The Relative Benefits of Green Versus Lean Office Space: Three Field Experiments

Abstract

Principles of lean office management increasingly call for space to be stripped of extraneous decorations so that it can flexibly accommodate changing numbers of people and different office functions within the same area. Yet this practice is at odds with evidence that office workers' quality of life can be enriched by office landscaping that involves the use of plants that have no formal work-related function. To examine the impact of these competing approaches, 3 field experiments were conducted in large commercial offices in The Netherlands and the U.K. These examined the impact of lean and "green" offices on subjective perceptions of air quality, concentration, and workplace satisfaction as well as objective measures of productivity. Two studies were longitudinal, examining effects of interventions over subsequent weeks and months. In all 3 experiments enhanced outcomes were observed when offices were enriched by plants. Implications for theory and practice are discussed. (PsycINFO Database Record (c) 2014 APA, all rights reserved).

Full text

Journal of Experimental Psychology: Applied
The Relative Benefits of Green Versus Lean Office Space:
Three Field Experiments
Marlon Nieuwenhuis, Craig Knight, Tom Postmes, and S. Alexander Haslam
Online First Publication, July 28, 2014. http://dx.doi.org/10.1037/xap0000024
CITATION
Nieuwenhuis, M., Knight, C., Postmes, T., & Haslam, S. A. (2014, July 28). The Relative
Benefits of Green Versus Lean Office Space: Three Field Experiments. Journal of
Experimental Psychology: Applied. Advance online publication.
http://dx.doi.org/10.1037/xap0000024

The Relative Benefits of Green Versus Lean Office Space:
Three Field Experiments
Marlon Nieuwenhuis
Cardiff University Craig Knight
University of Exeter
Tom Postmes
University of Groningen S. Alexander Haslam
University of Queensland
Principles of lean office management increasingly call for space to be stripped of extraneous decorations
so that it can flexibly accommodate changing numbers of people and different office functions within the
same area. Yet this practice is at odds with evidence that office workers’ quality of life can be enriched
by office landscaping that involves the use of plants that have no formal work-related function. To
examine the impact of these competing approaches, 3 field experiments were conducted in large
commercial offices in The Netherlands and the U.K. These examined the impact of lean and “green”
offices on subjective perceptions of air quality, concentration, and workplace satisfaction as well as
objective measures of productivity. Two studies were longitudinal, examining effects of interventions
over subsequent weeks and months. In all 3 experiments enhanced outcomes were observed when offices
were enriched by plants. Implications for theory and practice are discussed.
Keywords: space, office, plants, well-being, productivity
Supplemental materials: http://dx.doi.org/10.1037/xap0000024.supp
Shortly after his British general election victory in 2010, Prime
Minister (PM) David Cameron singled out the cost of flowers and
pot plants in Whitehall’s offices as clear evidence of the need to
eliminate waste in the public sector (Saner, 2012). His Communi-
ties Secretary, Eric Pickles, quickly followed suit and cancelled his
department’s floristry bill and berated the Audit Commission for
spending £40,000 on plants in its working environments.
Yet it appears that many of the PM’s cabinet colleagues were
not on message. It was revealed that four major government
departments — including the Foreign Office and Treasury (where
Chancellor George Osborne is responsible for the Government’s
austerity program)—spent £34,297.54 between them on plants and
flowers in the year after the Conservative election victory (Han-
sard, 2011). Luciana Berger Member of Parliament “denounced
the spending” (Morris, 2011, p. 11). David Laws, Treasury Sec-
retary, subsequently declared that his department’s spending on
plants had been cut to zero (Crampton, 2011).
Less is More: The Lean Office
Cameron’s policy—which was widely applauded in some cir-
cles—is clearly informed by a belief that money spent on office
plants is money wasted (Dravigne, Waliczek, Lineberger, & Zaji-
cek, 2008). This is a sentiment that is widely shared within the
business literature, where it is argued that clean, obstruction-free
work-surfaces are the most economical route to business health
and productivity (e.g., Haberkorn, 2005; Tapping & Dunn, 2006).
This lean philosophy has a long history. Indeed, the idea that
productive work requires a workspace clear of any interference
was first formally implemented by Josiah Wedgwood in the 18th
century (Dolan, 2004) and centuries later inspired Frederick Taylor
(1911) to apply his principles of scientific management to the
organization of office space (e.g., Crompton & Jones, 1984; Has-
lam & Knight, 2010, for a review). During the mid-20th century,
these manufacturing methods were also applied to white-collar
work (Haberkorn, 2005; Hyer & Wemmerlov, 2002) and it is from
this approach that the term the “lean office” emerged as a discrete
concept in the 1990s (e.g., Hirano, 1996). Reflecting this, it is
common for managers to insist that workspaces should be clear of
plants, pictures, souvenirs, food, and anything not directly required
for the job at hand in attempt to streamline business operations and
maximize productivity (Haslam & Knight, 2006; Skinner, 2005).
More generally, it has been observed there is a trend for offices
to move toward minimal decoration for two major reasons (Marko-
vitz, 2012). First and most importantly, this reflects the widespread
influence of a lean corporate philosophy. As the first sentence of
the Lean for Dummies guide puts it: “The principles and practices
of lean organizations are recognized the world over as the most
Marlon Nieuwenhuis, School of Psychology, Cardiff University; Craig
Knight, School of Psychology, University of Exeter; Tom Postmes, Faculty
of Behavioral and Social Sciences, University of Groningen; S. Alexander
Haslam, School of Psychology, University of Queensland.
This research was supported by an award from Productschap Tuinbow
(The Healthy Project, project number 13719) and further support from Ki
Plants. We thank Bart van Bezouw for his analysis of the productivity data.
Correspondence concerning this article should be addressed to Craig
Knight, School of Psychology, University of Exeter, Perry Road, Exeter,
EX4 4QG. E-mail: Craig.p.Knight@ex.ac.uk
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This article is intended solely for the personal use of the individual user and is not to be disseminated broadly.
Journal of Experimental Psychology: Applied © 2014 American Psychological Association
2014, Vol. 20, No. 3, 000 1076-898X/14/$12.00 http://dx.doi.org/10.1037/xap0000024
1

powerful and effective way to build and sustain continuously
improving buildings and institutions” (Sayer & Williams, 2006, p.
1). As Mann (2010) explains “Lean . . . has proved to be an
unbeatable way to organize productive operations” (p. 15). Sec-
ond, the lean concept is seen to have particular appeal in a time of
general economic recession because it fits with an emphasis on
austerity and cost-cutting (Saner, 2012). In a world where people
are losing their jobs, investment in plants and other “nonessential”
items appears frivolous.
Yet, perhaps because the idea that lean space is more productive
is so intuitively appealing, there is almost no quantitative evalua-
tion or controlled experimentation to support these ideas (e.g., see
Haberkorn, 2005; Worthington, 2006). Lean evidence is drawn
more or less exclusively from selective case studies (e.g., Honey-
well, NY Government Offices; see Harris & Harris, 2006; Marko-
vitz, 2012). But case studies of lean success can be countered with
equally dramatic instances of failure (e.g., HM Customs and Rev-
enue; Haslam & Knight, 2006). As far as we know, there is only
one experimental study of the effects of office design (Knight &
Haslam, 2010b). This research showed that people who work in an
environment enriched by office plants and artwork were more
productive than their counterparts assigned to work in a lean space.
Meanwhile, recorded levels of well-being—as measured by sick
office syndrome, feelings of comfort and levels of job satisfac-
tion—were significantly higher in an enriched space. Thus, in a
direct comparison of enriched spaces and lean office space, the
lean office was clearly inferior on all dimensions.
The Green Office: Improved Performance
Despite the enormous influence of lean philosophy on office
space management (George, 2003), its conclusions have been
challenged within both design and science. Perhaps the clearest
suggestion that office space might benefit from enrichment
emerges from the practice and literature surrounding the introduc-
tion of plants to office spaces. Such work was initially led by the
German Bürolandschaft movement (office landscaping), pioneered
by Eberhard and Wolfgang Schnelle, which sought to enrich office
space with plants in the 1950s and used indoor plants and parti-
tions to provide environmental enrichment and privacy (Duffy &
Hutton, 1998; Vischer, 2005). The intention was not only to
provide a more efficient working environment: Bürolandschaft
assumed that plants would make an environment more collabora-
tive and humane (Sundstrom & Sundstrom, 1986).
Studies of living plants in the workplace have indeed suggested
that they can have a range of beneficial influences. In particular, a
number of researchers have investigated the effects of indoor
plants on outcomes relevant to the effectiveness and well-being of
office workers. Those outcomes include psycho-physiological
stress responses, task performance, emotional states, and room
assessments (Adachi, Rohde, & Kendle, 2000; Chang & Chen,
2005; Coleman & Mattson, 1995; Kim & Mattson, 2002; Larsen,
Adams, Deal, Kweon, & Tyler, 1998; Liu, Kim, & Mattson, 2003;
Lohr, Pearson-Mims, & Goodwin, 1996; Shibata & Suzuki, 2001,
2002, 2004). In addition, some studies have investigated the effects
of indoor plants on health and discomfort symptoms related to the
sick building syndrome (Fjeld, 2000; Fjeld et al., 1999; Fjeld,
Veiersted, Sandvik, Riise, & Levy, 1998).
Outside the workplace, there is evidence that exposure to plants
and natural settings (as opposed to urban settings) can improve
positive mood and reduce negative mood (Hartig, Evans, Jamner,
Davis, & Garling, 2003; Ulrich, 1979; Ulrich et al., 1991). Find-
ings also indicate that physiological stress, or arousal (as measured
by heart rate, blood pressure, and/or skin conductance) is often
lower after exposure to plants and nature as compared with urban
settings (Hartig et al., 2003; Laumann, Gärling, & Stormark, 2003;
Ulrich & Simons, 1986; Ulrich et al., 1991). Furthermore, in-
creases in well-being have been shown to coincide with less
mental distress among people living in urban areas interspersed
with green spaces (White, Alcock, Wheeler, & Depledge, 2013). In
addition, exposure to nature has been shown to have the capacity
to improve attention (Berman, Jonides, & Kaplan, 2008; Berto,
2005; Cimprich, 1993; Cimprich & Ronis, 2003; Hartig et al.,
2003; Ottosson & Grahn, 2005; Tennessen & Cimprich, 1995).
An obvious question is why plants and green spaces might have
these beneficial psychosocial benefits. Currently, there are three
classes of explanations for such findings. According to the first,
plants, as living organisms, exert a beneficial influence on the
climate of the working and living environment. In particular,
plants are thought to be healthy because they improve air quality.
In this regard, when introduced in sufficient quantity, indoor
potted plants have been shown to remove most types of air-borne
pollutants arising from either outdoor or indoor sources. This has
been studied within laboratories (Orwell, Wood, Tarran, Torpy, &
Burchett, 2004; Tarran, Orwell, Burchett, Wood, & Torpy, 2002;
Wood, Orwell, Tarran, Torpy, & Burchett, 2002), as well as in
naturally ventilated and air-conditioned office spaces (Tarran,
Torpy, & Burchett, 2007; Wood et al., 2006). Air pollutants, even
at imperceptible levels, can cause “building-related illness” and
symptoms of headache, sore eyes, nose, and throat, or nausea
(Carrer et al., 1999; Mølhave & Krzyzanowski, 2003). Where
indoor plants have been installed, staff well-being is improved
with reduced sick-leave absence (Bergs, 2002; Fjeld, 2000). In
addition, plants can refresh the air by absorbing carbon dioxide
(CO
2
). The importance of this is suggested by studies which show
that student performance declines with increasing CO
2
(Shaugh-
nessy, Haverinen-Shaughnessy, Nevalainen, & Moschandreas,
2006), as does workplace productivity (Seppänen, Fisk, & Lei,
2006). Instructive in this regard is a study by Tarran, Torpy, and
Burchett (2007) which showed that in the presence of plants, CO
2
levels were reduced by about 10% in air-conditioned buildings,
and by about 25% in naturally ventilated buildings. However, as
well as objective changes in air quality, the presence of plants
might also result in a perceived change in air quality. This question
was investigated by Khan, Younis, Riaz and Abbas (2005) in an
academic setting. They found that students who worked in an
environment that had been enriched with plants reported that air
quality had improved. Such data thus suggest that enriching the
workplace with plants should have a positive effect on the (sub-
jective) air quality within the working environment.
The second explanation of plants’ beneficial effects centers on
the evolutionary explanation that a green, planted environment
reflects the natural world and thereby supports human physiology
(Appleton, 1975; Balling & Falk, 1982; Kaplan, Kaplan, & Brown,
1989; Orians, 1980; Orians & Heerwagen, 1992; Ulrich, 1983,
1986). Proponents of attention restoration theory (ART; Kaplan,
1995) argue that natural environments restore people’s capacity for
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2NIEUWENHUIS, KNIGHT, POSTMES, AND HASLAM

directed attention, whereas built environments tend to deplete this
capacity. The idea behind this theory is that the prolonged focus on
a specific stimulus or task results in “directed attention fatigue.”
According to ART, natural environments exert less demand on
directed attention and encourage more effortless brain functions,
thereby allowing the capacity for attention to be restored. Thus,
after an interaction with natural environments, one is able to
perform better on tasks that rely on directed-attention abilities.
According to this view, plants in the workplace should enhance
employees’ directed-attention capacity and therefore enhance their
concentration and productivity levels.
The third class of explanations moves away from physiological
responses and looks more closely at the relational and managerial
consequences of enrichment. The basic idea here is that enrich-
ment of the workspace (with plants or by other means) signals that
attempts are being made to enhance staff well-being and “envi-
ronmental comfort” (Vischer, 2005, p. 102). Enrichment thus
communicates managerial care and attention (a sense that “our
managers are on our side”), which may in turn lead to increased
attention and work engagement among employees (e.g., as argued
by Haslam, 2004; see also Katz & Kahn, 1966; Lewin, 1956). It
also follows that if people are physically, cognitively and emo-
tionally involved in their work there is a reduced risk of disen-
gagement (Kahn, 1990). This in turn is likely to translate into
higher levels of work satisfaction, productivity, and well-being
(Ottosson & Grahn, 2005; Parker, 1992; Tennessen & Cimprich,
1995).
Enrichment can be achieved in multiple ways, including via
indoor plants. Speaking to this possibility, a study by Dravigne,
Waliczek, Lineberger, and Zajicek (2008) showed that individuals
who worked in offices with plants reported that they felt better
about their job and the work they performed. Enriched offices are
also psychologically advantageous because they communicate and
help build a sense of belonging and shared identity (Elsbach, 2003;
Handy, 1990; Haslam & Knight, 2006; Myerson, 2007; Thomp-
son, 2000; Vischer, 2005; Zelinsky, 2006). In short, enriching the
environment with plants should signal managerial care and hence
result in increased engagement, attention and environmental sat-
isfaction. More broadly, this should also result in perceived im-
provement to psychological well-being and productivity in the
workspace.
The Present Research
Although previous work suggests that “greening” an office can
improve productivity and well-being, extant studies have clear
limitations (see also Bringslimark, Hartig, & Patil, 2007). In par-
ticular, the offices in which research has been conducted were
constructed specifically for the purpose of the research and thus
were rather artificial (notable exceptions being field studies by
Fjeld, 2000; Fjeld et al., 1999, 1998; Shoemaker, Randall, Relf, &
Geller, 1992). Moreover, they involved a single individual work-
ing in isolation in an unfamiliar environment without reference to
her or his standard work patterns and without social interaction.
Consequently, although the studies were designed to capture the
essence of office work, their ecological validity was limited.
Further, some research confounded plants with other decorations,
making it difficult to extrapolate the benefits—or otherwise—of a
green office (e.g., Knight & Haslam, 2010b). Finally, previous
studies were short-term, and we cannot establish whether the
reported effects would have continued to produce beneficial ef-
fects for any length of time.
A more persuasive test of the relative merits of lean and green
offices would therefore involve collecting data in more realistic
field contexts, and with plants only. This was the primary goal of
the present research. More specifically, it involved conducting
three experiments to examine the effects of introducing living
plants within a functioning office.
In all the experiments, office design was manipulated across two
conditions.
1
In a lean condition, minimalist office space was
intended to focus employees’ attention solely on the work at hand.
In the green condition, employees fulfilled the same work in an
office that incorporated plants. Study 1 was a longitudinal field
experiment that examined the short-term effects of office design
on workers’ environmental satisfaction (perceived air quality, per-
ceived concentration, workplace satisfaction and perceived pro-
ductivity). Study 2 examined the long-term effects of office design
on the same dependent variables, except focusing on objective
rather than subjective productivity levels. Study 3 examined the
effects of office design on levels of productivity.
Study 1
Our first experiment was conducted at the offices of an inter-
national consultancy business in central London. The floor where
the study took place had an open plan office design and employees
were mainly involved with the implementation and management of
large projects which also involved client meetings outside the
office. As a result, there were more employees nominally based in
the building than there were places at which they could work. The
desks were taken on a first-come,-first-served—or hot-desking—
basis (Barnatt, 1995; Millward, Haslam, & Postmes, 2007). The
employees themselves were highly paid consultants. The study
took place in one space, which was deliberately designed to be
lean. Different areas within this space were assigned to one of two
conditions. In one, the space remained lean; in the other the office
was landscaped with plants. The main goal of the study was to
examine whether this enrichment of office space had any impact
on employees’ well-being and productivity.
Method
Design. A2⫻2 mixed design was employed in the study.
Office design was manipulated as a between-subjects variable
(lean, green). Both office designs were located on the same floor
in open plan space and were separated from each other by archi-
tectural borders (e.g., cabinets and meeting rooms). In the lean
space participants had no plants in direct sight of their workstation;
in the green space plants were introduced into the office such that
1
In Study 1 and Study 2, the intention was to make a comparison
between three conditions: lean versus green versus empowered (as in
Knight & Haslam, 2010b). In the empowered condition the procedure was
the same as in the green condition with the exception that employees had
say in the design of their office space (in comparison with the green
condition were a designer developed the design). Because no significant
differences were found between the green and the empowered condition
(and empowerment had no significant additional value to the plants) both
conditions were combined into one condition.
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3
GREEN VS. LEAN OFFICE SPACE

each employee had at least two in direct view. Study phase was a
within-subjects variable, with measures administered both before
the introduction of the plants (T1) and 3 weeks after their intro-
duction (T2).
2
Participants and procedure. The study was conducted on
one floor of a large office building in central London. The floor
was approximately 4875 m
2
. All employees on the floor were
invited via email to take part in the longitudinal study (N⫽250).
The study was presented as an investigation into employees’
preferences for different kinds of office designs. One hundred and
66 employees (66% response rate) participated in the first mea-
surement at T1. Eight weeks later—in the green office—an interior
designer installed an array of green, large-leafed plants (average
height 90 cm) around the workfloor. There was an average of three
plants per five desks (at least two plants in direct sight of each
desk). In the lean office no changes to the working environment
were made. At T2, 3 weeks after the plants were installed, all
employees received a follow-up e-mail inviting them to complete
a second questionnaire. One-hundred and 48 employees completed
this, representing a 59% response rate. In order to match question-
naires to the right person, participants were asked to generate a
unique code at the beginning of their responses based on their
mother’s maiden name and their date of birth.
Allocation of space and participants to condition. At the start
of the study two spaces on the floor were identified which were
separated by architectural borders (e.g., cabinets and meeting
rooms). The two spaces were randomly assigned to an office
design (lean or green). Consequently, the space in which employ-
ees were working at the start of the study (i.e., the completion of
the first questionnaire) defined the condition of which they were a
part. Due to the use of hot-desking in the office, employees could
in principle work wherever they liked on the floor. However, in
practice, most employees tended to work in the same area every
day and were therefore working in one type of office design (either
lean or green) throughout the study. To verify where they were
working, each wave of questionnaires included a map of the
workfloor. Participants indicated (a) their main working area(s),
and (b) the area(s) in which they had been working on each day of
the previous week. Participants who indicated that their main
working area was outside the office (42 at T1 and 51 at T2) were
excluded from the sample (remaining Ns: T1 ⫽124, T2 ⫽97). In
addition, five participants who indicated that they had worked in
both types of office designs could not be assigned to a specific
condition and were also excluded from the sample.
The final sample. After applying the exclusion criteria, the
total sample consisted of 153 participants (see Table 1 for a
division per condition). The participants in this sample completed
either one (T1 or T2) or two waves (T1 and T2) of the study. After
listwise deletion, the final sample consisted of 67 participants who
participated in both waves of the study. The final sample included
39 men and 28 women ranging in age from 23 to 53 years (M⫽
30.02, SD ⫽6.41). Analyses revealed no differences (on any
measure) between the full samples at each time point and the final
sample was retained for analysis.
Measures. Participants completed a questionnaire that in-
cluded eight questions assessing four key constructs. In each case
participants responded using a 7-point scale ranging from 1 (com-
pletely disagree)to7(completely agree). Workplace satisfaction
was measured with four items (␣
T1
⫽.74; ␣
T2
⫽.75; e.g., “I feel
at home in the office,” after Knight & Haslam, 2010b). Concen-
tration was measured with one item (i.e., “In the office I am able
to concentrate well,” after Knight & Haslam, 2010b), as was air
quality (i.e., “The office has poor air quality;” reverse-coded, after
Knight & Haslam, 2010b). Subjective productivity was measured
with two items (␣
T1
⫽.76; ␣
T2
⫽.75; e.g., “I am happy with my
performance lately,” after Knight & Haslam, 2010b). In addition,
demographic statistics were collected on age, gender, and number
of work years for the company.
Results
Analytic strategy. Scores on all measures were subjected to a
two-way analysis of variance (ANOVA) with office design (lean,
green) as a between-subjects factor and study phase as a within-
subject factor (T1, T2). This was followed up by simple effects
analysis. Relevant means and statistics are presented in Table 2.
Demographics and premeasures. First, we tested whether
there were any differences across the two office designs (lean vs.
green) with regard to demographics of the participants. No signif-
icant differences were found on gender, ␹
2
(1) ⫽2.60, p⫽.11 or
on work years for the company, t(65) ⫽1.56, p⫽.125. However,
a difference was found for age, t(65) ⫽2.22, p⫽.031, as
participants in the lean condition where younger (M⫽28.13,
SD ⫽5.31) than participants in the green condition (M⫽31.31,
SD ⫽5.92). Upon further inspection, age was not significantly
correlated with any of the dependent variables of interest (at T1
and T2; rs⬍.12, ps⬎.30) and therefore not included in the
analysis of variance as a covariate.
Second, we tested if there were any differences across the two
office designs in the premeasures. No significant differences were
found on any of the dependent variables, ts(65) ⬍1.65, ps⬎.10.
Workplace satisfaction. Analysis of responses on this mea-
sure revealed a main effect for study phase, F(1, 65) ⫽23.0, p⬍
.001, ␩p
2⫽.26, 90% CI [.12, .39]. On average, participants became
more satisfied with their working environment over time (M
T1
⫽
3.77, M
T2
⫽4.39). This effect was not qualified by office design,
F(1, 65) ⫽1.44, p⫽.234.
Concentration. Analysis of participants’ subjective concen-
tration levels revealed a significant interaction between office
design and study phase, F(1, 65) ⫽8.59, p⫽.005, ␩p
2⫽.12, 90%
CI [.02, .24]. Simple effects showed that in the green condition
participants perceived there to be an increase in their ability to
2
A third measure was taken 2.5 months after the introduction of the
plants (T3) but the sample size for a 2 ⫻3 design was too low (N⫽48)
to allow us to conduct the desired statistical analysis. Importantly, how-
ever, comparison between T2 and T3 on all dependent variables showed no
significant differences between the two time-points.
Table 1
Sample Sizes per Wave and Condition for Study 1
Condition T1 T2 Total sample (completed
either T1, T2 or both) Final sample (after
listwise deletion)
Lean 54 52 71 34
Green 70 45 82 33
Total 124 97 153 67
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4NIEUWENHUIS, KNIGHT, POSTMES, AND HASLAM

concentrate after the introduction of plants, F(1, 65) ⫽11.11, p⫽
.001, 95% CI [.25, .99], ␩p
2⫽.15, 90% CI [.04, .27], whereas in the
lean office there was no difference over time, F(1, 65) ⫽.63, p⫽
.431, 95% CI [⫺.51, .22].
Air quality. Analysis of perceived air quality revealed a sig-
nificant interaction between office design and study phase, F(1,
65) ⫽4.21, p⫽.044, ␩p
2⫽.06, 90% CI [.00, .17]. In the green
office participants perceived an increase in air quality after the
introduction of the plants, F(1, 65) ⫽6.32, p⫽.014, 95% CI [.09,
.77], ␩p
2⫽.09, 90% CI [.01, .21], but not in the lean office, F(1,
65) ⫽.14, p⫽.711, 95% CI [⫺.40, .27].
Subjective productivity. Analysis of participants’ subjective
ratings of their own productivity revealed a significant interaction
effect between type of office design and study phase, F(1, 57) ⫽
6.83, p⫽.011, ␩p
2⫽.11, 90% CI [.01, .24]. In the green office
there was an increase in subjective productivity after the introduc-
tion of the plants, F(1, 57) ⫽3.81, p⫽.056, 95% CI [⫺.01, .54],
␩p
2⫽.06, 90% CI [.00, .18], whereas in the lean condition there
was a decrease in subjective productivity, F(1, 57) ⫽3.04, p⫽
.086, 95% CI [⫺.51, .03], ␩p
2⫽.05, 90% CI [.00, .16], although
both simple effects did not reach the critical significance level.
Multilevel analysis. Because attrition and missing data meant
that the final sample in Study 1 was quite small, an additional
multilevel analysis was conducted. In this regard, longitudinal data
can be seen as multilevel data, with repeated measures nested
within individuals (Hox, 2002). An advantage of multilevel anal-
ysis of longitudinal data is the ability to handle missing data, as
multilevel regression models do not assume equal numbers of
observations (unlike ANOVA; Snijders, 1996). That is, it is not a
problem if the available measurements are not the same for all
individuals. The multilevel analysis was based on the total sample
of N⫽153 (compared with N⫽67 for the ANOVAs; see Table
1). The pattern of results for the multilevel analysis was identical
to the ANOVA for all dependent variables; that is, a significant
main effect of study phase was found for workplace satisfaction,
and significant interaction effects (Study Phase ⫻Office Design)
were found for concentration and perceived air quality. All signif-
icant effects were in the same direction as in the ANOVAs, which
are reported here for reasons of interpretability. Further details
regarding this analysis are available as supplemental data.
Discussion
This experiment compared the productivity and well-being of
employees in two office environments: one where the office re-
mained lean, the other where the office was landscaped with
plants. Relative to the lean condition, participants in the green
office reported improved air quality, enhanced levels of concen-
tration, and showed improved productivity 3 weeks after the in-
troduction of plants on the workfloor. Unexpectedly, however,
satisfaction with the work environment improved in both office
types. These findings emerged from multivariate analyses but were
also confirmed by multilevel analysis that was conducted with a
larger sample (i.e., the total sample; see Table 1).
The reason for the improvement of workplace satisfaction in
both conditions is likely to be related to a limitation of Study 1.
Both green and lean conditions were located on the same floor in
an open plan office and although participants in the lean space (the
control condition) could not see any plants from their workstation,
it is possible that they might have been influenced by the presence
of the plants on the floor as they walked past them on their way to
their desks. We therefore sought to reduce the potential permea-
bility between the different conditions in Study 2. In addition, we
included a process measure of disengagement as a potential con-
tributing factor to well-being and performance, for reasons ex-
plained in more detail below. This study also aimed to enhance our
assessment of productivity by using a direct measure of employee
performance, rather than recording workers’ perceptions of their
own productivity (Peters & Waterman, 2004). Finally, this next
study also measured long-term effects of the presence of plants on
the workfloor.
Study 2
Study 2 was conducted within the service center of a large
health insurance company in Zwolle, The Netherlands. Employees
were mainly involved in giving insurance and declaration advice to
clients over the telephone. We used a discrete control condition to
address the limitation of Study 1. The study took place in two
open-plan offices located on different floors within the same
building. In this way—and unlike Study 1—employees in the lean
condition were unlikely to be influenced by the presence of plants
Table 2
Study 1: Employees’ Perceptions of Satisfaction, Concentration, Air Quality, and Productivity in Lean and Green
Office Environments
Phase Effect
T1 T2 Condition ⫻phase
F(1, 65)
T1 vs. T2
Measure Condition M(SD) 95% CI M(SD) 95% CI F(1, 65) ␩p
2
Workplace satisfaction L 3.77 (.80) [3.41, 4.14] 4.24 (.77) [3.93, 4.54] 1.44 2.56
ⴱ
.04
G 3.77 (1.29) [3.39, 4.14] 4.54 (.99) [4.24, 4.85] 4.21
ⴱⴱⴱ
.06
Concentration L 4.62 (1.33) [4.16, 5.07] 4.38 (1.39) [3.91, 4.86] 9.15
ⴱⴱ
.79 .01
G 3.90 (1.36) [3.44, 4.37] 4.79 (1.36) [4.31, 5.27] 3.33
ⴱⴱ
.05
Air quality L 4.29 (1.19) [3.79, 4.79] 4.21 (1.20) [3.67, 4.73] 4.21
ⴱ
.37 .01
G 3.64 (1.71) [3.13, 4.14] 4.24 (1.82) [3.71, 4.77] 2.51
ⴱ
.04
Productivity L 4.95 (.93) [4.59, 5.31] 4.61 (.85) [4.25, 4.97] 7.17
ⴱ
1.74
†
.03
G 4.63 (1.07) [4.27, 5.00] 5.02 (1.14) [4.64, 5.39] 1.95
†
.03
Note. L⫽lean condition; G ⫽green condition. T1 took place 8 weeks before the introduction of the plants in the green condition and T2 3 weeks after
the plants.
†
p⬍.10.
ⴱ
p⬍.05.
ⴱⴱ
p⬍.01.
ⴱⴱⴱ
p⬍.001.
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5
GREEN VS. LEAN OFFICE SPACE

in the green condition. In contrast to Study 1, participants were less
well paid, had less autonomy, and operated under conditions of
greater job surveillance. Nevertheless, the company’s clear and
monitored job stratification allowed for straightforward compari-
son between office workers of different status. The main goal of
the study was to examine whether enrichment of office space had
any impact on employees’ satisfaction with the work environment,
concentration levels, perceived air quality, and objective produc-
tivity levels over the short-term (after 2 weeks) and the long-term
(after 3.5 months).
Objective productivity measures were available from the
company, which continuously monitored the performance of its
agents. Unlike almost all other types of office work, call center
agents have their work routinely timed. The key productivity
measure is seen to be average handling time (AHT, i.e., the
average duration of a call). This measure has three components:
the duration of each call (talk-time); the time the agent places
the caller on hold (hold-time); and the time between successive
calls that is needed to report the necessary details within the
system (after call work, ACW). Office work of service center
agents requires concentration, verbal communication, logical
thinking under time pressure, visual attention, and the use of
computer software. The rationale behind the AHT measure is
that when a call center agent concentrates better or becomes
more motivated, they will increase their performance which is
likely to result in a shorter AHT. Limitations of the measure are
that shorter AHT can clearly arise from other factors and that it
is a measure of efficiency rather than quality.
We also collected additional data with a view to examining
mechanisms that, in the event of our main hypotheses being
confirmed, might account for the effects of plants on the work-
floor. More specifically, we examined whether disengagement
with the office environment could be a potential mediator for
outcomes of environmental satisfaction (i.e., perceived air qual-
ity, perceived concentration, and workplace satisfaction).
3
This
focus on disengagement speaks to the relational and managerial
consequences of plants, as discussed in the beginning of the
article. In short, enrichment of the office would signal mana-
gerial care and attention, which should stimulate employees to
become more physically, cognitively, and emotionally engaged
in their work. This will reduce the risk of disengagement (as
measured by feelings of apathy, boredom, distractedness and
tiredness) within the office. In turn, reduced disengagement
should result in enhanced concentration levels and a greater
sense of belonging within the workplace (i.e., workplace satis-
faction).
With regard to perceived air quality, the mediation can work in
two directions. First, feelings of disengagement within the office
space may result in a perception of poor air quality. That is,
employees may partly attribute feelings of apathy, tiredness, or
lack of attention (all indicators of disengagement) to the poor air
quality in the office. The enriching presence of plants may reduce
feelings of disengagement, resulting in a perceived enhancement
of the air quality within the office. Second, the presence of plants
might have a direct (physiological) effect on air quality, which in
turn enhances attention and focus thereby reducing (physical)
disengagement. Importantly, the use of a cross-lagged panel model
allowed for simultaneous examination of both these pathways.
Method
Design. A2⫻3 mixed design was employed in the study.
Office design was manipulated as a between-subjects variable
(lean, green). The office designs were located on different floors
within the same building in two identical open-plan spaces. In the
lean space participants had no plants in their office; in the green
space plants were introduced into the office such that each em-
ployee had at least one plant in direct view. Study phase was a
within-subjects variable, with measures administered before the
introduction of the plants (T1), 2 weeks after their introduction
(T2), and 3.5 months after their introduction (T3).
Participants and procedure. The study was conducted in two
open-plan offices located on different floors of a large office
building. Both floors were approximately 360 m
2
. All employees
in both offices were invited to take part in the longitudinal study
(N⫽191). They received paper-and-pencil questionnaires from
their manager. One-hundred and 43 employees returned completed
questionnaires via a collection box (75% response rate). Five
weeks later—in the green office—an interior designer installed an
array of green, large-leafed plants (average height 90 cm) around
the workfloor. There was an average of one plant per three desks.
In the lean office no changes to the working environment were
made. At T2, 2 weeks after the plants were installed in the green
space, all employees were invited to complete a second paper-and-
pencil questionnaire. One-hundred and 34 employees completed
this, representing a 70% response rate. At T3, 3.5 months after the
plants were introduced, all employees received a third question-
naire, which was completed by 111 people, representing a 58%
response rate. In order to match questionnaires to the right person,
all employees received a unique code at T1 and these codes were
used throughout the study.
The total sample consisted of 172 participants (see Table 3 for
numbers per condition). Participants in this sample completed
either one, two, or three waves of the study. After listwise deletion,
the final sample consisted of 81 participants who completed all
three waves of the study (15 men and 66 women), ranging in age
from 21 to 59 years (M⫽34.86, SD ⫽10.02). Analyses revealed
no differences (on any measure) between the full samples at each
time point and the final sample that was retained for analysis.
Besides the questionnaire data, we also used the company’s own
measures of productivity to assess how the presence of plants
affected performance. Productivity measures assessed how quickly
an employee handled a call (time in minutes). For 48 employees
who were working in the lean (N⫽26) and green (N⫽22)
offices, productivity measures were available across the three
time-points.
Measures. The questionnaire that participants completed in-
cluded 14 questions assessing four key constructs. Participants
responded on a 7-point scale, ranging from 1 (completely disagree)
to7(completely agree). Workplace satisfaction was measured with
four items (␣
T1
⫽.88; ␣
T2
⫽.84; ␣
T3
⫽.87; e.g., “I feel at home
in the office,” after Knight & Haslam, 2010b). Concentration was
measured with one item, that is, “In the office I am able to
concentrate well,” after Knight & Haslam, 2010b). Air quality was
3
These data were not included in our initial analyses of results, but were
conducted post hoc in light of comments from reviewers.
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6NIEUWENHUIS, KNIGHT, POSTMES, AND HASLAM

measured with three items (␣
T1
⫽.70; ␣
T2
⫽.78; ␣
T3
⫽.84; e.g.,
“The air in the office is dry;” reverse-coded, after Knight &
Haslam, 2010b). Disengagement was measured with six items
(␣
T1
⫽.83; ␣
T2
⫽.83; ␣
T3
⫽.84). Participants were asked to what
extent they had particular symptoms (i.e., “feeling apathetic,”
“feeling bored,” “being easily distracted,” “not being challenged,”
“feeling worried,” and “feeling tired”) in the office during the
previous week and were asked to provide responses on a 5-point
scale, ranging from 1 (not at all)to5(very often). Additional
questions asked participants to provide demographic details—
specifically, their age, gender, and number of work years at the
company.
Productivity measures were provided by the company, which
used AHT as the main indicator of productivity. AHT is the total
time (measured in minutes) employees spend on the phone with
clients, where a shorter handling time is taken to indicate greater
productivity as the employee will be able to handle more clients
per day. AHTs (the average for 2 weeks) were compared between
the lean and green offices across the three time-points.
Results
Analytic strategy. Scores on all measures were subjected to
two-way analysis of variance (ANOVA) with office design (lean,
green) as a between-subjects factor and study phase as a within-
subjects factor (T1, T2, T3). This was followed up by simple
contrast analysis to test for the overall effects of plants on the
workfloor (T1 vs. T2, T3) and to establish whether the changes
hold up in the long term (T2 vs. T3). Relevant means and statistics
are presented in Table 4. To test for possible mechanisms that
underlie the positive effects of green workspaces a cross-lagged
panel model (CLPM) for longitudinal data, based on a structural
equation modeling (SEM) approach, was used. The advantages of
the CLPM are that it allows time for causes to have their effects,
allows for stronger inference about the direction of causation in
comparison to models using cross-sectional data, and reduces the
probable parameter bias that arises when using cross-sectional data
(Selig & Preacher, 2009).
Demographics and premeasures. First, we tested whether
there were any differences across the two office designs (lean vs.
green) with regard to demographics of the participants. No signif-
icant differences were found on gender, ␹
2
(1) ⫽.001, p⫽.979,
age, t(79) ⫽.58, p⫽.565, or on work years for the company,
t(79) ⫽.02, p⫽.981. Second, we tested to see whether there were
any differences across the two floors in the premeasures. No
significant differences were found on any of the dependent vari-
ables, ts(158) ⬍1.20, ps⬎.23.
Workplace satisfaction. Analysis of participants’ workplace
satisfaction revealed a significant interaction between office de-
Table 3
Sample Sizes per Wave and Condition for Study 2
Condition T1 T2 T3
Total sample (completed
either one, two or three
waves of the study) Final sample (after
listwise deletion)
Lean 33 36 31 47 21
Green 110 98 80 125 60
Total 143 134 111 172 81
Table 4
Study 2: Employees’ Perceptions of Satisfaction, Concentration, and Air Quality and Objective Productivity in Lean and Green Office Environments
Phase Effects
T1 T2 T3 Condition ⫻phase
F(2, 158)
T1 vs. T2, T3 T2 vs. T3
Measure Condition M(SD) 95% CI M(SD) 95% CI M(SD) 95% CI F(1, 79) ␩p
2F(1, 79) ␩p
2
Workplace satisfaction L 5.10 (1.20) [4.52, 5.69] 4.73 (1.02) [4.35, 5.11] 4.93 (1.06) [4.48, 5.37] 7.40
ⴱⴱⴱ
1.30 .02 1.44 .02
G 4.91 (1.18) [4.61, 5.20] 5.52 (.70) [5.35, 5.70] 5.40 (.83) [5.18, 5.55] 22.18
ⴱⴱⴱ
.22 2.10 .03
Concentration L 4.88 (1.58) [4.10, 5.65] 4.81 (1.51) [4.14, 5.48] 5.10 (1.50) [4.41, 5.83] .93 .08 .00 1.17 .01
G 4.52 (1.56) [4.14, 4.91] 4.97 (1.30) [4.64, 5.30] 4.92 (1.41) [4.56, 5.27] 6.35
ⴱ
.07 .10 .00
Air quality L 4.18 (1.71) [3.44, 4.93] 3.78 (1.66) [3.04, 4.51] 4.25 (1.39) [3.55, 4.95] 3.67
ⴱ
.31 .00 2.16 .03
G 3.68 (1.43) [3.31, 4.05] 4.29 (1.43) [3.93, 4.65] 4.21 (1.41) [3.86, 4.55] 13.91
ⴱⴱⴱ
.15 .29 .00
Objective productivity
a
L 7.65 (1.42) [6.99, 8.29] 7.28 (1.12) [6.90, 7.67] 7.67 (.98) [7.30, 8.05] .19
b
.31 .01 4.84
ⴱ
.10
G 7.53 (.88) [6.83, 8.24] 6.97 (.76) [6.55, 7.38] 7.53 (.93) [7.13, 7.95] .83 .02 9.12
ⴱⴱ
.17
Note. L⫽lean condition; G ⫽green condition. T1 took place 5 weeks before the introduction of the plants, T2 2 weeks after the plants, and T3 3.5 months after the plants.
a
Time in minutes, where shorter time indicates larger productivity.
b
Fvalue based on dfs (2, 92).
ⴱ
p⬍.05.
ⴱⴱ
p⬍.01.
ⴱⴱⴱ
p⬍.001.
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7
GREEN VS. LEAN OFFICE SPACE

sign and study phase, F(2, 158) ⫽7.40, p⫽.001, ␩p
2⫽.09, 90%
CI [.02, .15]. Simple contrasts showed that in the green condition
participants became significantly more satisfied with their work
environment after the introduction of the plants (T1 vs. T2, T3),
F(1, 79) ⫽22.18, p⬍.001, 95% CI [.26, .65], ␩p
2⫽.22, 90% CI
[.10, .34]. In addition, this effect did not significantly decrease in
the long term (T2 vs. T3), F(1, 79) ⫽2.10, p⫽.151, 95% CI
[⫺.20, .03]. In the lean condition there was no difference over time
(T1 vs. T2, T3), F(1, 79) ⫽1.30, p⫽.256, 95% CI [⫺.61, .16].
Concentration. Analysis of responses on this measure re-
vealed a nonsignificant interaction between office design and
study phase, F(2, 158) ⫽.93, p⫽.40.
Air quality. Analysis of perceived air quality revealed a sig-
nificant interaction between office design and study phase, F(2,
158) ⫽3.67, p⫽.028, ␩p
2⫽.05, 90% CI [.00, .10]. Simple
contrasts showed that participants in the green condition perceived
an increase in air quality after the introduction of the plants, (T1
vs. T2, T3), F(1, 79) ⫽13.91, p⬍.001, 95% CI [.22, .71], ␩p
2⫽
.15, 90% CI [.05, .27]. In addition, this effect did not significantly
decrease in the long term (T2 vs. T3), F(1, 79) ⫽.29, p⫽.593,
95% CI [⫺.28, .16]. In the lean condition there was no difference
over time (T1 vs. T2, T3), F(1, 79) ⫽.31, p⫽.575, 95% CI
[⫺.64, .36].
Productivity. Analysis of objective measures of productivity
(time in minutes, where shorter time means more productive)
revealed a main effect for study phase, F(2, 92) ⫽3.93, p⫽.023,
␩p
2⫽.08, 90% CI [.01, .16]. However, the simple contrasts for
study phase showed that the change in productivity was not sig-
nificant over time (T1 vs. T2, T3), F(1, 46) ⫽1.11, p⫽.298, 95%
CI [⫺.17, .53], although there was a difference between the
postmeasures (T2 vs. T3), F(1, 46) ⫽13.81, p⫽.001, 95% CI
[⫺.53, ⫺.16], ␩p
2⫽.23, 90% CI [.07, .38], as participants showed
a decrease in productivity between T2 and T3. As this change only
happened 3.5 months after the introduction of the plants and in
both types of office design, it is unlikely that this is related to the
study. The main effect of study phase was not qualified by office
design, F(2, 92) ⫽.19, p⫽.829.
Multilevel analyses. As the final sample of Study 2 was
relatively small due to attrition, an additional multilevel analysis
was conducted. The multilevel analysis was based on the total
sample of N⫽172 (compared with N⫽81 for the ANOVAs; see
Table 3). As in Study 1, the pattern of results was similar for both
analyses on all dependent variables, that is significant interaction
effects (Study Phase ⫻Office Design) in the same direction were
found for workplace satisfaction and perceived air quality, whereas
no significant interaction was found for concentration. Further
details regarding this analysis are available as supplemental data.
For reasons of interpretability, it was chosen to report the ANOVA
results.
Cross-lagged panel model (CLPM). AMOS software was
used to test a CLPM for longitudinal data, based on a structural
model with measured variables. This type of model allows for
simultaneous examination of longitudinal influences of one con-
struct on another, and vice versa, while also controlling for con-
temporaneous associations between constructs, and the stability of
each construct over time. A separate model was tested for each of
the dependent variables (i.e., workplace satisfaction, concentra-
tion, and perceived air quality). Figure 1 provides a generic illus-
tration of these models. The model specified condition (0 ⫽lean;
1⫽green) as a predictor of disengagement (M
t1
⫽2.23, SD
t1
⫽
.99; M
t2
⫽2.18, SD
t2
⫽.97; M
t3
⫽2.16, SD
t3
⫽.91) and an
outcome variable (Y) at Time 2 to examine possible routes of
mediation. The relations between disengagement and an outcome
variable were specified as cross-lagged effects, which indicates the
prospective effect of one variable on the other (e.g., the effect of
disengagement at T1 on an outcome variable at T2), after control-
ling for their stability across time (e.g., the effect of an outcome
variable at T1 on an outcome variable at T2). We accounted for
variance due to specific measurement occasions by correlating the
residual variances within waves (e.g., the residual of disengage-
ment at T2 and the residual of an outcome variable at T2; cf. Cole
& Maxwell, 2003).
To determine the fit of the proposed model, we report the
chi-square goodness of fit test, the comparative fit index (CFI) and
the root mean squared error of approximation (RMSEA). A small,
nonsignificant chi-square value indicates optimal fit, whereas a
large, significant chi-square indicates poor fit. Values higher than
.95 for the CFI indicate that the tested model provides an adequate
fit to the data, as does an RMSEA value lower than .06 (see Hu &
Bentler, 1999). The fit values for each of the outcome variables
were satisfactory (see Table 5).
Model workplace satisfaction. Condition had a significant
direct effect on disengagement at Time 2 (␤⫽⫺.15, p⫽.040)
and on workplace satisfaction at Time 2 (␤⫽.37, p⬍.001; see
Figure 2). This indicates that, compared with the lean offices,
employees in the green offices became less disengaged and more
satisfied with their workplace after the introduction of the plants.
The cross-lagged effects showed that disengagement prospectively
predicted workplace satisfaction (T1 to T2, ␤⫽⫺.19, p⫽.025;
T2 to T3, ␤⫽⫺.24, p⫽.019) whereas workplace satisfaction did
Disengagement
(T1)
Y
(T1)
Condition
(0 = lean; 1 = green)
Y
(T2)
Y
(T3)
Disengagement
(T3)
Disengagement
(T2)
d1
d2
d3
d4
Figure 1. Cross-lagged regression model of the relations between disengagement and an outcome variable (Y).
Condition is added as a predictor of both disengagement and an outcome variable (Y) at Time 2 to examine
possible routes of mediation. Residual variances (i.e., disturbances) are denoted from d1 to d4.
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8NIEUWENHUIS, KNIGHT, POSTMES, AND HASLAM

not prospectively predict disengagement (T1 to T2, ␤⫽⫺.03, ns;
T2 to T3, ␤⫽.02, ns). The cross-lagged effects indicate that lower
levels of disengagement made employees more satisfied with their
workplace.
In sum, the model suggests that it is appropriate to regard
disengagement as a mediator of the relationship between condition
and workplace satisfaction (rather than examining workplace sat-
isfaction as a mediator between condition and disengagement).
That is, working in a green office (compared with a lean office)
tends to decrease employees’ levels of disengagement which in
turn has a positive effect on their workplace satisfaction.
Model concentration. As with the previous model, condition
had a direct effect on disengagement at T2 (␤⫽⫺.16, p⫽.026),
indicating that participants in the green workspace reported less
disengagement after the introduction of plants than participants in
the lean condition (see Figure 3). However, no direct effect of
condition was found on concentration at T2 (␤⫽.04, ns; which is
in line with the reported nonsignificant interaction for the ANOVA
on concentration). The cross-lagged effects for disengagement on
concentration were significant between T2 and T3 (␤⫽⫺.19, p⫽
.030), but not between T1 and T2 (␤⫽⫺.06, ns). Similarly, the
cross-lagged effects for concentration on disengagement were sig-
nificant between T2 and T3 (␤⫽⫺.16, p⫽.040), but not between
T1 and T2 (␤⫽⫺.12, p⫽.114). Although condition had no
significant direct effect on concentration at T2, results suggest that
condition influences concentration (at T3) indirectly via disen-
gagement (at T2). Accordingly, the model suggests that disengage-
ment mediates the relationship between condition and concentra-
tion (rather than concentration being a mediator between condition
and disengagement). In other words, working in a green office
(rather than a lean office) decreases employees’ levels of disen-
gagement which in turn has a positive effect on their concentration.
Model of perceived air quality. Condition had a significant
effect on disengagement at T2 (␤⫽⫺.16, p⫽.029) and on
perceived air quality at T2 (␤⫽.18, p⫽.020; see Figure 4). This
indicates that, compared to the lean offices, employees in the green
offices became less disengaged and perceived the air quality to be
improved after the introduction of the plants. As with the model
predicting workplace satisfaction, the cross-lagged effects of the
current model showed that disengagement prospectively predicted
perceived air quality (T1 to T2, ␤⫽⫺.17, p⫽.030; T2 to T3,
␤⫽⫺.17, p⫽.050) whereas perceived air quality did not
prospectively predict disengagement (T1 to T2, ␤⫽⫺.11, p⫽
.144; T2 to T3, ␤⫽.03, ns). These cross-lagged effects indicate
that lower levels of disengagement lead employees to perceive air
quality to be better. In sum, these results suggest that it is appro-
priate to see disengagement as a mediator of the relationship
between condition and air quality (rather than seeing air quality as
a mediator between condition and disengagement). That is, work-
ing in a green office (rather than a lean one) leads to a reduction
in levels of disengagement which in turn has a positive effect on
perceived air quality.
Discussion
Study 2 extended the findings of Study 1 by focusing on the
long-term effects of the presence of plants in the workspace. In line
with results from Study 1, green office space was associated with
enhanced workplace satisfaction and an increase in perceived air
quality in the short-term (2 weeks) and the long-term (3.5 months).
In contrast, however, there were no significant changes over either
time period in the lean condition. Reported concentration levels
seemed to increase within the green condition (see Table 4),
although we did not find that concentration increased relative to
the lean condition (i.e., there was no significant interaction effect).
Indeed, the multilevel analyses (which was conducted among a
larger sample, i.e., the total sample; see Table 3) on this measure
did not show a significant increase of concentration in the green
condition either. Importantly, however, the multilevel analysis
found exactly the same pattern of results as the multivariate
analyses for measures of workplace satisfaction and perceived air
quality.
In this study, we also conducted analyses to explore possible
mechanisms that might account for the impact that plants have in
the workplace. Results suggested that a green office leads to more
engagement among employees, which in turn has a positive impact
on their satisfaction with the workplace, their concentration, and
their perceptions of air quality.
Table 5
Model Fit for Each of the Outcome Variables
Outcome variable ␹
2
df p CFI RMSEA
Workplace satisfaction 8.04 6 .24 .99 .066
Concentration 6.56 6 .36 .99 .034
Air quality 5.51 6 .48 1.00 .000
Note. CFI ⫽comparative fit index; RMSEA ⫽root mean square error of
approximation.
.60***
-.15*
-.19*
.37***
-.24*
.50***
.74***
.34**
.02
-.03
Disengagement
(T1)
Workplace
satisfaction (T1)
Condition
(0 = lean; 1 = green)
Workplace
satisfaction (T2)
Workplace
satisfaction (T3)
Disengagement
(T3)
Disengagement
(T2)
Figure 2. Study 2: Cross-lagged regression model of workplace satisfaction. Standardized parameters are
reported.
ⴱ
p⬍.05.
ⴱⴱ
p⬍.01.
ⴱⴱⴱ
p⬍.001.
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9
GREEN VS. LEAN OFFICE SPACE

However, no effects of office design were found on our “objec-
tive” measure of productivity. Interpreting this null effect is com-
plicated by the fact that time on a call (AHT) is an ambiguous
performance measure. Although it may be better for operatives to
deal with calls quickly in some cases, in the present case of
operatives taking calls concerning health care insurance it is en-
tirely possible that—especially from a customer’s point of view—
those who spend longer on calls are delivering superior service.
Thus, AHT addresses the first two problems of performance mea-
surement (accuracy and objectivity) but not necessarily the third
(meaningfulness). Accordingly it is a moot question whether this is
a good measure of productivity at all (Baldry & Hallier, 2010;
Dixon, 2009; Peters & Waterman, 2004; Vischer, 2005). To ad-
dress this issue of measuring performance on office-based tasks in
a more appropriate fashion, we conducted a third study.
Study 3
In our third field experiment we revisited the concept of
office space productivity using metrics specifically developed
to measure office space productivity (Knight & Haslam,
2010b). These methods were adopted for two main reasons.
First, the measures of attention to detail, information processing
and information management aligned closely with tasks ex-
pected of auditors. Second, as noted by Knight and Haslam
(2010b), there is a dearth of viable alternative productivity
measures. The study was conducted among employees of a
large consultancy organization in London and took place within
their own working environment. Participants were randomly
assigned to one of two experimental conditions (lean or green
office design) where they performed two standard productivity
tasks in order to gauge the impact of office design on productivity.
Method
Participants. Thirty-three employees participated in the ex-
periment (16 men, 17 women), ranging in age from 22 to 33 years
(M⫽28.0, SD ⫽3.23), with 17 participating in the lean condition
and 16 in the green condition. Potential participants were recruited
from the same floor where the experiment took place (62% of the
sample), as well as on other floors within the same building where
similar work was performed (38% of the sample). Participation
was voluntary and unpaid.
Materials and procedure. The field experiment was con-
ducted in an open plan area where two different office designs
were implemented (lean, green). In every trial (three in total),
participants congregated in a meeting room at the end of the
working day (6 p.m.). The experimenters explained to the partic-
ipants that they would take part in a study examining performance
on analytical, processing, and intellectual tasks. Participants were
also told that they needed to complete the tasks as quickly and
accurately as possible. After the instructions participants were
randomly assigned to an experimental condition (lean or green)
and to a workstation.
In both experimental conditions the office space consisted of
rows of three to five workstations, separated by vertical dividers
(height 45 cm). The workstations consisted of a rectangular desk
(220 cm ⫻80 cm) and a comfortable office chair on castors. Each
desk housed a computer monitor and a telephone. In the lean
condition, no further additions to the office space were made. The
green office space also contained eight large green plants (average
height 90 cm). Because several participants were taking part in the
study at the same time, the view of the plants was not exactly the
same for each participant. However, each participant in the green
condition could see at least three plants from the workstation.
.53***
-.16*
-.06
.04
-.19*
.48***
.71***
.50***
-.16*
-.12
Disengagement
(T1)
Concentration
(T1)
Condition
(0 = lean; 1 = green)
Concentration
(T2)
Concentration
(T3)
Disengagement
(T3)
Disengagement
(T2)
Figure 3. Study 2: Cross-lagged regression model of concentration. Standardized parameters are reported.
ⴱ
p⬍.05.
ⴱⴱ
p⬍.01.
ⴱⴱⴱ
p⬍.001.
.56***
-.16*
-.17*
.18*
-.17*
.66***
.73***
.44***
.03
-.11
Disengagement
(T1)
Perceived air quality
(T1)
Condition
(0 = lean; 1 = green)
Perceived air quality
(T2)
Perceived air quality
(T3)
Disengagement
(T3)
Disengagement
(T2)
Figure 4. Study 2: Cross-lagged regression model of perceived air quality. Standardized parameters are
reported.
ⴱ
p⬍.05.
ⴱⴱ
p⬍.01.
ⴱⴱⴱ
p⬍.001.
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10 NIEUWENHUIS, KNIGHT, POSTMES, AND HASLAM

As part of the experiment, each desk contained two piles of
papers, with each pile containing a different experimental task.
Before starting, participants were asked to briefly describe their
immediate office environment on a separate sheet (quality of
workspace). This item was used as a manipulation check to mea-
sure whether the perceived quality of workspace indeed differed
across conditions. After this, participants performed an informa-
tion management and processing task followed by a vigilance task.
The experimenters recorded the time participants took to complete
each using a stopwatch.
Experimental tasks and measure. All responses on the ma-
nipulation check on quality of workspace were independently
coded by two individuals who were blind to the participants’
experimental condition and who rated each response on a scale
from 1 (very negative)to5(very positive). Interrater agreement
was excellent (ICC ⫽.90) based on Cicchetti and Sparrow’s
(1981) criteria (ICC ⬎.74). The ratings were used to calculate an
average score on perceived quality of workspace for each condi-
tion.
The first task was an information management and processing
task. Participants were asked to work with a shuffled pile of
corporate memoranda based on a fictitious company. They had to
imagine that they were employees of this company and (a) sort the
memoranda into chronological order (information management),
and then (b) answer 15 multiple-choice questions based on the data
contained in the memos (information processing). The time taken
to complete the task (in minutes) was measured as well as the
number of errors (wrongly answered multiple choice questions).
After this, participants performed a vigilance task. For this
purpose they were each given an A4 photocopy of the same
magazine article and asked to cross out and count all the lower
case letter bs that were on the page. The time taken to complete the
task (in minutes) was measured as well as the number of errors
(missed bs). In both cases the participants were told that they
needed to perform the tasks as quickly and as accurately as
possible.
Results
Manipulation check. Univariate analysis of variance
(ANOVA) revealed a significant effect of office design on per-
ceived quality of workspace, F(1, 28) ⫽6.25, p⫽.022, full ␩
2
⫽
.18, 90% CI [.02, .37]. Participants in the green condition rated the
office environment more positively (M⫽3.32, SD ⫽.87, 95% CI
[2.82, 3.82]), compared with participants in the lean condition
(M⫽2.41, SD ⫽1.15, 95% CI [1.79, 3.02]).
Productivity. To analyze the effect of office design on pro-
ductivity a MANCOVA was performed, with time taken to com-
plete the two tasks as dependent variables. Office design (lean,
green) was the between-subjects factor. The numbers of errors
made on either task were included as covariates in the analysis.
These covariates were included in order to measure a possible
change in efficiency, without loss of quality of work. See Table 6
for descriptives and intercorrelations for all variables.
Analysis of productivity revealed a significant effect of the
covariates, the number of errors on the vigilance task, F(2, 28) ⫽
4.89, p⫽.015, ␩p
2⫽.26, 90% CI [.03, .42], and the number of
errors on the information processing task, F(2, 28) ⫽6.59, p⫽
.005, ␩p
2⫽.32, 90% CI [.07, .48]. There was also a significant
effect of office design, controlling for the covariates, F(2, 28) ⫽
4.80, p⫽.016, ␩p
2⫽.26, 90% CI [.03, .42]. Next, separate
univariate ANCOVAs on the outcome variables were calculated.
There was a significant effect of the covariate (number of errors
made) on time taken to complete the vigilance task,F(1, 30) ⫽
7.69, p⫽.009, ␩p
2⫽.20, 90% CI [.03, .39]. There was also a
significant effect of office design on time taken to complete the
vigilance task, controlling for the covariate, F(1, 30) ⫽7.91, p⫽
.009, ␩p
2⫽.21, 90% CI [.03, .39]. Participants in the green
condition took less time to complete the task (adjusted M⫽5.39,
SD ⫽1.40, 95% CI [4.73, 6.05]), compared with participants in
the lean condition (adjusted M⫽6.67, SD ⫽1.43, 95% CI [6.03,
7.31]). With regard to the information processing task, the effect of
the covariate (numbers of errors made) was not significant, F(1,
30) ⫽2.50, p⫽.124, and a nonsignificant effect was found for
office design on time taken to complete the information processing
task, controlling for the covariate, F(1, 30) ⫽3.04, p⫽.092.
Participants in the green condition took less time to complete the
task (adjusted M⫽17.39, SD ⫽3.85, 95% CI [14.89, 19.89]),
compared with participants in the lean condition (adjusted M⫽
20.39, SD ⫽5.87, 95% CI [17.96, 22.81]). Separate ANOVAs
showed no effects of office design on the number of errors made
on either task, Fs(1, 31) ⫽.95, .60, ps⫽.34, .45.
Discussion
In comparison to the subjective measures used in Study 1 and
the corporate measures used in Study 2, this third study employed
a less problematic measure of productivity. Here the results un-
Table 6
Study 3: Intercorrelations and Descriptives for Office Design, Quality of Workspace, and Time
Taken and Numbers of Errors Made in the Vigilance and Information Processing Task
MSD 123456
1. Office design (0 ⫽lean; 1 ⫽green) .48 .51 —
2. Quality of workspace 2.83 1.12 .42
ⴱ
—
3. Time vigilance task
a
6.05 1.59 ⫺.48
ⴱⴱ
⫺.22 —
4. Errors vigilance task 16.91 7.31 .17 .08 ⫺.47
ⴱⴱ
—
5. Time information processing task
a
18.94 5.10 ⫺.26 ⫺.07 .12 ⫺.28 —
6. Errors information processing task 1.27 1.63 .14 .10 ⫺.50
ⴱⴱ
.14 .23 —
a
Time in minutes, where shorter time indicates greater productivity.
ⴱ
p⬍.05.
ⴱⴱ
p⬍.01.
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11
GREEN VS. LEAN OFFICE SPACE

ambiguously indicated that participants who worked in green
office space were more productive than their counterparts who
worked in a lean office space. Tasks were completed faster and—
importantly—without any accompanying rise in errors.
General Discussion
Three field studies were conducted to compare the effects of
working in an enriched green work environment with those of
working in a lean workspace. A consistent pattern emerged
whereby workers in green workspaces had a more positive orien-
tation to their work environment and to their work than those in
lean workspaces (for a summary see Table 7). That is, enriching a
previously lean office with plants served to significantly increase
workplace satisfaction, self-reported levels of concentration, and
perceived air quality. Moreover, these improvements were sus-
tained over both the short-term (Study 1) and the long-term (Study
2). Significant interactions were also found on four of six occa-
sions. Crucially, enriching space also improved perceived produc-
tivity in Study 1 and actual productivity in Study 3, and this is
something of a touchstone for business theorists (Allen, 2011).
Data from the present findings indicate that a green working
environment is consistently more enjoyable for employees, more
conducive to concentration, and more productive for the business
than its lean equivalent. Indeed, simply enriching a previously
spartan space with plants served to increase productivity by
15%—a figure that aligns closely with findings in previously
conducted laboratory studies (Knight & Haslam, 2010b).
Furthermore, our exploration of possible mechanisms underly-
ing the beneficial effects of indoor plants suggests that a green
office leads to more work engagement among employees, which in
turn has a positive impact on their satisfaction with the workplace,
their concentration, and their perceptions of air quality. It seems
that enhanced engagement increases positive ratings of the work
environment in general, which might be the result of people becoming
more physically, cognitively, and emotionally involved in their work
(Kahn, 1990). There is some support from related experimental work
which suggests that indoor plants can lead students to feel more
comfortable (Wiers-Jenssen et al., 2002) and hence to rate their course
and course environment more positively (Doxey, Waliczek, & Zaji-
cek, 2009). Within our study we have been able to show this positive
effect of plants on the work environment via maintained engagement
over time.
The mediating role of disengagement on concentration is also
consistent with the possibility that plants have a restorative effect
on attention as proposed by ART. Disengagement (as measured by
items such as “feeling apathetic,” “feeling bored,” and “not being
challenged”) may be linked to attentional fatigue as a result of hard
work and an inability to concentrate (Kaplan, 1995). In sum, the
mediating role of work engagement on workplace satisfaction,
perceived air quality and concentration is in line with explanations
that point to the importance of managerial care and attention. At
the same time, the effects on concentration and engagement are
consistent with restorative effects as proposed by ART. Of course,
these processes are not mutually exclusive: they may together
contribute to the beneficial effects of indoor plants, either inde-
pendently or jointly.
Beyond the processes involved, our findings represent an ad-
vance on previous studies by providing a direct, quantitative as-
sessment of the benefits of a lean approach to office space relative
to those of a green alternative. Although the patterns observed here
align with previous qualitative (e.g., Duffy & Hutton, 1998;
Elsbach, 2003; Myerson, 2007; Vischer, 2005) and quantitative
studies (e.g., Knight & Haslam, 2010b), the particular advantage of
the present research is that it uses an experimental approach to
manipulate relevant variables in the workplace and over the long-
term with consistent effects recorded regardless of the status of the
participant. In this, the present study develops the theme that the
impact of enrichment is universal and long term (Knight & Has-
lam, 2010a; Peters & Waterman, 2004; Zeisel, 2006). As a con-
sequence, these data simultaneously increase our confidence in the
causal status of our independent variables and the ecological
validity of our conclusions.
Results from the current studies are also in line with previous
studies into workplace performance as well as with qualitative
investigations into the elements that comprise an effective
workspace. Accordingly, they point to the value of introducing
plants into a workspace for the benefit of employees as well as
for the financial health of the organization. This conclusion is at
odds with the present economic and political zeitgeist as well as
with modern management techniques, yet it nevertheless iden-
tifies a pathway to a more enjoyable, more comfortable, and a
more profitable form of office-based working (Baldry, Bain, &
Taylor, 1998; Cohen, 2007; Crampton, 2011; Elsbach, 2003;
Taylor, 1911; Zelinsky, 2006).
Limitations and Further Research
Despite the consistency of findings—both internally and with
other psychological studies—this research has a number of
limitations. First, we should consider why two of the six pre-
dicted interactions were not significant. The first of these con-
cerned satisfaction with the workspace in Study 1: Satisfaction
increased in both the lean and green conditions. We argued that
the unexpected rise in satisfaction in the lean condition may
have been due to the exposure to plants en route to worksta-
tions, making the environment more attractive to look at. When
this design issue was resolved in Study 2—by using discrete
floors of a building rather than separate areas on the same
Table 7
Changes of Employees’ Satisfaction, Concentration, Perceived
Air Quality, and Productivity in Lean and Green Office
Environments Across all Studies
Study 1 Study 2 Study 3
Dependent variable L G L G L vs. G
Workplace satisfaction ⫹⫹⫹0⫹⫹ Not tested
Concentration 0 ⫹⫹ 0⫹Not tested
Perceived air quality 0 ⫹0⫹⫹ Not tested
Productivity
a
(⫺)(⫹)0 0 ⫹
b
Note. L⫽lean condition; G ⫽green condition. ⫹⫹⫽positive change
at p⬍.01. ⫹⫽positive change at p⬍.05. (⫹)⫽positive change at p⬍
.10. (⫺)⫽negative change at p⬍.10. 0 ⫽no change (p⬎.10). This table
was based on simple effect analyses in Studies 1 (T1 vs. T2) and 2 (T1 vs.
T2, T3) and the MANCOVA in Study 3.
a
Productivity was measured in different ways across the studies.
b
This
effect refers to the difference between the lean and the green condition.
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12 NIEUWENHUIS, KNIGHT, POSTMES, AND HASLAM

floor—the expected interaction was observed. In Study 2 the
effects for employees’ concentration levels did not reach sta-
tistical significance. Again, although concentration levels in-
creased somewhat in the green condition, there was also a small
but nonsignificant rise in concentration levels in the lean con-
dition preventing the interaction from becoming statistically
significant. Taking all findings together, we conclude that the
two nonsignificant effects are not so inconsistent as to seriously
invalidate the hypothesized effects. Therefore, we conclude that
overall there is reasonably strong evidence in favor of the
hypothesis.
Second, as already noted, the patterns observed in regard to
call-center productivity (Study 2) were discrepant from those
obtained on other measures. We attributed this to the ambiguous
nature of the productivity measurements used by the organiza-
tion in question (which valued fast responses over longer re-
sponses). We argued that such metrics are problematic in so far
as they have no bearing on the quality of the conversation, the
rapport developed between the engaged parties, or the financial
implications of the interaction. That a company should struggle
to measure productivity is not unusual (Allen, 2011; Djellal &
Gallouj, 2008; Blois, 1984). Indeed, the consultancy business
which hosted the productivity experiment (Study 3) was not
confident that their own measurements of face time with clients
and billable hours worked properly captured staff’s productiv-
ity. It was mooted that these business data might, for example,
reflect levels of seniority (where senior staff cherry pick—or
are given—the best jobs) or the quality of the secretarial sup-
port available. As a consequence, in our final study we relied
upon office-based tasks that approximated more closely to the
general skills pertinent to the modern workplace (following
Knight & Haslam, 2010b). Clearly, however, in future research
there is a need to calibrate these measures even more closely,
with a view to establishing the validity of our interpretation of
the outcomes observed across the three studies here.
Third, the focus of this study was on the differences between
lean space and green space. This is clearly a narrow band of
potential environmental options. Nevertheless, this very nar-
rowness can itself be taken as providing evidence of the rela-
tively minimal changes that seem to be needed to deliver both
psychological and commercial advantage. In this context, it is
all the more remarkable how reluctant organizations often are to
take advantage of such opportunities to improve the quality of
work environments for employees (Vischer, 2005).
It follows that, as a fourth point, more research needs to be
undertaken to advance upon the present work. In particular, the
third study had a small sample and replication of findings
across tasks and contexts would be important. In line with
previous studies, there would also seem to be value in clarifying
the potential for empowering workers to make decisions about
the office environment and any greening initiative that is un-
dertaken (Durmusoglu & Kulak, 2008; Elsbach, 2003; Knight &
Haslam, 2010b). Finally, the present research did not include a
measure of creativity. As this is something that both lean and
green workspace practitioners claim to be able to enhance
(Laing, Duffy, Jaunzens, & Willis, 1998; Tapping & Dunn,
2006), it would be useful to test these claims scientifically in
future research. Extending the rationale of the present study, we
have begun to explore these questions among various commer-
cial organizations where preliminary data accord closely with
the conclusions of the present research. Specifically, they indi-
cate that creative decision making is more prevalent in an office
space enriched with plants than in a lean alternative.
Concluding Comment
The present research makes a novel contribution to the liter-
ature on office space by directly comparing the benefits of two
modern approaches with contemporary office design. One of
these approaches—lean—is common, the other—enrichment—
less so, especially among lower-status workers. The results
demonstrate how office landscaping strategies that involve
transforming a lean office into a green one contribute not only
to employee welfare but also to organizational output. Lean, it
appears, is meaner than green, not only because it is less
pleasant but also because it is less productive.
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15
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Received May 20, 2013
Revision received May 22, 2014
Accepted May 22, 2014 䡲
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This article is intended solely for the personal use of the individual user and is not to be disseminated broadly.
16 NIEUWENHUIS, KNIGHT, POSTMES, AND HASLAM