ArticlePDF Available

Measuring work styles: Towards an understanding of the dynamic components of the Theory of Work Adjustment

Authors:

Abstract and Figures

Work styles are an important yet largely unexplored component of the Theory of Work Adjustment (TWA), describing a dynamic component of how individuals maintain and adjust fit with their work environment. The Active Work Style Scale (AWS) is the first attempt to develop a specific self-report measure of work styles suitable for longitudinal research. Results from three studies support Dawis and Lofquist (1984) proposed four factor structure, but these factors are related through a second-order factor describing a person’s generalised level of work activity and effort across time. The AWS scale demonstrated good evidence for the reliability and validity, and strong measurement invariance across time signifying its suitability for longitudinal research. In line with expectations, overall work style was positively related to conscientiousness and work engagement yet unrelated to stress. When controlling for these variables, AWS was positively related to demands-abilities fit, but not needs-supplies fit. Limitations and possibilities for future research are also discussed.
Content may be subject to copyright.
Measuring work styles: Towards an understanding of the
dynamic components of the theory of work adjustment
Piers H. Bayl-Smith
,1
, Barbara Grifn
Department of Psychology, Faculty of Human Sciences, Macquarie University, Australia
article info abstract
Article history:
Received 29 May 2015
Received in revised form 7 August 2015
Accepted 13 August 2015
Available online 18 August 2015
Work stylesare an important yet largely unexplored componentof the theory of work adjustment
(TWA), describing a dynamic component of how individuals maintain and adjust t with their
work environment. The active work style (AWS) scale is the rst attempt to develop a specic
self-report measure of work styles suitable for longitudinal research. Results from three studies
support Dawis and Lofquist's (1984) proposed four factor structure, but these factors are related
through a second-order factor describing a person's generalised level of work activity and effort
across time. The AWS scale demonstrated good evidence for reliability and validity, and strong
measurement invariance across time signifying its suitability for longitudinal research. In line
with expectations, overall work style was positively related to conscientiousness and work en-
gagement yet unrelatedto stress. When controlling for these variables, AWS was positively relat-
ed to demandsabilities t, but not needssupplies t. Limitations and possibilities for future
research are also discussed.
© 2015 Elsevier Inc. All rights reserved.
Keywords:
PEt
Theory of work adjustment
Work styles
Reliability
Validity
Personenvironment (PE) t theories have been widely utilised in industrial and organisational psychology for over 100 years
(Kristof-Brown, Zimmerman, & Johnson, 2005). Contemporary research has applied this framework to examine a wide range of
work domains including employee recruitment and selection (Carless, 2005), job attitudes (Verquer, Beehr, & Wagner, 2003), on-
job behaviour and performance (Hoffman & Woehr, 2006; Kristof-Brown et al., 2005), and job withdrawal and tenure (Donohue,
2006). Despite the prominence of PEt literature, one signicant limitation has been the conception of t as a static structure
(Jansen & Shipp, 2013; Kristof-Brown & Guay, 2011). PEt has predominantly viewed the person and the environment as relatively
stable entities, the correspondence of which determines the level of t and consequent outcomes (Caldwell, Herold, & Fedor, 2004).
However, both environment and persons are increasingly recognised as being in constant transition. For example, technological
change, mergers and acquisitions, and market globalisation have created organisational environments that are constantly in ux
(Pulakos, Arad, Donovan, & Plamondon, 2000). Furthermore, over time individuals experience change in their cognitive processes
(Bandura, 1999), abilities (Kanfer & Ackerman, 2008) and motivations (Kooij, Lange, Jansen, & Dikkers, 2008). Given the variability
within the person and the environment, both need tocontinually enact maintenance and adjustment behaviours in order to conserve
or achieve correspondence (Dawis & Lofquist, 1984). PEt research has predominantly neglected these processes, focusing more on
snapshot measurements of t at particular instances of time (Kristof-Brown & Jansen, 2007).
The theory of work adjustment (TWA; Dawis & Lofquist, 1984), by specifying both structural and dynamic components of PEt,
providesan important framework through which to understand theprocessesof mutual adaptation and adjustment (Jansen & Shipp,
Journal of Vocational Behavior 90 (2015) 132144
Special thanks to Beryl Hesketh, Emeritus Professor, Ofce of the Vice-Chancellor and President, University of Western Sydney, for providing useful feedback re-
garding the items in the active work style scale.
Corresponding author at: Department of Psychology, Faculty of Human Sciences, Macquarie University,NSW 2109, Australia.
E-mail address: piers.bayl-smith@mq.edu.au (P.H. Bayl-Smith).
1
Piers Bayl-Smith is currently receiving an APA scholarship.
http://dx.doi.org/10.1016/j.jvb.2015.08.004
0001-8791/© 2015 Elsevier Inc. All rights reserved.
Contents lists available at ScienceDirect
Journal of Vocational Behavior
journal homepage: www.elsevier.com/locate/jvb
2013). To describe the structural component of t, Dawis and Lofquist (1984) suggest that satisfactory performance results from the
correspondence between the abilities o f the person and those demanded by the environment ( demandsabilities t), and that job sat-
isfaction results from the correspondence between values supplied by the environment and those needed by the person (needssup-
plies t). Ultimately, tenure is seen as a consequence of reciprocal satisfaction. Understood as such, the structural component of TWA
is not dissimilar from other general theories of PEt.
However, TWA is uniquein that it differentiates this structural component of t from dynamicprocesses, labelled as style variables,
to explain how individuals and organisations are actively engaged in maintenance and adjustment behaviours to achieve ongoing t
(Dawis & Lofquist, 1984; Dawis, 2005). Here, adjustment behaviours aimed at decreasing mist are further distinguished from work
styles. In the presence of mist, an individual may engage in adjustment behaviours to increase their t by either acting upon the en-
vironment or acting upon themselves. Work styles on the other hand describe an individual's characteristic way of interacting with
their work environment and operate to maintain and adjust t. Whilst there has been some attention given to understanding proac-
tive and reactive adjustment behaviours, albeit largely outside the PEt literature (Grifn, Neal, & Parker, 2007; Pulakos et al., 2000),
the work styles concept has been largely ignored in empirical research despite its being anintegral part in such a key theory. The cur-
rent paper highlights this lesser known aspect of TWA, providing a measure to allow ongoing researchon variables that offer explan-
atory power for improving PEt over time.It is important to note that the environment likewise has style variables associated with
maintaining and increasing t, however the focus of this paper will be upon the behaviours and actions of the employee.
1. Work styles
Work styles were originally conceived as stable, trait-like attributes of the employee, developing in childhood through experimen-
tation and reinforcement, crystallised in adulthood, and declining as a result of physiological change due to the ageing process (Dawis
&Lofquist,1984). However, reecting later developments in the eld of personality (McCrae & Costa, 2008), work styles have more
recently been conceived as being responsive to inuences such as personal cognitions, social identities and environmental constraints
(Hesketh, Grifn, Dawis, & Bayl-Smith, 2015).
Work styles are distinguished by four specic characteristics; celerity, pace, rhythm and endurance. Respectively these describe
how quickly an employee typically initiates work behaviours, the usual levels of energy applied to work tasks, the characteristic pat-
terns of effort, and the degree to which the employee will persevere in doing tasks (Dawis, 2005; Hesketh et al., 2015). Dawis and
Lofquist (1984) describe work styles as an employee's skills and abilities (labelled as personality structure) in action. An individual
therefore may be described as having both a structural component their skills and abilities; as well as a dynamic component
their typical work style and adjustment behaviour. Consequently, even if an individual has a good t with their environment structur-
ally (i.e., they have the appropriate skills and abilities to meet the demands of their job), if the work style is inadequately expressed,
there will bea decrease in actual t and the requirements of the employer will not be satised. Alternatively, if t is poor structurally,
an employee may engage in a work style that maintains or even increases their actual t to satisfy the requisites of the organisation.
Work styles thus envisaged have a direct relationship with maintaining and adjusting t, as well as moderating the relationship be-
tween t and satisfaction (Dawis & Lofquist, 1984; Dawis, 2005).
As mentioned, there has been no research conducted upon work styles, apart from an early study by Lawson (1993) and a recent
theoretical application of TWA to older workers (Hesketh et al., 2015). This in part might be resultant from a lack of a suitable mea-
surement instrument (Dawis, 2005). It may also be due to the lack of longitudinal studies of changing PEt, which is clearly integral
to any study of a dynamic model. This paper goes someway in addressing this decit by rst describing work style facets, as well as
validating a short self-report scale suitable for longitudinal research.
Celerityis dened as the typical speed of responding to the environment or of initiating work behaviours (Dawis & Lofquist,
1984). Those who have high levels of celerity are thought to start job assignments early and respond quickly to work cues. The oppo-
site may be described as one who routinely delays performing tasks and making decisions. Stated as such, celerity may share some
conceptual links with time urgency or the facet of hurriedness (Landy, Rastegary, Thayer, & Colvin, 1991). Though unlike time urgen-
cy, celerity is more focused on the latency of response in the work environment, rather than generalised speed or hurriedness whilst
completing tasks (Dawis & Lofquist, 1984). Furthermore, hurriedness may indicate a level of recklessness which is not necessarily im-
plied by celeritous individuals. Celerity at low levels also bears somesimilarities with procrastination; though procrastination isoften
represented as avoidance behaviour not purposely planned (Van Eerde, 2003). Low celerity does not have this association; it merely
indicates someone who does not typically start on work tasks straight away.
Pacerefers to the habitual level of energy applied to work tasks (Dawis & Lofquist, 1984). High levels of pace are marked by an
appearance of busyness and constant engagement in work activities. However, pace is not merely effort working hard towards a
desired goal or performance level (Yeo & Neal, 2004) or doing one's best (De Cooman, De Gieter, Pepermans, Jegers, & Van Acker,
2009). Rather, pace is concerned more specically with employee levels of activity and consumption of energy. Whilst someone
who expends energy towards work tasks may describe their activity as hardworking, hardworking may also depict aspects of celerity,
rhythm and endurance. Hence pace needs to be carefully distinguished from broader conceptions and measures of effort intensity
(e.g., De Cooman et al., 2009).
Rhythmdescribes the typicalpattern of exerted effort at work; ranging from steady to erratic (Dawis & Lofquist, 1984). Someone
who has a steady rhythm typically functions atthe same level of effort or intensity, regardless of whether that levelof effort is high or
low. In contrast, an unstable or erratic rhythm is characterised by an employee displaying a lack of regularity or pattern in their work
efforts. To date, the concept of work rhythm has been relatively unexplored (Jansen & Kristof-Brown, 2005). Gold, Park, and Punnett
(2006) discuss routinization, where tasks are described as routine when the work cycle varies little, and non-routine when employee
133P.H. Bayl-Smith, B. Grifn / Journal of Vocational Behavior 90 (2015) 132144
activity cannot be predicted at a specied point in time. Here however, the focus is primarily upon rhythm within the environment
rather than rhythm within the person. Jansen and Kristof-Brown (2005) also recognise that different work environments have differ-
ent rhythms, though individual rhythms are conceived and measured as time urgency instead of characteristic patterns of effort
displayed in the work place.
Enduranceis dened as the customary amount of time applied to work tasks or interaction with one's environment (Dawis &
Lofquist, 1984). Endurance here needs to be distinguished from diligence, persistence in the face of adversity or working hard,
which is more characteristic of grit (Duckworth, Peterson, Matthews, & Kelly, 2007). Those with high endurance are characterised
simply by the maintenance of effort over long periods of time, often exemplied bythe completion of long-term projects. In contrast,
low endurance is typied by giving up on or not completing work tasks.
Together, the level of celerity, effort, rhythm and endurance describes the typical wayin which a person interacts with their work
environment. An individual may exhibit varying levels across different work style facets. For instance an employee with low celerity
but high effort would describe someone who often delays starting their tasks, yet expends high levels of energy once started. Even
though the original conception of work styles within TWA emphasised variability amongst its facets (Dawis & Lofquist, 1984), we
would argue that an employee may well exhibit uniformity across all four work style facets. This argument has two premises. First,
work styles are appropriately understood to be a characteristic adaptation that occurs over time rather than something that is basic
to or inherent in the person. Second, this adaptive development of work styles is inuenced by a wide range of factors, such as
organisational culture, personality,self-efcacy, identity and stereotyping. These are likely to impact the work style facets uniformly
such that they each correlate with these factors in a similar manner (Hesketh et al., 2015). For example, if an organisation is under-
stood to be supportive and enabling, employees willbe more likely to invest greater intensityand duration of effort over time across
all work style facets (Brown & Leigh, 1996). Likewise, if an employee has low-levels of self-efcacy it will likely have a negative impact
not only upon how much effort is expended, but also upon their speed of response, rhythm of effort and level of endurance (Hesketh
et al., 2015). Therefore, high levels of celerity, pace, rhythm and endurance would indicate an overarching approach to work that is
continually active, whilst low levels may denote an employee who is disengaged. Such a relationship between facets would be best
described by a second order factor that delineates an overall style of active and effortful interaction with one's work environment.
2. Construct validity: work styles, personality and work engagement
Two important factors likely to be signicantly related to work styles that are explored in this research include personality and
work engagement. The relationship of personality traits to TWA has not been extensively explored (Dawis, 2005), with several au-
thors criticising early articulations of TWA for not adequately taking into accountdevelopments in personality theory, namely the for-
mulation of the ve-factor model or Big 5 (Brown, 1993; Tinsley, 1993). In response, Dawis and Lofquist (1993; Dawis, 1996)
endeavour to distinguish personality traits, conceived as a static structural component of the individual, from style factors, the dynam-
ic factors within the individual that are enacted towards maintaining and adjusting t. Dawis (1996) described the potential associ-
ation with extraversion, suggesting that it may be related more to the work style facet of pace than the other styles given that
extraversion is associated with being sociable, assertive and active (Barrick & Mount, 1991).
In further developing the link between TWA and personality, Hesketh (1995) notes that work styles taken together may provide
an unique way of understanding conscientiousness in a work context. As work styles describe a person's response latency, intensity,
pattern and endurance of effort,work styles are likely to coincide with the volitionalcomponent of conscientiousness, characterised as
hardworking, persevering, and dependable (Barrick & Mount, 1991). That is, someone who is conscientious is likely to start their work
tasks sooner, apply higher levels of effort consistently over time and complete required tasks. However, these personal features of the
individual should not be confused with personality itself or a person's basic tendencies (McCrae & Costa, 2008); rather an individual's
work styles are best conceived as characteristic adaptations inuenced by multiple internal and external factors (Dawis & Lofquist,
1984; Hesketh et al., 2015). Therefore, work styles should exhibit a moderate to strong relationship with conscientiousness, but yet
not be so highly correlated that they would be considered to be empirically the same construct.
Work styles should also be signicantly related to work engagement. Work engagement is dened as a positive work related state
of mind characterised by vigour, dedication and absorption (Schaufeli, Salanova, Bakker, & Gonzales-Roma, 2002). Together, work en-
gagement describes an employee's willingness to invest effort at work, feel involved and enthused about work, and to experience
work as enthralling and captivating (Schaufeli & Bakker, 2006). Previous research has indicated that highly engagedemployees exhib-
it a willingness to expend more effort at work, as well as exhibit more initiative (Hakanen, Bakker, & Schaufeli, 2006; Hakanen,
Perhoniemi, & Toppinen-Tanner, 2008). Therefore, we would expect work styles to be positively related to work engagement, such
that highly engaged employees will exhibit high levels of celerity, pace, constancy of rhythm and lengthy endurance.
Below, we present three studies with the aim of determining and validating a self-report measure of work styles.
3. Study 1A: item generation and exploratory analysis
The purpose of this study was to generate a suitable pool of items to measure the four facets of workstyles; celerity, pace, rhythm
and endurance. In linewith recommendations for scale development (e.g. DeVellis, 1991), several steps were undertaken to develop a
suitable self-report instrument. First, TWA literature and extant scales tapping similar constructs were examined to create an initial
pool of items.Second, this pool of items was reviewed by subject matter experts. Third, the items were administered to a development
sample of working adults and responses examined to determine which items to discard or retain. Finally, the scales were analysed for
reliability (using Cronbach's alpha) and scale correlations were computed.
134 P.H. Bayl-Smith, B. Grifn / Journal of Vocational Behavior 90 (2015) 132144
3.1. Item generation
Items were generated to reect unidimensional measures of a person's typical level of celerity, pace, rhythm and endurance that
discriminate the individual facets without disproportionate conation. Therefore, items such as Iworkhardwere deemed unsuit-
able as theycould be applied to multiple workstyle components, and thus were avoided. Asrecommended (DeVellis, 1991), the initial
pool of items generated by the rst author were reviewed by Barbara Grifn and Beryl Hesketh (who have written extensively on the
TWA; e.g. Grifn & Hesketh, 2003; Hesketh & Grifn, 2005; Hesketh et al., 2015) to evaluate the items' clarity, conciseness and rele-
vancy to theintended construct. This processresulted in 20 items to measure the work style facets overall asdened by the TWA (six
celerity items, ve pace items, four rhythm items, ve endurance items).
3.2. Participants
Participants were recruited using the snowballing sample technique via two social media sites (Facebook and LinkedIn). Potential
participants were messaged an invitation to take part in a short online study and to share the link with others who also might be in-
terested. The study was restricted to Australian residents currently employed and working at least 8 h per week. Of the 139 who
responded, 59.0% were female and their mean age was 34.02 years (SD = 15.08 years). The majority of participants (58.3%) indicated
that they were employee/team members, 20.1% were employed in middle management, and the remaining 21.6% identied as senior
managers or above. On average respondents worked 33.53 h per week (SD = 17.09 h).
3.3. Measures
Using a 5-point Likert-type scale (1 = Never to 5 = Always), respondents were asked how often in the last month they did each
listed behaviour at work. An example item was, I startedprojects and tasks straight away.The 20 work style items were presented to
each participant in a random order to minimise any ordering effects.
To determine whether the created items belong to a specic scale and to identify their factor structure, a number of steps were
undertaken (De Vaus, 2002). First, to determine that each item measured their intended construct, the pattern of item correlations
was examined and four principal component analyses (PCA's) were conducted on items for each expected factor. PCA was chosen
for this initial stage of analysis as it provides an appropriate method of screening items and summarising sets of variables into
fewer components (Fabrigar, Wegener, MacCallum, & Strahan, 1999; Matsunaga, 2011). Items that did not load sufciently (N.40)
onto their respective factor were excluded from further analysis. Within each work style facet, inter-item correlation ranged from
r=.40tor= .68. Second, utilising principle axis factoring (PAF) with oblique rotation, the surviving items were subjected to an ex-
ploratory factor analysis (EFA) to determine their factor structure. Unlike PCA, PAF is used to understand the association between var-
iables with a focus upon latent factors, hence was deemed appropriate for this stage of the analysis (Fabrigar et al., 1999; Henson,
2006). Parallel analysis was used to determine the number of factors to retain in the EFA (Henson, 2006; Matsunaga, 2011). Third,
items with low loading or high cross loadings were eliminated one at a time, with the parallel analysis and EFA being repeated
until a satisfactory solution was acquired. All analysis in this study was conducted using SPSS version 21.
3.4. Results
From the PCA, four items were identied as not adequately loading onto their expected factor and thus were excluded from further
analysis. Parallel analysis of the remaining 16 items indicated a four factor solution, which was then specied in a PAF with oblique
rotation (Promax, κ= 4). Five further items were eliminated from the analysis due to low loadings (b.40) or high cross-loadings.
In sum, three celerity, three pace, three rhythm and two endurance items were retained, each loadingonto their expected factors. Par-
allel analysis continued to indicate the retention of four factors, whichaccounted for 73.9% of the total variance. Internal reliability for
each work style facet, measured using Cronbach's αranged from .71 to .83. The correlations between each component were signi-
cant (pb.001) ranging from r=.43tor=.58,indicatingasubstantialrelationship between work style factors (De Vaus, 2002).The
wording and factor loadings of the items are shown in Table 1.
The emergence of four factors with sensible item loadings in part provides empirical corroboration of work styles as explicated in
TWA. The size of correlations amongst the work style facets may also be indicative of an overall second-order work style factor as sug-
gested above, where high levels of celerity, effort, stability and endurance describe an overarching approach to work that is continu-
ally active.
4. Study 1B: post-hoc validation analysis
Following the identication of the four work style factors, a post-hoc analysis was conducted to provide a preliminary examination
of construct validity with respect to the relationship between personality and work styles.As noted above, the two factors within the
ve factor model that have been linked to work styles (Dawis, 1996; Hesketh, 1995) are extraversion and conscientiousness, both of
which are included in this study.
135P.H. Bayl-Smith, B. Grifn / Journal of Vocational Behavior 90 (2015) 132144
4.1. Measures
All means, standard deviations and reliability coefcients (Chronbach's alpha) are shown in Table 2.
4.1.1. Work styles
Celerity, pace, rhythm and endurance were calculated by obtaining the mean scores of their respective items developed from
Study 1A.
4.1.2. Personality
Extroversion and conscientiousness were measured using 8-item scales from Saucier (1994). Using a 9-point Likert-type scale
(1 = Extremely inaccurate to 9 = Extremely accurate), participants were asked to indicate how accurately an adjective trait generally
described them. Example items for extroversion include Energeticand Withdrawnwhilst example items for conscientiousness in-
clude Efcientand Disorganised.
4.2. Results
This preliminary analysis was conducted by examining the correlations (see Table 2) between the measured constructs. All work
style facets were positively related with extroversion and conscientiousness. However, the correlations were all in the small to mod-
erate range indicating that these are distinct constructs. Additionally, in support of Dawis (1996),extroversionwasrelatedtopace
more strongly than the other work style factors. Overall, these results provide preliminary support for the construct validity of the
work style items.
5. Study 2: CFA and longitudinal measurement invariance
To further evaluate the suitability of the factor structure identied in Study 1A, two competing factor models were tested in Study 2
using conrmatory factor analyses (CFA). Furthermore, longitudinal measurement invariance was tested in order ascertain whether
Table 2
Study 1B: Summary of intercorrelations, means, standard deviations and reliability coefcient alphas.
MSD1 23456789
1. Gender .59 .49
2. Age 34.02 15.08 .20
3. Work hours/week 33.53 17.09 .35⁎⁎ .52⁎⁎
4. Celerity 3.73 .66 .25⁎⁎
.12 .08 (.72)
5. Pace 3.97 .65 .17.10 .17.43⁎⁎ (.83)
6. Rhythm 3.71 .72 .12 .01 .07 .52⁎⁎ .58⁎⁎ (.82)
7. Endurance 4.28 .61 .17.07 .08 .47⁎⁎ .49⁎⁎ .49⁎⁎ (.71)
8. Extroversion 6.24 1.38 .10 .24⁎⁎ .29⁎⁎ .18.44⁎⁎ .25⁎⁎ .25⁎⁎ (.87)
9. Conscientiousness 7.03 1.11 .09 .31⁎⁎ .29⁎⁎ .39⁎⁎ .43⁎⁎ .48⁎⁎ .44⁎⁎ .29⁎⁎ (.83)
Note. Reliability coefcients (Cronbach's alpha) are in parentheses on the diagonal. Gender 0 = male, 1 = female.
pb.05.
⁎⁎ pb.01.
Table 1
Factor loadings with Promax rotation for the nal active work style (AWS) scale from Study 1 and Study3.
Variable 1234
I started projects and tasks straight away .82 (.72) .04 (.02) .05 (.15) .06 (.09)
I was quick to start my jobs .72 (.67) .00 (.07) .06 (.10) .11 (.15)
I delay my efforts at the start of a work project or task (reversed) (.56) (.14) (.05) (.10)
When given a task or project I began working on it immediately
a
.95 ().05 ().07 ().05 ()
I put a lot of energy into my work tasks .14 (.10) .58 (.60) .15 (.19) .08 (.40)
I expended a great deal of effort in carrying out my job .12 (.01) .83 (.79) .01 (.04) .12 (.12)
I used a high amount of effort and energy .12 (.10) .75 (.85) .06 (.03) .09 (.04)
My level of effort was steady over time .02 (.28) .06 (.04) .82 (.65) .01 (.14)
The levels of energy I put in was highly stable over time .07 (.14) .10 (.01) .74 (.92) .03 (.03)
I was consistent in the amount of effort and energy I put into my tasks at work .00 (.01) .04 (.03) .63 (.64) .20 (.15)
Inished whatever I began .14 (.11) .09 (.04) .09 (.04) .67 (.64)
Inished tasks that took a long time to complete .00 (.02) .19 (.05) .11 (.00) .68 (.78)
I persevered in doing my work tasks
b
.02 () .02 () .11 ().65 ()
Note. Numbers in parenthesis are from Study 1.
Bold-faced values indicate primary loadings.
a
Item added from Study 2.
b
Item added to Study 3.
136 P.H. Bayl-Smith, B. Grifn / Journal of Vocational Behavior 90 (2015) 132144
the meaning of the underlying constructs changed across time and therefore whether the measures for work stylesare suitable for
longitudinal research (Little, Preacher, Selig, & Card, 2007).
5.1. Participants
Participants for the second study were recruited as part of a larger study examining mid- to late-career workers aged 45 years and
over. Respondents were sourced from theOnline Research Unit(ORU), an Australianresearch panel company. The ORU has beenrated
with Gold Standardaccreditation for the Quality Standard for Online Access Panel (QSOAP)and has ISO certication for market so-
cial and option research (ISO 20252 and ISO 26362). Respondents are Australian citizens recruited to the ORU primarily through
ofine sources including telephone, print and post. A wide range of demographic factors are used to enable a representative sample
prole for the purposes of research. From their existing panel database, the ORU invited participants byemail to participate in a series
of online questionnaires. Participation was completely voluntary and participants could withdraw at any time without cost or penalty.
A mix of incentives including vouchers and charitable donations of small value (no more than $A 5.00) was provided to participants
via the ORU. For this study, three waves of data were collected at three to four week intervals. In total, there were 665 participants in
the rst wave of data collection, 408 at Time 2 (61.4% response rate) and 244 at Time 3 (36.7% of Time 1 participants). At Time 1, 57.9%
were male, with a mean age of 56.92 years (SD = 6.81 years). Following the Australian Bureau of Statistics (ABS) (2011)
categorisation of workers, 75.5% were employed as white collar workers(managers, professionals, community and service workers,
administrative workers and sales workers), whilst 16.1% indicated that they were blue collar workers(technicians and trade
workers, machinery operators and labourers). The remaining 8.4% did not provide sufcient information to determine job type. The
mean work hours per week was 34.41 h (SD = 14.16 h).
In comparison to available nationwide data(Australian Bureau of Statistics (ABS), 2010, 2011, 2015), this sample is representative
of the Australian population in terms of gender (54.4% males) and working hours (average of 34.1 h work per week). However, given
that the focus of this study was initially upon mid- to late-career workers, this sample was much older than the average Australian
worker (39.5 years). Furthermore, this sample has a slightly higher number of white collar workers than the national average (68.7%).
A one-way ANOVA was conducted to determine whether there were any signicant differences between those who responded
only at Time 1, at Time 1 and Time 2, and those who responded at all three times. There was no signicant difference between the
means for gender and working hours, however those who completed all three surveys were signicantly older by 1.82 years on av-
erage than those who completed Time 1 only (p= .01). A Chi square difference test alsoindicated nosignicant differences between
completion pattern and type of occupation (χ
2
(4) = 8.75, p=.068).
5.2. Measures
The measures utilised for evaluating work styles were derived from the EFA in the rst study. One celerity item from the rst study
was removed due to possible confounding with items measuring pace. This item was replaced with When given a task or project I
began working on it immediately.Therefore at each wave of measurement there was a total of three celerity items, three pace
items, three rhythm items, and two endurance items. All means, standard deviations and reliability coefcients across the three
waves are displayed in Table 3. In the rst wave, respondents were asked how often they did each listed behaviour at work over
the last month; however each succeeding wave specied three to four weeksin line with the time between waves. All items
were measured using a 5-point Likert-type scale (1 = Never to 5 = Always).
5.3. Results
5.3.1. Conrmatory factor analysis
To examine the factor structure of the work style measures, the t indices of the hypothesised four factor model was compared
with a one factor model where all work style items load onto a single work style factor. Goodness of t was assessed using compar-
ative t index (CFI N.95), TuckerLewis index (TLI N.95), root-mean-square errorsof approximation (RMSEA b.06) and standardised
root mean square residual (SRMR b.09), utilising the cut-off criteria provided by Hu and Bentler (1999). All analysis was conducted
using M-Plus 6.12. The four factor model demonstrated acceptable levels of t(χ
2
(38) = 83.978, p b.001; CFI = .987, TLI = .982,
RMSEA = .043, SRMR = 0.023) and provided a signicantly better t than the one factor model (χ
2
(44) = 550.330, p b.001;
CFI = .861, TLI = .827, RMSEA = .132, SRMR = 0.058; Δχ
2
(6) = 466.352, p b.001). These ndings suggest that four factor
model as specied in Study 1 is empirically supported in Study 2.
Table 3
Study 2: Means, standard deviations and reliability coefcient alphas for work style factors.
Factor Time 1 Time 2 Time 3
MSDαMSDαMSDα
Celerity 4.06 .68 .84 4.06 .69 .89 3.96 .69 .89
Pace 4.03 .68 .84 4.04 .71 .86 3.91 .80 .91
Rhythm 4.09 .62 .79 4.11 .66 .87 4.02 .64 .87
Endurance 4.34 .62 .63 4.37 .64 .77 4.26 .69 .84
137P.H. Bayl-Smith, B. Grifn / Journal of Vocational Behavior 90 (2015) 132144
Even though not originally hypothesised by the original TWA model, we have argued above that the work style variables may re-
late to each other through a secondorder factor describing the generalised level of effort and activity at work across time. Empirically,
Study 1 supports this contention giventhe size of the correlations betweenthe work style facets and the broad similarities in how they
relate to other constructs. Therefore, a model containing a second-order latent factor was also examined. The benets of including a
second-order factor include appropriately accounting for the relationship between variables in the rst-order, which will fashion a
more parsimonious model than one that is delineated only by lower order factors. Furthermore, the use of a higher order factor
may eliminate possible issues related to collinearity if the substantially correlated work style variables are used together as predictors
in a regression model (Dormann et al., 2013).
Labelled here as an active work style (AWS), AWS is comprised of the four work style facets and is conjectured to measure one's
generalised level of activity at work. This model was compared to the four factor model using Akaike information criterion (AIC),
where differences less than two suggest little difference between the models (Burnham & Anderson, 2002). The specied second-
order factor model demonstrated good t(χ
2
(40) = 89.49; CFI = .99; TLI = .98; RMSEA = .04; SRMR = .02) and the difference
in AIC was less than two (ΔAIC = 1.52). These results indicate that a second-order latent factor best describes a person's generalised
level of activity in their working environment and explains the relationship between the work style facets.
5.3.2. Longitudinal measurement invariance
To establish measurement invariance across time, we followed the steps recommended by Little et al. (2007). First, an unconstrained
or form invariant model is tested where the relationship between the items and their corresponding work style factor are expected to be
the same at each time of measurement. If this cannot be demonstrated, it signies that the observed items appraise different constructs
at different times. By adding constraints, weak factorial invariance and strong factorial invariance can be tested. Weak factorial invari-
ance constrains the factor loadings across time, indicating that across time the factors are measured in the same way or on the same
scale. Strong factorial invariance constrains both the factor loadings across time as well as the item intercepts. When demonstrated,
strong factorial invariance indicates that factors are not only measured in the same way across time, but that they also do not change
systematically higher or lower (Wang & Wang, 2012). This allows for factor means to be sensibly compared across time and thus is
an indicator of a suitable longitudinal instrument (Little et al., 2007). As the increasingly constrained models are nested, measurement
invariance is typically assessed using the change in χ
2
test, comparing t with the previous less constrained model.
The unconstrained model had an acceptable level of t across the three waves (χ
2
(429) = 783.68; CFI = .94; TLI = .92; RMSEA =
.05; SRMR = .04). The weak factorial invariance model was supported (Δχ
2
(14) = 16.34, pN.05) indicating that the items are mea-
sured similarly across time. The strong factorial invariance model was also supported (Δχ
2
(13) = 14.26, pN.05) suggesting that this
measure can sensibly compare means across time, and therefore is suitable for longitudinal research.
6. Study 3: construct validity and predictive capacity
To further test the validity of the AWS scale and the work style facets, several analyses were carried out. First, we conducted another
CFA to conrm that the four factor and single second-order factor model as identied in the two previous studies accounted for the ob-
served data appropriately. This was deemed to be suitable given the addition of an extra endurance item. This analysis was conducted in
M-Plus 6.12. Convergent validity was tested by examining the correlations of AWS and its four facets with conscientiousness and work
engagement. As noted above, conscientiousness is often depicted as a person's basic tendency to be hardworking, persevering and de-
pendable (Barrick & Mount, 1991), whilst work engagement is characterised as an employee's willingness to invest effort, feel involved
and enthused at work (Schaufeli & Bakker, 2006)features of an individual that are likely to be positively related to an active work style.
Discriminant validity was tested by examining the correlations of AWS and its facets with workplace stress. Stress has been com-
monly understood to result from an appraisal of a situation that threatens wellbeing, either through the taxing or exceeding of one's
personal resources (Lazarus & Folkman, 1984). If people believe they have available options or resources available to cope with the
situation, then the effect of the stressor is mitigated (Hobfoll, 1989; Lazarus & Folkman, 1984). However resources, whether dened
as things of value to theindividual (Hobfoll, 1989) or features in the work environment (Bakker & Demerouti, 2007), are conceptually
distinct from work styles which describe characteristic ways an individualinteracts with their environment. Therefore we would ex-
pect there to be little to no correlation between these factors.
To test the predictive capacity ofthe AWS scale, we examined how each work style andthe overall AWS was linked to measures of
perceived PEt. As suggested above and in line with TWA, those who exhibit an active work style, that is those who actively and
consistently engage their skills and abilities in workplace tasks, are more likely to t their environment than those who are
behaviourally disengaged. If the AWS scale is to be benecial to future research, it should be able to explain unique PEtvariance
above and beyond other related factors. This part of the analysis was conducted using SPSS 21.
6.1. Participants
Respondents for this study were sourced from the ORU, were employed for atleast 8 h of work,and had not taken part in the sec-
ond study. In total, 465 respondents participated in this study, 61.0% of whom were male. Their average age was 42.30 years (SD =
13.03), and they worked on average 37.21 h (SD = 14.96 h) per week. The majority of participants (77.2%) worked in traditional
white collar jobs, with 13.8% working in blue collar jobs and 9.0% not providing sufcient information to determine job type. There-
fore, this sample on average exhibited slightly more males and working hours, as well as a higher age and proportion of white collar
workers when compared to the national average.
138 P.H. Bayl-Smith, B. Grifn / Journal of Vocational Behavior 90 (2015) 132144
6.2. Measures
The means, standard deviations and correlations for this study are reported in Table 3.
6.2.1. Active work style (AWS)
Active work style was measured using the items developed from the previous two studies. Given that the endurance facet of work
styles only contained two items and demonstrated marginal reliability in the previous studies, the item I persevered in doing my
work taskswas added to increase the factor's robustness. Each item was measured using a 7-point Likert type scale (1 = Never to
7=Always). Overall AWS was calculated using themean of the 12 work style items. The individual work style factors were alsocom-
puted by calculating the mean of the three items that make up each factor. The wording of the items and factor weightings are
displayed in Table 1.
6.2.2. Conscientiousness
Conscientiousness was measured as per Study 1B using Saucier's (1994) 8-item scale.
6.2.3. Work engagement
To measure work engagement, the shortened 9-item Utrecht Work Engagement scale (UWES-9; Schaufeli & Bakker, 2006)was
used with a 7-point Likert type scale (1 = Never to 7 = Always). An example item includes, At my work, I feel bursting with energy.
6.2.4. General job stress
Stress was measured using the revised 8-item stress in general(SIG) scale (Yankelevich, Broadfoot, Gillespie, Gillespie, & Guidroz,
2012) where participants were asked to what extent each statement described their current job situation. Example items included
Demandingand Pressured. All items were measured using a 4-point Likert type scale (1 = Notatallto 4 = ALot).
6.2.5. Demandsabilities/Needssupplies t
Perceived t was measured using the items from Cable and DeRue (2002).Bothdemandsabilities t and needssupplies twere
measured with three items using a 7-point Likert-type scale (1 = Strongly disagree to 7 = Strongly agree). An example item includes
The match is very good between the demands of my job and my personal skills.
6.3. Results
6.3.1. Conrmatory factor analysis
Examination of the AWS scale revealed that the four factor model demonstrated good levels of t with the observed data
(χ
2
(48) = 103.34; CFI = .99; TLI = .98; RMSEA = .05; SRMR = .02). In this model, factor loadings ranged from .86 to .88 (celerity),
.79 to .90 (effort), .81 to .84 (rhythm) and .71 to .79 (endurance). The second-order latent factor model, where each work style
facet loaded onto an active work style factor, also demonstrated good t(χ
2
(50) = 109.84; CFI = .99; TLI = .98; RMSEA = .05;
SRMR = .02), and was not demonstrably inferior to the four factor model (ΔAIC = 2.50). Given these ndings, the four factor
work style model was demonstrated to be empirically sound. However, the more parsimonious model includes a higher-order factor,
an overall active work style (AWS) that explains the relationship between the lower order facets.
6.3.2. Convergent and discriminant validity
As hypothesised, the results (see Table 4) demonstrate positive signicant relationships between overall AWS and the four work
style factors with conscientiousness and work engagement. Nevertheless, the correlations were only of a moderate strength, suggest-
ing that they are separate constructs. Furthermore, there was no statistically signicant relationship between AWS and stress, though
there was a small signicant relationship between stress and the work style facet, pace.
6.3.3. Predictive capacity
The predictive capacity of the AWS scale was tested by examiningthe relationship between each work style factor andoverall AWS
with demandsabilities t and needssupplies t, controlling for age, gender, work hours, conscientiousness and work engagement.
Due to issues with collinearity (Condition Index (CI)
2
N30; Belsley, Kuh, & Welsch, 2004) several multiple-regression analyses were
carried out using two steps. In the rst step, the control variables were regressed on the t variable. In the second step, an individual
work style facet or overall AWS was added to the regression model.
A summary of the results is presented in Table 5.Therst set of regression analyses with demandsabilities t specied as the in-
dependent variable, indicated that the control variables (Step 1) explained a signicant amount of demandsabilities t variability.
Both conscientiousness and work engagement were signicantly related to demandsabilities t (and remained so after the inclusion
of the work style factors). The explained variance of the regression model was increased by a small but signicant amount when
adding an individual work style factor or the overall AWS. Therefore, controlling for all variables in Step 1, work style factors were sig-
nicantly related to demandsabilities t such that on average, an increase in a work style factor or the overall AWS was associated
with a corresponding increase in demandsabilities t. These effects imply that the AWS scale is capturing variancedistinct from con-
sciousness and work engagement in the predicted direction.
139P.H. Bayl-Smith, B. Grifn / Journal of Vocational Behavior 90 (2015) 132144
Results for the second regression analysis, with needssupplies tspecied as the independent variable, revealed that the control
variables (Step 1) explained 39.8% of the variance. Work engagement was signicantly related to needssupplies t, though conscious-
ness was not. When the individual work style factors and overall AWS were added to the regression model (Step 2), no additional var-
iance was accounted for. Overall, work styles did not signicantly relate to needssupplies t when controlling for all variables in Step 1.
Note however, that the zero order correlation between needssupplies t and the work style factors were signicant.
7. Discussion
The present set of studies were designed to empirically validate a self-report measure of work styles, a dynamic component of the
theory of work adjustment (TWA) that has been largely overlooked yet is conceived as an important component in maintaining and
adjusting personenvironment t. Across three studies, the results demonstrate that four factors, labelled as celerity, pace, rhythm
and endurance, were consistently differentiated by the active work style (AWS) scale. Furthermore, given the acknowledged
Table 5
Study 3: Regression analyses of the relationships between work styles with DAtandNSt.
R
2
FΔR
2
F
inc
dfs
inc
sr βB95% CI
SE Lower Upper
Variable DAt
Step 1 .34 45.69 .34 45.69⁎⁎ 5446
Gender .08 .08 .19.09 .01 .38
Age .14 .15 .01⁎⁎ .00 .01 .02
Work hours/week .10 .11 .01⁎⁎ .00 .00 .01
Conscientiousness .15 .16 .15⁎⁎ .04 .07 .22
Work Engagement .41 .43 .48⁎⁎ .04 .39 .57
Regression models
1. Step 2 celerity .35 32.72 .01 6.131445 .09 .11 .12.05 .03 .22
2. Step 2 pace .36 40.66 .02 10.59⁎⁎ 1445 .12 .14 .17⁎⁎ .05 .07 .27
3. Step 2 rhythm .36 41.93 .02 15.62⁎⁎ 1445 .15 .18 .22⁎⁎ .06 .11 .33
4. Step 2 endurance .36 41.84 .02 15.29⁎⁎ 1445 .15 .05 .21⁎⁎ .05 .10 .31
5. Step 2 AWS .36 42.16 .02 16.56⁎⁎ 1445 .15 .19 .25⁎⁎ .06 .13 .38
NSt
Step 1 .40 58.94 .39 58.94⁎⁎ 5446
Gender .03 .03 .09 .11 .12 .30
Age .12 .13 .01⁎⁎ .00 .01 .21
Work hours/week .10 .11 .01⁎⁎ .00 .00 .02
Conscientiousness .01 .01 .01 .04 .07 .10
Work engagement .54 .57 .77⁎⁎ .05 .67 .87
Regression models
6. Step 2 celerity .40 49.16 .00 .57 1445 .03 .03 .04 .06 .16 .07
7. Step 2 pace .40 49.21 .00 .74 1445 .03 .04 .05 .06 .07 .17
8. Step 2 rhythm .40 49.47 .00 1.69 1445 .05 .06 .09 .07 .04 .22
9. Step 2 endurance .40 49.36 .00 1.29 1445 .04 .05 .07 .06 .19 .05
10. Step 2 AWS .40 49.00 .00 .00 1445 .00 .00 .00 .07 .14 .15
Note. CI = condence interval. AWS = overall active work style.
pb.05.
⁎⁎ pb.01.
Table 4
Study 3: Summary of intercorrelations, means, standard deviations and reliability coefcient alphas.
MSD12345678910111213
1. Gender .61
2. Age 42.30 13.03 .01
3. Work hours/week 37.21 14.96 .27⁎⁎
.03
4. AWS 5.43 .36 .17⁎⁎ .23⁎⁎
.01 (.94)
5. Celerity 5.42 .97 .15⁎⁎ .18⁎⁎
.10.86⁎⁎ (.90)
6. Pace 5.36 .98 .17⁎⁎ .15⁎⁎ .04 .88⁎⁎ .65⁎⁎ (.87)
7. Rhythm 5.40 .92 .13⁎⁎ .24⁎⁎ .02 .90⁎⁎ .69⁎⁎ .75⁎⁎ (.87)
8. Endurance 5.57 .93 .15⁎⁎ .25⁎⁎
.00 .87⁎⁎ .68⁎⁎ .68⁎⁎ .71⁎⁎ (.80)
9. Conscientiousness 6.87 1.25 .11.30⁎⁎
.03 .44⁎⁎ .38⁎⁎ .37⁎⁎ .39⁎⁎ .40⁎⁎ (.86)
10. Work engagement 4.66 1.01 .09.14⁎⁎ .11.45⁎⁎ .34⁎⁎ .42⁎⁎ .48⁎⁎ .35⁎⁎ .26⁎⁎ (.93)
11. Stress 2.40 .70 .01 .19⁎⁎ .25⁎⁎ .03 .03 .14⁎⁎
.00 .00 .19⁎⁎
.03 (.90)
12. Demandsabilities t 5.39 1.11 .11.25⁎⁎ .12.45⁎⁎ .33.40⁎⁎ .45⁎⁎ .40⁎⁎ .33⁎⁎ .52⁎⁎ .01 (.90)
13. Needssupplies t 5.02 1.36 .06 .21⁎⁎ .15.29⁎⁎ .19⁎⁎ .30⁎⁎ .35⁎⁎ .20⁎⁎ .20⁎⁎ .61⁎⁎
.02 .66⁎⁎ (.93)
Note. reliability c oefcients (Cronbach's alpha) are in parentheses on the diagonal. Gender: 0 = female, 1 = male. Occupation: 0 = white collar, 1 = blue collar.
pb.05.
⁎⁎ pb.01.
140 P.H. Bayl-Smith, B. Grifn / Journal of Vocational Behavior 90 (2015) 132144
limitations inherent in past PEt research regarding snapshotmeasurement (Kristof-Brown & Jansen, 2007), it was important to
generate an instrument suitable for longitudinal research. The results from Study 2 suggest that the items demonstrated strong mea-
surement invariance across time, indicating that the AWS scale is suitable for future longitudinal research. Together, these ndings
provide credible evidence that the factors designating work styles are sensibly related and distinct constructs.
However, the second and third studies demonstrate that the relationship between these factors are best understood as being con-
nected through a second-order factor, an active work style that describes a person's generalised level of work activity andeffort across
time. This has not been previously conjectured in the TWA literature, but as argued is perhaps unsurprising given that work stylesare
understood to be inuenced in similar respects by a wide range of variables including personality, self-efcacy, identity and
stereotyping (Hesketh et al., 2015). For example, as demonstrated in Studies 1B and 3, higher levels of conscientiousness are related
to higher levels of celerity, pace, rhythm and endurance. However, despite their interconnectedness, the AWS scale has the advantage
of being able to differentiate the work style facets, which may be of interest in specic contexts; for example, work environments
where highly celeritous individuals are more likely to be successful or necessary (e.g., air trafc controller or emergency nurse).
In determining the convergent and discriminant validity of the AWS scale, our results demonstrate that a person's overall work
style is positively related to conscientiousness and work engagement yet unrelated to stress. Conscientiousness is characterised as
encompassing a basic disposition towards working hard, persevering, and being dependable (Barrick & Mount, 1991), which is likely
to inuence the levels of celerity, pace, rhythmand endurance of a person.The correlations derived from Study1B and Study 3 support
this contention, indicating that increased levels of conscientiousness are associated with a moreactive work style overall, and within
each facet. Work engagement, a work-related state of mind that is exemplied by a willingness to invest effort, feeling involved and
being engrossed in one's work (Schaufeli et al., 2002), also was expected to be related with work styles. The results of Study 3 support
this proposition indicating that those who have higher levels of work engagement on average have a higher overall active work
style a result that is repeated for each individual work style facet. Regarding conscientiousness and work engagement, it is impor-
tant to note that the positive relationships found were only of moderate strength; evidence that these constructs are empirically dis-
tinct. In regard to determining discriminant validity, overall AWS did not demonstrate any signicant relationship with stress,
however there was a positive association with the facet pace. As employees reported engaging in increased levels of work effort
and activity, perceptions of work place stress increased. This suggests that pace might be related to the consumption of personal re-
sources which are either unable to be recouped causing stress (Bakker & Demerouti, 2007), or that such effort may be stressful in itself
(Meurs & Perrewe, 2011). These ndings indicate thepossible value of bearing in mind the distinctions between the facets in the AWS
scale and how they might uniquely relate to particular variables and situations. Overall though, the AWS scale demonstrated conver-
gent and discriminant relationships with other measured constructs as expected.
When controlling for conscientiousness, work engagement, and several demographic variables, individual work style facets and
overall AWS is positively related to demandsabilities t. Those who report that they are more actively engaged and endure in
work tasks perceive an increased ability to meet the demands of their job. Broadly, this lends initial support to the importance of un-
derstanding and measuring the dynamic components of personenvironment t. More specically, work styles have been shown to
be a signicant component of demandsabilities t, explaining a signicant amount of observed variance. In line with TWA, this may
suggest that those who have a more active work style feel more able to meet the requirements of their job.
Interestingly, an unambiguous relationship between work styles and needssupplies t was not found. Even though there was a
moderate correlation between work style factors and needssupplies t, this relationship disappeared when controllingfor conscien-
tiousness and work engagement. One possible explanation is that work styles maytarget the fullment of work demands rather than
target the meeting of needs and values from one's work place. Another possible consideration is that work engagement and needs
supplies t are concepts overly intertwined such that when included in a regression model, other included variables such as work
styles become non-signicant.
These ndings suggest that measuring work styles may be of practical use to human resources professionals. Employees are ulti-
mately in control of howmuch of their time andenergy they will expend in conducting their work tasks(Brown & Leigh, 1996). Whilst
an employee may have all th e skills and abilities required to meet the demands of th eir work role, if they a re not investing effort or are
doing so inappropriately they will not likely meet the requirements of their job. Measuring work styles will allow an organisation to
track how effort is beingenacted over time and compare this to what is required. Furthermore, as work styles are not static but inu-
enced by a wide range of variables; through policy, structural change and environmental transformation, employee work styles may
be positively altered. The present measures may assist in the tracking of these changes over time as a result of organisational change.
Finally, work styles have been demonstrated to be positively related to PEt. If work styles prove to be an important component in
the maintenance and adjustment of PEt, then tracking how employees express their engagement of effort over time will be anim-
portant consideration for all organisations.
7.1. Limitations and future research
One particular limitation of this study is that all results were obtained by the use of self-report measures. However, the problems
associated with common method bias are to some extent alleviated by the use of three different samples in three different studies,
including one three-wave longitudinal study, which consistently demonstrated a coherent factor structure across the AWS facets
(Podsakoff, MacKenzie, & Podsakoff, 2012). Furthermore, the question order in all three studies were randomised and placed in a dif-
ferent item-context, reducingthe primingeffects or effects related to mood states induced by previous items, which may offset some
impact of common method bias (Podsakoff, MacKenzie, Lee, & Podsakoff, 2003). However, future studies could further validate the
141P.H. Bayl-Smith, B. Grifn / Journal of Vocational Behavior 90 (2015) 132144
AWS scale by examining the scales relation to other criterion such as supervisor or peer ratings and tracking project contributions and
completions.
A second limitation relates to the cross-sectional nature of Study 3 which demonstrated that the AWS scale was signicantly re-
lated to personenvironment t. However, the direction of causation in this study cannot be determined. Deriving theoretically
from TWA, increasing the utilisation of one's skills and abilities at work consistently over time will allow for an employee to maintain
or adjust their levels of personenvironment t(Dawis & Lofquist, 1984). However, it may also be possible that by tting with one's
environment, the employee is then enabled to activate their work style without physical or psychological hindrance. Therefore, we
would recommend future longitudinal studies to ascertain the causal relationship between work styles and personenvironment t.
Future longitudinal research would also benet by exploring different time frames between data collection waves to determine
how active work style inuences PEt across time. The present paper demonstrates that the AWS scale was suitable for a longitu-
dinal study, however this was examined only over a relatively short time period (three to four week intervals). Where both person
and environment are relatively constant, anemployee's work style is likely to be relatively stable due to there being little need for ad-
ditionalmaintenance and adjustment behaviours (Dawis & Lofquist,1984). Thereforewe would expect over shorter time frames,with
less chance of signicant workplace change, that work styles would be relatively stable. However, given that work environments do
transform over time, including their interactions with the personal characteristics of the employee (Pulakos et al., 2000), work styles
may alter markedly over the longer term as an employee attempts to increase or maintain their t by adapting their behaviours to
changing circumstances.
The AWS scale would also benet from testing several formal TWA propositions as proposed by Dawis (2005, pp. 2021) that di-
rectly relate to work styles and generally to work adjustment. Proposition X for example, suggests that work styles may moderate the
relationship between PEt and employer/employee satisfaction. By engaging an appropriate work style an individual may be more
able to meet the demands of the organisation aswell as have their needs met. Propositions XIII and XIV suggest that once satisfaction
has been achieved, work styles will be maintained. However, as a result of dissatisfaction, employees may attempt to vary their work
styles in order to facilitate increased levels of PEt. These propositions have not been empirically tested and therefore present ex-
cellent opportunities to not only understand the role of work styles in organisations, but also to meaningfully contribute to TWA.
Such an endeavour would require a longitudinal design.
Another possible limitation of this study and opportunity of future research relates to themeasurement of PEt itself. There are a
variety of methods in measuring PEt including atomistic, molecular and molar approaches (Edwards, Cable, Williamson, Lambert,
& Shipp, 2006). Edwards et al. (2006) demonstrate that these different approaches to understanding PEt are not interchangeable
which raises an interesting question regarding the nature of t. Hesketh et al. (2015) also note that molar approaches (such as those
used in this paper) may not provide useful details regarding how the person and environment interact. Regarding understanding the
role of work styles in determining PEt, an atomistic approach that assesses the person and environment independently may pro-
vide useful insight into how a person attempts to maintain and adjust their behaviours in order to achieve t.
In summary, the key contribution of this paper was to develop a measure of work styles, a neglected but important component of
TWA describing an individual's characteristic wayof interacting with their work environment. Both person and environment are un-
derstood to be constantly experiencing change, requiring the enactment of maintenance and adjustment behaviours in order to
achieve or preserve correspondence. According to Dawis and Lofquist (1984), work styles are a dynamic component of t describing
the way in which a person activates or engages their skills and abilities across time. Three studies were used to develop and validate a
suitable self-report measurement of work styles. The results derived from these studies support the conception of four separate work
style facets; celerity, pace, rhythm and endurance. However, these facets are related through a second-order factor describing a
person's generalised level of work activity and effortacross time. Results also demonstrated that the AWS scale was positively related
to measures of perceived PEt. Together, these ndings suggest that work styles, as measured by the AWS scale, likely play an im-
portant role in understanding how people achieve correspondence with their working environment.
References
Australian Bureau of Statistics (ABS) (2010). 6105.0 Australian labour market statistics, Oct 2010. http://www.abs.gov.au/ausstats/abs@.nsf/featurearticlesbytitle/
67AB5016DD143FA6CA2578680014A9D9?OpenDocument (Retrieved August 27, 2015, from).
Australian Bureau of Statistics (ABS) (2011). 6105.0 Australia n labour market statistics, Oct 2011. http://www.a bs.gov.au/ausstats/abs@.nsf/Lookup/6105.
0Feature+Article1Oct 2011 (Retrieved July 28, 2015, from).
Australian Bureau of Statistics (ABS) (2015). 6291.0.55.001 Labourforce, Australia, detailed Electronic delivery, Jun 2015. http://www.abs.gov.au/AUSSTATS/ABS@
Archive.nsf/log?openagent&6291009.xls&6291.0.55.001&Time Series Spreadsheet&9E5BA281B9A84351CA257E83001B2A89&0&Jun 2015&16.07.2015&Latest
(Retrieved July 27, 2015, from).
Bakker, A. B., & Demerouti, E. (2007). The job demandsresources model: State of the art. Journal of Managerial Psychology,22,309328. http://dx.doi.org/10.1108/
02683940710733115.
Bandura, A. (1999). Social cognitive theory of personality. In L. Previn, & O. John (Eds.), Handbook of personality (pp. 154196) (2nd ed.). New York : Guilford
Publications.
Barrick, M. R., & Mount, M. K. (1991). The big five personality dimensions and job performance: A meta-analysis. Personnel Psychology,44,126. http://dx.doi.org/10.
1111/j.1744-6570.1991.tb00688.x.
Belsley, D. A., Kuh, E., & Welsch, R. E. (2004). Regression diagnostics: Indentifying influential data sources of collinearity. Hoboken: John Wiley & Sons, Inc.
Brown, S. D. (1993). Contemporary psychological science and the theory of work adjustment: A proposal for integration and a favor returned. Journal of Vocational
Behavior,43,5866. http://dx.doi.org/10.1006/jvbe.1993.1030.
Brown, S. P., & Leigh, T. W. (1996). A new look at psychological climate and its relationship to job involveme nt, effort, and performance. The Journal of Applied
Psychology,81,358368. http://dx.doi.org/10.1037/0021-9010.81.4.358.
Burnham, K. P., & Anderson, D. R. (2002). Model selection and multimodel inference: A practical informationtheoretic approach (2nd ed.). New York: Springer.
Cable, D. M.,& DeRue, D. S. (2002). The convergent and discriminant validity of subjective fit perceptions. Journal of Applied Psychology,87,875884. http://dx.doi.org/
10.1037//0021-9010.87.5.875.
142 P.H. Bayl-Smith, B. Grifn / Journal of Vocational Behavior 90 (2015) 132144
Caldwell, S. D., Herold, D. M., & Fedor, D. B. (2004). Towardan understanding of therelationships among organizational change,individual differences, and changes in
personenvironment fit: A cross-level study. The Journal of Applied Psychology,89,868882. http://dx.doi.org/10.1037/0021-9010.89.5.868.
Carless,S. A. (2005). Personjob fit versus personorganization fit aspredictors of organizational attractionand job acceptance intentions:A longitudinal study. Journal
of Occupational and Organizational Psychology,78,411429. http://dx.doi.org/10.1348/096317905X25995.
Dawis, R. V. (1996). The theory of work adjustment and personenvironment-correspondence counseling. In D. Brown, & L. Brooks (Eds.), Career choice and develop-
ment (pp. 75120) (3rd ed.). San Francisco: Jossey-Bass Inc.
Dawis, R. V. (2005). The Minnesota theory of work adjustment. In S. D. Brown, & R. W. Lent (Eds.), Career development and counselling: Putting theory and research to
work (pp. 323). Hoboken: John Wiley & Sons, Inc.
Dawis, R. V., & Lofquist, L. H. (1984). A psychological theory of work adjustment. Minneapolis: University of Minnesota Press.
Dawis, R. V., & Lofquist, L. H. (1993). From TWA to PEC. Journal of Vocational Behavior,43,113121. http://dx.doi.org/10.1006/jvbe.1993.1037.
De Cooman, R., De Gieter, S., Pepermans, R., Jegers, M., & Van Acker, F. (2009). Development and validation of the work effort scale. European Journal of Psychological
Assessment,25,266273. http://dx.doi.org/10.1027/1015-5759.25.4.266.
De Vaus, D. A. (2002). Surveys in social research (5th ed.). Crows Nest: Allen & Unwin.
DeVellis, R. F. (1991). Scale development: Theory and applications. Newbury Park: SAGE Publications, Inc.
Donohue,R. (2006). Personenvironmentcongruence in relation to careerchange and career persistence. Journal of Vocational Behavior,68,504515. http://dx.doi.org/
10.1016/j.jvb.2005.11.002.
Dormann,C. F., Elith, J., Bacher, S., Buchmann, C., Carl,G., Carré, G., et al. (2013). Collinearity: A review of methodsto deal with it and a simulation studyevaluating their
performance. Ecography,36,2746. http://dx.doi.org/10.1111/j.1600-0587.2012.07348.x.
Duckworth,A. L., Peterson, C.,Matthews, M. D., & Kelly,D. R. (2007). Grit: Perseveranceand passion for long-term goals. Journal of Personality and Social Psychology,92,
10871101. http://dx.doi.org/10.1037/0022-3514.92.6.1087.
Edwards, J. R., Cable, D. M., Williamson, I. O., Lambert, L. S., & Shipp,A. J. (2006). The phenomenology of fit: Linking the person and environment to the subjective ex-
perience of personenvironment fit. The Journal of Applied Psychology,91,802827. http://dx.doi.org/10.1037/0021-9010.91.4.802.
Fabrigar,L. R., Wegener, D. T.,MacCallum, R. C., & Strahan, E. J. (1999). Evaluating the use of exploratory factor analysisin psychological research. Psychological Methods,
4(3), 272299. http://dx.doi.org/10.1037/1082-989X.4.3.272.
Gold, J. E., Park, J. -S., & Punnett, L. (2006). Work routinization and implications for ergonomic exposure assessment. Ergonomics,49(1), 1227. http://dx.doi.org/10.
1080/00140130500356643.
Griffin,B., & Hesketh, B. (2003). Adaptable behaviours for successful work andcareer adjustment.Australian Journal of Psychology,55,6573. http://dx.doi.org/10.1080/
00049530412331312914.
Griffin, M. A., Neal, A., & Parker, S. K. (2007). A new model of work role performance: Positive behaviour in uncertain and interdependent contexts. Academy of
Management Journal,50,327347. http://dx.doi.org/10.5465/AMJ.2007.24634438.
Hakanen, J. J., Bakker, A. B., & Schaufeli, W. B. (2006). Burnout and work engagement among teachers. Journal of School Psychology,43,495513. http://dx.doi.org/10.
1016/j.jsp.2005.11.001.
Hakanen, J. J., Perhoniemi, R., & Toppinen-Tanner, S. (2008). Positive gain spirals at work: From job resources to work engagement, personal initiative and work-unit
innovativeness. Journal of Vocational Behavior,73,7891. http://dx.doi.org/10.1016/j.jvb.2008.01.003.
Henson, R. K. (2006). Use of exploratory factor analysis in published research common errors and some comment on improved practice.Educational and Psychological
Measurement,66,393416. http://dx.doi.org/10.1177/0013164405282485.
Hesketh, B. (1995). Personality and adjustment styles: A theory of work adjustment approach to career enhancing strategies. Journal of Vocational Behavior,46,
274282. http://dx.doi.org/10.1006/jvbe.1995.1020.
Hesketh, B., & Griffin, B. (2005 ). Work Adjustment. In W. B. Walsh, & M. L. Savickas (Eds. ), Handbook of Vo cational Psych ology: Theory, Research and Pra ctice
(pp. 245266) (3rd ). Mahwah: Lawrence Erlbaum Associates, Publishers.
Hesketh, B., Griffin, B., Dawis, R. V., & Bayl-Smith, P. (2015). Extensions to the dynamic aspects of the Retirement Transition and Adjustment Framework (RTAF):
Adjustment behaviors, work styles and identity. Work, Aging & Retirement,1,7991. http://dx.doi.org/10.1093/workar/wau004.
Hobfoll, S. E. (1989). Conservation of resources. A new attempt at conceptualizing stress. The American Psychologist,44, 513524. http://dx.doi.org/10.1037/0003-066X.44.3.
513.
Hoffman,B. J., & Woehr, D. J. (2006). A quantitative review of the relationship between personorganization fit and behavioral outcomes. Journal of Vocational Behavior,
68,389399. http://dx.doi.org/10.1016/j.jvb.2005.08.003.
Hu, L., & Bentler, P. M. (1999). Cutoff criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives.Structural Equation Modeling:
A Multidisciplinary Journal,6,155. http://dx.doi.org/10.1080/10705519909540118.
Jansen, K. J., & Kristof-Brown, A. L. (2005). Marching to the beat of a different drummer: Examining the impact of pacing congruence. Organizational Behavior and
HumanDecisionProcesses,97,93105. http://dx.doi.org/10.1016/j.obhdp.2005.03.005.
Jansen, K.J., & Shipp, A. J. (2013). A review and agendafor incorporatingtime in fit research. In A. L. Kristof-Brown,& J. Billsberry (Eds.), Organizational fit: Key issues and
new directions (pp. 195221). Chichester: John Wiley & Sons, Ltd.
Kanfer, R., & Ackerman, P. L. (2008). Aging and work motivation. In C. Wankel (Ed.), 21st century management: A reference handbook (pp.160170). Los Angeles (CA):
SAGE Publications, Inc (Vol. 2).
Kooij, D., Lange, A. De, Jansen, P., & Dikkers, J. (2008). Older workers'motivation to continueto work: Five meanings of age: A conceptual review. Journal of Managerial
Psychology,23,364394. http://dx.doi.org/10.1108/02683940810869015.
Kristof-Brown, A. L., & Guay, R. P. (2011). Personenvironment fit. In S. Zedeck (Ed.), APA handbook of industrial and organizational psychology (pp. 350). Washington,
DC: American Psychological Association. http://dx.doi.org/10.1037/1217 1-001 (Vol. 3).
Kristof-Brown, A. L., & Jansen, K. J. (2007). Issues of personorganization fit. In C. Ostroff, & T. A. Judge (Eds.), Perspectives on organizationalfit (pp. 123154). Mahwah:
Taylor & Franicis Group, LLC (Retrieved from http://books.google.com/books?hl=en&lr=&id=9jOynKk2UjUC&pgis=1).
Kristof-Brown, A. L., Zimmerman, R. D., & Johnson, E. C. (2005). Consequences of individuals' fit at work: A meta-analysis of personjob, personorganization, person
group, and personsupervisor fit. Personnel Psychology,58,281342.
Landy, F. J.,Rastegary, H., Thayer, J., & Colvin,C. (1991). Time urgency:The construct and its measurement.Journal of Applied Psychology,76,644657. http://dx.doi.org/
10.1037/0021-9010.76.5.644.
Lawson, L. (1993). Theory of work adjustment personality constructs. Journal of Vocational Behavior,43,4657. http://dx.doi.org/10.1006/jvbe.1993.1029.
Lazarus, R. S., & Folkman, S. (1984). Stress, appraisal, and coping. New York: Springer Publishing Company, Inc.
Little, T. D., Preacher, K. J., Selig, J. P., & Card, N. A. (2007). New developments in latent variable panel analyses of longitudinal data. International Journal of Behavioral
Developmenthttp://dx.doi.org/10.1177/0165025407077757.
Matsunaga, M. (2011). How to factor-analyze your data right: Do's, don'ts, and how-to's. International Journal of Psychological Research,3,97110.
McCrae, R. R., & Costa, P. T. J. (2008). The five-factor theory of personality. In O.P. John, R. W. Robins, & L. A. Pervin (Eds.), Handbook of personality: Theory and research
(pp. 159181) (3rd ed.). New York: The Guilford Press.
Meurs, J. A., & Perrewe, P. L. (2011). Cognitive activation theory of stress: An integrative theoretical approach to work stress. Journal of Managementhttp://dx.doi.org/
10.1177/0149206310387303.
Podsakoff, P. M., MacKenzie, S. B., Lee, J. -Y., & Podsakoff, N. P. (2003). Common method biases in behavioral research: A critical review of the literature and recom-
mended remedies. The Journal of Applied Psychology,88,879903. http://dx.doi.org/10.1037/0021-9010.88.5.879.
Podsakoff, P. M., MacKenzie, S. B., & Podsakoff, N. P.(2012). Sources of method bias in social scienceresearch and recommendationson how to control it. AnnualReview
of Psychologyhttp://dx.doi.org/10.1146/annurev-psych-120710-100452.
Pulakos, E. D., Arad, S., Donovan, M. A., & Plamondon, K. E. (2000). Adaptability in the workplace: Development of a taxonomy of adaptive performance. Journal of
Applied Psychology,85,612624. http://dx.doi.org/10.1037//0021-9010.85.4.612.
143P.H. Bayl-Smith, B. Grifn / Journal of Vocational Behavior 90 (2015) 132144
Saucier, G. (1994). Mini-markers: A brief version of Goldberg's unipolar big-five markers. Journal of Personality Assessment,63,506516. http://dx.doi.org/10.1207/
s15327752jpa6303_8.
Schaufeli, W. B., & Bakker, A. B. (2006). The measurement of work engagement with a short questionnaire: A cross-national study. Educational and Psychological
Measurement,66,701716. http://dx.doi.org/10.1177/0013164405282471.
Schaufeli, W. B., Salanova, M., Bakker, A. B., & Gonzales-Roma, V. (2002). The measurement of engagement and burnout: A two sample confirmatory factoranalytic
approach. Journal of Happiness Studies,3,7192. http://dx.doi.org/10.1023/A:1015630930326.
Tinsley, D. J. (1993). Extensions, elaborations, and construct validation of the Theory of Work Adjustment. Journal of Vocational Behavior,43,6774. http://dx.doi.org/
10.1006/jvbe.1993.1031.
Van Eerde, W. (2003). A meta-analytically derived nomological network of procrastination. Personality and Individual Differences,35,14011418. http://dx.doi.org/10.
1016/S0191-8869(02)00358-6.
Verquer, M. L., Beehr, T. a, & Wagner, S. H. (2003). A meta-analysis of relations between personorganization fit and work attitudes. Journal of Vocational Behavior,63,
473489. http://dx.doi.org/10.1016/S0001-8791(02)00036-2.
Wang, J., & Wang, X. (2012). Structural equation modeling: Applications using Mplus. Chichester: Higher Education Press.
Yankelevich, M., Broadfoot, A., Gillespie, J. Z., Gillespie, M. A., & Guidroz, A. (2012).General job stress: A unidimensional measure and its non-linear relations with out-
come variables. Stress and Health,28,137148. http://dx.doi.org/10.1002/smi.1413.
Yeo, G. B., & Neal, A. (2004). A multilevel analysis of effort, practice, and performance: Effects of ability, conscientiousness, and goal orientation. The Journal of Applied
Psychology,89,231247. http://dx.doi.org/10.1037/0021-9010.89.2.231.
144 P.H. Bayl-Smith, B. Grifn / Journal of Vocational Behavior 90 (2015) 132144
... To fill this gap, this study aims to investigate the major causes of Chinese employees' complaints and develop a scale to measure them. The theory of work adjustment (Dawis and Lofquist, 1984)-a theory concerning a person (P) in a work environment (E) and the fit and interactions between the P and the E-was widely used in organizational psychology to explain employees' job-related behaviors (Bayl-Smith and Griffin, 2015;Guan et al., 2021), this study follows this theory to explore the causes of employees' complaints. Through two survey-based studies, this research identifies six crucial causes of Chinese employees' complaints, four of which are P-E interactional factors: dissatisfaction with (a) interpersonal relationships; (b) management systems; (c) work conditions; and (d) authoritarian leadership; the remaining two are P-E misfit factors: perceived misfit regarding (e) work content; and (f) job responsibilities. ...
... Extensive prior studies in the field of organizational psychology applied the theory of work adjustment to explain employees' satisfied or dissatisfied behaviors in the workplace (Bayl-Smith and Griffin, 2015;Guan et al., 2021). It can also provide explanations for the possible causes of Chinese employees' complaints in their workplace. ...
Article
Full-text available
This study aims to investigate the causes of workplace complaints among Chinese employees and to develop a scale to measure them, drawing on the theory of work adjustment. We first obtained 49 items regarding employees' complaints following rigorous item generation and refinement procedures. Then, we conducted a survey with convenience sampling and obtained a sample of 268 employees. The exploratory factor analysis based on this sample generated a six-factor solution that explained 65.85% of the variance. The six factors include four person-environment (P-E) interactional factors, namely, dissatisfaction due to (a) interpersonal relationships; (b) management systems; (c) work conditions; and (d) authoritarian leadership; and two P-E misfit factors, namely, perceived misfit regarding (e) work content; and (f) job responsibilities. Furthermore, we obtained another sample of 349 employees through snowball sampling, on which we further validated the six-correlated-factor solution through confirmatory factor analysis. This study contributes to the literature by identifying causes of Chinese employees' complaints different from those attributed to their counterparts in Western cultures. This outcome particularly reveals that “dissatisfaction with interpersonal relationships” with colleagues was the leading cause of complaints among Chinese employees, rather than the “misfit between employees' needs and organizational rewards” revealed by Western culture-based studies. Both our findings and the scale we developed have practical implications for companies that employ Chinese employees.
... According to work adaptation theory, when the external work environment changes, employees' sense of matching with the new environment will be reduced, which will trigger their own adaptive behavioral response mechanism and remold self-directed work to reconstruct the sense of matching (Bayl-Smith & Griffin, 2015). E-HRM implementation attempts to stimulate the individual initiative of employees through network interactive self-organizing management. ...
... Work adaptation theory pays attention to the matching of individual needs and supply and emphasizes the problem of employee adaptation in work (Bayl-Smith & Griffin, 2015). Employees strive to find a match between themselves and new environments. ...
Article
Full-text available
As a new management reform adapting the development of the times, electronic human resource management (E-HRM) covers all possible integration mechanisms and contents between HRM and Information Technologies. E-HRM promotes employees' subject status with the network characteristics of openness and cooperation. Taking the theory of work adjustment as the instruction, this research studies the adaptive process induced by reconstructing the sense of matching when employees experience the reform, along with the influence of E-HRM on employee's initiative behavior from the perspective of job crafting. In total, 706 employees and their supervisors were investigated with matched questionnaire survey. The results show that: (1) E-HRM can stimulate employees' personal initiative behavior; (2) task crating, relational crafting and cognitive crafting as three dimensions of employees' job crafting, mediate the effect of E-HRM on personal initiative behavior and (3) the self-development motivation of employees' internet use plays a positive moderating role, steering self-oriented job crafting in the positive direction which conforms to the organizations' expectation.
... In order to reduce common method variance (Podsakoff et al., 2003;Podsakoff et al., 2012), we invited supervisorsubordinate dyads to participate in the study. Following previous studies that have adopted a similar technique (e.g., Bayl-Smith & Griffin, 2015;Ezeofor & Lent, 2014;Meyer et al., 2013), we first sent the respective online survey links (i.e., supervisor or subordinate survey) to our contacts (i.e., supervisor or subordinate) working in China via an online survey platform (http:// www. wjx. ...
... To eliminate the potential contaminations of our findings, we sought to enhance the data quality by emphasizing the data collection process (e.g., clearly stating the procedures at the beginning of the surveys and used unique identification codes to match the surveys). Despite these shortcomings, the snowball sampling technique is widely used in organizational research (e.g., Bayl-Smith & Griffin, 2015;Ezeofor & Lent, 2014;Haar et al., 2014;Zacher et al., 2015) due to its convenience and ability to obtain diverse samples, which can enhance the generalizability of study results (Kausel et al., 2016). Nevertheless, we encourage future studies to use probability sampling method to collect data and compare findings to those of ours. ...
Article
Full-text available
Drawing upon the citizenship motives framework and voice research, this study theorizes that both organizational concern (OC) and impression management (IM) motives are key predictors of employee promotive and prohibitive voice. This study further explores the moderating effect of perceived voice level in the work context on the relationships between motives and voice. The results of 140 pairings of supervisor-subordinate dyads indicate that both OC and IM motives are determinants of promotive and prohibitive voice. Moreover, perceived voice level in the work context plays distinct roles in moderating the main effects of motives on voice. Specifically, perceived voice level in the work context mitigates the influence of OC motives on promotive and prohibitive voice, whereas it strengthens the impact of IM motives on promotive and prohibitive voice. This study provides implications for both theory and practice. Limitations and future directions are also discussed.
... Furthermore, dynamic patterns can differ. The Minnesota theory of work adjustment indicates that adaptation processes follow celerity, pace, rhythm, and endurance working modes (Bayl-Smith & Griffin, 2015). Changing trajectories are particularly indicated by pace, which marks the level of energy usually devoted to work activities and would indicate initial levels of information-seeking behavior. ...
... The big-five personality characteristics have been shown to impact adaptive work behaviors (Bayl-Smith & Griffin, 2015). Consequently, we believe that personality characteristics will relate to patterns of information-seeking. ...
Article
This article reports results of a study observing how big-five personality traits influence the trajectories of information-seeking adaptive behaviors among university freshmen. Data are collected from 409 freshmen at a Chinese university at 3, 5, 7, and 9 months after university enrollment. A latent growth mixture model is applied to reveal four trajectories of information-seeking behaviors: high or low maintaining, downward or upward. When the information-seeking trajectories are related to personality traits, openness and agreeableness are associated with high maintaining, while agreeableness is associated with downward trajectories. The study provides strong empirical evidence supporting the Minnesota theory of work adjustment and provides important insights to practitioners who want to enhance newcomer adjustment at all organizations.
... The adjustment to work depends on the TMW's psychological acceptance and comfort with the various job aspects that operate at the workplace, such as what should, can, and is expected to be done. Bayl-Smith and Griffin (2015) further suggested that the workplace can adjust to the worker at the same time to enhance the job satisfaction and attachment levels. Thus, the SCA reflects the extent to which the TMWs have learned the local culture and acquired the social skills (Ward & Kennedy, 1999). ...
Article
In this study, we explore and assess the nature of the double guests and host roles of tourism migrant workers (TMWs), and their effects on the TWSs' adjusted person-place relationships and local identities by employing a systematic modeling approach in the context of the TMWs working in the intangible cultural tourism (ICH) businesses. The research site is fittingly set in Suzhou of east China, a destination whose rich historical and cultural heritages are now co-expressed and co-presented by a migrant workforce that has already outsized the locals. Research findings have shown that the socio-cultural adjustments availed by working in the ICH tourism businesses positively influence the local identities of TMWs, as mediated by their place attachment. This study advances a theoretical understanding of the mechanism of migrant integration in the particular context of cultural tourism development, and shows how tourism can contribute towards healthy, rather than stigmatizing, dialogues pertaining to migrant integration in the society at large.
... In the presence of misfit of work styles, individuals might engage in adjustment behaviours to increase their fitness by either acting with the environment or acting upon themselves (Bayl-Smith & Griffin, 2015). Engaging in work with host nationals in an organization could lead to social adaptation of an individual. ...
... In the presence of misfit of work styles, individuals might engage in adjustment behaviours to increase their fitness by either acting with the environment or acting upon themselves (Bayl-Smith & Griffin, 2015). Engaging in work with host nationals in an organisation could lead to social adaptation of an individual. ...
Article
Full-text available
The challenge of adapting to a new environment is one of the issues that leads to expatriates' poor performance. What contributes to the success of an individual in a workplace is the psycho-social comfort that is prevalent in the new environment. Diversity of culture, race and religion in an organisation is acceptable when there is tolerance. The study aims to develop a new model of cross-cultural work adjustments for Malaysian professional expatriates. The presence of two or more different cultures with different ideas and customs in the same organisation need to be acceptable to its members, depending on their level of tolerance. The present research has found that adjusting to the host's national custom or culture, religious practice, and kinds of entertainment are among the elements that influence the personal and work cross-cultural adjustments of expatriates. The research method used for this study is the content analysis by reviewing forty-two articles. A prescriptive model on factors that contribute to expatriate adjustment is proposed. Organisations could use the findings of the research to take necessary actions to reduce the propensity of professionals leaving their home companies abroad. Suggestions and recommendations are provided for the companies to improve so that Malaysian professional expatriates will remain in the companies that they are working for.
Article
Full-text available
We use a meta-analysis to introduce a framework that integrates research on the relationship between working hours and the work-family interface. Using the work-home resources model, we integrate work-family enrichment and conflict theory, focusing on the positive and negative mediational processes of human energy. We conceptualize working hours, within the framework of the work-home resources model, as having the potential to increase vigor and exhaustion in tandem, which in turn would lead to increased work-family enrichment and work-family conflict, respectively. Our model suggests, and a meta-analytic investigation (N = 459,846) confirms that the two dimensions of human energy, vigor and exhaustion, mediate the relationship between working hours and work-to-family enrichment and conflict, respectively. Taken together, our findings contribute to the literature by integrating the positive and negative energy mechanisms in the relationship between working hours and work-to-family enrichment and conflict. Specifically, by showing the parallel paths of vigor and exhaustion that occur when individuals increase working hours, we reconcile mixed findings regarding the effect of working hours on the work-family interface.
Article
This article is part of the 50th anniversary issue of the Journal of Vocational Behavior (JVB), with a focus on person-environment (P-E) fit. P-E fit has been a central research area in vocational and organizational psychology. With a focus on highly influential work in both fields, this article aims to synthesize P-E fit literature and develop theoretical models to guide future research. First, we summarize key perspectives and the state of the art in the general P-E fit literature. Second, based on a succinct review of P-E fit papers published in JVB, we take an interdisciplinary approach to critically discuss the conceptual and methodical ambiguities in this area. Third, we integrate identity and social exchange theories to present an Identity-Capability-Reward (ICR) model to conceptualize P-E fit across job roles and work entities at different levels. Fourth, we draw upon self-regulation and life-span development perspectives to propose a cybernetic development model that theorizes the self-regulated changes of fit experiences across time. We conclude with recommendations for an integrative, dynamic, and developmental approach to advance the P-E fit theories.
Article
Full-text available
Theories of person-environment (P-E) fit describe a dynamic process in which fit should improve over time due to changes in a person’s attributes, the environment, or both. Although these ideas are central in several theoretical perspectives, they have largely gone untested. Here, we report a longitudinal examination of interest congruence (i.e., interest fit) across 12 years during the transition from education to the workforce. The study uses four methods to capture interest congruence and the drivers of fit change: growth models, latent congruence models, person and environment latent difference scores, and piecewise growth models based on environmental transitions. Each method uses a different lens to understand interest congruence in educational and work domains. Across methods, three results were typically found: (1) interest congruence improved over time in school and at work, (2) participants’ interests often predicted educational and work changes, and (3) participants’ interests rarely changed in response to their environment. These results support a dynamic conceptualization of fit and suggest that selection—rather than socialization—is the main mechanism through which individuals achieve better interest fit during young adulthood. Other implications are discussed for theory development and the applied use of interest assessments.
Article
Full-text available
We review fundamental issues in one traditional structural equation modeling (SEM) approach to analyzing longitudinal data — cross-lagged panel designs. We then discuss a number of new developments in SEM that are applicable to analyzing panel designs. These issues include setting appropriate scales for latent variables, specifying an appropriate null model, evaluating factorial invariance in an appropriate manner, and examining both direct and indirect (mediated), effects in ways better suited for panel designs. We supplement each topic with discussion intended to enhance conceptual and statistical understanding.
Article
Interest in the problem of method biases has a long history in the behavioral sciences. Despite this, a comprehensive summary of the potential sources of method biases and how to control for them does not exist. Therefore, the purpose of this article is to examine the extent to which method biases influence behavioral research results, identify potential sources of method biases, discuss the cognitive processes through which method biases influence responses to measures, evaluate the many different procedural and statistical techniques that can be used to control method biases, and provide recommendations for how to select appropriate procedural and statistical remedies for different types of research settings.