Discussion 1: Understanding Job Attitudes and Their Measurement (1 page paper without title and reference page.)
Generational differences in workplace attitudes and
job satisfaction Lack of sizable differences across cohorts
Jeffrey M. Cucina and Kevin A. Byle U.S. Customs and Border Protection, Washington, District of Columbia, USA
Nicholas R. Martin Aon, Washington, District of Columbia, USA
Sharron T. Peyton U.S. Secret Service, Washington, District of Columbia, USA, and
Ilene F. Gast U.S. Customs and Border Protection (Retired),
Washington, District of Columbia, USA
Abstract Purpose – The purpose of this paper is to examine the presence of generational differences in items measuring workplace attitudes (e.g. job satisfaction, employee engagement). Design/methodology/approach – Data from two empirical studies were used; the first study examined generational differences in large sample, multi-organizational administrations of an employee survey at both the item and general-factor levels. The second study compared job satisfaction ratings between parents and their children from a large nationwide longitudinal survey. Findings – Although statistically significant, most generational differences in Study 1 did not meet established cutoffs for a medium effect size. Type II error was ruled out given the large power. In Study 2, generational differences again failed to reach Cohen’s cutoff for a medium effect size. Across both studies, over 98 percent of the variance in workplace attitudes lies within groups, as opposed to between groups, and the distributions of scores on these variables overlap by over 79 percent. Originality/value – Prior studies examining generational differences in workplace attitudes focused on scale-level constructs. The present paper focused on more specific item-level constructs and employed larger sample sizes, which reduced the effects of sampling error. In terms of workplace attitudes, it appears that generations are more similar than they are different. Keywords Attitudes, Job satisfaction, Employee engagement, Generational differences Paper type Research paper
Generational differences receive extensive coverage in the media (Stein and Sanburn, 2013). But how much of these differences exist in reality? Some cross-sectional and longitudinal research has suggested that some differences do in fact exist across generations. McCrae et al. (1999) found that older individuals had higher levels of conscientiousness than younger individuals. Twenge et al. (2012) found in a cross-temporal study that Millenials tended to place more significance on extrinsic values (e.g. money, fame) and that civic engagement (e.g. interest in social problems, trust in government) has decreased across generations. Other research has found generational differences in several work values or traits such as work centrality, work ethic, and valuing leisure (Twenge, 2010).
Journal of Managerial Psychology Vol. 33 No. 3, 2018 pp. 246-264 © Emerald Publishing Limited 0268-3946 DOI 10.1108/JMP-03-2017-0115
Received 18 March 2017 Revised 1 August 2017 14 December 2017 Accepted 23 December 2017
The current issue and full text archive of this journal is available on Emerald Insight at: www.emeraldinsight.com/0268-3946.htm
The views expressed in this paper are those of the authors and do not necessarily reflect the views of U.S. Customs and Border Protection, the U.S. Secret Service, the U.S. Federal Government, or Aon. Portions of this research have been presented at the 2014 annual meeting of the Society for Industrial and Organizational Psychology.
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In contrast, some research argues against generational differences. Trzesniewski and Donnellan (2010) examined multiple samples (i.e. 477,380 total cases) of high school seniors over a 30-year time period and found little evidence of generational differences in a variety of non-work-related constructs (e.g. life satisfaction, individualism, self-esteem, time spent watching television) and one work-related construct (i.e. time-spent working). These conflicting findings may partly be due to methodological inconsistencies, issues with statistical power, age-related developmental changes, or changes in the dynamic of the workforce or environment (Lyons and Kuron, 2014; Ng and Parry, 2016).
One of the popular areas of focus for generational differences is workplace values and attitudes. This is understandable as a person spends a significant amount of time at work over the course of a lifetime, and the workplace is an aspect of life where generational differences are likely to be pronounced, as multiple generations interact with each other while performing similar occupational roles. Managers are often exposed to articles describing generational differences and highlighting how they should acknowledge differences among generations and manage differently to them. Thus, it is important to get clarity into whether differences in workplace attitudes and values exist using empirical research.
The results of studies on workplace generational differences have been mixed. A special issue of the Journal of Managerial Psychology (Culpin et al., 2015) was devoted to multi-generational issues. In that issue, Lyons et al. (2015) reported generational differences in career mobility patterns, with younger generations having more job and organizational mobility. An empirical study found some evidence of generational differences for job mobility and overtime work (Becton et al., 2014). Van der Heijden et al. (2015) found that age moderated the relationship between self-perceptions of employability and developmental opportunities, with a stronger relationship for older employees. Hatak et al. (2015) observed that younger employees were more likely to be entrepreneurial than older employees. Another article reported generational differences in job satisfaction when younger employees had feelings of self-consciousness with respect to age-related stereotyping (Ryan et al., 2015). Differences in work ethic have also been found among generations (Meriac et al., 2010), which may be in part due to different generations’ interpretations of scale items.
Other research has found that generational differences do not exist for certain workplace- related constructs. Sirota et al. (2005) stated that large-scale internal research demonstrated a lack of generational differences. Deal (2007) and Deal et al. (2013) provided empirical evidence for a lack of generational differences. A panel (Anderson, 2012; Bartram and Inceoglu, 2012; Meyer, 2012a, b; Wadlington and Elizondo, 2012) reported only minor differences in motives and motivation, and vocational and occupational interests. Meta- analytic research on workplace generational differences reported little evidence for generational differences in workplace attitudes, but was limited by a relatively small research base (Costanza et al., 2012). A summary of existing research by Costanza and Finkelstein (2015) questioned the presence of generational differences, but was met with commentaries containing opposing viewpoints (e.g. Campbell et al., 2015).
Much of the research on generational differences has focused on behaviors and values. In terms of the workplace, we believe that generational differences are most likely to emerge in terms of attitudes and values. Workplace attitudes are employees’ evaluations, feelings, attachments, and beliefs concerning different aspects of their job and workplace (Eagly and Chaiken, 1993; Judge, and Kammeyer-Mueller, 2012). Attitudes (e.g. job satisfaction) and values both influence a person’s behavior. However, we do not believe it is likely that there are generational differences on the most important work-related behavior: performance. Knowing that age is uncorrelated with performance (operational validity ¼ −0.01; Schmidt and Hunter, 1998), it is unlikely that generational differences exist on performance. However, much of the anecdotal evidence of generational differences tends to focus on
247
Generational differences in
workplace attitudes
attitude-related differences (e.g. work orientation). Thus, attitudes are one area in which generational differences may exist in the workplace.
There have been some conceptual reasons put forth for why there may be attitudinal differences based on generational membership, rather than age. Much of this research stems from the sociology literature. Generations have been defined conceptually as individuals who are from a similar period in history and who have formed, through shared events and experiences, a common awareness of that time period (Mannheim, 1952; Gilleard, 2004). The shared events and experiences (including popular culture, habits, lifestyle, political climate, economic conditions, and technological advances) can impact psychological variables (e.g. behavior, attitudes, preferences, and emotions) via “generational imprinting” (Parry and Urwin, 2011). For example, the economic downturn during the Great Depression could lead Traditionals (i.e. those born in 1944 and earlier) to value their jobs and employers more. The entry of women into the workforce changed the dynamic of the workplace for Baby Boomers. Adams (2000) suggested the “information age” (e.g. the emergence of the internet and e-mail) led Generation X to seek immediate feedback at work more than other generations. Corporate downsizing and outsourcing of jobs could lead members of Generation X to be less loyal to and have more negative opinions of organizations (Adams, 2000).
On the other hand, other research has found within-generational sources of attitudinal differences. Job satisfaction has been found to be correlated with job status, tenure, and age (Bedeian et al., 1992; Hulin and Smith, 1965; Kacmar and Ferris, 1989; White and Spector, 1987). Research has also documented the “honeymoon effect,” a positive feeling about one’s new job that wanes over time (Boswell and Boudreau, 2005). The personality construct agreeableness has also been found to increase with age (Donnellan and Lucas, 2008; Roberts et al., 2006).
There are several reasons to believe that the conceptual rationales for generational differences are somewhat speculative and in some cases more stereotypical (e.g. Millennials stereotyped as being more computer savvy than other generations) than fact based, and that within-generation attitudinal differences are more common than between-generation differences. There are also theoretical reasons why generational differences might be perceived as existing when in fact they do not (or are smaller than perceived). Individuals are not very efficient and accurate in perceiving information and making judgments about others. Social cognition research has documented various cognitive biases influencing the interpretation of information (Kunda, 1999). Individuals make shortcuts when processing information (e.g. confirmation bias) resulting in different people having different conclusions based on the same initial information (Tajfel and Wilkes, 1963). This decreases perceptions of within-group differences and increases perceptions of between- group differences (Taylor et al., 1978), including generational differences (Lester et al., 2012). Additionally, information processing limitations lead to the use of heuristics and stereotypes (Chaiken et al., 1989). The easy dissemination of information through the internet and media coupled with individual cognitive limitations makes it easy to see how generational labels and stereotypes could gain traction in the public consciousness, regardless of their veracity.
Current study There are mixed results found in research on generational differences in workplace attitudes and a lack of research specifically focusing on facets of job satisfaction. There are also competing hypotheses on whether these generational differences exist; however, each set of hypotheses have minimal conceptual and theoretical justification despite the fact that the media and organizational leaders believe that these differences exist. Therefore, we feel it is important to conduct additional research on generational workplace differences. We conducted two studies to examine generational differences in workplace attitudes. Study 1 examined the relationship between generational differences and employee attitudes using a cross-sectional design. This study extends Costanza et al.’s (2012) work by providing
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smaller confidence intervals (CIs) and a more fine-tuned examination of differences at the item-level. Since there is little solid conceptual and theoretical justification for the existence or lack of generational differences in workplace attitudes, we conducted an additional analysis. We identified items that should show generational differences (based on the pop- psychology literature on generational differences) and examined whether these speculations were supported by the data. We also examined a general hypothesis (from Stein and Sanburn, 2013) that Millennials have lower job satisfaction. Study 2 used longitudinal data sets that measured overall job satisfaction in a cohort of individuals and their children.
Study 1 Method We used publicly available data sets of responses to a Federal government-wide employee survey administered by the US Office of Personnel Management in 2004, 2006, 2008, 2010, 2011, and 2012. The organizations represented have diverse workforces and missions, ranging from law enforcement to science.
Age groups. A demographic item asked respondents “What is your age group?” As Costanza et al. (2012) noted, there is a lack of consistency among the cutoffs for the birth years that form each generation. We addressed this problem as follows. The age group item allows for breakouts by five groups (“29 and under,” “30-39,” “40-49,” “50-59,” “60 or older”). Since the survey was administered multiple times, the age group item covers different generational groups during each administration. We computed the midpoint of the ranges of the birth-year generational cutoffs that Costanza et al. reported and used these as the cutoffs for each generation, resulting in the following birth-years: Traditionals – 1944 and earlier; Baby Boomers – 1945-1962; Generation X – 1963-1978; Millennials – 1979 and later. We adjusted our strategy for the cutoffs between Generation X and Baby Boomers since Costanza et al. reported an endpoint range of 1960-9 (median of 1964) for Baby Boomers and a beginning point range of 1961-5 for Generation X. Table I provides sample sizes for the age groups and Table II provides the assignments for each of the age groups to generations.
Survey items. Each year, a core set of 59 items (shown in Table III) covering a variety of job attitudes (e.g. satisfaction, engagement, and organizational climate) was administered. The content of the survey is representative of typical employee surveys. Past research suggests the presence of a general factor underlying responses to employee surveys (Harter et al., 2002). This finding is likely due to the “a” factor in employee attitudes (Newman et al., 2010). That said, Cucina et al. (2014) found evidence of six additional factors (in addition to the general factor) in this survey. Additionally, items can contain unique variance. Therefore, we investigated whether generational differences existed on the general factor, the specific factors, the items, and the items controlling for the general factor. To do this, we computed scores on the first unrotated principal component across all items for each participant as a measure of the general factor; this approach is consistent with research on general mental ability in the mental abilities literature (Ree and Earles, 1991). It also
2004 2006 2008 2010 2011 2012 n % n % n % n % n % n %
Under 30 1,105 2.8 8,794 4.0 8,858 4.2 12,045 4.9 13,612 5.6 37,863 6.0 30-39 3,545 8.8 31,369 14.4 29,382 14.1 35,656 14.4 38,343 15.7 109,019 17.2 40-49 13,544 33.7 70,132 32.2 64,117 30.7 73,979 29.9 71,619 29.2 182,885 28.9 50-59 18,109 45.1 87,049 40.0 82,008 39.3 93,741 37.9 89,358 36.5 224,645 35.5 60 or older 3,865 9.6 20,192 9.3 24,553 11.8 32,195 13.0 31,988 13.1 78,860 12.5 Total 40,168 100.0 217,528 100.0 208,911 100.0 247,616 100.0 244,910 100.0 633,206 100.0
Table I. Frequencies and percentages of age groups by
survey year
249
Generational differences in
workplace attitudes
provides a scale score with outstanding reliability (Coefficient α for the 2012 data was 0.98). We also computed subscale scores for the six specific factors (i.e. work experience, work unit, agency, supervisory/team leader, leadership, and satisfaction) using the coding scheme employed by Cucina et al. (2014). Beginning in 2010, two additional items that appear related to generational differences were added: “When needed I am willing to put in the extra effort to get a job done” (for which we expect lower scores from generations that are characterized as less hard working) and “I am constantly looking for ways to do my job better” (for which we expect lower scores from older generations that are “resistant to change”). These items were not used to compute the factor scores but were included in other analyses.
Evaluator judgments. In order to speculate which items might have generational differences, a panel evaluated each item and made ratings as to whether differences might exist. This is best described as an exploratory analysis rather than formal hypothesizing. Five PhD level I/O psychologists were presented with generational grouping dyads and were asked to review each survey item, indicating whether one of the groups would rate the
Survey year No. Age group Age 2004 2006 2008 2010 2011 2012
1 29 and under
16 October 24, 1988
July 18, 1990 September 6, 1992
March 10, 1994
May 9, 1995
May 24, 1996
29 October 31, 1975
July 24, 1977 September 13, 1979
March 16, 1981
May 15, 1982
May 31, 1983
Gens.a X, Miln. X, Miln. Miln. Miln. Miln. Miln. 2 30-39 30 October 31,
1974 July 24, 1976 September 13,
1978 March 16, 1980
May 15, 1981
May 31, 1982
39 November 4, 1965
July 29, 1967 September 17, 1969
March 21, 1971
May 19, 1972
June 4, 1973
Gens. X X X X, Miln. X, Miln. X, Miln. 3 40-49 40 November 5,
1964 July 30, 1966 September 18,
1968 March 22, 1970
May 21, 1971
June 5, 1972
49 November 10, 1955
August 3, 1957
September 23, 1959
March 26, 1961
May 25, 1962
June 10, 1963
Gens. X, Boomer X, Boomer X, Boomer X, Boomer X, Boomer
X
4 50-59 50 November 10, 1954
August 3, 1956
September 23, 1958
March 26, 1960
May 25, 1961
June 10, 1962
59 November 14, 1945
August 8, 1947
September 27, 1949
March 31, 1951
May 29, 1952
June 14, 1953
Gens. Boomer Boomer Boomer Boomer Boomer Boomer 5 60 or older 60 November 15,
1944 August 9, 1946
September 28, 1948
April 1, 1950
May 31, 1951
June 15, 1952
80 November 25, 1924
August 19, 1926
October 8, 1928
April 11, 1930
June 10, 1931
June 25, 1932
Gens. Traditional Trad., Bmr. Trad., Bmr. Trad., Bmr. Trad., Bmr.
Trad., Bmr.
Notes: Survey respondents selected their age group using the response options provided in the first column. The second column provides the minimum and maximum age for each group (we assumed that the youngest and oldest possible ages would be roughly 16 and 80). The next columns provide the birthdates that would form the lower end of the response option. This information is provided for each year. Note that the surveys were administered over the course of several weeks, we computed the birthdates based on the date that appears in the middle (or midpoint) of the survey administration period. aGens. – Generations, X – Generation X, Miln. – Millennials. The generational representation was determined based on the minimum and maximum possible birthdates (obtained using the starting and ending dates of the survey and the age ranges) and the following cutoffs: Traditionals – 1944 and earlier; Baby Boomers – 1945-1962; Generation X – 1963-1978; Millennials 1979 and later
Table II. Birthdates (at midpoint of survey administration) and generational representation for different age groups by survey year
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M iln
.-X M iln
.-B oo m .
X -B oo m r.
X -T ra d.
B oo m r. -T ra d.
d d E
M M
d d E
M M
d d E
M M
d d E
M M
d d E
M M
N o.
G en er al
fa ct or
sc or e
0. 10 ** *
0. 11 ** *
− 0. 01
− 0. 24 ** *
− 0. 17 ** *
S ub sc al es
W or k ex pe ri en ce
o 0. 01
− 0. 05 ** *
0. 03 ** *
− 0. 04 ** *
o 0. 01
0. 01
− 0. 24 ** *
o 0. 01
− 0. 19 ** *
− 0. 03
W or k un
it 0. 04 ** *
− 0. 04 ** *
0. 05 ** *
− 0. 06 ** *
− 0. 03 ** *
− 0. 03 ** *
− 0. 27 ** *
− 0. 07 **
− 0. 14 ** *
0. 01
A ge nc y
0. 07 ** *
0. 03 ** *
0. 11 ** *
0. 01 **
− 0. 02 ** *
− 0. 01 ** *
− 0. 25 ** *
− 0. 04
− 0. 15 ** *
o 0. 01
Su pe rv is or y/ T ea m
le ad er
0. 08 ** *
0. 03 ** *
0. 16 ** *
0. 06 ** *
0. 05 ** *
0. 04 ** *
− 0. 11 ** *
0. 09 ** *
− 0. 10 ** *
0. 04 *
L ea de rs hi p
0. 14 ** *
0. 09 ** *
0. 16 ** *
0. 09 ** *
o 0. 01
o 0. 01
− 0. 21 ** *
0. 01
− 0. 14 ** *
o 0. 01
Sa ti sf ac ti on
0. 03 ** *
− 0. 02 ** *
0. 08 ** *
− 0. 01 **
0. 01 ** *
0. 01 ** *
− 0. 21 ** *
0. 02
− 0. 17 ** *
− 0. 01
1 T he
pe op le I w or k w it h co op er at e to
ge t
th e jo b do ne
− 0. 05 ** *
− 0. 08 ** *
− 0. 08 ** *
− 0. 14 ** *
− 0. 06 ** *
− 0. 07 ** *
− 0. 25 ** *
− 0. 10 ** *
− 0. 10 ** *
o 0. 01
2 I am
gi ve n a re al
op po rt un
it y to
im pr ov e
m y sk ill s in
m y or ga ni za ti on
0. 08 ** *
0. 03 ** *
0. 13 ** *
0. 05 ** *
0 .0 3 ** *
0 .0 2 ** *
− 0 .0 5 *
0 .1 2 ** *
− 0. 08 ** *
0. 04 *
3 I ha ve
en ou gh
in fo rm
at io n to
do m y jo b
w el l
0. 03 ** *
− 0. 02 ** *
0. 03 ** *
− 0. 04 ** *
− 0. 02 ** *
− 0. 02 ** *
− 0. 28 ** *
− 0. 11 ** *
− 0. 18 ** *
− 0. 07 ** *
4 I fe el en co ur ag ed
to co m e up
w it h ne w
an d be tt er
w ay s of
do in g th in gs
− 0. 08 ** *
− 0. 14 ** *
− 0. 06 ** *
− 0. 14 ** *
− 0. 01 **
− 0. 01 *
− 0 .1 1 ** *
0 .0 6 *
− 0. 08 ** *
0. 03
5 M y w or k gi ve s m e a fe el in g of
pe rs on al
ac co m pl is hm
en t
− 0 .1 4 ** *
− 0 .1 8 ** *
− 0 .1 7 ** *
− 0 .2 2 ** *
− 0 .0 5 ** *
− 0 .0 4 ** *
− 0 .2 7 ** *
− 0 .0 7 **
− 0. 19 ** *
− 0. 06 ** *
6 I lik
e th e ki nd
of w or k I do
− 0. 28 ** *
− 0. 29 ** *
− 0 .3 0 ** *
− 0 .3 4 ** *
− 0 .0 5 ** *
− 0 .0 6 ** *
− 0 .3 1 ** *
− 0 .1 5 ** *
− 0. 18 ** *
− 0. 07 ** *
7 I re co m m en d m y or ga ni za ti on
as a go od
pl ac e to
w or k
0 .0 4 ** *
o 0 .0 1
0 .0 9 ** *
0 .0 2 ** *
0 .0 2 ** *
0. 02 ** *
− 0 .1 4 ** *
0 .0 5 *
− 0. 14 ** *
− 0. 01
8 O ve ra ll,
ho w
go od
a jo b do
yo u fe el is
be in g do ne
by yo ur
im m ed ia te su pe rv is or /
te am
le ad er ?
0. 06 ** *
0. 03 ** *
0 .1 0 ** *
0 .0 3 ** *
o 0. 01
− 0. 01 *
− 0 .1 4 ** *
0 .0 3
− 0. 09 ** *
0. 03
9 H ow
w ou ld
yo u ra te th e ov er al lq
ua lit y of
w or k do ne
by yo ur
w or k gr ou p?
− 0. 11 ** *
− 0. 14 ** *
− 0 .1 5 ** *
− 0 .2 1 ** *
− 0. 09 ** *
− 0. 08 ** *
− 0. 29 ** *
− 0. 15 ** *
− 0. 11 ** *
− 0. 02
10 T he
w or kf or ce
ha s th e jo b- re le va nt
kn ow
le dg
e an d sk ill s ne ce ss ar y to
ac co m pl is h or ga ni za ti on al
go al s
0. 08 ** *
0. 02 ** *
0. 12 ** *
0. 05 ** *
o 0. 01
o 0. 01
− 0. 22 ** *
− 0. 09 ** *
− 0. 15 ** *
− 0. 06 ** *
11 M y su pe rv is or
su pp
or ts
m y ne ed
to ba la nc e w or k an d fa m ily
is su es
0. 06 ** *
0. 04 ** *
0 .1 5 ** *
0 .0 9 ** *
0. 06 ** *
0. 06 ** *
o 0 .0 1
0 .1 3 ** *
− 0. 07 ** *
0. 03
12 Su
pe rv is or s/ te am
le ad er s in
m y w or k un
it pr ov id e em
pl oy ee s w it h th e op po rt un
it ie s
to de m on st ra te
th ei r le ad er sh ip
sk ill s
o 0 .0 1
− 0 .0 4 ** *
0 .0 6 ** *
− 0 .0 1 *
0. 04 ** *
0. 04 ** *
− 0 .1 0 ** *
0 .0 7 **
− 0. 08 ** *
0. 04 *
(c o n ti n u ed
)
Table III. Effect sizes (using
Cohen’s d) for generational differences
251
Generational differences in
workplace attitudes
M iln
.-X M iln
.-B oo m .
X -B oo m r.
X -T ra d.
B oo m r. -T ra d.
d d E
M M
d d E
M M
d d E
M M
d d E
M M
d d E
M M
13 M y w or k un
it is ab le to re cr ui tp
eo pl e w it h
th e ri gh
t sk ill s
0. 07 ** *
0. 05 ** *
0. 13 ** *
0. 10 ** *
0. 03 ** *
0. 04 ** *
− 0. 18 ** *
− 0. 03
− 0. 13 ** *
− 0. 03
14 T he
sk ill
le ve l in
m y w or k un
it ha s
im pr ov ed
in th e pa st
ye ar
0. 16 ** *
0. 09 ** *
0. 20 ** *
0. 11 ** *
0. 04 ** *
0. 03 ** *
− 0. 03
0. 12 ** *
− 0. 09 ** *
0. 01
15 I ha ve
su ff ic ie nt
re so ur ce s (e .g .p
eo pl e,
m at er ia ls ,b
ud ge t) to
ge t m y jo b do ne
0. 18 ** *
0. 19 ** *
0. 24 ** *
0. 25 ** *
0. 04 ** *
0. 07 ** *
− 0. 10 ** *
0. 04
− 0. 17 ** *
− 0. 09 ** *
16 M y w or kl oa d is re as on ab le
0. 17 ** *
0. 17 ** *
0 .2 2 ** *
0 .2 1 ** *
0 .0 5 ** *
0 .0 5 ** *
− 0 .1 6 ** *
− 0 .0 3
− 0. 21 ** *
− 0. 14 ** *
17 M y ta le nt s ar e us ed
w el li n th e w or kp
la ce
− 0 .0 8 ** *
− 0 .1 2 ** *
− 0 .0 6 ** *
− 0 .1 1 ** *
o 0 .0 1
0 .0 1 ** *
− 0 .1 4 ** *
0 .0 5
− 0. 11 ** *
0. 01
18 I kn
ow ho w
m y w or k re la te s to
th e
ag en cy ’s go al s an d pr io ri ti es
− 0 .0 4 ** *
− 0 .0 8 ** *
− 0 .0 5 ** *
− 0 .1 1 ** *
− 0 .0 3 ** *
− 0 .0 2 ** *
− 0. 17 ** *
− 0. 03
− 0. 09 ** *
o 0. 01
19 T he
w or k I do
is im
po rt an t
− 0. 18 ** *
− 0. 26 ** *
− 0. 22 ** *
− 0. 30 ** *
− 0 .0 4 ** *
− 0 .0 4 ** *
− 0. 19 ** *
− 0. 04
− 0. 08 ** *
0. 01
20 P hy
si ca l co nd
it io ns
(e .g .n
oi se
le ve l,
te m pe ra tu re ,l ig ht in g,
cl ea nl in es s in
th e
w or kp
la ce ) al lo w
em pl oy ee s to
pe rf or m
th ei r jo bs
w el l
− 0. 04 ** *
− 0. 07 ** *
o 0. 01
− 0. 03 ** *
0. 02 ** *
0. 02 ** *
− 0. 13 ** *
− 0. 01
− 0. 09 ** *
− 0. 02
21 P ro m ot io ns
in m y w or k un
it ar e ba se d on
m er it
0. 05 ** *
0. 01
0 .1 0 ** *
0 .0 2 ** *
o 0 .0 1
0 .0 1 ** *
− 0 .0 9 ** *
0 .0 7 **
− 0. 04 *
0. 07 ** *
22 In
m y w or k un
it ,s te ps
ar e ta ke n to
de al
w it h a po or
pe rf or m er
w ho
ca nn
ot or
w ill
no t im
pr ov e
− 0. 10 ** *
− 0. 16 ** *
− 0. 17 ** *
− 0. 21 ** *
− 0. 12 ** *
− 0. 09 ** *
− 0. 39 ** *
− 0. 22 ** *
− 0. 13 ** *
− 0. 03
23 E m pl oy ee s ha ve
a fe el in g of
pe rs on al
em po w er m en t w it h re sp ec t to
w or k
pr oc es se s
0 .0 5 ** *
0 .0 1 *
0 .0 6 ** *
0 .0 1 *
− 0. 03 ** *
− 0. 02 ** *
− 0. 23 ** *
− 0. 05 *
− 0. 12 ** *
o 0. 01
24 E m pl oy ee s ar e re w ar de d fo r pr ov id in g
hi gh
qu al it y pr od uc ts
an d se rv ic es
to cu st om
er s
0. 04 ** *
− 0. 01 **
0 .0 4 ** *
− 0 .0 4 ** *
− 0. 04 ** *
− 0. 04 ** *
− 0. 29 ** *
− 0. 13 ** *
− 0. 13 ** *
o 0. 01
25 C re at iv it y an d in no va ti on
ar e re w ar de d
o 0. 01
− 0. 05 ** *
o 0 .0 1
− 0 .0 8 ** *
− 0 .0 3 ** *
− 0 .0 3 ** *
− 0 .2 7 ** *
− 0 .0 9 ** *
− 0. 14 ** *
− 0. 01
26 A w ar ds
in m y w or k un
it de pe nd
on ho w
w el l em
pl oy ee s pe rf or m
th ei r jo bs
0. 03 ** *
− 0. 01 *
0 .0 3 ** *
− 0 .0 4 ** *
− 0. 04 ** *
− 0. 04 ** *
− 0. 22 ** *
− 0. 05 *
− 0. 09 ** *
0. 03
27 In
m y w or k un
it ,d
if fe re nc es
in pe rf or m an ce
ar e re co gn
iz ed
in a
m ea ni ng
fu l w ay
− 0. 03 ** *
− 0. 08 ** *
− 0. 05 ** *
− 0. 11 ** *
− 0. 07 ** *
− 0. 06 ** *
− 0. 30 ** *
− 0. 12 ** *
− 0. 13 ** *
− 0. 01
28 M y pe rf or m an ce
ap pr ai sa l is a fa ir
re fl ec ti on
of m y pe rf or m an ce
0. 07 ** *
0. 05 ** *
0 .1 5 ** *
0 .0 8 ** *
0. 05 ** *
0. 05 ** *
− 0. 09 ** *
0. 05
− 0. 10 ** *
0. 01
(c o n ti n u ed
)
Table III.
252
JMP 33,3
M iln
.-X M iln
.-B oo m .
X -B oo m r.
X -T ra d.
B oo m r. -T ra d.
d d E
M M
d d E
M M
d d E
M M
d d E
M M
d d E
M M
29 D is cu ss io ns
w it h m y su pe rv is or /t ea m
le ad er
ab ou t m y pe rf or m an ce
ar e
w or th w hi le
0. 08 ** *
0. 05 ** *
0 .1 6 ** *
0 .1 0 ** *
0 .0 7 ** *
0 .0 6 ** *
− 0. 02
0. 16 ** *
− 0. 09 ** *
0. 04 *
30 I am
he ld
ac co un
ta bl e fo r ac hi ev in g
re su lt s
− 0. 09 ** *
− 0. 10 ** *
− 0 .1 2 ** *
− 0 .1 4 ** *
− 0 .0 6 ** *
− 0 .0 4 ** *
− 0 .2 2 ** *
− 0 .0 8 ** *
− 0. 09 ** *
0. 01
31 Su
pe rv is or s/ te am
-le ad er s in
m y w or k un
it ar e co m m it te d to
a w or kf or ce
re pr es en ta ti ve
of al l se gm
en ts
of so ci et y
0. 06 ** *
o 0. 01
0. 11 ** *
0. 01 **
0. 02 ** *
0. 01 ** *
− 0. 17 ** *
0. 01
− 0. 10 ** *
0. 02
32 P ol ic ie s an d pr og ra m s pr om
ot e di ve rs it y
in th e w or kp
la ce
(e .g .r ec ru it in g m in or it ie s
an d w om
en ,t ra in in g in
aw ar en es s of
di ve rs it y is su es ,m
en to ri ng
) 0. 12 ** *
0. 08 ** *
0. 14 ** *
0. 05 ** *
o 0. 01
o 0. 01
− 0. 12 ** *
0. 04
− 0. 11 ** *
− 0. 01
33 M an ag er s/ su pe rv is or s/ te am
le ad er s w or k
w el l w it h em
pl oy ee s of
di ff er en t
ba ck gr ou nd
s 0. 12 ** *
0. 08 ** *
0. 16 ** *
0. 07 ** *
0. 01 **
o 0. 01
− 0. 13 ** *
0. 07 **
− 0. 10 ** *
0. 03
34 I ha ve
a hi gh
le ve l of
re sp ec t fo r m y
or ga ni za ti on ’s se ni or
le ad er s
0 .1 6 ** *
0 .1 1 ** *
0 .2 4 ** *
0 .1 6 ** *
0. 04 ** *
0. 05 ** *
− 0 .1 1 ** *
0 .0 6 *
− 0 .1 3 ** *
o 0 .0 1
35 In
m y or ga ni za ti on ,l ea de rs
ge ne ra te
hi gh
le ve ls of
m ot iv at io n an d co m m it m en t in
th e w or kf or ce
0 .0 9 ** *
0 .0 6 ** *
0 .1 2 ** *
0 .0 6 ** *
− 0. 01 ** *
o 0. 01
− 0. 25 ** *
− 0. 05 *
− 0. 16 ** *
− 0. 02
36 M y or ga ni za ti on
’s le ad er s m ai nt ai n hi gh
st an da rd s of
ho ne st y an d in te gr it y
0. 15 ** *
0. 11 ** *
0. 17 ** *
0. 09 ** *
− 0. 01 ** *
− 0. 01 ** *
− 0. 22 ** *
− 0. 04
− 0. 12 ** *
o 0. 01
37 M an ag er s co m m un
ic at e th e go al s an d
pr io ri ti es
of th e or ga ni za ti on
0. 11 ** *
0. 09 ** *
0. 12 ** *
0. 05 ** *
− 0. 01 ** *
− 0. 02 ** *
− 0. 20 ** *
− 0. 03
− 0. 14 ** *
− 0. 01
38 M an ag er s re vi ew
an d ev al ua te
th e
or ga ni za ti on ’s pr og re ss
to w ar d m ee ti ng
it s go al s an d ob je ct iv es
0. 12 ** *
0. 08 ** *
0. 14 ** *
0. 07 ** *
− 0. 01 **
− 0. 01 *
− 0. 19 ** *
− 0. 02
− 0. 13 ** *
o 0. 01
39 E m pl oy ee s ar e pr ot ec te d fr om
he al th
an d
sa fe ty
ha za rd s on
th e jo b
0. 04 ** *
0. 06 ** *
0. 07 ** *
0. 04 ** *
− 0. 01 ** *
o 0. 01
− 0. 13 ** *
0. 01
− 0. 08 ** *
0. 01
40 M y or ga ni za ti on
ha s pr ep ar ed
em pl oy ee s
fo r po te nt ia l se cu ri ty
th re at s
0. 02 ** *
o 0. 01
− 0. 02 ** *
− 0. 05 ** *
− 0. 05 ** *
− 0. 03 ** *
− 0. 14 ** *
− 0. 03
− 0. 11 ** *
− 0. 02
41 A rb it ra ry
ac ti on ,p
er so na l fa vo ri ti sm
an d
co er ci on
fo r pa rt is an
po lit ic al
pu rp os es
ar e no t to le ra te d
0. 03 ** *
0. 03 ** *
0. 05 ** *
o 0. 01
− 0. 02 ** *
− 0. 01 ** *
− 0. 18 ** *
− 0. 02
− 0. 09 ** *
0. 03
(c o n ti n u ed
)
Table III.
253
Generational differences in
workplace attitudes
M iln
.-X M iln
.-B oo m .
X -B oo m r.
X -T ra d.
B oo m r. -T ra d.
d d E
M M
d d E
M M
d d E
M M
d d E
M M
d d E
M M
42 P ro hi bi te d P er so nn
el P ra ct ic es
(e .g .
ill eg al ly
di sc ri m in at in g fo r or
ag ai ns t an y
em pl oy ee /a pp
lic an t, ob st ru ct in g a
pe rs on ’s ri gh
t to
co m pe te fo r em
pl oy m en t,
kn ow
in gl y vi ol at in g ve te ra ns ’ pr ef er en ce
re qu
ir em
en ts ) ar e no t to le ra te d
0. 17 ** *
0. 10 ** *
0. 21 ** *
0. 10 ** *
0. 03 ** *
0. 02 ** *
− 0. 08 ** *
0. 06 *
− 0. 07 ** *
0. 05 **
43 I ca n di sc lo se
a su sp ec te d vi ol at io n of
an y
la w ,r ul e or
re gu
la ti on
w it ho ut
fe ar
of re pr is al
0. 13 ** *
0. 09 ** *
0. 17 ** *
0. 08 ** *
0. 03 ** *
0. 03 ** *
− 0. 13 ** *
0. 03
− 0. 11 ** *
0. 01
44 Su
pe rv is or s/ te am
le ad er s pr ov id e
em pl oy ee s w it h co ns tr uc ti ve
su gg
es ti on s
to im
pr ov e th ei r jo b pe rf or m an ce
0. 08 ** *
0. 03 ** *
0 .1 5 ** *
0 .0 8 ** *
0 .0 4 ** *
0 .0 4 ** *
− 0 .1 3 ** *
0 .0 5
− 0. 08 ** *
0. 04 *
45 Su
pe rv is or s/ te am
le ad er s in
m y w or k un
it su pp
or t em
pl oy ee
de ve lo pm
en t
0. 10 ** *
0. 05 ** *
0. 16 ** *
0. 07 ** *
0. 03 ** *
0. 02 ** *
− 0. 10 ** *
0. 04
− 0. 07 ** *
0. 04 *
46 M y tr ai ni ng
ne ed s ar e as se ss ed
0. 11 ** *
0. 06 ** *
0. 14 ** *
0. 08 ** *
0. 01 ** *
0. 01 ** *
− 0. 09 ** *
0. 08 ** *
− 0. 11 ** *
o 0. 01
47 M an ag er s pr om
ot e co m m un
ic at io n
am on g di ff er en t w or k un
it s (e .g .a bo ut
pr oj ec ts ,g
oa ls ,n
ee de d re so ur ce s)
0. 08 ** *
0. 02 ** *
0. 10 ** *
0. 02 ** *
o 0. 01
o 0. 01
− 0. 16 ** *
0. 04
− 0. 11 ** *
0. 03
48 E m pl oy ee s in
m y w or k un
it sh ar e jo b
kn ow
le dg
e w it h ea ch
ot he r
0. 13 ** *
0. 03 ** *
0. 14 ** *
0. 02 ** *
o 0. 01
− 0. 01 ** *
− 0. 10 ** *
0. 03
− 0. 09 ** *
0. 01
49 H ow
sa ti sf ie d ar e yo u w it h yo ur
in vo lv em
en t in
de ci si on s th at
af fe ct
yo ur
w or k?
o 0 .0 1
− 0 .0 6 ** *
0 .0 4 ** *
− 0 .0 3 ** *
0 .0 2 ** *
0 .0 3 ** *
− 0 .1 3 ** *
0 .0 6 *
− 0. 12 ** *
0. 01
50 H ow
sa ti sf ie d ar e yo u w it h th e
in fo rm
at io n yo u re ce iv e fr om
m an ag em
en t on
w ha t’s
go in g on
in yo ur
or ga ni za ti on ?
0. 01
− 0. 04 ** *
0 .0 3 ** *
− 0 .0 4 ** *
o 0. 01
o 0. 01
− 0 .1 9 ** *
0 .0 1
− 0. 13 ** *
0. 02
51 H ow
sa ti sf ie d ar e yo u w it h th e re co gn
it io n
yo u re ce iv e fo r do in g a go od
jo b?
o 0. 01
− 0. 04 ** *
0 .0 4 ** *
− 0 .0 4 ** *
o 0. 01
o 0. 01
− 0 .2 0 ** *
− 0 .0 2
− 0. 11 ** *
0. 01
52 H ow
sa ti sf ie d ar e yo u w it h th e po lic ie s
an d pr ac ti ce s of
yo ur
se ni or
le ad er s?
0. 09 ** *
0. 08 ** *
0 .1 5 ** *
0 .1 1 ** *
0. 03 ** *
0. 04 ** *
− 0 .1 7 ** *
0 .0 2
− 0. 13 ** *
o 0. 01
53 H ow
sa ti sf ie d ar e yo u w it h yo ur
op po rt un
it y to
ge t a be tt er
jo b in
yo ur
or ga ni za ti on ?
0. 06 ** *
0. 03 ** *
0. 13 ** *
0. 08 ** *
0 .0 3 ** *
0 .0 4 ** *
− 0 .0 7 **
0 .1 1 ** *
− 0. 11 ** *
0. 01
(c o n ti n u ed
)
Table III.
254
JMP 33,3
M iln
.-X M iln
.-B oo m .
X -B oo m r.
X -T ra d.
B oo m r. -T ra d.
d d E
M M
d d E
M M
d d E
M M
d d E
M M
d d E
M M
54 H ow
sa ti sf ie d ar e yo u w it h th e tr ai ni ng
yo u re ce iv e fo r yo ur
pr es en t jo b?
0. 07 ** *
0. 01 *
0 .0 8 ** *
0 .0 1
o 0. 01
− 0. 01 ** *
− 0. 14 ** *
0. 03
− 0. 11 ** *
o 0. 01
55 C on si de ri ng
ev er yt hi ng
,h ow
sa ti sf ie d ar e
yo u w it h yo ur
jo b?
− 0. 06 ** *
− 0. 09 ** *
− 0 .0 4 ** *
− 0 .1 0 ** *
− 0. 02 ** *
− 0. 02 ** *
− 0 .2 5 ** *
− 0 .0 5 *
− 0. 19 ** *
− 0. 05 **
56 C on si de ri ng
ev er yt hi ng
,h ow
sa ti sf ie d ar e
yo u w it h yo ur
pa y?
− 0. 01 *
− 0. 05 ** *
− 0 .0 1 **
− 0 .0 8 ** *
o 0. 01
o 0. 01
− 0 .1 6 ** *
− 0 .0 5 *
− 0. 13 ** *
− 0. 07 ** *
57 C on si de ri ng
ev er yt hi ng
,h ow
sa ti sf ie d ar e
yo u w it h yo ur
or ga ni za ti on ?
0. 04 ** *
o 0. 01
0 .1 0 ** *
0 .0 1 **
0 .0 3 ** *
0 .0 3 ** *
− 0 .1 7 ** *
0 .0 4
− 0. 16 ** *
− 0. 01
58 H ow
sa ti sf ie d ar e yo u w it h te le w or k/
te le co m m ut in g?
0. 05 ** *
0. 01
0 .0 7 ** *
0 .0 1
o 0 .0 1
o 0 .0 1
− 0 .2 3 ** *
− 0 .1 6 ** *
− 0. 16 ** *
− 0. 12 ** *
59 H ow
sa ti sf ie d ar e yo u w it h al te rn at iv e
w or k sc he du
le s?
0. 12 ** *
0. 12 ** *
0. 16 ** *
0. 10 ** *
o 0. 01
− 0. 01 *
o 0. 01
0. 06 *
− 0. 04 *
0. 01
60 W he n ne ed ed
I am
w ill in g to
pu t in
th e
ex tr a ef fo rt to
ge t a jo b do ne
− 0. 06 ** *
− 0. 10 ** *
− 0 .0 5 ** *
− 0 .1 3 ** *
0 .0 2 ** *
− 0 .0 1 **
61 Ia m co ns ta nt ly lo ok in g fo r w ay s to do
m y
jo b be tt er
− 0. 09 ** *
− 0. 13 ** *
− 0. 06 ** *
− 0. 12 ** *
0. 04 ** *
0. 02 ** *
M ax im
um |d -v al ue |
0. 28
0. 29
0. 30
0. 34
0. 12
0. 09
0. 39
0. 22
0. 21
0. 14
M in im
um |d -v al ue |
o 0. 01
o 0. 01
o 0. 01
o 0. 01
o 0. 01
o 0. 01
o 0. 01
0. 01
0. 04
o 0. 01
M ax im
um C on fi de nc e In te rv al
W id th
0. 08
0. 08
0. 08
0. 11
0. 08
M in im
um C on fi de nc e In te rv al
W id th
o 0. 01
0. 01
o 0. 01
o 0. 01
0. 07
N o te s: d E
M M ar e d- va lu es
co m pu
te d on
th e es ti m at ed
m ar gi na liz ed
m ea ns
(w hi ch
co nt ro lf or
th e co rr el at io n be tw
ee n th e ge ne ra lf ac to r an d ea ch
it em
). St at is ti cs
ap pe ar
in bo ld fo nt
ar e th os e in vo lv in g th e sp ec ul at ed
ge ne ra ti on al
di ff er en ce s de sc ri be d in
th e m ai n te xt .* p ⩽ 0. 05 ;* *p
⩽ 0. 01 ;* ** p ⩽ 0. 00 1
Table III.
255
Generational differences in
workplace attitudes
item higher in agreement (e.g. Baby Boomers rate the item “The work I do is important” higher in agreement than Traditionalists) or no difference in rating, based on perceptions formed from a review of generational differences (Tolbize, 2008).
Results We compared the item, factor score, and subscale means for generations within each administration of the survey using t-tests, Cohen’s d, CIs about d, and estimated marginal means (EMMs). Recognizing that year-to-year differences in overall engagement across the entire population might occur, we computed the d-values comparing each generation separately for each year and then computed a sample-size weighted average across all years. We focused our interpretation on these weighted averages, which are shown in Table III along with the maximum and minimum CI widths (across all administrations of the survey). EMMs were computed to provide the mean item scores for each age group partialling out scores on the general factor for each participant. We computed d-values for the comparisons of the EMMs and report these in Table III. This analysis addresses the possibility that generational differences in the unique variance of each item could be masked by a general factor.
Given the large sample sizes, most results were statistically significant. Consequently, we focused on the effect sizes using six interpretations. First, we used Cohen’s (1992) cutoffs (small: d ¼ 0.20; medium: d ¼ 0.50; large: d ¼ 0.80). Second, we converted Bosco et al.’s (2015) tertile cutoffs for correlation coefficient effect sizes into Cohen’s (1992) d-values assuming a 50-50 split between the two groups. The cutoff points between the small and medium tertiles and between the medium and large tertiles are d ¼ 0.18 and d ¼ 0.54. Third, we converted Paterson et al.’s (2016) percentile cutoffs for correlation effect sizes into d-values. This conversion was done for the 5th (d ¼ 0.06), 10th (d ¼ 0.12), 15th (d ¼ 0.16), 20th (d ¼ 0.20), 25th (d ¼ 0.24), 30th (d ¼ 0.28), 35th (d ¼ 0.30), 40th (d ¼ 0.34), 45th (d ¼ 0.39), and 50th (d ¼ 0.410) percentiles. Fourth, we considered the variance between groups and percent overlap in normal distributions between two groups for the following values of d: 0 (0 percent variance between groups; 100 percent overlap), 0.1 (0.2 percent variance between groups; 92 percent overlap), 0.2 (1 percent variance between groups; 85 percent overlap), 0.3 (2 percent variance between groups; 79 percent overlap), and 0.4 (4 percent variance between groups, 73 percent overlap).
Fifth, we considered the practical significance of small differences in job satisfaction, using Cohen’s (1992) cutoff given that this variable is related to individual and unit-level outcomes. With the meta-analytic relationship between job satisfaction and performance being a true score correlation of 0.30 (Judge et al., 2001), small, medium, and large effect sizes are associated with a 0.06, 0.15, and 0.40 SD increase in performance. Harter et al. (2002) reported roughly similar magnitudes for customer satisfaction (0.32), profit (0.15), productivity (0.20), turnover (−0.36), and safety (−0.20). Thus, a 0.2 SD difference on satisfaction is associated with differences of 0.03 to 0.07 SDs on these other criteria. On a related note, assuming a 50-50 split between generational groups, a Cohen’s (1992) d of 0.2, is equivalent to a correlation of 0.10. Assuming that generational differences impact performance only through job satisfaction, this suggests an indirect effect of 0.2 ×0.3 or 0.06. The indirect effect is in correlational units – thus, it is and essentially a criterion-related validity coefficient. The US Department of Labor (2000) interpreted validities below 0.11 as “unlikely to be useful” (Chapter 3, p. 10). Consequently, we suggest that a small effect size using Cohen’s (1992) cutoff has minimal impact for organizations.
Table III provides average effect sizes for comparisons between the various generational groups. We used only the age groups that are defined by a single generation (see Table II) when computing these averages. The magnitude of generational differences is small to near-zero for most the items using all of the effect size criteria mentioned above. The results for the general factor and subscale scores, provided in the first row of Table III, also show small differences between generations when the items are combined to form more reliable composites.
256
JMP 33,3
Effect sizes computed using the EMMs (also shown in Table III) suggest that the results hold-up when the effects of the general factor on each item are controlled.
Histograms of the d-values for the item comparisons for different generations are in the Supplementary File (https://drive.google.com/file/d/1DwtnLfTSzPSDvqDKppI9Bi_GuTRm 5aok/view?usp=sharing). Only a handful of items had a |d| of 0.20 or higher, which is at Cohen’s (1992) cutoff for a small effect, near Bosco et al.’s (2015) 0.18 cutoff for a medium effect, and at Paterson et al.’s (2016) cutoff of 0.20 for the 20th percentile. In general, those items (No. 5, No. 6, and No. 19) tend to suggest that Millennials are slightly less satisfied with the duties they perform, compared to other groups. This might suggest that Millennials are less satisfied with their jobs; however, their scores on the general factor were actually slightly higher than Boomers and Generation X (d ¼ 0.11 and 0.10, respectively). Compared to Boomers and Generation X, Millennials were also slightly more likely to feel respect for their leaders (No. 34), to feel their workload is reasonable (No. 16), and to report having sufficient work-related resources (No. 15). Overall, Traditionals had a somewhat higher score on the general factor than Boomers and Generation X (d ¼ 0.17 and 0.24, respectively). A number of items did have |d| of 0.20 or higher when Traditionalists were compared to Boomer and Generation X; however, after controlling for the differences in the general factors, only one item (concerning how poor performers were handled) had a |d| of 0.20 or higher.
In terms of the speculated differences, we present the results for the items that were speculated to have generational differences, bolding d and dEMM within each dyad found in Table III. The mode rating was used to indicate which items were speculated to differ and only a few had a |d| of 0.20 or higher (recall that the speculation was based on the generational differences pop-literature). In terms of the additional items measuring work motivation administered in 2010, 2011, and 2012, the |d|-values were always less than 0.20.
Additional analyses. Recall that age group variables were collapsed and recoded into generational groups. A reviewer inquired about the magnitude of effect sizes of differences in the uncollapsed and originally coded variables. Cohen’s (1992) d-values for these comparisons were small (see the Supplementary File (https://drive.google.com/file/d/1DwtnLfTSzPSDvqDK ppI9Bi_GuTRm5aok/view?usp=sharing) for these results). A reviewer also questioned whether the results would be similar when controlling for tenure and other variables. We obtained EMMs for the items and scales controlling separately for the following five variables: location (i.e. field or headquarters), supervisory status, tenure at agency, agency, and component (of the agency). We also conducted simultaneous controls using either agency or component and the remaining variables. The results, which can be found in the Supplementary File (https://drive. google.com/file/d/1DwtnLfTSzPSDvqDKppI9Bi_GuTRm5aok/view?usp=sharing), indicate that generational differences were small even when controlling for these variables.
Study 2 This study replicated the findings of Study 1 using a separate data set that included respondents from both the public and private sectors. The general hypothesis and literature review for Study 2 is similar to Study 1; thus, we focused on describing the methodology and results. Study 2 used data from the 1979 cohort of the National Longitudinal Study of Youth (NLSY), which is a longitudinal study conducted by the US Bureau of Labor Statistics. As part of the NLSY, 12,698 high-school students were randomly sampled from the US population. They had birth years ranging from 1957 to 1965, placing them in both the Baby Boomer generation (i.e. birth years 1945-1962) and Generation X (i.e. birth years 1963-1978). That said, we adopted a slightly different definition of generation in Study 2. In Study 1, we used the generational cutoffs by birth year; another approach to defining generation is to compare parents and their children, as is often the case in family trees. Thus, in Study 2 we directly compare job satisfaction between the 1979 cohort and the offspring of the female participants, who were studied
257
Generational differences in
workplace attitudes
beginning in 1994 (the offspring of male participants were not surveyed). Both samples were administered a global job satisfaction question, allowing us to compare the job satisfaction of the 1979 cohort to their offspring.
Method Both the 1979 and the offspring NLSY cohorts were administered a one-item job satisfaction question using a verbal interview roughly every other year. In some years, participants were able to provide job satisfaction ratings for more than one employer that they worked for in a given year. We only included data from the current or most recent employer (denoted as “job #01” in the NLSY data sets that contain data for more than one employer).
Job satisfaction was measured using an item that read “How [do/did] you feel about your job with [Name of employer]? [Do/Did] you like it very much, like it fairly well, dislike it somewhat, or dislike it very much?” with the following response options: “1. Like it very much,” “2. Like it fairly well,” “3. Dislike it somewhat,” and “4. Dislike it very much.” (Note that unlike Study 1, lower scores on this scale are associated with higher levels of job satisfaction.) The 1979 and 1982 administrations included additional employee-survey items. Factor analytic research indicated that most of the items loaded onto a general factor; cross-validated confirmatory factor analyses yielded good fit (NFI ¼ 0.950 in 1979 and NFI¼ 0.970 in 1982) and correlations of 0.737 and 0.674, respectively, between the global item and the general factor (Cucina et al., 2014).
Results Job satisfaction data were available for both the 1979 cohort and their children every even numbered year from 1994 to 2010. In addition, the 1979 cohort also has data from 1980 to 1992 and the children have data from 2012. Table IV contains the sample sizes, means, SDs, and ds (when applicable) for the two samples and Figure 1 presents a longitudinal
1979 cohort Children (95% confidence interval) Year n M SD n M SD p d Low High
1980 6,741 1.85 0.76 1981 7,176 1.85 0.75 1982 10,078 1.85 0.79 1983 7,671 1.74 0.74 1984 10,213 1.78 0.78 1985 9,361 1.72 0.75 1986 9,280 1.71 0.74 1987 9,188 1.70 0.71 1988 9,220 1.75 0.74 1989 9,291 1.69 0.73 1990 9,141 1.69 0.74 1991 7,728 1.67 0.72 1992 7,769 1.68 0.73 1993 7,702 1.69 0.73 1994 7,590 1.68 0.72 532 1.83 0.82 o0.001 −0.21 −0.12 −0.30 1996 7,636 1.66 0.72 975 1.92 0.80 o0.001 −0.36 −0.29 −0.43 1998 7,518 1.61 0.69 1,221 1.88 0.82 o0.001 −0.37 −0.31 −0.44 2000 7,240 1.60 0.69 2,224 1.82 0.85 o0.001 −0.30 −0.25 −0.35 2002 6,900 1.59 0.69 2,940 1.89 0.86 o0.001 −0.41 −0.36 −0.45 2004 6,672 1.59 0.68 3,596 1.88 0.86 o0.001 −0.38 −0.34 −0.42 2006 6,667 1.60 0.70 4,357 1.82 0.83 o0.001 −0.30 −0.26 −0.34 2008 6,710 1.59 0.69 4,892 1.80 0.83 o0.001 −0.29 −0.25 −0.33 2010 6,364 1.60 0.69 4,692 1.83 0.83 o0.001 −0.31 −0.27 −0.35 2012 4,796 1.79 0.81
Table IV. Generational differences in overall job satisfaction for 1979 NLSY cohort and children
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plot of the data. Both Table IV and Figure 1 show that the 1979 cohort consistently had higher levels of job satisfaction. The generational differences were always statistically significant and slightly larger than in Study 1 with a median absolute value of 0.31. This is in the small range of Cohen’s (1992) cutoffs, the medium range of Bosco et al.’s (2015) cutoff, and at the 35th percentile for Paterson’s et al.’s (2016) results.
Discussion Our studies showed statistically significant, but practically small, generational differences in work-related attitudes. We corroborated some of past research on this topic (e.g. Costanza et al., 2012; Deal, 2007; Deal et al., 2013); however, we ruled out the possibility that sampling error could have reduced the magnitude of the results in past research. We also found a lack of practically significant generational differences at the item-level on employee surveys. Past studies focused on construct-level differences, leaving open the possibility that generations may differ significantly on item-level attitudes.
In Study 1, we found little support for our speculations concerning items that might show generational differences. Given the large sample sizes and small CIs, it seems reasonable to conclude that generational differences in employee attitudes were not very large. In most cases, the d-values were 0.3 or less, indicating that less than 2 percent of the variance in employee attitudes is due to generations.
Study 1 reported slightly lower generational differences than Study 2. Study 1 included only employees who work for the US Federal Government (a broad organization) and employees were nested within agencies and subagencies. Study 2 included a representative sample of the US population. Schneider’s (1987) attraction-selection-attrition model may offer a potential conceptual basis for this finding. Organizations attempt to recruit employees who will fit in with the organization’s values. Employees who do not fit in are likely to turnover eventually which could cause work attitudes and values to be more homogeneous within an organization over time, leading to lower generational differences in Study 1.
Future researchers could examine differences in job performance (perhaps the most important construct in I/O psychology) across generations. Previous research indicates a near-zero (i.e. −0.01) correlation between age and job performance (Schmidt and Hunter, 1998). However, this research is nearly 30 years old.
Limitations Study 1 was limited by the use of a cross-sectional design to analyze the data. Study 2 used a cross-temporal design, but our work would have been stronger if Study 1 was also cross-temporal. As noted by an anonymous reviewer, cross-sectional design has been a major limitation to generational research. When differences are found, it cannot be ruled out that maturational effects led to the results since age and generation are confounded.
0
0.5
1
1.5
2
2.5
3
3.5
4
1980 1985 1990 1995 2000 2005 2010
1979 Cohort Child
Figure 1. Longitudinal plot of
overall job satisfaction for 1979 NLSY cohort
and children
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Although preferable, longitudinal research is difficult to conduct and would require decades of data collection. A related limitation of our two studies is the difficulty in determining whether the small generational differences we found were due to maturational influences (e.g. differences in age and participant’s location on a developmental lifespan) vs cohort influences (e.g. differences in societal forces or other factors that cause individuals with similar birth years to be different from other individuals regardless of age and maturation). Study 2 does address this limitation, in part, by comparing job satisfaction for two generations across time. However, additional research is likely needed to tease out the underlying influences of the small generational differences.
An anonymous reviewer mentioned several potential confounds with the data from Study 2. In order to address potential confounds of age, generation, and sample composition upon job satisfaction in the data from Study 2, we performed additional post hoc analyses using linear and non-linear analyses. We investigated whether age was related to job satisfaction in the child sample for each year the study was conducted and found correlations that were less than 0.10 in each instance. Curvefitting analyses were conducted in SPSS to determine if any non-linear relationships exist; we did not find evidence of non-linearity. Thus, it appears that age only has a small influence on job satisfaction in the child sample. To address the possibility that mothers who had children had different levels of job satisfaction, we reran the analyses removing participants who did not have children. We obtained a similar median effect size (−0.32) as in the original analysis (−0.31). We also reanalyzed the data by including only mothers and their daughters and found a median effect size of −0.35, which is very similar to the original value. Additionally, we also examined the relationship between the age at which the first child was born and job satisfaction for each year and found small correlations (mean r ¼ −0.03; maximum|r| ¼ 0.06); there was no evidence of non-linearity in the data. The additional analyses are available in the Supplementary File (https://drive.google. com/file/d/1DwtnLfTSzPSDvqDKppI9Bi_GuTRm5aok/view?usp=sharing).
We could not control for some key variables such as occupation because of limitations of the data set. It could be that generational differences in work attitudes are found in some occupations but not others, and we believe this would be an important question to address in future research. A limitation to Study 2 was our use of offspring of an original cohort, rather than a random sample of the population. Another limitation is the job satisfaction measures used. Study 2 used a one-item measure and some of the items in Study 1 were double-barreled or non-specific. Finally, the generalizability of results is limited as our study focused very narrowly on work attitudes such as job satisfaction.
Practical implications Our findings suggest that generational differences in workplace attitudes are small, yet, we are aware that many managers in organizations report the presence of generational differences. In general, the largest effect sizes we saw were in Study 2, which had a Cohen’s (1992) d of about 0.30. A reviewer asked us how managerial psychologists might explain this effect size to managers. We think that this discussion could begin by stating that research studies on generational differences in workplace attitudes have reported statistically significant, but small differences. Information on the size of the differences could be conveyed using the following points:
• Statisticians compute a variable called the standard deviation to describe the distribution of scores. Generally, almost 100 percent of the scores are within three standard deviations of the average score. Looking at generational differences, there was only a 0.3 standard deviation in the scores for different generations.
• If we look at the distribution of scores on workplace attitudes for two different generations, the two distributions overlap by 79 percent.
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• There is far more (49 times) variance within generations than between generations. Only 2 percent of the variance in workplace attitudes is due to generational differences. The other 98 percent of the variance lies within each generation.
• Votraw and Cucina (2016) developed an infographic depicting a Cohen’s (1992) d of 0.5 in SAT scores; they also provide additional information on conveying effect sizes. Managerial psychologists could consult that paper for additional ideas.
It is possible that managers are noticing and reporting the small effect size generational differences that we report in this paper. Exaggerating or selectively attending to behavior and attitudes stereotypical of different generations might explain why managers tend to report larger differences than those that actually exist. Alternately, it is possible that generational differences truly exist, but are not manifested as differences in employee attitudes (or even job-related individual differences such as job performance).
Some research exists that suggests that generational differences are best defined in terms of perceptions. There is qualitative evidence that individuals define themselves and others in terms of generational membership (Urick and Hollensbe, 2014). These perceived differences can lead to intergenerational conflict according to work by Urick et al. (2017). Similarly, Foster (2013) provides evidence of generational differences from qualitative data she collected from narratives and stories by employees in different generations. However, Foster (2013) also dispels a number of generational myths and McDaniel (2013) suggested that Foster (2013) should be “required reading” for organizational leaders and human resource professionals. So, managerial psychologists working with organizations could suggest that clients concerned about generational differences read Foster (2013).
We suggest that managers approach news articles describing generational differences in work attitudes with a healthy skepticism, given the lack of practically significant differences found in this study. Our findings suggest that practitioners conducting employee surveys might not want to put in the effort of examining generational differences in employee surveys given the magnitudes of the effect sizes we found. Furthermore, if an organization believes it is experiencing generational conflict, a more focused investigation might be required (e.g. focus groups or surveys focusing on generational conflict). In this situation, team building or diversity-focused training interventions might be considered.
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Corresponding author Jeffrey M. Cucina can be contacted at: jcucina@gmail.com
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