Impact of activity-based
workplaces on burnout and
Department of the Built Environment, Eindhoven University of Technology,
Eindhoven, The Netherlands
Theo van der Voordt
Department of Management in the Built Environment, Faculty of Architecture,
Delft University of Technology, Delft, The Netherlands and
Center for People and Buildings, Delft, The Netherlands
vb&t Vastgoedmanagement bv, Eindhoven, The Netherlands
Department of the Built Environment, Eindhoven University of Technology,
Eindhoven, The Netherlands, and
Pascale Le Blanc
Industrial Engineering and Innovation Sciences,
Eindhoven University of Technology, Eindhoven, The Netherlands
Purpose –This paper aims to explore, which characteristics of activity-based ofﬁces are related to the
position of workers on the burnout –engagement continuum.
Design/methodology/approach –Literature review and an online survey amongst knowledge workers
in the Netherlands, which provided data of 184 respondents from 14 organisations. The data has been
analysed by descriptive statistics, bivariate analyses, factor analyses and path analysis, to test the conceptual
Findings –Five physical work environment constructs were identiﬁed of which three showed to have
signiﬁcant relations with employees’position on one of the three dimensions of the burnout –engagement
continuum. Distraction has a direct and indirect (through overload) negative relation with the individual
strain (meaning increasedexhaustion). Ofﬁce comfort has indirect positive relations (through recognition and
appreciation) with the interpersonal strain (meaning increased involvement). The possibility for teleworking
has an indirect positive relation (through control) on the self-evaluation strain (meaning increased efﬁcacy).
Practical implications –The ﬁndings show that in the design and management of a healthy physical
work environment, corporate real estate managers and human resource managers should particularly pay
© Rianne Appel-Meulenbroek, Theo van der Voordt, Rik Aussems, Theo Arentze and Pascale Le
Blanc. Published by Emerald Publishing Limited. This article is published under the Creative
Commons Attribution (CC BY 4.0) licence. Anyone may reproduce, distribute, translate and create
derivative works of this article (for both commercial and non-commercial purposes), subject to full
attribution to the original publication and authors. The full terms of this licence may be seen at http://
Received 13 September2019
Revised 2 March 2020
11 May 2020
18 June 2020
Accepted 30 June2020
Journal of Corporate Real Estate
Emerald Publishing Limited
The current issue and full text archive of this journal is available on Emerald Insight at:
attention to lowering distraction, providing comfortable workplaces and considering the option of
teleworking to some extent.
Originality/value –This paper provides new insights into the impact of distinct activity-based workplace
characteristics on workers’position on the burnout –engagement continuum.
Keywords Burnout, Engagement, Health, Distraction, Comfort, Activity-based workplaces
Paper type Research paper
According to Maslach and Leiter (1997), people’s psychological relationship to their job can
be positioned on a continuum between the negative experience of burnout and the positive
experience of engagement. Burnout can be deﬁned as a state of mental and physical
exhaustion caused by one’s professional life (Freudenberger, 1974). It is associated with
psychological and physical health problems (Schaufeli and Enzmann, 1998;Shirom et al.,
2005), job dissatisfaction, low levels of commitment and destabilisation of one’s work-life
balance (Grawitch et al.,2006), increased sickness absence (Schaufeli et al.,2009) and
reduced productivity and job performance (Maslach and Leiter, 2008). The opposite on the
continuum, work engagement, is deﬁned as a positive, fulﬁlling, work-related state of mind
that is characterised by vigour, dedication and absorption (Schaufeli et al., 2002). The
engagement has been associated with high levels of energy, pleasure, activation and
commitment (Parker and Grifﬁn, 2011). Engaged workers appear to be more open to new
experiences, explore their work environments and, in doing so, become more creative
In a present-day competitive society with its war on talent, employees are recognised as
the most valuable assets of the organisation. Regarding corporate real estate (CRE)
management, it is, thus, important to better understand the role of the physical environment
in reducing the risk of burnout and instead of stimulating engagement. In line with the
person-environment ﬁt theory, a suboptimal ﬁt between the work environment and
employees’needs and abilities would otherwise result in stress (Edwards et al., 1998). This
could mean that a poor ofﬁce workplace might push people towards the negative side of the
burnout-engagement continuum (BEC). So far, studies on healthy workplaces have focussed
mostly on isolated design aspects such as plants, indoor climate and sick building syndrome
(Arif et al., 2016). Knowledge about the impact of activity-based workplaces (ABW) on
health is very limited (Engelen et al.,2019). We only found one study that included the BEC
(Van Steenbergen et al.,2018). This before-after study (amongst 126 employees of a large
Dutch provider of ﬁnancial services) showed new ways of working to be beneﬁcial in
reducing mental demands and workload. It did not harm relationships with supervisors and
co-workers, but autonomy and possibilities for professional development decreased.
Burnout and work engagement remained stable over time. The current paper further
explores, which characteristics of ABW inﬂuence employees’position on the BEC. A
literature-based conceptual model is tested through path analysis for relations and effect
sizes. The model incorporates physical work environment characteristics as independent
variables, job-related situational characteristics as mediators and individual characteristics
as control variables.
Burnout and engagement: dimensions and inﬂuencing factors
Maslach and Leiter (1997) distinguished three sub-dimensions in their BEC theory as
follows: individual strain (exhaustion –energy), interpersonal strain (depersonalisation –
involvement) and self-evaluation strain (inefﬁcacy –efﬁcacy). Exhaustion refers to feelings
of being overextended and depleted of one’s emotional and physical resources. It is related to
work fatigue, i.e. extreme physical, mental and/or emotional tiredness and reduced
functional capacity (Frone and Tidwell, 2015). It is the most widely reported and most
thoroughly analysed dimension (Maslach et al., 2001;Maslach and Leiter, 2008), with energy
as the engagement opposite. Depersonalisation refers to a negative or excessively detached
response to various aspects of the job (Maslach et al., 2001). To make this depersonalisation
dimension applicable in multiple industries, Schaufeli et al. (1996) replaced
depersonalisation by the term cynicism, reﬂecting a distant attitude towards work, with
involvement as the engagement opposite. Inefﬁcacy refers to feelings of incompetence and
declined personal achievements at work (Maslach et al.,2001;Maslach and Leiter, 2008),
with efﬁcacy as the engagement opposite. The three dimensions are included as dependent
variables in our conceptual model, see Figure 1.
The antecedents of burnout and engagement are often classiﬁed into individual factors
and situational factors (Maslach et al.,2001;Bakker and Demerouti, 2008). In this paper, the
individual variables are incorporated as control variables, whereas the situational
characteristics are treated as mediators between the BEC dimensions and the characteristics
of the physical work environment (the independent variables). Besides being antecedents of
the BEC, these situational factors are likely to be inﬂuenced by the ABW as well. See
Figure 1 for the full model that is tested in this study. The next literature review will explain
the four main hypotheses and the variables chosen for each box to test these hypotheses.
In the past decades, various new ofﬁce concepts have been developed to support optimal use
of the available space and to empower knowledge workers to work more efﬁciently and
effectively. ABW is characterised by the shared use of different types of workplaces that are
supposed to optimally ﬁt with different ofﬁce tasks, mainly in open and semi-open settings.
The additional support by modern information and communication technology (ICT)
provides workers more autonomy and freedom to work how, when and where they ﬁnd this
most appropriate (Van der Voordt, 2004;Haapakangas et al.,2019). Such new ways of
(ﬂexible) working may provide better opportunities for communication, collaboration and
interaction (Engelen et al.,2019), but are also associated with less social cohesion amongst
co-workers, referring to a lower sense of community. Complaints include lack of privacy and
concentration, loss of storage space and loss of personal and group identity by not being
able to personalise the workspace (Gorgievski et al.,2010). In particular distraction by
conversations of colleagues and phone calls and lack of visual and auditory privacy cause
dissatisfaction amongst employees (Brunia et al.,2016). So far, it remains unclear whether
ABWs would have a positive or negative inﬂuence on workers’position on the BEC and how
their characteristics relate to the three distinct dimensions.
Vos et al. (1999) and De Croon et al. (2005) argue that ofﬁces can be described according to
three constructs, being ofﬁce location (place of work: at the ofﬁce versus teleworking at
home/third places), ofﬁce layout (space design i.e. open plan, cellular ofﬁces, team ofﬁces or
combi-ofﬁces) and ofﬁce use (personal desks versus non-assigned desks). Haynes (2007a)
developed a model with two constructs as follows: the physical environment and the
behavioural environment, each with two subcomponents, respectively, ofﬁce layout and
ofﬁce comfort and interaction and distraction. These authors did not speciﬁcally study
ABWs, which is, perhaps, why ICT support was not part of their frameworks. However, it is
an essential element of ABWs. Building on these references, the ABW component of the
conceptual model is split into ﬁve main constructs as follows (Figure 1): ofﬁce layout, ofﬁce
comfort, ofﬁce use, teleworking and ICT access.
Ofﬁce layouts that do not ﬁt with user needs and behaviour may result in feelings of lack
of control and community, and thus higher levels of workplace stress (Vischer, 2007). Based
on a review of 24 studies, De Croon et al. (2005) conclude that there is much evidence that
working in open workplaces reduces the ofﬁce worker’s psychological privacy and some
evidence that working in open workplaces and close distances between workstations
intensify cognitive workload and/or worsen interpersonal relations. They also found the
relationship between these two design aspects and performance to be inconsistent. So
potentially, ofﬁce layout relates to all three dimensions of the BEC. In ABWs the variety of
workplaces may increase feelings of autonomy, which has a positive relationship with work
engagement (Maslach and Leiter, 2008). Haynes et al. (2017) even showed that the
availability of a variety of spaces had the greatest impact on productivity (the self-
Ofﬁce comfort is usually related to ambient factors (Seppänen and Fisk, 2006) and
ergonomics (Kroemer and Kroemer, 2016). Indoor climate and lighting are often ranked
highest in the ofﬁce’s impact on perceived health and performance (Bae et al., 2017). Kroemer
and Kroemer (2016) point out that ofﬁce ergonomics can lower stress, increase personal
engagement and raise performance as well. Besides comfort, the ability to adjust these
factors to individual preferences may contribute to feelings of control and fairness (e.g. equal
treatment regardless of job rank) (Clements-Croome and Li, 1997) and as such may be
related to dimensions of the BECas well, following Maslach and Leiter (2008).
Ofﬁce use regards both interaction and distraction and desk-sharing. Interaction and
distraction are highly interrelated. One person’s interaction is another person’s distraction
(Haynes and Price, 2004) and can decrease feelings of privacy. Both social and work
interactions may be linked to feelings of community, while distraction by interruptions,
feelings of crowding and noise and feelings of lack of control and privacy may be related to
all three dimensions of the BEC (Bakker et al., 2014;Haynes, 2007b). The ABW environment
adds additional relevant use-aspects, as workers have to share workspaces and are expected
to switch between different workspaces. The evidence of whether desk-sharing increases
overload is still inconsistent but provided by some studies according to De Croon et al.
(2005). Only 4% of workers switch workstations during the day (Hoendervanger et al.,2016).
Apparently, this ABW-rule is not perceived as a positive demand and might cause stress.
Additionally, it determines who sits by whom and could, thus, relate to the interpersonal
Teleworking may result in more autonomy where to work, and thus in less interaction
between staff members, which may reduce the possibility to obtain social support and
feedback. It also may indicate that work is never completed (Demerouti et al., 2014;Peters
and Van der Lippe, 2007). Teleworking is shown to create loneliness, irritability, worry and
guilt and stress (Mann and Holdsworth, 2003). Besides these potential links to the individual
and the interpersonal dimensions of the BEC, research has shown that telework intensity
has consequences for the efﬁcacy dimension (Hoornweg et al.,2016).
Last, inappropriate ICT facilities, information overload, the pressure to respond quickly
to e-mails and social media and insufﬁcient skills to cope with these issues may result in
perceived work overload (Rennecker and Derks, 2012;Demerouti et al.,2014). As a
consequence, a relationship with at least the individual dimension of the BEC can be
expected. ICT access has also been shown to relate to the productivity of workers
(Nurmilaakso, 2009). Intuitively, technology such as intranet and cloud computing could
relate to the interpersonal dimension as well, as people can exchange information this way.
Therefore, we pose:
H1. ABW characteristics have a direct effect on an employee’s position on the BEC.
Individual control variables
Not all individuals are equally likely to get a burnout. Therefore, various individual
characteristics are included in the model as control variables. Maslach et al. (2001) pointed
out that the level of burnout amongst younger employees is higher than amongst those over
30 or 40 years old. This suggests that workers are more at risk to burn out earlier in their
careers. Men score a little higher on the cynicism dimension of burnout, whereas women
score higher on the exhaustion dimension of burnout (Maslach et al.,2001), so gender
matters as well. Also, employees with higher levels of education and singles are more likely
to experience burnout (Maslach et al.,2001). With regard to personality, Schaufeli and
Enzmann (1998) refer to numerous studies that included one or more of the Big ﬁve
personality characteristics. For example, people who score high on neuroticism are more
sensitive to stress (Albrecht, 2010) while extraversion and conscientiousness are directly
associated with a higher level of well-being (Parent-Lamarche and Marchand, 2019).
Besides personal characteristics, individual job-related aspects could be relevant as well.
Knowledge workers have to be productive in three different main activities, namely
concentrated work, formal interactions and informal interactions (De Been et al.,2016). It
might differ between workers how important each activity is, which could be relevant to the
interpersonal strain (interactions) and, perhaps, also to the other BEC dimensions. Also,
Maslach et al. (2001) mention that burnout is higher amongst people in lower job ranks, who
have little participation in decision making. Also, work experience acquired through on-the-
job-training has been shown to lead to greater productivity (Qui
nones et al., 1995), and thus
may affect the self-evaluation strain.
Therefore, we pose:
H2. Individual control variables affect an employee’s position on the BEC.
Bakker et al. (2014) found that stressful aspects of the work situation are even more
important predictors of burnout than personal control variables. Maslach and Leiter (1997)
identiﬁed six domains of situational work environment factors as follows: stress, control,
reward, community, fairness and values. TNO (2015) showed that job stress is mainly
caused by insufﬁcient autonomy (44%) and excessive workload (38%). High job demands
and lack of control may result in job stress, which has been recognised as an early predictor
of burnout and as an impairment of physical health, psychological well-being and work
performance (Kahn and Byosiere, 1992). Reward refers to the power of reinforcements to
shape behaviour and stress (Leiter and Maslach, 2005). A high level of a perceived
community may reduce stress (Schaufeli and Bakker, 2004), e.g. by social support from co-
workers and supervisors. Fairness emerged from the literature on equity and social justice.
Unfairness occurs when there is the inequity of workload or reward, when there is cheating
or when evaluations and promotions are handled inappropriately (Maslach et al., 2001). The
sixth domain –Values –picks up the cognitive-emotional power of job goals and
expectations (Leiter and Maslach, 2005). When a conﬂict of values occurs at the job, workers
will ﬁnd themselves making a trade-off between the work they want to do and the work they
have to do (Maslach et al.,2001;Maslach and Leiter, 2008):
H3. Situational variables affect an employee’s position on the BEC.
Besides a direct relation between situational variables and the BEC, the ofﬁce environment
is likely to relate to these situational variables as well, so they are included as mediators in
the conceptual model. For example, Van der Voordt (2004) warns for additional workload
due to desk sharing and switching, as workers lose time by ﬁnding available workspaces
and adjusting their settings to their own preferences. Then, teleworking could reduce social
support (community) and increase workload (Demerouti et al., 2014;Peters and Van der
Lippe, 2007). Oseland (2009) states that ofﬁce design should provide workers with a feeling
of control through both the personal space and the way they are allowed to use the ofﬁce.
Access to ICT and teleworking might also increase feelings of control. Reward not only
relates to ﬁnancial payment but also to a feeling of being appreciated. Supportive ofﬁce
design and comfort might add to this feeling (Rothe et al., 2011). On the other hand, an ofﬁce
design that does not ﬁt with user needs and behaviour may result in a lack of feelings of a
community (Vischer, 2007). Studies on activity-based ofﬁces also refer to fairness and
values, for example, by mentioning that ABW is not considered as fair if not all levels in the
organisation give up their dedicated desks (Appel-Meulenbroek et al.,2015).
So last, we pose:
H4. ABW characteristics have an indirect effect on employee’s position on the BEC, via
the situational variables.
Sampling and measuring
To test the conceptual model and hypotheses, quantitative data has been collected by means
of an online questionnaire. CRE managers, facility-managers and human resource managers
of 14 organisations with an ABW concept were asked to distribute the questionnaire to
knowledge workers within their organisation, between 10 July and 4 September 2018. In
total, 184 employeescompleted the full questionnaire with 85 questions and statements.
Regarding the ABW environment, respondents were asked to respond to a number of
statements, using a ﬁve-point scale. The ofﬁce layout is operationalised by workplace
variety, workplace availability, openness, the distance between workplaces and facilities.
The responses to eight statements (e.g. “The variety of workspaces allows me to choose the
workspace that best ﬁts the activity”and “In my opinion, the spatial design of the ofﬁce
environment is optimal”) range from (strongly) disagree till (strongly) agree. Ofﬁce comfort
has been measured by 10 statements on ambient factors (e.g. air quality, ventilation,
personal control), ergonomic furniture (desks and chairs) and overall comfort, with
responses ranging from (very) uncomfortable till (very) comfortable. Ofﬁce use has been
operationalised by the frequency of choosing a workplace that ﬁts best with the activity,
leaving behind a clean desk, claiming a workplace by personalisation, interaction,
distraction, the experience of excessive noise and opportunities to isolate themselves from
colleagues, using 10 items (e.g. “during work, I interact with colleagues on a social level”and
“during work, I am easily distracted by colleagues”). For teleworking two items were used
(“I can work at home”and “I can work between home and the ofﬁce”at any given time) and
for ICT three items (e.g. “I can use cloud computing to store my data”), both with answers
ranging from never till always.
The individual control variables age, gender, level of education and household
composition were measured by closed questions. Personality has been measured by the Big
Five Inventory (BFI-10) questionnaire (Rammstedt and John, 2007), job rank by marking one
out of six choices (e.g. trainee, board member, other) and work experience by indicating
years of deployment at the current employer. Activities, in particular communication and
concentration, were measured by their importance on a ﬁve-point scale. The six situational
variables have been measured by 11 statements from the areas of work-life scale measure
(AWS) (Leiter and Maslach, 2003), e.g. “I have too much work to do”and “I perceive my
social rewards (e.g. appreciation, respect) as being sufﬁcient for the work I do”.
For the employees’position on the BEC, 15 statements (seven-point scale) were adopted
from the Utrecht Burnout Scale (UBOS, Brenninkmeijer and Van Yperen, 2003). The UBOS-
GS is very similar to the widely used MBI-GS that assesses the three BEC dimensions
(Maslach and Leiter, 2008). See Aussems (2019) for the full survey set-up.
Checks were conducted on sufﬁcient sample size, multicollinearity and singularity, outliers,
normal distribution, linearity and homoscedasticity, to deﬁne, which statistical analyses
would be most appropriate and what kind of data reduction could be applied before the main
analysis. Scale constructs were checked on internal consistency by Cronbach’s alpha, which
showed to be sufﬁciently high (>0.70) for most variables. Distraction conditions in the ofﬁce
(close proximity) lowered Cronbach’s alpha of the ofﬁce layout construct from 0.81 to 0.71.
Because of its expected impact based on the many ofﬁce noise studies, it was kept as a
separate “proximity”variable. The ofﬁce use items (
= 0.34) were entered into a factor
analysis (Principal Axis Factoring and Direct Oblimin with Kaiser normalisation) to reduce
the set of variables while assuming a latent construct of ofﬁce use. This provided four
factors, labelled interaction, distraction, desk-switching and claiming, explaining 62.8% of
the total variance. The six situational variables were reduced by factor analysis as well due
to low Cronbach’s alpha values (
= 0.634 (control), 0.540 (rewards) and 0.306 (community)
with single items for the other three variables). The factor analyses reduced the set of
variables to four factors, explaining 62.5% of the total variance. Recognition includes
ﬁnancial and social rewards and fairness. Overload and values group together. The control
contains all original control items, while appreciation combines the social support items
(from co-workers and from supervisors) with intrinsic rewards (pride). Table 1 shows the
ﬁnal variables that were used for further analyses. A path analysis was used as an extension
of multiple regression analysis to simultaneously analyse the direct and indirect effects of
ABWs on all three strains of the BEC and the relationships between the strains while
controlling for individual variables and placing the situational variables as mediators. A
major advantage is that this method can estimate direct and indirect effects simultaneously
and allows them to include several dependent variables. To select, which variables and
relations to include in the path analysis, ﬁrst bivariate correlation analyses were performed
for all possible relations in the model, to check whether the theoretical assumptions are
replicated in this sample. A minimum sample size for regression type analyses is N =
50 þ8k, in which k is the number of predictors or independent variables (Tabachnick and
Fidell, 2007). The variable with the highest amount of (15) predictors in the path model is the
self-evaluation strain and 50 þ8 * 15 = 170 still falls within the sample size of 184
with BEC dimensions
Variables Individual strain Interpersonal strain Self-evaluation strain
Ofﬁce layout 0.100 0.036 0.060
Proximity 0.077 0.030 0.176*
Ofﬁce comfort 0.023 0.135 0.144*
- Interaction 0.078 0.085 0.168*
- Distraction 0.282** 0.176*0.110
- Desk-switching 0.008 0.074 0.210**
- Claiming 0.086 0.103 0.0.37
Possibility to telework 0.015 0.020 0.006
ICT access 0.091 0.076 0.155*
Individual control variables
- Age 0.106 0.109 0.277**
- Gender Z = 0.354** Z = 0.131 Z = 0.767
- Education level 0.046 0.066 0.064
- Household composition 0.050 0.024 0.061
- Extraversion 0.121 0.221** 0.263**
- Agreeableness 0.087 0.212** 0.198**
- Conscientiousness 0.061 0.188*0.225**
- Neuroticism 0.202** 0.150*0.314**
- Openness 0.015 0.231** 0.158*
- Job Rank Z = 0.218 Z = 0.036 Z = 0.133
- Work experience 0.038 0.052 0.339**
- Activities_concentration 0.039 0.112 0.083
- Activities_informal interaction 0.097 0.191** 0.080
- Activities_formal interaction 0.028 0.307** 0.010
Recognition 0.228** 0.297** 0.146*
Overload 0.365** 0.106 0.037
Control 0.130 0.196** 0.370**
Appreciation 0.054 0.367** 0.290**
Notes: ** = signiﬁcant at 0.01 level; * = signiﬁcant at 0.05 level. A test on interrelationships between the
three BEC dimensions showed two correlations to be signiﬁcant: between the individual and interpersonal
strain (0.419**) and between the self-evaluation and interpersonal strain (0.289**). The correlation between
individual strain and self-evaluation strain was not signiﬁcant. As Maslach and Leiter (1997) did assume
relations between all three strains, we stick to including all three relations in the path model, with arrows in
The sample contains a larger share of women (56.0%) compared to the whole Dutch work
population (46%). The respondents are between 20 and 66 years of age (M = 43.7; SD =
11.8), whereas the overall average age of Dutch workers is 42.1 years; the difference is not
signiﬁcant. The majority of respondents (77.7%) is highly educated, 20% is single, 76.6% is
living together/married without children (32.1%) or with children (44.6%) and 3.3% marked
“other”. The majority of respondents perceive themselves as outgoing and sociable (72.8%),
indicating extravert personalities. For agreeableness, most respondents see themselves as
generally having trust (91.8%). The majority of respondents identify themselves as doing a
thorough job (91.8%) and, thus being conscientious. For neuroticism, the majority of
respondents identify themselves as being relaxed and handling stressful situations well
(66.3%), rather than being nervous easily (6.5%). With respect to openness, the majority of
respondents identify themselves positively too. Work experience averages 13.1 years (SD =
11.4). Most respondents are regular employees (71.2%), with 20.7% being a manager/
supervisor. The importance of the three activities (concentration, formal and informal
communication) is very similar for all respondents as follows: the average is a little above 4
(= important) with standard deviations of approximately 0.7.
In general, the mean scores on the BEC traits were on the positive side of the seven-point
scale, so pointing towards an engaged sample with relatively low burnout symptoms. The
individual dimension scored a 6.13 average (SD = 0.74), the interpersonal dimension 6.36
(SD = 0.82) and the self-evaluation dimension 5.70 (SD = 0.713).
Bivariate correlation analyses
The ﬁndings of the bivariate analyses (Table 1) indicate signiﬁcant relationships between
most ABW constructs and all situational variables with at least one of the BEC dimensions.
Only ofﬁce layout, desk claiming and teleworking did not show any signiﬁcant direct
correlations. However, ofﬁce layout and teleworking do show potential for an indirect
relation mediated by situational variables, as they correlated, respectively, with recognition
and with control and appreciation (Table 2). Again, desk claiming did not, and therefore is
left out of the path analysis, as there is also no existing proof in previous studies relating this
speciﬁc aspect of ofﬁce use to any of the situational variables or the BEC.
The individual control variables age, gender and personality also showed to be
signiﬁcantly correlated with at least one of the BEC dimensions, whereas education level
Workplace characteristics Recognition Overload Control Appreciation
Ofﬁce layout 0.149* 0.071 0.103 0.037
Proximity 0.027 0.007 0.097 0.078
Ofﬁce comfort 0.255** 0.090 0.127 0.233**
- Interaction 0.093 0.060 0.044 0.112
- Distraction 0.069 0.153* 0.100 0.038
- Desk-switching 0.107 0.056 0.143 0.060
- Claiming 0.089 0.030 0.091 0.116
Possibility to telework 0.114 0.122 0.205** 0.170*
ICT access 0.117 0.091 0.128 0.118
Notes: ** = signiﬁcant at 0.01 level; * = signiﬁcant at 0.05 level
and household composition did not. Regarding the ﬁve work-related variables, work
experience and formal and informal interaction showed to be signiﬁcantly correlated, with,
respectively, the self-evaluation strain and the interpersonal strain.
The model to be tested, based on theory and bivariate analyses, is presented in Figure 2.
Figure 3 shows the relations that remained signiﬁcant in the path analysis, with the
standardised coefﬁcient for each link. The R
is 0.20 for the individual strain, 0.25 for the
interpersonal strain and 0.31 for the self-evaluation strain. So, a maximum of almost a third
of the variation in the BEC dimension is explained by the independent variables. The ABW
constructs explain only a few per cent of the variation in the situational variables
= 0.07; overload R
= 0.02; control R
= 0.04; appreciation R
= 0.07). Three
ABW constructs showed signiﬁcant relations with a BEC dimension, namely distraction
(ofﬁce use), Ofﬁce comfort and teleworking. The interpersonal strain has (bidirectional) links
both with the individual (
= 0.31) and the self-evaluation strain (
= 0.12), but again the
relationship between the individual and the self-evaluation strain was not signiﬁcant.
Distraction has a direct negative relationship with the individual strain (
indicating that when distraction increases, exhaustion increases. More peculiar is the
indirect relationship through overload, where distraction decreases overload (
and increases energy (
= 0.22). Also, women score higher on individual strain (more
energy) than men (
Ofﬁce comfort only has indirect relations, both through increasing feelings of recognition
= 0.23) and appreciation (
= 0.20), with increased involvement (the interpersonal strain,
= 0.18 and 0.17). Workers for who formal meetings are more important (
= 0.23) or who
have more open personalities (
= 0.15) also score higher on the interpersonal strain.
The possibility for teleworking relates to increased feelings of control (
= 0.21), which
relates to efﬁcacy (the self-evaluation strain,
= 0.20), so again only an indirect relation.
Model used for path
More conscientious (
= 0.17) and more agreeable (
= 0.04) personalities and workers with
more work experience (in years at this employer;
= 0.24) also score higher on efﬁcacy,
while more neurotic persons score lower (
Discussion, implications and limitations
Impact of activity-based workplaces on employees’position on the burnout-engagement
Hypothesis H1 (ABW characteristics have a direct effect on an employee’s position on the
BEC) can only be partially accepted for ofﬁce use. Only one signiﬁcant, negative direct
relation came forward, between distraction and the individual strain (exhaustion-energy) of
the BEC. A lot of distractions can be frustrating, which costs energy on its own and people
have to work longer to get their work done by making up for a lost time. There is not much
research yet on how to deal with distractions. Most studies on acoustics and noise focus on
sound levels (Keränen and Hongisto, 2013) or noise effects on satisfaction (Kim and De Dear,
2013) but not on (mental) health of employees. With the trend towards increased open
ofﬁces, this deserves further research into the effects of technologies such as sound masking
(Jahncke et al.,2016) and optimising coping behaviour. Contrary to previous studies on
productivity (Haynes, 2007b), distraction did not relate to the self-evaluation strain. As there
was no link between the individual and self-evaluation strain, there is also no indirect effect
of distraction on efﬁcacy, which is unexpected. As many respondents in this sample rated
their efﬁcacy very high, there might be a restriction of range in the dependent variable. All
the other ABW characteristics did not relate to the self-evaluation strain in the path model
either, where previous studies suggested a relationship with comfort (Bae et al.,2017) and
ICT access (Nurmilaakso, 2009).
That desk-switching supports people’sefﬁcacy is one of the basic assumptions of ABW,
but it has not been proven in studies and again is not conﬁrmed here. Previous work suggests
that task-switching triggers overload (Demerouti et al.,2014), but for desk-switching
Final model after
(which is supposed to be based on switching tasks) this is not conﬁrmed by our ﬁndings.
Perhaps, for desk switching this is only the case when there are “negative”reasons (e.g.
distraction) causing the switch (Hoendervanger et al.,2016). Claiming the same desk by
personalising does not seem to support the efﬁcacy or provide less exhaustion either.
Perhaps, those who claim desks, do this for different reasons than stress, for example, to
express status or to be able to use a preferred workplace every day.
Also, surprising is the lack of a relation between interaction and interpersonal strain
(involvement). Where the importance of formal meeting activities for one’s work was related
to increased involvement in the model, actually having more social or work-related
interactions was not. As involvement deﬁnitions are generally based on communication
processes (Lopes et al., 2017), this seems counterintuitive. On the other hand, the actual
interactions might not have provided a positive experience to the employees. Clearly, further
research on ofﬁce use is needed to fully understand ABW environments. It would also be
interesting to replicate this research amongst people with more extensive burnout
Hypothesis H4 (ABW characteristics have an indirect effect on employee’s position on
the BEC via the situational variables) can be accepted more strongly. First, where
distraction already had a direct effect, there is additionally a mediated effect through a
negative effect on overload. Remarkably, the data do not only suggest that an increase in
overload (“I have too much work to do”) increases feelings of energy but also that distraction
decreases perceived overload. A lack of (auditory) privacy is generally associated with
greater feelings of exhaustion (Bakker et al.,2014), but maybe there are also welcome forms
of distraction, which make people relax for a moment. A large part of the sample scored high
on the individual strain (more energy), so, perhaps, they get energy from having a lot of
work to do. However, the continuation of this situation might lead to burnout in the long run.
Clearly, distraction in the ofﬁce deserves further research.
Second, perceived ofﬁce comfort relates signiﬁcantly to both feelings of recognition and
appreciation. Like in earlier research (Maslach and Leiter, 2008), such feelings increase the
involvement of workers (interpersonal strain). One of the major dilemmas in designing ofﬁce
comfort remains that what is optimal for one person or group may not be optimal for other
people (Bitner, 1992). There exist signiﬁcant individual differences in preferences (Wang
et al.,2018) and Budie et al. (2019) showed that those using the open spaces in ABWs a lot
ﬁnd comfort even more important.
Third, teleworking improved efﬁcacy via increased control. While teleworking provides
some autonomy, and thus control, Hoornweg et al. (2016) showed that there might be a limit
to this effect, as the effect on productivity changed from positive to negative with a higher
telework intensity. Also, telecommuters experience more time pressure in thelong run, while
making longer work hours (Peters and Van der Lippe, 2007), although in this sample this did
not lead to more exhaustion. The increased perceived efﬁcacy could also be caused by the
fact that the respondents found a distraction-free environment at home or a better work-life
The expected indirect relations between ofﬁce layout and all BEC dimensions through
recognition were not conﬁrmed in the path analysis. So, relations of ofﬁce layout design with
the workload and interpersonal relations (De Croon et al.,2005) and control (Vischer, 2007)
could not be conﬁrmed. In general, all layout items scored a mean between 3 and 4 on a ﬁve-
point scale indicating that workers in the sample perceive a good ﬁt between their needs and
abilities and the layout of their ABW. Perhaps, there was too little variation in layout quality
to identify an effect. Another explanation might be that the high demands of an open ABW
environment (noise-causing exhaustion and less efﬁcacy) are compensated by appropriate
resources (variety in spaces, facilities), as put forward in the Job-demands-resources model
by Bakker and Demerouti (2007). Further research should shed more light on whether and
how the ABW layout design affects burnout and engagement.
Burnout-engagement continuum and personal control variables
It was not completely unexpected that no relationships between the individual and self-
evaluation strain were found in the path analyses. Others (Lee and Ashforth, 1996) found
relatively low correlations of professional efﬁcacy with both other dimensions as well. The
relationship between the individual and interpersonal strain was conﬁrmed, which is in line
with the idea that these form the core of burnout (Green et al.,1991).
Hypothesis H2 (Individual control variables affect an employee’s position on the BEC)
and H3 (Situational variables affect an employee’s position on the BEC) are conﬁrmed, but
less complete than expected. For example, Alarcon et al. (2009) found that neurotic workers
feel less energetic and experience more exhaustion, while in this study the neuroticism trait
only relates negatively to efﬁcacy. Previous research (Langelaan et al., 2006) claims that
high neuroticism is the core antecedent of burnout, whereas people who score high on work
engagement are characterised by low neuroticism in combination with high extraversion.
The positive relation between openness and efﬁcacy is also not conﬁrmed, nor are previous
ﬁndings of a relation between neuroticism and the interpersonal dimension (Schaufeli and
Enzmann, 1998). It is clear that personality plays a role, but further research with larger and
more diverse samples is necessary to gain more insight into how personality inﬂuences the
BEC in an ABW context. Also, the ﬁndings regarding the effect on gender oppose that of
Maslach et al. (2001), as men scored higher on exhaustion than women.
As expected, more experienced workers are more likely to see themselves as efﬁcacious.
Maslach et al. (2001) argued that age is related to work experience, suggesting that the risk
of burnout is higher in an earlier phase of ones’career, but in this study, age was not related
to any of the BEC dimensions. Regarding the importance of activities, workers who consider
formal meetings more important show higher involvement. This does not apply to informal
meetings. Further research should identify why this might be the case.
Limitations of the study
The study of complex phenomena such as burnout and engagement would beneﬁt from
longitudinal research. Due to the cross-sectional design of our study, it is impossible to
derive causal relationships. Besides being a cross-sectional survey, this study was limited to
the perceived impact of the physical environment, workers’activities, individual
characteristics and work-related situational variables on burnout/engagement. The R
values suggest that additional variables exist that explain workers’position on the BEC
The sample only included Dutch respondents and was relatively small. Although the
current sample showed to be sufﬁciently large to conduct an appropriate path analysis, the
limited size of the sample and a large number of inﬂuencing variables allowed to identify
only relatively strong relationships. Not identifying relationships does not mean that they
do not exist, but probably they are not sufﬁciently strong to be identiﬁed with the present
size of the sample. A larger sample might have resulted in the identiﬁcation of more
relationships between the many independent variables and the burnout-engagement
dimensions. The sample also includes workers from many different organisations. However,
apart from being an ofﬁcial organisation, no further information about these organisations
was available. Also, the ﬁndings can only be an indication of the Dutch context in which the
data were gathered.
While the burnout-engagement dimensions have been measured by validated measures,
this does not (yet) apply to some of the independent variables. Additionally, using a more
extended questionnaire (e.g. all 29 statements derived from the AWS, rather than the
selection of 11 statements in this study) would be worthwhile to conduct more in-depth
analyses of the relationships between the physical workplace characteristics, control
variables and other potentially relevant variables, if the samplehad been bigger.
The current study is partly exploratory (data-driven decisions, which variables to
include in the path analysis) and partly theory-driven (testing hypotheses of
interrelationships between families of independent, mediating and control variables and the
BEC). When a more extended theory is available, follow-up research could focus on more
detailed hypotheses regarding single variables.
Besides larger samples, qualitative research using workshops with medical experts,
business managers, CRE and facilities managers, human resource managers and well-
informed employees and analyses of sick leave data should be used to further validate the
scales of the BEC and its relationship with ABW characteristics.
Especially ofﬁce use requires more attention of workplace managers in practice when
implementing the ABW concept. CRE managers aiming at mentally healthy workplaces
should focus on offering a low distraction, comfortable environment. Workers should have
the opportunity (and the organisational culture, Babapour, 2019) to isolate themselves from
distraction when necessary, by providing various types of workplaces that support
concentration (e.g. cell-ofﬁces, quiet areas, private spaces) and/or clear use-protocols in more
open environments. Furthermore, CRE managers are recommended to support teleworking
to a certain extent, to keep employees feeling in control but still connected to the
organisation and their colleagues. In all cases, individual preferences should be taken into
account as well.
Overload showed to be the strongest predictor of the individual (exhaustion-energy)
dimension of the BEC, the importance of formal interaction of the interpersonal (cynicism-
involvement) dimension and work experience of the self-evaluation (inefﬁcacy-efﬁcacy)
dimension. Because CRE is a supportive resource, it makes sense that work and individual
characteristics have a larger effect on employees’mental health than the CRE. However, the
standardised coefﬁcients of the ABW constructs were of a similar size as those of the
individual and situational variables. So, although neglected in previous studies, the physical
work environment should clearly be included in future studies on burnout and engagement
in ABWs as well. An additional novelty of this paper is that several general assumptions of
ABW did not come forward in this analysis and clearly need more research to show whether
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