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There has been a great deal of anecdotal evidence to suggest that weather affects consumer decision making. In this paper, we provide empirical evidence to explain how the weather affects consumer spending and we detail the psychological mechanism that underlies this phenomenon. Specifically, we propose that the effect of weather – and, in particular, sunlight – on consumer spending is mediated by negative affect. That is, as exposure to sunlight increases, negative affect decreases and consumer spending tends to increase. We find strong support for this prediction across a series of three mixed methods studies in both the lab and the field.
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The effect of weather on consumer spending
Kyle B. Murray
, Fabrizio Di Muro
, Adam Finn
, Peter Popkowski Leszczyc
School of Business, University of Alberta, Edmonton, Canada AB T6G 2R6
Faculty of Business and Economics, University of Winnipeg, Canada
article info
Consumer choice
There has been a great deal of anecdotal evidence to suggest that weather affects consumer decision
making. In this paper, we provide empirical evidence to explain how the weather affects consumer
spending and we detail the psychological mechanism that underlies this phenomenon. Specifically, we
propose that the effect of weather – and, in particular, sunlight – on consumer spending is mediated by
negative affect. That is, as exposure to sunlight increases, negative affect decreases and consumer
spending tends to increase. We find strong support for this prediction across a series of three mixed
methods studies in both the lab and the field.
&2010 Elsevier Ltd. All rights reserved.
1. Introduction
Weather seems to influence human behavior in a variety of
ways. Sometimes, weather influences general behavior. This
occurred when Hurricane Katrina forced the temporary abandon-
ment of New Orleans in 2005. Other times, weather influences
specific consumption behaviors. For instance, the type of clothing
we wear depends on the weathere.g., we wear warmer clothing
in the winter and cooler clothing in the summer.
Building on this type of anecdotal evidence, research has found
that weather variables can affect human behavior. For instance,
research in finance suggests that the weather may affect stock
returns (Saunders, 1993; Trombley, 1997; Hirshleifer and Shum-
way, 2003; Goetzmann and Zhu, 2005) and that this effect may be
attributed to the influence that weather has on mood (Cao and
Wei, 2005; Kamstra et al., 2003). Similarly, research exploring the
link between weather and a social activity has reported that
higher temperatures are correlated with increases in violent
assaults and homicides (Cohn, 1990a, 1990b). Researchers have
also found that the number of suicides rise with increases in
barometric pressure and with decreases in wind (Barker et al.,
1994; Stoupel et al., 1999). In addition, results from several
laboratory studies show that artificial sunlight reduces seasonal
affective disorder (SAD) symptoms for the majority of SAD and
non-SAD depressed participants (Kripke, 1998; Stain-Malmgrem
et al., 1998).
Although the influence of weather on behavior has been
explored in fields such as finance and psychology, it has been
largely ignored in the marketing literature. However, there is
anecdotal evidence that firms incorporate weather variables into
models that they use to predict sales. For example, Wal-Mart
lowered its June 2006 sales forecasts because unusually cool
summer weather adversely affected sales of air conditioners, as
well as swimming pool supplies. Coca-Cola developed vending
machines that dynamically alter the price consumers are charged
for the soft drink based on changes in the ambient tempera-
turei.e., the vending machines increase the price of a soda as the
weather gets hotter (King and Narayandas, 2000).
Nevertheless, the effect of weather on consumer spending has
received only limited attention in the marketing literature (Parker
and Tavassoli, 2000; Parsons, 2001; Steele, 1951). Our work
differs from prior studies as we employ a mixture of methods and
types of data to investigate this issue. This approach is consistent
with Winer (1999), which argues that it is necessary for theory
application research in consumer behavior to establish both
internal and external validity. It is important to not only establish
how variables influence consumer behavior in an artificial
laboratory setting, but also to determine whether these variables
influence behavior in an actual retail setting. In addition, the
research reported in this paper is the first to go beyond
demonstrating an effect of weather on consumer behavior to
propose and test the psychological mechanism (i.e., negative
affect) through which a specific weather variable (i.e., sunlight)
affects consumer spending. Importantly, we find that only
negative affect mediates the effect of weather on spending (i.e.,
changes in positive affect do not impact spending).
Our work begins with an analysis of daily sales data, which
establishes an effect of weather on consumer spending at one
independent retail store. Building on the results of the first study,
Contents lists available at ScienceDirect
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Journal of Retailing and Consumer Services
0969-6989/$ - see front matter &2010 Elsevier Ltd. All rights reserved.
Corresponding author. Tel.: +1 780 248 1091.
E-mail addresses: (K.B. Murray), (F. Di Muro), (A. Finn), (P. Popkowski Leszczyc).
Tel.: +1 780 492 5369.
Tel.: +1 780 492 1866.
Journal of Retailing and Consumer Services 17 (2010) 512–520
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we investigate the effect of weather, and in particular, sunlight, on
participants’ moods and consumption using panel data. The third
study uses a laboratory experiment to directly test the causal
chain predicted by our theoretical model. We find strong support
for the theory that the effect of weather – and, in particular,
sunlight – on consumer spending is mediated by negative affect.
In the next section, we review the literature in three relevant
areas: the influence of weather on consumer spending, the
influence of weather on mood and the influence of mood on
consumer spending. We then describe the three studies we
conducted, along with their results. We conclude with a general
discussion of our findings.
2. Theoretical background
The extant literature has identified three general categories of
effects that weather can have on consumer behavior. The first is
relatively straightforward: bad weather keeps people at home. In
particular, rain, snow and extreme temperatures have been
identified as factors that can make going out to shop less
attractive and, thereby, negatively affect both sales and store
traffic (Parsons, 2001; Steele, 1951).
A second set of effects influence both sales volume and store
traffic in particular product categories (Agnew and Thornes, 1995;
Fox, 1993). For example, when temperatures fall, ice cream sales
decrease, while sales of oatmeal porridge increase (Harrison,
1992). Similarly, people tend to purchase more clothing and
footwear in the winter and more food and drinks in the summer
(Agnew and Palutikof, 1999; Roslow et al., 2000). Retailers
themselves are aware of such effects and use weather as a cue
to begin and end merchandising seasons (Cawthorne, 1998). For
example, gardening supplies begin to appear on store shelves
with the arrival of spring weather, while the sale of snow shovels
coincides with the onset of winter. In general, these studies point
out that some products are better suited to, or even designed for,
particular types of weather.
More interestingly, it has been suggested that weather can
influence sales by affecting consumers’ internal states. Although
there is very little research that directly addresses this third
category of effects, a few studies have provided preliminary
support for this idea. For example, Parker and Tavassoli (2000)
present a global climate-based model of the effect of weather on
consumer behavior, which predicts variation in consumption
patterns in response to different temperatures and exposure to
sunlight. They argue that consumers do adapt to changes in the
environment by modifying their purchasing behavior to both
maintain physiological homeostasis and to achieve optimal
stimulation levels. Of particular relevance to the current research
is the authors’ suggestion that consumers adapt to lower levels of
sunlight, by consuming stimulants such as alcohol, coffee and
cigarettes. Based on these previous findings, we predict that:
H1. Weather variables and, sunlight in particular, affect con-
sumer spending.
Moreover, we go beyond this basic prediction, and extend the
nascent stream of research that has examined the impact of
weather on consumer behavior, by proposing and testing the
following theoretical model: the effect of weather – and, in
particular, sunlight – on consumer spending is mediated by mood.
In the sections that follow we build on the work cited above,
which indicates that the weather can affect sales, and we briefly
review research that has established links between weather and
mood, as well as between mood and consumer spending. We
conclude our literature review with a section on the mediating
role that mood has been shown to play in the effect of weather on
behavior and extend those studies to predict that mood also
mediates the effect of weather on consumer spending.
2.1. Influence of weather on mood
Overall, substantial research in psychology has confirmed that
weather can influence an individual’s mood. For instance, Per-
singer and Levesque (1983) examined the effects of temperature,
relative humidity, wind speed, sunshine hours, barometric
pressure, geomagnetic activity and precipitation on a unidimen-
sional mood rating scale. They found that 40% of mood evalua-
tions were accounted for by a combination of meteorological
events; in particular, barometric pressure and sunshine had the
strongest impact on mood. Other researchers employing varying
mood scales have found that low levels of humidity (Sanders and
Brizzolara, 1982), high levels of sunlight (Cunningham, 1979;
Parrott and Sabini, 1990; Schwarz and Clore, 1983), high
barometric pressure (Goldstein, 1972) and high temperature
(Cunningham, 1979; Howarth and Hoffman, 1984) are associated
with positive mood. Research has also found that weather’s
psychological influences are moderated by the season and the
amount of time spent outside (Keller et al., 2005).
In addition to studies reporting an effect of weather on positive
affect, research has shown that weather can also impact negative
affect. In particular, exposure to sunlight improves peoples’ mood
by reducing negative affect. This effect appears to be associated
with the production of serotonin in the human brain. Specifically,
the rate of serotonin production is directly related to the length of
exposure to sunlight, and rises rapidly with increased exposure to
sunlight (Lambert et al., 2002). Artificial sunlight is also able to
improve mood by reducing negative affect. Controlled laboratory
studies have shown that artificial sunlight – produced, for
example, by ‘‘sun lamps’’ – can improve mood and diminish
SAD symptoms for both SAD and non-SAD depressed patients
(Kripke, 1998; Stain-Malmgrem et al., 1998). Other studies
utilizing artificial sunlight indicate that such lighting improves
mood and vitality among non-depressed individuals (Leppamaki
et al., 2002, 2003). This leads us to predict that with regards to
mood sunlight is a particularly important weather variable and
that it has its primary effect on the negative dimension of affect.
H2. Exposure to sunlight reduces negative affect.
2.2. Influence of mood on consumer spending
According to Gardner (1985), mood is as a phenomenological
property of an individual’s perceived affective state. In addition,
she argues that moods are mild, transient, general and pervasive
states that may be particularly influential in retail or service
encounters, because of their interpersonal or dyadic nature.
Empirical research suggests that people in positive moods are
more likely to evaluate consumer goods (e.g., cars, TVs, etc.) more
favorably than those in neutral moods (e.g., Bitner, 1992; Isen
et al., 1978; Obermiller and Bitner, 1984). Prior work has also
demonstrated that people in a positive mood are more likely to
self-reward and tend to spend more money (Golden and Zimmer-
man, 1986; Sherman and Smith, 1987; Underwood et al., 1973).
In a store intercept study, Donovan et al. (1994) examined the
relationship between shoppers’ emotional states and their actual
in-store spending. They found that more positive states resulted
in greater overall spending. In related research, Spies et al. (1997)
proposed that store atmospheric variables affect consumers’
moods, which in turn affects their purchasing behavior. The
authors compared the effects of two IKEA stores that differed in
terms of their atmosphere (i.e., layout, interior colors, recency of
K.B. Murray et al. / Journal of Retailing and Consumer Services 17 (2010) 512–520 513
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renovations, presentation of furniture, etc.). One of the stores,
described as ‘‘pleasant,’’ was rated as more attractive and
appealing on these dimensions than the other (‘‘unpleasant’’)
store. They measured the effects of these differences on
consumers’ mood and spending. Their results indicate that
consumers’ moods improved during their time in the store with
the more pleasant atmosphere. In addition, they found that
customers’ moods had a direct effect on how much money they
tended to spendthat is, people in more positive moods spend
more money.
These prior findings suggest that consumers in a better mood
will tend to spend more money. We recognize that a consumer’s
mood can be improved by increasing positive affect or by
decreasing negative affect, but prior research has not differen-
tiated between these two distinct mechanisms. Given that we
expect sunlight to reduce negative affect, we more specifically
predict that:
H3. As negative affect decreases, consumer spending increases.
2.3. The mediating effect of mood
Previous research has demonstrated that weather influences
behavior and that mood can mediate such effects (e.g., Barker
et al., 1994;Cao and Wei, 2005;Cohn, 1990a, 1990b;Cunning-
ham, 1979;Kamastra et al., 2003). The literature reviewed above
provides support for the effect of weather on mood, the effects of
mood on consumer spending, and the effect of weather on
consumer spending. In addition, of the weather variables that
have been studied, sunlight appears to play a particularly
important role in improving mood (Keller et al., 2005; Kripke,
1998; Lambert et al., 2002; Leppamaki et al., 2003; Stain-
Malmgrem et al., 1998). Specifically, both natural and artificial
sunlight are able to improve mood by reducing negative affect.
Similarly, the little research examining the relationship between
weather and consumer spending suggests that sunlight is also an
important factor in consumption decisions (e.g., Parker and
Tavassoli, 2000). Therefore, as illustrated in Fig. 1, we predict
that negative (but not positive) affect plays an important
mediating role in the relationship between sunlight and consumer
behavior. Specifically,
H4. Negative affect mediates the effect of sunlight on consumer
We next present the results of three studies that examine the
relationship between weather and consumer spending. Each
study employs a different method in an attempt to triangulate
the effect of weather on consumer spending with daily sales data,
panel data and a laboratory experiment. The first study estab-
lishes the effect that weather can have on consumer spending by
examining the correlation between a wide variety of weather
variables and the daily sales of a small independent retailer. The
results show that snow fall, humidity and sunlight all have
significant effects on consumer spending. The second study
focuses on correlations between weather variables and panel
data, recorded by individual consumers in a daily diary, which
captures consumption patterns and measures fluctuations in
mood (positive affect and negative affect) over twenty days. We
find that sunlight influences mood (negative affect), which
subsequently affects consumption. The third study manipulates
(artificial) sunlight in a laboratory setting. The results of this study
confirm that negative affect can mediate the effect of sunlight on
consumer spending decisions. Specifically, we find that partici-
pants exposed to artificial sunlight are willing to pay significantly
more for a variety of products than participants exposed to
regular lighting only, and that this effect is mediated by negative
3. Study 1
The primary objective of study 1 was to test the general
premise that weather variables can affect consumer spending. We
wanted to see if and how weather might influence daily sales in a
retail setting. In this study, we analyze secondary sales data from
one independent retail store located in a large North American
city. The store specialized in a single product line: tea and related
3.1. Method
Data: Our data consist of six years of daily sales and daily
weather variables. The dependent variable in our model is the
store’s total daily sales. Our independent weather variables are:
temperature (minimum, maximum and average), rain fall, snow
fall, dry bulb, which is a measure of air temperature measured by
a thermometer freely exposed to the air but shielded from
radiation and moisture (minimum, maximum and average),
humidity (minimum, maximum and average), wind direction,
wind speed (minimum, maximum and average), barometric
pressure (minimum, maximum and average) and sunlight. In
addition, we controlled for season, the month, the day of the
week, whether or not the store was open, and whether or not it
was a holiday.
Model used: To test hypothesis 1, we estimated a random
effects model, with the log of daily sales as the dependent variable
(see below). A log transformation was used to normalize the sales
data. This model has a random intercept to control for differences
in sales across month and day (where day is treated as nested
within month)
is the log of daily tea sales in month iand day j; for
i¼1, y, 12, j¼1, y,7;a
is the intercept for month iand day j;
Temp is the average temperature for the day; Snow is the total
snow fall during the day; Sun is the total hours of sunshine for the
day; Temp
is the quadratic term for the average temperature for
the day; e
is a random error term.
Fig. 1. The mediating role of negative affect in the effect of sunlight on consumer spending.
K.B. Murray et al. / Journal of Retailing and Consumer Services 17 (2010) 512–520514
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3.2. Results
The results are reported in Table 1. Consistent with hypothesis
1, we found that several weather variables had a significant effect
on daily sales in this store over the six year time period.
Specifically, we found main effects for average temperature
¼0.042; t¼6.81; po0.001), snow fall (b
t¼2.11; p¼0.035), sunlight (b
¼0.259; t¼3.69; po0.001)
and a main effect for humidity (b
¼0.010; t¼4.24; po0.001).
We also found an interaction effect between average temperature
and sunlight (b
¼0.029; t¼5.08; po0.001) such that the effect of
sunlight on sales is positive at lower temperatures and negative at
higher temperatures. In addition, there is a nonlinear effect of
temperature on sales. Specifically, there is a negative linear effect
¼0.042; t¼6.81; po0.001) and a positive quadratic effect
¼0.0002; t¼4.86; po0.001) of temperature on sales, suggest-
ing that sales go up as temperature goes down but this effect on
sales diminishes as temperatures become lower.
3.3. Discussion
The results are compatible with previous research, which has
found three general categories of weather effects. For example,
consistent with the effects from the first category – i.e., bad
weather can make going out to shop less attractive – we find that
when it snows sales decrease. We also find effects that may be
product specificthat is, sales of tea (and related accessories)
decline when the weather is warmer and more humid. However,
Persinger (1975) found that both humidity and precipitation can
contribute to a negative mood and, therefore, these effects may be
mood related.
Similarly, the results of study 1 indicate that the effect of
sunlight, is conditional upon the average temperaturethat is,
the effect is captured by the interaction, which indicates that
when temperatures are low, increased sunlight has a positive
effect on tea sales. Although sunlight has been identified as a key
variable in previous studies of the impact of weather on mood
(Cunningham, 1979; Parrott and Sabini, 1990; Schwarz and Clore,
1983; Kripke, 1998; Stain-Malmgrem et al., 1998; Leppamaki
et al., 2002, 2003; Lambert et al., 2002), the direction of this effect
is consistent with both a product specific category explanation
and a reduction in negative affect story. When it is already warm,
higher levels of sunlight decrease tea sales.
Supporting hypothesis 1, study 1 provides strong evidence that
weather can affect sales. However, the secondary data used in this
study lacks measures of consumer mood, which are required to
test hypotheses 2 through 4. In study 2, we use daily panel data to
focus on the relationship between weather and mood, as well as
the relationship between mood and consumption.
4. Study 2
4.1. Method
Participants: This study utilized 33 participants who were
recruited from the general population of students at a large North
American university. Participants were paid $100 to provide daily
panel data by completing a web survey at the end of each day for
twenty days in the month of March (average daily high 361F).
Data: The daily survey included structured questions to
measure participants’ mood, spending on and consumption of
tea and coffee, as well as individuals’ total expenditures for the
day. Building on study 1, this study adds a new product category
(coffee) and in addition to measuring dollars spent we also ask
participants for information on their actual consumption beha-
viors (i.e., not just how much they spend on tea and coffee, but
how many cups of each beverage they drink). Respondents
reported their mood using the PANAS scale (Watson et al.,
1988) to capture positive and negative affect. The weather
variables recorded during the collection of the panel data include
the daily averages for temperature, humidity and barometric
pressure, as well as the total hours of sunshine for the day.
4.2. Results
To test the prediction that weather, and sunlight in particular
(H2), affect mood, factor scores for positive and negative affect
were estimated using the pooled PANAS data. Then, the factor
scores for positive affect and negative affect were each regressed
on the daily weather variables, resulting in one model with
positive mood as the dependent variable and one with negative
mood as the dependent variable
is the factor score for positive affect or negative affect for
panel member ion day of the week j;a
is the intercept for panel
member iand day of the week j;Temp
is the average temperature
for the day of the week j;Sun
is the total hours of sunshine for the
day of the week j;Humid
is the average humidity for the day of
the week j;Pressure
is the average barometric pressure for the
day of the week j;e
is a random error term for panel member ion
day of the week j.
Consistent with hypothesis 2, increased sunlight reduced
negative affect (b
¼0.042; t¼2.04; p¼0.042). We also found
that increased humidity reduced positive affect (b
t¼2.02; p¼0.044). No other effects of weather on mood were
present in this data. The full results are reported in Table 2aandb.
Only 25 purchases of tea or coffee were recorded over the 20
day period of the panel data. As a result of this small number of
observations, we were unable to test hypothesis 1, 3 and 4 (i.e.,
the effects of weather and mood on consumer spending) with this
data. Therefore, our analysis focuses on consumption patterns for
which we have sufficient data points. Specifically, we ran two
regression models with consumption (i.e., the cups of tea or coffee
consumed per day) as the dependent variable and the mood
variables (i.e., positive and negative affect factor scores) as the
independent variables. We find no effect of mood on coffee
consumption (NA:
¼0.002, t¼0.060, p¼0.950; PA:
t¼0.870, p¼0.387); however, negative affect does have a
significant positive impact on tea consumption (NA:
t¼2.020, p¼0.040). The effect of positive affect on tea
Table 1
Study 1results of the random effects model.
Variables Coefficients t-values p-values
Intercept 5.560 9.89 o0.001
Temperature 0.042 6.81 o0.001
Snow fall 0.042 2.11 0.035
Sunlight 0.259 3.69 o0.001
Humidity 0.010 4.24 o0.001
Sunlight Temperature 0.029 5.08 o0.001
Temperature Temperature 0.0002 4.86 o0.001
We used the Bayesian Information Criteria to determine which interaction
and quadratic terms to include in the model.
We tested for non-linearity of the weather related variables; however, no
significant quadratic effects were found.
K.B. Murray et al. / Journal of Retailing and Consumer Services 17 (2010) 512–520 515
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consumption was not significant (PA:
¼0.026, t¼0.870,
p¼0.387) (Table 3).
4.3. Discussion
Study 2 uses consumer panel data that includes measures of
mood, and thus, addresses a limitation of study 1. Specifically, the
key finding of study 2 is that sunlight reduces negative affect,
which supports hypothesis 2 and replicates the effect of sunlight
on negative affect that has been documented in prior research
(Kripke, 1998; Stain-Malmgrem et al., 1998). In addition, we find
that humidity decreases positive affect, which is also consistent
with prior work (Sanders and Brizzolara, 1982).
Spending on tea and coffee was unexpectedly too infrequent in
this data set to allow us to test hypotheses 1, 3 and 4.
Interestingly, however, we did find that as negative affect
increased the consumption of tea also increased. In study 1,
although we did not measure mood, the results were consistent
with the expected mood congruency effectthat is, people tend
to buy more tea when they were in a better mood. In study 2, we
observe what appears to be a mood regulation effectthat is,
people tend to drink more tea when their mood is worse (i.e.,
negative affect is higher). Study 3 allows us to more directly test
the impact that sunlight and mood have on spending in a
controlled laboratory environment. We discuss our results in
terms of these two types of effects – i.e., mood regulation and
mood congruency – in more detail in the general discussion.
Overall, the results of study 2 provide further support for our
theoretical model and, in particular, the critical link between
sunlight and negative affect (H2). However, the panel data has its
own limitations. First, these data were collected in an environ-
ment where significant noise was present. Second, the measure of
mood was only recorded once at the end of the day and not at the
time of the spending or consumption decisions. Third, the lack of
spending data did not allow us to test hypotheses 1, 3 and 4.
Fourth, because exposure to sunlight was not manipulated, we
cannot claim strong support for the causal effect on mood
predicted by our model (Fig. 1). Nevertheless, studies 1 and 2
provide converging evidence that is consistent with our model
using two different data sets that were developed with two
distinct methods. In study 3, we again test the propositions of our
model, this time using a third method (i.e., a laboratory
experiment). Importantly, study 3 allows us to directly test
hypothesis 4 – i.e., negative affect mediates the effect of sunlight
on consumer spending – in a controlled environment where
exposure to (artificial) sunlight is manipulated and mood is
measured at the time the spending decision is made.
5. Study 3
Studies 1 and 2 indicated that sunlight is the weather variable
that appears to have the predominant effect on both mood (i.e.,
negative affect) and consumer spending. Therefore, study 3
focuses on sunlight and manipulates participants’ exposure to
artificial sunlight using a specially designed ‘‘sun lamp.’’ In
addition, study 3 extends the product categories that are
investigated beyond tea to include a variety of common consumer
products (i.e., orange juice, a one-month gym membership, an
airline ticket and a one-month newspaper subscription). We
measure positive and negative affect after exposure to the
artificial sunlight and immediately before participants express
their willingness-to-pay for each of these products.
5.1. Method
Participants: This study was completed by 78 students at a large
North American university. Five participants were removed because
they were identified as outliers: their willingness to pay for a
product was greater than three standard deviations from the mean.
Procedure: In this experiment, sunlight was manipulated with
a sun lamp in a between-subjects design. The sun lamp was a desk
lamp that was designed to produce light very similar in wave
length to natural sunlight. Participants were randomly assigned to
either a room containing a sun lamp, or to a room without a sun
lamp. The sun lamp’s location was counterbalanced between the
two roomsi.e., it was located in each room for approximately
half of the time. This was done to control for the effects of any
potential particularities associated with the two rooms.
Once participants were randomly assigned to an experimental
condition, they were asked to read a short document (a review of
English literature written during the time period from 1660 to
1689). Reading this document took, on average, 20 min. Partici-
pants were then asked to complete the PANAS mood scale and
finally responded to open ended questions eliciting their will-
ingness to pay for five products: green tea, juice, a gym
membership, an airline ticket and a newspaper subscription.
Data: The dependent variable was measured by asking
participants how much they would pay for a certain quantity of
the product in question. Specifically, participants were asked how
much they would be willing to pay for (1) 24 tea bags of Lipton’s
Green Tea; (2) a 2L carton of orange juice; (3) an one-month
gym membership; (4) an airline ticket; and, (5) an one-month
Table 3
Study 2the influence of weather on sales.
Coefficients t-values p-values
Number of cups
of tea
Intercept 0.792 0.94 0.347
Temperature 0.0002 0.06 0.952
Sunlight 0.006 0.62 0.539
Humidity 0.034 0.10 0.924
Pressure 0.001 1.21 0.225
Tea volume Intercept 8.775 0.54 0.589
Temperature 0.037 0.60 0.552
Sunlight 0.009 0.05 0.961
Humidity 2.746 0.40 0.687
Pressure 0.105 0.69 0.488
Coffee Intercept 1.389 1.20 0.233
Temperature 0.002 0.41 0.679
Sunlight 0.014 1.13 0.259
Humidity 0.128 0.26 0.793
Pressure 0.016 1.50 0.135
Table 2
Variables Coefficients t-values p-values
(a) Study 2the influence of weather on positive affect
Intercept 3.032 1.91 0.056
Temperature 0.002 0.35 0.729
Sunlight 0.018 0.99 0.322
Humidity 1.40 2.02 0.044
Pressure 0.021 1.37 0.173
(b) Study 2the influence of weather on negative affect
Intercept 0.041 0.02 0.983
Temperature 0.008 1.04 0.297
Sunlight 0.042 2.04 0.042
Humidity 0.007 0.37 0.710
Pressure 0.913 1.14 0.256
K.B. Murray et al. / Journal of Retailing and Consumer Services 17 (2010) 512–520516
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newspaper subscription. These products were chosen because
they are thought to be relevant to the student participants. In all
cases, participants’ mood was assessed using the PANAS mood
scale (Watson et al., 1988), which provides measures of both
positive and negative affect.
5.2. Results
First, consistent with hypothesis 1, we find that sunlight has a
significant positive effect on willingness-to-pay (see Table 4) for
all five products. Second, consistent with hypothesis 2, we find
that sunlight has a significant negative effect on negative affect
¼2.94; t¼2.99, p¼0.004), but no significant effect on positive
affect (
¼0.57; t¼0.35, p¼0.731).
Next we test the effect of negative affect on spending (H3) and
the predicted mediating role of negative affect in the relationship
between sunlight and willingness to pay (H4). The results
reported in Table 5 provide strong support for hypotheses 3 and
4. The results indicate that for all five products the effect of
sunlight on willingness to pay is mediated by negative affect
(Baron and Kenny, 1986). Moreover, in all cases the mediation is
partial, as the effect of sunlight on willingness to pay is still
significant after controlling for negative affect. However, the size
of the coefficient for sunlight is substantially reduced after
controlling for negative affect.
5.3. Discussion
As recommended by Winer (1999), we have employed three
different methods and types of data in an attempt to triangulate
the effects of weather on consumer spending and to establish the
external validity of findings from our laboratory experiment. Our
experimental design allows us to demonstrate a cause-and-effect
relationship between exposure to sunlight and an increased
willingness to pay for common products. This finding builds on
and complements the results of studies 1 and 2. In addition, study
3 extends our results to five products categories, all of which
provide strong support for our model.
6. General discussion
The results of the studies reported in this paper provide
evidence of how weather can impact consumer spending. We find
that temperature, humidity, snow fall, and, especially sunlight,
can affect retail sales. In addition, the panel data replicate the
general result of previous research, which found that sunlight
affects mood (Cunningham, 1979; Parrott and Sabini, 1990;
Schwarz and Clore, 1983), while simultaneously demonstrating
that reductions in negative affect are associated with higher levels
of consumption and spending. Also, we found a causal effect of
sunlight on willingness to pay and demonstrated that the effect
was mediated by negative affect.
Our finding that the effect of sunlight on consumption is
mediated by negative affect is an important extension of prior
theories that found a more positive mood facilitates spending
(Donovan et al., 1994; Golden and Zimmerman, 1986; Sherman
and Smith, 1987; Spies et al., 1997; Underwood et al., 1973).
Specifically, we find that although some weather variables such as
humidity may have an impact on mood through positive affect,
only negative affect has an effect on consumer spending. This
result provides further insight into the underlying psychological
mechanism and, based on prior SAD research (Lambert et al.,
2002), suggests a possible neuro-chemical basis for this effect (i.e.,
serotonin). This opens the door for future research to dig deeper
into the specific link between weather based changes in mood and
consumer spending.
This research also contributes to the literature on the influence
of store atmosphere on consumer shopping behavior. Regarding
store atmosphere, research by Kotler (1973) indicates that
consumers respond to the ‘‘total product’’, and that a significant
component of the total product is the place where the product is
bought or consumed. In fact, the store atmosphere could be more
Table 4
Study 3willingness to pay for products in sunlight and no sunlight conditions.
Products Sunlight condition
(mean willingness-to-pay in $)
No sunlight condition
(mean willingness-to-pay in $)
t-values p-values
Green tea 4.61 3.35 2.36 0.021
Orange juice 3.51 2.90 2.19 0.032
Gym membership 41.67 32.89 2.07 0.042
Airline ticket 517.98 400.00 2.20 0.031
Newspaper subscription 17.79 11.41 2.30 0.024
Table 5
Study 3results of Barron and Kenny (1986) and Sobel (1982) mediation tests.
Products Sunlight on WTP for
NA on WTP for
PA on WTP for
Impact of sunlight on WTP
controlling for NA
Sobel test
Green tea 1.26
Orange juice 0.62
Gym membership 8.78
Airline ticket 117.98
Numbers in the table represent beta-coefficients; for the Sobel test, numbers represent z-values.
NA refers to negative affect; PA refers to positive affect.
K.B. Murray et al. / Journal of Retailing and Consumer Services 17 (2010) 512–520 517
Author's personal copy
influential than the product itself in the purchase decision (Kotler
1973, p. 48). Lighting is considered to be an important component
of the store atmosphere, as a more appealing store with better-
illuminated merchandise could entice shoppers to visit the store,
linger, and perhaps even make a purchase (Summers and Hebert,
In the store atmosphere literature, the dominant theoretical
model, the Mehrabian and Russell (1974) (M–R) model of
approach–avoidance behavior, posits that the combined effects
of pleasure, arousal and dominance influences people’s behaviors
in shopping environments. Regarding lighting, the M–R (1974)
model theorizes that brighter lighting increases pleasantness and
arousal, and that the combination of pleasantness and arousal will
positively influence consumers’ shopping behaviors. Although few
empirical lighting studies have been conducted (Areni and Kim,
1994; Summers and Hebert, 2001), these studies have supported
the M–R (1974) model of approach–avoidance behavior. For
instance, Areni and Kim (1994) studied the impact of in-store
lighting on shopping behavior utilizing a sample of 171 wine store
consumers over a 16-night period. Lighting was manipulated to
be ‘‘soft’’ on eight different evenings by replacing some of the
store’s existing lamps with lower-wattage lighting. On the eight
remaining evenings, lighting was manipulated such that it was
‘‘bright’’ by replacing lamps with higher-wattage lighting. Results
of this research show that consumers examined and handled
significantly more items under ‘‘bright’’ lighting conditions than
under ‘‘soft’’ lighting conditions.
Summers and Hebert (2001) tested the influence of lighting on
consumers’ approach behavior by installing supplemental lighting
in two hardware stores. The lighting treatment was alternated
each Friday and Saturday for 8 h/day per display. The results of
this study indicate that lighting influences consumer approach
behavior, as consumers touched, and picked up more items when
additional lighting was present. In addition, consumers spent
more time at displays under the on treatment than the off
treatment. Overall, the results of these studies suggest that the
observed effect of lighting on consumer behavior is attributed to
arousal and pleasure. However, our results suggest a mechanism
not captured by the M–R (1974) model. Specifically, we find that
the mitigation of negative affect can explain the positive effect of
lighting on shopping behavior. Furthermore, we show that the
positive influence of lighting, caused by the mitigation of negative
affect, actually influences consumer spending, while Summers
and Hebert (2001) and Areni and Kim (1994) do not measure
consumer spending.
Managerial implications: The weather is not under manage-
ment’s control; yet, retailers must respond to changes in the
weather on a regular basis. Prior research has demonstrated that
weather can affect store traffic and complicate staffing decisions
(Agnew and Thornes, 1995; Parsons, 2001; Steele, 1951). It can
also drive consumers towards some products and away from
otherse.g., ice cream when its hot and oatmeal when its cold
(Harrison, 1992). In addition, retail distribution networks, which
have been designed for efficiency, tend to struggle in the face of
unexpected adverse weather conditions that can range from
relatively minor regional storms to global disruptions from
climate change and volcanic activity (e.g., Koetse and Rietveld,
2009; Prater et al., 2001; Stecke and Kumar, 2009). As a result,
retailers are often forced to respond to the effects of weather in a
reactive, rather than proactive manner.
In this paper, we provide compelling evidence that weather
variables can also affect consumers’ internal states, which then
influence their spending decisions. Specifically, we find that
sunlight can reduce negative affect that, in turn, increases
consumer spending. In addition, we have demonstrated that such
affects occur with both natural and artificial sunlight. These
findings build on prior research – which has demonstrated the
influence that store atmospheric variables such as scent and
music have on consumer spending (e.g., Bruner, 1990; Morrison
et al., forthcoming) – and imply that one key weather variable
may be proactively managed by retailers. For example, our results
suggest that retail stores could selectively increase lighting levels
on bad weather days in order to reduce negative feelings, which,
in turn, should help increase sales. When the weather is already
good, consumers’ negative feelings will already tend to be low.
In addition, our results suggest that stores incorporate natural
lighting (i.e. daylight) and/or alter their lighting such that it
closely resembles sunlight, in order to reduce consumers’
negative affect and increase sales. Such greater use of natural
lighting has benefits for employees (Edwards and Torcellini, 2002)
and should also lead to significant cost savings. In fact, for some
buildings, over 90% of lighting energy consumed can be an
unnecessary expense of excessive illumination (Hawken, 2000).
Thus, turning off some electric lights when sufficient daylight is
available should help save on lighting energy costs. Recent
research has shown that daylight can introduce large energy
savings in single-story commercial buildings, especially when it
enters through the top of the building (Hesong et al., 2002).
Furthermore, because daylight introduces less heat into a building
than the equivalent amount of electric light, cooling costs can be
significantly reduced.
Limitations and directions for future research: One limitation of
our work is that study 2 and study 3 were both conducted during
the cooler half of the year. The main effects of sunshine which we
observed might not generalize to other times of the year when
temperatures are warmer and negative affect is less prevalent.
Indeed, we found an interaction effect between temperature and
sunlight in study 1, which suggests that the effect of more
sunlight on retail sales becomes negative when the weather is
already warm (e.g., during the summer). Second, the evidence
that negative affect mediates the effect of weather on consumer
behavior is only available for sunshine. However, our study 1
analysis of the retail stores’ sales found other effects of weather
variables that might also be accounted for by their effects on
mood. The research on weather effects has used various measures
of mood, but it includes some results that are consistent with the
negative effects we found for humidity and snow fall (precipita-
tion) on retail sales. Additional research, is needed to examine
whether the effects of these weather variables on consumer
behavior are also mediated by mood.
Similarly, our predictions were motivated by a stream of
research that has found that as consumers’ moods become more
positive, they spend more money (Spies et al., 1997; Underwood
et al., 1973). In studies 1 and 2, we find that as sunlight reduces
negative affect – and thus consumers’ moods become more
positive – consumers do tend to be willing to spend more. In
study 2, however, we find that lower negative affect is correlated
with more cups of tea being consumed. This finding is consistent
with prior work on mood regulation (Bruyneel et al., 2009; Kivetz
and Kivetz, 2008). For example, in contrast to the work cited
above, prior research has found people in a negative mood tend to
self-gratify or self-reward through consumption and purchasing
more than controls (Thayer et al., 1994; Hadjimarcou and Marks,
1994; Gardner and Scott, 1990; Garg et al., 2007).
Recently, Kivetz and Kivetz (2008) have proposed that these
conflicting results can be explained by two distinct mood
mechanisms: (1) mood congruency, which states that people
respond in accordance with their mood; and, (2) mood regulation,
which states that people try to manage their mood. They argue
that the psychological distance between individuals and the
consequences of their actions and decisions is an important
moderator of the impact of mood. Specifically, they contend that
K.B. Murray et al. / Journal of Retailing and Consumer Services 17 (2010) 512–520518
Author's personal copy
mood congruency is most likely to be observed in decisions with
psychologically distant outcomes, while mood regulation is more
likely to occur when outcomes are proximal to the self and easy to
experience. Two of the studies reported in this paper focused on
psychologically distant outcomesthat is, willingness to pay
(study 3) and the purchase of products to be consumed in the
future (study 1). The results of both of these studies are consistent
with mood congruency. In study 2, which looked at the
psychologically proximate consumption of tea and the results
were consistent with mood regulation. Additional research is
required to improve our understanding of the opposing nature of
these two types of effects.
Finally, future research should also investigate the relationship
between weather, mood and the effectiveness of in-store promo-
tional activities. One possibility is that promotional activities that
temporarily reduce margins are less necessary when the weather
is good and customers already have lower levels of negative
affect, which increases willingness-to-pay.
The authors would like to thank the tea company that provided
the data for Study 1 and acknowledge the support of the
University of Alberta’s School of Retailing and the Bannister Chair
in Marketing held by the third author.
Agnew, M.D., Palutikof, J.P., 1999. The impacts of climate on retailing in the UK
with particular reference to the anomalously hot summer of 1995. Interna-
tional Journal of Climatology 19 (November), 1493–1507.
Agnew, M.D., Thorne, J.E., 1995. The weather sensitivity of the UK food retail and
distribution industry. Meteorological Applications 2 (June), 137–147.
Areni, C.S., Kim, D., 1994. The influence of in-store lighting on consumers’
examination of merchandise in a wine shop. International Journal of Research
in Marketing 11 (March), 117–125.
Barker, A., Hawton, K., Fagg, J., Jennison, C., 1994. Seasonal and weather factors in
parasuicide. British Journal of Psychiatry 165 (3), 375–380.
Baron, R.M., Kenny, D.M., 1986. The moderator–mediator variable distinction in
social psychological research: conceptual, strategic and statistical considera-
tions. Journal of Personality and Social Psychology 51 (6), 1173–1182.
Bitner, M.J., 1992. Servicescapes: the impact of physical surroundings on
customers and employees. Journal of Marketing 56 (April), 57–71.
Bruner, G.C., 1990. Music, mood and marketing. Journal of Marketing 54 (October),
Bruyneel, S.D., Dewitte, S., Hans, F.P., Dekimpe, M.G., 2009. I felt low and my purse
feels light: depleting mood regulation attempts affect risk decision making.
Journal of Behavioral Decision Making 2 (22), 153–170.
Cao, M., Wei, J., 2005. Stock market returns: a note on temperature anomaly.
Journal of Banking & Finance 29 (June), 1559–1573.
Cawthorne, C.P., 1998. Weather as a strategic element in demand chain planning.
The Journal of Business Forecasting Methods and Systems 17 (Fall), 18–21.
Cohn, E.G., 1990a. Weather and crime. British Journal of Criminology 30 (1), 51–64.
Cohn, E.G., 1990b. Weather and violent crime. Environment and Behavior 22
(March), 28–94.
Cunningham, M.R., 1979. Weather, mood, and helping behavior: quasi experi-
ments with the sunshine samaritan. Journal of Personality and Social
Psychology 37 (November), 1947–1956.
Donovan, R.J., Rossiter, J.R., Marcoolyn, G., Nesdale, A., 1994. Store atmosphere and
purchasing behavior. Journal of Retailing 70 (3), 283–294.
Edwards, L., Torcellini, P., 2002. A Literature Review of the Effects of Natural Light
on Building Occupants. (NREL/TP-550-30769). National Renewable Energy
Laboratory, Golden, CO.
Fox, F.D., 1993. Managing the impact of weather. Retail Control 61, 14–18.
Gardner, M.P., 1985. Mood states and consumer behavior: a critical review. Journal
of Consumer Research 12 (December), 281–300.
Gardner, M.P., Scott, John, 1990. Product type: a neglected moderator of
mood. In: Goldberg, M.E., Gorn, G., Pollay, R.W. (Eds.), Advances in Consumer
Research, vol. 17. Association for Consumer Research, Provo, UT, pp. 585–589.
Garg, N., Wansink, B., Inman, J.J., 2007. The influence of incidental affect on
consumers’ food intake. Journal of Marketing 71 (January), 194–206.
Goetzmann, W.N., Zhu, N., 2005. Rain or shine: where is the weather effect?
European Financial Management 11 (November) 559–578.
Golden, L.G., Zimmerman, D.A., 1986. Relationship between affect, patronage,
frequency and amount of money spent with a comment on affect scaling and
measurement. In: Lutz, R.J., Provo, U.T. (Eds.), Advances in Consumer Research,
vol. 13. Association for Consumer Research.
Goldstein, K.M., 1972. Weather, mood, and internal–external control. Perceptual
and Motor Skills 35 (August), 786.
Hadjimarcou, J., Marks, L.J., 1994. An examination of the effects of context-
inducted mood states on the evaluation of a ‘feel-good’ product: the
moderating role of the product type and the consistency effects model. In:
Allen, C.T., John, Deborah Roedder (Eds.), Advances in Consumer Research, vol.
21. Association for Consumer Research, Provo, UT, pp. 509–513.
Harrison, K., 1992. Whether the weather be good. Super Marketing, 15–17.
Hawken, P., 2000. Imagine: What America Could Be in the 21st Century.
Pennsylvania: Rodale Press.
Hesong, L., Wright, R.L., Okura, S., 2002. Daylighting impacts on retail sales
performance. Journal of the Illuminating Engineering Society 31 (2), 21–25.
Hirshleifer, D., Shumway, T., 2003. Good day sunshine: stock returns and the
weather. Journal of Finance 58 (June), 1009–1032.
Howarth, E., Hoffman, M.S., 1984. A multidimensional approach to the relationship
between mood and weather. British Journal of Psychology 75 (February),
Isen, A.M., Shalker, T.E., Clark, M.S., Karp, L., 1978. Influence of positive affecton the
subjective utility of gains and losses: it is just not worth the risk. Journal of
Personality and Social Psychology 55, 710–717.
Kamstra, M.J., Kramer, L.A., Levi, M.D., 2003. Winter blues: a SAD stock market
cycle. American Economic Review 93 (1), 324–343.
Keller, M.C., Fredrickson, B.L., Ybarra, O., Cote, S., Johnson, K., Mikels, J., Conway, A.,
Wager, T., 2005. A warm heart and a clear head: the contingent effects
of weather on mood and cognition. Psychological Science 16 (September),
King, C., Narayandas, D., 2000. Coca-cola’s new vending machine (A): pricing to
capture value, or not? Harvard Business School Case # 9-500-068.
Kivetz, R., Kivetz, Y., 2008. Reconciling mood congruency and mood regulation,
working paper, Columbia Business School.
Koetse, M.J., Rietveld, P., 2009. The impact of climate change and weather on
transport: an overview of empirical findings. Transportation Research Part D:
Transport and Environment 14 (3), 205–221.
Kotler, P., 1973. Atmospherics as a marketing tool. Journal of Retailing 49 (Winter),
Kripke, D.F., 1998. Light treatment for non-seasonal depression: speed, efficacy,
and combined treatment. Journal of Affective Disorders 49 (2), 109–117.
Lambert, G.W., Reid, C., Kaye, D.M., Jennings, G.L., Esler, M.D., 2002. Effects of
sunlight and season on serotonin turnover in the brain. The Lancet 360
(December), 1840–1842.
Leppamaki, S., Partonen, T., Lonnqvist, J., 2002. Bright-light exposure combined
with physical exercise elevates mood. Journal of Affective Disorders 72
(November), 139–144.
Leppamaki, S., Partonen, T., Piiroinen, P., Haukka, J., Lonnqvist, J., 2003. Timed
bright-light exposure and complaints related to shift work among women.
Scandinavian Journal of Work, Environment, and Health 29 (February), 22–26.
Mehrabian, A., Russell, J.A., 1974. An Approach to Environmental Psychology. MIT
Press, Cambridge, MA.
Morrison, M., Gan, S., Dubelaar, C., Oppewal, H.. In-store music and aroma
influences on shopper behavior and satisfaction. Journal of Business Research
forthcoming, doi:10.1016/j.jbusres.2010.06.006.
Obermiller, C., Bitner, M.J., 1984. Store atmosphere: a peripheral cue for product
evaluation. In: Stewart, David C. (Ed.), American Psychological Association
Annual Conference Proceedings, Consumer Psychology Division. American
Psychological Association, pp. 52–53.
Parker, P.M., Tavassoli, N.T., 2000. Homeostasis and consumer behavior across
cultures. International Journal of Research in Marketing 17 (March), 33–53.
Parrott, W.G., Sabini, J., 1990. Mood and memory under natural conditions:
evidence for mood incongruent recall. Journal of Personality and Social
Psychology 59 (August), 321–336.
Parsons, A.G., 2001. The association between daily weather and daily shopping
patterns. Australasian Marketing Journal 9 (2), 78–84.
Persinger, M.A., 1975. Lag responses in mood reports to changes in the weather
matrix. International Journal of Biometeorology 19 (2), 108–114.
Persinger, M.A., Levesque, B.F., 1983. Geophysical variables and behavior: XII: the
weather matrix accommodates large portions of variance of measured daily
mood. Perceptual and Motor Skills 57 (February), 868–870.
Prater, E., Biehl, M., Smith, A.M., 2001. International supply chain agility: tradeoffs
between flexibility and uncertainty. International Journal of Operations and
Product Management 21 (5/6), 823–839.
Roslow, S., Li, T., Nicholls, J.A.F., 2000. Impact of situational variables and
demographic attributes in two seasons on purchase behavior. European
Journal of Marketing 34 (9/10), 1167–1180.
Sanders, J.L., Brizzolara, M.S., 1982. Relationships between weather and mood.
Journal of General Psychology 107 (July), 155–156.
Saunders, E.M., 1993. Stock prices and wall street weather. The American
Economic Review 83 (December), 1337–1345.
Schwarz, N., Clore, G.L., 1983. Mood, misattribution, and judgement of well-being:
informative and directive functions of affective states. Journal of Personality
and Social Psychology 45 (February), 513–523.
Sherman, E., Smith, R.B., 1987. Mood states of shoppers and store image:
promising interactions and possible behavioral effects. In: Wallendorf, M.,
Anderson, P. (Eds.), Advances in Consumer Research, vol. 14. Association for
Consumer Research, Provo, UT.
K.B. Murray et al. / Journal of Retailing and Consumer Services 17 (2010) 512–520 519
Author's personal copy
Sobel, M.E., 1982. Asymptotic intervals for indirect effects in structural equations
models. In: Leinhart, S., San Francisco, C.A. (Eds.), Sociological Methodology,
vol. 13. Jossey-Bass, pp. 290–312.
Spies, K., Hesse, F., Loesch, K., 1997. Store atmosphere, mood, and purchasing
behavior. International Journal of Research in Marketing 14 (February),
Stain-Malmgrem, R., Kjellman, B.F., Aberg-Wistedt, A., 1998. Platelet serotonergic
functions and light therapy in seasonal affective disorder. Psychiatric Research
78 (May), 163–172.
Stecke, K.E., Kumar, S., 2009. Sources of supply chain disruptions, factors that
breed vulnerability, and mitigating strategies. Journal of Marketing Channels
16 (3), 193–226.
Steele, A.T., 1951. Weather’s effect on the sales of a department store. Journal of
Marketing 15 (April), 436–443.
Stoupel, E., Abramson, E., Sulkes, J., 1999. The effect of environmental physical
influences on suicide. How long is the delay? Archives of Suicide Research 5
(September) 241–244.
Summers, Ta A., Hebert, P.R., 2001. Shedding some light on store atmospherics:
influence of illumination on consumer behavior. Journal of Business Research
54 (November), 145–150.
Thayer, R.E., Robert, N.J., McClain, T.M., 1994. Self-regulation of mood:
strategies for changing a bad mood, raising energy, and reducing
tension. Journal of Personality and Social Psychology 67 (November),
Trombley, M.A., 1997. Stock price and wall street weather: additional evidence.
Quarterly Journal of Business and Economics 36 (Summer), 11–21.
Underwood, B., Moore, B.S., Rosenhan, D.L., 1973. Affect and self-gratification.
Developmental Psychology 8 (2), 209–214.
Watson, D., Anna, C.L., Tellegen, A., 1988. Development and validation of brief
measures of positive and negative affect: the PANAS scales. Journal of
Personality and Social Psychology 54 (June), 1063–1070.
Winer, R.S., 1999. Experimentation in the 21st century: the importance
of external validity. Journal of the Academy of Marketing Science 29 (3),
K.B. Murray et al. / Journal of Retailing and Consumer Services 17 (2010) 512–520520
... In contrast, during bad weather conditions, like windy days, people tend to choose the safest alternative, e.g., voting for the status quo in referenda (Bassi 2013). Good weather has also been proven to affect consumer spending positively (Murray et al. 2010). ...
... Finally, good weather has been proven to affect consumer spending positively (Murray et al. 2010), and weather conditions have been associated with greater variety-seeking behavior in supermarkets (Tian et al. 2018). ...
... Moreover, respondents show higher WTPs for locally offered management policies during sunny and calm days. Overall, these results are in line with those obtained by Murray et al. (2010), that found a positive relationship between good weather and consumer spending, and the vast psychological and financial literature on the effect of good and bad AWCs on behavior and decision-making processes of people, with good weather conditions leading more to some action and bad conditions to less or no action. ...
Full-text available
One of the assumptions in stated preference studies is the stability of respondents’ preferences. This assumption might be violated in situations of context dependence, i.e., when the contingent situation influences respondents’ choices. Ambient weather conditions (AWCs) are one element of the context that may influence stated preferences. The literature suggests that AWCs affect people’s emotions, behaviors, and decision-making processes; however, the potential AWCs impact in environmental preference studies has not yet been investigated. This aspect is of high importance because context-dependent choices return biased willingness to pay estimates and affect the subsequent welfare analysis that informs public policy. To shed light on this important aspect of non-market valuation studies, we explore the effect of AWCs on preferences elicited with a Discrete Choice Experiment for ecosystem services management of a Nature Park. Results of a generalized mixed logit model evidenced a significant effect of AWCs on respondents’ choices, with good weather conditions leading to higher preferences and willingness to pay for ecosystem services management. This result, which is consistent with previous psychological studies, raises the issue of sampling design and reveals the importance of a sensitivity analysis of WTP. As this issue is still unexplored in stated preference studies, we also encourage undertaking similar studies to add a priori knowledge for more accurate ex-post calibration of WTP estimates.
... In the interest of space, we will not discuss these papers here. Many recent studies, such as [2,3,5,[28][29][30][31][32][33][34][35][36][37], have controlled for climate in their analyses. For example, ref. [38] was one of the first studies to consider the impact of weather on sales, focusing on the seven weeks prior to Easter over a nine-year period. ...
... Ref. [35] found that sunlight has a negative effect on consumer spending, but their study only considered a single store or laboratory setting. In contrast, our analysis utilizes countywide data, providing a broader understanding of the impact of weather on sales in brick-and-mortar retail settings. ...
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In this paper, we explore the importance of accounting for climate when determining the impact of weather on product sales. Using a France-wide scanner panel dataset provided by our industry partner, we show that if climate is not accounted for, product categories may be misclassified as being weather sensitive when they are not, and vice versa. This is motivated by previous research and industry reports that suggest a relationship between weather and retail sales. However, these studies often fail to distinguish between weather and climate, leading to inaccurate conclusions. Our results highlight the need to control for climate in order to accurately assess the effects of weather on retail sales. We use ordinary least squares regression to estimate the relationship between temperature and sales for 29 different product categories. The regression models control for various factors, including shelf space allocation, week of observation, quantity purchased, promotion, store brand, store surface area, store competition, and consumer behavior measures. We find that when accounting for climate, only a subset of the product categories is sensitive to weather. Additionally, we show that climate can be approximated using a week index, eliminating the need for additional data collection and approximation efforts. Our findings have implications for both researchers and practitioners. Researchers should be aware of the importance of accounting for climate when studying the impact of weather on retail sales, as failing to do so may lead to erroneous conclusions. Practitioners can use our results to inform their marketing and sales strategies, taking into account the weather sensitivity of different product categories and the role of climate in shaping consumer behavior. Overall, our study emphasizes the need to consider climate when determining the impact of weather on retail sales, and provides practical insights for retailers and economists.
... The weather affects consumer purchase behavior by regulating negative emotions. When people are bathed in sunlight, negative emotions decrease, and consumer tendency to complete purchases increases (Murray et al. 2010). However, when the weather is bad, people are more likely to purchase online. ...
... Finally, from the results of the three cities, the purchasing behav-ior of food delivery was more sensitive to cold than to heat. Research by Murray et al. revealed the mediating effect of mood on weather and sales (Murray et al. 2010). Under uncomfortable weather conditions, people's moods are significantly lower than under comfortable weather conditions. ...
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The online food delivery industry has been rapidly growing with the advancement of mobile internet technology and mobile payments. In this context, understanding the impact of situational effects on online food delivery sales becomes crucial. This study aims to investigate the influence of weather and time factors on online food -delivery sales on a Chinese online food delivery platform over a year. The study also performs a comparative analysis of urban user groups to examine the situational effects of weather and time factors on online food delivery sales. To carry out the study, the research team collected data from platform A, a popular online food delivery platform with a long operation time, abundant user resources, and sufficient data. The meteorological data was obtained from China's Meteorological Data Network, which provides accurate weather data from various stations across the country. The study analyzed food delivery order quantity data and weather factor data from three cities, Beijing, Harbin, and Hangzhou, constituting different stages of evolution in delivering the food online in Chinese cities, and with different climatic conditions, shopping habits, and diets. The meteorological indicators considered for the study include temperature, precipitation, humidity, rainfall, snowfall, and air quality index. The findings of the study suggest that situational effects have significant impacts on online food delivery sales. Specifically, the study found that weather conditions, such as rain, snow, and air quality, and time factors, such as weekends and pre- and post-holiday periods, have a significant influence on online food delivery sales. The comparative analysis of urban user groups also revealed differences in the impact of situational effects on online food delivery sales between the three cities. Overall, this study provides valuable insights into the situational effects on online food delivery sales and can assist online food delivery platforms and businesses in making informed decisions to improve their sales and profitability.
... Additionally, the findings of a multi-group research demonstrate that the influence of advertising value and appeal on the emotional element of impulse purchasing tendency considerably varies by gender. Moreover, it is claimed that consumers who are in a good mood spend more money (Murray et al., 2010). This may be the likely cause that deceptiveness and irritation in advertising appeal do not have a significant positive influence on impulsive purchase. ...
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The purpose of this research is to identify the relationship between advertising appeals and impulse purchase inclination in the presence of self-control and marital status as moderators. A pre-designed questionnaire was used to collect data. PLS-SEM (Partial Least Squares Structural Equation Modelling) is used to determine the nature of the link between the mentioned variables, as well as the function of self-control as a moderator. A multi-group analysis is conducted to see how the model varies from gender variation. Furthermore, Andrew F. Hayes Process Macro is also utilized as a data analysis approach. According to the findings of Andrew F. Hayes Process Macro, self-control has a considerable negative influence on impulse purchase inclination. According to PLS-SEM findings, entertaining advertising appeal has a considerable positive influence on the cognitive element of impulsive purchasing tendency, but informative advertising appeal has a significant positive impact on both the cognitive and affective aspects of impulse buying tendency. Surprisingly, irritating commercial appeal has a large favorable influence on the cognitive aspect of impulse purchasing inclination. However, the study discovered a minor complimentary function of self-control in the relationship between advertising appeals and impulse purchase inclination. The results of a multi-group investigation show that the influence of advertising value ad appeal on the emotive aspect of impulse purchase inclination vary greatly depending on gender. The study is significant for marketers because it shows that self-control acts as a barrier in the route of impulsive buying.
... The classical heat hypothesis postulates that elevated temperatures could escalate the propensity of individuals towards agitation and heightened aggression [1]. This relationship is also reflected in the higher consumption of antidepressant medication during frigid winters as compared to temperate summers [2]. The study by Patz further reveals the ability of temperature fluctuations to alter psychological states and cognitive behaviors, predominantly evidenced by an upsurge in adverse emotions such as anxiety, depression, and sadness [3]. ...
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Existing studies have shown that temperature is related to mental illness and sleep disorders. However, few studies have explored the relationship between temperature and microblog negative emotions (MNE) and the predictive effect of MNE on sleep disorders. The present study elucidating the temperature patterns of MNE and sleep disorders, examines the predictive capability of these adverse emotions in precipitating sleep disorders, and operating within the schema of “climate-psychology-behavior”. A negative binomial regression model (NBR) was formulated, amalgamating Temperature data, negative affective information procured from microblog, and sleep disorder records. Temperature and Apparent Air Temperature (AAT) were found to have a non-linear association with microblog negative emotions and sleep disorders, exhibiting a modest effect within a specified range, while extreme temperatures (both high and low) demonstrated substantial effects. In the constructed model, gender serves as a moderating factor, with females being more susceptible to temperature and AAT effects on MNE and sleep disorders than their male counterparts. Interestingly, AAT surfaced as a superior predictor compared to actual temperature. MNE were effective predictors of sleep disorders. Employing social media-centric models, as showcased in this study, augments the identification and prevention strategies targeting disease symptoms or pathologies within mental and public health domains.
... It is claimed that consumers who are in a good mood spend more money (Murray et al., 2010). Furthermore, Beatty and Ferrell (1998) state that positive mood leads to more impulse purchases than negative mood. ...
... For instance, some studies have reported that sunny weather is correlated positively with daily stock market returns [21,22]. Other studies have found that more exposure to sunlight decreases negative affect and increases consumer spending [23][24][25][26], whereas warm temperatures increase consumers' valuation of products [27]. Relationships between weather and attitudes and behaviour are not limited to business and consumer psychology. ...
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We examine associations between prevailing weather conditions and music features in all available songs that reached the United Kingdom weekly top charts throughout a 67-year period (1953-2019), comprising 23 859 unique entries. We found that music features reflecting high intensity and positive emotions were positively associated with daily temperatures and negatively associated with rainfall, whereas music features reflecting low intensity and negative emotions were not related to weather conditions. These results held true after controlling for the mediating effects of year (temporal patterns) and month (seasonal patterns). However, music-weather associations were more nuanced than previously assumed by linear models, becoming only meaningful in those months and seasons when changes in weather were the most notable. Importantly, the observed associations depended on the popularity of the music: while songs in the top 10 of the charts exhibited the strongest associations with weather, less popular songs showed no relationship. This suggests that a song's fit with prevailing weather may be a factor pushing a song into the top of the charts. Our work extends previous research on non-musical domains (e.g. finance, crime, mental health) by showing that large-scale population-level preferences for cultural phenomena (music) are also influenced by broad environmental factors that exist over long periods of time (weather) via mood-regulation mechanisms. We discuss these results in terms of the limited nature of correlational studies and cross-cultural generalizability.
... Under a sudden price surge, Zhang et al. (2020) argue that the perceived threat of the disease alters people's mood and magnifies individuals' negative emotional reactions to disadvantaged price inequality. In this regard, extant works have shown that mood alters judgement, decision-making and economic choices (e.g., Murray et al., 2010;Shu, 2010). ...
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This study evaluates the changes in the expenditure-price elasticities of foreign tourists in the summer periods of 2019, 2020, and 2021. We first develop a theoretical characterization that combines microeconomic, loss aversion, price inequality and precautionary savings theories. Next, exploiting microdata for more than 34,000 foreign tourists visiting Spain, we estimate OLS and quantile regressions to empirically examine the expenditure elasticities with respect to the prices of transport services , leisure activities and bars and restaurants at the destination (17 regions). We find that (i) the expenditure-price elasticity of transportation (leisure activities) increases (decreases) during the pandemic, whereas that of bars and restaurants remains unchanged, (ii) foreign tourists are comparatively less expenditure-price elastic at high expenditure levels in transportation and bars and restaurants, and (iii) expenditure-price elasticities are highly heterogeneous depending on the origin country. Managerial and theoretical implications of the findings for firms' pricing strategies are discussed.
... With the frequent heat waves, research on the influence of extremely high temperature on human investment decision making is still at its infancy. Some scholars have designed experiments to explore the influence of high temperature on consumer purchases (Busse et al., 2015;Cheema & Patrick, 2012;Lundberg et al., 2021;Murray et al., 2010). Sinha and Bagchi (2019) found that ambient temperature affects consumers' willingness to pay in different types of purchasing environment, and a significantly positive correlation exists between temperature and aggressiveness in the purchase process. ...
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We estimate the relationship between high‐temperature exposure and land transaction using daily transaction data from 2013 to 2018 in China. Standard hedonic price method is used to perform multidimensional fixed effects regression on 458,564 transaction samples. This study shows that each additional day of the extremely high temperature increases the average bid price by 0.6%, which is equivalent to an additional annual increase of 15.018 billion yuan in land transaction costs. The effect of high temperature on land prices is considerably stronger for residential and commercial lands. We further find that high‐temperature‐induced changes of mood and cognition play a role. Extreme gradient boosting (XGBoost) algorithm is used to calculate price deviation, which overcome missing eigenvalues and reduce nonlinear measurement error. Our findings indicate that heat can make investors more aggressive, which occurs when bidders continue to raise prices to win. The number of bidding behavior will not drop due to the hidden costs of land transactions. Specially, bidding experience offsets the cognitive output bias. This study contributes to the behavioral finance and decision‐making literature, helps investors make better investment management decisions, and alleviates the negative effect of land transaction premium on the real estate market.
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In this article, we attempt to distinguish between the properties of moderator and mediator variables at a number of levels. First, we seek to make theorists and researchers aware of the importance of not using the terms moderator and mediator interchangeably by carefully elaborating, both conceptually and strategically, the many ways in which moderators and mediators differ. We then go beyond this largely pedagogical function and delineate the conceptual and strategic implications of making use of such distinctions with regard to a wide range of phenomena, including control and stress, attitudes, and personality traits. We also provide a specific compendium of analytic procedures appropriate for making the most effective use of the moderator and mediator distinction, both separately and in terms of a broader causal system that includes both moderators and mediators. (46 ref) (PsycINFO Database Record (c) 2012 APA, all rights reserved)
Recent studies by our group have demonstrated a relationship between certain physical environmental factors and fluctuations in the monthly number of deaths (including suicides), first admission of psychiatric patients, and occurrences of some neurologic pathologies and serotonin-related clinical syndromes (Raps et al., 1991, 1992; Stoupel, 1992; Stoupel et al., 1995a, b; Stoupel et al., 1996, Stoupel et al., 1997). In the present work we investigated the length of delay between environmental changes and suicides. The monthly suicides in Israel over an eight-year period (1981-1989) were correlated with geomagnetic activity levels, hours of positive and negative ionization of the ionosphere, maximal and minimal indices of radiowave propagation, and space proton flux (>90 MeV), both in the month of each suicide and the preceding one or two months. The monthly number of suicides was obtained from the registry of the Central Bureau of Statistics of the State of Israel, and the cosmophysical data were obtained from the National Space Services Center and the National Geophysical Data Center, Boulder, CO, USA and the Izmiran Institute of the Academy of Sciences, Izmiran, CIS. Pearson correlation coefficients and their probabilities were calculated. A probability of p ≥ 0.05 was considered significant.
Conducted 2 field studies on the relationship of weather variables to helping behavior. In Study 1 (540 adult Ss), which was executed in the spring and summer and subsequently replicated in the winter, the amount of sunshine reaching the earth was found to be a strong predictor of an S's willingness to assist an interviewer. Smaller relationships were also found between helping and temperature, humidity, wind velocity, and lunar phase. Exp II was conducted indoors with 130 dining parties to control for comfort factors. Sunshine, lunar phase, and S's age and sex were found to predict the generosity of the tip left for a restaurant waitress. Sunshine and temperature were also significantly related to the 6 waitresses' self-reports of mood. (35 ref) (PsycINFO Database Record (c) 2006 APA, all rights reserved).
In studying the causes of crime, most criminologists have concentrated on traditional socio-demographic variables, such as age, sex, race, and socio-economic status. However, some researchers have investigated the influence of the physical environment on criminal behaviour. There is a recent theoretical basis for research into the influence of weather on crime: the situational approach, rational choice theory, and routine activities theory all suggest that weather could significantly influence crime rates and criminal behaviour. This paper brings together for the first time the accumulated research on weather and crime. It discusses the theoretical background, examines research into the influence of different weather conditions (such as high temperatures, rain, and wind) on various types of criminal behaviour, outlines problems with the current research, and suggests ways of advancing knowledge about weather and crime. © 1990 The Institute for the Study and Treatment of Delinquency.
This paper investigates the role of seasonal affective disorder (SAD) in the seasonal time-variation of stock market returns. SAD is an extensively documented medical condition whereby the shortness of the days in fall and winter leads to depression for many people. Experimental research in psychology and economics indicates that depression, in turn, causes heightened risk aversion. Building on these links between the length of day, depression, and risk aversion, we provide international evidence that stock market returns vary seasonally with the length of the day, a result we call the SAD effect. Using data from numerous stock exchanges and controlling for well-known market seasonals as well as other environmental factors, stock returns are shown to be significantly related to the amount of daylight through the fall and winter. Patterns at different latitudes and in both hemispheres provide compelling evidence of a link between seasonal depression and seasonal variation in stock returns: Higher latitude markets show more pronounced SAD effects and results in the Southern Hemisphere are six months out of phase, as are the seasons. Overall, the economic magnitude of the SAD effect is large.