Journal The Winners, 25(1) 2024, 13-23

IT Affordances, Flow, and Perceived Scarcity:

A Study on Impulsive Buying Behavior and Post-Purchase
Dissonance in Live Shopping
Evi Rinawati Simanjuntak1*; Rendy Setya Pratama2
1-2
Management Department, BINUS Business School Master Program Bina Nusantara University
Jakarta, Indonesia 10270
1
esimanjuntak@binus.edu; 2rendy.pratama002@binus.ac.id

Received: 19th April 2024/ Revised: 27th June 2024

Accepted: 28th June 2024/ Published Online: 3rd July 2024

Abstract - Live shopping has evolved with caution only when necessary to accelerate the
significantly as extensive publications have explored call to action.
this phenomenon from the perspective of streamers
and consumers. However, there is limited analysis Keywords: IT affordances, flow, perceived scarcity,
from the human-computer interaction perspective, impulsive buying behavior, post-purchase dissonance,
particularly concerning IT affordances. Therefore, live shopping
the research aimed to enhance the understanding
of human-computer interaction in live streaming
sessions, exploring flow experiences and the influence I. INTRODUCTION
on impulsive buying behavior, which led to post-
purchase dissonance. The moderating role of perceived Live streaming is a popular form of user-
scarcity was also examined. The research adopted generated content (Hu et al., 2017), where streamers
convenience sampling and obtained 250 online survey upload real-time video content on various topics such
responses. The data were analyzed using Partial Least as games, talent shows, and daily life. Among these,
Squares - Structural Equation Modeling (PLS-SEM) live streaming or shopping has evolved as a significant
to test the hypotheses. The results show that three IT innovation in the e-commerce industry (Chen et al.,
affordance components, visibility, metavoicing, and 2023). It occurs during live video streaming sessions
interactivity, foster flow experiences, but guidance on e-commerce platforms and rapidly gains popularity.
shopping does not. Furthermore, flow experiences are According to a Statista report, the Gross Merchandise
found to stimulate impulsive buying behavior, which Value (GMV) of the Indonesian e-commerce market
subsequently leads to post-purchase dissonance. reached over $62 billion in 2023, with approximately
The results further show a negative impact of $5 billion attributed to live shopping (Wolf, 2023).
perceived scarcity on buying behavior, while the With nearly 234 million active Internet users, the
effect of scarcity is anticipated to enhance buying Indonesian e-commerce market is expected to grow to
motivation. These results contribute to understanding around $120 billion by 2025 and $200 billion by 2028
the significant drivers of flow experiences in live (Uzunoglu, 2024). Due to the substantial commercial
shopping and the implications of perceived scarcity. potential, conducting an in-depth study into live
Enhancing interactive communication between shopping is highly valuable.
streamers and viewers is essential for businesses while Online shopping can be challenging due to the
promoting attractive visibility and comprehensive need for physical interaction with products. Consumers
product information during live shopping sessions. also experience a Zero Moment of Truth (ZMoT) when
Additionally, scarcity effects should be approached pursuing information about a product through online
platforms such as search engines, product reviews, and
advertisements. Therefore, difficulty in evaluating the
product before buying can lead to dissatisfaction (Syah
*Corresponding Author

doi: https://doi.org/10.21512/tw.v25i1.11526
1412-1212/2541-2388 ©2024 Authors
This is an open access article under the CC BY-NC-SA license(https://creativecommons.org/licenses/by-nc-sa/4.0/)
Journal The Winners is accredited as Sinta 2 Journal (https://sinta.kemdikbud.go.id/journals/profile/261)
How to Cite: Simanjuntak, E. R., & Pratama, R. S. (2024). IT affordances, flow, and perceived scarcity:
A study on impulsive buying behavior and post-purchase dissonance in live shopping. Journal The Winners, 25(1), 13-23.
& Olivia, 2022). Live shopping further addresses this between visibility and flow experiences in online
issue by allowing consumers to investigate products shopping. Sellers foster positive interactions and
during live streaming sessions, facilitating interaction greater consumer engagement by simultaneously
on both a one-to-many (streamer to viewer) and many- showcasing and introducing products, leading to
to-many (among viewers) basis (Fonseca & Barbosa, an immersive shopping experience (Fengliang &
2021). This method enhances the human-computer Jianhong, 2021; Ma et al., 2022). The following
interface during consumers’ ZMoT (Al-Ababneh, hypothesis is proposed based on these results.
2022).
From the human-computer interaction H1: Visibility positively influences flow
perspective, creating an effective web interface that experiences.
facilitates communication between consumers and
online sellers is crucial for a smooth ZMoT experience. Metavoicing is an engagement in online
Previous publications also show that social and interactions by responding to consumers' presence,
technical aspects interact during streaming sessions profile, content, and activities (Zhou & Lou, 2024).
(Min & Tan, 2022a). The relationship between social Previous publications show that streamers deliver
(users) and the technical aspects (IT features) is defined instant personalized services to consumers effectively
as IT affordances (Chatterjee et al., 2020), which through metavoicing, which aids in buying decisions
are potential behaviors arising from the interaction (Lu et al., 2023; Alghamdi et al., 2023). Consumers
between an object or actor with a specific purpose. In can also ask advanced questions by responding to
information systems, affordances refer to the possibility streamer comments and receive answers through the
that an object can influence an individual to perform a interactive process (Zhang et al., 2023). Metavoicing
particular activity. Furthermore, affordances relate to further motivates consumers to obtain helpful
the potential buying actions enabled by the technical information about desired products (Tuncer, 2021).
attributes of an e-commerce platform, enhancing user Metavoicing increases engagement in live shopping
satisfaction (Shao et al., 2020) and developing platform by enabling consumers to comment and interact with
stickiness. The study of user perceptions and technical the streamer. This interaction further fosters flow
aspects is also allowed by features such as guidance experiences, where consumers feel immersed and
shopping, visibility, metavoicing, and interactivity. engaged in shopping activity (Dong et al., 2016; Hu et
Although extensive publications exist on IT al., 2017). The following hypothesis is proposed based
affordances, the relationship with flow experiences on these results.
is still underexplored. The relationship between flow
experiences and impulsive buying behavior is also H2: Metavoicing positively influences flow
well-documented, but the role of perceived scarcity experiences.
in affecting this impact requires further investigation.
Shopping guidance offers products and services
Previous publications have examined the formation
customized to the needs, interests, and demands
of impulsive buying behavior with limited discussion
of customers (Dong & Wang, 2018). Sellers can
on post-purchase dissonance. Therefore, further
provide real-time shopping guidance by improving
publication is necessary to understand how live
the buying quality and strengthening the interaction of
shopping influences IT affordances, including visibility,
consumers (Sun et al., 2019). Technical features such
metavoicing, guidance shopping, interactivity, flow
as personalized product recommendations also play a
experiences, perceived scarcity, impulsive buying
crucial role in aiding consumers’ decisions (Saffanah
behavior, and post-purchase dissonance.
et al., 2023). However, consumers feel comfortable
The psychological model of Stimulus‒
using a live shopping platform when the streamer
Organism‒Response (S-O-R) has been validated in
can effectively assist with personalized online
a live-streaming context by identifying systems and
shopping tasks, leading to the development of flow
services as stimuli that develop flow as the organism
experiences (Fengliang & Jianhong, 2021; Tuncer,
and recognize compulsive buying as the response (Min
2021). Consumers also feel more comfortable when
& Tan, 2022b). Additionally, the technical features of
guided by platform features adapted to individual
live-streaming e-commerce, which are influenced by
needs. It allows consumers to focus more on shopping
the flow experiences, are essential variables affecting
and increases the possibility of flow experiences
impulsive buying behavior and post-purchase
(Dong et al., 2016; Zhang et al., 2023). Based on these
dissonance (Gao & Bai, 2014; Liu et al., 2022).
discoveries, the following hypothesis is proposed.
Visibility also allows consumers to access
product information when live shopping (Ciuchita H3: Guidance shopping positively influences flow
et al., 2022), directly showing that product-related experiences.
pictures and details help to reduce perceived
uncertainty and risk. Sellers showcasing product Interactivity, including two-way communication
pictures and relevant information simultaneously can and synchronicity between sellers and consumers,
enhance positive interactions between consumers and further affects the shopping experience. It refers to the
platforms (Dong & Wang, 2018; Sun et al., 2019). degree and depth of mutual communication between
The previous research further identifies a relationship two parties (Ma et al., 2022). In live shopping,

14 Journal The Winners, Vol. 25 No. 1 June 2024, 13-23

interactivity increases consumers’ engagement, affects the value of the subject, making the products
strengthens vendor responsiveness to questions, and and services appear more valuable. A perception of a
further improves the online shopping experience lack of resources, such as money or time, can force
(Kang et al., 2021). Sellers are also enabled to improve an individual to focus on urgent needs, increasing
responsiveness to consumers’ inquiries and provide the intention to acquire the goods impulsively (Hao
measured information in real-time (Xue et al., 2020; & Huang, 2023). In live shopping, perceived scarcity
Zhang et al., 2023), allowing viewers to experience can intensify the activities and increase susceptibility
extensive sensory sensations without the time and to impulsive buying as consumers become more
place limits (Dong et al., 2022). Real-time interactions immersed in the experience. This statement suggests
further develop intense interactions between streamers that perceived scarcity increases the impact of flow
and consumers, allowing consumers to focus entirely in driving impulsive buying behavior. Based on these
on shopping activity (Liu et al., 2022). Based on these discoveries, the following hypothesis is proposed.
discoveries, the following hypothesis is proposed.
H6: Perceived scarcity moderates the relationship
H4: Interactivity possesses a positive influence on between flow experiences and impulsive
flow experiences. buying behavior.
Flow experiences are psychological conditions Impulsive purchases often lead to feelings
where an individual fully engages in an activity with a of discomfort, post-purchase dissatisfaction, or
high concentration (Csikszentmihalyi, 1990). It further dissonance (Barta et al., 2023). Post-purchase
occurs when a task is carried out with full attention. dissonance is the psychological discomfort
It happens when internal and external conditions experienced after purchase, specifically when there
are correlated, such as deep concentration, feeling is a discrepancy between expectations and reality.
controlled, feedback, and balancing task challenges There are two types of dissonances, namely product
and expertise (Kotler et al., 2022). In live shopping, and emotional. Impulsive buying behavior is found to
flow experiences enable consumers to focus and fully impact product dissonance significantly (Chen et al.,
engage in the activity, which further improves buying 2020). In online purchases, cognitive dissonance may
decisions (Fang et al., 2018). It reduces the differences occur due to a lack of control and physical interaction
of opinion between consumers and streamers, speeding with products, while impulsive purchases make
up the buying process to result in impulsive buying consumers vulnerable to post-purchase dissonance in
(Lu et al., 2023). live shopping (Lazim et al., 2020).
Impulsive buying behavior can further be The publication shows that impulsive
triggered by unexpected needs, visual signals, buying can lead to product dissonance, with
promotional campaigns, and reduced cognitive consumers experiencing negative emotions such
control (Rodrigues et al., 2021). This behavior only as disappointment and regret (Chen et al., 2020).
occurs when a sudden and intense emotional desire Impulsive purchases, often made without thorough
triggers reactive action with low cognitive control. consideration, can lead to post-purchase dissonance,
Interactivity and emotional stimulation can also where consumers doubt the buying decisions and
increase consumers’ tendencies to make impulsive experience regret (Rodrigues et al., 2021; Lin et al.,
buying in live shopping (Li et al., 2022). Activities, 2023; Barta et al., 2023). Therefore, impulsive buying
such as exciting background music, attractive visuals, behavior in live shopping environments filled with
entertaining videos, and user-friendly interactive stimuli can increase consumers’ risk of post-purchase
designs, make consumers feel comfortable and dissonance. Based on these discoveries, the following
focused, prompting unplanned buying (Ming et al., hypothesis is proposed.
2021). The sense of total participation and augmented
positive emotions increase the tendency to buy H7: Impulsive buying behavior positively
impulsively (Wu et al., 2020; Paraman et al., 2022). influences post-purchase dissonance.
Based on these discoveries, the following hypothesis
is proposed.

H5: Flow experiences have a positive influence on II. METHODS

impulsive buying behavior.
Descriptive statistics are used to analyze
Marketers in e-commerce often use scarcity quantitative data through statistical measures such as
promotions, where the availability of products or mean, minimum, maximum, and standard deviation.
events is limited (Gong & Jiang, 2023). Companies Data are collected cross-sectionally in Indonesia over
may even attempt to develop a shortage by deliberately two months (from November to December 2023).
and artificially limiting supply or creating a perception Then, a pilot test is further conducted to validate the
of shortages through scarcity messages (Cengiz & questionnaire and the feedback on clarity as well as
Şenel, 2024). Perceived scarcity is defined in the ambiguity is used to refine the questions. Furthermore,
research as the perception that a particular object is the unit of analysis comprises individuals who have
rare or limited (Baumgärtner et al., 2006), which also watched live shopping for at least 15 minutes in the

IT Affordances, Flow, and Perceived .... (Evi Rinawati Simanjuntak; Rendy Setya Pratama.) 15
last two months. constructs and (b) testing the proposed hypotheses
Responses are collected using convenience in the structural model. Then, hypothesis testing is
sampling, and a 5-point Likert scale is systematically conducted after confirming that the measurements
compiled through the Google Forms platform. The meet reliability and validity requirements. The testing
dimensions of IT affordances, including visibility, focuses on evaluating the relationships between
metavoicing, guidance shopping, and interactivity, are variables in the model. In addition to verifying the
measured using an adapted scale proposed by (Dong statistical significance (p < 0.05), the path coefficient
& Wang, 2018), with each dimension evaluated using and the R2 value are examined. A weight near 0 shows
four indicators. Flow experiences are measured with a weak relationship, while a weight near +1 (or -1)
five indicators from Dong et al. (2022) and Hong et suggests a strong positive (or negative) relationship.
al. (2016), while perceived scarcity is assessed with Concurrently, R2 values range from 0 to 1, with higher
five indicators adapted from Broeder and Wentink values suggesting greater explanatory power, leading
(2022) and Zhang et al. (2022). Four items measuring to a more favorable outcome. The explanatory power
impulsive buying behavior are taken from Park et al. of R2 values of 0.75, 0.50, and 0.25 are categorized
(2012) and Ming et al. (2021). Then, four items to individually as strong, moderate, and low, respectively.
assess post-purchase dissonance are taken from Koller Next, bootstrapping with 5,000 sub-samples is
and Salzberger (2007). further used to test the hypotheses according to the
The research analyzes the data using Partial study model in Figure 1. A one-tailed statistical test is
Least Squares - Structural Equation Modeling (PLS- used to verify the hypotheses. The moderating effect
SEM) in SmartPLS 4.0, incorporating a two-stage is also tested using the interaction method and simple
method: (a) testing the measurement properties of the slope analysis.

Figure 1 Theoretical Model

16 Journal The Winners, Vol. 25 No. 1 June 2024, 13-23

 III. RESULTS AND DISCUSSIONS The measurement items are tested for reliability
and validity before the questionnaire is distributed.
Among the 349 survey respondents, 299 meet The reliability test results show that all items met
the screening criteria, and 250 responses are used Cronbach’s Alpha (CA) and Composite Reliability
after further cleaning. The majority of respondents are (CR) criteria, both greater than 0.7. The validity test
observed to be women (60%), with most (82%) being suggests that all items have factor loading exceeding
within the age range of 18-30 years. The remaining 0.7 and are statistically significant with an Average
18% are aged between 31-43 years. The respondents Variance Extracted (AVE) ≥ 0.5. These results confirm
primarily consist of private employees (57%), followed that all variables meet the requirements of reliability
by students (14%), government employees (14%), and and validity testing (Hair Jr. et al., 2021), as shown in
entrepreneurs (13%). Frequent watchers who watch Table 1.
live shopping 5 to 10 times per month make up 65% Discriminant validity is assessed, showing that
of the respondents, while 28% watch less than 5 times the Heterotrait-Monotrait (HTMT) value does not
monthly. exceed the threshold of 0.9 (Henseler et al., 2015), as

Table 1 Construct Reliability and Validity

Variable Items Factor Loading CA (> 0.7) CR (> 0.7) AVE (> 0.5)
Visibility VIS1 0.759 0.792 0.865 0.615
VIS2 0.810
VIS3 0.801
VIS4 0.766
Metavoicing MTA1 0.716 0.817 0.879 0.647
MTA2 0.795
MTA3 0.856
MTA4 0.842
Guidance Shopping SGD1 0.712 0.807 0.874 0.635
SGD2 0.865
SGD3 0.768
SGD4 0.835
Interactivity ITV1 0.803 0.810 0.875 0.637
ITV2 0.791
ITV3 0.823
ITV4 0.773
Flow Experience FLW1 0.808 0.848 0.892 0.622
FLW2 0.795
FLW3 0.787
FLW4 0.790
FLW5 0.764
Perceived Scarcity PSC1 0.783 0.841 0.887 0.612
PSC2 0.747
PSC3 0.805
PSC4 0.774
PSC5 0.801
Impulsive Buying Behavior IBB1 0.806 0.831 0.888 0.664
IBB2 0.840
IBB3 0.823
IBB4 0.790
Post Purchase Dissonance PPD1 0.825 0.820 0.881 0.650
PPD2 0.819
PPD3 0.762
PPD4 0.816
Note: Cronbach’s Alpha (CA), Composite Reliability (CR), and Average Variance Extracted (AVE)

IT Affordances, Flow, and Perceived .... (Evi Rinawati Simanjuntak; Rendy Setya Pratama.) 17
detailed in Table 2. The result confirms the discriminant buying behavior (R2 = 0.513). Among the four
validity of the measurement items of each construct. dimensions of IT affordances, interactivity evolves as
Figure 2 shows the full PLS-SEM (outer and the strongest driver of flow experiences (β = 0.276),
inner) model used in the research. Analysis of the followed by visibility (β = 0.156), and metavoicing
data supports six hypotheses except for H3 (guidance (β = 0.108). The impact of flow on impulse buying
shopping → flow experiences, t = 1.000, t < 1.64) behavior is evident with a strong predictive power (R2
as detailed in Table 3. The R2 value shows that the = 0.513).
components of IT affordances effectively predict flow The testing of H6 on the moderating effect
experiences. Furthermore, flow interacts significantly of perceived scarcity shows that it significantly
with perceived scarcity, showing a strong predictive influences the relationship between flow experiences
capability (R2 = 0.513) for impulsive buying behavior. and impulsive buying behavior. However, this effect
This model effectively predicts post-purchase is weak (β = -0.068, t > 1.64) and has a negative effect
dissonance through the examination of impulsive which is contrary to the hypothesis.

Table 2 Discriminant Validity – Heterotrait-Monotrait Value

FLW IBB ITV MTA PPD PSC SGD VIS PSC x FLW
FLW
IBB 0.823
ITV 0.783 0.563
MTA 0.599 0.665 0.554
PPD 0.849 0.864 0.590 0.598
PSC 0.869 0.741 0.617 0.511 0.808
SGD 0.711 0.493 0.824 0.659 0.524 0.505
VIS 0.698 0.535 0.651 0.637 0.592 0.546 0.834
PSC x FLW 0.429 0.395 0.359 0.338 0.359 0.388 0.342 0.289

Note: Visibility (VIS), Metavoicing (MTA), Guidance Shopping (SGD), Interactivity (ITV), Flow Experience (FLW), Per-
ceived Scarcity (PSC), Impulsive Buying Behavior (IBB), and Post Purchase Dissonance (PPD)

Figure 2 Full Model

(Path Coefficient & Factor Loading)

18 Journal The Winners, Vol. 25 No. 1 June 2024, 13-23

 Table 3 Hypothesis Testing Result

Hypothesis Path R2 Path Coefficient T-Values Conclusion

H1 VIS --> FLW 0.524 0.483 2.629 supported
H2 MTA --> FLW 0.108 2.080 supported
H3 SGD --> FLW 0.096 1.000 not supported
H4 ITV --> FLW 0.276 5.359 supported
H5 FLW --> IBB 0.513 0.335 6.522 supported
H6 PSC x FLW --> IBB -0.068 1.973 supported
H7 IBB --> PPD 0.497 17.253 supported

Note: Visibility (VIS), Metavoicing (MTA), Guidance Shopping (SGD), Interactivity (ITV), Flow Experience (FLW),
Perceived Scarcity (PSC), Impulsive Buying Behavior (IBB), and Post Purchase Dissonance (PPD).

Figure 3 Slope Analysis

The effect suggests that perceived scarcity events.

can decrease the influence of flow experiences on Metavoicing in the form of feedback or reviews
impulsive buying behavior. A simple slope plot engages consumers in current discussions about the
analysis (see Figure 3) confirms the results and shows shopping experiences, thereby promoting sustained
similar outcomes. The green line in the results shows flow experiences (Zhang et al., 2023). This engagement
that higher perceived scarcity hinders the influence keeps consumers focused and engaged during live
of flow experiences on impulsive buying behavior. shopping activities continuously, facilitating more
Conversely, the red line suggests that lower perceived profound flow experiences (Sun et al., 2019). A given
scarcity strengthens the influence of flow experiences rate that appears directly on the screen without moving
on impulsive buying behavior. pages can provide instant feedback to live shopping
The results show that increased visibility in streamers and other users. It can be an additional
live shopping contributes to a more profound buying motivation for users to engage more deeply in live
experience for consumers. Clear and prominent shopping activities.
activities in live shopping are instrumental in generating Contrary to expectations, the research finds
flow experiences for users. This result is consistent no support for the influence of shopping guidance
with the theory in Tuncer (2021) that emphasizes on flow experiences. Effective guidance shopping
the importance of providing comprehensive product should customize responses to individual consumers’
information to aid consumers in making informed needs. The result implies that guidance shopping
buying decisions. High-quality pictures and video should be able to answer questions and solve the
demonstrations increase product appeal, enhancing needs of consumers in a personalized manner (Tuncer,
consumers’ interest and immersion in live shopping 2021). However, the research finds that the platform

IT Affordances, Flow, and Perceived .... (Evi Rinawati Simanjuntak; Rendy Setya Pratama.) 19
guidance often fails to deliver personalization It will ensure consistency in information delivery
assistance for consumers’ requests. Misinformation and offer compelling alternatives rather than simply
or irrelevant guidance can further lead to confusion emphasizing limited stock.
among consumers and hinder the ability to find
desired products or obtain necessary information.
These conditions disrupt flow experiences and further IV. CONCLUSIONS
disengage consumers from live shopping activities
(Chandrruangphen et al., 2021). In conclusion, the research aims to examine
Interactivity in live shopping helps to create a how IT affordances, including visibility, metavoicing,
more profound consumer shopping experience (Liu guidance shopping, and interactivity, enhance
et al., 2022). The results show that a higher level of consumers' flow experiences, such as concentration
interactivity increases the possibility for users to and immersion, influencing impulsive buying
experience flow. It emphasizes the importance of behavior. During the examination, perceived scarcity
active interaction between users and streamers as live is found to negatively moderate the impact of flow
shopping can develop a deep shopping experience for experiences on impulsive buying behavior. The
users. The interaction between buyers and sellers also research further contributes to advancing the S-O-R
produces an intense dynamic that gives consumers a model in the context of live shopping, particularly by
sense of independence from reality, removes anxiety, exploring the theoretical role of perceived scarcity.
and is more immersed in a shopping experience with a Visibility, metavoicing, and interactivity are also
high level of immersion (Liu et al., 2022; Dong et al., found to foster a positive environment conducive to
2022). Live shopping platform companies can further exploring live shopping experiences, with interactivity
add a product voting feature where users participate evolving as the most critical driver of flow. However,
in a favorite product or event theme selection. The no significant influence of shopping guidance on flow
platform can also provide a live voting option or creation is observed.
polling feature and publish the results directly to Although the research focuses on users of
enhance user engagement. Additionally, companies the entire e-commerce live shopping platform, it
add Group Buying features by motivating users to recognizes the potential influence of cultural variations,
shop together and offering special discounts when demographic differences, social characteristics, and
several consumers buy products simultaneously. By economic conditions across different regions in
implementing these features, live shopping platforms Indonesia. The results provide valuable insights but
can develop a more dynamic and engaging experience require careful consideration when generalizing to
stimulating interaction between event organizers, represent diverse live shopping behavior across the
sellers, and users. country. Future research should examine regional
Consumers who are fully immersed in live differences more deeply to understand variations in
shopping environments have more probability of live shopping responses better.
exhibiting impulsive buying behavior, which is Given the outcome that perceived scarcity can
strongly stimulated by the environment. Furthermore, diminish the relationship between flow experiences
flow experiences have the potential to make an and impulsive buying behavior, future research can
unplanned buying due to a feeling of being highly explore contextual limitations by exploring how
engaged and an increase in positive emotions during perceived scarcity operates within specific products
live shopping sessions. It further increases the tendency or platforms. Additionally, expanding the scope to
of consumers to engage in impulsive shopping (Wu et investigate the relationship between impulsive buying
al., 2020). behavior and post-purchase dissonance, possibly
Post-purchase restlessness often originates from considering moderating factors, such as materialism,
hasty decisions made without thorough consideration can provide new insights. Materialistic tendencies
(Lazim et al., 2020; Barta et al., 2023). Doubts about have also been shown to influence feelings of regret
buying decisions or feelings of misallocation of funds over buying decisions, impacting emotions and daily
can signal impulse-driven purchases (Chen et al., well-being, thereby offering a promising avenue for
2020). Furthermore, perceived scarcity can diminish studies in the domain of live shopping.
the impact of flow experiences on impulsive buying Furthermore, future research can explore
behavior. It can be because awareness of scarcity advanced responses to post-purchase dissonance, such
develops a form of internal disruption that distracts as examining consumers’ decisions regarding product
attention from continuous flow experiences. In returns. Research on product returns can offer practical
the context of live shopping, the disruption of live insights into managing return rates originating from
shopping users can cause flow interruption. Users consumer dissatisfaction. It can further affect the
whose attention is not on shopping are more inclined profitability and reputation of the company’s brand.
to engage in rational evaluations rather than impulsive This line of inquiry can inform companies in designing
buying behavior. It will decrease the influence of flow more effective and sustainable after-sales policies.
and reduce the tendency to be impulsive. Additionally,
sellers should strategically manage user experiences Author Contributions: Writing-original draft, E.
to mitigate distractions caused by perceived scarcity. R. S., and R. S. P.; Methods-data collection, R. S. P.;

20 Journal The Winners, Vol. 25 No. 1 June 2024, 13-23

Analysis, R. S., P. ; Review & Proofread, E. R. S. for Data Science (IRI) (pp. 425-429). IEEE. https://
doi.org/10.1109/IRI49571.2020.00071.
Data Availability Statement: Data are available from Ciuchita, R., Medberg, G., Penttinen, V., Lutz, C., &
the corresponding author, E. R. S., upon reasonable Heinonen, K. (2022). Affordances advancing
request. User-Created Communication (UCC) in service:
Interactivity, visibility and anonymity. Journal of
Service Management, 33(4/5), 688-704. https://doi.
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