature of the function as the result of a series
of trials (Rotter, 1966, p. 5) .
Therefore, the process of learning differs depending upon
whether an individual perceives a task to be primarily
influenced by skill or chance.
Rotter and his colleagues did demonstrate that learning
under skill conditions differed from learning under chance
conditions. For example, past successes had greater effect on
subjects' expectancies for future success when they were told
that success depended upon their skill (Phares, 1957).
Subjects were also more persistent at a task they had
previously been consistently successful performing if they had
been told the success was based upon 'skill' rather than
'chance' (James & Rotter, 1958; Rotter, Liverant, & Crowne,
1961) .
Rotter hypothesized that an individual's history of
reinforcement may influence the degree to which he or she
attributes reinforcements to his or her own actions (Rotter,
1966, 1982). This history of reinforcement may therefore lead
to a generalized expectation that events are either within
control of or outside the control of the individual. This
personality variable was labeled 'locus of control'. People
21
with an internal locus of control exhibited a tendency to
believe that outcomes were caused by their own efforts,
behavior, or due to relatively permanent individual
characteristics. People with an external locus of control
tended to view events as having been caused by factors out of
their control, such as fate, luck, chance, caused by powerful
others, or due factors to complex to be predictable.
In 1966 Rotter published in Psychological Monographs the
I-E scale, a test measuring locus of control, along with
reliability, discriminant validity and normative data for the
test. This instrument contained 29 forced choice items and
was a revision of a 60-item scale developed by Phares (1957).
Rotter anticipated that most individuals would fall in the
middle of the Internal-External continuum when scoring the
scale, because "individuals at both extremes of the internal
versus external control of reinforcement dimension are
essentially unrealistic" (Rotter, 1966, p. 4). This
expectation was confirmed, with scores for both male and
female students being approximately normally distributed with
means of 8.15 (males) and 8.42 (females) on a scale from 0 to
20. In addition. Rotter reported test-retest and internal
consistency reliability for the I-E scale as calculated for a
number of samples rxx=-49 to r^=.83, with most estimates
approximating r^=.70.
Rotter also reported validity data for his scale and the
locus of control construct. Studies demonstrated that "the
22
behavior of externals differed from that of internals in the
same way that the overall population differed under chance
instructions as compared with skill instructions" (Rotter,
1966, p. 19 referring to James, 1957) .
In introducing locus of control. Rotter (1975) proposed
that the variable may be specific to a situation or
generalized across situations. Experience with a specific
type of situation creates expectations about locus of control
for that type of situation. The more novel a situation is to
an individual, the more important that person's generalized
locus of control will be in influencing behavior.
A number of studies have demonstrated that experience in
the job search process influences locus of control. For
example, Baubion, Megemon and Sellinger (1989) found that
among unemployed workers in Prance, locus of control became
more external as length of unemployment increased. In
addition, the unemployed became less confident and less
hopeful about future employment, and decreased their
receptivity to employment information as unemployment
continued.
Mallinckrodt and Fretz (1988) measured locus of control
as one of several stress symptoms among unemployed
professionals over the age of 40. These researchers found
that stressors including financial concerns and increasing
length of unemployment were related to a decrease self-esteem,
a more external locus of control and a decrease in job seeking
23
behaviors. However, these researchers also found that access
to a social support system decreased the effects of the
stressors on locus control, self-esteem, and job seeking
activities.
Social learning theory as outlined by Rotter asserts that
our experience influences locus of control, which in turn
affects our future behavior. So this theory would predict
that just as level of success in the job search influences
locus of control, locus of control influences the job search.
Research tends to support this hypothesis. For example,
Baubion, Megemon, and Bellinger's (1989) study revealed that
as length of unemployment increased, not only did locus of
control become more external, the study participants also
decreased their receptivity to employment information. Plumly
and Oliver (1987) suggest that internally and externally
oriented locus of control individuals may differ in their job
searching behavior depending upon rate of unemployment and job
market conditions.
Friedrich (1987) studied the relationships between locus
of control and job search activities in undergraduates seeking
summer employment. His findings indicated that individuals
with external locus of control as evidenced by scores on the
Vocational Locus of Control Scale, sought less information
regarding job alternatives, generated fewer alternatives,
considered fewer evaluative criteria, and engaged in less
24
advanced planning than those with an internal locus of
control.
A study by Holmes and Werbel (1992) presents further
evidence of the importance of locus of control in the job
search process. Their study compared subjects who had
obtained employment within three months of their job loss to
those who remained unemployed. Those who had found a job were
more "internal" in locus of control, had greater self-
efficacy, and possessed better problem-solving skills than
those who had not.
Rotter's social learning theory with its locus of control
construct is similar to the attribution theory of Weiner and
his colleagues (Weiner, 1979; Weiner, Russell, & Lerman,
1978). Weiner's theory asserts that people explain success
and failure experiences using three dimensions. The
individual may describe the outcome of a situation as being
due to skill or effort, in which case the individual has made
an internal attribution. Alternatively, the individual may
attribute the outcome to external forces, such as luck, task
difficulty, etc. This internal versus external dimension is
what Weiner termed the Locus Dimension. The individual may
also evaluate the stability of the cause of the outcome,
making attributions which are categorized as either stable,
such as ability or task difficulty, or unstable, such as luck
and effort. Weiner called this the Stability Dimension.
Finally, some factors are directly under the control of the
25
individual, such as effort. Other factors are quite
uncontrollable, such as ability and luck. This is what Weiner
labeled the Controllability Dimension.
Like Rotter's theory, these attributions are learned and
based upon experience (success or failure). According to
Weiner (1979), after an individual experiences success or
failure, he or she will make an appraisal of the situation in
his or her mind. Locus has the greatest impact on an
individual's affect or emotional reaction to a situation;
therefore we tend to attribute failure to external causes to
protect self-esteem. Stability affects one's behavior by
changing one's expectations of future success or failure.
Controllability is assumed to have an impact on both emotional
and behavioral reactions. People who attribute performance to
controllable factors tend to experience more positive
emotional reactions and are more optimistic in their
expectations for future performance.
Kulik and Rowland (1989) investigated undergraduates
during their job search to determine the effect of success or
failure on their beliefs about the cause of the success or
failure of their job search strategy. These researchers
reported differences in locus of control and stability of
influential variables between successful and unsuccessful job
searchers, Students who described their search as a success
tended to perceive stable and internal factors as influencing
their job search outcomes. Subjects who viewed their job
26
search as a failure deemphasize internal and stable factors,
and attributed the outcomes to external factors beyond their
control. Basing their study on Weiner's attribution theory,
Kulik and Rowland submit that deemphasizing internal and
stable attributions allows failing job seekers to protect
their self-esteem and retain optimism for the future.
Like locus of control, causal attributions can influence
future behavior. For example, when Sherman, Skove, Hervitz,
and Stock (1981) asked subjects to describe the cause of a
successful or unsuccessful future outcome, people who had
explained a successful outcome had greater expectations for
success and exhibited better performance than those who had
explained failure.
Self-efficacy
Another expectation which may influence the job search is
self-efficacy. Self-efficacy is the belief in one's ability
to successfully perform a specific task. It refers to an
expectation for performance or confidence in one's own ability
to engage in certain behaviors. Bandura introduced self-
efficacy within the framework of his version of social
learning theory. According to Bandura (1977b) theories
proposing drives or other spurious internal causes of behavior
have proven to be inadequate to explain complex human
behavior. However, in an effort to overcome these
inadequacies, radical behaviorism neglected, and perhaps even
27
actively avoided, addressing cognitive influences on behavior.
Bandura did not deny that reinforcement and response
consequences influence behavior. However, he suggested that
this influence is much more likely to be because of cognitive
factors such as the information conveyed through reinforcement
or increases in motivation, than through the automatic
mechanical reinforcement suggested by the radical
behaviorists. In addition, Bandura emphasized the importance
of modeling and symbolic influences in learning.
Expectations play a prominent and influential role in
Bandura's social learning theory. Bandura described two types
of expectations which he believed influenced behavior. He
defined efficacy expectations as "a person's estimate that a
given behavior will lead to certain outcomes" (Bandura, 1977b,
p. 79) and outcome expectations as "the conviction that one
can successfully execute the behavior required to produce the
outcomes. Outcome and efficacy expectations are
differentiated because individuals can come to believe that a
particular course of action will produce certain outcomes, but
question whether they can perform those actions" (Bandura,
1977b, p.79). Although Bandura acknowledged the influence of
outcome expectations, he believed that efficacy expectations
had much greater influence on behavior.
According to Bandura, personal, behavioral, and
environmental determinants interact in a reciprocal fashion,
so that expectations influence behavior and the outcomes of
28
behavior alter expectations. Expectations are influenced most
by performance accomplishments, with success raising
expectations and failures lowering expectations. Expectations
may also be influenced by live and symbolic modeling, verbal
persuasion, and emotional arousal, although the effects of
these are generally less permanent and less influential than
those gained through performance accomplishments.
Once efficacy expectations have been established through
learning, they may generalize from the original learning
situation and influence future behaviors. These efficacy
expectations may then influence a wide range of behavior
including the choice to engage in certain activities and
persistence at a task. "Efficacy expectations determine how
much effort people will expend and how long they will persist
in the face of obstacles and aversive experiences" (Bandura,
1977b, p. 80). "In this conceptual system, expectations of
personal mastery affect both initiation and persistence of
coping behavior" (Bandura, 1977a, p. 193).
Self-efficacy expectations seem to play an important role
in career development. For example, an individual's
confidence in his or her ability to perform tasks associated
with specific occupations has been found to influence career
choice (e.g., Lapan & Jingeleski, 1992; Rooney & Opisow,
1992) . This influence results when self-efficacy restricts
the perceived range of career options because of beliefs about
one's ability to perform the tasks necessary for the job (Betz
29
& Hackett, 1981; Lent, Brown, & Larkin, 1987; Rotberg, Brown,
Sc. Ware, 1987), and seems to be mediated by interests (Lent,
Larkin, & Brown, 1989). The influence of self-efficacy on
career choice is especially salient when examining confidence
in one's math ability and the decision to enter careers
requiring math or science (Hackett, 1985; Hackett & Betz,
1981, 1989; Lent, Larkin & Brown, 1989; Post, Stewart & Smith,
1991). Career related self-efficacy has been suggested as a
reason for the persistence of a gender gap related to the
number of women entering non-traditional careers (Betz &
Hackett, 1981, 1983; Lapan, Boggs, & Morrill, 1989; Lips,
1992). For example, Betz and Hackett (1981) found that female
college students possessed higher self-efficacy for their
performance in occupations which are traditionally held by
women than for their performance in male-dominated careers.
Male college students displayed equal levels of self-efficacy
for male and female dominated occupations. These researchers
also report "that self-efficacy expectations were related to
both the type and number of occupations considered and to
expressed interest in traditional and nontraditional
occupations" (p. 399).
Self-efficacy has also been found to be related to the
ability to make a decision about a career. Taylor and Betz
(1983) introduced the concept of Career Decision-Making Self-
Efficacy suggesting that some individuals fail to decide on a
career because they do not believe they are able to make that
30
decision. These researchers found that high levels of
vocational indecision are related to low levels of career
decision-making self-efficacy among university students.
Self-efficacy was especially related to components of
indecision related to lack of structure and confidence with
respect to career decisions. Taylor and Popma (1990),
confirming the findings of Taylor and Betz (1983), reported
that career decision-making self-efficacy was negatively
related to vocational indecision and locus of control among
college students. Matsui & Onglatto (1992) found that career
decision-making self-efficacy expectations were negatively
related to career choice anxiety among Japanese high school
girls.
As Bandura proposed, self-efficacy is also related to
achievement and persistence in career related behaviors.
Lent, Brown, and Larkin (1984) found that college students
with high levels of academic self-efficacy expectations were
more successful and persistent preparing for science and
engineering careers. Several researchers have also found that
choice and persistence in major among those studying math,
science, and engineering are related to self-efficacy (Janis &
Mann, 1977; Lent, Brown, & Larkin, 1984, 1986; Betz & Hackett,
1983) . In addition, self-efficacy has been shown to be
related to job performance for occupations for which
persistence would seem to be important including sales
31
(Barling & Beattie, 1983; Lee & Gillen, (1989) and telephone
solicitation (Lee, 1988).
Eden and Aviram (1993) demonstrated the influence of
self-efficacy on job search behavior in their study of 66
unemployed persons in Israel. These researchers demonstrated
that enrolling unemployed individuals in a self-efficacy
training session increased the general self-efficacy of those
individuals whose pre-treatment self-efficacy was low. These
researchers also reported that those with higher general self-
efficacy engaged in more job search behaviors and that those
who engaged in greater job search activities were more likely
to find a job.
Holmes and Werbel (1992) found differences between
unemployed and reemployed workers three months after job loss
in self-efficacy and six other coping resources. These
researchers reported that individuals who became reemployed
within three months of job loss had greater self-efficacy than
those who remained unemployed. Stumpf, Austin, and Hartman
(1984) measured self-efficacy as one of three variables (along
with perceived past performance and verbal persuasion) they
termed "interview readiness". Their longitudinal study
involving graduate business students revealed that the three
interview readiness variables were related to degree of career
exploration, interview performance ratings and interview
outcomes (including call-back interviews and job offers).
Wooten (1991) found that self-efficacy influenced job
32
acceptance behavior among undergraduates participating in mock
job interviews. According to the study results, individuals
with high self-efficacy made job acceptance decisions based
upon personal adjustment, while those with low self-efficacy
made decisions based upon skill assessment and autonomy.
Blustein (1989) found that self-efficacy and overall goal-
directedness was associated with career exploratory behavior
among college students.
Expectations about the Job Market
When considering the effects of expectations on behavior,
expectations about conditions outside the individual may be as
important as expectations about one's self. For job search
behavior the most evident of these external expectations
involves information about the job market, economic
conditions, and expectations for finding a job.
Economic variables have been demonstrated to influence
job seeking behavior among employed individuals in the form of
turnover. Economic theories emphasize rate of unemployment as
an important determinant of turnover. Muchinsky and Morrow
(1980) proposed a model of turnover accounting for individual
and work factors as well as economic variables. These authors
hypothesized that the effects of work-related and personal
factors such as job satisfaction, job autonomy and
responsibility, vocational interest and length of service, are
contingent upon level of economic factors such as unemployment
33
rate and alternative employment opportunity. During times of
high unemployment and few alternative job opportunities,
individual's who are not happy with their job will be less
likely to quit than during times of low unemployment and
plentiful job opportunities.
In their meta-analysis of the literature examining the
job satisfaction-turnover relationship, Carsten and Spector
(1987) found support for the Muchinsky & Morrow model. These
researchers found negative correlations between unemployment
rates for dates in which the studies were conducted and the
reported size of the relationship between satisfaction and
turnover and between intention to quit and turnover. It seems
economic variables do influence the choice to leave an
organization and engage in job search activities. Employees
are much more reluctant to enter a job market in which there
are few jobs available.
A study conducted by Dayton (1981) shows that job seekers
tend to attribute their lack of success in the job market to
economic factors. Dayton presented 35 job-seeking activities
and 35 barriers/aids, asking participants to indicate which
job seeking activities they had tried and which barriers or
aids they found relevant to their experience. Participants
indicated that the state of the economy was the greatest
barrier to finding a job, with 20% of all participants
indicating that the state of the economy served as a barrier
to their job search efforts. Also included in the top ten
34
barriers was unemployment rate, with 18% of the participants
indicating that the unemployment rate acted as a barrier.
Because of the importance of economic variables on job
search, labor economists have been major contributors to the
investigation and understanding of the job search process
(Allen & Keaveny, 1980). Reid (1972) examined the
effectiveness of job-finding methods from an economist's
perspective. In his study of recently laid off workers in
engineering and metal-using trades, Reid found that those
workers who were most likely to have a difficult time finding
a job (i.e., low skill and older workers) were most likely to
delay their job search until after their current position
ended. This finding was inconsistent with Reid's hypothesis
that these workers would be more likely to begin their job
search early. Reid suggested that imperfect knowledge of the
labor market may have caused these workers to delay their job
search; that is, perhaps these older and unskilled workers
thought it would be easy to find a job. However, examining
results from a questionnaire revealed that the older and
unskilled workers were more likely to report that they
expected it would be difficult to find a job. For example,
88.6% of the unskilled workers reported that they expected
finding a job would be difficult, compared to only 55.6% of
the skilled workers. Yet only 17.6% of the unskilled workers,
compared with 52.3% of the skilled workers, began their job
search before leaving their previous employer.
35
As an economist, Reid had a difficult time explaining
these data. However, it is consistent with a number of
theories within the field of psychology, including the
expectancy-value theories of behavior. Because these workers
believed that their job search efforts would be less likely to
be rewarded, they had little motivation to engage in these
activities. They therefore delayed their job search as long
as possible; in most cases they delayed the search until they
were forced to look for a job because their current job had
ended.
These findings are consistent with other research
indicating that individuals expected to have a more difficult
time finding a job often delay entry into the job market. For
example, Jones (1985) found that among 16 year old school
leavers, poorly qualified applicants made far fewer
applications than those with average or above average
qualifications. Again, it would seem that those who may have
the hardest time finding a job, put less effort into the job
search.
Research by Steffy, Shaw, and Noe (1989) also supports
the idea that an individual's expectations related to finding
a job and his or her own abilities influence job search
activities. Using path analysis to examine antecedents and
consequences of job search behaviors, these researchers
demonstrated that the number of placement recruiting
interviews obtained by an individual was influenced by level
36
of environmental exploration and the certainty that job search
efforts would lead to positive placement outcomes. In fact,
these two variables exerted more influence on the number of
interviews obtained than did search focus or degree of
intended or systematic search engaged in (both of which
manifested non-significant path coefficients).
Rynes (1991) suggests that when applicants first enter
the job market, they may be unsure about how difficult it will
be to obtain a job. Because their expectancies are not yet
fully fomed, applicants search for clues to create
expectancies related to receiving a job offer. These may
include clues such as the way a specific recruiter interacts
with an applicant. These expectancies then influence whether
or not an individual will be motivated to pursue an offer for
any given job.
A study conducted by Rynes and Lawler (1983) indicates
that there are vast individual differences in the extent to
which expectations about receiving a job offer influence the
probability that an individual will pursue a given job lead.
In this study, researchers gave participants information about
a hypothetical job opening, including information about the
probability of receiving a job offer. Each participant was
then asked to estimate the probability that he or she would
pursue the job offer, that is, apply for the job. A few
individuals did report that expectations about whether they
will receive a job offer should be deliberately ignored when
37
deciding whether to pursue a job. These participants stated
that the decision should be based solely on job attributes.
On the other hand, for most subjects expectancies had a major
impact on whether or not to pursue a job offer, with the
percent of decision variance explained by main and interactive
expectancy effects reaching up to 43%. On the average,
expectancy of receiving a job offer did influence the decision
whether or not to pursue a job. Subjects reported an average
probability of .20 of pursuing a job offer at the 5% level of
expectancy, .46 at the 35% level, and .54 at the 65% level.
It does appear that at a within-subjects level, individuals
are more likely to pursue a job if they believe there is a
good probability that it will lead to a job offer.
Rynes and Lawler's study does show support for the
influence of expectations on job search behavior.
Unfortunately, decisions made by individuals who are actually
applying for real jobs are much more complicated than the
behaviors allowed for by the study. In the real job market,
expectancies are not fixed, but are subjective estimates made
by the individual confronted with the decision of whether or
not to apply for the job. These expectancies vary among
individuals and may or may not be accurate. For example, we
may expect that individuals with high self-efficacy or
internal locus of control to consistently over estimate the
probability that their efforts will lead to a job offer.
Although they did not measure personality variables or similar
38
personal attributes in their study, Rynes and Lawler (1983)
suggest that variables such as risk aversion, self-esteem,
need for achievement, or neuroticism may have influenced the
variability among individuals in the effect of expectancies on
decision to apply for a job.
As mentioned earlier, several individuals in Rynes and
Lawler's study stated that they were not influenced at all by
the expectancies of a job offer assigned by the researchers.
These individuals indicated that expectancies should not make
a difference in a person's choice whether to pursue a job,
therefore they ignored that variable in making their
decisions. However, individuals making actual decisions about
whether to apply for a job may be influenced by expectations
even if they do not indicate that they would be on a self
report measure. Given that students seeking jobs have limited
resources, both in terms of money and time, it is unlikely
that expectations would actually play no role in the decision
about whether to apply for a job.
Economic Psychology
The area of study which most recognizes the influence of
expectations and perceptions of the economy on behavior is the
field of Economic Psychology. According to van Raaij (1981)
"Economic psychology is concerned with the study of economic
behavior, its antecedents and consequences. Economic behavior
comprises consumer behavior, employment behavior, fiscal
39
behavior and the reactions of consumers/citizens to economic
conditions" (p. 3) .
The field of Economic Psychology was founded by George
Katona in the early 1950s (Katona, 1951, 1963). At that time,
the rapid increase in affluence in the United States following
World War II had resulted in an increase in discretionary
spending (Katona & Strumpel, 1978). Consumers of the time
suddenly had much more control over their spending than tbey
had previously experienced; for the first time they could
decide when to spend and when to save. This affluence and
ability to regulate spending activities gave consumers much
more power in the marketplace, and much greater influence on
the economy. "Consequently, when consumers began to spend,
the economy improved. Conversely, when consumers began to
save, the economy contracted." (Mowen, 1990, p. 684) Today,
"fully two-thirds of our gross national product results from
consumer spending" (Mowen, 1990, p. 684).
It was in this environment of increased consumer
influence in the marketplace, that Katona first introduced his
theory of Economic Psychology. Because of the increased
influence of consumers in the marketplace, Katona proposed
that in order to predict economic conditions, one must look at
the attitudes of consumers. Consumers make economic
decisions, such as whether they should make large purchases
based partly on what they believe will happen in the future.
As such, purchase decisions are based in part upon individual
40
consumer's economic beliefs such as attitude toward the
economy as a whole and expected future earnings. According to
Katona's model, these attitudes are based upon the actual
economic environment, but mediated by "personal
characteristics, such as aspirations, expectations, internal
versus external control of reinforcement, and life style" (van
Raaij, 1981, p. 7). It is these attitudes and subjective
interpretations of the economic environment that influence the
individual's economic behavior. If a consumer thinks that
business conditions will be good, he or she will use this
expectation in making economic decisions. He or she may
anticipate better conditions in the company for which they
work, may in turn feel their earning potential is high, and
anticipate their future earnings will increase. This
expectation may therefore lead to an increase in spending,
purchase of large items, etc. On the other hand, if a
consumer feels the economy is poor, he or she may anticipate
the possible loss of income or at least feel the potential for
earning more money is low. In this case the consumer will be
less likely to make major purchases, will be more likely to
postpone major purchases until economic times are better or
until their perspective on the economy is more optimistic.
Aggregated across consumers, these behaviors in turn influence
economic conditions. Attitudes toward the economy therefore
produce behaviors which in turn influence the economy as a
whole.
41
Katona proposed that researchers should be able to
predict changes in the economy by measuring these consumer
attitudes. With the founding of the Survey Research Center at
the University of Michigan and the development of the Index of
Consumer Sentiment, Katona was able to test his theory. What
he and his colleagues found was that attitudes and
expectations of consumers predicted future economic conditions
and consumer expenditures better than traditional economic
variables such as absolute or relative income, price
increases, etc. (Curtin, 1982; Katona & Strumpel, 1978; van
Raaij, 1981).
Although the first issue of the Journal of Economic
Psycholocry cites decisions regarding work and psychological
determinants of unemployment as topics of study within the
field of economic psychology (van Raaij, 1981), theories of
economic psychology have not been applied to the prediction of
job seeking behavior.
42
THE PRESENT STUDY
The current study was designed to examine individual
differences in job search behavior and the expectations which
may contribute to those differences. Specifically, this study
examines expectations about finding a job including
expectations about the job market and the individual's ability
to get a job in that job market.
This study is not designed to test a specific theory of
motivation or behavior. However, the hypotheses are based in
general on the family of theories which recognize the
importance of expectations on behavior. The study explores
the relationships between expectations and behaviors among job
seekers. It was designed to examine the hypothesis that those
who do not expect to be rewarded for their job search efforts
will be less motivated to engage in job search behaviors, and
will in turn delay the onset of their job search, and exert
less effort by engaging in fewer and less frequent job search
activities.
Although it could be considered within the domain of both
vocational and industrial psychology, very few research
studies in psychology have focused on the job search itself.
Instead, research has tended to focus on career development
involving issues such as choice of a career or selection
issues dealing with an organization's choice of the best
candidate for a job. A better understanding of the job search
43
process would contribute our understanding of the career
development process as well as the selection process.
One of the challenges facing industrial psychologists is
to develop methods to identify job applicants able to perform
a specific job well. Unfortunately, despite advances in
selection procedures and our understanding of the various
influences on selection, job seeking skills continue to
influence hiring decisions made by businesses. Even the best
selection procedures cannot totally escape the bias produced
by differences in job search skills and activities among
applicants. By gaining a better understanding of what
influences the job seeker to behave in certain ways,
industrial psychologists can improve their understanding of
what it takes to hire the best candidate for the job.
Gaining a better understanding of the job search also has
implications for the career counselor. Research in vocational
behavior has traditionally dealt with helping the client
select the appropriate career path, focusing on assessment of
interests or abilities, matching jobs with people, and
tracking development throughout the career course. However,
the goal of career counseling intervention is to have the
person actually working in a job he or she enjoys and can be
successful in. Therefore, understanding of the career
process may also be enhanced by a better understanding of the
process of finding a job and the expectations which influence
job seeking behavior.
44
METHOD
Participants
Seven hundred twenty four students were randomly selected
from all seniors graduating from Iowa State University in
Spring 1994. Thirty students' names were dropped from the
mailing list because they did not have local in-session
addresses listed with the university's registrar's office.
Six hundred ninety four questionnaires were sent to graduating
college seniors in the last month before graduation.
As an incentive to complete the questionnaire, one dollar
was enclosed with each questionnaire. The funds for the
incentive were provided by the author. The cover letter
accompanying the questionnaire asked that participants
choosing not to participate in the study return the
questionnaire uncompleted. Reminder telephone calls were made
to survey recipients who had not returned their questionnaires
after two weeks.
A total of 395 questionnaires were returned: 370
completed and 25 uncompleted, yielding a response rate of 53%.
Fifty-three percent of the participants were male (n=194);
forty-six percent were female {n=17l). Ninety three percent
of the participants reported their race to be white (n=344).
Participants ranged in age from 20 to 52, with a median age of
22.4. A total of 82 academic majors were represented in the
sample (see Appendix A).
45
Instruments
The survey instrument consisted of scales measuring locus
of control, self-efficacy, attitude toward the job market, and
job search behavior. It also contained items asking for
demographic information including age, sex, race, college
major, and grade point average of the participant.
Career locus of control
Locus of control was measured using the Career Locus of
Control Scale (Trice, Haire & Elliott, 1989) . The Career
Locus of Control Scale is an 18-item scale measuring attitudes
toward career planning and locus of control related to career
development. Trice, Haire and Elliott (1989) report a
correlation of .52 with Rotter's (1966) I-E scale and a non
significant correlation with the Marlowe-Crowne Social
Desirability scale (Crowne & Marlowe, 1964). They also report
KR-20 internal consistency coefficients ranging from .78 to
.82 for various samples of undergraduate students sampled
during the scale's development and validation process.
Scoring the scale in the manner suggested by Trice,
Haire, and Elliott produces a scale in which high scores
indicate external locus of control, and low scores indicate
internal locus of control. These scores were reversed to make
the scores on this scale more consistent with other scales
included in the study, and to ease in the interpretation of
the various analyses. For scores reported in this study, high
46
scores indicate internal locus of control and low scores
indicate external locus of control.
Self-efficacy
Two measures of job search self-efficacy were used: the
first was a subscale of the Outplacement Needs Inventory
(Kanfer & Hulin, 1985) and the second, a measure of job
seeking confidence developed by the Institute for Social
Research at the University of Michigan {van Ryn & Vinokur,
1992) .
The Outplacement Needs Inventory (ONI) is a 38-item
questionnaire measuring various constructs related to
unemployment and job search behaviors. The instrument
contains four major content areas. The first section contains
items measuring demographic and background characteristics
including age, marital status, length of employment in current
job, and knowledge of the community which may be helpful to
the job search. The second portion of the ONI measures
attitudes toward termination of employment and unemployment
including depression, job satisfaction, and perceptions of
organizational fairness. The third section of the ONI
contains six items measuring self-efficacy expectation for
specific job search skills. The final section of the ONI asks
about job search behaviors already engaged in and behavioral
intentions to apply for new positions.
47
The job search self-efficacy portion of the ONI asks
participants to indicate on a seven point Likert type scale
their confidence in their ability to perform six job search
behaviors. The rating scale contains three anchors: very
unsure of myself, moderately sure of myself, and very sure of
myself. Kanfer and Hulin (1985) report coefficient alpha for
the job search self-efficacy portion of the scale to be .84.
The second measure of job search self-efficacy was a
measure of job seeking confidence developed by the Institute
for Social Research at the University of Michigan. This six
item scale asks participants to indicate how confident they
are that they can perform various job seeking activities such
as completing a good job application and resume. The scale
requires individuals to indicate their degree of confidence on
a five-point scale, ranging from "not at all" (1) to "a great
deal" (5).
The Job Seeking Confidence scale was adapted so that the
rating scale would be consistent with the seven point scale
from the ONI. Internal consistency reliability for the job
seeking confidence scale has been reported to be .87 (van Ryn
& Vinokur, 1992). The two scales were combined to form one
twelve item scale measuring job search self-efficacy, based
upon the high internal consistency reliability produced by
combining the scales (see Results).
48
Perceptions of the economy
Two methods of measuring perceptions of the economy were
utilized. The first was the Employment Outlook segment of the
Career Exploration Survey (Stumpf, Colarelli, & Hartman, 1983)
and the second was the Business Conditions segment of the
University of Michigan's Surveys of Consumers, the scale which
is used to compute the Index of Consumer Sentiment.
The Survey of Consumers was developed by George Katona in
an attempt to measure consumer attitudes which may in turn
effect the economy. Since the mid-1940s, the survey has been
used by the University of Michigan' Survey Research Center to
predict consumer and economic trends. Research using the
survey have shown it to be a successful predictor of a variety
of consumer trends including home sales and car sales.
The Survey of Consumers contains 40 core questions
covering three broad areas: personal finances, business
conditions, and buying conditions. The present study used the
business conditions portion of the survey to measure the
participants' expectations and attitudes regarding business
conditions. The business conditions portion of the Survey of
Consumers contains 12 items asking the participant questions
such as whether business conditions are better or worse than a
year ago, whether he or she expects a change in unemployment,
and whether he or she expects changes in prices and interest
rates.
49
The second measure of attitude about economic conditions
was taken from the Career Exploration Survey (CES). The CES
was developed by Stumpf, Colarelli, and Hartman (1983) to
measure 16 dimensions of the career exploration process.
Seven of these dimensions deal with the actual exploration
process, such as self-exploration and the number of
occupations considered; three of the dimensions deal with
reactions to exploration including satisfaction and stress;
and six of the dimensions deal with beliefs such as employment
outlook and search instrumentality.
The present study used the Employment Outlook segment of
the CES. This three item scale was designed to measure an
individual's view of the job market for his/her chosen
occupation. It asks the participant to indicate on a five
point scale ranging from "not good" (1) to "very good" (5) how
employment possibilities look for the job(s) he or she
prefers, the organization(s) he or she prefers, and the
occupation(s) he or she prefers. Stumpf, Colarelli, and
Hartman report the coefficient alpha for the Employment
Outlook segment of the Career Exploration Survey to be .88.
Job search activity
Past researchers examining job search behavior have
measured actual job search activity in a number of ways.
These include examining the number of job search activities
engaged in (Caplan, Vinokur, Price, & Van Ryn, 1989; Dayton,
50
1981; Friedrich, 1987; Rowley & Feather, 1987); amount of time
spent looking for work (Baik, Hosseini, & Priesmeyer, 1989;
Barron & Gilley, 1979; Ellis & Taylor, 1983); and how often an
individual looks for a job (Feather, 1992; Feather & O'Brien,
1987; Rowley & Feather, 1987) . Conceptually, each of these
are important aspects of the job search and each represents a
different way to measure the degree to which an individual is
involved in the job search process. Because of this, the
current study measured all three aspects of job search
behavior: number of job search activities engaged in, amount
of time spent looking for work, and frequency of job search.
The current study also included one additional measure of job
search activity: date of entry into the job search process.
In addition, the questionnaire asked participants whether they
were looking for a job, whether they had received any job
offers, and whether they had accepted an offer for full time
employment upon graduation.
Number of job search activities engaged in were measured
using the job search behaviors portion of the Outplacement
Needs Inventory (Kanfer & Hulin, 1985) . This scale requires
participants to indicate which of seven job search behaviors
they have already taken toward obtaining employment. The
overall number of search behaviors is measured by summing the
number of items marked "yes." Kanfer and Hulin (1985) do not
report a reliability coefficient for the job search behavior
scale. However, they do report that using this method for
51
measuring job search activity successful distinguishes between
reemployed and unemployed individuals, with reemployed
individuals reporting having taken significantly more
behavioral actions related to job search than unemployed
individuals. They also report that job search self-efficacy
scores are significantly correlated with the search behavior
measure (r=.51).
Frequency of job search was measured using a single item
used in a number of studies conducted by Feather (Feather,
1992; Feather & O'Brien, 1987). This item asks participants
to indicate how frequently they look for a job by choosing one
of the following: not looking for a job, when I feel like it,
monthly, weekly, every couple of days, daily. This measure of
job-seeking behavior has been shown to be related to job
valence, negative affect associated with unemployment, and
length of time unemployed (Feather, 1992; Feather & O'Brien,
1987). This item also asked that participants who had already
found a job at the time of the survey to indicate how often
they looked for work before they found a job.
The amount of time spent looking for work was measured by
asking applicants to estimate the total number of hours spent
looking for work over the past four weeks. Again,
participants who had already found employment were asked to
indicate how much time they spent looking for work during the
four weeks before they received a job offer. This item was
chosen to provide a more behaviorally based and accurate
52
estimate of time spent job searching than would be obtained by
simply asking for a more general estimate of amount of time
spent looking for work. The period of time chosen needed to
be recent enough to allow for easy recall of how the
participant actually spent his or her time. However, because
students' schedules vary from week to week, the period of time
needed to be long enough to allow for an accurate measurement
even if during a specific week the student had less time to
spend job seeking because of tests or projects that happened
to be due the week before the survey was sent out. Four weeks
seemed to be an amount of time which satisfied both of these
requirements.
Date of job search onset was measured by asking
applicants to indicate the date they first engaged in each of
the job search behaviors indicated on the job search behaviors
portion of the ONI. The date associated with each job search
behavior was then converted to the number of weeks before
graduation to facilitate data analysis. The majority of dates
listed for most job search behaviors were within a few months
of graduation. However, some participants listed dates well
beyond a year before graduation. Dates listed which were one
hundred or more weeks before graduation were coded as 99 weeks
to reduce the effects of extreme outliers. For most of the
analyses, onset of job search was measured by using the
earliest date listed for each participant.
53
RESULTS
Preliminary Analyses
Scale reliabilities
Internal consistency reliabilities were assessed by
computing Cronbach's Coefficient Alpha for all scales (see
Table 1). Coefficient Alpha for the Career Locus of Control
Scale (Trice, Haire & Elliott, 1989) revealed rather low
internal consistency {r^=.AS) . This coefficient was much
lower than those reported by the scale's authors to
r^=.82 depending upon sample). In the article describing the
development of the scale. Trice, Haire and Elliott warned that
the reliability coefficient reported may be biased because it
was calculated using data from the sample used for the
Table 1; Internal consistency reliability for scales (n=370).
Coefficient # of Siibscale Aloha Items
Career Locus of Control Scale .46 18
Job Search Self Efficacy (Combined Scale) .89 12
Outplacement Needs Inventory .74 6
Job Seeking Confidence Scale .87 6
Employment Outlook (CES) .94 3
Business Conditions Expectations (ICS) .71 12
Number of Job Search Steps Employed .67 9
54
development of the scale. However, the authors did report
that the scale had demonstrated high temporal stability, with
stability coefficient rxx=.93 for a sample of 41 men retested
after three weeks. Although the temporal stability of this
scale was not assessed in this study, there is no reason to
believe that this study's participants were fundamentally
different from those participating in the study by Trice,
Haire, and Elliott. It is therefore probable that the
stability coefficient for this scale would be higher than the
internal consistency coefficient. However, the validity of
any instrument and its ability to predict is limited by its
reliability. Therefore, it should be noted that the low
internal consistency of this scale may have had an effect on
the analyses which included Career Locus of Control as a
variable.
As mentioned earlier, Job Search Self Efficacy was
measured using two separate six-item scales; one was a
subscale of the Outplacement Needs Inventory and the other was
the Job Seeking Confidence Scale developed by the Institute
for Social Research at the University of Michigan. The
decision to combine the two scales into a single measure of
job search self-efficacy was made based upon the high internal
consistency obtained by combining the scales (r^=.89).
All other scales demonstrated reasonable internal
consistency reliability. The three-item Employment Outlook
subscale revealed extremely high internal consistency
55
considering the length of the scale =.94) . This was even
higher than the =.88 reported by the authors (Stumpf,
Colarelli, & Hartman, 1983). The reliability of the Business
Conditions Expectations segment of the Index of Consumer
Sentiment was not extremely high (r^=.7l), but was reasonable
considering this instrument was actually developed for use as
an interview, and not as a paper and pencil survey.
The internal consistency of the Number of Job Search
Steps Employed was acceptable, but not high (r^=.67). Because
this measure is a check list of activities rather than a
homogeneous measure of job search activity, one might expect
that the internal consistency would be somewhat lower than
that of a scale measuring a unified construct. The checklist
included activities which were not equally likely to be
performed by students looking for a job. For example, 89.2%
of all participants reported that they had prepared a resume;
while only 33.6% reported that they had contacted an
employment agency or job-finding center. This tendency for
some activities to be more commonly performed than others, may
lower internal consistency of the checklist when used as a
scale. However, the checklist did produce a range of scores
(from a minimum of 0 steps to a maximum 8 steps employed) and
fair degree of variance (X=5.25, s^=2.98) which would indicate
it is detecting differences among participants in the degree
56
to which they were actively seeking a job at the time the
survey was completed.
Correlations between scales
Correlations between scales were examined for all
variables (see Table 2). Attitudinal variables tended to be
highly correlated with each other, indicating a relationship
exists between the various types of attitudes measured. The
variable with the lowest correlation with other attitudinal
variables was Career Locus of Control. This was probably due
in part to the low internal consistency reliability of the
scale.
Behavioral variables also tended to be related to each
other. Measures of the number of job search steps taken,
number of hours spent job searching, and the frequency of job
search were all highly related to one another. The behavioral
variable exhibiting the lowest correlation with other
behavioral variables was the date for onset of job search.
The relationships between attitudinal and behavioral
variables were weaker than those among attitudinal variables
or those among behavioral variables. The strongest was the
relationship between date job search began and career locus of
control. Number of job search steps employed tended to be
more highly correlated with attitudinal variables than did
other job search variables.
Table 2: Pearson product moment correlations among variables (n=370)
CARLOC JOBCONF OUTLOOK BUSCOND NUMSTEPS JSHOURS FREQ DATE GPA
CARLOC 1.00 .14* .12* .14* .12* .10 .15* .18* .22*
JOBCONF
o
o
H .43* .19* .14* - .02 .10 .11 .01
OUTLOOK
o
o
H .27* .12* .07 .07 .15* - .03
BUSCOND 1.00 .12* .12* .15* .00 - .00
NUMSTEPS 1.00 .34* .54* .15* - .03
JSHOURS O
O
.34* .06 .05
FREQ O
O
-.02 .01
DATE 1.00 .07
GPA 1.00
* p<.05 CARLOC = Career Locus of Control; JOBCONF = Job Seeking Confidence; OUTLOOK = Employment Outlook; BUSCOND = Business Conditions Expectations; NUMSTEPS = Number of Job Search Steps Employed; FREQ = Frequency of Job Search Behaviors; JSHOURS = # of hours spent job searching over the past four weeks. DATE = Date job search began in weeks before graduation; GPA = Self-reported Grade Point Average.
58
Tests for collinearity
Correlations were examined to determine whether
collinearity would pose a problem in later analyses.
Collinearity results when a linear or near linear relationship
exists between two or more variables in a regression equation.
When this condition exists regression coefficients display
very high variances and are highly unstable, causing problems
with interpretation of regression coefficients. If a linear
relationship exists between variables, it often, although not
always, produces correlation coefficients close to one.
Although a many of the correlations were statistically
significant none were large enough to indicate collinearity
existed. The largest correlation coefficient was between
frequency of job search and number of job search steps
employed (r=.54). This coefficient was not close enough to
one to warrant concern over problems of Table 3:Variance
multi-collinearity. inflation factors (VIFs).
A second way to diagnosis the threat
of collinearity is through variance
inflation factors (VIF) (see Table 3).
These factors measure the degree of
"inflation" in the variance of regression
coefficients among variables in a
regression equation. Formal guidelines
for determining whether a given variance
inflation factor is too large have not
VARIABLE VIF CARLOC 1.16
JOBCONF 1.25 OUTLOOK 1.27 BUSCOND 1.12 NUMSTEPS 1.46 JSHOURS 1.20 FREQ 1.46 DATE 1.09 GPA 1.05 See Table 2 for explanations of variable name abbreviations.
59
been established (SAS, 1989). Chatterjee and Price (1977)
have suggested that VIFs over 10 indicate that multi-
collinearity may create problems in estimating regression
coefficients, although this criterion may be too stringent for
much of the research in the social sciences. Based upon these
guidelines, the calculated VIFs presented in Table 3 suggested
that collinearity would not present a problem with this set of
data.
Variable means
Means, standard deviations, minimum and maximum values
for all variables are listed in Table 4. All attitudinal
variables were scored in a direction which is consistent with
what one might intuitively expect, with high scores indicating
more of a desirable attitude or trait. For example, high
scores on the Career Locus of Control Scale (Career L.O.C.)
signify a more internal locus of control; high scores on Job
Search Self-Efficacy scale indicate higher self-efficacy; and
high scores on scales measuring Employment Outlook (Empmt
Outlook) and Business Conditions Expectations (Business Cond)
represent more optimistic expectations. Behavioral variables
were similarly scored, with high scores indicating more
frequent, more diverse, more intense or earlier onset of job
search.
All variables produced scores which were distributed
across the entire possible range. The mean for most variables
60
Teible 4: Mean scores for all variables for entire sample (n=370).
Variable Mean S D. Min. Max.
Career L.O.C. 13 .18 2 22 7
o
o 18. 00
Self Efficacy 64 .72 10 45 24 .00 84. 00
Empmt Outlook 13 .78 4 62 3 .00 21. 00
Business Cond 29 .52 5 32 12 .00 41. 00
# of Steps 4 .87 1 98 0 .00 8. 00
Search Frequency 3 .94 1 54 1 .00 6. 00
Search Hours 15 .85 16 .70 0 .00 99. 00
Onset of Search 42 .63 29 .40 4 .00 99. 00
GPA 3 .03 0 .46 2 .00 4. 00
fell around the midpoint of the distribution, or slightly-
above the midpoint. The variables calculated from open ended
questions (i.e., Search Hours and Onset of Search) tended to
produce the greatest range and the most variable
distributions. The distributions of these variables also
tended to be the most skewed.
Participants were grouped according to their response to
the question "What do you plan to be doing in Fall 1994?"
Table 5 displays the various responses to this question.
Based upon their responses, participants were placed into one
of three groups: Students planning to be working full time in
the fall (n=278), students planning to be doing something
other than working full time (i.e., graduate school, the
military, etc., n=61), and students who will probably work
61
Table 5: Participants' plans for Fall 1994.
Plans for Fall n
Working Full Time 270
Graduate or Professional School 51
Working and Taking Classes 23
Military or Peace Corps 5
Unsure or Considering Several Options such as Graduate School, Working, Peace Corp, Etc. 9
Stay Home with Child/Homemaking 3
Start Own Business 2
Farming and Working 2
Working Part Time 1
Did not respond to question 4
Total 370
full time, but were considering other alternatives as well
(e-g-/ graduate school, military, etc., n=27). Grouping was
based upon the author's judgment about whether each
participant would be actively seeking employment based upon
his or her response to the question about plans for fall.
Therefore, individuals indicating that they planned to start a
business were grouped with those planning to be doing
something other than working full time. Of the 309 students
who were looking for a job, almost half (n=l43) had received
62
an offer and one third (n=103) had accepted an offer for full
time employment after graduation.
Scale means were examined for each of the subscales,
sorted by participants' plans for fall and employment status
after graduation (see Table 6). Multiple discriminant
analysis was employed to determine whether the differences
between groups were statistically significant. The
multivariate F statistic was 5.81 for the differences between
those planning to work full time in the fall and with plans
other than full time employment; and 6.62 for the differences
between those who had already secured employment and those who
had not. Both of these were statistically significant at
p<.0001, indicating that differences between the groups
existed for at least one of the variables.
Univariate statistics were then analyzed to determine
which variables produced statistically significant
differences. The few differences between the groups were not
surprising. As one may expect, those planning to work full
time exhibited a higher degree of job search behavior than
those who were not. Those planning something other than full
time employment, such as graduate school, reported performing
fewer job search steps (effect size, d=8.10), looking less
frequently (d=7.27) and searching fewer hours (d=6.97) than
those planning full time employment. It should be noted that
the job search behaviors undertaken by these students were
generally related to part-time employment or assistantship to
Table 6: Variable means by Plans for Fall and Employment Status.
Plans for Fall Employment Status at Time of Studv
Full Time Employment
(n=309)
Not Full Time Employment
(n=61)
Secured Es^loyment
(n=104)
Not Secured Entployment
(n=202)
Variable Mean SD Mean SD Mean SD Mean SD
Career L.0.C. 13 .13 2 .26 13 .56 2.00 13 .35 2.19 12 .98 2.30
Self Efficacy 64.87 10 .49 64.70 9.20 68.87 10.30 62 .57 10.33*
Empmt Outlook 13,78 4.63 13 .59 4.58 16.52 3 .84 12.38 4.39*
Business Cond 29 .60 5.38 29 .18 5.64 30.18 5.31 29.19 5.31*
# of Steps 5.25 1.73 2 .95 2.08* 5 .45 1.88 5 .16 1.63
Search Frequency 4.19 1.36 2.53 1.69* 4.24 1.36 4.20 1.36
Search Hours 17 .16 17.60 7.11 8.06* 17.84 18.95 16.85 16.93
Onset of Search 42 .14 28.82 44.50 32 .90 45 .46 30.41 40 .03 27 .53
CPA 3 .00 0 .45 3 .21 0 .48* 3.04 0 .44 2 .97 0 .45
Statistically significant differences (p<.05) discriminant analysis are designated with an
between means *
based upon
64
be held during graduate school. Other participants considered
searching for and applying to graduate school when answering
the questions related to job search activities. Only two
participants suggested that they decided on graduate school
after beginning their job search. Mean GPA was slightly
higher for those having plans other than working full time
than for those planning to work full time in the fall
(d=1.75).
There was a difference in Employment Outlook between
those who had already secured employment and those who were
still looking for a job, with those who had secured employment
being more optimistic than those who had not (d=17.45). Those
who had found a job also possessed a greater degree of job
search self-efficacy than those who had not yet found a job
(d=5.06). Because of the concurrent nature of the data
collection, one cannot be sure whether these attitudes
influenced behavior or if experience in the job market
influenced attitude. It seems most likely that the attitudes
of those who had found a job were more optimistic due to their
positive experiences looking for and finding a job.
Job search steps employed
The utilization of various job search steps was examined
for the 309 participants indicating they planned to be working
full time in the fall. For the most part, job seekers tended
to use a variety of techniques when looking for a job. The
65
Perceni of Sample Employing Various Job Search Sfeps
100- S4.SX 8*.7X
75- 71.4X
C ® O 50-
® Q.
67.97!
27.9%
35.7%
25-
NEWSPR FREND RESUME AGENCY PHONE APPLY WTERVW OTHER
job search step
NEWSPR = Losktd In Hk ntwipaptr for opanlngs. FRIENO = Tdkad with frttnia or r«loHrts vbout |«b pr«if)Kti. RESUME = Prtpwtd a rasumt or vllo, AGENCY - Contoclwl an wrploinranl dgtncy or a |ob fkidhig etnlar. PHONE = TaUphonad a protpwtiv* wnployar. APPLY = FIM eut
on flpptcollMi (or • |ob opsnlnB* INTERVW - Obloined a {ob Interview. OTHER — Other.
Figure 1: Job search steps employed by participants planning to work full time in the fall (n=309).
mean number of steps employed was 5.25, the mode was 6 steps,
and 73% of the sample indicated that they had employed five or
more of the eight steps listed. Only two (0.6%) of the 309
participants indicated they had not yet engaged in any of the
job search steps listed, and only 11 (3.6%) indicated that
they had employed just one step.
As one might expect, there was variability in the degree
to which each of the job search steps was utilized (see Figure
2). Almost all (94.5%) of the participants had already
prepared a resume. Almost as many (84.7%) indicated that they
66
had talked with friends or relatives specifically about job
prospects. Other job search steps that were commonly used
included looking in the newspaper for openings, telephoning
prospective employers, filling out applications for job
openings, and obtaining job interviews, with approximately 70%
of the sample indicating that they engaged in each of these
behaviors.
The least popular job search step listed was contacting
an employment agency or a job-finding center, with 35.7% of
those planning on full time employment making use of this
option. Approximately 28% listed additional search behaviors
under the option "Other". These included behaviors such as
researching potential employers, sending prospecting letters
or letters of application, arranging plant trips, office
visits or informational interviews, researching career
interests, and obtaining internships or summer jobs from
potential future employers.
Job search steps employed by those who had obtained a job
offer were compared with those who had not. Discriminant
analysis was employed to whether the differences between
groups were statistically significant. The multivariate F
statistic was 12.23 which was statistically significant at
p<.0001, indicating that differences between the groups
existed for at least one of the variables.
Univariate statistics were then analyzed to determine
which job search steps produced statistically significant
67
Teible 7: Differences in job search steps utilized by students who had obtained job offers and those who had not (n=309).
Effect Job Recvd No Size Search Job Job Cohen's Steps Offer Offer d F-Value
NEWSPR 63.38% 78.66% .34 2.86 N.S.
FRIEND 80.28% 89.02% .25 0.31 N.S.
RESUME 95.77% 93 .29% .11 6.06 p<.05
AGENCY 35.21% 36.59% .23 0.06 N.S.
PHONE 83.80% 59.76% .55 33.79 p<.0001
APPLY 73.94% 62 .80% .24 15.76 p<.0001
INTERVW 90 .14% 57.93% .77 68.30 p<.0001
OTHER 38.73% 18.29% .47 11.86 p<.0006
differences (see Table 7). The groups of students who had
obtained a job offer differed significantly from those who had
not primarily in their use of five job search steps. Those
who had received offers were much more likely to have 1)
telephoned a prospective employer; 2) filled out an
application for a job opening; 3) obtained a job interview; 4)
performed an additional job search behavior which was not
listed on the questionnaire. These students were also
somewhat more likely to have prepared a resume than those who
had not yet received an offer. Those who had not received an
offer were more likely to have looked in the newspaper for
openings and talked with friends or relatives about job
prospects. Although these differences were not statistically
68
Table 8: Differences in job search steps utilized by students who had accepted job offers and those who had not (n=309).
Not Effect Job Accpt Accpt Size Search Job Job Cohen's Steps Offer Offer d F-Value
NEWSPR 55.77% 79.60% .54 12.00 p<.0006
FRIEND 75.96% 89.55% .26 1.93 N.S.
RESUME 93.27% 95.02% .23 0.27 N.S.
AGENCY 34.62% 36.82% .05 0.08 N.S.
PHONE 82.69% 67.68% .40 14.92 p<.0001
APPLY 71.15% 66.17% .11 3.40 N.S.
INTERVW 87.50% 65.17% .51 22.97 p<.0001
OTHER 44.23% 19.40% .40 21.94 p<.0001
significant, they may be worth examining since they may
indicate these job search steps are somewhat less effective
than others listed.
Differences in job search steps utilized were also
examined for those who had accepted a job offer and those who
had not. Again, discriminant analysis was used to determine
whether differences between the groups were statistically
significant. The multivariate F-statistic indicated that the
groups differed significantly on at least one job search
behavior (F=8.53, p<.0001).
Univariate statistics revealed patterns similar, but not
identical to those reported above. Again, those who had
accepted a job were more likely to have telephoned a
69
prospective employer, obtained an interview, and engaged in
additional behaviors not listed on the survey. Although not
statistically significant, those who had accepted a job offer
were also slightly more likely to have filled out an
application for a job opening than those who had not. Again,
those who had not accepted a job offer were much more likely
to have looked in a newspaper for openings, and slightly more
likely to have talked with friends or relatives about job
prospects and prepared a resume.
Dates for enaaaina in iob search steps
Dates for engaging in the various job search steps were
examined for participants who had engaged in each of the job
search steps listed (see Figure 2 & Table 9). Dates listed on
the questionnaire were converted to weeks before graduation
prior to analysis. The
majority of dates listed
for most job search
behaviors were within a
few months of graduation.
However, some
participants listed dates
well beyond a year before
graduation. Dates listed
which were one hundred or
more weeks before
Tsdsle 9: Dates for initiating various job search steps (n=309).
Stet) Mean SD Med Mode
NEWSPR 19.9 16. 6 15 .9 16
FRIEND 27.9 23 . 6 20 .8 16
RESUME 38.6 28. 9 29 .4 29
AGENCY 24.6 22 . 4 16 .3 16
PHONE 19.5 21. 0 12 .2 8
APPLY 21.2 21. 7 12 .2 8
INTERVW 19.4 20 . 3 12 .1 8
OTHER 22.8 21. 2 15 .7 12
70
Average Dates for Initiating Various Job Search Steps
40 q
NEWSPR FREND RESUME AGENCY PHOHE APPLY NTERVW OTHER
job search step
KZ881 Mean HI Median Mode
NEWSPR = Lo«k«d in thi ncwspaptr for opininss. FRIEND = Tdkcd with frlinds or rtlatlvts obout job prospscla. RESUME = Prepved o resume or vita. AGENCY = Cantacled on eirploytnenl agtncy or a job Undlng c*nt«r. PliONE = Teltphcfwd a prcspectivi ffrf>loy«r. APPLY = nM out
an appli(»il1on for a job opening. NTERVW = Obfofned a fob interview. OTHER = Qther.
Figure 2: Mean, Median, and Modal dates for initiating various job search steps measured in weeks before graduation {n=309) .
graduation were coded as 99 weeks to reduce the effects of
extreme outliers. The number of participants indicating that
they performed a job search step 100 or more weeks before
graduation was seven or less for all but two job search steps:
preparing a resume or vita and talking with friends or
relatives about job prospects. There were 28 participants who
indicated that they had prepared a resume more than 99 weeks
before graduation and 12 participants who indicated that they
had talked with friends or relatives about job prospects more
than 99 weeks before graduation. All the distributions of
71
dates tended to be somewhat positively skewed, with most
participants performing most job search behaviors shortly
before graduation, and a few starting much earlier.
Therefore, the mean dates for each of the behaviors listed
tended to be somewhat higher than did the median or modal
dates.
The job search behavior which tended to be performed the
earliest was preparation of a resume or vita. The mean date
for preparing a resume or vita was 38.6 weeks before
graduation. The modal date was 29 weeks, with 31 out of 261
respondents reporting this date, and the median was 29.4 weeks
before graduation. Twenty-eight participants indicated that
they had prepared their resume 100 or more weeks before
graduation. This number was higher than for any other job
search behavior.
The second earliest step performed tended to be talking
with friends or relatives about job prospects. The mean date
for performing this behavior was 27.9 weeks, and the median
was 20.8 weeks before graduation. The modal date was 16
weeks, with 40 out of 230 respondents reporting this date.
Twelve participants indicated that they performed this
behavior 100 or more weeks before graduation.
Although few participants reported that they had
contacted an employment agency or a job finding center, those
who had, tended to do so early: between four and six months
before graduation. Looking in the newspaper for openings also
72
tended to be performed around four to five months before
graduation. Telephoning prospective employers, filling out
applications for openings, and obtaining job interviews,
tended to be conducted closer to graduation, with a modal date
for those behaviors just two months before graduation.
Cluster Analysis
Cluster Analysis was used to group job seekers on the
basis of the four attitudinal variables: Career Locus of
Control, Job Seeking Confidence, Economic Outlook, and
Business Conditions Expectations. Ward's (1963) method of
cluster analysis was chosen because of it's reported
effectiveness for recovering underlying structure within the
data (Borgen & Weiss, 1971). Ward's method is a hierarchical
method which uses an algorithm designed to minimize variance
in squared Euclidean distances within clusters. The squared
Euclidian distance (d^) is the sum of the squared differences
over all of the variables. Because Euclidian distance
measures are heavily influenced by units of measurement, all
variables were converted to z-scores prior to conducting the
cluster analysis. Participants who had indicated that they
were not planning to work full time in Fall 1994 were not
included in the cluster analysis.
The decision about the appropriate number of clusters for
these data was made based upon changes in the semi-partial
multiple correlation coefficients (semi-partial R^) . When
73
semi-partial was plotted
against the number of
clusters, a sudden change in
slope occurred between the
six and seven cluster
solutions. This indicates
that the amount of additional
variance explained by adding
a seventh cluster is much
less than that for adding a
sixth cluster. In other words, little is lost by moving from
a seven cluster solution to a six cluster solution, but a
great deal of explanatory power is lost when one moves from a
six cluster to a five cluster solution. Based upon this
information, a six cluster solution was chosen.
After clusters were formed based upon standardized
attitudinal variables, attitudinal variables, variables
measuring job search behaviors, and mean grade point averages
(GPAs) were examined for each of the six resulting clusters.
The following describes each of the six clusters.
First cluster
Figure 2 displays the standardized variable means for the
first cluster. Sixty seven students (31 male, 36 female) were
included in this cluster. These students tended to exhibit
job search locus of control scores which were slightly more
0.15
0.1
Figure 3: Semi-partial plotted against number of clusters.
74
1.50:
1.2si 1.00:
0.75 i
0.50:
standardized Variable Means First Cluster
Z 0.25: O O 0.00:
0.2fi7 0.131
-0.25!
-0.50 =
-0J5:
-i.ooi -1.25:
-1.50-BUSCOND NUM^ePS JSHOURS DATE CARLQC JOBCONF OUUOOK FRZO CPA
/ariable
CAIS.OC = Carter Loeua of Control; JOGCONT = Job S««fclng Conlldanoe; OUTLOOK = Enplojfrrwnl Outlook: BUSCONO = Biralntst ComHtloiw Expoctolions; MMSTEPS =
Number of Job Search Steps Employed; FREQ = Frequency of Job Search Behovlors; JSHOIRS = # of hours spent job teorcMng ovw (he post four weekt;
DATE - Dole job secrch began h weeks before grtidixilicn: GPA = ^If reporled grade poTnt overage.
Figure 4; Variable means for first cluster (n=67).
internal than those of their peers. They also tended to be
more optimistic than average in their expectations about
business conditions. However, their employment outlook tended
to be more pessimistic than that of other students. Their job
seeking confidence tended to be about average compared with
other students in the sample. These students tended to
exhibit slightly higher grades than students in other
clusters, with mean GPA for the cluster being 3.12.
These students' job search behavior tended to be only
slightly above average compared with other participants.
Students in this cluster reported engaging in a mean of 5.37
75
job search steps, as compared to the mean 5.25 steps for the
entire sample of job seekers. 40.9% of the students in this
cluster reported that they look for a job weekly, compared to
the overall average of 37.6%; 30.3% said that they look for a
job every couple of days, and 16.7% said they search daily.
Only 12% of the sample reported looking for a job less
frequently than weekly, compared to the overall average,
18.8%. These students spent an average of 19.5 hours looking
for a job during the four weeks prior to receiving the survey,
compared to an average 17.2 hours in the sample as a whole.
The only measure of job search behavior that was below
average for this group was the date reported for entering the
job search. This group tended to enter the job search later
than other groups. The earliest date for engaging in job
search behaviors was performed an average of 34.7 weeks before
graduation, compared to the mean 42.3 weeks for the overall
sample. For example, although more students in this group had
prepared a resume (93%) than the overall sample (84%), they
tended to have done so later (X=33.0 weeks before graduation)
than the overall sample (X=38.6 weeks before graduation).
This group was somewhat less likely than the entire
sample to have received and accepted a job offer. 38.8%
reported that they had received an offer for full time,
permanent employment upon graduation, 28.4% reported that they
76
Standardized Variable Means Second Cluster
l.SOg 1.25
1.00
0.75
0.50 ;
® 0.25 = O : O 0.00 E
-0.5D:
cms
-0.75; -1.00:
-1.25E
-1.50= DATE CARLOC JOBCONF OUTLOOK BUSCOND NUMSTEPS TREO
variable
CPA
CARLOC = Caraer Locus of Conlrok JOGCONT = Job BmkTng Confidence; OUTLOOK = Ejnploynwnt Ojtloolc BUSCONO = Gusinvss Condilions Dcptclationsi NUMSTEFS =
Number of Jd) Search Steps Emplo/ed; FREQ = Frequency of Job Sevch Behaviors; JSMOURS = of hours 6p«nt |ob s«oreKlng ov«r th* post lour WMks:
DATE = Date job search ba^ In weeks before graduation: CPA = ^If reported grode paTnt averoge.
Figure 5: Variable means for second cluster (n=63).
had accepted a full time permanent job for after graduation,
and 69.7% said that they were still looking for a job.
Second cluster
The second cluster included 63 students (41 male, 22
female) who tended to be the most optimistic group of students
participating in the study (see Figure 3). These students
tended to exhibit internal locus of control and were quite
confident in their abilities to look for and find a job, when
compared to students in other clusters. These students tended
to be optimistic about the economy as well, both for their own
77
career (Occupational Outlook), and for business conditions as
a whole (Business Conditions Expectations). Students in this
group had earned GPAs which were about average when compared
with other clusters (X=2.97).
Students in this clustei were also more active in
engaging in job search behavior than the average student. The
mean number of job search steps employed for this cluster was
5.70, compared to the overall average of 5.25. This group
tended to have begun their job search earlier than any other
group, with the mean first job search step reported having
occurred 52.59 weeks before graduation, compared to the
overall mean of 42.34 weeks. These students also reported
above average frequency of job search: 35.5% reported looking
for a job weekly, 27,4% every couple of days, and 25.8% daily.
Fewer than 12% of the students in this cluster looked for a
job less than once per week. This group of students spent an
average of 19.8 hours looking for a job during the four weeks
before receiving the survey, as compared to 17.2 hours for the
overall group average.
This group was more likely to have received and accepted
an offer for a job than were students in other groups. 65.1%
reported that they had received an offer for full time,
permanent employment upon graduation, 50% reported that they
had accepted a full time permanent job for after graduation,
and 48.4% said that they were still looking for a job.
78
Standardized Variable Means Third Cluster
1.5Qq
1.25
1.00 0.787
0.75
0.50
u 0.25 i O O 0.00:
Loia —
N
-0.75; -1.00!
CARLOC JGBCONT OUTIOOK BUSCONO t4MSTEPS DKO JSHOURS DATE GPA
variable
CARLOC = Carter Locus of Con<ral! JOaCONF = Job 5a«ktn{| Confldtnce; OUTLOOK = EnvloynMnt Outlogto BUSCONO = Bualnrat Comfltioin bpwtallonsi NUMSTEFS = Hunim of Job Search Steps Employed; TREO = Frequency of Job Seorch Bebovhrs;
JSHOURS = /jt of hours spent |ob searching over Ih* potl four weeks; DATE = Dots job search began In weeks before grodualkxK GPA = reported gro<le point overoge.
Figure 6: Variable means for the third cluster (n=33).
Third cluster
The third cluster contained 33 students (22 male, 11
female) who were somewhat optimistic about the economy, but
were much less confident in their own ability than were their
peers (see Figure 4). These students exhibited Career Locus
of Control scores which were very external, falling more than
one standard deviation from the overall mean Career Locus of
Control score. These students were also far less confident in
their ability to look for and find a job than students in
other clusters. However, they were quite optimistic in their
79
view toward the economy and their own careers, with scores on
the Employment Outlook scale falling slightly above the
overall mean and scores on the scale measuring expectations
about business conditions falling well above the overall mean.
Their grades were slightly below average when compared to
other clusters, with a mean GPA of 2.89.
The job search activities of this group were average when
compared with other groups. Students in this group spent a
mean 18.1 hours during the previous four weeks looking for a
job, compared to the overall mean of 17.2 hours. The mean
number of job search steps engaged in was 5.18, compared to
the overall mean of 5.25 steps. The date reported for job
search initiation was about the same as the overall mean, with
this cluster's mean being 41.8 weeks before graduation and the
overall mean being 42.3 weeks before graduation. Although the
mean frequency of job search was about the same as that for
the entire sample, this group displayed the greatest variation
in frequency of job search. Over 30% of the cluster reported
that they looked for a job less than once per week. This
percentage was higher than for any other group, with only
18.7% of the entire sample reporting having looked for a job
less than once per week. Yet 33.3% of the group reported that
they looked for a job daily, again higher than any other
group, with only 17.8% of the entire sample reporting that
they looked for a job daily.
80
Students in this cluster were less likely than other
students to have been offered and to have accepted a job.
34.4% reported that they had received an offer for full time,
permanent employment upon graduation, 25% reported that they
had accepted a full time permanent job for after graduation,
and 69.7% said that they were still looking for a job.
Standardized Variable Means Fourth Cluster
1,50:-
1.25 = -
1.00:-
0.75 = -
0.50:-
0.25:-
0.00 j-
-0̂ 5:--0.50=-
-0.75;-
-1.00:-
-1.25=-
-0i*5 -0^16 -0.2.16 -0̂ 5
"1.50 " I I I I I I I I CARLOC JO0CONF OUTLOOK BUSCOND NUMSTEPS FREO JSHOURS DATE GPA
variable
CAKLOC = Carter Locus of Control: JOBCONF r Job S««kTng Confldonce; OUROOK = Envlayrntnl Outlook: BUSCOND = Butlmo Condlllora Eipactallsns; NUMSTEFS =
Nunto o( Job Search Steps Employed; FR£Q = Frequency of Job Snrch Behovlors; JSHOURS = # of hours tp«nt |ob Morehlng ovar Ih* post four wMkt;
DATE - Dole |ob swrch ba^ In waaks before groduotion: GPA s Self reported grade point avaroga.
Figure 7: Variable means for the fourth cluster (n=62).
Fourth cluster
The fourth cluster contained 62 students (25 male, 36
female, 1 omitted gender) who were far more pessimistic in
their outlook toward the job search, their career and business
81
conditions as a whole (see Figure 5). These students
exhibited Career Locus of Control scores which were more
external than the mean for the overall sample. They were also
less confident in their ability to look for and find a job
than were students in other groups, as evidenced by below
average scores on the Job Seeking Confidence scale. Both
their employment outlook and their expectations about business
conditions were well below the mean for the overall sample.
Their grades were lower than those of any other cluster, with
a mean GPA of 2.87.
Students in this cluster were less active in their job
search than were students in other groups. These students
reported having engaged in the fewest number of job search
steps of any group, X=4.76, compared to the overall sample
mean of 5.25 steps. These students also tended to look for a
job less frequently than any other group. 27.4% of this group
reported looking for a job less than once per week, 35.5%
weekly, 30.6% every couple of days. The percent of students
looking daily was the lowest of any group, only 6.5% compared
with 17.8% of the entire sample reporting that they searched
for a job daily.
This group was the least likely to have received and
accepted a job offer. 22.6% reported that they had received
an offer for full time, permanent employment upon graduation,
12.9% reported that they had accepted a full time permanent
82
Sfandardized Variable Means Fifth Cluster
1.50:
1.25 =
-1.50 I I I I I I ^ I I CARLOC JOBCONF OUTLOOK BUSCOND NUMSTEPS FReO JSHOURS DATE GPA
variable
CARLOC = CorAtr Locus of Control: JOSCONT = Job Soeking Confidence; OUTLOOK = Empkjymml Oullmic BLtSCOMO = Bu«InfS8 Condilions Exp«ctalions; NUMSTEPS =
Nurto of Job Search Steps Employed; FREQ = Frequency of Job Seorch Behaviors; JSHOURS = # of hours spent |ob seorchtng ovir the post tour weeks;
DATE = Date job sacrch began in weeks before groduatkxi: GPA = Sglf reported grode poTnt overage.
Figure 8: Variable means for the fifth cluster (n=40).
job for after graduation, and 80.3% said that they were still
looking for a job.
Fifth cluster
This group of 40 students (22 male, 18 female) tended to
manifest average scores for all but two variables: the Career
Locus of Control and Business Conditions Expectations. These
students appear to believe that they have a great deal of
control over their ability to find a job, with a mean Career
Locus of Control score which was more internal than for any
other group. Their confidence in their ability to look for
83
and find a job was average when compared with the entire
sample, as was their employment outlook. However, this group
was much more pessimistic in their expectations about
business conditions than any other group, as evidenced by a
Business Conditions Expectations score more than one standard
deviation below the overall group average. In addition, these
students reported grades higher than for any other group, with
a mean GPA of 3.14.
Students in this cluster tended to exhibit average levels
of job search behaviors for all measures including the number
of steps performed, the frequency of their job search, and the
number of hours spent looking for a job. The mean number of
job search steps employed by this group was 5.35, compared
with an overall mean of 5.25 steps. This group's frequency of
job search also was very similar to that of the entire sample:
47.5% of this group reported that they look for a job weekly,
compared with 37.6% of the entire sample; 27.5% reported
looking every couple of days, compared with 25.8% of the
entire sample; and 12.5% reported that they looked for a job
daily, compared with 17.8% of the entire sample. 12.6% of the
students in this cluster reported that they looked for a job
less than once per week, compared with 18.7% of the entire
sample.
This number of respondents who had received and accepted
job offers was about the same for this group as for other
groups. 50% reported that they had received an offer for full
84
time, permanent employment upon graduation, 37.5% reported
that they had accepted a full time permanent job for after
graduation, and 61.5% said that they were still looking for a
job.
Standardized Variable Means Sixth Cluster
1.50:
1.25:
1.00i
.50 I I I I " " ! — " " 1 " I " ' I CARLOC JOQCONF OUUOOK BUSCOND NUMSTCPS TREO JSHOURS DATE GPA
variable
CARLOC = C<r«<r Loon of Ccmtrsl: JOBCONT = Jeb SmkTnd ConUdDnce; OUaOOK = Enfbynwnl Outloolc BUSCONO = Butlrwss Condilloira Eiptctatlons: NUMSTEPS =
Nunto of Jcb Search Steps Employed; FREQ = Frtquwicy of Job Search Behaviors; JSHCXJRS = # of hours spirit job Marching evtr lha pott four WMkc
DATE = Data |ob starch bs^ in weeks before grodinllon; GPA = &tf reported grade point overage.
Figure 9: Variable means for the sixth cluster (n=35).
Sixth cluster
The last cluster contained 35 students (25 male, 10
female) who were confident and optimistic about their own
ability to find a job, yet pessimistic in their expectations
about business conditions and external in their locus of
control (see Figure 7). Individuals in this cluster tended to
85
be extremely external in their Locus of Control, much more
external than any other group, with a mean Career Locus of
Control score more than one standard deviation from the mean
for the entire sample. These individuals were confident in
their ability to look for and find a job, and optimistic about
the prospects for employment. However, their expectations
about business conditions as a whole were more pessimistic
than most students participating in the study. The grades for
students in this cluster tended to be average or just slightly
below, with a mean GPA of 2.93.
Students in this cluster tended to employ a greater
number of job search steps than did students in the entire
sample. The mean number of job search steps employed for this
group was 5.59, compared with 5.25 for the entire sample.
However, these students reported spending less time searching
for a job than did students in the overall sample. Students
in this cluster spent an average of 14.58 hours searching for
a job during the four weeks before receiving the survey. This
is slightly lower than the overall mean of 17.21 hours for the
entire sample. Over 25% of the students in this cluster
reported that they searched for a job less frequently than
once per week, 40% said they looked for a job weekly, 17,1%
said every couple of days, and 17.1% daily. These numbers
indicate that students in this cluster looked for a job
slightly less often than did students in the entire sample.
The mean date (41.39 weeks before graduation) for entry into
86
the job search was about the same as the mean for the entire
sample (42.34 weeks before graduation).
Students in this cluster were much more likely than other
students to have received and accepted an offer for full time
employment. If fact, this cluster contained more students who
had received and accepted job offers than any other cluster.
77.1% reported that they had received an offer for full time,
permanent employment upon graduation, 60% reported that they
had accepted a full time permanent job for after graduation,
and 40% said that they were still looking for a job.
MANOVA
Multi-variate analysis of variance was used to determine
whether clusters of job seekers formed on the basis of the
attitudinal variables differed in their ability (GPA) and job
search activities. Job search behavior variables including 1)
date for initiating job search, 2) number of job search steps
employed, 3) number of hours spent searching, and 4) frequency
of job search, were compared across clusters. The multi
variate F-statistic was statistically significant (F=1.56,
p<.05), indicating that the clusters differed on at least one
of the variables.
Univariate analysis of variance statistics were examined
to determine which variables differed. Two variables revealed
statistically significant differences: GPA (F=2.58, p<.05)
and date for initiating job search (F=3.12, p<.01). Tukey's
87
Studentized Range Test (Honestly Significant Difference) was
used to determine which clusters differed on these two
variables (see Table 10) .
Results indicated that the second cluster differed from
the fourth and first cluster in the date they initiated their
job search. Students in the second cluster tended to begin
their job search earlier than students in the other clusters.
These students also tended to be more optimistic in their
expectations about their own career and the economy as a
whole. Students belonging to the first and fourth clusters
tended to begin their job search later. Students in these
clusters also tended to be more pessimistic in their
employment outlook than were students in other clusters.
The fourth cluster differed from the first and the fifth
cluster in mean GPA. Students in the fourth cluster tended to
have lower GPAs than did students in other clusters. Again,
this cluster contained students who were less confident in
their ability to look for and find a job, and students who had
pessimistic expectations about their own careers and the
economy as a whole. Students in the first and fifth clusters,
whose GPAs tended to be higher, exhibited average job seeking
confidence and internal locus of control. Students in the
first cluster tended to be optimistic in their expectations
about business conditions, but pessimistic in their own
employment outlook. Students in the fifth cluster, on the
other hand, were pessimistic in their expectations about
88
business conditions, and average in their own employment
outlook.
Table 10: Differences in means between cluster on date of initiating job search and GPA.
Mean Mean Date GPA
(in weeks) First Cluster 34.66" 3.12® Second Cluster 52.59® 2.98®" Third Cluster 41.83®" 2 . 89®" Fourth Cluster 36.09" 2.87" Fifth Cluster 49.76®" 3 .14® Sixth Cluster 41.39®" 2 .94®"
Note: Looking down the columns, means with the same letter are not significantly different based upon Tukey's Studentized Range (HSD) with FWa=.05 for each variable. Means are reported as raw scores.
89
DISCUSSION
Expectancy theory hypothesizes that our behavior is
influenced by our expectations about the probability that we
will be rewarded for our efforts. As expectations become more
optimistic, we are motivated to increase our effort to obtain
that reward. The present study applies the basic principles
of expectancy theory to behavior in the job market. The study
was designed to explore differences in job seekers' attitudes
toward the job search process and related differences in
behavior in the job market. Specifically, it was hypothesized
that, among graduating university seniors, behavior in the job
market would depend in part upon their expectations about
whether their behavior would be rewarded. Those with
optimistic expectations about the job search would engage in
more job search activity than those with more pessimistic
expectations.
The study found real differences among job seekers in the
ways in which they search for a job and their attitudes toward
the job search process. The patterns produced by the cluster
analysis show some support for the hypothesis relating job
search behavior to expectations.
Attitudinal Differences Among Job Seekers
The differences in attitude between those who had and
those who had not secured employment at the time of the survey
is consistent with research involving unemployed adults.
90
There were statistically significant differences in attitude
between those who had and those who had not secured employment
at the time of the survey. Students who had found a job were
more confident in their ability to search for and find a job,
had a more positive employment outlook and had more optimistic
expectations about the economy than those who had not secured
employment. Although the differences were not statistically
significant, those who had secured employment also exhibited a
more internal locus of control, reported having engaged in
more job search behaviors, and had a slightly higher mean GPA
than did students who had not yet found a job.
These differences are not particularly surprising. One
would expect that those who had engaged in more job search
behaviors would be more likely to have found a job. It is
somewhat surprising, however, that the difference between
these groups was not larger. Perhaps more surprising is the
fact that the biggest difference between these groups was not
behavioral, but attitudinal. The largest differences between
those who had found a job and those who had not were the
differences in job search self efficacy and employment
outlook. Those who had found a job were much more optimistic
about their employment opportunities and had much more
confidence in their ability to find a job. It is possible
that these differences in attitudes spurred job search
activity, which in turn increased the likelihood of
employment. However, given the small differences in job
91
search behavior, it is more likely that the attitudinal
differences were caused by positive experiences in the job
market.
Differences in attitude between those who had found a job
and those who had not are consistent with previous research
involving unemployed adults. For example, researchers
exploring job search self-efficacy among those who have lost
their job have demonstrated that job search self-efficacy is
higher among those who have found a job than among those who
remain unemployed (Holmes & Werbel, 1992). Consistent with
Bandura's theory, job search self-efficacy seems to be
influenced by experience in the job market. It would appear
that this experience also influences a job seekers employment
outlook.
Students who have not yet graduated from college have
probably not yet become discouraged in their job search. The
attitudinal variables tended to produce scores which were more
optimistic than might be expected from a sample of unemployed
non-student adults. Scores on all the attitudinal variables
tended to have high means when compared to the range of
possible scores, reflecting the tendency toward a more
optimistic attitude among the college seniors in the study.
Finding a job probably increased scores on attitudinal
variables for many students. It is less likely that not
finding a job decreased attitudinal variable scores since
participants had not really had an opportunity to become
92
discouraged with the job market. Based upon past research,
those who had not found a job some time after graduation,
probably became less optimistic in their attitudes toward the
job market. Had the study been done after graduation, it is
very likely that the means would be lower for these variables
reflecting the negative effects of not finding a job on the
attitudes of some students.
Behavioral Differences Among Job Seekers
The results of this study suggest that real differences
exist among college students in their job search behaviors.
There also appear to be real differences in the methods used
by those who are successful and those who are not successful
in their job search. These differences in job search
behaviors suggest a difference in effectiveness of various
methods. Those who had obtained and/or accepted a job offer
were more likely to have telephoned prospective employers,
filled out an application for a job opening, obtained a job
interview and performed additional steps not listed on the
survey. Those who had not obtained and/or accepted a job
offer were more likely to have looked in the newspaper for
openings, talked with friends or relatives about job
prospects, and contact an employment agency or a job finding
center.
It would appear from these results that direct methods
such as calling an employer or going to fill out an
93
application, are more effective than less direct methods, such
as networking or looking in the newspaper for openings.
However, it could be that the steps utilized more frequently
by employed students were steps that are only taken by job
seekers in the final stages of the job search. For example,
one is often required to fill out an application at the tine
one is interviewed by the potential employer. This takes
place after the person's resume has been selected and the
person is in the final stages of job application. Interviews
are also among the last things employers do during the hiring
process, after other pre-screening takes place. Those who had
obtained interviews with potential employers also have more
reason to telephone that employer, whether that phone call is
returning the employer call or calling to see if a decision
had been made. It is logical, therefore, that those who had
obtained employment would be more likely to have engaged in
these behaviors.
It is more difficult to explain why students who had not
yet obtained or accepted a job offer were more likely to have
looked in the newspaper for openings, talked to a friend or
relative about job prospects, and contacted an employment
agency or job finding center. It is possible that these are
less effective methods for searching for a job. It is also
possible that these tend to be last resort types of behaviors
that are more likely to be used by those who have been
unsuccessful in finding a job.
94
Cluster Analysis Results
The cluster analysis produced some interesting patterns
of attitudes and behaviors, and provided some support for the
applicability of expectancy theory to job search behavior.
The main hypothesis posed by this study dealt with the effects
of expectations about the job market on job search behavior.
Specifically, it was hypothesized that those with pessimistic
expectations would be less motivated to search for a job.
Therefore, those who expected it to be difficult to find a job
would actually search less, rather than more, for a job. This
would be true in part because these individuals believe that
the probability is lower that they will be rewarded for their
efforts.
Several clusters seem to be supportive of the study's
hypothesis, especially the second and the fourth clusters.
According to expectancy theory, individuals who do not expect
to be rewarded will be less motivated to act and will exhibit
less effort than those with more optimistic expectations. The
second and fourth clusters represent students with very
optimistic and pessimistic expectations toward the job market,
based upon their scores on attitudinal variables.
The fourth cluster was the most pessimistic of all the
groups. According to the hypothesis, students who are very
pessimistic about finding a job should be less motivated to
engage in job seeking behavior. This seemed to be true for
this cluster, with mean job seeking behavior variables being
95
lower for Cluster Four than for any other cluster. These
students engaged in fewer job search steps, looked less
frequently, spent fewer hours searching and entered the job
market later than any other group in the study. These
students also reported lower GPAs than the students in any
other cluster. Like the employees in Reid's (1972) study of
recently laid off workers, those who believed it would be
difficult to find a job, seemed to avoid the job search
process. Also like the employees in Reid's study, these
students may have been less qualified than students in other
clusters, based upon their GPA. This may influenced job
search attitudes, which in turn lead to an avoidance of the
job search process. Because of this avoidance, this group is
less likely than any other to have found a job.
Because of the concurrent, self-report method of data
collection, one cannot be sure that the attitudes were the
cause of the behavior. Therefore, other explanations for the
pattern seen in the fourth cluster need to be considered. For
example, it is possible that the attitudes were the result of
experience in the job market. Since very few of the students
in this cluster had found jobs at the time they received the
survey, it is possible that negative experiences in the job
market led to negative, pessimistic attitudes. However, based
upon their self-reported job search activity, it appears this
group's experience in the job market had been very limited.
Because their search experience has been so limited, it is
96
difficult to imagine that this group could be discouraged
already.
The second cluster contained a pattern of variables which
also seems to support the hypothesis that attitudes influence
behavior in the job market. This group was the most
optimistic group in their attitudes about economic and job
market conditions and in their expectations about their own
ability to influence job search outcomes. This group also
engaged in the greatest degree of job search behaviors.
Students in this cluster engaged in more job search steps,
spent more time searching, looked for a job more often, and
tended to have entered the job market earlier than students in
other clusters. This cluster would seem to support the
hypothesis that expectations about success influence behavior,
and that those with more positive expectations for reward are
more likely to engage in the behaviors expected to bring that
reward.
This group also lends support for the importance of job
search activity, rather than qualifications, leading to
success in the job market. With a mean GPA that was average
when compared with the entire sample, this cluster was more
likely than any other cluster to have received and accepted an
offer for full time employment.
Again, because of the concurrent method with which the
data were collected, caution must be exercised in interpreting
these results. Again, we cannot assume that attitudes toward
97
the job search necessarily lead to increased activity in the
job market. Because of the high employment rate for this
cluster, it is very likely that experience in the job market
influenced attitudes and expectations about participants'
abilities to find jobs. An individual who has worked hard
and, as a result received a job offer, is much more likely
than other students to believe that 1) he or she has control
over the outcome in the job search process (Career Locus of
Control), 2) he or she is able to successfully perform the
steps necessary to obtain a job (Job Seeking Confidence), and
3) economic conditions are favorable for finding employment
(Employment Outlook and Business Conditions Expectations). So
although this cluster also demonstrates support for the
hypothesis that expectations influence behavior in the job
market, it is more open to other interpretations because of
the probable influence of experience in the job market on
attitudes.
The sixth cluster exhibited a pattern of variable means
which would seem to present the best support that experiences
in the job market influenced the attitudes and expectations of
the students. This group displayed an interesting profile of
scores, with extremely external locus of control scores and
pessimistic expectations about business conditions coupled
with a high degree of confidence in one's ability to find a
job and a positive employment outlook.
98
This unexpected pattern of attitudes is probably the
result of the students' experiences in the job market. Except
for the variable measuring the number of job search steps
employed, this group was below average in their self reported
job search activity. Yet this group was more likely than any
other group to have received and accepted an offer for full
time employment. This group seems to contain students who had
received jobs without really looking very hard as compared to
other students. In addition, based upon their GPAs, which
tended to be average or slightly below average, this group
would not appear to be more qualified than students in other
clusters. It is no wonder that these students would have high
employment expectations and a great deal of confidence in
their ability to find a job. It is also intuitive that these
students would exhibit external job search locus of control
based upon their experiences in the j ob market.
It is less clear how these experiences might lead to
pessimistic expectations about business conditions. It is
possible that this attitude was present before the job search
began. It is also possible that this pessimistic attitude was
the precursor which lead to lower levels of job search
activity. However, it is impossible to know what the pattern
of attitudes looked like before these students found
employment. It would be interesting to see how attitudes may
have changed over the course of the job search process.
99
Directions for Future Research
The present study examined job search attitudes and job
search behavior among college students. Differences were
found in the attitudes and activities of those who had found
and those who had not found employment. This study did not
examine the long term effects of the search activities on the
job which was eventually found. It would be interesting to
find out whether greater degrees of job search behavior lead
to a better match between the individual and the job. Future
research examining job satisfaction related to these job
search activities is needed.
The cluster analysis produced results that seem to
support the study's hypothesis at least to some extent. There
do seem to be differences in behavior related to differences
in job search attitudes. However, the inclusion of additional
attitudinal variables in the cluster analysis may have helped
to better define the clusters so as to better predict job
search behavior. Clearly there are other influences on job
search behavior besides one's expectations. Including
additional variables in the analysis may have helped clarify
the role of expectations by taking into account the effects of
these other variables.
One variable that was not included that may have
influenced the onset and frequency of job search behavior was
the importance of academic achievement to the job seeker.
Performing well in classes may have been more important to
100
some individuals than to others. For others, getting a good
job is the reason for being in school; and grades in the last
semester are not as important as finding a good job. It is
possible that those who felt strongly about performing well in
classes were less likely to take time away from course-work to
search for a job, regardless of their expectations about their
ability to get a job. On the other hand, those for whom
college is only a means to an end (that end being employment) ,
may be more likely to spend a great deal of time during their
last semester of college looking for a job.
A related variable which may have influenced job search
behavior is employment commitment. Research has shown that
individuals differ in how much they value employment and the
importance that work plays in their lives (Warr & Jackson,
1984). Rowley and Feather (1987) found that employment
commitment was related to job search activities among
unemployed men, with those who were more committed looking
more frequently than those who were less committed.
Employment commitment may have also influenced job search
behavior among students participating in the present study.
Finally, regardless of one's expectations, some
individuals are simply better at organizing their time, and
are more conscientious in pursuing whatever tasks they
undertake. Inclusion of variables measuring time structure
(Feather & Bond, 1983) and conscientiousness (Schmit, Amel, &
101
Ryan, 1993) may have contributed to the understanding the
relationships examined in this study.
Because there are so many possible influences on job
search behavior, it was impractical in include them all in the
present study. This study chose to limit the scope to
examination of the influence of expectations on job search
behavior. The relationship between attitudes and behavior is
always complex. Clearly the relationship between job search
expectations and job search behavior is also complex.
Additional research is needed which includes larger sample
sizes, as well as additional variables which may confound the
relationship between expectations and job search behavior.
Finally, there may be limits to the generalizability of
the findings. The present study examined the effects of
expectations on job search behaviors among university seniors.
Clearly there may be differences in the job search behaviors
of university seniors and other populations. For example, the
university students have not truly had an opportunity to
become discouraged in their job search. Therefore, the
effects of discouragement on the job search could not be
observed. In addition, the students in this study represented
a wide variety of majors and job choices. Clearly students
from various majors experience very different job prospects.
In some occupations, job are more easily obtained than in
others. This may have influenced job search activities as
well as attitudes. We cannot tell from the present study
102
whether the results had been different if another population
of students, say trade school students, had been used instead.
103
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