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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
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... Several studies in marketing, psychology and economics have shown that weather affects movie ticket purchase (Buchheim & Kolaska, 2017), retail sales (Sandqvist & Siliverstovs, 2021), car purchases (Busse et al., 2015), museum attendance (Cellini & Cuccia, 2015) and mobile promotion effectiveness (Li et al., 2017), to cite some. Using both experimental and field data, Murray et al. (2010) study the psychological causal mechanism that underlies this phenomenon and shows that bad weather conditions damage individuals' mood (affective state), which translates into lower consumer spending and willingness to pay. These findings, coupled with other works in psychology Simonsohn, 2006), suggest that factors like sunshine, rainfall or temperature affect people's moods and their subsequent purchasing behaviours. ...
... Overall, this literature documents that weather exerts non-negligible effects on tourists' behaviour at destination, particularly on unplanned activities. The causal mechanism that underlies this pattern can be found in the work by Murray et al. (2010). These authors show that unpleasant weather conditions negatively affect people's moods (affective state), and this psychological mechanism is likely to explain why bad weather causes lower engagement into tourist activities and willingness to consume. ...
... As discussed in Matzarakis (2006), another weakness of the TCI is that it does not include the effects of short-and long-wave radiation fluxes; that is, it does not consider human thermal sensitivity or thermal stress caused to individuals. Since consumers' affective state appears to be the channel by which weather affects consumption patterns (Murray et al., 2010), we need an indicator that captures how weather alters humans physiologically. The Physiologically Equivalent Temperature (PET) index (Matzarakis & Mayer, 1997) expands the TCI index by considering the effect of the thermal environment on humans (i.e. the human energy balance for the assessment of the thermal ambient conditions). ...
Weather has been shown to affect consumption patterns by altering people's moods. This paper examines the impact of atmospheric conditions on destination expenditure considering cruise passengers' onshore expenditure as the case study. We exploit quasi-random variation in a set of hourly real-time weather indicators in a port of call, through the Tourism Climate Index (TCI) and the Physiologically Equivalent Temperature (PET), to draw inference about their effect on destination expenditure. Therefore, we capture the specific atmospheric conditions encountered by tourists, alleviating the usual aggregation bias in related studies. In particular, information about mean and maximum air temperature, wind speed, rainfall, sunshine duration and mean and minimum relative humidity is considered. We estimate a heteroskedastic Tobit model with an inverse hyperbolic sine transformation of the dependent variable that deals with problems of non-normality and extreme values. Controlling for several sociodemographic characteristics and cruise size, we find consistent evidence that pleasant weather (either using TCI or PET indexes) increases onshore expenditure. Our findings have important implications for destination management.
... Based on this background, prior studies have long observed the eects of meteorological conditions [15] with the help of various variables, such as temperature [16][17][18][19], sunlight [20][21][22][23][24][25], and rainfall [26][27][28][29][30][31]. However, weather conditions are not the only factors that aect consumer behavior. ...
... Note that temperature aects purchasing behavior even in cases of products that are non-outdoor oriented such as stock market [19]. Second, sunlight makes people feel good [20] and inuences purchasing decisions [21,22]. Negative emotions caused by a lack of sunlight exposure cause mood-changing behaviors, leading to a variety-seeking tendency in consumer behavior [23]. ...
... Even luxury goods such as cars are aected in this regard [31]. In addition, meteorological conditions, such as humidity [22], atmospheric pressure [32], and snow [6,33], have been reported to aect purchasing behavior. Based on the magnitude of their impact, meteorological conditions are incorporated into demand forecasting models [34][35][36][37]. ...
... Furthermore, most previous studies have identified a relationship between weather factors and clothing sales in brick-and-mortar stores. Similar results have been confirmed that bad weather, such as rain, snow, and snow depth, becomes a physical and psychological obstacle to consumers who cannot go to stores (Martinezde-Albeniz and BelKaid 2021; Murray et al. 2010). ...
New normal weather, more significant variations in temperature and precipitation, and more extreme weather events have resulted in sluggish sales in the clothing industry. Since the industry is a highly fragmented global value chain and procurement of clothing products requires long lead times, weather forecasts are essential information for product planning. Thus, this study aims to develop a model of merchandising strategy for retailers using weather factors within a season. As a place-specific study, we acquire the data from Goggle Trend and weather observation sites from October 2008 to January 2019. Temperature, precipitation, wind speed, snowfall, snow depth, and wind chill were analyzed to find influential factors in seasonal clothing demand. Exploratory data analysis, Pearson correlation analysis, cross-correlation analysis, and Genialized Linear Mixed Model (GLMM) are conducted. Wind chill and the month of the year are significant predictors of seasonal clothing demand. Since the wind chill changes lead to the demand for seasonal clothing one day ahead, this study uses the one-day-lagged windchill data (WindChill_lag1). GLMM model separates the linear relationship between WindChill_lag1 and monthly consumer demand in winter seasons with random effects for multiple years. In addition, the model shows that there are unmeasured characteristics of consumer demand which are indicated through intercept covariance between years. This study provides meaningful information to the clothing industry, which can modify their merchandising plan at the right time according to a weather change.
... People with positive moods take optimistic decisions and spend more (Schwarz andClore, 1983 andMurray et al., 2010). ...
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This paper investigates the impact of psychological factors of Canadian and Mexican tourists on the US tourism sector. Using the data of 1996–2019, the study uses vector autoregression models and the spillover analysis to perform the investigation. The paper discovers that high insecurity of tourists significantly reduces tourist arrivals, passenger fare receipts, and expenditure of tourists in the US. Also, tourist inflows are highly influenced by insecurity during terrorist attacks, natural disasters, and the financial crisis of the US. It is found that high sentiment of Canadian and Mexican tourists increases their outbound travel to the US, but the impact of sentiment is relatively stronger for the Canadian tourists. Results show that the tourist inflows from Canada and Mexico are influenced by low sentiment during recessionary periods of Canada and Mexico, respectively. The paper finds no robust evidence of mood and nationalism-based retaliation of tourists for traveling to the US.
... Although non-store retailing, such as online and TV home shopping networks, comprises a viral buying channel, brick-and-mortar stores still serve a key social and economic function in local communities. In addition, as weather affects consumer mood (Murray et al. 2010), weather can affect sales, so the psychological factors of consumers shopping at brick-and-mortar and non-store retailers along with weather should be studied together. ...
Climate change-induced weather changes have a sensitive impact on the clothing industry. Developing a predictive model for demand volatility caused by weather changes is necessary to allow a company to generate profit while reducing unnecessary resource use and greenhouse gas and wastewater emissions due to overproduction. This review compares and analyzes empirical clothing research papers published in the Republic of Korea since 2000 and examines research directions on the integration of clothing and weather and how weather information is utilized in the clothing industry. We summarize the impact of temperature, precipitation, wind, humidity, and other weather factors on sales. Specifically, the mixed results published in Korea were compared with previous international studies to find weather data and analysis methods. This study identifies the challenges in weather and sales-related studies and presents the scope of methodological improvements. Furthermore, the role of weather forecasting in the clothing industry’s supply chain is proposed to respond to unpredictable weather patterns caused by climate change. The results of this review study should be considered that there is a limit to analyzing clothing sales in Korea only with weather factors because consumers’ purchasing motives are very diverse.
... Prior research has demonstrated that the environment broadly affects human behavior (Hirshleifer & Shumway, 2003;Murray, Di Muro, Finn, & Leszczyc, 2010). As a global environmental issue, air pollution also exerts a great influence on how people behave (Chang, Huang, & Wang, 2018;Huang, Xu, & Yu, 2020;Li, Moul, & Zhang, 2017). ...
Air pollution has been a major environmental problem impacting billions of people worldwide. Despite a large stream of literature discussing the psychological, economic, and environmental effects of air pollution, limited research has explored how people’s pro-environmental behavior (PEB) is affected by air pollution. The present research indicates that people are less willing to engage in PEB when air pollution is severe. Our results show that public attention to PEB is significantly negatively related to air quality (Pilot Study). Additionally, when exposed to air pollution, people are less likely to purchase pro-environmental products (Studies 1 and 2), engage in recycling (Study 3), participate in sustainable travel (Study 4) and donate to environmental organizations (Studies 4 and 5). This is because the negative mood triggered by air pollution inhibits their willingness to engage in PEB (Studies 1 and 3). The theoretical and practical implications of the present research are also discussed.
... Agarwal et al. examined the causal effect of sunshine-induced mood on shoppers' spending. They identified a significant positive relation between abnormal sunshine and same-day credit card spending [36], which agrees with Murray finding that concluded that "as exposure to sunlight increases, negative effect decreases and customer spending tends to increase" [37]. A similar correlation was documented between sunshine and stock returns [38]. ...
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Given the rapid rise in the efficiency of artificial lighting systems, the challenges for any daylighting system on the basis of energy savings will be more challenging in the future. To sustain the role of daylighting in shopping malls, a field survey was conducted to explore daylighting benefits from the customers’ perspective. By analyzing the data collected from 552 Carian shopping malls’ customers, the present study supports the emerging idea that daylighting is more important to improving users’ mood than saving energy. The study found that ‘illumination’ was ranked as the most important element in the shopping malls' internal environment. Connection to outside views and the presence of sunlight were preferred and significantly enhanced the customers’ ability to recognize the utilization of daylight, which, in turn, increased customer satisfaction level. However, the study argues that lighting quality, rather than lighting source (natural or artificial), is what increases customer satisfaction. More studies are essential for elucidating the association between the conscious/subconscious perception of daylight utilization and the achievement of the intended human-related benefits. A better understanding of the customers’ perspectives will guide building designers toward effective daylighting solutions and shift the attention from the functional to the emotional role of daylighting.
Purpose: While the demand for mental health services increases, supply often stagnates. Providing treatment to those most in need is an important factor in its efficient distribution. We propose and conduct a statistical procedure for detecting rater-biases in patient prioritization tools. Design / Method / Approach: We gather real-life data from 266 illness severity assessments in an Austrian publicly funded mental health service provider, including a rich set of covariates. To ensure robustness, we merge this data with determinants of mental health and assessment identified by previous research, such as weather or seasonal indicators. Findings: We find statistically significant effects of rater-biases. These effects are robust to a large array of controls. Practical Implications: A back-of-the-envelope calculation reveals that the identified rater effects can translate to large changes in the waiting times for patients. Misspecified treatment allocations may lead to worsened symptoms and potentially fatal outcomes. Originality / Value: Although a growing literature focuses on patient prioritization tools, many articles study these in synthetic contexts using “vignettes”. In comparison, our study adds external validity by considering real-life treatments in the field. Research Limitations / Future Research: This study can be used as a starting point for deeper, causally focused studies. Disclaimer: In accordance with publisher policies and our ethical obligations as researchers, we report that one of the authors is employed at a company that may be affected by the research reported in the enclosed paper. We have disclosed those interests fully. Paper type: Empirical
This study performs the bootstrap full- and sub-sample rolling-window Granger causality tests, in order to investigate the time-varying causal relationship between the consumer confidence index (CCI) and the outbound tourism expenditure (OTM) in China. For this purpose, it introduces the variable of consumer confidence as a subjective psychological perception variable into the gravity model and explores its impact on the outbound travel. The results reveal that CCI tends to exert positive impacts on the OTM in most subsamples. That is to say that the Chinese consumer confidence can be considered as a catalyst for the OTM. However, the impact tends to be negative during times such as the global financial crisis, caused by the appreciation in the renminbi. In turn, OTM does not affect CCI. This suggests that the only change of private expenditure on outbound tourism cannot alter consumer confidence regarding the current economic and income situation. These findings compel the foreign tourism authorities to take CCI into account, especially when predicating the tourism arrivals from China, and hence plan their tourism strategy accordingly. Also, Chinese travel agencies should ideally take notice of the CCI in order to plan their international tour packages.
The relationship between customer mindset metrics (CMMs) and consumer spending has been extensively investigated at the consumer and firm level, but little is known about it at the national level, nor about how it differs between countries. Drawing on five publicly available datasets gathered in 10 European countries over 20 years, our study traces the connections between three CMMs – customer satisfaction, perceived service quality and loyalty intentions – and consumer spending, as well as examining the moderating cross‐country effects of culture, socioeconomic factors, economic structure and political–economic elements. The results show that the CMMs significantly influence consumer spending in all the countries studied, with the effects most pronounced in societies with relatively low education levels, a dominant service sector, fewer barriers to business and international trade and a foundation of survival values rather than self‐expressive values. Our findings suggest that CMMs can be used to boost not just business performance but also economic growth, and therefore have significant implications for policymakers as well as practitioners and companies.
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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.