Effects of sales promotion on impulse buying

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What are the effects of sales promotion
on impulse buying on social commerce?
Master Thesis
Hoang – Quan NGUYEN
Supervisor
Dr. Constantinos Coursaris
T H E S I S I N F O A B S T R A C T
Submissiondate:
November 22, 2018
Online impulse purchasing has become a popular research topic in
recent years. However, there are few studies have been made to
evaluate this phenomenon on social commerce context as well as
reveal the underneath of customer’s impulsive behavior. To address
these research gaps, this study investigates the effect of sales
promotion to individuals’ urge to buy impulsively (UBI) in social
commerce through shopping emotions. Two group factors of sales
promotion on social commerce were set up: (1) Promotion Methods,
including (1.1) Money – based promotion, (1.2) Product- based
promotion, and (2) Promotion Scarcity, including (1.1) Time scarcity,
(2.2)Quantity scarcity and(2.3) Frequency scarcity. Twogroupfactors
create six conditions for the experimental design. Results were
analyzed from the data of 181 respondent from the Qualtrics online
survey. First, different promotion stimuli caused different urge to buy
impulsively responses. However, there is no significant difference in
emotions of individuals when exposing with different sales
promotions. This study also confirms the roles of emotional responses
to impulse buying behaviors. Lastly, impulsiveness is founded to have
a significant effect on the urge to buy impulsively but no mediation
effect on the relationship between shopping emotions and UBI.
Keywords:
Social Commerce
Sales Promotion Stimuli
Impulse buying
Urge to buy impulsively
Emotional Response
Impulsiveness

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Table of Contents
I. Introduction.....................................................................................................................................................................5
II. Literature Review.........................................................................................................................................................6
2.1 SOR framework....................................................................................................................................................6
2.2 Impulse buying.....................................................................................................................................................6
2.3 Urge to buy impulsively..................................................................................................................................8
2.4 Social commerce stimuli..............................................................................................................................11
2.5 Pleasure – Arousal – Dominance (PAD model).............................................................................12
2.6 Impulsiveness....................................................................................................................................................13
III. Theoretical foundation and Hypothesis Development.........................................................................15
3.1 Stimulus: Sales Promotion................................................................................................................................15
3.2 Organism: Emotional Responses..................................................................................................................16
3.3 Behavioral response: Urge to buy impulsively ....................................................................................17
3.4 Effect of impulsiveness.......................................................................................................................................17
IV. Research Methodology.............................................................................................................................................19
4.1 Research Design......................................................................................................................................................19
4.1.1 Three design methods................................................................................................................................19
4.1.2 Quantitative or qualitative.......................................................................................................................19
4.2 Participants................................................................................................................................................................20
4.3 Experiment Procedure........................................................................................................................................21
4.3.1 Questionnaire design..................................................................................................................................21
4.3.2 Pilot study..........................................................................................................................................................21
4.3.3 Collection procedure...................................................................................................................................21
4.3.4 Stimulus material ..........................................................................................................................................22
4.3.5 Procedures.........................................................................................................................................................23
4.4 Measurement Instrument.................................................................................................................................24
4.4.1 Emotion Measurement...............................................................................................................................24
4.4.2 Urge to Buy Impulsively Measurement...........................................................................................26
4.4.3 Impulsiveness Measurement.................................................................................................................27
V. Data analysis and Results.........................................................................................................................................28
5.1 Two-ways ANOVA analysis..............................................................................................................................28
5.1.1 Sales Promotion Stimuli - Emotions..................................................................................................28

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5.1.2 Sales Promotion Stimuli - UBI................................................................................................................32
5.2 Regression analysis...............................................................................................................................................33
5.2.1 Arousal – Pleasure........................................................................................................................................33
5.2.2 Dominance – Pleasure................................................................................................................................34
5.2.3 Pleasure – UBI..................................................................................................................................................34
5.2.4 Mediating Effect of Pleasure...................................................................................................................35
5.2.5 Impulsiveness – UBI.....................................................................................................................................36
5.2.6 Results Summary...........................................................................................................................................37
VI. Discussion and Implication....................................................................................................................................38
6.1 Findings and discussion.....................................................................................................................................38
6.2 Academic implication ..........................................................................................................................................38
6.3 Practical implication.............................................................................................................................................39
6.4 Limitation and future research......................................................................................................................39
References...............................................................................................................................................................................41
Appendix A: Stimuli of social commerce promotions...................................................................................45
Appendix B: Survey............................................................................................................................................................51

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List of Tables
Table 1. Literature summary........................................................................................................................................10
Table 2: Sample profile....................................................................................................................................................20
Table 3: Experimental conditions.............................................................................................................................23
Table 4. Emotion Measurement.................................................................................................................................24
Table 5. Emotions - KMO and Bartlett's Test....................................................................................................24
Table 6. Emotions – Communalities ........................................................................................................................24
Table 7. Emotions - Total Variance Explained..................................................................................................25
Table 8. Dominance - Reliability Statistics...........................................................................................................25
Table 9. Dominance - Correlations...........................................................................................................................26
Table 10. Urge to Buy Impulsively Measurement...........................................................................................26
Table 11.UBI - KMO and Bartlett's Test................................................................................................................26
Table 12. UBI - Total Variance Explained.............................................................................................................26
Table 13. UBI - Reliability Statistics .........................................................................................................................27
Table 14. Impulsiveness Measurement.................................................................................................................27
Table 15. Impulsiveness - KMO and Bartlett's Test .......................................................................................27
Table 16. Impulsiveness - Total Variance Explained.....................................................................................28
Table 17. Impulsiveness - Reliability Statistics.................................................................................................28
Table 18. ANOVA Result (Promotions - Pleasure)..........................................................................................29
Table 19. Main Effect Means (Promotions - Pleasure).................................................................................29
Table 20. ANOVA Result (Promotions - Arousal)............................................................................................29
Table 21. Main Effect Means (Promotions - Arousal)...................................................................................30
Table 22. ANOVA Result (Promotions - Dominance)....................................................................................30
Table 23. Main Effect Means (Promotions - Dominance)...........................................................................31
Table 24. Group Statistics of Promotion Methods..........................................................................................31
Table 25. ANOVA Result (Promotions - Urge to buy impulsively)........................................................32
Table 26. Interaction Effect Means (Promotions - Urge to buy impulsively).................................32
Table 27. Regression Analysis (Arousal - Pleasure)......................................................................................33
Table 28. Regression Analysis (Dominance- Pleasure)...............................................................................34
Table 29. Regression Analysis (Pleasure-UBI)..................................................................................................35
Table 30. Mediation analysis (Dominance - Pleasure - UBI)....................................................................35
Table 31. Mediation analysis (Arousal - Pleasure - UBI).............................................................................36
Table 32. Table 28. Regression Analysis (Impulsiveness-UBI)...............................................................36
Table 33. Moderated Regression Analysis Results.........................................................................................37

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I. Introduction
With the development of the internet, e-commerce becomes more and more important. The
switching from the shopping of line to online has been a trend for decades and the behavior
of customer on the online environment has been considered as an important topic. There
was a force that pushes online shopping to a new level is the development of the social
network. The social network is one of the fastest growing marketing channels in the world.
It brings a new area for researcher and business practice on online environment beside
offline one. With the fast development of the social network, social media and e-commerce
are two phenomenal which were studied in marketing and other academic areas. A
phenomenon of the social network, that has the characteristic of both social media and e-
commerce is social commerce. The definition of social commerce may vary by papers, but it
can be referred to the use of social media for commercial activities which include social
interaction and the contribution of users (Liang, et al. 2011). To be successful in competitive
markets nowadays, businesses must take into account the participation of customer and
understand their motivation on social commerce.
In academic areas, there are a lot of papers researched on consumer decision making as a
rational process. That the purchasing decision of customer is a reasoned action. However,
there were a few papers considered these decisions as irrational ones. Beside purchasing
intention, as a rational behavior, impulse buying behavior is a very potential topic to
research on purchasing behavior. Impulse purchasing has been studied in both offline and
online context for years. However, few papers investigate this topic on social commerce
context (Chan, Cheung and Lee 2017). In area of experiment research design, various factors
affecting impulse buying have been studies in recent researches, such as media format
(Adelaar, et al. 2003), payment feature (Dutta, Jarvenpaa and Tomak 2003), website feature
(Hu, et al. 2016; Parboteeah, et al. 2009; Wells, et al. 2011), scarcity (Zheng, Liu and Zhao
2013). Moreover, a few types of research study impulse purchasing in social commerce
context, such as on Facebook group (Chen, Su and Widjaja 2016), some Korean social
commerce platform (Song, Chung and Koo 2015) or Wechat (Chena, et al. 2018). However,
there were no studies about this topic on Instagram.
Moreover, most of the previous research focuses on technical factors such as website
stimulus. It is required to consider marketing stimuli, such as promotion, on the effect to
impulse purchasing. Previous researches studied the promotion of online impulse
purchasing but it was just a basic approach to bonus and discount promotion bonus and
discount (Xu and Huang 2014).
Therefore, in this research, we intend to fulfill these research gaps in the literature and
answer the following question:
- What are the effects ofsales promotion on impulse buying behavior on social commerce,
especially on Instagram shopping platform?
- What is the underneath of customer impulse purchasing decision on social commerce?
To answer these questions, we apply the SOR (stimulus-organism – response) framework
and PAD (pleasure – arousal – dominance) model in the research. Moreover, personal trait,

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such asimpulsiveness, is taken into accountto understandfully aboutimpulsive behavioron
social commerce.
The structureofthis paperasfollows. First, we start with the literature review to understand
the relevant theory. Theoretical foundation and hypothesis are discussed in the next section.
This part is followed by the research methodology and data analysis. The last part is for
discussion and implication form the results as well as limitation and conclusions.
II. Literature Review
2.1 SOR framework
According to Wu and Li 2018, this model was first introduced in 1928 and known for known
for describing how the organism mediates the relationship between the stimulus and
response by suggesting different mediating mechanisms operating in the organism. The
mediating mechanism or organism, translate the environmental stimuli to responses. The
response can be behaviors such as customers’ intentions or perceptions. In the early period
after being introduced, this model was studied mostly in psychology.
The SOR framework is the extension of the stimulus-response framework. This model was
extended by Mehrabian and Russell 1974 for both physical and nonphysical elements. In the
research, the aspect of the environment (S) was expanded to customer experience or a
physical appearance of a store. These physical stimuli can affect to organismic experiences
(O), such as perception, feeling, and thinking activities, which in turn drive their behavioral
responses (R), such as satisfaction, support, intention, number of items purchased, and
money spent in the store. The following diagram simplifies the SOR model.
Eroglu and Davis 2003 is the first research that use this model to apply for the online
environment when verifying that the atmospheric cues (S) of the online store affect
shoppers’ cognitive and emotional states (O), which then influence their shopping
behavioral outcomes (R). There is two type of stimulus that arouses consumers (Chan,
Cheung and Lee 2017), which are internal and external.
Wecan seethat with the developmentof technologyandthe introduction of the internet, this
model has been applied comprehensively in many areas. In the context of social commerce,
stimulus phenomenoncanbeclassified in 4 main themes accordingto (Zhangand Benyoucef
2016). With each concept, we will review the definition and discuss the main finding and
limitation of previous researches.
2.2 Impulse buying
Impulse buying is defined as “a sudden and immediate purchase with no pre-shopping
intentionseither tobuy the specific product category or to full fill a specific buying task” (Beatty
and Ferrell 1998). Impulse buying has been considered an important purchasing behavior
in shopping. In a research of Verhagen and Dolen 2011 showed that impulse buying

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behaviors happen in about 40% of all online expenditures. Easy accessing to the product,
easy purchasing, the lack of social pressure and the absence of delivery effort were indicated
as the reasons for that case.
On the path of purchase, the customer is easy to be attracted by the combination of social
and commercial activities. The amount of online information growth day by day. The
customer has to deal with more and more information that affect their purchasing decision.
Duringthe onlineshopping, therearemoreofmarketing stimulus andinformationthat affect
customer desire to buy something unintentionally (L. Huang 2016).
There are three types of impulse buying, including pure, suggestive, reminder, and planned
impulse buying (Wells, Parboteeah and Valacich 2011). It’s called pure impulse buying when
an individual has an unplanned buying behavior after experience whit a stimulus, such as a
promotion, call to action, decoration. With this type of stimulus, there is almost no plan
before the purchase. This kind of behavior happens a lot. An example in the online
environment is that when a customer goes to Amazon to search for some product
information and have no plan to buy anything. Or it can be an individual who browsed on
Instagram for kill time and saw a promotion post of a good promotion for running shoe. He
or she may click on the promotion link and purchased the product without planning before.
The decision of buying some books, which can be considered a pure impulse buying
behavior.
If a customer makes a purchase after experience some cue, information or stimuli related to
the product, it is a reminder impulse. In this case, the individual still did not have a plan to
buy anything but he or she exposed to the items, it reminds them about their needs or their
previous experience. For example, one female searching on www.sephora.com for perfume
product then she saw a cleanser appeared on the website when she realized she was out of
cleanser. She immediately bought the product without planning.
Suggestive purchasing happens when an individual sees the stimuli for the first time and
then imagines a need for the products. The individual has neither experience nor desire for
the item. One example is that a female customer shopping online on www.amazon.com has
an unplanned purchase of a moisturizer product which is suggested by an advertising on the
online platform. The man saw the advertising and he visualizes of how he can take care of
his skin with the product despite he has never used it before.
The last type of this phenomenon is planned impulse purchase. This behavior happens when
an individual does not have a plan to purchase a product but searching the information of
the product such as promotion to take advantage of. When he or she does shopping, there is
no item in the list but he or she can decide to buy the product base on the promotions
program. A good example of this behavior is when a person on Thank giving days, go to
online on Amazon to search for good deals. He or she may do not have the plan to buy a
certain type for the product but when he or she experiences a good stimulus, such as a good
discount, he or she would decide to buy the product to have the advantage of good value.
All four types of impulse are differing base on how the individual had experience with the
product and stimulus, but they have the same thread of unplanned nature of the behavior.

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2.3 Urge to buy impulsively
When it comes to impulse buying, the consumer’s reaction can be two-fold. Firstly, a
customer may feel a sudden, unplanned or spontaneous urge to buy the product after
experience a stimulus. It can be an environmental factor such as decoration, website
interface, promotional information or internal factor such as individual trait. In this state,
the urge to buy (UTB) phenomenon has been defined as “the state of desire that is
experienced upon encountering an object in the environment” (Beatty and Ferrell 1998).
UTB has been defined as a state that is complex, unexpected, sometimes tempting, and
persistent (Piron 1991). After that, the customer decides whether to take the action, which
is impulsively purchasing the product of interest. In other words, the impulse buying
behavior happens after the individual first experiences the urge to buy. Therefore, urge to
buy can be a good prediction for impulse buying behavior. According to Beatty and Ferrell
1998, the more customer experienced with urges to buy state, the higher the likelihood that
they make the decision to purchase impulsively. In this research, it is thus expected to be
positively associated with the actual impulsive buying.
In the control setting, it is challenging to capture the impulse buying behavior (Luo 2005). It
is because the individual becomes less impulsive when he or is being observed (Rook and
Fisher 1995). Social desirability is also a factor that makes a response in controlled settings
become biased (Fisher 1993). It is difficult to examine impulse buying behavior in the most
appropriate setting and at the most appropriate time. Moreover, supporting the previous
findings, there is a limitation of success when studies actual impulse buying behavior in the
online environment.
To overcome that problematic, there are a lot of research papers chose “urge to buy” as a
factor that represents actual impulse buying behavior. This method has been proved in both
offline andonline research.(Beatty andFerrell1998) pointed out that urgeto buy had a high
accuracy of representation of impulse buying behavior. This was confirmed in the online
context in several papers (Parboteeah, et al. 2009).
Therefore, in the context of this paper, which is social commerce on Instagram, urge to buy
is chosen as a proxy factor of impulse purchasing behavior.
The literature on impulse buying and urge to buy mostly show the direct relationship
between stimuli and response of customer on the purchase path (L. Huang 2016). There are
few works of literature that study the internal processes. Despite impulsive buying is a
sudden, unplanned behavior but explore the internal organism of customers is still
important.
Despite impulse buying is not a new phenomenon has been studied, but there are a few
empirical studies about online impulse purchase and the behavior on social commerce
environment.
(Chen, Su and Widjaja 2016) tested the six text dimensions (relevance, ease of
understanding, accuracy, completeness, format, and currency) effect on consumers’ impulse
buying behaviors on Facebook sell and buy group in China. The previous paper just tests the
information quality on e-commerce context on the e-commerce platform, but this paper is
had to fill the gap when examining the stimulus on a social commerce environment.

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Customer experience with high information quality on Facebook sells -buy the group, have a
higher degree impulse buying behavior. The paper also revealed the effect of impulsiveness,
as a personal trait, to the relation between stimuli, information quality, and the response,
impulse purchasing. However, the study just approached the behaviors on one social
commerce platform, which is a Facebook group, while there is more platform such as
Instagram or Pinterest shopping. With the nature of group Facebook, where most of the
transaction is C2C, the finding of this study cannot apply to the B2C transaction. Moreover,
having most respondents who are Asian is also a limitation of the research, which means
there are less diversify in nationality and culture.
(L. Huang2016)studies the effectsof anaffective andreactive factor,which aresocial capital,
content attractiveness on impulse behavior. This research also confirms the difference
between impulse buying and the urge to buy which is a very important phenomenon in this
research.Byapply the SOR model, (L. Huang2016)also revealsan urgeto buyas the internal
process of impulse buying behavior. However, the model of the research is not full enough
to show the underline organism of impulse behavior. Browsing activities are the sequence
of content attractiveness, but the reason underneath this action was not revealed. Lacking
nationality and culture diversity is also a limitation of this studies. The research method,
which is a survey asking about customer past experience on Facebook may have bias and
inaccurate to measure exactly response of individual when shopping online and how the
actual respond to the stimuli.
(L. T. Huang 2017) broadens the context of impulse buying behavior on mobile commerce
when examining the relationship ofpleasure,dominance, andarousalonthe urgeto buy. The
research as examines the effect of website atmospherics and mobile characters, like the
stimulus, on customer urge to buy behavior. It explores the relationship between
environment, organism process, and customer’s responses. Beside managerial implications
and academic contribution. The paper still has some limitation while base only one recalled
the experience of customers who use mobile commerce. It examines the difference between
customer urge to buy base on control variable Impulsive but has not studies how that
personal trait can affect the relationship between emotion and urge to buy behavior.
Promotion and scarcity were on social commerce were first indicated in research of (Song,
Chung and Koo 2015). The paper shows that scarcity message and serendipitous
information has a significant effect on enjoyment which leads to the urge to buy impulsively
which is a predictor of impulse buying. This paper has supported the literature while the
focus on restaurant customer. But the paper can be more fulfilling if testing the different
effect between types of scarcity message, for example, time and quantity scarcity. Moreover,
the behavior of customers may be a different by-product. Therefore, considering various
types of products in the researches of impulse buying on social commerce is important in
future research. In managerial application, discount promotion is just one of several types of
promotion that can affect customer decision, such as a coupon, free gifts or lucky draw. To
show just the discount price as a stimulus factor is not enough to show to the effect of
promotion to customers.

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While Facebook is the most popular social network as well as a social commerce platform,
there are few of research studies impulse purchase behaviors on other social commerce
platforms. (Chena, et al. 2018) implemented the research on WeChat, the best well-known
social network in China. The contribution of the research on literature is that it shows the
importance of trust, which built through recommender-related and product-related signals,
in increasing the urge to buy behavior of the customer. However, the paper just studies the
indirect effect of stimulus to impulse buying through the lens of signaling theory but does
not show the direct effect of observable cures on the dependent variable. This should be a
room for future research. The main findings in previous literature are a sum in the following
table.
Table 1. Literature summary
Source (Chen, Su and
Widjaja 2016)
(L. Huang
2016)
(L. T. Huang
2017)
(Song, Chung
and Koo
2015)
(Chena, et
al. 2018)
Industry C2C retail N/A N/A Foods and
Beverage
N/A
Platform Facebook sell-
buy group
Facebook Mobile
commerce
Korean
Social
Commerce
platforms
Wechat in
China
Total N 277 responses 410 responses 410
responses
332
responses
251
responses
Data
Analysis
Method
Experimental
analysis
comparative
analysis
Confirmatory
factor
analysis
Confirmator
y factor
analysis
Confirmato
ry factor
analysis
Metrics Text
dimensions
(relevance,
ease of
understanding,
accuracy,
completeness,
format, and
currency)
Social Capital
Content
Attractiveness
Website
atmospherics
Mobile
Characteristic
Scarcity
message
Discount
price
Recommen
der related
signals
Product-
related
signals
Domains Information
quality
Communication Website
design
Communicat
ion
Informatio
n quality
Limitations Studies only
one social
commerce
platform.
Lack of culture
diversity
Recalled
experience
Does not
examine the
effect of the
personal trait
Does not
show the
difference
between
No direct
effect of the
stimulus on

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Lack of
nationality and
culture
diversity
Does not have a
practical
application for
the B2C
transaction.
survey, difficult
to examine the
behavior
on the
relationship
between
factors.
Base on
recalled
experience
different
types of
message.
Uses only
one type of
promotion
as a factor.
Lack of
product
diversity
the urge to
buy
2.4 Social commerce stimuli
The development of social commerce cannot succeed without the affection of different
stimulus, which is the controlfactors ofthis paper.This phenomenonisa veryimportant and
relevant research area nowadays. On the perspective of academic research, this is one of the
main trends for future study. According to Lin, Li and Wang 2017, three major research
themes in the current social commerce research are an organization, advertisement, and
word-of-mouth (WOM). Each theme discusses topics such as user-generated content,
reputation, and innovation among others. In addition, there are several trends in this
research area. One of the two main trends is that online reviews, trust, and e-word-of-mouth
(eWOM) are attracting more attention from researchers. This trend represents some
components of social commerce stimuli constructs. Moreover, social commerce stimuli are
very important for business practice because of the importance of social commerce in
decades for business. Social commerce, an evolution of the social network and web 2.0
technologies that emphasize the role of online social networking in facilitating business, has
become popular recently ( (Hu, et al. 2016). Therefore, understanding the stimuli concept
and how they work is very important with businesses to maximize the effect on social
commerce.
According to Chan, Cheung and Lee 2017, social commerce stimulus can be classified into
two categories. The first one is external stimuli. They were website stimulus, marketing
stimulus, and situational stimulus. The second one is an internal stimulus. They were
impulsive consumer characteristic.
On marketing stimuli, there are few articles research about the effect of promotion on
impulse buying. The first one is of (Dawson and Kim 2010), which investigate 20 external
trigger cues by focus interview of online retailer to find what types of stimuli they can use
on their website to encourage impulse buying. The paper shows that sales, promotions,
ideas, and suggestionsaremost desired toolsused online. This researchdid not only confirm
the marketing validation of this stimulus on impulsive behavior context but also open more
opportunities to studies deeper each of these stimuli.
The secondoneis (Xu and Huang2014)which analyzes theeffect ofpricediscount andbonus
pack sales promotion on impulse buying on the online environment. The interesting finding
is that with the utilitarian products, bonus promotions have the more significant effect than
discount promotions on impulse buying, while with the hedonic product, in contrast,

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discount promotions were more effective than bonus promotions. The gap of this research
is that it just analyses the money related promotion, while product-based promotions were
not considered. Therefore, it is an opportunity for this research to fulfill that gap.
In this research, sales promotion is classified into two main groups, represent two factors.
Promotion Scarcity:
Definition of scarcity
As an original definition, scarcity is the imbalance between demand and supply, and this
leads to shortages and competition for resources. The economist Walrus has a definition of
scarcity is “something is useful but of limited quantity”. (Zheng, Liu and Zhao 2013)
Type of scarcity
There are various types of scarcity. It can be classified to types, including product scarcity
and resource scarcity (Hamilton, et al. 2018). Product scarcity is a real or perceived lack of
good or services to the customers in short term or long term. This type of product can be
varied in different modes, such as the limited availability of the size, color or quantity of a
specific brand. Resource scarcity related to the various form of capital, such as financial,
social, cultural or time resources. This type of scarcity relates more to an individual because
these resources are necessary for survival, maintenance or growth.
In the context of sales promotion, scarcity can be classified into three types, continuing time
scarcity, quantity scarcity and frequency scarcity (Zheng, Liu and Zhao 2013). Continuing
time scarcity indicates that consumer can receive the promotion in a short amount of time.
For example, “the promotion only lasts a day. Buy now!” is a message which delivery
continuing time scarcity. Quantity scarcity is accounted for the limitation of production
quantity. For example, there is a promotion of a headphone with a good price that only
applied for 100 first bought products. Promotion with frequency scarcity is the one with a
low frequency. For instance, Alibaba is very famous for Single Day, which is the events a lot
of good promotion which happens once a year on November 1st.
In this research, the classification scarcity into three types, time, quantity and frequency are
used,
Promotion methods
In other dimension, sales promotion was categorized to Product promotion and
environment promotions (Alvarez and Casielles 2005). Environment promotion, or store –
based promotion is related more to offline store, therefore, in the context of this paper, we
just focus on product promotion. Product promotion can be classified to product-based and
money-basedpromotion.Productbasedincluded 2 main schemessuch as pricereducing and
coupon. Product-based include extra product and samples schemes (Brassington and Pettit
1997).
2.5 Pleasure – Arousal – Dominance (PAD model)
If we just investigate the effect of stimuli to impulse buying, it would provide a limited view
ofthe whole phenomenon.To identify the underneathof this relationship is also very critical
which give us more understanding about the behavior. Moreover, finding and investigating
the right organism will full fill the SOR framework which proposed in this research.

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Peoplejoin a social network to exchangeforinformation with their network. In a transitional
context like communities, people communication and has emotion to each other. That’s why
we can see arelationship like lovers, friends, families, andthey haveinterpersonalemotions.
An individual in a relationship can affect the emotion of others. (Dixon-Gordon, Bernecker
and Christensen 2015). Therefore, it is important to consider emotions in a social network
context.
Emotion is defined as the states of feeling that may affect human behaviors. (Dwyer and
Scampion 1995). Emotions have a significant effect on an individual behavior not only in a
cognitive way but also a physical way.
In previous literature, impulse buying is considered a behavioral factor. It is also suggested
that emotional response is the precedence of impulse buying. According to Donovan and
Rossiter 1982, there are three factors of emotional response that can be obtained by self-
reports, including pleasure, arousal, and dominance.
First, pleasure is defined as a state of feeling of a person, including good, joyful, happy or
satisfied with a particular situation.
Arousal is defined as the extent to which a person feels of excitement, stimulation, alertness
or activeness to being tired, sleepy or bored.
Dominance, this is a state of feeling that a person feels in control of or free to act in a
particular situation.
In this research, we want to investigate emotion as the organism that explains customer
impulsive behavior.
2.6 Impulsiveness
To understand deeper of the buying behavior such as impulse buying, it is important to
consider both inherent trait and their state of mind of customers (Wells, Parboteeah and
Valacich 2011). The personal trait can be used as a control factor that distinguishes between
individuals or groups. There are common characteristic and traits of a person who
frequently experience with impulsive behaviors. For example, it is founded that there is a
relationship between age and impulse buying which younger people tend to become more
impulsive than elder people (Bellenger, Robertson and Hirschman 1978). There are also
other researches on offline environment indicates the relationship between age, culture,
shoppingenjoyment andself-discrepancy asthe factorswhich affectto the degreeofimpulse
buying of groups of people. Traits mentioned were studied mostly in traditional or offline
shopping context and there are few factors that can be tested on online context.
In the context of impulse buying behavior, there is a previous literature which studies on
impulsiveness and its effect on impulse buying, which can be applied to a different context.
As a personal trait, impulsiveness can both affect to impulse buying online and offline
environment. It has the gain the attention of researchers in both contexts.
For the offline environment, (Rookand Fisher1995) is oneofthe first paperresearchonthis
trait-behavior for impulse purchasing in a retail setting. The study shows that there is a
significant difference in impulsive purchase between groups classified by buying
impulsiveness. In other words, more impulsive customers are more likely to have impulse
buying behavior.

14
Impulsiveness is also studied in the online environment. When studies the importance of e-
commercewebsite, it is critical to take inherent impulsiveness ofan individual to understand
how and why customer react impulsively to various degree of website design quality (Wells,
Parboteeah and Valacich 2011). There is the evidence for the moderating effect of
impulsiveness trait of the customer on the relationship between stimuli which is website
quality, and the response, urge to buy impulsively. When comparing the groups of people by
this behavioral trait, it is interesting that individual with higher impulsiveness level when
experienced with the high-quality website is likely response with a higher level of urge to
buy impulsively. The research shows the importance of studying how the varying degrees of
a stimulus can affect the dependent variable, impulse buying.
Therefore, it is critical to take into account the behavioral trait to engage in the experiment.
Previous researches also open opportunities for future investigation the impulsiveness in
another context, such as social commerce or how impulsive as an independent variable
which can affect to urge to buy behavior besides the moderating and mediating effects.

15
III. Theoretical foundation and Hypothesis Development
3.1 Stimulus:Sales Promotion
The relationship between sales promotion stimuli and Emotional Responses
The relationship between stimulus an emotion in impulse buying behavior hasbeen founded
in previous researches. From previous studies, there is the relationship between marketing
stimuli to emotional responses in an online environment. On mobile commerce, web
atmospheric and mobile characteristics were found to have significant effects on users’
emotions (L. T. Huang 2017). Media format, such as text, picture, and video were posited to
have different effects on emotions and impulse buying behaviors (Adelaar, et al. 2003).
Therefore, in social commerce context, we want to posit that there may be a link between
sales promotion, as marketing stimuli, and emotional responses. Apply to these findings in
the previous study, it can be suggested that customer exposes to a different type of
promotions can have a different emotional organism. Therefore, the following hypothesis is
proposed to reveal the effect of promotion to emotion on social commerce.
H1: There are different effects of promotion stimuli on individuals’ shopping
emotions on social commerce.
H1a: There are the different effect of promotion stimuli on individuals’ pleasure on
social commerce.
H1b: There are the different effect of promotion stimuli on individuals’ arousal on social
commerce.
H1c: There are the different effect of promotion stimuli on individuals’ dominance on
social commerce.
The relationship between sales promotion stimuli and Urge to buy
The relationship between promotion stimuli and urge to buy had been investigated in some
previous researches. When using different sales promotion methods, it was suggested that
marketer should use instant reward promotion rather than delayed reward promotion to
evoke reminder impulse behaviors (Liao, Shen and Chu 2009). Free gifts, as a product –
based promotion, was considered the most effective methods to arouse customer impulse
buying. With different products, utilitarian or hedonic value, marketers should use
monetary-based promotion or nonmonetary based promotions. Moreover, both monetary
andnon-monetarypromotionsarefoundedto havesignification effectson reminderimpulse
buying.
H2: There are different effects of sales promotion stimuli on the urge to buy
impulsively.
When comparing between discount promotion, money-based promotion, and bonus packs,
product-based promotion, it is founded that price discounts resulted in greater impulse
purchasing than bonus packs when the product was hedonic, but when the products are

16
utilitarian, bonuspacksaremoreeffective than discount promotion.Therefore,thefollowing
hypothesis is proposed:
H2a: There are the different effect of sales promotion stimuli on the urge to buy
impulsively
In the context of the online environment, scarcity promotion message is proved to have an
indirect effect on impulse buying through consumers’ desirability in the deals (Gwee and
Chang 2013). In a extend level, frequency scarcity is founded to have the strongest effect on
unplanned behaviors, follows by quantity scarcity and continuing time scarcity. The reason
is that tie pressure of frequency scarcity is higher than of two other methods. Thus, the
following hypothesis is drawn.
H2b: There are different effects of promotion scarcity on the urge to buy
Moreover, in this research, we expect to identify the interaction effect of promotion stimuli
based on scarcity, including continuing time scarcity, frequency time scarcity and quantity
scarcity, and promotion method, including product based and money based on the urge to
buy behavior. This is to find how the combination of different types of promotion can affect
customers buying behaviors. This hypothesis is a combine of the two-previous prediction on
how promotion formats can affect impulse buying.
H2c: There are differences in the urge to buy responses for different combinations of
promotion methods and promotion scarcity.
3.2 Organism:Emotional Responses
There are three types of emotional responses: pleasure, arousal, and dominance (PAD
model), which discussed in literature review. This organism was studied in the context of
offline shopping, e-commerce, and mobile commerce environment but there still no
application of PAD in social commerce, especially in the Instagram shopping environment.
The relationship between states of emotions had been studied in some researches. Pleasure
had been posited to have mediation effect between arousal, dominance and shopping
behaviors (Ding and Lin 2012). There was also a positive relationship between dominance
and pleasure, which customers with higher dominance responses may have higher pleasure
when shopping (Eroglu, Machleit and Davis 2003). In the research of Hsieh, et al. 2014, the
indirect relationship between dominance and buying intention had been founded with the
mediation effect of pleasure. Therefore, we propose the following hypothesis to reveal the
relationship between emotional states in social commerce context.
H3: Individuals’ arousal is positively associated with their pleasure in social
commerce.
H4: Individuals’ dominance is positively associated with their pleasure in social
commerce.

17
3.3 Behavioral response:Urge to buy impulsively
The relationship between emotional responses and the Urge to buy
Generally, how an individual has affective reactions, or emotional organism, to the
environment will determine his or her responses (Mehrabian and Russell 1974). In the
study, the response is the impulse buying.
The significant effect of emotion on impulse buying has been proved in both offline (Shen
and Khalifa 2012) and online context (Adelaar, et al. 2003). Emotional responses can be a
factor predict the impulse buying behavior to buy the CD (Adelaar, et al. 2003).
Specifically, about arousal, it has been proved to have impacts on impulse buying through
mobilization (Rook and Gardner 1993).
The flow of three emotion stages, pleasure, arousal and dominance has been analyzed in
previous researches. In and website shopping experience context, when customer
experiment a pleasure stage when browsing the platform, the more customers are aroused,
the more change they continue exploring the shopping. In contrast, if customers experience
a pleasant experience on the website, the more arousal they are, the more they tend to
discontinue shopping on the website (Donovan, Rossiter and Marcoolyn, et al. 1994).
It can be expected that the more individual feel positive toward the stimuli, the greater
response of impulse purchasing behavior. Therefore, the discussion of emotional responses
and impulse buying, which represented buy urge to buy impulsively leads to the following
hypothesis:
H5: Individuals’ pleasure has a positive effect on the urge to buy impulsively.
Moreover, based on the Mehrabian - Russell Model (Mehrabian and Russell 1974), which
indicates that behaviors are an outcome of the emotional states an individual’s experiences
within the environment. Pleasure had been posited to have mediation effect between
arousal, dominance and shopping behaviors (Ding and Lin 2012). Therefore, we can expect
that pleasure mediates the relationship between arousal and dominance and the urge to buy
impulsively.
H6a: Individuals’ pleasure mediates the relationship between their arousal and
urges to buy impulsively.
H6b: Individuals’ pleasure mediates the relationship between their dominance
and urges to buy impulsively.
3.4 Effect of impulsiveness
Previous researches founded the influence of impulsiveness on consumer behavior. In an
offline environment, people with high level of impulsiveness have been found to be higher in
the urgeto buybehaviors (Beatty and Ferrell1998). Moreover,inan online context, a similar
relationship has been founded that an individual with higher impulsiveness level has

18
experienced a higher level of urge to buy impulsively in comparison to lower impulsiveness
individuals (Wells, Parboteeah and Valacich 2011). Therefore, in this paper, we posit that
there will be a similar relationship between the urge to buy and impulsiveness on social
commerce context:
H7a: Individuals’ impulsiveness has a positive effect on the urge to buy
impulsively.
Impulsiveness was studied not only on the direct effect to urge to buy but also on the
moderating effect. People who are with higher impulsiveness traits are more sensitive and
responsive to environmental stimuli, then they become more likely to respond with higher
level of urge to buy impulsively (Youn and Faber 2000) In addition, Impulsiveness has
moderating effect on the relationship between website quality and urge to buy (Wells,
Parboteeah and Valacich 2011). In the context of a social commerce platform, Facebook Sell-
buy group, there is a significant interaction effect among personal trait impulsiveness,
textual information quality, number of “likes” and consumer urge to buy impulsively.
Therefore, in the context of Instagram shopping platform, we posit that when the individual
response in different states of emotions, the individuals’ urge to buy will be affected by their
level of impulsiveness.
H7b: There will be an interaction effect of individual’s impulsiveness on the
relationship between individuals’ pleasure and individual’s urge to buy
impulsively.
In summary, the model and its hypothesis were described in the following figure.
Figure 1. Research Model

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IV. Research Methodology
In this section, the methodology and experimental procedures of the research will be
discussed, including the research design, participants, experiment procedure, measurement
instrument, and data analysis.
4.1 Research Design
4.1.1 Three design methods
In the context on social research, there are three different research designs, including
exploratory research design, descriptive research design, and causal research design. (Vaus
2001). The descriptive design, which uses mathematical techniques, is used to define an
opinion, attitude or behavior of an individual or a population. The descriptive research uses
a lot of surveys and it is conclusive because of its nature uses of a quantitative approach. The
answer to the survey questions are mostly predetermined choices, which are usable for
statistical data. The exploratory research design aims to explore or discover the ideas and
insights of the research problem. This type of research is suitable at the beginning of a
research plan to define the research problems.
The third research method, casual design, which like descriptive methods, uses a
quantitative approach in nature. However, the difference is that it tries to investigate cause
and effect relationship between variables, including independent variables and dependent
variables.
With respect to this study, it is suitable to use a descriptive research design to define the
research problem in a statistical way using hypotheses testing.
4.1.2 Quantitative or qualitative
It is helpful to distingue between qualitative and quantitative research. The distinction
between quantitative and qualitative is that quantitative employ measurement and
qualitative research do not. (Bryman and Bell 2007) posit that choosing research strategy
have to base on the quantification in the collection and data analysis. The quantitative
method, which usually emphasizes quantification, will be suitable if the research has the
threefollowing satisfactions. First, it hasan emphasisonthe testing oftheories,andit reveals
or tries to confirm the relationship between theory and research. Second, it has combined
the practices of the natural scientific model and the norms of positivism. Third, it has to be
objective when viewing social reality. The qualitative design, which usually emphasizes
words, is in contrast with the quantitative design. In the context of social commerce, this
research tries to test the environmental psychology theory, which analysis the impulsive
buying behavior of individuals when experiencing an environmental stimulus. The research
is also objective, which bases on the experience from the Instagram users’ perspective.
Therefore, a quantitative approach is chosen to be the research method for this paper.
In addition, while the qualitative method is highly reliable with exploratory design,
quantitative method accords with descriptive research design. The quantitative approach,
by using some methods, such as focus group or in-depth interview, gain fundamental

20
information about the research problem. In contrast, quantitative method, through
statistical toolsin sucha manner (Creswell 2013),studies deep andinsightful understanding
of the research problem through. Moreover, beside experiments methods, survey technique
is the most common quantitative track in the area of social studies.
In sum, a quantitative method using the survey method has used the analysis of the research
problem raised in this paper.
4.2 Participants
Participants or population of a research is the set of individuals that are the key interest of
the research (Bryman and Bell 2007). This research focuses on the behaviors of individuals
in social commerce context, which is mainly on Instagram shopping platform. Therefore, the
target population of this study is defined as Instagram users who are from over 18 years old.
Because the limit of times and resources, it is hard for this study to cover all the population.
However, the total sample is 181 individuals and it follows sections.
To select the sample, there are two main methods, probability, and non-probability. The
difference between two methods is that probability sampling means every individual of the
population has the same chance to be chosen in the sample while non-probability has an
unequal probability of being selected into the sample (Susa 2017). Probability method
includes some techniques such as simple random sample, clustering sample, and stratified
samples while non-probability method includes convenience sample, purposive sample, and
snowball sample. For this research, the sample was drawn from the population that close to
hand, orin otherwords, the sample was collected froma groupofpeoplethat easyto contact
such as friends, student network, and personal professional networks. Therefore, the
convenience sample technique was chosen for this paper.
The sample included 181 people aged from 18 to 40 years old. Age groups were as follows:
51.4% ages 18-25, 48.6% ages 25-40. By ethnic groups, 59.7% of the sample is Asian/Pacific
Islander, 37% is White/Caucasian, and the others left is Black/African American. By
education level, most of the respondents are a graduate degree (54.7%), follows by some
graduated studies (20.4%), undergraduate degree (16.6%).
The details of the sample are described in the following table.
Table 2: Sample profile
Frequency Percent Cumulative %
Gender Male 71 39.2 39.2
Female 110 60.8 100
Age Young Adults (18 – 25) 93 51.4 51.4
Adulthood (25 – 40) 88 48.6 100
Ethnic Group Asian/Pacific Islander 108 59.7 59.7

21
White/Caucasian 67 37 96.7
Black/African American 6 3.3 100
Education Level High School 7 3.9 3.9
Some undergraduate studies 8 4.4 8.3
Undergraduate degree 30 16.6 24.9
Some graduate studies 37 20.4 45.3
Graduate degree (e.g., MA,
MBA, PhD)
99 54.7 100
4.3 Experiment Procedure
4.3.1 Questionnaire design
The survey was created on Qualtrics in such as short and concise manner to maximize the
response rate. There were parts of the survey. The first part is anonymous message and
question to filter Instagram users. Part 2 is a self-report survey which participant gave
valuation about their impulsive traits, impulsiveness. Part 3 is the experiment where
respondent explored with the stimulus before reported how they feel and respond to the
stimulus. Part 4 is for collecting demography data of respondents.
More specially, part 2 and part 3 are the two main parts of the survey which contain
measurement for the studied factors of this research. All the items in these two parts are
designed with the continuous scale of 7-point Likert which are 1 - Strongly disagree, 2 –
Disagree, 3 - Somewhat disagree, 4 - Neither agree or disagree, 5 - Somewhat agree, 6 -
Agree, 7 - Strongly agree.
4.3.2 Pilot study
Before implementing the formal study, it is important to employ a pilot study to improve the
wording, translating between languages (English and Vietnamese), and any confusing
question in the survey. Specifically, the testing version of the survey was sent to 5 people
who have an Instagram account to experience and gather the feedback and response. After
carefully considering their feedbacks, some of the questions were change in expression to
make them more clear and easier to understand. Moreover, the Vietnamese version was
fixed in translation and expression, especially in emotion testing section. The time spending
for completing a full survey was calculated for about 3 to 4 minutes. The time for the
experimental part, which saw the post, was decreased from 30 seconds to 15 seconds to
avoid the long waiting of respondents. Participants in the pilot test were excluded from the
official survey.
4.3.3 Collection procedure
The data collection was from December 22nd to November 5th. The survey was created in
Qualtrics platform and sent to three main channels. The English version was sent to the
English speaker personal network. The Vietnamese version was distributed to Vietnamese

22
youth who use Instagram. There was also a version for Ieseg school student network. There
were 246 respondents collected. After removing invalid response, there was 209 valid
response, including 181 individuals use Instagram and 28 individuals do not. The response
rate was 73 percent.
4.3.4 Stimulus material
In order to create an appropriate stimulus for sales promotion on Instagram context, the
choice of product, promotion message and design for the post considered.
About the promotion product, it should be a familiar type of product which people might
want to shop online, and it should have no difference of needs between man and woman.
According to a report of PwC, in the path of purchase, 52% of global shopper preferto search
purchase online for clothing and footwear. These product categories are just behind books,
music, movies and video games categories. Footwear was chosen to be the product
categories for this research. After searching for top footwear sold on Instagram, a pair of
Adidas Ultra Boost, priced at 200 euros, was chosen to be the promotional product for the
experimental study.
About the sales promotion scheme, the challenge is to find the right promotion that can have
enough effect to change individual behaviors. Previous research posited that only when
combined what high price discount promotion, can quantity scarcity promotion and time
scarcity promotion have significant effects on customers’ buying behaviors. Moreover, the
promotion discount was at or over 34% considered suitable for having influences on
behaviors (Xishu, Nian and Li 2013). In another literature which studied the promotion in
the online context in a period of 15 days, the average discount was found out to be at 57.54%
(Aydinli, Bertini and Lambrecht 2014). Therefore, we chose a reasonable percentage of 40
percent for the money-based promotion of the stimulus. The value of the promotion was 80
euros based on the price of the promotional product. To have the same effect as discount
promotion,the product-basedpromotionhadto beat the same value. A wireless headphone
was chosen based on the promotion value of 80 euros.
The next step is to create the scarcity effect for the promotions, including product quantity
scarcity (QS), frequency scarcity (FS) and time scarcity (TS). The challenge is to make the
equal relative effectiveness of three these simulations. They should be similar in potency. In
previous research of Xishu, Nian, & Li, 2013, three potency promotion scarcities were used,
and they found to have significant differential effects on the unplanned purchase. The
scarcity expressions are “only 100 products left” for QS, “lasts for only one day” for TS and
“happens only once a year”. Therefore, the experiment for scarcity used three types of this
expression. Moreover, the promotion message was modified to be suitable with the
Instagram post.
Combining two promotion methods, money-based promotion, and product-based
promotion, three promotion scarcity, time, quantity and frequency, we created six distinct
experiments, presented on six different Instagram posts. The experimental conditions were
described in Table 3.

23
Table 3: Experimental conditions
Experimental Condition Stimuli Format
G1: Money – Based + Quantity Scarcity Get a discount of up to 40%. There are only 100
products left.
Buy now!
G2: Money – based + Time Scarcity Get adiscount ofup to 40%. The promotionlasts
for only one day.
Buy now!
G3: Money – based + Frequency Scarcity Get a discount of up to 40%. The promotion
happens only once a year.
Buy now!
G4: Product – based + Quantity Scarcity Get a free sport wireless headphone worth $80.
There are only 100 products left.
Buy now!
G5: Product – based + Time Scarcity Get a free sport wireless headphone worth $80.
The promotion lasts for only one day.
Buy now!
G6: Product– based+ FrequencyScarcity Get a free sport wireless headphone worth $80.
The promotion happens only once a year.
Buy now!
Other factors of the simulation, such as images, call to action message, a number of like were
kept the same to avoid bias in individuals’ responses. Six distinct posts were designed and
created for the stimulus materials in the experiment (see Appendix A). The layout, text
position and colors were controlled in the designing to reduce as much as possible the
potential factors that might have effects on the individuals’ behavioral responses. All of the
stimuli were shown at the same 15’ seconds before the “next” button appears on the screen.
4.3.5 Procedures
Firstly, after the anonymous messages, the participants were asked whether he or she has
Instagram or not. Respondents who have no Instagram account were eliminated from the
experiment. The Instagram-used respondents were moved to the next section where they
answered several self-reported questions about their personal impulsiveness trait. After
that, theonline surveysystem randomly assignedrespondentsinto sixconditions (see Table
3: Experimental conditions). After the participant had been exposed to one stimulus, they
have answered the survey about emotion and urge to buy impulsively (see Appendix B). The
last part collected the demographic information of respondents, including age, professional,
academic background, relatives and friends, follower and following on social commerce
platform.

24
4.4 Measurement Instrument
4.4.1 Emotion Measurement
Emotional responses contain three factors, including pleasure, arousal, and dominance.
These factors were measured by using 13-items scale (Mehrabian and Russell 1974). The
semantic 7 Linkert scales were used to determine the emotional responses of each stimulus.
List of emotional responses is as follow.
Table 4. Emotion Measurement
We implemented factor analysis to reduce the reduce data in underlying dimension and
different items into factors.
Table 5. Emotions - KMO and Bartlett's Test
Kaiser-Meyer-Olkin Measure of Sampling Adequacy. .865
Bartlett's Test of
Sphericity
Approx. Chi-Square 988.793
df 78
Sig. .000
The KMO (= 0.86 >0.5) and Bartlett’s (=.000 <0.05) tests suggest that the variables included
in the factor analysis have high correlations. With a sufficient degree of correlation, the
factor analysis is meaningful.
Table 6. Emotions – Communalities
Initial Extraction
PL1 1.000 0.675
PL2 1.000 0.46
Factor Code Item
Pleasure PL1 Unhappy - Happy
PL2 Melancholic - Contented
PL3 Despairing - Hopeful
PL4 Annoyed - Pleased
PL5 Unsatisfied - Satisfied
PL6 Bored - Relaxed
Arousal AR1 Relaxed - Stimulated
AR2 Calm - Excited
AR3 Sluggish - Frenzied
AR4 Dull - Jittery
Dominance DO1 Cared-for - In Control
DO2 Controlled - Controlling
DO3 Influenced - Influential

25
PL3 1.000 0.591
PL4 1.000 0.606
PL5 1.000 0.639
PL6 1.000 0.663
AR1 1.000 0.725
AR2 1.000 0.725
AR3 1.000 0.564
AR4 1.000 0.625
DO1 1.000 0.388
DO2 1.000 0.752
DO3 1.000 0.584
Extraction Method: Principal Component
DO1 had the extraction score under 0.45, it was a sign to remove this item from factor.
Table 7. Emotions - Total Variance Explained
Component
Initial Eigenvalues Extraction Sums of Squared Loadings
Total % of Variance Cumulative % Total % of Variance Cumulative %
1 5.406 41.587 41.587 5.406 41.587 41.587
2 1.466 11.275 52.862 1.466 11.275 52.862
3 1.125 8.655 61.518 1.125 8.655 61.518
4 .964 7.412 68.929
The cumulative score was at 61.51% for three components. Therefore, it was confirmed to
have three factors for emotions responses. We continued to implement Cronbach’s Alpha to
test the reliability of these items.
For Pleasure and Arousal, it was confirmed to retain 2 factors (α=.868 and .774). Dominance
factor has the α <.6 which is a poor value for reliability. Item DO1 was suggested to be
removed from the factor to increase reliability, the score increased from .598 to .654
Table 8. Dominance - Reliability Statistics
Cronbach's Alpha N of Items
.598 3
Scale Mean if
Item Deleted
Scale Variance if
Item Deleted
Corrected Item-
Total Correlation
Cronbach's Alpha
if Item Deleted
Dominance1 8.83 6.087 .291 .654
Dominance2 8.82 4.591 .555 .264
Dominance3 9.13 5.238 .391 .522

26
To confirm the removal, we implemented a Pearson test to find the correlation between
DO2 and DO3. The result showed that two items were moderately correlated (r=.487,
p<0.01). Therefore, item DO1 was removed from the factor Dominance.
Table 9. Dominance - Correlations
Dominance2 Dominance3
Dominance2 Pearson Correlation 1 .487**
Sig. (2-tailed) .000
N 181 181
Dominance3 Pearson Correlation .487** 1
Sig. (2-tailed) .000
N 181 181
**. Correlation is significant at the 0.01 level (2-tailed).
4.4.2 Urge to Buy Impulsively Measurement
Urge to buyimpulsively (UBI) was measuredusing three questions (Parboteeah,et al. 2009).
Table 10. Urge to Buy Impulsively Measurement
Factor Code Item
Urge to buy
impulsively
UR1 As I saw this post, I had the urge to purchase items
other than or in addition to my specific shopping goal.
UR2 Seeing these posts, I had a desire to buy items that did
not pertain to my specific shopping goal.
UR3 While seeing the posts, I had the inclination to purchase
items outside my specific shopping goal.
A factor analysis and Alpha Cronbach’s analysis were conducted to access the validity and
reliability of the structure of the factor.
Table 11.UBI - KMO and Bartlett's Test
Bartlett's Test of Sphericity Approx. Chi-Square 338.870
df 3
Sig. .000
Table 12. UBI - Total Variance Explained
Component
Total % of VarianceCumulative %Total % of VarianceCumulative %
1 2.489 82.967 82.967 2.489 82.967 82.967
2 .328 10.945 93.912
3 .183 6.088 100.000
Extraction Method: Principal Component Analysis.

27
in the factoranalysis havehigh correlations.With asufficient degreeofcorrelation,thefactor
analysis is meaningful. The extraction is at 82% for one component. Therefore, it has a sign
that these items are good to combine into one factor.
The reliability of three items was tested using Cronbach’s Alpha test.
Table 13. UBI - Reliability Statistics
Cronbach's Alpha if Item Deleted
UR1 .897
UR2 .815
UR3 .842
The reliability scored at .897 which indicated that three items measure the same general
construct produce similar scores. Therefore, we retained one factor: urge to buy impulsively.
4.4.3 Impulsiveness Measurement
The impulsive trait ofthe individual was measuredusingfouritems that adapted from Wells,
Parboteeah and Valacich 2011.
Table 14. Impulsiveness Measurement
Coding Items
IM1 “Just do it” describes the way I buy things.
IM2 I often buy things without thinking.
IM3 “I see it, I buy it” describes me.
IM4 “Buy now, think about it later” describes me
Exploratory factor analysis was conducted to test the validity and reliability of four items.
Table 15. Impulsiveness - KMO and Bartlett's Test
Bartlett's Test of Sphericity Approx. Chi-Square 248.786
df 6
Sig. .000
.897 3

28
Table 16. Impulsiveness - Total Variance Explained
in the factoranalysis havehigh correlations.With asufficient degreeofcorrelation,thefactor
analysis is meaningful. % of the explained variance: Cumulative percentage of the first
component is 65.6%, which is good enough to group to one factor.
Table 17. Impulsiveness - Reliability Statistics
Reliability Statistics
.825 4
Good Alpha level is .825, which is very good. No items should be removed. Therefore, we
retained one factor: impulsiveness.
V. Data analysis and Results
5.1 Two-ways ANOVA analysis
5.1.1 Sales Promotion Stimuli - Emotions
To test the difference between the effect of sales promotion stimuli to emotions, we
implemented three separated two-way, between subjects ANOVA tests. The results for H1
are discussed as follow.
H1a: There are the different effect of promotion stimuli on individuals’ pleasure on
social commerce.
The result of the ANOVA test and main effect means are shown in Table 17 and Table 18.
There was no direction effect of Promotion Scarcity on individuals’ pleasure (α=0.05
F(2,175) = .855, p=.427). Similarly, Promotion Methods had no statistically significant
effects onindividuals’ pleasure(α=0.05 F(1,175) = .014, p=.906). Finally, as we can seefrom
two-way ANOVA result, there was also no interaction effect of Promotion Scarcity *
Promotion Methods on Pleasure (α=0.05 F(2,175) = 1.549, p=.215)., which means, when
Component
Total % of Variance
Cumulative
%
Total
% of
Variance
Cumulative
%
1 2.625 65.624 65.624 2.625 65.624 65.624
2 0.532 13.297 78.921
3 0.452 11.299 90.22
4 0.391 9.78 100
Extraction Method: Principal Component Analysis.
Item-Total Statistics
Cronbach's Alpha if Item Deleted
Impulsive1 .801
Impulsive2 .772
Impulsive3 .763
Impulsive4 .779

29
compared to types of promotion schemes, there would be no difference in customer’s
pleasure responses.
Table 18. ANOVA Result (Promotions - Pleasure)
Dependent Variable: Pleasure
Source
Sum of
Squares
df
Mean
Square
F Sig.
Promotion Scarcity 1.83 2 0.915 0.855 .427
Promotion Methods 0.015 1 0.015 0.014 .906
Promotion Scarcity *
Promotion Methods
3.316 2 1.658 1.549 .215
Error 187.349 175 1.071
Total 3655.111 181
Corrected Total 192.481 180
a. R Squared = .027 (Adjusted R Squared = -.001)
Table 19. Main Effect Means (Promotions - Pleasure)
Factors Low High Difference
Promotion Scarcity
Quantity Scarcity 3.972 4.500 0.53
Time Scarcity 4.150 4.678 0.53
Frequency Scarcity 4.211 4.734 0.52
Promotion Methods
Money – Based 4.15 4.58 0.43
Product – based 4.17 4.60 0.43
Dependent Variable: Pleasure
Thus, H1a was not supported.
H1b: There are the different effect of promotion stimuli on individuals’ arousal on social
commerce.
Similar to the previous test, the 2x3 ANOVA was implemented. According to Table 19, there
was no direction effect of Promotion Scarcity on individuals’ arousal (α=0.05 F(2,175) = .36,
p=.699). Similarly, Promotion Methods had no statistically significant effects on individuals’
arousal (α=0.05 F(1,175) = .053, p=.817).
Table 20. ANOVA Result (Promotions - Arousal)
Dependent Variable: Arousal
Source
Sum of
Squares
df
Mean
Square
F Sig.

30
Promotion Methods
3.878 2 1.939 1.749 .177
Error 194.07 175 1.109
Total 3189.6 181
a. R Squared = .024 (Adjusted R Squared = -.004)
Finally, as we find from two-way ANOVA result, there was also no interaction effect of
Promotion Scarcity * Promotion Methods on arousal (α=0.05 F(2,175) = 1.749, p=.177).,
which means, when compared to types of promotion schemes, there would be no difference
in customer’s arousal responses.
Table 21. Main Effect Means (Promotions - Arousal)
Promotion Scarcity
Promotion Methods
Money-Based 3.87 4.30 0.44
Dependent Variable: Arousal
Thus, H1b was not supported.
H1c: There are the different effect of promotion stimuli on individuals’ dominance on
social commerce.
As we can see from Table 22, there was no significant difference between the effects of
Promotion Scarcity on individuals’ dominance (α=0.05 F(2,175) = 1.537, p=.217).
However, promotion had a statistically significant effect on dominance (α=0.05 F(1,175) =
4.077, p=.045).
The interaction effect of Promotion Scarcity * Promotion Methods was founded not
statistically significant (α=0.05 F(2,175) = 2.764, p=.066). Thus, H1c was not supported.
Table 22. ANOVA Result (Promotions - Dominance)
Dependent Variable: Dominance
Source
Sum of
Squares
df
Mean
Square
F Sig.
Promotion Methods
8.071 2 4.035 2.764 .066
Error 255.513 175 1.460

31
Total 3,801.000 181
a. R Squared = .067 (Adjusted R Squared = .041)
Table 23. Main Effect Means (Promotions - Dominance)
Promotion Scarcity
Promotion Methods
Money-Based 4.35 4.85 0.50
Dependent Variable: Dominance
As the ANOVA test shown the main effect of promotion methods on dominance, we lookedcloser
to the two groups of promotion methods, money based showed to have a high score mean of
Dominance. That means when customers exposed with Money – Based promotion, they tend
to have higher Dominance feeling or feel more in control. Thus, individuals exposed to
money-based promotion (mean = 4.59 and n = 91) were likely to feel more emotions of
dominance than individuals exposed to product-based promotion (mean = 4.23 and n = 90)
Table 24. Group Statistics of Promotion Methods
Promotion
Methods
N Mean
Std.
Deviation
Std. Error
Mean
Dominance
Money – Based 91 4.5934 1.1783 0.1235
Product – based 90 4.2333 1.26802 0.1337
F Sig. t df
Sig. (2-
tailed)
Mean
Difference
Std. Error
Difference
Dominance
Equal variances
assumed
0.122 .727 1.979 179 .049 0.360 0.1819
Equal variances
not assumed
1.978 177.74 .049 0.360 0.182
Overall, Hypothesis 1 was not supported that there are no different effects of promotion
stimuli on individuals’ shopping emotions on social commerce.

32
5.1.2 Sales Promotion Stimuli - UBI
To find out how promotion stimuli affect the urge to buy impulsively, we continued using
two-way 2x3 ANOVA tests, including two level of promotion methods and three levels of
promotion scarcity.
The main effects of Promotion Methods and Promotion Scarcity are not statistically
significant with p = .739 and p = .073, respectively.
There was a statistically significant interaction between Promotion scarcity and Promotion
Methods (p=0.010). We implemented A two-way ANOVA to examine the effect of promotion
scarcity and promotion methods on the urge to buy impulsively. There was a statistically
significant interaction between Promotion scarcity and Promotion Methods on the urge to
buy F (2, 175) = 4.730, p = .010 with R2=.078. It meant that when combining two types of
promotion, there was a signification of stimuli on individuals’ urge to buy impulsively.
Therefore, hypothesis 2 is supported.
Table 25. ANOVA Result (Promotions - Urge to buy impulsively)
Dependent Variable: Urge to buy impulsively
Source
Sum of
Squares
df
Mean
Square
F Sig.
Promotion Methods
22.394 2 11.197 4.730 .010
Error 414.246 175 2.367
Total 2,841.556 181
a. R Squared = .078 (Adjusted R Squared = .052)
We tried to examine how mains effects affect differently to urge to buy impulsively. Time
Scarcity seems to be more effective with money-based promotion (mean = 4.322) than with
product – based promotion (mean=3.344). In contrast, with quantity scarcity promotion,
individual response with higher urge to buy impulsively when exposing to product-based
promotion (mean=3.633) than money-base promotion (mean=2.889). The individual had a
similar response with frequency scarcity promotion (see Table 26).
While these results were interesting, we founded that the effect of promotion methods on
the urge to buy impulsively is more pronounced with time scarcity promotion (4.322-
3.344=0.978) than with quantity scarcity (2.889-3.633=-0.744) and frequency scarcity
(3.806-3.811=-0.005).
Table 26. Interaction Effect Means (Promotions - Urge to buy impulsively)
Promotion
Scarcity
Promotion
Methods Mean Low High Difference
Quantity Scarcity Money-Based 2.889 2.335 3.443 1.109

33
Product – Based 3.633 3.079 4.188 1.109
Time Scarcity
Money-Based 4.322 3.768 4.877 1.109
Product – based 3.344 2.790 3.899 1.109
Frequency
Scarcity
Money-Based 3.806 3.261 4.352 1.091
Product – based 3.811 3.257 4.365 1.109
Dependent Variable: Urge to buy impulsively
5.2 Regressionanalysis
We implement multiple regression analysis to identify the effect of emotional responses and
personal impulsiveness on the urge to buy impulsively. All the regression assumptions had
been checked, including linear relationship, multivariate normality, no or little
multicollinearity, no auto-correlation and homoscedasticity.
5.2.1 Arousal – Pleasure
Table 27. Regression Analysis (Arousal - Pleasure)
Model Summary ANOVA
R
R
Square
Adjusted
R Square
Sum of
Squares
df
Mean
Square
F Sig.
.674a .454 .451 Regression 65.580 1 65.580 142.340 .000b
a. Predictors: (Constant), Arousal Residual 78.785 171 0.461
b. Dependent Variable: Pleasure Total 144.365 172
Coefficients
Source B Std. Error Beta t Sig.
(Constant) 2.010 0.206 9.769 .000
Arousal 0.582 0.049 0.674 11.931 .000
A simple regression was calculated to predict individuals’ pleasure emotions based on their
arousal. From Table 26, Adjusted R Square = .451, which increased from .31 after we
removed outlier. With R2 >.25, there is enough variance in the dependent variables can be
explained by the independent variables in the regression model. In other words, Arousal
explains 45.1% of the variability of pleasure.
The ANOVA shows that overall, individuals’ Arousal statistically significantly predict their
pleasure behavior, (F(1,171) = 142.340, p<0.001) with R2 of .454. Therefore, the model to
predict pleasure was a good fit of the data. Arousal had a positive significant effect pleasure
(p<.001) which Pleasure increases .582 for each unit of Arousal. The regression equation is
described as follows.
Pleasure = 2.010 + 0.582*Arousal + ε

34
Thus, Hypothesis 3 was supported that individuals’ arousal has positive effect pleasure or
the more people feel arousal, the more they feel pleasure.
5.2.2 Dominance – Pleasure
Similar to the previous test, a simple regression was calculated to predict individuals’
pleasure emotions based on their dominance.
Table 28. Regression Analysis (Dominance- Pleasure)
Model Summary ANOVA
R R Square
Adjusted R
Square
Sum of
Squares
df
Mean
Square
F Sig.
502a
.252 .248 Regression 25.987 1 25.987 54.314 .000b
a. Predictors: (Constant), Dominance Residual 77.032 161 .478
b. Dependent Variable: Pleasure Total 103.019 162
Coefficients
B Std. Error Beta t Sig.
(Constant) 2.896 .214 13.544 .000
Dominance 0.344 .051 .502 7.370 .000
From Table 27, Adjusted R Square = .248, which increased from .115 after we removed
outlier. In other words, dominance explains nearly 25% of the variability of pleasure.
The ANOVA shows that individuals’ Dominance statistically significantly predict their
pleasure behavior, (F(1,171) = 52.857, p<0.001) with R2 of .252. Therefore, the model to
predict pleasure was a good fit of the data. Dominance had a positive significant effect
pleasure (p<.001). The regression equation is described as follows.
Pleasure = 2.896 + 0.344*Dominance + ε
Thus, Hypothesis 4 was supported that individuals’ arousal has positive effect pleasure or
the more people feel arousal, the more they feel pleasure.
5.2.3 Pleasure – UBI
A simple regression was calculated to predict individuals’ pleasure emotions based on their
arousal. From Table 28, with R2 >.25, there is enough variance in the dependent variables
can be explained by the independent variables in the regression model. In other words,
Pleasure explains 37.9% of the variability of pleasure.
The ANOVA shows that individuals’ Arousal statistically significantly associates with their
urge to buy impulsively, (F(1,174) = 107.821, p<0.001) with R2 of .383 (see Table 29).
Therefore, the model to predict pleasure was a good fit of the data. Hypothesis 5 was
supported that individuals’ pleasure has a positive effect on the urge to buy impulsively. It
indicates that pleasure is critical to inducing individual impulse purchasing on social
commerce. The regression equation is described as follows.
UBI = -0.407 + 0.926*Pleasure + ε

35
Table 29. Regression Analysis (Pleasure-UBI)
Model Summary ANOVA
R
R
Square
Adjusted R
Square
Sum of
Squares
df
Mean
Square
F Sig.
.619a
.383 .379 Regression 158.074 1 158.073 107.821 .000b
a. Predictors: (Constant), Pleasure Residual 255.098 174 1.466
b. Dependent Variable: UBI Total 413.171 175
Coefficients
Source B Std. Error Beta t Sig.
(Constant) -0.407 .401 -1.015 .311
Pleasure 0.926 .089 .619 10.384 .000
5.2.4 Mediating Effect of Pleasure
The requirements for mediation test were satisfied. According to H4 and H5, Dominance has
significant effectonmediator Pleasure (F(1,171)= 52.857,p<0.001) with R2 of.252, Pleasure
positively associates with UBI (F(1,174) = 107.821, p<0.001) with R2 of .383. We continued
to implement a simple regression analysis with Dominance predicting UBI and a multiple
regression analysis with Dominance and Pleasure predicting UBI. Path “a” indicates that
Dominance has a significant association with UBI. However, in path “d”, the effect of
Dominanceon UBI is no longersign (p=.238) and theeffect of Pleasure on UBI still significant
(p<.001). It is a sign that there is a full mediation effect of moderator Pleasure on the
relationship between Dominance and UBI. Thus, the Hypothesis H6a is supported.
Table 30. Mediation analysis (Dominance - Pleasure - UBI)
Path IV DV B
Std.
Error
Beta t Sig.
a Dominance UBI 0.361 0.092 0.283 3.901 .000
b Dominance Pleasure 0.344 0.051 0.502 7.37 .000
c Pleasure UBI 0.926 0.089 0.619 10.384 .000
d
Dominance
UBI
0.101 0.086 0.079 1.184 .238
Pleasure 0.799 0.100 0.539 8.028 .000
For Arousal – UBI relationship, we processed the same paths. The results are shown in the
following table. Because all the paths show the significant effect of IV and mediator on UBI,
there is no full mediation effect of Pleasure. The hypothesis H6b is not supported.

36
Table 31. Mediation analysis (Arousal - Pleasure - UBI)
Path IV DV B
Std.
Error
Beta t Sig.
a Arousal UBI 0.829 0.092 0.564 9.038 .000
b Arousal Pleasure 0.582 0.049 0.674 11.931 .000
c Pleasure UBI 0.926 0.089 0.619 10.384 .000
d
Arousal
UBI
0.540 0.106 0.364 5.076 .000
Pleasure 0.519 0.105 0.353 4.930 .000
5.2.5 Impulsiveness – UBI
Adjusted R Square = .254 indicated that our independent variables explained 25.4% of the
variability of the urge to buy impulsively.
Table 32. Table 28. Regression Analysis (Impulsiveness-UBI)
Model Summary ANOVA
R
R
Square
Adjusted
R Square
Sum of
Squares
df
Mean
Square
F Sig.
.504a .254 .250 Regression 109.336 1 109.336 60.223 .000b
a. Predictors: (Constant),
Impulsiveness
Residual 321.348 177 1.816
b. Dependent Variable: UBI Total 430.684 178
Coefficients
Source B Std. Error Beta T Sig.
(Constant) 1.951 0.254 7.672 .000
Impulsiveness 0.541 0.074 0.484 7.789 .000
The ANOVA shows that Impulsiveness statistically significantly affects the urge to buy
behavior, F(1,177) = 60.223, p<.001) with R2=25.4 %. Therefore, the hypothesis H7a is
supported that impulsiveness had a positive effect on the urge to buy behavior or the more
impulsive people are, the more they likely become an urge to buy impulsively.
The regression equation is described as follows.
UBI = 1.951 + 0.541*Impulsiveness + ε
We hypothesized that impulsive trait of the individual would moderate the relationship
between emotional responses and urge to buy impulsively. Although pleasure had
statistically significant effects on the Urge to buy in step 1 and 2, there were no interaction
effects of emotional responses and Impulsiveness in step 3 (see Table 33). Therefore, the
hypothesis, H7b was not supported that there was no interaction effect of individual’s

37
impulsiveness on the relationship between states of emotion and individual’s urge to buy
impulsively.
Table 33. Moderated Regression Analysis Results
Step 1 Step 2 Step 3
Variables B t p B t p B t p
Pleasure .926 10.384 .000 .808 5.515 .000 .898 5.447 .000
Impulsiveness .338 4.236 .000 .313 3.798 .000
Pleasure x
Impulsiveness
-.232 -1.183 .242
R squared .383 .580 0.590
Adjust R square .379 .567 0.570
F 107.821 42.203 28.785
Dependent Variable: Urge to Buy Impulsively
5.2.6 Results Summary
The results of our data analysis are summed up as follow.
Figure 2. Results summary

38
VI. Discussion and Implication
This chapter provides the conclusions of this master’s thesis paper. Firstly, the contribution of this
research is discussed under a theoretical point of view to highlight the academic value of this paper.
Secondly, managerial implications are given in accordance with the empirical findings in chapter
4 above to exhibit the practical value of this research in the context of Vietnam. In addition, the
end of chapter 5 objectively addresses the limitations existing in this empirical paper and the
suggestions for future studies.
6.1 Findings and discussion
First, the main effects of sales promotion stimuli on UBI are not different but the interaction
of sales promotion stimuli, including promotion methods and promotion scarcity, are
different. The individual has a difference of UBI responses when exposes with six different
promotion experiments. It was interesting that promotion methods, money based, or
product-based promotion, are more pronounced with time scarcity promotion in
comparison with two other scarcity promotions. And the interaction effects of time scarcity
and money based promotion has the highest effect to simulate the urge to buy impulsively.
However,the low level ofRsquaredindicates that only 7.8% ofthechange in UBI is explained
by sales promotions stimuli. Therefore, there should be other factors or stimuli that also
predicts UBI on social commerce context.
Second, the effect of sales promotion stimuli on individuals’ emotion has not been founded
in generally. This can be explained by the experimental design which promotion messages
are described by text in the context of the Instagram environment which mostly based on
images. Therefore, the effect of stimuli might not strong enough to impact on individual
emotion differently. In specifically, people who expose with money-based promotion tend to
feel more dominance.
Third, the result confirms the roles of emotional responses to impulse buying behaviors,
which represent by the urge to buy impulsively. It also confirms the relationship between
states of emotions when an individual exposed to environmental stimuli. Arousal and
Dominance are founded to have a positive association with pleasure. Customer feel more
joyful, satisfied or happier when they feel simulated and in control. While dominance has the
indirect effect to urge to buy impulsively through pleasure, Arousal affects directly to UBI
and Pleasure. It is interesting that Arousal has an important role in an emotional state when
it hasa high explainedvarianceof pleasure(45.4%) in comparisonwith Dominance (25.2%).
Lastly, personal trait, impulsiveness is founded to have a significant effect on UBI. However,
the moderating effect of impulsiveness on the relationship between emotion and UBI is not
supported.
6.2 Academic implication
Firstly, we explore the relationship between sales promotion, shopping emotion and urge to
buy base on SOR (stimuli – organism-response) framework, which is very popular with
researchesaboutimpulse buying. Moreover,weapply PAD (pleasure – arousal–dominance)
model in our research in social commerce context. Previous researches used this model in
with some factors such as website design, or media format on e-commerce but no one used

39
it in social commerce. Thus, this research confirms the valid of PAD and SOR in social
commerce.
Second, we emphasize the importance of sales promotion in the research area of impulse
buying behaviors on social commerce. This is the first paper investigated the roles of sales
promotion stimuli, as a marketing stimulus, on Instagram shopping platform. The results
show that promotion stimuli can affect significantly to urge to buy. Moreover, pleasure has a
direct effect on UBI, arousal can have the direct and indirect effect to UBI through pleasure,
and dominance has an indirect effect on UBI through pleasure.
Lastly, sales promotion is not a new factor in marketing research and impulse buying
behavior. However, two group of promotion stimuli, we introduce the new way to formulate
sales promotion stimuli in experimental design. One factor is promotion methods, including
money-based promotion and product-based promotion. One is promotion scarcity, include
time, quantity and frequency scarcity.
6.3 Practical implication
Beside purchasing intention, impulsive purchasing should be considered as an important
factor that leads to actual purchasing. Sales promotion could be a factor that effects urge to
buy impulsively. Therefore, the seller should use promotion effectively to increase customer
experience when shopping on social commerce platform.
Second, the research proved a practical method of using different promotions stimuli to
affect customers’ urge to buy impulsively on social commerce, especially on Instagram
shopping platform. Sellers should flexible use combination of promotion methods such as
discount or free gift. The message will become more attractive to the customer when it
appears with the limitation of time or quantity. For a product like footwear, this research
suggests that to us money-based promotion with a limit of time to simulate customers urge
to buy behavior.
Third, for marketing implication on social commerce, companies should consider the
customers’ emotion states when they exposed to environmental stimuli. To have suitable
stimuli that improve customers’ arousal and pleasure are essential to increase their
intention to have to have the urge to buy. Making customers feel control over the situation is
also important to make them feel happy about social commerce. When it comes to emotional
response, the marketer should use different methods to simulate customers’ feeling of
arousal and pleasure which directly associate with impulse buying. What can make a
customer feels more excited, stimulated or happier is must answered question.
6.4 Limitationand future research
First, the design of the experiment is not fully cover all the stimuli of an Instagram post on
the platform while the difference between stimuli is the content, which described by text. To
have a full understanding of how promotion can affect UBI and emotion, it is essential for
future research to take into account image, video, or sounds as the ways to express
promotion message.
Second, the value perception of each promotion stimulus should be investigated more in
futureresearchto have asignificant impact onemotions. Each stimulus shouldhavethesame

40
value perception in experimental designs. A pre-test to examine the difference in value
perception of each stimulus should be executed in future research. In addition, with on
promotion methods or promotion scarcity, there would more promotion scheme can be
founded to study. For example, coupon reward or “Buy two get one free” can replace direct
discount as a money-based promotion. Therefore, diversity in promotion scheme should be
included in future research.
Third, this paper used an experimental design and quantitative survey technique to
investigate the research problem, however, the qualitative technique should have been
included. This is because the qualitative can help us understand more about personal
feelings, which is a part of this research model. Future analysis thinks about employing the
qualitative technique, such as in-depth interviewing, as a preliminary study to get a lot of
perceptive evidence before formally planning the survey form.
Finally, this analysis focused on Instagram shopping platform as a social commerce context
which is still new to customers. Therefore, it's important that future studies should
implement experiments on another social commerce platform such as Facebook, Twitter,
Snapchat or Weibo.

41
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