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The Measurement of Atmospherics

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  • Amsterdam University of Applied Sciences

Abstract and Figures

Atmosphere is an important factor in how a visitor experiences a space or environment. To establish the importance of the atmosphere factor, a good measuring instrument is required. This study offers a proposal for such a measuring instrument. For this purpose, a meta-analysis was carried out on existing empirical and theoretical studies on atmosphere in marketing literature and museum studies. Stores and museums are two relevant examples of places where atmosphere plays an evident role in visitor experience and behavior.
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The Measurement of
ATMOSPHERICS
Harry van Vliet
(c) 2018 Plan B Publishers
Deventer
The Measurement of
ATMOSPHERICS
Harry van Vliet
(c) 2018 Plan B Publishers, Deventer
Design: MXStudio
The moral rights of the author have been asserted
This research was partly funded by NWO (Nationaal Regieorgaan
Praktijkgericht Onderzoek SIA)
ISBN 978-90-813161-8-7!
Contents
Introduction 1
The impact of environmental stimuli 3
Theories on atmospherics 10
The S of Stimuli 13
The O of Organism 18
The R of Response 24
Conclusion 28
Atmospherics in museums 29
How to measure atmospherics? 41
Environmental cues 42
Perceived atmosphere 44
Felt emotion 48
Approach/Avoidance 57
Atmospheric responsiveness 58
Conclusion 60
Notes 61
References 66
Appendix 1: Survey items for measuring atmospherics 74
Introduction
Atmosphere is an important factor in how a visitor experiences a
space or environment. In various studies, visitors name a festival’s
atmosphere as the most important element in how they experience
the festival (Van Vliet, 2012). Atmosphere is also named as an
important distinctive element for stores compared to web shops
which can serve to attract consumers to the physical store itself
(Van Vliet, Moes & Schrandt, 2015). And many studies highlight the
role of atmosphere in cognitive and emotional processes; for
example, already in 1956 it was demonstrated that judgments of
psychological states of photographed faces differed in three
physically different rooms that had different atmospheres (Maslow
& Mintz, 1956).
To establish the importance of the atmosphere factor, a good
measuring instrument is required. This study offers a proposal for
such a measuring instrument. For this purpose, a meta-analysis was
carried out on existing empirical and theoretical studies on
atmosphere in marketing literature and museum studies. Stores and
museums are two relevant examples of places where atmosphere
plays an evident role in visitor experience and behavior. So, it’s no
wonder that atmosphere has received a fair amount of attention
from these disciplines.
The role of atmosphere on how people experience a space or
environment has been studied for decades by researchers
particularly those from the ‘environmental psychology’ field who
focus on the interplay of humans and their environment (Mehrabian
& Russell, 1974). At first, most of this research delved into the work
and home environments, as well as environments such as hotels,
1
schools and prisons. Later, focus also turned to the role of
atmosphere in the store environment. One milestone in the
research into atmosphere was the introduction of the term
atmospherics by Kotler (1973) to characterize the atmosphere in a
store. However, in previous decades, research had already been
done on the relationship between the environment and consumer
behavior (including Martineau’s research into ’store personality’,
and Laird’s research into odor influencing how a product’s quality is
perceived).1 After Kotler’s initial ‘kick-off’, most atmospheric
research was in the context of marketing research into consumer
behavior in stores and other ‘service’ environments such as hotels,
restaurants and airports. Later, museums and festivals also entered
the fold (Van Vliet, 2014). Much of the atmospheric research
outside of retail, such as on museums, builds on earlier research
and theory related to how consumers experience stores (e.g.
Forrest, 2014).
First, we will make an inventory of the burden of proof that exists
for the influence of environmental stimuli on the experience and
behavior of people in a specific space. We will then look at the
theories – largely based on studies on store atmospherics – that
have been put forward to explain these results. We will then
describe and evaluate the research that has been undertaken into
museum atmospherics. Together, these insights will contribute to
putting together a reference questionnaire for measuring
atmospherics – which will be described in the last section and
presented in the appendix.
2
The impact of environmental stimuli
The interest in the effect of environmental stimuli on a customer
comes from the idea that this can have a direct effect on a
customer’s buying behavior. Kotler (1973) already modeled this
relationship by proposing four consecutive phases: a) a product is
offered for sale in a specific spot that has sensorial qualities that
may, or may not, have been consciously designed; b) the consumer
absorbs certain environmental characteristics which c) influence
their “information and affective state”; and, in turn, d) these
changes can increase the chance of a purchase. Evidence indeed
exists that environmental stimuli can influence purchasing
behavior. One example: a study by Donovan et al. (1994) of 60
shoppers in two different stores showed that “pleasure induced by
store environments appears to be a strong cause of consumers
spending extra time in the store and spending more money than
intended” (p. 291). Another example: Peck & Childers (2008)
showed that a positive evaluation of a store environment influenced
the perceived quality of a product in the store.
The burden of proof is not limited to just these two examples. In-
depth research has been undertaken on how store environments
influence a consumer’s experience (e.g. Turley & Milliman, 2000;
Peck & Childers, 2008; Mari & Poggessi, 2011; Olahut, El-Murad &
Plaias, 2012; Farias, Aguiar & Melo, 2014). Most of this research
has been on the impact of music, largely because it’s easy to
‘manipulate’. For example, the music’s tempo influences the
walking pace of consumers, the number of bought products and the
stay duration. The popularity of a piece of music influences the stay
duration in a store and how time is experienced while waiting in
line. By creating a pleasurable mood, music can indirectly
3
influence product choice and exploratory behavior in the store.
Pleasant odors influence how a person estimates how long they
have stayed in the store, the number of purchases and exploratory
behavior, particularly when the scent is congruent with the sold
product, such as the smell of bread in a bakery (Mattila & Wirtz,
2001) or how the smell of chocolate in a bookshop has a positive
effect on cookbook sales (Doucé, Poels, Janssens & Backer, 2013).
Colors influence (red negatively, blue positively) how much time is
spent in a store, the level of pleasant feelings while shopping, the
number of purchases, the image a client has of the store and the
attractant power of the product presentations. While light clearly
influences the experienced atmosphere in a store (Vogels, 2008;
Custers et al., 2010), its effects and what it affects remain unclear.
Taste has been mostly studied in the context of tasting product
samples – and therefore focuses more on the product than the
environment as a whole. The lay-out of a store elicits consumer
movements and gestures that can be performed during the
shopping trip, and have shown to influence number of purchases
(Bonnin & Goudey, 2012). Where and how a product is placed in a
store and how it’s referenced to, influences the choices consumers
make; however, the results are not always clear to interpretation.
The experienced crowdedness has a negative effect on factors such
as satisfaction, perception of quality and number of purchases.
Friendly personnel who are clearly recognizable and present in
required numbers leads to the experience of a higher service
quality. In short: music, smell, color, light, the product’s placement
and available information, store lay-out and personnel can
influence the (emotional) experience of consumers. And this, in
turn, can influence their purchasing behavior.
4
Research results don’t always all point in the same direction and
are sometimes even contradictory. These differences can be
partially explained by differences in how the constructs are put into
practice, the used research methods and the specific situations
wherein the data is collected – after all, not all stores are the same
(Foxall, 1997; Mari & Poggessi, 2011). But another important
reason is how different factors can influence how consumers
experience environmental stimuli. Examples of such factors
include:
Individual differences. This does not only include age and sex,
but also individual differences in one’s sensitivity for certain
sensory experiences (warmth, noise, crowding et cetera) and the
coping strategies one has to deal with these experiences. This
factor also includes cultural differences and certain dispositions
(sensation-seeking, variety-seeking et cetera).
Motivation. Example: ‘hedonistic’ shopping (for fun) and
‘utilitarian’ shopping (task-related) are different starting points for
experiencing a store (Van Vliet, 2014) and result in different
experiences of atmosphere (Rayburn & Voss, 2013). Shopping
behavior (impulse buying versus contemplative shopping; rituals
in shopping behavior) can also influence how the store’s
atmosphere is experienced and which environmental stimuli
contribute to that experience.
A store’s assortment. Example: clothing is more inviting to touch
than CD cases. Touching products has an effect on the evaluation
of the products, particularly with higher quality products that
have characteristics that appeal to being touched, such as
softness and texture (Grohmann, Spangenberg & Sprott, 2007).
Certain product types bring certain environmental stimuli to the
forefront earlier and thereby can unleash certain behavior and
5
associated experiences earlier. The difference between ‘branded’
products and ‘normal’ products can also play a role.
Congruence. Similarity between different senses is an important
factor: a Christmas scent combined with Christmas music
strengthens the store’s positive evaluation, sense of space and the
available products (Spangenberg, Grohmann & Sprott, 2005); for
a jewelry store, classical music is more fitting than pop music et
cetera (Turley & Milliman, 2000; Mari & Poggessi, 2011).
Incongruity between, for example, odor and music can nullify, or
even reverse, the effects of the individual elements (see Mattila &
Wirtz, 2001).
This last factor also raises an important critical point: namely that
most research has focused on discrete elements (color, light, scent
et cetera) in the store environment and their effects. At most, some
studies have combined a small number of cues (e.g. Baker,
Parasuraman, Grewal & Voss, 2002; Harris & Ezeh, 2008) or
considered the effect of congruency. However, this kind of research
remains scarce (Mari & Poggessi, 2011). The preference for discrete
elements is driven by the search for causal relations between
certain stimuli (e.g. music) and behavioral change with consumers
(e.g. increased purchasing) (Eroglu & Machleit, 2008). This leads to
an associated experiment methodology that involves manipulating
one independent variable. Any found relationship can then be
directly translated as advice to retailers (“Classical music in wine
stores leads to more expensive purchasing!”). But others take a
more holistic view: “When a customer enters a store they do not
experience the music in isolation; they do not smell the scent
without seeing the colors as well; they do not walk on the floor-
covering without feeling the ambient temperature. The typical
customer experiences degrees of all these and other stimuli as an
6
ongoing, collective experience” (Ballantine, Jack & Parsons, 2010,
p. 642).2 This view is also known under such names as the ‘Gestalt
Conception’ (Mari & Poggessi, 2011) and ‘transactional approach’:
“Its unit of analysis is the person-in-environment and its focus the
person’s transactions (experience and actions) with the
environment. Rather than emphasizing the antecedent-consequent
or cause-effect relations, the attention is directed on understanding
the whole transaction, the relationship between its aspects and how
they work in combination” (Eroglu & Machleit, 2008, p. 826). Since
people and their evaluation of a behavior in a certain situation
cannot be separated from the physical and social context, the
phenomena that take place must be regarded as holistic situations
instead of independent elements (also see Schorch, 2013). This
view also has consequences on the theory and measurement of
atmosphere (see pages 47-48).
Meanwhile, attention is now also being directed towards the role of
new technologies in stores and the influence these have on visitor
experience. Some may regard this as late in the game since these
developments seem to be occurring rapidly and seem to have a
clear potential to strengthen client behavior for example, using
personalization to play on the behavior and expectations of
consumers (Varadarajan et al., 2010; Pantano & Viassone, 2013).
But in fact, the introduction of new technologies into retail is going
slowly (Pantano & Viassone, 2013; Van Vliet, Moes, Schrandt, 2015)
due to: overwhelming choice, smaller stores cannot always afford
the required large investments, some of the technologies are not
always yet fully developed, the uncertainly around a technology’s
true effect on revenue, and a certain conservatism among retailers
(“I don’t need that”). Poncin & Mimoun (2014) is one of few
examples of research into new technology’s role in stores and the
7
influence it has on store experience. They found that the use of
augmented reality and interactive game terminals in a toy store had
a direct effect on how the store was experienced, the level of
positive emotions and purchase intention.
From the beginning of this century, attention has also been given to
online atmospherics, also known as virtual servicescapes or e-
scapes (Mari & Poggessi, 2011). The manipulation of color,
graphics, interactivity, layout, photos, animation, music and design
can all lead to a more pleasant online experience for the consumer
(e.g. Szymanski & Hise, 2000). The elements studied online may
differ from the offline world involving more design cues and a
less prominent role of, for instance, music but the approach and
guiding theoretical frameworks (such as the S-O-R model and the
PAD-model, see next section) remain the same (see Eroglu,
Machleit & Davis, 2001; Menon & Kahn, 2002). One example of a
study of online atmospherics, Eroglu, Machleit & Davis (2003),
researched whether changing certain atmosphere characteristics of
a website influenced a user’s experienced pleasure. The data
showed an effect that seemed moderated by the user’s level of in-
volvement and atmospheric responsiveness (see further Varadarajan
et al., 2010). Yet another approach is to look at how the summoned
experiences on a store’s website can lead to a more positive view of
the physical store. One study by Moes & Van Vliet (2017) reported
on how differently presented visual material on a website
influenced, among other things, the intention to visit the physical
store. Compared to consumers who only saw a regular photo or a
360-degree photo of the store, consumers who saw a VR photo had
a more positive store experience, an increased purchase intention,
a higher intention to visit the physical store and a better online
experience.
8
Most studies focus on the positive effect that environmental stimuli
have on the consumer (e.g. Ballantine, Jack & Parsons, 2010;
Muhammad, Musa & Ali, 2014; Poncin & Minoun, 2014).
However, it’s easy to imagine that negative effects can sometimes
have even more of an impact (Baker, Parasuraman, Grewal & Voss,
2002). Mari & Poggessi (2011) refer to this as the ‘dark side’ of the
servicescape. A study by d’Astous (2000) looked at the irritating
aspects of the store environment that lead to negative feelings in the
consumer. From the preliminary research into shopping irritations
named by clients, 18 such irritations were selected that fell under
Baker’s 3 main categories of environmental stimuli (see page 15).
Examples include: bad smells, overly hot, overly loud music and
not clean (ambient factors), not being able to find what you need,
poor directions, overly narrow spaces, no mirror in changing room
(design factors) and crowding, personnel indifference and no
available personnel (social factors). The results from interviews with
281 consumers showed that the ambient and social factors caused
more irritation than design factors. Some irritations also showed an
effect based on sex (females are irritated more than males when it
comes to factors such as overly hot, not being able to find what
they are looking for, or no mirror in fitting room) and age (older
people get more irritated by overly loud music). Stores can
immediately adapt these insights into concrete actions that remove
these irritations (e.g. training personnel, providing better directions
to products, reformulating store’s design to combat crowding). You
can also choose to take a further step by researching the
dysfunctional behavior of clients in a store, such as misbehavior,
aggression and theft – where servicescape elements (dirty, loud,
badly ventilated, overcrowded) have been shown to play a
demonstrable (indirect) role (see Reynolds & Harris, 2009).!
9
Theories on atmospherics
So, what theoretical framework can bring together all these
different experimental findings on the impact of environmental
stimuli on the consumer/visitor? The writings on atmospherics by
Kotler (1973) still form a good basis for further theory development:
“The conscious designing of space to create certain effect in
buyers”, and “the effort to design buying environments to produce
specific emotional effects in the buyer that enhance his purchase
probability” (p. 50). While over time, different variations have been
formulated (see Olahut, El-Murad & Plaias, 2012), the core aspects
remain: the conscious manipulation of a space to cause specific
effects (behavior, cognition, affect) on those entering that space.
Herein are two important assumptions:
1. A product is part of what Kotler calls a ‘total package’ that
includes the atmosphere of the place where the product is sold,
which is sometimes even more important than the product
itself. For Kotler, a store’s atmosphere is therefore an important
way to differentiate yourself from the competitors – certainly
within a competitive market: “Atmospherics becomes one of
the chief tools for attempting to attract and hold a specific
segment of the market” (Kotler, 1973, p. 53).3 With this obser-
vation, Kotler foresaw the rise of the ‘experience economy’ in
the 1990s.
2. A difference exists between the intended atmosphere (the
atmosphere that the designer aspires for with his design) and
the perceived atmosphere (the atmosphere experienced by the
consumers). In other words, a space that was created to come
across as ‘warm’ and inspire ‘wonder’ may not always come
across as such by those in that space. This does not mean that
10
the 'objective' description of space and the research of
experienced environmental cues are meaningless; it is precisely
the interaction between intended and perceived atmosphere
that is relevant (see also Belk (1975) for this discussion).
Using Kotler’s remarks, we can give a definition of atmospherics.
Important elements within this definition are the role of
environmental stimuli, the difference between intended and
perceived atmosphere and the effect on the (total) experience of the
person at that moment in that situation (Kotler, 1973; Fisher, 1974;
Belk, 1975; Turley & Mulliman, 2000). Milliman & Fugate (1993)
already provide a definition that bring together these elements:
“Atmospherics is the study of (a composition of) stimuli in an
individual’s perceptual field that stimulates one’s senses and affects
the total experience of being in a given place at a given time”.
However, within this definition, little is said about how that process
takes place - a necessary requirement to explain results based on a
theoretical framework.
Kotler’s efforts in 1973 did not immediately lead to a surge in
empirical research and theory development. It is Bitner who
concludes some twenty years later: "In marketing there is a
surprising lack of empirical research or theoretically based
frameworks addressing the role of physical surroundings in
consumption settings" (1992, p. 57). The first empirical study based
on Kotler’s ideas was undertaken almost a decade later (1982), but
was then followed by a significant increase in related research (see
previous section).4 However, with theory development, the profits
have been much more modest. In a reflection on the achieved
results of research into atmospherics to that point, Eroglu &
Machleit (2008) concluded: “There have not been major
11
conceptual developments in the past three decades of work in this
area” (p. 826). The various cited studies, use as a theoretical
framework the S-O-R (Stimulus - Organism - Response) model from
environmental psychology – that was also the underlying theory
used by the often-cited study by Mehrabian & Russell (1974).
Stimuli (S) in the environment are processed by an organism (O),
which in turn inspires a response (R). The S-O-R model is
categorized as a paradigm (by, for example, Douce, Poels, Janssens,
Backer, 2013; Elbachir, 2014) but also as a framework (Grohmann,
Spangenberg & Sportt, 2007) and a theory (Turley & Milliman,
2000). However, Eroglu & Machleit (2008) questioned this last
category. Rightly so, since a theory would explain how and why an
organism ‘selects’ stimuli from its Umwelt and benefits from this
selection (see, for example, Dennett, 2017 for a theory about this).
A theory would also explain what the ‘processing’ of stimuli
involves and what this means for the organism in relation to its
environment (see, for example, Neisser, 1976). In addition, a theory
would explain which behavioral repertoire an organism can have
and use in response to, and as a consequence of, its environment –
for example through coping strategies (as seen, for example, in
Richard Lazarus’s studies into stress and coping). These basic theory
elements are all still missing. At most, the widely-used PAD model
in atmospherics research is a (partial) theory of an organism’s
emotional processing of stimuli. But this view has some
fundamental limitations as will be shown below (pages 19-22).
Various calls have been made, mainly in review articles, for a
stronger theoretical foundation. For example, at the turn of the
century, Turley & Milliman (2000) wondered: “Are there theories
beyond the S-O-R paradigm?” (p. 208). Nonetheless, let us explore
the progress on building knowledge of atmospherics in the context
of the S-O-R model.
12
The S of Stimuli
The number of elements in an environment that can influence a
person, are too many to work with meaningfully within a theory
the Umwelt is simply too richly filled with stimuli and information
that can directly or indirectly influence a person’s thinking, actions
and feelings. Even if we limit the studied spaces to, for example,
artificially constructed environments (as opposed to natural envi-
ronments), micro-environments (as opposed to macro environ-
ments, such as a landscape), public environments (not private
spaces, such as people’s homes) and on spaces with consumer-
personnel interaction (Eroglu & Machleit, 2008), then an environ-
ment such as a store is still an endless “group of cues, messages,
and suggestions” (Farias, Aguiar & Melo, 2014, p. 87; also see
Mehrabian & Russell, 1974). Even if you only name 57 possible
stimuli (Donovan & Rossiter, 1982), this still results in thousands of
possible interactions between these stimuli (Ballantine, Jack &
Parsons, 2010; Bonnin & Goudey, 2013; Rayburn & Voss, 2013).
Back in 1975 it is Belk who already stated: "The ultimate problem
for all future situational research is the lack of a comprehensive
taxonomy of situational characteristics and normal combinations of
these characteristics" (Belk, 1975, p. 162).
But a comprehensive taxonomy is just one of three possible ways to
approach the problem of the wealth of cues in environments. First,
the impact of individual elements can be put into perspective by
favoring the environment’s overall impression. We already came
across this 'holistic' view above as criticism on the research done to
date on individual envirionmental stimuli (Kaltcheva & Weitz,
2006; Ballantine, Jack & Parsons, 2010; Rayburn & Voss, 2013).
Consequently, questioning consumers on their experience is
13
oriented towards general impressions of the atmosphere (see pages
47-48).
A second approach is to not focus particularly on individual
elements, but to describe the space’s underlying dimensions.
Named dimensions are for instance novelty (new, unexpected),
complexity (the number of elements and level of change in the
surroundings) and spaciousness. In their study, Donovan & Rossiter
(1982) found dimensions such as variety and irregularity. Custers et
al. (2010) brought in other found dimensions, such as mystery,
legibility, coherence and order. Gilboa & Rafaeli (2003) researched
the influence the complexity and order of supermarkets have on
experienced emotions and approach/avoidance behavior. These
dimensions often arise from the statistical analysis of the words
people use to describe a space. Called intangible atmospheric cues
by Kottasz (2014), these dimensions refer to a quality of
atmospherics that the philosopher Böhme describes as “in the air” –
dimensions that transcend the objects themselves (Dorrian, 2014).
None of these studies offer a theoretical framework that explains
why it must be these particular dimensions. However, these
dimensions can still be used, in a pragmatic way, to organize the
items used to describe a space (see page 45).
The third, and most applied, approach is to order stimuli into
categories creating a sense of overview, as Belk (1975) hoped for.
The question then rises on what categories should be used and
this has been answered with various propositions. Kotler (1973)
already used different categories based on the senses to describe a
store’s atmosphere: visual (color, brightness, size, shapes), aural
(volume, pitch), olfactory (scent, freshness) and tactile (softness,
smoothness, temperature). However, this classification has had few
14
followers; it’s also confusing since it’s based on a person’s senses
and not on environment’s elements. Two typologies are often cited
in the literature: those of Julie Baker and Mary Jo Bitner.5
Baker’s proposed typology (Baker, Grewal & Parasuraman, 1994;
Baker, Parasuraman, Grewal & Voss, 2002) is regularly used in
research and divides the (physical) surroundings into three
categories:
1. Ambient factors: ‘Background features’ that are picked up
unconsciously or consciously by the person and have influence
on their senses, such as smell, light, sound (including music),
air quality et cetera.
2. Design factors: Aesthetic characteristics of the environment that
are noticed directly by the consumer, such as architecture, use
of color, wall and floor material, et cetera. These factors also
include more functional features, such as aisles, store layout,
signage and comfort.
3. Social factors: The presence, appearance and behavior of
personnel and other customers.
In her study, Bitner (1992) uses a marketing perspective to highlight
the influence of the physical environment on consumers and
personnel. Bitner uses the term servicescape to describe the situa-
tion: “All of the objective physical factors that can be controlled by
the firm to enhance (or constrain) employee and customer actions.”
(p. 65). This manipulation can be done through many forms,
including light, temperature, furniture, music, color, spatial layout
et cetera. According to Bitner, these different types of manipulation
can be placed under three categories:
15
1. Ambient conditions. This includes characteristics of the space
such as temperature, light, sound, music, odor and other factors
that play directly to our senses.
2. Spatial layout and functionality. This covers both the spatial
ordering of the used objects (furniture, plants et cetera) and
their relative positioning to each other, as well as how the
spatial layout supports the achieving of particular goals (e.g.
whether the cashiers in the store are easily visible and
accessible so the client can pay as quickly as possible).
3. Signs, symbols & artifacts. There are all sorts of explicit signs in
a space – from labels (name of company, advertising) and
directions (‘Exit’) to signs that communicate behavioral rules
(‘No smoking’). There are also all sorts of implicit signs, symbols
and artifacts that say something about the space: white
tablecloths and dimmed lighting in a restaurant represent good
service and high prices; the largeness of the desk and the
diplomas on the wall influence the image people have of that
manager or therapist. Such manipulations create a complex
whole that cannot always be controlled or interpreted as
intended.
These three categories are intended to clearly describe the
influences within the servicescape. However, consumers will not
experience these categories as different dimensions. The consumer
will form a holistic image based on all the servicescape’s stimuli:
“Total configuration of environmental dimensions is responsible for
the constitution of the servicescape” (Bitner, 1992, p. 67). Bitner
calls this general impression the ‘perceived servicescape’.
While the three categories of Baker and Bitner are not always easy
to map onto each other, their respective elements do share many
16
similarities. It’s striking though that Bitner does not include the
social factor in her typology, especially of its importance: “the
character of an environment is dependent on part on the typical
characteristics of its members” (Moos, 1973, p. 655). Instead she
places the social factor in her servicescape model as a ‘moderator’
– something that influences the end behavior in a store.
All kinds of variations, rearrangements and additions to the
categorizations of Baker and Bitner have been published with the
most extensive being by Turley & Milliman (2000) that was then
expanded on by others (e.g. Olahut, El-Murad & Plaias, 2012). An
important addition in the structuring of Turley & Milliman (2000) is
the role of 'external variables', such as the appearance of the
building (size, architecture et cetera) and its location’s environment.
Tzortzi (2016) emphasizes how the internal and external
architecture of a museum can contribute to the narrative that the
museum wants to tell. This effect is rarely mentioned in other
studies, apart from Reynolds & Harris (2009). Perhaps this omission
is because of the lack of retail research into, for example, the role
of display windows. Olahut, El-Murad & Plaias (2012) name just a
few studies that show an increase in sales of products shown in a
display window, or that entering a store is dependent on the
appearance of the store window and the information it provides
which, in turn, is dependent on, among other things, a client’s
motivation. Also, of the little research that has been done on
shopping environment atmospherics, most focused on malls
(Michon, Chebat & Turley, 2005 among others). The research of
Yüksel (2007) is one of the exceptions: it studied the perception of
the macro-environment such as shopping districts and its effect on
emotions, the perceived value of shopping experience and
approach behavior. The study found, among other things, that a
17
positively perceived environment leads to more consumer
approach behavior.
Nevertheless, the conclusion remains that the offered categories are
a pragmatic way to arrange an environment’s many elements in a
way that makes research feasible. However, no compelling
framework exists that explains why it must be these particular
categories.
The O of Organism
Within the S-O-R model, environmental stimuli ensure that the
environment does ‘something’ with the person (the O) in that
environment – specifically with the person’s emotional state. To
model this emotional state, atmospherics research often use the
PAD model (Mehrabian & Russel, 1974), a so-called ‘dimensional’
model of emotions (Van Vliet, in prep.). This model proposes that
emotions can be scaled within three independent dimensions:
pleasant/unpleasant, active/passive (degree of arousal) and
dominance/submissiveness. The PAD model doesn’t necessarily
measure the emotions, but rather the perceived pleasure, arousal
and dominance triggered by the stimuli. This is done using 18
semantic differential items, six for each dimension, such as
unhappy/happy (pleasure), relaxed/stimulated (arousal) and
controlled/controlling (dominance). Since emotions take a place
within the three-dimensional PAD model, the scores can be related
to certain emotions. Diverse research has shown that the
dominance factor contributes little to explaining phenomena and is
therefore often omitted (e.g. Bradley & Lang, 1994; Sherman,
Mathur & Smith, 1997). However, Mari & Poggessi (2011) have
18
signaled that this dimension is making a comeback in empirical
research.
The first empirical study of atmospherics (Donovan & Rossiter,
1982) followed the train of thought behind the PAD model, and its
influence continues through to recent studies by, for example,
Farias, Aguiar & Melo (2014): “The store atmosphere is represented
psychologically by consumers in terms of two major emotional
states – pleasure and arousal“ (p. 89). However, five points of
criticism can be directed towards the PAD model (Van Vliet, in
prep):
1. The PAD model cannot differentiate between clearly different
emotions. In other words there’s a ‘lack of granularity’: “The
PAD typology (…) has been criticized as being too narrow in
scope and not encompassing the range of possible variations in
emotional reactions” (Eroglu, Machlet & Davis, 2001, p. 181)
and also: “For anyone interested in understanding the rich
diversity and subtle nuance of emotional life, a simple
characterization of emotions as pleasant or unpleasant, strong
or weak, seems both theoretically sterile and experientially
implausible” (Smith & Ellsworth, 1985, p. 814). For example,
fear and anger are both categorized as unpleasurable (negative
valence) and with a high arousal, and therefore end up beside
each other in PAD model as similar emotions. As Richins (1997)
concluded over the use of the PAD dimensions: “Best used
when a researcher (…) does not need to know the specific
emotions being experienced by study participants“ (p. 128).
2. It remains unclear which dimensions are needed, or are even
essential, for the model. The dominance dimension is often left
out in empirical studies because ‘it doesn’t do much’. The
model can then be simplified into a V-A (valence – arousal/
19
activation) model such as the one that forms the basis for the
well-known circumplex model. The crucial role of arousal has
been under fire for decades: “Its role [autonomic arousal] in
emotional experiences certainly has been overrated” (Frijda,
Kuipers & Ter Schure, 1989, p. 226). In addition, alternative
dimensions have been proposed such as approach/avoidance.
But it is also completely unclear why a dimension such as
novelty does not get a prominent place since there is abundant
research showing the 'basicness' of novelty detection (Scherer,
2009). This reflects certain arbitrariness in what dimensions are
chosen. Although few researchers will deny the importance of
'valence' and 'activation', there are questions about the claim
that these are 'core' dimensions: “It is not clear in what sense
and why valence and arousal feelings are considered as more
‘core’, ‘primitive’ or ‘basic’ than other internal representations”
(Scherer, 2009, p, 1335). That people can reliably describe their
emotions in this way is not a conclusive argument, especially
because in free format descriptions of emotional events people
rarely answer spontaneously in terms of valence and arousal
gradation: “The two-dimensional valence by arousal space
seems to be considered basic on the basis of countless factor
analyses that show stability for only these two dimensions.
However, it is questionable whether this is not an artefact of
methodology” (Scherer, 2009, p. 1336).
3. Additionally, one can wonder whether these different
dimensions describe the same conceptual ‘space’: arousal is a
physiological component, pleasure is a subjective experience
and dominance (as well as approach/avoidance) seems to
describe a behavioral component. In this way, the different
components are not of the same order. It seems more sensible
to investigate these components individually and placing them
20
within a process model that does justice to their specific role
and characteristics in emotions (see, for example, Frijda, 1986,
Scherer, 2009). By regarding these dimensions as components
(physiology, subjective experience, behavior) also makes it clear
that an important component is missing: the appraisal of the
situation (Van Vliet, in prep.).
4. The dimensions of valence and arousal are ambiguous. For
instance, it remains mostly unclear what kind of arousal is
being referred to: mental activation, sympathetic arousal or
parasympathetic arousal? They are quite different in terms of
type, the consequences of the activation and how they are
measured (Scherer, 2009). Even more important: “One of the
major drawbacks (…) is the difficulty of knowing whether the
valence dimension describes the intrinsic quality of an eliciting
object or the quality of the feeling (which may not
coincide)” (Scherer, 2005, p. 719). An ‘inherently’ funny event
may not lead to a good feeling for all kinds of reasons. So, what
does the valence score represent for such an event: the assess-
ment of the funniness of the event or one’s own feeling state?
The same goes for arousal: does the subject’s rating refer to the
perceived activation in a situation or to the own proprioceptive
feeling of arousal as induced by the stimulus event? And metho-
dologically: what does it mean if for instance a wild exciting
car chase scene does not lead to a high state of arousal? Is the
subject disregarded for not ‘getting’ the experimental manipu-
lation?
5. The PAD model is based on a so-called bipolar space where
emotion words are placed as opposites within a single dimen-
sion (e.g. relaxed versus stimulated). This is underlined by the
use of the semantic differential in PAD measurement which
presupposes bipolarity. Bipolarity raises the more fundamental
21
question on whether positive and negative emotions are indeed
polar opposites or are relatively independent of each other. For
example, those who accept the idea of a limited set of basic
emotions take the latter position. The bipolar view also
becomes problematic when trying to explain 'mixed emotions'
situations when we experience multiple (opposite) emotions
simultaneously.6
The PAD model goes back to an understanding of emotions that is
not without problems (Van Vliet, in prep.). However, just like the
circumplex model of emotions (another 'dimensional' conception
of emotions), it has nestled itself into many empirical studies of
atmospherics, and also more broadly in studies of experiences,
because of its relatively easy way to question emotions (too easy
one might say). Theoretically, research into emotions has already
‘moved on’ - in the sense that there are alternative theories that can
better explain the differentiation of emotions in different situations.
The most important example is the appraisal theory of emotions – a
theoretical perspective that remains almost non-existent within
atmospheric research. A positive exception is provided by Chebat &
Michon (2003) and their research into the effect of smell in a
shopping mall that explicitly uses two explanatory models to test
which one is best the pleasure/arousal model (PAD model minus
the dominance dimension) used by Donovan & Rossiter (1982),
and the appraisal model as developed by Richard Lazarus (Lazarus
& Folkman, 1984). The results show that smell contributes to having
a positive experience of a shopping mall. The study also concludes
with: “Our findings strongly support the model derived from
Lazarus” (Chebat & Michon, 2003, p. 537). A person’s evaluation of
an environment is an important predictor of how the product
quality and the store surroundings are experienced and how much
22
is spent – more so than mood (pleasure and arousal). This result
also fits nicely with what Bitner (1992) called the ‘perceived
servicescape’, since the ‘perceivedness’ represents appraisal
processes (see Van Vliet, 2012).7
Regardless of what explanation model was chosen for the
emotional state, various studies have made clear that the ‘O’ is
more complex than just measuring pleasure and arousal. A study
from Kaltcheva & Weitz (2006) shows that a consumer’s motivation
is an important moderator on the arousal effect generated by the
shopping environment. When the motivation to shop is more
recreational (hedonistic), the generated arousal has a positive effect
on the experienced pleasure; when the motivation is more task-
oriented (utilitarian), the generated arousal has a negative effect on
the experienced pleasure. Eroglu, Machleit & Davis (2003) found
evidence for the moderating effect of user involvement and
atmospheric responsiveness on the effect of environmental stimuli
on the experienced pleasure of the person. Baker, Parasuraman,
Grewal & Voss (2002) found an effect of time/effort cost and
psychic cost (mental stress, emotional work) on the experience of
atmosphere. Fischer (1974) had already found an effect on the
experienced equality with others in a space on how the space was
experienced. Rayburn & Voss (2013) show in their study that there
is a direct relation between atmospherics and hedonic and
utilitarian shopping evaluations. In review articles, other modera-
tors have also been named, such as: mood, attention, motivation,
involvement and attitude, social climate and ‘interpersonal and
socio-cultural qualities of a setting’ (Turley & Milliman, 2000;
Eroglu & Machleit, 2008). Besides these moderators, various
mediators have also been proposed. In her studies, Baker
emphatically placed ‘inferences’ between the stimuli and the
23
people’s image of the store (‘store image’). These inferences had, for
example, a relationship with how the quality of the products and
services are perceived (Baker, Grewal & Parasuraman, 1994), which
acted as antecedents for the consumer image of the store. In a later
study (Baker, Parasuraman, Grewal & Voss, 2002), Baker also added
the perception of the price and the quality of the personnel as an
influence on choosing a store. In theories on atmospherics, little
attention is paid to these ‘inferences’ and also the appraisal
processes of the environment. On the other hand, a preoccupation
exists with how pleasant an environment is: “Retail atmospherics
research focused on the effect of environmental cues on
mood” (Chebat & Michon, 2003, p. 531).
The R of Response
In the conducted research, the consumer’s response is backed by as
little theory as with environmental stimuli. There’s not even a
discussion about specific response categories since such categories
are hardly presented. Consumer response merely exists as a
collection of (dependent) measured variables, such as revenue,
time spent in store, number of items looked at, purchases, purchase
intention, purchase attitude and more general variables such as
enjoyment, satisfaction and loyalty (e.g. Turley & Milliman, 2000).
Various studies measure approach/avoidance (including Donovan
et al., 1982; Gilboa & Rafaeli, 2003; Yüksel, 2007). Bitner (1992)
also includes it in her theoretical servicescapes model. This
regularly used approach/avoidance response does have some
theoretical anchoring (van Vliet, in prep.). Approach represents
wanting to stay in a space and explore further; avoidance represents
wanting to leave the space and not explore further. The response’s
24
popularity in the literature can be traced back to the study by
Donovan & Rossiter (1982). Inspired by Mehrabian & Russell
(1974), they propose that all responses to an environment come
down to approach or avoidance behavior. This behavior has four
characteristics:
1. A desire to physically stay in (approach) or to get out of
(avoidance) the environment.
2. A desire or willingness to look around and to explore the
environment (approach) versus a tendency to avoid moving
through or interacting with the environment or a tendency to
remain inanimate in the environment (avoidance).
3. A desire or willingness to communicate with others in the
environment (approach) as opposed to a tendency to avoid
interacting with others or to ignore communication attempts
from others (avoidance).
4. The degree of enhancement (approach) or hindrance (avoi-
dance) of performance and satisfaction with task performances.
(Donovan & Rossiter, 1982, p. 37).8
When characterizing approach and avoidance, one must note that
it involves 'behavior'. This is important in two ways: 1) it is
consistent with the observation that physiological and neurological
research into emotions can only reliably establish whether the
activation involves approach or avoidance since these are
apparently basic reactions (Van Vliet, in prep.); 2) it gives the
opportunity to connect approach/avoidance with the concept of
action tendency in Frijda’s theory (Van Vliet, 2012; in prep.), since
behavior is not always externalized (actually walking away) but can
also be an (internal) willingness to walk away that can be betrayed
by a (unconscious) tensing of muscles and subtle changes in body
positioning.
25
In elaborating this second point, Van Vliet (2012) linked Bitner's
servicescape model with Frijda's emotion theory by connecting the
previously made distinction between involvement and detachment
(Van Vliet, 1991) with the approach/avoidance concept pair.
Involvement is not regarded as a state but a ‘movement’ – a
movement towards, an approaching, a wanting to enter, a desire to
become one with something. In short, involvement is an action
tendency, a readiness to engage in interaction with the
environment, and that follows appraising a situation as relevant and
seeing the possibilities to engage with that situation. Involvement
can have a dual nature: the action tendency can lead to an actual
behavior of the visitor participating, or the involvement can be
vicarious whereby the action tendency leads to reappraisals to
bring the desired situation ‘closer’. For such reappraisals, we often
use words such as empathy and identification.9
One consequence of describing involvement as a ‘moving towards’
action tendency, is the need for a complementary concept that
covers the removal of the situation to ‘move away’. This concept
is detachment and consists of a range of mechanisms that reference
such things as the defense mechanisms formulated by Anna Freud,
the coping strategies from Richard Lazarus’s research into stress,
and all sorts of heuristic rules for dealing with situations, such as
humor, relativizing, denial, intellectualizing and simply walking
away (Van Vliet, 1991). The detachment concept can be
differentiated in a similar way as involvement: the action tendency
can lead to actual behavior (walking away, shutting eyes,
‘removing’ the threat) or to the reappraisal of the situation through,
for example, humor, intellectualizing or relativizing.
26
If the applied approach/avoidance duo is used as a general
characterization of the action tendencies, we can then group
involvement and under there, in the knowledge that other forms of
approach and avoidance exist. Interest/fascination is a form of
approach through the intense focusing of attention on a particular
object or subject. Aesthetic distance is a form of avoidance
whereby people take distance from an (artistic) product such as an
art object, film or performance by explicitly focusing on elements
that emphasize how the project was realized (technique, structure,
author, actor et cetera). The figure below shows how the different
action tendencies are organized.
Figure 1:
General structure of approach/avoidance action tendencies
(Van Vliet, 1991; 2012)
27
Action
tendencies
Approach Avoidance
Involvement Fascination Aesthetic
distance Detachment
Identification Empathy Participation
Conclusion
The S-O-R model forms the basis for much atmospherics research.
The critical questions that have risen around this model can now be
answered substantively. We can say that the doubts expressed by
Eroglu & Machleit (2008) are warranted. Not only are essential
questions not being answered but the only theoretical elements in
the model is the PAD model and the dual concept of approach/
avoidance. It’s indeed a thin theoretical basis. We fully endorse the
call by Mari & Poggessi (2011) after an in-depth analysis of research
into atmospherics and servicescapes: “We urge researchers to go
beyond the S-O-R paradigm in explaining the complexities of
customer behavior” (p. 8). We can also give an affirmative answer
to the question from Turley & Milliman (2000): “Are there theories
beyond the S-O-R paradigm?” (p. 208). Within emotion studies of
the past decades, large strides have been made in research into
appraisal processes, action tendencies and coping strategies.
Integrated theories, such as those of Frijda (1986) and Scherer
(2009), can be ably linked with research models for how people
behave in (service) environments, such as Bitner’s servicescape
model (see for example Van Vliet, 2012). These new insights also
provides an answer on the how of the process of atmosphere
experiences: characteristics of a situation and its affordances are
appraised in light of the relevance for the organism’s well-being;
these appraisals and subsequent reappraisals, regulation processes
and coping strategies may or may not lead to specific subjective
feelings (e.g. joy), action tendencies (e.g. approach behavior),
peripheral physiological changes (e.g. arousal) and expressive and
instrumental behavior (e.g. laughing).
28
Atmospherics in museums
The field of visitor studies has grown exponentially since the 1970s
(Bitgood & Shettel, 1996; Forrest, 2014). However, the portion of
research into visitor experience remains limited (Kirchberg &
Tröndle, 2012), with specific research into museum atmospherics
even more so, according to Kottasz (2014): “Research to date has
rarely investigated the impact of atmospheric cues on visitor
responses and behavior in museums and little is known about this
important topic” (p. 97). Forrest (2014) has also observed that: “The
design appearance of the exhibition environment has been studied
only rarely, and those experiments that have been conducted are of
limited scope” (p. 66). Meanwhile it’s not unusual to regard
museums as particularly “atmospheric environments” (Dorrian,
2014). Yet decisions around the (re)design of exhibition spaces
cannot call on a shared sector-wide analysis framework and
validated measuring instruments. Rather, they must rely on expe-
rience, intuition and assumptions: “Design decisions frequently rest
on intuition and assumptions made about visitor needs, rather than
being grounded in research” (Forrest, 2014, p. 5).10
Museum atmospherics research generally mirrors that of marketing
research into store atmospherics. The museum research builds on,
or at least refers to, the research into specific environmental stimuli
(music, layout et cetera) and the underlying frameworks such as
those from environmental psychology. There’s also the shared view
that a museum visit is a service encounter or servicescape (e.g.
Goulding, 2000; Hume, 2011; Del Chiappa, Andreu & Gallarza,
2014). Explicit references to the ‘source’ – Kotler’s concept of
atmospherics are also common (e.g. Bonn et al., 2007; Forrest,
2014). This overlap is not surprising since the underlying hypothesis
29
has the same focus: a person’s interaction with a space and their
evaluation of that space. In addition, the glory days of environ-
mental psychology more or less coincide historically with the rise
of visitor studies.11 Of course, differences exist between visitor
studies in museums and the retail atmospherics research, but these
are mainly on the level of objectives (e.g. knowledge transfer in
museums versus sales in stores) and the method in which success is
measured and made concrete (e.g. visitor satisfaction in museums
versus revenue in stores).
We therefore see comparable research between the visitor
experience in museum studies and the influence of specific
environmental stimuli on visitor experience in retail. Goulding
(2000) found the influence of routing and crowding on visitor
experience, and Wineman & Peponis (2010) concluded in their
research that the movement of visitors in a museum is related to
spatial characteristics such as accessibility and visibility. Tröndle
(2014) showed the role of a building’s architecture on visitor
experience. (Background) music in a museum influences the visitor
experience resulting in a longer stay and an increase in learning
(Chen & Tsai, 2015; Brenner, 2016). The location, word count and
font size of object labels influence the attention and behavior of
visitors (Bitgood & Patterson, 1993). Jeong & Lee (2006) found that
the exhibition space itself (what is being displayed, how they are
being displayed, accessibility, lighting and rest areas) has the
biggest effect on the satisfaction of visitors. Trondle et al. (2014)
studied the effect of an exhibition’s arrangement by hanging up
alternate paintings or changing painting placement within the same
exhibition. They found that this had an impact on the behavior of
visitors and their attention for the paintings. Kent (2010) studied the
role of the museum shop as an extension of the museum
30
experience. Yet other research has focused on labels and other
contextual elements, spatial configuration, light use, color use on
walls, exhibition size and routing (for an overview, see Forrest,
2014).
There are also studies that take a more overall perspective. Henry
(2000), in an analysis of 33 essays from students about their most
positive and most negative museum experiences, found that
‘exhibition environment’ was one of the most determining factors
for the museum experience. Specifically: the lighting, layout of the
exhibition, crowding, personnel behavior, spatial characteristics
(e.g. height of the space) and routing all familiar elements from
our earlier discussion on environmental stimuli in the context of
retail.
Bonn et al. (2007) researched the influence of environmental
stimuli on visitors to heritage sites with the idea that these visitors
could make a relevant contribution to helping uniquely position a
heritage location within a competitive market: “A major part of
creating this ‘ideal’ experience lies in creating the right atmosphere
or physical environment in which to view the display, exhibit, or
attraction” (p. 347). The research made use of the categorizing of
environmental stimuli of Baker and the S-O-R model. In their study
of 500 museum visitors, they found evidence of the influence of
ambience (lighting, color), design (layout, routing) and social
factors (friendly personnel) on visitor attitude towards the heritage
attraction, as well as on the intentions to revisit the site and
recommend it to friends and others.
Kottasz (2014) adopted the complete atmospherics framework from
the marketing tradition for the museum context: Baker’s
31
classification of environmental stimuli, the PAD model and the
approach/avoidance concept pair. The study’s results from 140
museum visitors collected over 10 museums, showed that
environmental stimuli also have an influence on the PAD
dimensions in museums, particularly with such variables as light,
temperature and decorative elements: “Clearly there is room for
improvement here and museums should re-evaluate their approach
to this aspect of the environment if they are to attract and retain
audiences” (p. 114). In addition, space-describing dimensions such
as novelty, complexity, coherence and mystery also have an
influence on PAD dimensions and approach/avoidance behavior.
The conceptual model presented by Kottasz (Figure 2) is interesting
for its relatively rich and nuanced list of aspects that can influence
the experience atmosphere and the exhibited behavior (see also the
model in Van Vliet, 2012).
The most extensive and recent study of atmospherics in museums is
the study by Forrest (2014). Like Kottasz (2014), Forrest observes
that little research has been carried out into how museum visitors
react to the physical museum space, despite the recognized
importance of this and the (financial) interests involved, such as in
the redesign of museum spaces. Forrest's study aims to provide
insight into how visitors perceive different exhibition spaces and its
relationship with different aspects of the visitor experience. Forrest
developed a model and a measuring instrument for this purpose.
32
Figure 2:
Kottasz’s conceptual model of the effect of atmosphere stimuli on
emotions and behavior
(Kottasz, 2014)
For the development of her model, Forrest reaches back to several
theoretical frameworks: Kotler (definition of atmospherics), Baker
(categorizing environmental stimuli) and environmental psychology
(the interaction between person and environments as a
transactional model). Thereby Forrest follows the distinction Kotler
33
made between intended atmosphere and perceived atmosphere,
and focuses her research on perceived atmosphere. She follows
Baker’s categorizing and focuses on design factors – particularly,
the “visual dimensions of the environment” (2014, p. 37). Herein,
she chooses neither for social factors nor for ambient factors,
except for lighting. She gives no substantive reasons for this choice
– only that it’s beyond the scope of the research. Forrest recognizes
the importance that the S-O-R model has played in atmospheric
theory formation and the use of the PAD model within empirical
research, but mentions two limitations of such research: 1)
atmospherics are not studied in depth, and 2) the S-O-R model
cannot be adapted to multisensory experiences and therefore
cannot be used for a more holistic study of perceived atmospheres.
Both points of criticism are debatable: enough studies exist that try
to make precise statements about the workings of atmospherics,
including the involvement of unpleasant emotions and negative
cues (e.g. d’Astous, 2000). Also, other studies have looked at
multiple cues simultaneously (e.g. Baker, Parasuraman, Grewal &
Voss, 2002). Forrest’s points of criticism are more technical than
fundamental in nature, and can be resolved through better and
additional research. However, it must be noted that the above
observations here are not meant to defend the S-O-R model (see
above). The consequence that Forrest draws from this criticism is
interesting because it is in line with the proposed approach of
integrating the appraisal theory of emotion with the servicescape
theory (see above; Van Vliet, 2012). Forrest summarizes the
cognitive appraisal theory by stating that it involves the cognitive
evaluation (appraisals) of stimuli related to the goals and needs of
the person. These evaluations include recurring aspects, such as the
degree of control over the situation and the agency (who 'causes'
the situation).
34
Forrest’s resulting model for atmospherics is presented as an
alternative for the S-O-R model and as a synthesis of the literature
and research around atmospherics and servicescapes (see Figure 3).
But this stated ambition does raise some relevant questions:
1. The most important ‘change’ that Forrest brings to the S-O-R
model is in the way she speaks of perceived atmosphere instead
of the direct influence of environmental stimuli on the
emotions.12 We have seen that Kotler (1973) already
differentiated between intended and perceived atmosphere and
that Bitner’s servicescape model (1992) already used the
concept of a ‘perceived servicescape’. We’ve also seen that
diverse empirical studies from decades ago were already talking
about ‘inferences’ and, for example, ‘perceived price and quali-
ty’ (Baker, Grewal & Parasuraman, 1994; Baker, Parasuraman,
Grewal & Voss, 2002). While it’s correct to state that these
insights were not all included in the original S-O-R model, too
little credit is given to the (theoretical) work that followed.
2. The introduction of ‘perceived atmosphere’, in the sense of a
person’s appraisals of the environment, has impact on how the
relationship between the environment and the person must be
seen. Cognitive appraisal theories as proposed by, for example,
Frijda (1986) and Scherer (2009) can be seen as an elaboration
of this relationship. However, we see little or nothing of this
impact in Forrest’s model, which still follows the same triplet of
S, O (albeit now ‘perceived’) and R. The introduction of
‘perceivedness’ in the model lacks any further (theoretical)
backing or elaboration. At first it seems that Forrest is following
the path of cognitive appraisal theory (2014, p. 41), but this
later proves to be mere lip service since the term appraisal only
appears sporadically. In addition, only indirect references are
made to the theory via appraisal dimensions such as agency,
35
controllability and outcome desirability. In fact, the empirical
research itself 'reaches back' to the PAD model (just as Kottasz,
2014) and the theory of basic emotions. So, the model is not
really an elaboration on the appraisal theory – which is also
evident in Forrest's discussion about measuring emotions (2014,
p. 113/114).
3. Forrest’s model also encompasses few new insights. In
marketing research into store experience, we have already
encountered all sorts of ‘moderators’ and ‘mediators’ that
influence the visitor experience. A similar summary can also be
found in research into museum experience that apply aspects
such as motivations, values, expectations, a person’s charac-
teristics, demographic characteristics, experience, mood, invol-
vement, emotions, exhibition type, museum type, social context
of who you visit the museum with, how your social group looks
at museum visits (social approval/cultural capital), how you
identify with other visitors (social identification) et cetera (e.g.
Van Vliet, 2009; Sheng & Chen, 2012; Del Chiappa, Andreu &
Gallarza, 2014; Kottasz, 2014). Few of these aspects can be
found in Forrest’s model; only ‘motivations and goals’ are
explicitly named in the end as visitor aspects, and based on the
empirical material the revised model sees the addition of
personality characteristics such as arousal seeking – although
this element was already there in the original model of
Mehrabian & Russel (1974, p. 8). Also in Forrest’s discussion of
different contextual aspects of the visitor experience, there are
enough points of departure to be found to enrich the model.
But as is, it remains stuck in the 'environmental properties', and
lacks, for example, anything related to social context as covered
in the work of John Falk (Falk & Dierking, 1992). Furthermore,
the model’s components have been only slightly elaborated
36
upon in terms of content. For the ‘environmental properties’
there are enough proposals (Baker, Bitner), including the
discussion about research into individual environmental cues
and a more holistic approach. Forrest seems to be open to the
latter (e.g. “Such findings reinforce the need to research
atmospheres holistically and in context” p. 52) but chooses to
research only one limited set of stimuli (design appearance)
resulting in the model being neither fish nor fowl. And finally,
the comment about “visitor experience should encompass
affective elements as well as cognitive and behavioral
responses” (p. 80) is perhaps a new insight for the visitor studies
field but adds little to current research into atmospherics. The
question is how these aspects relate to each other and ‘react’ to
the appraisal and reappraisal of the environment. A concept
pair such as approach/avoidance (see above) can already give a
more specific and directly testable interpretation – something
that Kottasz (2014) at least does attempt but Forrest does not.
Forrest’s model as a general atmospheric model contributes little to
the models that already exist (e.g. Bitner, Kottasz). In fact, it’s but a
pale mirror of the theoretical and empirical knowledge that already
exists. It’s also a missed opportunity for what Forrest herself so
nicely formulates: “The challenge for researchers is thus to develop
theoretical frameworks that have the capacity to incorporate the full
spectrum of the visitor experience, ranging from the public and
social aspects to the deeply personal” (p. 71).
37
Figure 3:
Forrest’s Atmospherics Model
(Forrest, 2014)
In the end, Forrest studies three aspects of the perceived
atmosphere: design appearance (the visual impression that the
environment makes via such things as light and color); spatiality
(architectural characteristics of the space and its layout), and
information rate (the impression of the complexity of the space, the
effort that is needed to use that space). At different exhibitions at
the South Australian Museum, she collected both qualitative and
quantitative data via visitor research. This led to, among other
things, to the development of a measuring instrument called the
Perceived Atmosphere Instrument (PAI). This instrument consists of
30 semantically differential items that focus on describing a space’s
atmosphere, such as dark/light, active/passive, cozy/formal et
cetera.13
38
Environmental
Properties
Visitor
Motivations and
Goals
Perceived
Atmosphere
- Design
appearance
- Spatiality
- Information
rate
Visitor
Responses
- Cognitive
- Affective
- Behavioural
A quantitative analysis of the 602 completed PAI questionnaires
delivers four factors: vibrancy (with traits such as vibrant, striking,
dynamic, energetic), spatiality (wide, spacious, open), theatricality
(winding, modern, new) and order (ordered, structured, flowing).
Three of the four factors align nicely with aspects isolated by Forrest
of the perceived atmosphere: design (vibrancy), spatiality (spatiality)
and information rate (order). Forrest has difficulty explaining the
factor theatricality while saying further research is outside the scope
of her research even though this factor shows the most variation
between the different exhibitions in the research.14
Forrest also studied the connection between perceived atmosphere
and visitor experience. Little relationship was found between
perceived atmosphere and her 15 dimensions of visitor experience
save for a found correlation between vibrancy and excitement
and fascination, which while significant, only explains 12% to 13%
of the total variance. Other relationships studied by Forrest were:
the ‘affective responses’ (consisting of affective engagement,
displeasure and relaxation) and cognitive responses (consisting of
cognitive engagement and cognitive overload). She summarizes
these results with: “This indicates that visitors feel more affectively
and cognitively engaged, more relaxed and less overloaded and
dissatisfied in environments they perceive to be more vibrant,
ordered and spacious” (p. 175).15
Forrest’s research is one of the most extensive studies of atmosphere
in museums. However, the building up of theory is only beginning:
“Theory in this area [visitor centered investigations of the exhibition
environment] [is] at a relatively early stage of development” (2014,
p. 83). Of course, there are already theories in the field of visitor
studies, and Forrest integrates several of these in her study but it
39
remains fragmented. The segmenting of the public is given a lot of
attention, such as the IPOP model (Pekarik et al., 2014), which
posits four primary visitor interests16 that determine where one’s
attention is directed, what the visitor does, and how the visitor
reacts (but then without explaining why it must be these four
interests). Furthermore, many proposals exist on how to categorize
visitors (see Van Vliet, 2009), as well as on the motivations of
museum visitors and learning in museums. In a review article,
Kirchberg & Tröndle (2012) discuss five additional general theories
about visitor experience in museums, including Falk & Dierking’s
contextual learning model and Csikszentmihalyi’s flow model. With
atmosphere not being a specific point of attention within these
models, we will not evaluate the possible consequences these
theories may have on how to look at museum atmospherics. In the
summary offered by Kirchberg & Tröndle, where they integrate
different models, no elements are offered that we have not already
encountered above: “Overall, the studies exhibit a rather
homogeneous kind of knowledge concerning visitor experiences in
the museum. A predominant resemblance is the general idea of
chronology and causality, perpetually using the same underlying
schema. There are always social, personal, or physical characte-
ristics (pre-visit parameters) that influence the visit experiences
(satisfying, confirming, or aesthetic). Subsequently, the effects of the
visit experiences are always some kind of utilitarian measures of
post-visit satisfaction and reward consequences, either cognitive or
emotional” (2012, p. 447-448).
40
How to measure atmospherics?
The big question remains… How do you measure atmospherics?
We can now finally make a proposal based on the research and
theory discussed above. However, it must be said that not all the
discussed studies explicitly describe how atmosphere is studied or
measured. Some just name a few sample questions (e.g. Michon,
Chebat & Turley, 2005); others just mention a few catchwords used
in the data analysis without citing the actual questions (e.g. Mattila
& Wirtz, 2001); and yet others just refer to a selection of questions
from other studies without actually listing the selection (e.g. Poncin
& Mimoun, 2014). In addition, we are focusing here on measuring
atmosphere using a questionnaire, this method is not only the most
often used, but is also a very economical research method and has
high response rates compared to other methods. Other research
methods are also possible: may it be qualitative through interviews
(e.g. Schorch, 2013) or diaries/essays (e.g. Henry, 2000), or
quantitative in the form of measuring the position and walking
behavior in the museum using sensors or Wi-Fi tracking (e.g.
Tröndle, 2014) (see Van Vliet, in prep. for a discussion).
In the described studies on atmospherics, four components appear
regularly and play a role in every presented ‘model’: environmental
cues, perceived atmosphere, felt emotion and approach/avoidance
(see also Milliman & Fugate, 1993). We will go through these
components one by one. However, this neither means that these
components can determine the full experience of atmosphere, as
we have seen personality traits but also mood, involvement and
other factors have their influence on atmospherics. Nor does this
means that these will be the only components measured in the
atmospherics research. Attention also needs to be directed on
41
aspects that the visitor ‘brings along’, such as expectations (Sheng &
Chen, 2012; Kottasz, 2014), motivations (Kaltcheva & Weitz, 2006;
Sheng & Chen, 2012; Forrest, 2014; Kottasz, 2014) and mood
(Kottasz, 2014); the ‘effort’ that a visitor must exert during a visit,
such as cognitive overload and cognitive engagement (Brenner,
2016; Forrest, 2014), fatigue (Jeong & Lee, 2006); and the ‘reaction’
of the visitor to the visit, such as the experienced quality (Baker et
al., 1994; Donovan et al., 1994; Baker et al., 2002; Chebat &
Michon, 2003; Michon et al., 2005; Hume, 2011), satisfaction
(Mattila & Wirtz, 2001; Baker et al., 2002; Eroglu et al., 2003;
Jeong & Lee, 2006; Hume, 2011; Del Chiappa et al., 2014; Poncin
& Mimoun, 2014) and loyalty (Baker et al., 2002; Kaltcheva &
Weitz, 2006; Bonn et al., 2007; Poncin & Minoun, 2014). All these
components can be put into a mutual relationship within a model
of experiencescapes (see Van Vliet, 2012).
Environmental cues
Almost all the cases presented here of research on the effect of
certain environmental stimuli on visitors follow Baker’s categoriza-
tions of ambient, design and social (Baker et al., 1994; d’Astous,
2000; Baker et al., 2002; Bonn et al., 2007; Harris & Ezeh, 2008;
Reynolds & Harris, 2009; Kottasz, 2014; Muhammad, Musa & Ali,
2014). Jeong & Lee (2006) use another category they call ‘physical
environment’, which includes environmental stimuli that we’ve
encountered in other studies, such as illumination, noise and visitor
density. Elbachir (2014) chooses for music, odor and store design
from a ‘sensory marketing’ perspective where the store design
represents the visual aspect. The use of these items fits seamlessly
with those items used in studies that are based on Baker. On
occasion, an addition is made to Baker’s trio, such as the ‘exterior’
42
aspect (e.g. Reynolds & Harris, 2009; Kottasz, 2014) where, for
example, questions are asked about the building itself or parking
availability; or the aspect of ‘kinect quality’, as the appreciation of
the store with regard to the movements and gestures that can be
performed during the shopping trip (Bonnin & Goudey, 2012).
The three categories are usually investigated using a limited
number of elements, often 3 or 4 items per category. In most cases,
use is made of a 5-point or 7-point Likert scale from ’strongly
disagree’ to ‘strongly agree’. Examples of items are: “This facility
has good lightning” (Bonn et al., 2007), “The employees were well
dressed and appeared neat” (Baker et al., 1994), “The restaurant
had clean walkways and exits” (Harris & Ezeh, 2008), and “It was
easy to move around the outlet” (Reynolds & Harris, 2009). The
choices of questions seem quite arbitrary, with one study asking
about music while another study might focus on color. This has to
do with an environment’s vast number of possible stimuli they
simply cannot all be investigated. Custers et al. (2010) came up
with 31items for lighting alone; while d’Astous (2000) generated 38
possible irritating elements in a store. Studies by Baker et al. (1994),
Harris & Ezeh (2008) and Reynolds & Harris (2009) involve the
most extensive questioning around environmental stimuli. A
selection of questions can be found in Appendix 1.
Research into environmental stimuli is certainly enriched by the
careful examination of the effects of an environment’s specific
elements. However, one must remain aware of the mutual influence
of that the stimuli in the total space have on each other. In terms of
method, one could take an alternative experimental approach
where a small but relevant change is made in the environment, for
example by replacing an artwork, or making a specific manipu-
43
lation such as with the layout of the exhibition (see for example
Tröndle et al., 2014). However, such an approach requires signifi-
cant cooperation with, in this case, the museum. The most impor-
tant point remains the previously mentioned theoretical objection
involving how a visitor’s experience is more holistic in nature and is
therefore difficult, or even impossible, to reduce to individual
environmental stimuli. Therefore, it seems necessary to take a
position in this discussion before proceeding to measuring the
effects of environmental stimuli.
Perceived Atmosphere
We describe a space by using words such as cozy, cramped,
uplifting, organized, inspiring or gloomy. In fact, there is no
shortage of terms to describe the impression that a space gives. In
an early study, Kasmar (1970) already found 500 different
adjectives used by test subjects to describe just a few different
spaces. When measuring perceived atmosphere, it’s essential to
differentiate between a space’s descriptive description and its
evaluative description. The difference is not black-and-white since
we are dealing with the meaning of words that are used to describe
a space in a more objective or subjective manner. However, the
difference is not meaningless: for example, you can describe a
space as being full or busy, but then evaluate it as claustrophobic (a
train at rush hour) or as stimulating (a sold-out concert hall).
In both museum studies (Kent, 2010; Forrest, 2015; Brenner, 2016)
and other studies into atmospherics (Fischer, 1974; Donovan &
Rossiter, 1982; Vogels, 2008; Rayburn & Voss, 2013), you can find
examples of descriptive terms being used to measure the
experienced atmosphere. The used terms vary greatly, with 64
44
different adjective pairs being used in this small set of studies,
measured via a semantic differential.17 There are 12 adjective pairs
that are used in more than 1 study: active/passive, dramatic/plain,
warm/cool, ordinary/striking, vibrant/dull, hard/soft, symmetrical/
asymmetrical, small scale/large scale, large/small, crowded/
uncrowded, dynamic/static (2x), simple/complex (4x).
A more limited, yet qualitative, selection of terms can be made by
applying three criteria that exclude the following: 1) terms related
to a specific element in the space such as light, color and sound
(e.g. well-lit/dark, colorful/uncolorful, quiet/noisy, airy/not airy); 2)
terms with an evaluative connotation (e.g. vibrant/dull, energetic/
serene, cozy/formal, interesting/monotonous); 3) terms that are
abstract descriptions of the space (e.g. hard/soft, dynamic/static, far/
close, hidden/obvious). The 20 remaining adjective pairs cover 7
aspects of the space:18
1. Order: ordered/jumbled, cluttered/uncluttered, symmetrical/
asymmetrical;
2. Coherence: structured/unstructured, patterned/random,
organized/random;
3. Variety: varied/repetitive, similar/contrasting, redundant/varied,
non-uniform/uniform;
4. Scale: small/large, small scale/large scale;
5. Crowdedness: sparse/dense, roomy/cramped, crowded/
uncrowded, crowdy/empty;
6. Spaciousness: open/enclosed, spacious/confined, wide/narrow;
7. Complexity: simple/complex.
These items can be questioned via the sentence “I would describe
the space as …” and using a 5-point Likert scale (‘Totally disagree’
‘Totally agree’). It’s advisable to cover both positively and
45
negatively formulated items. Another option, and one that fits with
the named studies that use these terms, is to use a 7-point semantic
differential since the terms lend themselves to being opposites (see
Appendix 1).
Museum studies rarely use evaluative terms to measure atmo-
spherics. Only Forrest (2014) used two general items (see below).
Retail studies, however, often use evaluative terms to measure
atmospherics (Fischer, 1974; Mattila & Wirtz, 2001; Sherman,
Mathur & Smith, 1997; Spangenberg, Grohman & Sprott, 2005;
Yüksel, 2007; Vogels, 2008; Custers et al., 2010; Bonnin & Goudey,
2012; Rayburn & Voss, 2013; Elbachir, 2014; Moes & Van Vliet,
2017). With the exceptions of Vogels (2008), Custers et al. (2010)
and Bonnin & Goudey (2012), these studies use a semantic
differential scale for measurement. A relatively large similarity exists
in what adjectives are used: only 26 different adjective pairs are
used in these studies19, of which half appear in more than 1 study:
uninteresting/interesting (2x), unmotivating/motivating, tense/
relaxed (3x), boring/stimulating, negative/positive, colorful/drab,
un-lively/lively (4x), good/bad, bright/dull, attractive/unattractive,
comfortable/uncomfortable, pleasant/unpleasant (5x) and depres-
sing/cheerful (7x).
Also here, one can use three qualitative criteria to limit the number
of terms by omitting the following: 1) terms related to a specific
element in the space such as light, color and sound (e.g. colorful/
drab, cluttered aisles/uncluttered aisles, pleasant smelling/unplea-
sant smelling, courteous salespeople/discourteous salespeople); 2)
terms that are descriptive (e.g. roomy/cramped, large/small, well-
organized layout/unorganized layout); 3) terms that are abstract
descriptions of the space (e.g. good/bad, negative/positive,
46
innovative/average). As a result, only 13 adjective pairs remain (see
Appendix 1). Several other adjective pairs can be added based on
specific research. Firstly, from the found dimensions (see above):
mysterious (mysterious/clear) and novelty (novel/familiar). Secondly,
Rayburn & Voss (2013) use the adjective pair charming/obnoxious,
which is an interesting addition. And thirdly, the study of Vogels
(2008) has a few terms that offer a substantial contribution:20
intimate (intimate/distant), cozy (cozy/formal), hostile (hostile/
friendly) and threatening (threatening/inviting). All these twenty
items can be questioned using a 7-point semantic differential (see
Appendix 1).
In addition to differentiating between the descriptive and the
evaluative, we must also decide whether to choose for a more
holistic basis (see above). Such an approach is not at odds with the
already presented items – on the contrary. The descriptive and
evaluative terms already in fact ‘transcend’ the concrete
environmental stimuli, as those measured by the environmental
cues (see above), to capture more of a total impression as
intangible atmospheric cues as Kottasz (2014) calls them. Those few
studies that aspire for a more holistic approach also often use the
same (evaluative) terms, such as pleasant, uncomfortable (Baker et
al., 2002), boring, lively, interesting (Chebat & Michon, 2003),
complexity, order (Gilboa & Rafaeli, 2003) and (un)comfortable,
charming/obnoxious, (dis)pleasing, (un)appealing (Rayburn & Voss,
2013). Another addition to a holistic measurement is to ask for a
total judgment about the visit, as Forrest (2014) did with her two
questions about how ‘enjoyable’ the exhibition was and whether it
was a ‘worthwhile experience’. While legitimate questions, they do
go further than a final judgment about the atmosphere. The same
argument arises with the ‘holistic’ questions used by Moes & Van
47
Vliet (2017) that include terms such as immersion, connection and
memorableness. While relevant concepts, they have more to do
with measuring the experience rather than being aspects of the
atmosphere. It is possible to apply Forrest’s more general questions
to explore the space, which would also connect more with the
studies that ask more general attitude questions related to the space
which often use such recurring words such as favorable/
unfavorable, positive/negative, good/bad, like/dislike, enjoyable/not
enjoyable (Eroglu, Machleit & Davis, 2003; Spangenberg, Grohman
& Sprott, 2005; Kaltcheva & Weitz, 2006; Bonn et al. 2007). These
questions can be asked using a 7-point semantic differential (see
Appendix 1) and should be enough to serve as input for the
“paramount” need, as argued by Farias, Aguiar & Melo (2014) for
“a scale that aims to measure customer’s retail experience in a
holistic way” (p. 95).
Felt Emotion
It seems that perceived atmosphere can be charted out nicely using
descriptive, evaluative and holistic questions. So, what added value
does asking about the experienced emotions provide? There are two
possible and complementary answers for this. One inadequate
yet undeniably practical answer would be: the clear majority of
atmospheric studies measured felt emotion, particularly when these
studies were about perceived atmosphere. The prominence of felt
emotion in the research is related to the importance given to the
studies of Mehrabian & Russell (1974) and Kotler (1973) – from
which a lot of research has been derived. These studies also gave an
explicit role to ‘emotional responses’ and ‘affective states’ as
intervening variables in the behavior reaction of people in a space.
Only those studies that mainly focused on researching environ-
48
mental cues often did not include felt emotion because they were
looking into what categories precisely existed, such as lighting with
Vogels (2008) and Custers et al. (2010) and irritating elements in
the store environment with d’Astous (2000); or they were studying
the relationship between environmental cues and dependent
variables such as service quality (Baker et al., 1994; Baker et al.,
2002), satisfaction (Harris & Ezeh, 2008; Reynolds & Harris, 2009)
or loyalty (Bonn et al., 2007).
The second answer is related to theory development. Over the last
decades an awareness has grown, based on empirical research, that
emotions have a greater coherence with perception and behavior
than just being an 'intermediate' variable. The perceivedness of a
situation is already an essential part of the emotional process – and
in fact are intrinsically linked with each other. Building on the work
of Magda Arnold, Richard Lazarus and others, new theories of
cognitive emotions have been developed wherein appraisal plays a
large (causal) role (Frijda, 1986; Scherer, 2009; Moors, Ellsworth,
Scherer & Frijda, 2013). While a complex discussion (see Van Vliet,
in press), a simplistic and previously mentioned example can
provide some insight: that of the difference between the descriptive
and the evaluative as exemplified by how a full space can be
regarded either as claustrophobic (a full train) or as stimulating (a
full concert venue). Here, nothing is being said of the emotions
being felt: a claustrophobic train can be paired with frustration but
also with joy from having a chance conversation. Meanwhile, a
stimulating full concert venue does not always have to be paired
with positive emotions stimulation can be paired with fear since
movement is now restricted. A different appraisal of the same kind
of situation stimuli can therefore be paired with different emotions
(see pages 52-56).
49
Based on the above answers, we can consider measuring emotions
as an important part of measuring atmospherics. The choices on
what emotions to measure and how to measure them are closely
related to a person’s theoretical view on what emotions are. Herein
we can roughly differentiate between three points of view: a
dimensional view (including PAD), the basic emotion theory and
the appraisal theory (Van Vliet, in prep.). These different theoretical
points of view lead to different lines of questioning.
In the previously discussed retail studies, emotions are most
commonly measured using the PAD model (Foxall, 1979; Donovan
& Rossiter, 1982; Donovan et al., 1994; Sherman, Mathur & Smith,
1997; Mattila & Wirtz, 2001; Chebat & Michon, 2003; Eroglu et al.,
2003; Gilboa & Rafaeli, 2003; Michon et al., 2005; Spangenberg,
Grohman & Sprott, 2005; Kaltcheva & Weitz, 2006; Yüksel, 2007;
Poncin & Minoun, 2014). Only a few cases, such as with Foxall
(1997) and Spangenberg, Grohmann & Sprott (2005), use the full
list of 18 items that formed the original basis of the PAD model
(Mehrabian & Russell, 1974) and which was also already proposed
by Dovovan & Rossiter (1982).21 In most cases, the dominance
items were not used. As for the other two dimensions, only 3 or 4
of the original 6 are usually used, and sometimes with other
wording. For pleasure, these are often the items: happy/unhappy,
pleased/annoyed, satisfied/dissatisfied, contended/depressed. For
arousal, the terms were often: stimulated/relaxed, excited/calm,
wide awake/sleepy, aroused/un-aroused. These words were queried
in the form of a semantic differential (see Appendix 1 for a list of
the original terms from Mehrabian & Russell, 1974).22
With museum studies, the PAD is used much less, with only Kottasz
(2014) applying it consistently. Other studies seem to make an
50
arbitrary choice of emotion words. In his study on the influence of
music, Brenner (2016) uses 10 emotion terms, such as irritated,
bored and confusing. Del Chappia et al. (2014) uses a complete
mixed bag of ‘emotions’, such as disoriented, surprised, waste of
my time (!) and learned something new. Based on preliminary
research, Forrest (2014) concluded that the PAD analysis provides
no useable results, and seeks refuge in the viewpoint of basic
emotions, despite her positive presentation of appraisal theory.
Forrest (2014) is the only found study that reaches back to the
theoretical view that there are basic emotions. Basic emotions are
universal, have a unique biological basis and have evolutionary
advantage (for example, fear helps avoid dangerous situations). In
addition, basic emotions can be easily recognized in facial
expressions and underlying biological processes. This view is also
described as a ‘discrete’ or ‘categorical’ take on emotions. These
basic emotions are by definition a limited set, although there is no
agreement on the actual number of basic emotions and which
emotions are precisely included. Silvan Tomkins distinguished nine
affects: interest, enjoyment, surprise, distress, anger, fear, shame,
dissmell and disgust. Carroll Izard came up with ten basic
emotions: interest, enjoyment, surprise, sadness, anger, disgust,
contempt, fear, shame/shyness and guilt. Her Differential Emotions
Scale (DES) measures these 10 basic emotions using three
adjectives for each. Robert Plutchik tallied eight basic emotions:
fear, anger, joy, sadness, acceptance, disgust, expectancy and
surprise. These are measured with the Emotions Profile Index (EPI)
where respondents build a score around these basic emotions using
62 forced-choice emotion descriptor pairs. A shorter measure was
developed with three adjectives for each emotion (Richins, 1997).
Despite the differences, a basic consensus exists on 6 basic
51
emotions: joy, anger, disgust, fear, sadness and surprise. As a whole,
the theory of basic emotions is not without criticism (Richins, 1997;
Van Vliet, in press). Forrest uses 24 items based on Plutchik’s theory
of 8 basic emotions. In Appendix 1 the 8 basic emotions mentioned
by Plutchik are included in the reference questionnaire with
different adjectives that can be used. There is no reason not to
include also the ‘additional’ basic emotions as mentioned by Izard
and Tomkins.
The appraisal theory, also known as the cognitive appraisal theory
(CAT), is currently the most attractive theory to explain emotions,
bot theoretically and empirically (Van Vliet, 1991, 2012, in press).
In short, the appraisal theory of emotion states that: 1) Emotions are
functional adaptive responses based on appraisals of features and
(action) affordances of the environment that are relevant to the
person’s well-being; and 2) Emotions are multi-componential
response patterns in which appraisals are the main causal
determinants of the (quality and intensity of) various other compo-
nents: subjective feeling, instrumental behavior, action tendencies
and physiological responses. The component view on emotions
leads to a process architecture involving discussions on the sequen-
cing of (sub)processes, interdependencies and feedback loops
(Frijda, 1986; Scherer, 2009). As an essential phase in emotions,
appraisals can be broken down into different stages, such as prima-
ry appraisal, establishment of relevance, and secondary appraisal,
the assessment of coping abilities (Lazarus & Folkman, 1984). The
theory can also work to define appraisal patterns that underlie
specific emotions (Frijda, 1986; Scherer, 2005, 2009). While still in
development in regards to how the specific mechanisms work (see
Moors, Ellsworth, Scherer & Frijda, 2013), appraisal theory is
already far more explicit in explaining the confluence of cognition
52
and emotion (and behavior for that matter) than the many other
models that list emotion, cognition and behavior as visitor
responses, but then without providing much explanation of their
interdependencies and workings (e.g. Forrest, but also Bitner). In
addition, over the last 30 years numerous empirical studies have
found substantial experimental evidence for many of the
predications provided by the appraisal theory (e.g. Scherer, Schorr
& Johnstone, 2001; Scherer, 2009).
In appraisal theory, only the assessment of all component changes
involved can provide a comprehensive measure of an emotion:
appraisal process, neurophysiological response patterns, action
tendencies, patterns of facial and vocal expression as well as body
movements, and subjective feelings. But: “Such comprehensive
measurement of emotion has never been performed and is unlikely
to become standard procedure in the near future” (Scherer, 2005, p.
709). Most research has focused on the process of appraisal, not
only because it is the most distinctive element in the theory
compared to other emotion theories, but also because appraisal is
the (causal) trigger that sets off a chain of response patterns: “If one
knows the result of an individual’s event appraisal on the major
checks, one can approximately predict what kind of emotion he or
she will most likely experience (…) what motor expressions, action
tendencies, and physiological changes can be expected to underlie
this experience” (Scherer, 2009, p. 1326) – a statement that has
been backed by several experimental studies (e.g. Frijda, Kuijpers &
Ter Schure, 1989; Roseman & Evdokas, 2004). Considering
atmospherics research, the appraisal component is also of primary
interest because it focuses on the assessment of environmental
stimuli. Herein, the main viewpoint of appraisal theory is that:
“Appraisal theories assume that there is a variable relation between
53
stimuli and emotions, but a stable relation between appraisals and
emotions. In general, the same appraisals lead to the same
emotions; different appraisals lead to different emotions.” (Moors,
Ellsworth, Scherer & Frijda, 2013, p. 121). In other words, different
emotions may be elicited by the same situation and the same
environmental stimuli when people differ in their appraisal of the
situation.
The appraisal process is made up of different variables that play a
role in the detection and assessment of the significance of the
environment for a person’s well-being. Several appraisals variables
have been proposed and tested, not only by emotion researchers
(e.g. Frijda, 1986; Scherer, 2009), but also by researchers in the
context of, for instance, consumer behavior (e.g. Watson & Spence,
2007), tourism (e.g. Hosany, 2012) and leisure (e.g. Ma & Gao,
2013). However, as far as could be established, no such variables
have been tested in atmospherics research.23 The most recurring
and widely agreed upon appraisal variables are:
Goal relevance: How relevant is this event for me, for my
concerns?
Goal congruence/Outcome desirability: Is this event conductive
to fulfilment of my goals?
Certainty/Outcome predictability: How do I perceive the
likelihood of a particular outcome?
Agency: Is the event caused by myself, someone else, or
impersonal circumstances?
Controllability: Do I have control over the event?
Coping potential: How well can I cope with the event?
Novelty/Expectancy: Does the event deviates from what I
expected?
54
Other appraisal variables that have been proposed are: urgency,
intentionality, legitimacy or fairness, norm compatibility (relevance
for self-concept and social norms and values), pleasantness,
modifiability, focality, attention, anticipated effort (Smith &
Ellsworth, 1985; Frijda, 1986; Roseman, Antoniou & Jose, 1996;
Watson & Spence, 2007; Scherer, 2009) and reality level (van Vliet,
1991). This growing list of appraisal variables is not a weakness of
the theory but its strongpoint: “Appraisal theories allow variation in
the number of appraisals that are made (appraisal variables that are
processed). If only a few appraisals yield results, the emotional ex-
perience is relatively undifferentiated and global, if many appraisals
are made, the emotional experience is highly differentiated and
specific” (Moors, Ellsworth, Scherer & Frijda, 2013, p. 121).
The scores on the appraisal variables result in a specific pattern or
profile that represent a certain emotion. For instance, ‘agency’
differs between surprise and anger (others), and pride, shame and
guilt (oneself as agent); ‘certainty’ differentiates between hope and
fear (uncertain) and happy and proud (certain). Fear and anger have
different appraisal profiles and can therefore be easily dis-
tinguished: anger is caused by goal incongruence, others or circum-
stances (agency), in an event that is thought to be modifiable
(control), whereas fear is caused by uncertainty of the outcome and
lack of control. While both are unpleasant and lead to arousal,
there is more to it than that. Also, more uncommon emotions such
as delight have an appraisal profile, it is caused by high goal rele-
vance, high goal congruence, certain outcome, circumstances
(agency) and unexpectedness. Much research effort has gone into
mapping appraisals profiles onto specific emotions (Smith &
Ellsworth, 1985; Frijda, 1986; Smith & Lazarus, 1993; Roseman,
55
Antoniou & Jose, 1996; Scherer, Schorr & Johnstone, 2001; Scherer,
2009).
The measurement of felt emotion through appraisal variables can
be done by asking question on the specific appraisal variables.
These questions can be extracted from the several studies
mentioned in this discussion – however, this is not without its
problems (see Schorr, 2001). Or one can use the Geneva Appraisal
Questionnaire (2002) which is, however, likely too extensive for
many cases. In Appendix 1, a selection of questions is proposed. It’s
important to ask about the cause of the experienced emotion and
not to ask for a characterization of the content of the emotion itself.
With scores on these questions and the resulting profiles, one can
look up corresponding emotions in the literature. Or one can also
ask for specific subjective feelings through use of emotion words
and then do one’s own mapping based on the gathered data. But
either way: “The issue of predicting emotion names from appraisals
and action readiness is, however, complex” (Frijda, Kuipers & Ter
Schure, 1989, p. 213). One final remark concerns the fact that most
research on appraisal up until now has targeted ‘modal’ or
‘elementary’ emotions - namely emotions focused on adapting to
events that have important consequences for our well-being: joy,
anger, sadness, fear, disgust. Other specific groups of emotions,
such as aesthetic emotions, emotions related to specific situations
(e.g. shopping) and more specific emotions such as wonder,
admiration, bliss and solemnity, have not yet received much
attention.
56
Approach/Avoidance
The relationship of a person to a space in terms of behavior
(intention and readiness) is expressed with the concept pair
approach/avoidance. Within retail research into atmospherics, this
has been measured in various studies, from the very first study by
Donovan & Rossiter (1982) to later studies (Foxall, 1997; Sherman,
Mathur & Smith, 1997; Mattila & Wirtz, 2001; Eroglu et al., 2003;
Gilboa & Rafaeli, 2003; Kaltcheva & Weitz, 2006; Yüksel, 2007).
Within museum research, only Kottasz (2014) has measured
approach/avoidance. In the study by Forrest (2014, p. 122), there is
1 item that seems to refer to approach/avoidance (“This environ-
ment really invites me to explore it”), but this item is placed under
the construct cognitive engagement.
Many studies use similar concrete items, since they mostly build on
the study of Donovan & Rossiter (1982) and use the categories of
Mehrabian & Russell (1974). One exception is the study by
Sherman, Mathur & Smith (1997) that measures approach/
avoidance using concrete metrics such as ‘number of items
purchased’ and ‘amount of time spent in the store’. Sometimes an
item is used that is not properly put into practice, such as ‘I like this
location’ (no behavior intention) in Yüksel (2007) and ‘I like the
store environment’ in Sherman, Mathur & Smith (1997)24, or a
question on fulfilled expectations such as the item ‘the current visit
has entirely met my expectations’ used by Kottasz (2014).
The items can be separated into the four categories of Mehrabian &
Russell (1974) and Donovan & Rossiter (1982): questions on
wanting or not wanting to leave the space (avoidance or approach);
questions on wanting or not wanting to explore the space further;
57
questions on seeking or avoiding contact with others in the space;
and questions on wanting or not wanting, or being able, to work on
a difficult task within that space. There’s something to be said about
dropping the last category, as Foxall (1997) argues, since it’s less
directly relevant in the context of a store or museum. However, for
the sake of completeness, the category remains included here.
In most of the discussed studies, a 5- or 7-point Likert scale is used;
only Ergolu et al. (2003) use a semantic differential and place
approach and avoidance opposite each other. However, it’s plau-
sible that approach and avoidance each have their own repertoire
of behaviors as is also evident from the various coping strategies
people have on hand (Van Vliet, 1991; in press). It’s therefore re-
commended to use separate questions for approach and avoidance
using, for example, a 7-point Likert scale. Since with approach/
avoidance it’s about a certain degree of action tendencies, it’s wise
to use suitable descriptions for the Likert scale, such as ‘not at all -
extremely so’ as already proposed by Mehrabian & Russell (1974)
(See Appendix 1).25
Atmospheric responsiveness
Since many moderators and mediators have been mentioned that
influence the experiencing of a space (see above), these will have
to be looked at elsewhere to see how they can be measured. But
we will make one exception. The influence of personal charac-
teristics on the experiencing of a space runs like a recurring thread
in the explanatory models from Mehrabian & Russel (1974) to
Forrest (2014). These characteristics can be general ones, such as
the disposition for sensation seeking (Mehrabian & Russell, 1974;
Zuckerman, 1979). However, specific research has also been done
58
into so-called ‘environmental dispositions’ – the difference ways
people ‘habitually interact with the environment’. The most well-
known measuring instrument for environmental dispositions is
likely the Environmental Response Inventory (ERI) from McKechnie
(1970; 1977) that consists of 184 statements about daily situations.
While the ERI measures 8 underlying factors, it does not
specifically focus on atmospherics. Grossbart et al. (1990) did show
however that these underlying factors relate to each other in
varying degrees in how clients react to store atmospherics. Other
examples are Mehrabian’s Stimulus Screening Questionnaire
(Mehrabian, 1977) which later became the Trait Arousability Scale
(TAS) and also Aiko Satow’s Environmental Sensory Stimulus Scale.
Although these questionnaires contain some useful items (e.g. “My
moods are not quickly affected when I enter new places”) they are
not directed at specific atmospheric dispositions.
A specific disposition does exist that relates directly to atmo-
spherics: atmospheric responsiveness. This can be characterized as
“the extent to which environmental characteristics influence
customers’ decisions on where and how to shop and how much
time to spend shopping” (Eroglu, Machleit & Davis, 2001, p. 181).
The only found study that actually measures atmospheric
responsiveness is one from Eroglu, Machleit & Davis (2003), where
four items are used in the context of a store. With some fine-tuning,
these items can also be used for other spaces, including museums
(see Appendix 1).
59
Conclusion
This study set out to propose a measuring tool for atmospherics
based on empirical and theoretical studies available in marketing
literature and museum visitor studies. Since empirical testing is
intertwined with a theoretical perspective, it’s impossible to design
one ultimate atmospherics survey. Regardless, the evaluation of
current research has brought forward several recurring components
and items in the measurement of atmospherics as well as the
theoretical decisions to make in selecting components and items.
The proposed set of survey items is largely based on earlier
measurements of atmospherics in a wide range of studies, with
some fine-tuning in the exact wording of items and some
methodological refinements (such as not asking two things in the
same question, e.g. ‘Feel friendly and talkative’) and harmonization
(such as the consequential use of a 7-point measurement scale). The
items need further refinement depending on the context of use:
items can be added (for instance more or different environmental
cues items), omitted (for instance several items in the PAD
dimensions), or rephrased to be more appropriate for the situation
at hand. These adjustments will have consequences for the
interpretation of the results but still it is believed that the presented
reference survey item list will help to push research on
atmospherics forward and make results more reliable and
comparable over different situations.
60
Notes
1) A different historical background on the concept of atmospherics goes
back to Walter Benjamin’s concept of aura, its interpretation by the
philosopher Genot Böhme as atmospherics and the incorporation of
this idea in an aesthetic theory (see Dorrian, 2014). We don’t explore
this historical line since it ultimately does not focus on making
atmospherics measurable.
2) Mehrabian & Russell (1974) already observed this: “Most environ-
ments that are encountered are much more complex and
simultaneously include stimulation in all the sense modalities, as well
as along several stimulus dimensions within each modality (e.g. the
many colors in a typical setting, together with various combinations of
sounds, odors, temperatures, or textures). Many of these stimulus
components also vary in time. The combination of all these variations
results in different overall patterns, contrasts, and levels of information,
which then determine responses” (p. 77). For this ‘combination’, they
use the concept of information rate. This concept stays very close to
the characteristics of environmental stimuli and differs greatly from the
appraisal processes that are inherent in a concept such as ‘perceived
atmosphere’. Hence with Mehrabian & Russell, the information rate
has a direct effect on, for example, arousal.
3) This argument is still being made in recent publications. For example,
Tzortzi (2016) talks about internal and external architectural elements
of a building having a “differential advantage” in the ‘“competitive
leisure marketplace”.
4) That is not to say that in the interim period nothing happened in
atmospherics research. For example, there’s the study from Grossbart
et al. (1975). However, Donovan & Rossiter’s study from 1982 can be
considered a precursor of much of the research that followed.
5) See also earlier discussions on typologies of situations, such as in
Kasmar (1970), Moos (1973) and Belk (1975), and also on the
structure of situations (‘frames’), in Goffman (1974). A more recent
proposal on categorization of environmental stimuli is, for example,
the study by Rayburn & Voss (2013), which distinguishes between
perceived organization, perceived style and perceived moderness.
However, this is a reshuffle of elements that have been mentioned
before, mainly from the categories design (Baker) and spatial layout
(Bitner).
61
6) See, for example, Penz & Hogg (2008) who use the PAD model in
their study to investigate mixed emotions in consumer behavior, and
for example find that 'arousal' in traditional stores does not correlate
with emotional states such as enjoyment, pleasure and dominance (!),
in contrast to online stores. Furthermore, they do not find a clear
distinction between online and offline in regard to the mediating
effects of mixed emotions. In the discussion they do not question the
PAD model, whereas in my opinion this should have been done given
these results and the existence of other emotion theories that could
possibly explain these results conclusively.
7) Chebat & Michon (2003) hold the view that in Bitner’s servicescape
model pleasure and arousal precede cognition. They give no
arguments to support this statement (p. 531). This seems to be an
incorrect interpretation of Bitner’s proposals for two reasons: 1) Bitner
explicitly talks about ‘perceived servicescape’ that can be interpreted
as the moment of inferences or appraisal; 2) Bitner’s model includes
‘internal processes’ under which cognition, emotion and physiology
collectively fall together, with no specific sequentially.
8) The wording of Donovan & Rossiter (1982) varies slightly with that of
Mehrabian & Russell (1974). They cover the ‘desire to work in the
situation’ in the 4th category, with on one hand the question whether
the space offers a good chance at completing a difficult task, and on
the other hand the straightforward question on whether there is a
‘dislike’ in working in this particular space.
9) The determining factor in differentiating empathy from identification is
called the 'self-other distinction': ‘I imagine how the other
feels’ (empathy) versus ‘I coincide with that person’ (identification). In
the first case, emotions arise as a reaction to what other person feels
(compassion, sympathy, admiration). In the second case, you are
experiencing the same emotions as the other. The arts, literature, film
and television of course ‘play around’ with these reactions to induce
empathy or distance in the viewer. Identification can be subdivided
further into different types: wish identification, similarity identification
et cetera. For an in-depth discussion and analysis, see Van Vliet (1991).
10) Not limited to museums, similar observations can be made in other
sectors. For example, with the performing arts, “despite the great
investment of the last twenty years in developing strategic marketing
knowhow, we do no know enough about and do not know how to
describe – the benefits that audiences derive from arts experien-
ces” (Radbourne, Glow & Johanson, 2013, p. xiv).
62
11) Forrest (2014) also refers to a “history of cross-fertilization between
retail and museum design, with the same practitioners undertaking
both over the course of their careers” (p. 32).
12) This contrasts with Kottasz (2014) who sees cues having an immediate
effect on emotions.
13) In the development of a measurement scale, evaluative terms were
originally included, such as cheerful, exciting and gloomy (Forrest,
2014, p. 98). But in the end, these were removed: “The evaluative
terms appear to be less useful in characterizing the exhibition
environment than the descriptive terminology, as they do not
characterize the environment beyond the simple positive or negative
judgments” (p. 104). This is a striking argument for several reasons: 1)
From a ‘perceived’ or appraisal standpoint, the attention should
actually be directed to the evaluative terms instead of the purely
descriptive terms, since this says more about the personal evaluation
of the space than more ‘objective’ terms, such as light/dark, full/empty
et cetera; 2) This ‘simple judgment’ argument does not return when
Forrest reaches back to the PAD model where a ‘simple’ dimension
such as ‘valence’ (pleasant/unpleasant) plays a big role; 3) In the
results of the measured emotions, ‘displeasure’ is one of the three
found factors (p. 119). Forrest makes no comment here about its
‘usefulness’ (or lack of it). In the end, Forrest uses two evaluative
questions to measure the ‘general perceptions of pleasantness’ (p.
155). When the measurements are analyzed, she concludes: “These
results show that the Perceived Atmosphere Instrument offers a
characterization of the environment that is more nuanced than a
simple evaluative judgment” (p. 156). This conclusion is of course
somewhat skewed since if you base an analysis on 30 specific items as
with the PAI and then compare it to 2 general items, then it’s not
surprising that the 30 specific items give a more nuanced image.
14) It’s of course somewhat of a 'self-fulfilling prophecy' to statistically
find 3 factors that coincide with 3 presumed aspects for which you
have selected specific items to measure them with. Indeed, you show
that you can separately measure these aspects. But it goes too far to
say that you have hereby identified the “underlying dimensions of
perceived atmosphere” (p. 113). For this, you also have to include all
the factors in the environment – including the social aspects, for
example. Now you still don’t know if, for example, social factors
interacting with design factors can expose other ‘underlying’
dimensions.
63
15) More precisely: “Vibrancy is the strongest predictor of both affective
and cognitive engagement. In addition, there is a weak positive
relationship between Spatiality and Relaxation, and a weak negative
relationship between Order and Cognitive Overload.” (Forrest, 2014,
p. 177)
16) Namely: 1) Ideas: an attraction to concepts, abstractions, linear
thought, facts and reasons; 2) People: an attraction to human
connection, affective experience, stories and social interactions; 3)
Objects: an attraction to things, aesthetics, craftsmanship, ownership,
and visual language; 4) Physical: an attraction to somatic sensations,
including movement, touch, sound, taste, light, and smell (Pekarik et
al., 2014, p. 6).
17) In 8 cases, there is a correspondence with the 66 ‘environmental
descriptors’ of Mehrabian & Russell (1974): cluttered/uncluttered,
crowded/uncrowded, dark/light, tidy/untidy, large/small, simple/
complex, old/new, warm/cool. This modest correspondence may be
related to Mehrabian & Russell not making any distinctions between
descriptive and evaluative terms.
18) These are the five previously mentioned underlying dimensions, with
the addition of ‘scale’ and ‘crowdedness’ from Mehrabian & Russell
(1974). The adjective pairs strongly resemble the 14 adjective pairs
that Mehrabian & Russell used to measure the level of ‘information
rate’ of an environment only 5 adjective pairs do not appear in the
list presented here. Three of these (novel/familiar, usual/surprising,
common/rare) are considered to be more evaluative terms. The
adjective pair intermittent/continuous could be added to variety, and
immediate/distant to spaciousness.
19) Twelve of these match the list of 66 ‘environmental descriptors’ in
Mehrabian & Russell (1974).
20) Vogels (2008) does not use adjective pairs. In fact, for her terms
intimate, cozy, hostile and threatening, opposite terms were added.
21) A number of small differences exist between the 18 items from
Mehrabian & Russell (1974) and the 18 items from Donovan &
Rossiter (1982):
- Contented/melancholic is replaced by contented/depressed.
- Important/awed is replaced by important/insignificant.
- In control/cared for and autonomous/guided no longer appear with
Donovan & Rossiter (1982). The items restricted/free and crowded/
overcrowded have been added in their place.
64
22) Besides the semantic differential other forms are available, such as an
affective grid as used by Falk & Gillepsie (2009) wherein arousal and
pleasantness are asked about at the same time. There’s also the Self-
Assessment Manikin (SAM) that works with pictograms (Bradley &
Lang, 1994). See Van Vliet (in prep.) for a discussion on the different
research methods used in the measuring of emotions.
23) Cheat & Michon (2003) is the only found study on atmospherics that
refers to the appraisal theory, but it does not use specific appraisal
items in its questionnaire. Forrest (2014) refers also to appraisal theory
but fails to implement this in her own empirical research.
24) And actually, also in the original study from Donnovan & Rossiter
(1982): “Do you like this store environment?”. Also, the item “Would
you enjoy shopping in this store?” puts more emphasis on ‘enjoyment’
than it has to do with behavior (intention).
25) Additional items can be extracted from action readiness dimensions in
appraisal theory such as avoidance (“I wanted to have nothing to do
with something or someone, to be bothered by it as little as possible,
to stay away”), attending (“I wanted to observe well, to understand, or
I paid attention”), and be with (“I wanted to stay close, to be receptive
to someone”). See for example Frijda, Kuipers & Ter Schure, 1989).
65
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Appendix 1: Survey items for measuring atmospherics
(Environmental cues: ambient)
The music was appropriate (+)
The place was clean (+)
The temperature in the place was too hot (-)
The smell of the place was bad (-)
(Environmental cues: design)
The color scheme of the space was pleasing (+)
The physical facilities were attractive (+)
Directions in the place were inadequate (-)
The layout of the place was confusing (-)
(Environmental cues: social)
The employees appeared neat (+)
The employees had a negative attitude (-)
Other visitors behaved in an unpleasant manner (-)
It was enjoyable being around other visitors (+)
(Environmental cues: exterior)
The place was located in a nice area (+)
The exterior of the building was unappealing (-)
*measurement scale:
Strongly disagree (1) _ _ _ _ _ _ _ Strongly agree (7)
(descriptive atmospherics)
How would you describe the space you visited?
Ordered _ _ _ _ _ _ _ Jumbled
74
Patterned _ _ _ _ _ _ _ Random
Varied _ _ _ _ _ _ _ Repetitive
Small _ _ _ _ _ _ _ Large
Roomy _ _ _ _ _ _ _ Cramped
Open _ _ _ _ _ _ _ Enclosed
Simple _ _ _ _ _ _ _ Complex
(evaluative atmospherics)
I found the space…
Depressing _ _ _ _ _ _ _ Cheerful
Pleasant _ _ _ _ _ _ _ Unpleasant
Comfortable _ _ _ _ _ _ _ Uncomfortable
Attractive _ _ _ _ _ _ _ Unattractive
Bright _ _ _ _ _ _ _ Dull
Unlively _ _ _ _ _ _ _ Lively
Boring _ _ _ _ _ _ _ Stimulating
Tense _ _ _ _ _ _ _ Relaxed
Unmotivating _ _ _ _ _ _ _ Motivating
Uninteresting _ _ _ _ _ _ _ Interesting
Annoying _ _ _ _ _ _ _ Appeasing
Unusual _ _ _ _ _ _ _ Usual
Unique _ _ _ _ _ _ _ Ordinary
Mysterious _ _ _ _ _ _ _ Clear
Charming _ _ _ _ _ _ _ Obnoxious
Novel _ _ _ _ _ _ _ Familiar
Intimate _ _ _ _ _ _ _ Distant
Cozy _ _ _ _ _ _ _ Formal
Hostile _ _ _ _ _ _ _ Friendly
Threatening _ _ _ _ _ _ _ Inviting
75
(holistic atmospherics)
My general attitude towards the space is…
Favorable _ _ _ _ _ _ _ Unfavorable
Positive _ _ _ _ _ _ _ Negative
Good _ _ _ _ _ _ _ Bad
Like _ _ _ _ _ _ _ Dislike
Enjoyable _ _ _ _ _ _ _ Unenjoyable
(felt emotion - PAD)
I felt…
Happy _ _ _ _ _ _ _ Unhappy
Pleased _ _ _ _ _ _ _ Annoyed
Satisfied _ _ _ _ _ _ _ Unsatisfied
Contented _ _ _ _ _ _ _ Melancholic
Hopeful _ _ _ _ _ _ _ Despairing
Relaxed _ _ _ _ _ _ _ Bored
Stimulated _ _ _ _ _ _ _ Relaxed
Excited _ _ _ _ _ _ _ Calm
Frenzied _ _ _ _ _ _ _ Sluggish
Jittery _ _ _ _ _ _ _ Dull
Wide-awake _ _ _ _ _ _ _ Sleepy
Aroused _ _ _ _ _ _ _ Unaroused
Controlling _ _ _ _ _ _ _ Controlled
Influential _ _ _ _ _ _ _ Influenced
In control _ _ _ _ _ _ _ Cared-for
Important _ _ _ _ _ _ _ Awed
Dominant _ _ _ _ _ _ _ Submissive
76
Autonomous _ _ _ _ _ _ _ Guided
(felt emotion - Basic emotions)
I felt…
Enjoyment/Joy (happy/cheerful/delighted)
Surprise (puzzled/confused/startled)
Sadness (gloomy/sad/depressed)
Anger (hostile/annoyed/irritated)
Disgust (disgusted/offended/unpleasant)
Acceptance (helped/accepted/trusted)
Expectancy (alert/attentive/curious)
Fear (threatened/frightened/intimidated)
Interest (attentive/concentrating/alert)
Sadness (downhearted/sad/discouraged)
Shame (sheepish/bashful/shy)
Guilt (repentant/guilty/blameworthy)
Contempt (contemptuous/scornful/disdainful)
Distress
Dissmell
*measurement scale:
Not at all (1) _ _ _ _ _ _ _ Extremely so (7)
(felt emotion - Appraisals)
The emotion I felt was caused by:
Goal relevance:
The situation having a personal relevance for me (+)
77
The situation having an importance for my well-being (+)
The situation meaning nothing to me (-)
Goal congruence:
The situation being obstructive to my goals (-)
The situation being inconsistent with what I wanted (-)
The situation helped me satisfy my needs (+)
Certainty/Outcome predictability:
I knew how the situation would end (+)
I could predict the outcome (+)
I was not certain how things would unfold (-)
Agency:
Things happening beyond anyone’s control
Other people were controlling the situation
My own behavior
Controllability:
I had no control over the situation (-)
I was in control of the situation (+)
I could change the situation the way I wanted (+)
Coping potential:
I could cope with what the situation asked of me (+)
I did not know what to do to change the situation (-)
I did not know how to react (-)
Novelty/Expectancy:
That the situation was new to me (+)
Things happening that I did not expect (+)
78
The fact that nothing surprised me (-)
*measurement scale:
Not at all (1) _ _ _ _ _ _ _ Extremely so (7)
(approach - avoidance)
How much would you want to spend more time in this space?
How much would you like to return to this space?
How much would you try to get out of this space?
How much would you avoid ever having to return to this space?
How much would you try to explore the space?
How much would you try to avoid looking around in this space?
How much does this space makes you talkative to a stranger next to
you?
How much does this space makes you want to avoid talking to
strangers next to you?
How much would you dislike having to work in this space
How much do you think is this space a good opportunity to think
out some difficult task you have been working on?
*measurement scale:
Not at all (1) _ _ _ _ _ _ _ Extremely so (7)
(atmospheric responsiveness)
When I go shopping/to a museum, I pay attention to the store/
museum environment
79
Things like sound, color, lighting in a store/museum make a
difference to me in deciding which store I will shop at/museum I
will visit
I find myself making decisions at what store to shop/what museum
to visit, based on the store/museum looks
Store/Museum decor influences my decision about where I shop /
which museum to visit
*measurement scale:
Strongly disagree (1) _ _ _ _ _ _ _ Strongly agree (7)
80
81
82
83
The Measurement of
ATMOSPHERICS
Harry van Vliet
(c) 2018 Plan B Publishers
Deventer
... • de mate waarin men zegt emotioneel te zijn geraakt (gebaseerd op Versloot, 2014); • bevraging welke emoties men heeft ervaren als resultaat van het gehele bezoek en aangaande speciieke onderdelen van de tentoonstelling (gebaseerd op Leister et al., 2017;Van Vliet, 2018). ...
... • Ervaren gevoelens, beschrijving van ruimte, approach/avoidance gedrag, elementen die sfeer beïnvloedde, ontvankelijkheid van sfeer (onder andere gebaseerd op Kottler, 1973;Van Vliet, 2018). ...
... Approach staat voor het willen blijven in de ruimte, het verder willen exploreren van de ruimte, terwijl avoidance staat voor het willen verlaten van de ruimte en het niet verder willen verkennen van de ruimte. De aandacht hiervoor is te herleiden tot de studie van Mehrabian & Russell (1974), maar is ook in een bredere context van beleving een belangrijk begrippenpaar (Van Vliet, 1991;2018). ...
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In dit boek worden de inzichten en resultaten van twee onderzoeksprojecten gepresenteerd, te weten Designing Experiencescapes (2014-2016) en De Tentoonstellingsmaker van de 21ste Eeuw (2017-2019). Het is onmiskenbaar dat beleving een onderdeel is geworden van museale opstellingen anno 2019. Tegelijkertijd is er, als het gaat om beleving, weinig onderbouwing van wat werkt en waarom. In de jaren sinds het verschijnen van de Nationale Kennisagenda voor het Museale Veld (2014), met daarin een prominente rol voor de belevingswaarde van museale opstellingen, hebben we samen met professionals in het werkveld antwoord gezocht op de vraag hoe men kan sturen op beleving in tentoonstellingen. Gesprekken met professionals en bezoekers, data over hoe professionals hun eigen museum zien en hoe bezoekers het museum ervaren, observaties van hoe bezoekers zich feitelijke gedragen en vele ontwerpsessies later kunnen we de balans opmaken over wat dit heeft opgeleverd.
... This emotional state is often described through the PAD model (Mehrabian & Russell 1974). However, this view of emotions is not without its problems ( Van Vliet 2018). Various studies have also made clear that the 'O' is more complex than what can be uncovered by mere measurement of, for example, arousal. ...
... 'Approach' designates wanting to stay in a space to explore; 'avoidance' represents not wanting to explore and leaving. This division can be further anchored in research into emotions and hereby seems to be a primary concept when describing the experiencing of atmosphere of a space ( Van Vliet 2018). ...
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Researchers have been studying the influence of atmosphere for decades, particularly through the lens of environmental psychology, which focuses on the interplay between humans and their environment. A milestone in atmosphere research was the introduction of the concept of ‘atmospherics’ by Kotler (1973). From here, research into atmosphere mainly took place in the context of marketing research into consumer behaviour in shopes and service environments such as restaurants, hotels, museums and festivals. The question here is whether these gathered insights contribute to understanding how atmosphere works in open public spaces.
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