Effect of Atmospherics on Impulse Purchases in Live Streaming:
Based on Structural Equation Model
Liping Yan and Ming Xue
*
School of Business Administration, Shanghai Lixin University of Accounting and Finance, Shanghai, China
*
Keywords: Physical Atmospherics, Social Atmospherics, Impulse Purchases, e-Commerce Live Streaming, Taobao Live.
Abstract: With the emergence and development of e-commerce live streaming, academia has begun to pay attention to
the factors affecting customer behavioral intention. This study aims to refine the subcategories of physical
and social atmospheric elements in the e-commerce live-streaming setting and investigate how the physical
atmosphere and streamer- and viewer-based stimuli induce customers’ perceived arousal and credibility,
which increases their impulse purchases. The study surveyed 509 Taobao Live users in China to test our
hypotheses. Structural equation modeling was employed using AMOS 20.0 and the overall fit of the structural
model was highly acceptable. The results of the structural equation modeling indicated that customers’
perceived arousal is positively affected by visual appeal, other viewers’ engagement behaviors and streamer’
s affective delivery. Customers’ perceived credibility is positively affected by the streamer providing
elaborate information. Customers’ perceived arousal and perceived credibility positively affect their impulse
purchase behavior.
1 INTRODUCTION
Live streaming provides a new way to shop (Sun,
2019). Compared to traditional e-commerce (e.g.,
brand community, word of mouth and vivid
descriptions), live-streamed shopping has some
unique characteristics, including the displaying of
products from different angles; the revealing of the
seller’s face, personality and office/studio; and the
answering of customer questions in real time,
showing other viewers’ instant response and
behaviors, which constitute of atmospherics
fundamentally different with that of traditional e-
commerce. In China, the market value of live-
streamed shopping reached RMB 5.2 billion in 2019,
an increase of 52% from that in 2018 (Hu, 2020).
As the market share of e-commerce live streaming
continues to grow, scholars have begun to pay
attention to consumer behaviors in e-commerce live
streaming, like customer engagement (Hu, 2020) and
purchase behavior (Zhang, 2020). An impulse
purchase is described as an unplanned, compelling
and hedonically complex purchasing process in
which customers make a sudden and immediate
purchase without preshopping intentions (Chan,
2017). Compared with physical shopping, consumers
are more impulsive when shopping online (Wu,
2020). Previous studies found the effect of some
atmospherics elements on customers’ impulse
purchases in the context of offline store, such as
layout (Flamand, 2017), music, lighting and staff
(Barros, 2019). However, to date, few studies have
paid attention what elements constitute of
atmospherics in e-commerce live streaming, and
whether and how these elements affect customers’
impulse purchases. As such, this study aims to
identify the elements of physical and social
atmospherics in e-commerce live streaming and use
the Stimulus-Organism-Response (S-O-R)
framework to investigate how customers’ impulse
purchases are impacted by physical and social
atmospheric elements of e-commerce live streaming.
2 THEORETICAL
BACKGROUND AND
HYPOTHESES
The S-O-R framework was proposed by Mehrabian
and Russell (Mehrabian, 1974) and assumes that the
environment contains stimuli that affect people’s
Yan, L. and Xue, M.
Effect of Atmospherics on Impulse Purchases in Live Streaming: Based on Structural Equation Model.
DOI: 10.5220/0011720400003607
In Proceedings of the 1st International Conference on Public Management, Digital Economy and Internet Technology (ICPDI 2022), pages 31-36
ISBN: 978-989-758-620-0
Copyright
c
 2023 by SCITEPRESS – Science and Technology Publications, Lda. Under CC license (CC BY-NC-ND 4.0)
31

internal, or organismic, states (O), which in turn lead
to approach or avoidance responses (R). The stimuli
in the S-O-R framework are represented by a set of
attributes that affect consumer perceptions
(Mehrabian, 1974). These attributes are the starting
point for the formation of consumer behavior; that is,
they are clues that stimulate consumer cognition and
awareness to take action. Organisms are the second
component of the S-O-R framework. Consumers’
affective and cognitive reactions to an environment
are deemed to be organismic responses (Mehrabian,
1974). Affective reactions are related to an
individual’s emotional response when he or she is
stimulated by the environment (Xiang, 2016). A
cognitive reaction is defined as the “mental process
occurring in an individual’s mind when he or she
interacts with the stimulus” (Eroglu, 2001). In line
with the S-O-R model, responses represent the final
outcomes and decisions of users, which include
approach or avoidance behaviors (Mehrabian, 1974).
In the current study, we will incorporate elements
of the physical and social atmospherics of e-
commerce live streaming as stimuli and investigate
the effect of these stimuli on consumers’ affective
(arousal) and cognitive reactions (perceived
credibility) as well as the subsequent effect on
customers’ responses (i.e., impulse purchases).
Visual appeal is a critical dimension of physical
atmospherics (Bitner, 1992). With reference to Tang
and Zhang (Tang, 2020), this study defines visual
appeal as a set of decoration, design and layout
characteristics that are related to the attractiveness of
an e-commerce live-streaming studio. Arousal is a
state of feeling that varies from feelings of
excitement, stimulation, alertness or activeness, to
feeling of being tired, sleepy, or bored (Chan, 2017).
Existing studies have confirmed that visual appeal is
an important aspect of shopping environments
because they can create a pleasurable interaction and
increase consumers’ excitement. For example, Barros
et al. found that the design of traditional retail stores
positively effects the arousal of consumers (Barros,
2019). Eroglu et al. demonstrated that the decoration
of site atmospherics positively influences users’
arousal (Eroglu, 2001). Based on the influence of
visual appeal on users’ arousal in the shopping
environment, this study speculates that in the e-
commerce live-streaming setting, visual appeal has a
positive impact on arousal.
H1. Customers’ perception of visual appeal is
positively related to arousal.
Social atmospherics have been investigated in
terms of salespersons and other customers (Baker,
1992). In this study, we investigated social
atmospheric cues in terms of other viewers and
streamers.
According to Manning theory (Wicker, 1973), to
maintain a particular setting, the behaviors of a
certain number of people are necessary. Past research
has suggested that the expressive behavioral patterns
of other customers, like other viewers’ clapping after
a play and shouting and booing at a sports game
(Uhrich, 2012), as well as other customers’
purchasing behaviors at a flea market (Grove, 1997).
In the context of this study, other viewers’
engagement behaviors refer to behaviors such as
making purchases, “liking” the live stream, sharing
with friends, joining fans, and interacting with the
streamer. In the live-streaming context, other
viewers’ engagement behaviors can be seen in full
view. We propose that these behaviors are preferable
environmental components and sources of
amusement during live-streaming activities, which
can increase customers’ excitement. Based on the
above discussion, we propose the following
hypothesis:
H2. Other viewers’ engagement behaviors are
positively related to customers’ arousal.
Affective delivery is mainly accomplished
through an individual’s facial expression (e.g., a
smile) and manner of speaking (e.g., in a positive,
passionate tone) (Wichroski, 1994). In the context of
service interaction, studies have found that emotional
contagion creates a ripple effect from employees to
customers; that is, the positive emotions displayed by
frontline employees have an impact on customers’
positive emotions (Tsai, 2002). An employee smiling
at customers may be contagious, which will change
the emotional state of customers and further affect
their perception and evaluation of their service
exposure (Tsai, 2002). We believe that in the context
of e-commerce live streaming, streamers’ positive
affective delivery, including smiles and passionate
tones, will positively affect customers’ emotional
experience. Based on the above discussion, we
propose the following hypothesis:
H3. Streamers’ affective delivery is positively
related to customers’ arousal.
Elaborate information often includes more details
about the product and how and where the product can
be used in specific contexts (Mudambi, 2010), which
reduce potential risks and increase the level of trust
among consumers. For example, in virtual
communities, elaborate posts and comments will help
users gain a better understanding of the topic, feel
support from others and make better decisions
(Zhang, 2008). In the context of this research, the
elaborate information provided by a streamer implies
ICPDI 2022 - International Conference on Public Management, Digital Economy and Internet Technology
32

that he or she may have more consumption
experience and product-related knowledge, thereby
providing consumers with credible knowledge about
products and services. We propose that streamers
who are high in expertise are likely to possess greater
awareness and knowledge of the products they
recommend, a fact reflected by the elaborateness of
their information. Based on the above discussion, we
propose the following hypothesis:
H4. The providing of elaborate information is
positively related to customers’ perceived credibility.
Affective reactions have been proven to be
prominent determining factors of impulse purchase
behaviors (Chan, 2017). Past studies have suggested
that customers’ perceived arousal is linked to their
increased risk taking (Wu, 2020) and, subsequently,
their purchase fever (Adam, 2019). Customers with
excited emotions are more likely to be impulsive in
spending more money and purchasing more products.
In the context of e-commerce live streaming, excited
customers are more inclined to experience purchase
fever, which encourages them to buy products that
they did not originally intend to purchase. Hence, we
propose the following hypothesis:
H5. Perceived arousal is positively related to
customers’ making impulse purchases.
Impulse purchases usually occur under the
condition that customers believe that such purchases
are appropriate (Rook, 1995). Research in the context
of e-commerce has also highlighted the influence of
trusting beliefs on users’ intention to follow an e-
retailer’s advice (McKnight, 2002). Some scholars
have found that the credibility of online stores plays
a critical role in customers’ purchasing decisions
(Kim, 2008). Trust can make people have positive
feelings about online sellers and, thus, increase their
willingness to purchase from these sellers. In this
context, viewers’ perceived credibility of streamers
makes them believe that the product is of high quality
and worth buying, which induces viewers to follow
streamers’ advice and finally leads viewers to make
impulse purchases. Based on the above discussion,
we propose the following hypothesis:
H6. Perceived credibility is positively related to
customers’ making impulse purchases.
3 METHODS
To increase the reliability and validity of each
question, we conducted a pilot study before our main
survey. The pilot study helped us refine the survey
questionnaire, solve small problems related to some
measurement items, and improve the readability of
the items.
To test our theoretical model, we selected Taobao
Live—the largest e-commerce live-streaming
platform in China—as an appropriate source of data
for our main survey. The questionnaire was set up on
Wenjuanxing, a Chinese online market research
website, which is able to forward the link of the
questionnaire to potential respondents. Since this
research focuses on customers’ willingness to engage
in live-streaming activities, we first ask participants
to finish a question to screen out those who have not
previously watched live-streaming activities on
Taobao Live. In the end, 532 responses were
obtained. After removing invalid questionnaires, 509
valid questionnaires were obtained.
The measures used were adapted from the
literature and slightly modified to fit the context of e-
commerce live streaming. All the items used 5-point
Likert scales ranging from 1 (strongly disagree) to 5
(strongly agree). We choose items from Blázquez
(Blázquez, 2014) to measure visual appeal.
Engagement behavior was measured using items
drawn from (Hu, 2020). Affective delivery was
measured using items drawn from (Tsai, 2002). Items
were adapted from Mudambi and Schuff (Mudambi,
2010) to measure providing elaborate information.
We adapted items from Barbin and Darden (Babin,
1995) to measure perceived arousal. The scale
measuring Perceived credibility were adapted form
Filieri et al. (Filieri, 2015). Impulse purchase was
measured using items drawn from Beatty and Ferrell
(Beatty, 1998).
We conducted Harman’s one-factor test to check
for common method variance. As a result, a total of 7
factors with eigenvalues greater than 1 were
extracted, and the first factor explained 16.53% of the
total variance. Since the number of factors greater
than 1 is obtained and no one factor can explain most
of the covariance of the variables, this shows that
there is no common method bias in our survey.
Subsequently, to test the measurement validity of
the scale, this study used AMOS 20.0 to conduct a
confirmatory factor analysis. The results showed a
good model fit to the data: χ2 = 578.76, yielding a
value of χ2/df = 1.59, CFI = 0.95, TLI = 0.94, NFI =
0.92 and RMSEA = 0.04. The standard loadings of the
retained items ranged from 0.70 to 0.90. The average
variance extracted (AVE) of each construct was
greater than 0.5, which implied that the scales have
good aggregate validity. The composite reliability
(CR) and Cronbach’s alpha coefficient were both
greater than 0.70, indicating high reliability.
To estimate the discriminative validity of the
Effect of Atmospherics on Impulse Purchases in Live Streaming: Based on Structural Equation Model
33

Notes. *p＜.05; **p＜.01; and *** p＜.001.
Figure 1: Results of the structural equation modeling analysis.
scale, this study compared the square root of the AVE
score of each construct with the correlation
coefficient between the construct and other
constructs. The results showed that the square root of
the AVE score was higher than the correlation
coefficient of any other variables, thus indicating an
acceptable level of discriminant validity.
Structural equation modeling was employed using
AMOS 20.0 to test our proposed hypotheses. The
overall fit of the structural model was highly
acceptable: χ2= 505.96, df = 364, yielding a value of
χ2/df = 1.39; CFI = 0.92, TLI = 0.91, NFI = 0.90 and
RMSEA = 0.06. Figure 1 shows the results of the
structural equation modeling analysis.
The results showed that the path coefficient
between visual appeal and perceived arousal was β =
0.26 (p < 0.001), indicating that visual appeal are
positively associated with customers’ perceived
arousal, thus supporting H1.
The results showed that the path coefficient
between visual appeal and perceived arousal was β =
0.26 (p < 0.001), indicating that visual appeal is
positively associated with customers’ perceived
arousal, thus supporting H1.
The perception of other viewers’ engagement
behavior was positively related to customers’
perceived arousal (β = 0.32, p < 0.001), thus
supporting H2.
The results showed that a streamer’s affective
delivery was positively related to customers’
perceived arousal (β = 0.41, p < 0.001), thus
supporting H3.
The effect of streamers providing elaborate
information on customers’ perceived credibility was
significantly positive (β = 0.39, p < 0.001), thus
supporting H4.
Customers’ perceived arousal (β = 0.21, p < 0.01)
and perceived credibility of streamers (β = 0.43, p <
0.001) were positively related to customers making
impulse purchases.
4 CONCLUSION
This study was designed to investigate the influencing
effect of atmospheric elements on customers’
perceived arousal and credibility, and subsequently
on their impulse purchases.
The results indicate that visual appeal positively
affects viewers’ perceived arousal and, subsequently,
their making impulse purchases. Although previous
research has identified effects of the decor of brick-
and-mortar stores (Barros, 2019) and the appealing
design of traditional e-commerce websites (Chan,
2017; Eroglu, 2001) on customers’ purchase
behavior, to date, few studies have investigated the
effects of visual appeal on consumer behavior in e-
commerce live streaming. The current study extends
prior studies to demonstrate the effect of visual appeal
on customers making impulse purchases in the
context of e-commerce live streaming.
Other viewers’ engagement behavior has been
proven to be positively related to customers’ arousal
and their subsequent impulse purchases. Unlike
traditional e-commerce, live streaming can show the
real-time responses of other viewers. This study first
investigates the promoting effect of other viewers’
behavior on customers’ purchases in the context of e-
commerce live streaming.
The findings show that streamers’ affective
delivery is positively related to customers’ perceived
arousal from live-streaming activities. The
phenomenon of “emotional contagion” (Tsai, 2002)
Visual appeal
Engagement behavior
Affective delivery
Providing elaborate information
Perceived arousal
Perceived credibility
Impulse purchases
0.26***
0.32***
0.41***
0.39***
0.21**
0.43***
ICPDI 2022 - International Conference on Public Management, Digital Economy and Internet Technology
34

occurs between streamers and customers. Customers
can perceive more excitement when a streamer’s
affect is delivered in a joyful and passionate manner.
Thus, a streamer plays a very important role in live
streaming (Hou, 2020). Existing studies have
confirmed the influence of the appearance appeal of
an entertainment streamer on audiences’ attitude
changes (Hou, 2020), but few studies have
investigated the effects of sale streamers’ affective
delivery on viewers’ purchase behavior.
The results indicate that streamers providing
elaborate information positively affect customers’
perceived credibility, which in turn positively
impacts consumers making impulse purchases. This
finding seems to be consistent with the notion of past
research that an individual will use central cues to
infer whether an information source is credible
(Racherla, 2012). In this study, the elaborate
information provided by a streamer can be regarded
as a central cue, which enables customers to assess
whether he or she is credible.
REFERENCES
A. Mehrabian, and J. A. Russell, An approach to
environmental psychology. Cambrige, MA: MIT
Press,1974.
A. W. Wicker, “Undermanning theory and research:
implications for the study of psychological and
behavioral effects of excess populations,”
Representative research in social psychology, 1973,
4(1), pp.185-206.
B.J. Babin, and W.R. Darden, “Consumer Self-Regulation
in a Retail Environment,” Journal of Retailing, 1995,
71(1), pp.47-70.
D. W. Rook, and R. J. Fisher, “Normative influences on
impulsive buying behavior,” Journal of Consumer
Research, 1995, 22(3), pp. 305-313.
D. H. McKnight, V. Choudhury, and C. Kacmar, “The
impact of initial consumer trust on intentions to transact
with a web site: A trust building model,” Journal of
Strategic Information Systems, 2002, 11(3-4), 297-323.
F. Hou, Z. Guan, B. Li, and A.Y. L. Chong, “Factors
influencing people’s continuous watching intention and
consumption intention in live streaming: Evidence from
China,” Internet Research, 2020, 30(1), PP.141-163.
J. Tang, and P. Zhang, “The impact of atmospheric cues on
consumers’ approach and avoidance behavioral
intentions in social commerce websites,” Computers in
Human Behavior, 2020, 108, pp.1-17.
J. Baker, M. Levy, and D. Grewal, “An experimental
approach to making retail store environment decisions,”
Journal of Retailing, 1992, 68(4), pp. 445-460.
L. B. L. Barros, M. Petroll, C. Damacena, and M. Knoppe,
“Store atmosphere and impulse: a cross-cultural study,”
International Journal of Retail & Distribution
Management, 2019, 47(8), pp. 817-835.
L. Xiang, X. Zheng, M. K. O. Lee, and D. Zhao, “Exploring
consumers’ impulse buying behavior on social
commerce platform: The role of parasocial interaction,”
International Journal of Information Management,
2016, 36(3), pp. 333-347.
L. B. L. Barros, M. Petroll, C. Damacena, and M. Knoppe,
“Store atmosphere and impulse: a cross-cultural study,”
International Journal of Retail & Distribution
Management, 2019, 47(8), pp.817-835.
M. Hu, and S.S. Chaudhry, “Enhancing consumer
engagement in e-commerce live streaming via relational
bonds,” Internet Research, 2020, 30 (3), pp.1019-1041.
M. Zhang, F. Qin, G. A. Wang, and C. Luo, “The impact of
live video streaming on online purchase intention,” The
Service Industries Journal, 2020, 40(9-10), pp. 656-681.
M. J. Bitner, “Servicescapes: the impact of physical
surroundings on customers and employees,” Journal of
Marketing, 1992, 56, pp. 57-71.
M.A. Wichroski, “The secretary: Invisible labor in the work
world of women,” Human Organization, 1994, 53(1),
pp. 33-41.
M.T. Adam, G. Ku, and E. Lux, “Auction fever: The
unrecognized effects of incidental arousal – Science
Direct,” Journal of Experimental Social Psychology,
2019, 80, pp. 52-58.
M. Kim, and S. Lennon, “The effects of visual and verbal
information on attitudes and purchase intentions in
internet shopping,” Psychology and Marketing, 2008,
25(2), pp.146-178.
M. Blázquez, “Fashion shopping in multichannel retail: the
role of technology in enhancing the customer
experience,” International Journal of Electronic
Commerce, 2014, 28(4), pp.97-116.
P. Racherla, W. Friske, “Perceived ‘usefulness’ of online
consumer reviews: an exploratory investigation across
three services categories,” Electronic Commerce
Research and Applications, 2012, 11(1-6), PP. 548-559.
R. Filieri, S. Alguezaui, and F. Mcleay, “Why do travelers
trust tripadvisor? Antecedents of trust towards
consumer-generated media and its influence on
recommendation adoption and word of mouth,”
Tourism Management, 2015, 51, pp.174-185.
S. A. Eroglu, K. A. Machleit, and L. M. Davis,
“Atmospheric qualities of online retailing: A
conceptual model and implications,” Journal of
Business Research, 2001, 54(2), pp. 177-184.
S. Uhrich, and M. Benkenstein, “Physical and social
atmospheric effects in hedonic service consumption:
Customers’ roles at sporting events,” The Service
Industries Journal, 2012, 32(11-12), pp. 1741-1757.
S. J. Grove, and R. P. Fisk, “The impact of other customers
on service experiences: A critical incident examination
of ‘getting along’,” Journal of Retailing, 1997, 73(1),
pp. 63-85.
S.M. Mudambi, and D. Schuff, “What makes a helpful
online review? a study of customer reviews on
amazon.com,” MIS Quarterly, 2010, 34(1), pp.185-200.
Effect of Atmospherics on Impulse Purchases in Live Streaming: Based on Structural Equation Model
35

S. E. Beatty, and M. E. Ferrell, “Impulse buying: modeling
its precursors,” Journal of Retailing, 1998, 74(2),
pp.169-191.
T. K. H. Chan, C. M. K. Cheung, and Z. W. Y. Lee, “The
state of online impulse-buying research: a literature
analysis,” Information & Management, 2017, 54, pp.
204-217.
T. Flamand, A. Ghoniem, and B. Maddah, “Promoting
impulse buying by allocating retail shelf space to
grouped product categories,” Journal of the Operational
Research Society, 2017, 67, pp. 953-969.
W. C. Tsai, and Y.M. Huang, “Mechanisms Linking
Employee Affective Delivery and Customer Behavioral
Intentions,” Journal of Applied Psychology, 2002,
87(5), pp.1001-1008.
W. Zhang, and S.A. Watts, “Capitalizing on content:
information adoption in two online communities,”
Journal of the Association for Information Systems,
2008, 9, pp. 73-94.
Y. Sun, X. Shao, and X. Li, “How live streaming influences
purchase intentions in social commerce: An IT
affordance perspective,” Electronic Commerce
Research and Applications, 2019, 37, pp. 1-12.
Y. Wu, L. Xin, D. Li, J. Yu, and J. Guo, “How does scarcity
promotion lead to impulse purchase in the online
market? a field experiment,” Information &
Management, 2020, 58(1), pp.1-10.
ICPDI 2022 - International Conference on Public Management, Digital Economy and Internet Technology
36