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Generational Differences in Work Ethic: An Examination of Measurement Equivalence Across Three Cohorts

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Purpose The purpose of this study was to examine the differences across three generational cohorts (Millennials, Generation X, and Baby Boomers) on dimensions of the work ethic construct using the multidimensional work ethic profile (MWEP). Design/Methodology/Approach Data were collected from multiple samples and combined into a large database (N = 1860). Measurement equivalence was examined using Raju et al.’s (1995) differential functioning of items and tests (DFIT) procedure. Findings Several dimensions of the MWEP were not equivalent across cohorts, indicating that item content may not operate in the same manner across groups. When equivalent, several significant mean differences were detected across cohorts, indicating that respondents do differ in important work-related attitudes and behaviors. Implications Despite several reviews of generational differences across cohorts, relatively few empirical examinations have been undertaken, and no studies have yet examined the measurement equivalence of constructs across generational cohorts. These findings provide evidence that differences do exist across cohorts on dimensions of work ethic, and some differences may be a result of respondents interpreting content in different ways. Managers of multigenerational employees should consider these differences in managing employees and conflict that may arise as a result. Originality/Value This is one of the first studies to provide empirical evidence of generational differences in the work ethic construct. In addition, this is the first study to evaluate the measurement equivalence of a work ethic inventory or any other work related individual difference construct across generational cohorts.
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Generational Differences in Work Ethic: An Examination
of Measurement Equivalence Across Three Cohorts
John P. Meriac David J. Woehr Christina Banister
ÓSpringer Science+Business Media, LLC 2010
Abstract
Purpose The purpose of this study was to examine the
differences across three generational cohorts (Millennials,
Generation X, and Baby Boomers) on dimensions of the
work ethic construct using the multidimensional work ethic
profile (MWEP).
Design/Methodology/Approach Data were collected from
multiple samples and combined into a large database
(N=1860). Measurement equivalence was examined
using Raju et al.’s (1995) differential functioning of items
and tests (DFIT) procedure.
Findings Several dimensions of the MWEP were not
equivalent across cohorts, indicating that item content
may not operate in the same manner across groups. When
equivalent, several significant mean differences were
detected across cohorts, indicating that respondents do
differ in important work-related attitudes and behaviors.
Implications Despite several reviews of generational
differences across cohorts, relatively few empirical exam-
inations have been undertaken, and no studies have yet
examined the measurement equivalence of constructs
across generational cohorts. These findings provide evi-
dence that differences do exist across cohorts on dimen-
sions of work ethic, and some differences may be a result
of respondents interpreting content in different ways.
Managers of multigenerational employees should consider
these differences in managing employees and conflict that
may arise as a result.
Originality/Value This is one of the first studies to pro-
vide empirical evidence of generational differences in the
work ethic construct. In addition, this is the first study to
evaluate the measurement equivalence of a work ethic
inventory or any other work related individual difference
construct across generational cohorts.
Keywords Work ethic Generational cohorts
Millennials Generation X Baby Boomers
Arguably no aspect of potential differences across gener-
ational cohorts has received as much attention as that
pertaining to work-related attitudes and values. Genera-
tional cohorts reportedly hold different perceptions of
each other, which can result in conflict and misunder-
standings in the workplace. Numerous explanations of
how these conflicts emerge and their implications exist in
both popular press articles (e.g., Erickson 2008; O’Con-
nell, 2008) as well as books published on the topic (e.g.,
Lancaster & Stillman, 2002). In addition, a recent study
evaluated perceptions of Millennials (the latest cohort to
reach the workplace), and found that members of earlier
cohorts had differing views of Millennials regarding work-
related characteristics (Pham et al. 2008). However, as
noted by Macky et al. (2008), these views have rarely
been challenged or subjected to empirical scrutiny.
Moreover, while previous research has focused on mean
differences across cohorts on measures of work-related
attitudes and values, little or no research has examined the
measurement equivalence of specific measures across
generations to determine whether generations respond to
item content in the same manner. In this study, we seek to
J. P. Meriac (&)C. Banister
Department of Psychology, University of Missouri—St. Louis,
425 Stadler Hall, One University Boulevard, St. Louis,
MO 63121-4499, USA
e-mail: meriacj@umsl.edu
D. J. Woehr
Department of Management, The University of Tennessee,
Knoxville, TN, USA
123
J Bus Psychol
DOI 10.1007/s10869-010-9164-7
fill this gap with respect to an important work-related
construct, work ethic.
We examine three generations in this study: Baby
Boomers (1946–1964), Generation Xers (1965–1980), and
Millennials (1981–1999). It has been widely postulated that
generational cohorts develop similarities in their attitudes
and beliefs based on shared life experiences. As a result,
generational cohorts have identifiable characteristics on
which they differ (Kupperschmidt 2000). Several authors
(Cennamo and Gardner 2008; Dries et al. 2008; Duchscher
and Cowin 2004; Lancaster and Stillman 2002; Wong et al.
2008; Zemke et al. 1999) have provided extensive detail
regarding how different cohorts’ shared life experiences
have impacted their attitudes toward work. Views toward
life activities, particularly work, are shaped by the social
context in which people develop (Dries et al. 2008). The
influences that impact a person’s development include
peers, parents, and popular culture, as well as prominent
events (Twenge and Campbell 2008). As generational
cohorts experience different events in their formation of
attitudes and beliefs, they come to exhibit distinct group
differences across cohorts. In this study, we are specifically
interested in the work ethic construct and it’s relation to
generational cohorts.
Work Ethic
Work ethic may be defined as a set of beliefs and attitudes
reflecting the fundamental value of work (Miller et al.
2002). Drawing on the large body of literature stemming
from Weber’s (1904–1905/1958) original work, Miller
et al. (2002) argue that work ethic is not a single unitary
construct, but a constellation of attitudes and beliefs per-
taining to work behavior. They posited that work ethic: (a)
is multidimensional; (b) pertains to work and work-related
activity in general, not specific to any particular job (yet
may generalize to domains other than work, such as school,
hobbies, etc.); (c) is learned; (d) refers to attitudes and
beliefs (not necessarily behavior); (e) is a motivational
construct reflected in behavior; and (f) is secular, not
necessarily tied to any one set of religious beliefs. On the
basis of previous literature as well as original empirical
research, Miller et al. identified seven components or
dimensions that they suggest constitute the work ethic
construct. The dimensions are labeled ‘centrality of work’,
‘self-reliance’, ‘hard work’, ‘leisure’, ‘morality/ethics’,
‘delay of gratification’, and ‘wasted time’ (see Miller et al.
(2002) for a full definition of each dimension and items).
While there has been much discussion of potential gen-
erational differences with respect to work ethic (e.g.,
Duchscher and Cowin 2004; Lancaster and Stillman 2002),
little, if any, empirical research has directly assessed these
potential differences. Smola and Sutton (2002) examined
generational differences in work values across samples from
1974 and 1999, and concluded that differences on dimen-
sions of the construct were attributable more to cohort
effects than age. However, their sample did not include
enough Millennials to include in their analyses. Pogson et al.
(2003) used the Multidimensional Work Ethic Profile
(MWEP; Miller et al. 2002) to directly examine differences
in work ethic as a function of one’s career stage. Specifi-
cally, Pogson et al. used age to assign individuals to career
stage levels and demonstrated differences across career
stages with respect to various dimensions of work ethic. One
limitation of the Pogson et al. study, however, was the use of
a cross-sectional design in which individuals at various
career stages completed the work ethic measure. With this
approach, any generational differences are confounded with
age/career stage. Thus, in this study we examine work ethic
differences as a function of generational cohort while at
least partially controlling for age.
Another limitation of previous research has been an
exclusive focus on mean differences in work-related
values, attitudes, and beliefs as a function of age or gen-
erational cohort without an explicit consideration of the
extent to which the measurement instruments are actually
assessing the same thing. Thus we also sought to provide a
direct test of the measurement equivalence of the MWEP
across generational cohorts.
Measurement Equivalence
Measurement equivalence reflects the extent to which a
measure assesses a construct the same way for two or more
groups. More technically, measurement equivalence may
be defined as the extent to which individuals from different
groups, who are identical on the construct of interest (e.g.,
work ethic), have equal probabilities of attaining the same
score on a test of that construct. Any meaningful cross-
group comparisons are predicated on cross-group mea-
surement invariance. As stated by Vandenberg and Lance
(2000), ‘‘Violations of measurement equivalence assump-
tions are as threatening to substantive interpretations as is
an inability to demonstrate reliability and validity’’ (p. 6).
Several studies have directly examined the cross-group
measurement equivalence of Miller et al.’s (2002) MWEP.
Specifically, Woehr et al. (2007) demonstrated measure-
ment equivalence of Spanish and Korean language versions
of the MWEP with the original English language version.
In addition, Meriac et al. (2009) demonstrated measure-
ment equivalence of the original English version of the
MWEP across male and female respondents. To date,
however, no research has examined measurement equiva-
lence with respect to generational cohorts.
J Bus Psychol
123
Approaches to the analysis of measurement equivalence
are based on classical test theory and include mean
differences across groups, relationships with external
variables, internal covariance differences across item
responses, or multi-group confirmatory factor analysis
(CFA). While Vandenberg and Lance (2000) indicated that
a multi-group CFA approach was the most common
method for assessing measurement equivalence, an equally
appropriate approach is based on item response theory
(IRT; Embretson and Reise 2000). While a full comparison
of CFA and IRT approaches is beyond the scope of this
study, IRT-based approaches offer advantages for item-
level comparisons as well as allowing test or scale level
comparisons (Meade and Lautenschlager 2004; Zickar and
Broadfoot 2009). Thus, we use an IRT-based approach to
measurement equivalence in this study. In IRT terminol-
ogy, a lack of measurement equivalence at the item level is
referred to as differential item functioning (DIF), and a
lack of equivalence at the scale/test level is referred to as
differential test functioning (DTF). Further, DTF is largely
an additive function of DIF. Readers interested in a more
thorough comparison of CFA and IRT-based approaches
for the assessment of measurement equivalence are
encouraged to see Meade and Lautenschlager (2004).
In sum, although several authors have posited differ-
ences among generations relevant to work ethic, little
research has empirically examined differences among the
dimensions of work ethic as a function of generational
cohort. In this study, we attempt to assess the extent to
which a specific measure of work ethic (i.e., the MWEP)
demonstrates measurement equivalence across cohorts.
Then, where justified on the basis of equivalent measure-
ment, we also examine mean differences across genera-
tional cohorts.
Method
Participants
Data for this study were drawn from a large dataset collected
over a 12-year period ranging from 1996 to 2008. To obtain
a large, comprehensive sample of respondents from each
cohort, data were collected from business students at a large
Southeastern university and combined with portions of
responses included in Miller et al. (2002). This total dataset
consisted of 1,860 participants. Across the total sample, the
mean age at which participants completed the MWEP was
24.67 (SD =8.75), 55.3% were male, 73% were students,
87% indicated that they were employed either full- or part-
time, and 86% were Caucasian. Data for each participant
included the year in which they completed the MWEP as
well as their age at that time. Based on this information, we
were able to compute participants’ year of birth as the year
in which they completed the MWEP minus their age at
MWEP completion (e.g., 1996 -20 =1976). We then
grouped participants into one of three generational cohorts
based on their year of birth using the dates used by Lancaster
and Stillman (2002). Specifically, Baby Boomers (n=251)
were born between 1946 and 1964, Generation Xers
(n=1021) were born between 1965 and 1980, and Mill-
ennials (n=588) were born between 1981 and 1999.
Demographic characteristics for each cohort are presented
in Table 1. All three groups were approximately equivalent
with respect to gender and racial composition. In addition, it
is important to note that Generation Xers and Millennials
were not significantly different with respect to the age at
which they completed the MWEP. However, Baby Boomers
were significantly older than the other two cohorts. Thus,
while generational cohort may be confounded with age and
Table 1 Demographic characteristics of generational cohorts
Cohort Age Gender (%) Race (%) Student status (%)
Baby Boomers (N=251) M=44.5 (SD =5.2) Male =67
Female =33
AA =2
C=90
H=6
Other =3
S=2
NS =98
Generation X (N=1071) M=22.62 (SD =5.04) Male =51.5
Female =48.5
AA =1
C=85
H=11
Other =3
S=80
NS =20
Millennials (N=588) M=21.3 (SD =1.6) Male =52
Female =48
AA =6
C=86
H=4
Other =4
S=99
NS =1
AA African-American, CCaucasian, HHispanic, Sstudent at time of data collection, NS not student at time of data collection
J Bus Psychol
123
career stage for any tests between Baby Boomers and the
other two cohorts, no such confound exists between Gen-
eration Xers and Millennials.
Work Ethic Measure
All participants in this study completed the Multidimen-
sional Work Ethic Profile (MWEP; Miller et al. 2002). The
MWEP is a 65-item self-report scale that measures seven
dimensions of ‘work ethic’. Self-reliance, morality/ethics,
leisure, hard work, and centrality of work are each mea-
sured with 10 items, and wasted time and delay of grati-
fication are measured with 8 and 7 items, respectively. All
items are rated on a 5-point Likert-type scale (1 =strongly
disagree to 5 =strongly agree). As reported by Miller
et al. (2002), the MWEP has internal consistency estimates
ranging from .75 to .89 across the seven dimensions, an
acceptable seven-factor structure as evident from CFA
results, the dimensions are related to and distinct from
theoretically meaningful external constructs (i.e., conver-
gent and discriminate validity), and it demonstrates crite-
rion-related validity evidence as a predictor of work
performance.
Analyses
We estimated item parameters with MULTILOG 7.03
(Thissen 2003), using Samejima’s (1969) graded response
model. To equate parameters so they could be compared
across groups, we used the Stocking and Lord (1983)
procedures, implemented in the EQUATE 2.1 program
(Baker 1995). In each two-group (i.e., pairwise) compari-
son, one group was designated the reference group and the
other was designated the focal group: (1) Generation Xers
(reference group) and Baby Boomers (focal group), (2)
Generation Xers (reference group) and Millennials (focal
group), and (3) Baby Boomers (focal group) and Millen-
nials (reference group). Equating is a two-step process that
necessitates choosing items that do not exhibit DIF to serve
as ‘linking’ items (Flowers et al. 1999). We first used all
items in the subscale as linking items, identifying items
that exhibit DIF, then re-scaling items using non-DIF items
as linking items.
Finally, we evaluated differential functioning using by
Raju’s (1999) DFITPS6 program. This program computes
three indices of differential functioning, including non-
compensatory DIF (NCDIF), compensatory DIF (CDIF),
and DTF. The NCDIF index represents the average squared
difference between the two groups’ item-level true scores
(e.g., whether items exhibit DIF independent of the other
items in the test), and the CDIF index represents the
cumulative impact in DTF that each item contributes. The
NCDIF index utilizes a cutoff value to determine whether
items exhibit DIF independent of other items (i.e., without
the influence of other items). Based on recommendations
by Raju (1999), the cutoff value of .096 was used for
determining whether DIF was present since the MWEP
items were rated on a five-point scale. The DTF value is
computed by cumulatively adding CDIF values (i.e., con-
sidering the impact of other items on differential func-
tioning at the test level). The DTF cutoff is determined by
multiplying this cutoff score by the number of items, such
that the cutoffs for DTF for five of the MWEP dimensions
were .960 (since they contain 10 items), .768 for the
dimension with 8 items (wasted time), and .672 for the
dimension with seven items (delay of gratification).
Results
Assumption Checks and Parameter Estimation
IRT parameter estimation is predicated on the assumption
that the underlying construct is unidimensional. Miller
et al. (2002) provide clear evidence for the unidimension-
ality of each of the seven MWEP subscales. However, as a
direct assumption check, we also assessed the dimension-
ality of each subscale for each generational cohort in this
study using principal axis exploratory factor analysis.
Specifically, within each dimension, the average percent
variance explained by the first factor was 43.64%
(Min =37.92, Max =50.27) for Baby Boomers, 54.19%
(Min =39.01, Max =80.56) for Generation Xers, and
56.90% (Min =46.71, Max =79.50) for Millennials.
These values were all well beyond the 20% rule of thumb
recommended by Reckase (1979). In addition, visual
examination of the scree plots strongly indicated that a
single dominant factor best represented the data. We sub-
sequently proceeded to conduct the IRT analyses. Item
parameters were used as the input for the EQUATE and
DFIT procedures. Complete factor analysis information
and item parameter estimates are available from the first
author upon request.
DFIT Analyses
Our primary goal in this study was to determine whether
each of the seven subscales (i.e., dimensions) of the MWEP
was invariant across each of the generational cohorts.
Consequently, we first focused on the DTF index. If this
index indicated a lack of equivalence across any pairing of
generational cohorts, we then looked at differences with
respect to individual items (i.e., CDIF values). To the
extent that DTF is driven by relatively few scale items, it is
possible to eliminate those items and make comparisons
based on the mean response to the remaining items. If,
J Bus Psychol
123
however, a large proportion of the items on a given
dimension are not equivalent across groups, comparisons
are not warranted.
As summarized in Table 2, of the 21 comparisons (three
generational cohorts measured on each of the seven MWEP
dimensions), a lack of scale equivalence was evident for
nine. More specifically, when comparing Generation Xers
and Baby Boomers, measurement equivalence was sup-
ported for five of the MWEP dimensions (self-reliance,
leisure, centrality of work, wasted time, and delay of
gratification) and a lack of equivalence was indicated for
the morality/ethics and hard work dimensions. Similarly,
when comparing Millennials and Baby Boomers, mea-
surement equivalence was supported for six of the MWEP
dimensions (self-reliance, leisure, centrality of work,
wasted time, hard work, and morality/ethics) and a lack of
equivalence was indicated for delay of gratification.
However, when comparing Generation Xers and Millen-
nials, a lack of equivalence was indicated for six of the
seven MWEP dimensions (i.e., equivalence was supported
only with the leisure dimension).
Next, we examined item-level differences to provide a
more in depth analyses of the lack measurement equiva-
lence. Here we examined CDIF indices as they indicate the
relative contribution of each item to overall DTF. On two
of the nine comparisons for which a lack of measurement
equivalence was initially indicated, this difference was
attributable to relatively few items. Specifically, when
comparing Millennials and Baby Boomers, results revealed
that the lack of test equivalence for the delay of gratifica-
tion subscale was attributable to two items. Similarly, when
comparing Generation Xers and Baby Boomers, results
indicated that the lack of test equivalence for the hard work
subscale was due to one item. The specific items demon-
strating a lack of equivalence are presented in Table 3.
Further, given that the majority of items on these subscales
were equivalent across cohorts, it is appropriate to use
these items as a scale to assess the level of work ethic on
these dimensions. Consequently, we dropped the three
non-equivalent items (presented in Table 3) in all further
comparisons across cohorts.
Examination of the item-level differences for the
non-equivalent scales for the Millennial and Generation X
cohorts, however, revealed that the lack of equivalence was
pervasive and consistent across all or nearly all of the items
on each subscale. When comparing Generation Xers and
Millennials on the remaining dimensions, both item and
test-level indices indicate that individuals from these
cohorts are interpreting item content in different ways.
Accordingly, any differences among means on these
dimensions may be indicative of different interpretations of
item content, rather than a reflection of actual work ethic.
In other words, respondents from different cohorts may not
be interpreting content in the same way on these particular
items. Hence, with the exception of leisure, the majority of
MWEP dimensions are not comparable between Millen-
nials and Generation Xers.
Examination of Mean Differences
We next looked at the pattern of mean differences across
the three generational cohorts. Descriptive data for each of
the seven MWEP scales is presented in Table 4. One-way
ANOVAs indicated a significant main effect for genera-
tional cohort on all of the MWEP dimensions except lei-
sure. Moreover, post hoc comparisons revealed a consistent
trend such that Baby Boomers were significantly higher
than both Generation Xers and Millennials on all dimen-
sions except leisure. In addition, Millennials were signifi-
cantly higher than Generation Xers on three dimensions
(morality/ethics, hard work, and delay of gratification) and
Table 2 Differential test functioning values among generational
cohorts
Dimension Boom–Gen X Gen X–Mill Boom–Mill
Self-reliance .152 14.580 .870
Morality/ethics 289.448 199.609 .295
Leisure .076 .926 .013
Hard work .961 (.385) 31.234 .190
Centrality of work .044 57.776 .329
Wasted time .239 38.554 .633
Delay of gratification .014 7.131 2.021 (.087)
Values in italics were not equivalent across cohorts. Values in
parentheses represent DTF indices after removing items. Complete
DFIT indices are presented in the appendix
Boom Baby Boomers, Gen X Generation X, Mill Millennials
Table 3 Items with DIF removed to allow mean comparisons
Generational comparison MWEP dimension Non-equivalent items
Baby Boomers versus Generation X Hard work By working hard a person can overcome every obstacle that life presents.
Baby Boomers versus Millennials Delay of gratification The best things in life are those you have to wait for.
The only way to get anything worthwhile is to save for it.
J Bus Psychol
123
not significantly different on four dimensions (leisure, self-
reliance, centrality of work, and wasted time). This pattern
appears to suggest that Generation Xers manifest the
lowest level of work ethic across the three cohorts. How-
ever, it is important to note that, based on the tests for
measurement equivalence, all comparisons between Mill-
ennials and Generation Xers with the exception of leisure
are based on non-equivalent scales. Thus, it is impossible
to determine whether the mean differences reflect true
differences across these cohorts or simply measurement
differences. Similar interpretation issues arise with com-
parisons between Baby Boomers and Generation Xers on
the morality/ethics dimension. Finally, effect size estimates
(Cohen’s d) are also presented in Table 4for all compar-
isons based on equivalent scales. Examination of these
estimates indicates that most mean differences are at least
moderate in magnitude, suggesting meaningful differences
across cohorts.
Discussion
A great deal of the published literature on differences across
generational cohorts, especially Millennials, has been based
on limited empirical data (Macky et al. 2008). Instead, many
previous studies have focused on subjective perceptions or
anecdotal evidence reported in interviews. This study pro-
vides empirical evidence supporting differences among
generational cohorts with respect to work ethic. However,
we also found that in many cases direct examinations of
mean differences might be misleading because different
generational cohorts may be interpreting scales differently.
Somewhat surprisingly, we found that this lack of
equivalence was greatest between the two most recent
cohorts to enter the workforce (i.e., Generation Xers and
Millennials). Yet, for the most part both of these cohorts
demonstrated scale equivalence with Baby Boomers.
Here it is important to note that Generation Xers in our
study did not significantly differ from Millennials with
respect to the age at which they completed the MWEP, but
both were significantly younger than participants repre-
senting the ‘Baby Boomer’ cohort. If measurement dif-
ferences were attributable to other variables (i.e., age or
career stage), one would expect to see larger differences
between Baby Boomers and the other two cohorts. In fact,
results pertaining to measurement equivalence indicate the
opposite—while Baby Boomers were significantly older
than both Generation Xers and Millennials, they demon-
strated similar response tendencies to both groups. Thus,
differences in test functioning between Generation Xers
and Millennials could not be due to differences in age or
career stage.
Mean differences between Baby Boomers and the two
other cohorts, however, may reflect age-related changes to
some extent. Specifically, they are significantly higher in
several dimensions of work ethic, so the possibility that age
has some impact on differences cannot be ruled out. As
previous studies have noted, these differences may be
partially attributable to age or career stage (Pogson et al.
2003). However, our findings also suggest that Generation
Xers and Millennials demonstrate several differences in
their response tendencies across dimensions. Although this
lack of equivalence precludes a meaningful comparison of
mean differences on six of the MWEP dimensions, the lack
of equivalence suggests that the groups respond differ-
ently (i.e., they may not be interpreting item content
Table 4 Mean item response levels on each mwep dimension and effect sizes across generational cohorts
Dimension Mean differences FCohen’s d
Baby Boomers Generation X Millennial BX BM XM
Mean SD Mean SD Mean SD
Self-reliance 3.35
a
.65 3.00
b
.79 3.00
b
.74 23.74* .46 .49
Morality/ethics 4.48
a
.53 2.84
b
1.46 3.33
c
1.34 156.17* .99
Leisure 2.91
a
.58 2.98
a
.63 3.03
a
.85 3.44 -.11 -.15 -.09
Hard work 3.79
a
.68 2.93
b
1.05 3.20
c
1.02 78.15* .87 .63
Centrality of work 3.87
a
.54 3.04
b
.90 3.07
b
.89 99.69* .98 1.00
Wasted time 3.84
a
.52 3.04
b
.84 3.08
b
.79 109.69* 1.01 1.06
Delay of gratification 3.42
a
.69 2.87
b
.90 3.10
c
.88 48.19* .64 .39
Values with different superscript letters in each row are significantly different, P\.01. Effect size estimates were not conducted for comparisons
that were not equivalent across groups
*P\.01
BX Baby Boomers compared with Generation X, XM Generation X compared with Millennials, BM Baby Boomers compared with Millennials
J Bus Psychol
123
consistently). Importantly, these findings do not support a
linear trend in one’s level of work ethic as a function of age
or career stage.
In evaluating generational differences on constructs
such as work ethic, researchers may have been premature
in evaluating mean differences to begin with. The results
of this study demonstrate, at least with the MWEP, sev-
eral comparisons may not be substantively meaningful
due to the lack of equivalence across cohorts. As indi-
cated in Table 2, several of the comparisons were not
equivalent, even when dropping a few of the items that
exhibited DIF. Future research should attempt to deter-
mine why we do not find equivalence across all cohorts.
An examination of the items dropped as presented in
Table 3may shed light on this issue. In comparing Baby
Boomers and Generation Xers on the hard work item that
was removed, Baby Boomers developed in a time of great
prosperity and saw effort lead to success, where Gener-
ation Xers were exposed to a much different environment
that may have fostered different expectations regarding
the results of their efforts (Lancaster and Stillman 2002).
Examination of the item parameters revealed that the item
was more discriminating for Baby Boomers, indicating
that it is more effective at identifying differences among
them, and was higher in its location on the latent trait
continuum, indicating that it is more effective at mea-
suring the construct at high levels of hard work compared
with Generation Xers. Hence, the idea that one can
‘overcome every obstacle’’ may hold different meaning
for these groups. One could speculate on the various
reasons why other items were invariant on other dimen-
sions. Examining item parameters may suggest what
content may be interpreted inconsistently across cohorts.
In this study, no consistent pattern was evident across
items or subscales between cohorts. However, specific
content of items that possess DIF may still uncover rea-
sons for differences across cohorts. Interested readers are
referred to the Miller et al. (2002) study where a full list
of items is provided.
Regarding differences in the level of work ethic across
cohorts, the findings are less clear due to the lack of
equivalence, primarily between Generation Xers and
Millennials. The only dimension that allowed for a com-
parison across all three cohorts (leisure) indicated that there
were no significant differences between them. For the
remaining dimensions that were equivalent between Baby
Boomers and the other two cohorts, Baby Boomers
reported higher levels of work ethic on all dimensions. In
most cases, these differences were practically significant as
indicated by the Cohen’s dvalues reported. Three dimen-
sions were significantly different between Generation Xers
and Millennials, but given the lack of measurement
equivalence, what this means is unclear.
Limitations and Future Directions
In this study, age is confounded with generation, at least in
comparisons between Baby Boomers with the other two
cohorts. Demographic characteristics indicate that the
mean age of the baby boomers at the time of testing was
roughly 20 years greater than either the Generation X or
Millennial respondents. Accordingly, one might speculate
that differences are based on a person’s age or possibly
work experience. However, as the Generation Xers and
Millennials were approximately the same age at the time of
data collection, this confound is less of an issue with these
comparisons. Hence, the lack of equivalence across these
samples is more attributable to generational cohort rather
than other explanations like age or career stage. In addition,
previous research examining these effects lends support to
generational differences in comparison with other vari-
ables. Smola and Sutton (2002) used a longitudinal design
to evaluate generational differences using a similar con-
struct, work values, and found that a person’s generational
cohort had a substantially greater impact on observed dif-
ferences in work values than did their age or experience. In
addition, ter Bogt et al. (2005) conducted a longitudinal
study beginning during adolescence and found that work
ethic was a very stable construct, where levels of work
ethic of adolescents were strongly related to levels of work
ethic during adulthood.
Another perspective on these differences is that one’s
career stage might impact their level of work ethic. Pogson
et al. (2003) demonstrated that work ethic increases as a
function of one’s career stage. As mentioned above, the fact
that cohorts differ in employment or student status signals
potential differences in career stage. Also, as pointed out by
a reviewer, cohorts may further differ in other unmeasured
variables such as their socioeconomic status, which might
be related to work ethic (Cherrington et al. 1979). Future
research may be able to more effectively determine whether
differences in work ethic are attributable more to age,
generational cohort, career stage, or other variables by
implementing a method that allows for the examination of a
cross-lagged effect. Although it would be very difficult to
conduct such a study that includes all three cohorts such as
in this study, Millennials, Generation Xers and future gen-
erations could be studied in this capacity. Further, in this
study groups differed in their sample sizes, where there were
fewer Baby Boomers than Generation Xers or Millennials.
Given that IRT parameter estimates are more stable with
larger sample sizes, more stable estimates might be obtained
by including more Baby Boomers.
It is important to determine whether the attitudinal and
motivational proclivities of members of each cohort are
manifested in important outcomes relevant for organiza-
tions. The large differences in several dimensions of work
J Bus Psychol
123
ethic may contribute to misunderstandings, differences in
work-related expectations, or other sources of conflict
among members from different cohorts. However, the
extent to which these relationships actually exist has not
been thoroughly examined. Much like research on gener-
ational differences, any evidence that exists at this point
has been based on speculation or anecdotal reports rather
than empirical research. Future studies should examine
how generational differences in work ethic impact impor-
tant organizational outcomes (as well as other motivational
or attitudinal constructs for that matter).
Summary and Conclusions
Generational cohorts differed on several dimensions of
work ethic, but this goes beyond simple mean differences.
The lack of measurement equivalence found in several
comparisons indicates that generations may not always
see eye-to-eye due to different interpretations of item
content. Much of the previous literature made assertions
on differences among cohorts, but has not addressed the
issue of whether comparisons are using equivalent mea-
sures. This study provides important empirical evidence
to confirm that cohorts do in fact differ on their level of
work ethic, but in more complex ways than previously
suggested.
Appendix
Tables 5,6,7include all DFIT results. Indices reported are
based on all items in each MWEP subscale.
Table 5 Millennials and Baby
Boomers: DIF and DTF
estimates for MWEP subscales
a
Dimension exhibited
differential test functioning
Item SR ME LE HW CW WT DG
NCDIF
1 .069 .115 .128 .012 .066 .002 .272
2 .041 .415 .105 .002 .115 .003 .073
3 .021 1.498 .009 .008 .064 .060 .006
4 .075 .316 .126 .006 .221 .029 .143
5 .025 .556 .006 .044 .023 .041 .019
6 .004 1.834 .101 .032 .009 .142 .374
7 0.057 0.179 0.006 0.007 0.210 0.060 0.314
8 0.125 0.310 0.464 0.016 0.008 0.003
9 0.078 1.641 0.061 0.144 0.124
10 0.016 0.495 0.025 0.011 0.158
CDIF
1 0.001 0.080 -0.015 -0.005 -0.105 -0.027 0.713
2 0.049 0.067 -0.018 0.014 0.170 0.045 0.380
3 0.121 -0.065 -0.008 0.034 -0.109 0.188 -0.102
4 0.103 0.057 0.026 0.021 0.230 0.135 -0.435
5 0.039 0.087 0.006 -0.028 -0.070 0.161 -0.187
6 0.058 -0.065 -0.018 -0.038 0.007 0.295 0.865
7-.005 .082 .005 .027 -.194 -.188 .786
8 .319 .073 .039 .053 .006 .022
9 .077 -.067 -.011 .121 .186
10 .108 .046 .007 -.009 .206
DTF
.86971 .29465 .01322 .18985 .32868 .63252 2.02067
a
J Bus Psychol
123
Table 6 Generation X and
Baby Boomers: DIF and DTF
estimates for MWEP subscales
a
Dimension exhibited
differential test functioning
Item SR ME LE HW CW WT DG
NCDIF
1 .117 11.380 .151 .001 .011 .013 .052
2 .061 7.481 .228 .003 .030 .010 .006
3 .047 2.193 .008 .027 .059 .003 .004
4 .231 9.185 .370 .017 .080 .017 .013
5 .032 9.159 .072 .239 .005 .002 .021
6 .040 2.836 .105 .204 .011 .056 .040
7 .126 12.157 .003 .004 .045 .006 .009
8 .010 7.442 .689 .029 .016 .001
9 .178 1.855 .052 .184 .021
10 .026 9.957 .001 .051 .045
CDIF
1-.005 57.391 -.100 .027 .011 -.033 -.024
2 .026 46.522 -.127 .014 .027 .047 .007
3-.072 -25.158 -.022 .146 -.036 .013 .006
4 .129 51.552 .164 -.119 .042 .062 .012
5 .019 51.484 .069 .408 -.010 -.001 -.016
6-.042 -28.607 -.087 .373 -.008 .109 .022
7-.060 59.315 .013 .054 -.025 .035 .007
8 .032 46.406 .220 .060 -.017 .006
9 .080 -23.129 -.058 -.192 .023
10 .046 53.672 .003 .191 .035
DTF
.15220 289.448
a
.07577 .96078
a
.04392 .23859 .01376
Table 7 Generation X and
Millennials: DIF and DTF
estimates for MWEP subscales
a
Dimension exhibited
differential test functioning
Item SR ME LE HW CW WT DG
NCDIF
1 .229 6.262 .028 .330 .603 .884 .193
2 .220 3.139 .093 .305 .720 .803 .226
3 .043 .072 .041 .457 .609 .423 .392
4 .190 4.399 .061 .253 .589 .925 .241
5 .156 3.717 .018 .377 .758 .609 .096
6 .085 .121 .042 .327 .495 .403 .086
7 .152 6.362 .032 .378 .466 .745 .257
8 .090 3.397 .020 .249 .464 .257
9 .180 .006 .015 .250 .676
10 .233 4.387 .075 .297 .567
CDIF
1 1.822 35.337 .156 3.193 5.783 5.830 .755
2 1.784 25.003 .276 3.078 6.427 5.555 1.267
3 .719 -3.356 .193 3.753 5.919 4.028 1.573
4 1.633 29.591 -.202 2.713 5.821 5.969 .976
5 1.498 27.225 -.107 3.395 6.602 4.816 .709
6 1.106 -4.338 .195 3.126 5.343 3.941 .746
7 1.457 35.605 .171 3.387 5.047 5.273 1.104
8 1.102 26.001 -.127 2.779 5.172 3.142
9 1.619 -1.011 .117 2.771 6.059
10 1.839 29.552 .253 3.039 5.605
DTF
14.5804
a
199.609
a
.92566 31.2342
a
57.7764
a
38.5539
a
7.13113
a
J Bus Psychol
123
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