Article

Explore the Feeling of Presence and Purchase Intention in

Livestream Shopping: A Flow-Based Model
Jielin Yin 1 , Yinghua Huang 1 and Zhenzhong Ma 2,3, *

1 School of Economics and Management, Beijing Information Science & Technology University,
Beijing 100101, China
2 School of Business, Nanjing Audit University, Nanjing 211815, China
3 Odette School of Business, University of Windsor, Windsor, ON N9B 3P4, Canada
* Correspondence: maz@uwindsor.ca

Abstract: Livestream shopping has attracted great attention in an increasingly digitalized society.
This study is to explore the mechanism through which social presence and physical presence affect
consumer purchase intentions in livestream shopping as an emerging e-commerce model. Based on
the flow theory, this study proposes an integrated model to explain the mechanism through which
the feeling of presence affects consumers’ purchase intentions in livestream shopping. Empirical data
on livestream shopping were collected in China to test the proposed model for an exploratory study.
The results show that the feeling of physical presence influences consumers’ purchase intentions
through concentration and perceived control, and the feeling of social presence influences consumers’
purchase intentions through concentration and enjoyment, and, thus, both social presence and
physical presence are important elements in livestream shopping. This study provides a better
understanding on the mechanism of how the feeling of presence helps improve purchase intentions
in livestream shopping. This study shows both physical presence and social presence are positively
related to consumers’ purchase intention, but with different paths, and, thus, sheds new lights on the
feeling of presence and its impact on consumer behaviors in e-commerce.

Keywords: interactive marketing; flow theory; livestream shopping; presence; purchase intention;
e-commerce
Citation: Yin, J.; Huang, Y.; Ma, Z.
Explore the Feeling of Presence and
Purchase Intention in Livestream
Shopping: A Flow-Based Model. J. 1. Introduction
Theor. Appl. Electron. Commer. Res. Livestream shopping is a new way to buy and sell products in an increasingly digital-
2023, 18, 237–256. https://doi.org/ ized society. Unlike traditional marketing approaches that often rely on pictures and text
10.3390/jtaer18010013 descriptions to attract consumers, livestream brings a new type of interactive social space to
Academic Editor: Xuefeng Zhang change the way brands interact with their audiences in e-commerce businesses [1,2]. Using
a live video strategy, livestream can engage viewers in immediate and authentic ways that
Received: 14 December 2022 other social media formats cannot [3]. During the livestream, consumers can communicate
Revised: 13 January 2023
with the livestream anchors and other consumers and sometimes watch product usage in
Accepted: 28 January 2023
real time. This new shopping approach is enjoying increasing popularity among consumers
Published: 30 January 2023
because consumers can learn about products and services from the anchors and from each
other, rather than only through product description, pictures, or consumer reviews such
as likes, ratings and comments [4–6] and, thus, can greatly improve consumers’ purchase
Copyright: © 2023 by the authors.
intentions [7–9].
Licensee MDPI, Basel, Switzerland. Along with the fast development of social media and e-commerce, booming livestream
This article is an open access article shopping has attracted scholars’ attentions and existing research has focused on how
distributed under the terms and livestreaming affects consumers’ experiences and purchase intentions [1,10–13]. For in-
conditions of the Creative Commons stance, studies have employed a consumer engagement perspective to explore consumers’
Attribution (CC BY) license (https:// purchase intentions in livestream shopping [14,15], and others have examined the mediat-
creativecommons.org/licenses/by/ ing effect of consumers’ trust in livestreaming and consumers’ purchase intentions [9,16].
4.0/). While the existing studies have generated important insights on livestream shopping, an

J. Theor. Appl. Electron. Commer. Res. 2023, 18, 237–256. https://doi.org/10.3390/jtaer18010013 https://www.mdpi.com/journal/jtaer
J. Theor. Appl. Electron. Commer. Res. 2023, 18 238

emerging stream of research has called on researchers to adopt the concept of presence to
investigate the impact of the feeling of presence on consumers’ purchase intentions [7,17,18],
which has a great potential to help better understand the dynamics of livestream shopping
and the value livestreaming can bring to contemporary marketing research and practice [8].
The feeling of presence is a “perceptual illusion of non-mediation”, which occurs when peo-
ple fail to perceive or realize the existence of a medium in their interactions with others and
thus respond as if the medium were not there [7,19,20]. Presence in a mediated environment
such as livestream shopping consists of physical presence and social presence [19]. In the
dynamic process of livestream shopping, consumers not only experience the social presence
of socially being together with others through interacting with livestream anchors and other
consumers, but also virtually experience the physical presence of being located somewhere,
generated through the interface [7,13]. While social presence has been examined in many
mediated environments such as online gaming or behaviors in virtual communities, few
studies have explored the roles of physical presence and social presence at the same time
or their joint effects in online shopping activities [7,15,17,18]. It is worthwhile to explore
whether both physical presence and social presence facilitate the formation of purchase
intention in livestream shopping [7,17]. This is critical in understanding the mechanism
through which livestreaming attracts customers to make purchase decisions. In addition,
although both physical presence and social presence are important types of presence, it
is not clear what the differentiated effects are of these two types of presence affecting
consumers’ purchase intentions in livestream shopping [7,18]. While many studies have
explored livestream shopping, there is a paucity in integrating the whole process [7]. This
study attempts to provide such an integrated model
This study is intended to employ the flow theory to explore the impact of the feel-
ing of presence on purchase intentions in livestream shopping—a flow-based interactive
e-commerce business model. More specifically, this study will explore how the two di-
mensions of presence—both social presence and physical presence help form the flow so
as to motivate consumers to make a purchase decision in the newly emerged livestream
shopping. The flow theory is about the mental state of people who conduct their activities
for pleasure, not for rewards of money or fame. and people experience a holistic sensation
when they act with total involvement. The data were collected in China, one of the most im-
portant emerging markets, that has received increasing attention in management research
due to its important role in the world market [21–25] and also has a flourishing livestream
sector [7,9,13,16,25,26]. China is one of the first few markets to endorse and widely pro-
mote livestream shopping and has also achieved great success since Taobao launched the
livestream function in 2016, known as the first year of livestream shopping in China [10].
According to the data from CNNIC (China Internet Network Information Center), the num-
ber of consumers participating in livestream shopping reached 390 million in December
2020, about 39.2 percent of the total number of internet users in China, and livestream
shopping has become a very popular shopping approach among Chinese consumers.
The findings of this study will be able to shed light on livestream shopping, the fast-
emerging shopping approach, for a better understanding on how to engage consumers
and to increase their purchase intention in the increasingly digitalized consumer market, in
particular, considering that the COVID-19 pandemic has forced consumers to rely more on
enriched online experiences to make shopping decisions. In this study, a research model
will be developed based on the flow theory and then empirically tested with the two di-
mensions of presence as antecedents, three dimensions of the flow including concentration,
perceived control, and enjoyment as mediators, and consumers’ purchase intention as
the criterion. The remainder of the paper is organized as follows. We first present the
theoretical framework based on the flow theory and related literature on presence, and
then develop a research model on the proposed relationships, followed by data collection,
analyses, results, and findings. The final section discusses theoretical and managerial
implications of this study and further future research directions.
J. Theor. Appl. Electron. Commer. Res. 2023, 18 239

2. Theoretical Framework
2.1. Livestream Shopping
As a newly emerged e-commerce format, livestreaming provides real-time audio and
video transmission of an event over the internet [27]. Livestream shopping is a new e-
commerce format with high HCI (human–computer interaction) which can create the feeling
of presence [7,26]: while consumers are not there physically, they can experience being
there when interacting with the anchors and other consumers through HCI. As a rapidly
emerging shopping approach, livestreaming has the power to expand the viewership
into millions and reach audiences of an unprecedented scale for product marketing and
sales [2,4].
Livestreaming is a unique method of online shopping, and it provides a highly inter-
active medium to introduce and demonstrate how to use the products to the consumers.
Livestreaming has a public scrolling text screen at the livestream interface where customers
can ask questions or requests through the text box to the screen, and livestream anchors can
answer these questions immediately to achieve real-time communication [10]. Compared
with traditional online shopping or television shopping channels, livestream shopping
has three unique characteristics that can attract consumers to stay focused on shopping
activities. First, consumers can learn about targeted products through real-time video
display instead of only depending on pictures or text descriptions, such as in traditional
online shopping [9]. Second, in livestream shopping, anchors can reply immediately when-
ever consumers ask questions on the targeted products, and consumers can also interact
with other consumers, which leads to a better social experience for consumers than that in
traditional television shopping channels [26] or traditional online shopping. Third, the lack
of face-to-face interactions in traditional online shopping often leads to questions about
the authenticities of marketers and their products while livestream shopping can solve this
problem [12]. Therefore, livestreaming as a real-time, interactive, and authentic social shop-
ping approach [2,9] can motivate consumers to be better involved in shopping activities
and, thus, enhance their sense of presence and involvement, and ultimately increase their
purchase intentions [3,9].
The increasing popularity of livestream shopping in e-commerce has attracted great
research interest. Research has explored the impact of interface features (e.g., the website)
on consumers’ behaviors [27], consumer engagement in livestream shopping [1,8,14], the
impact of comments made in livestream shopping on consumers’ purchase intentions [28],
as well as the mechanism through which livestreaming affects purchase intention [7,13],
with important insights generated on livestreaming and consumer behaviors [11,18]. Table 1
summarizes the key antecedents of purchase intentions in livestream shopping examined
in previous research.

Table 1. A summary of antecedents of purchase intentions in livestream shopping.

Antecedents of Purchase Intentions in Livestreaming Studies

Interface features [27]
Comments made in livestreaming [28,29]
Psychological distance [11]
Para-social interaction [10]
Live content—product fit [30]
Consumer trust [9,11,12,16]
Consumer engagement [1,8,14]
Social presence [7,13,17,18,26]
J. Theor. Appl. Electron. Commer. Res. 2023, 18 240

2.2. Presence
With the fast development of virtual reality technology, the sense of ‘being there’, or
presence, in a mediated environment has received substantial attention [2,19]. Presence is
a sense of being present at a remote location through human–computer interaction [31],
a virtual presence generated in the virtual environment [32]. Presence as the “perceptual
illusion of non-mediation” happens when a person fails to perceive or recognize the
existence of a medium in the experience of a technology intermediary [20].
Scientific research on presence shows that, from a psychological perspective, presence
consists of physical presence and social presence [20]. Physical presence refers to the
feeling of being somewhere, while social presence refers to the feeling of being (and
communicating) with others [19]. While physical presence and social presence do not
always occur at the same time, consumers in livestream are able to feel physical presence
and social presence at the same time, thanks to the development of human–computer
interaction technology often used in the livestream virtual environment.
Research shows that four main factors can affect the feeling of presence [19,32–34],
including the ability to create an intermediary environment that conveys enough infor-
mation, real-time updates, social elements in the interactions, and users’ characteristics.
Livestreaming incorporates the first three in its interactions with consumers and thus can
effectively stimulate the generation of the feeling of presence. Research literature has
shown that social presence can impact consumers’ purchase intention in livestreaming.
Zhu et al. [35] used the stimulus–organism–response (SOR) theory to show that social
presence had a positive effect on consumers’ purchase intentions. However, few studies
have investigated the impact of physical presence on consumers’ purchase intentions in a
mediated environment [7]. Therefore, more studies are still needed to better understand
how the feeling of presence, both physical presence and social presence, can enhance
purchase intentions in livestream shopping.

2.3. The Flow Theory

The flow theory was proposed in the 1970s based on research examining the mental
state of people who carry out activities for pleasure, not for rewards of money or fame [36].
According to the flow theory, flow is the “holistic sensation that people feel when they act
with total involvement”, and a flow state is the state in which “people are so involved in an
activity that nothing else seems to matter; the experience is so enjoyable that people will
continue to do it even at great cost, for the sheer sake of doing it” [36]. The flow theory has
been used for research in various fields including psychology, management, arts, human–
computer interactions, and marketing to explore how individuals are motivated by and
absorbed in what they are doing [36–41]. A great amount of research on flow has focused
on a computer-mediated environment to investigate user experience in using the internet,
with the antecedents of flow, including consistency of perceived skills and challenges,
concentration, and interactions [42] and the consequences of flow, including increased
learning, perceived behavior control, repeat visits, and positive subjective experiences [43].
These consequences are often experienced in livestream shopping activities. Therefore,
the flow theory provides a good conceptual framework to explore how consumers are
absorbed in the computer-mediated activities—livestream shopping and further make
purchase decisions [7].

2.4. A Flow-Based Research Model on Livestream Shopping

Livestream shopping is a unique shopping approach occurring in a computer mediated
environment. Studies have shown that livestream shopping is interactive, real-time, and
often associated with the feeling of presence: feeling of being in a remote location—physical
presence and feeling of being together with others—social presence [7,9,27,35]. Flow refers
to the feeling of a person when fully engaged in an activity [36], such as livestream shopping,
which makes people feel happy and have a sense of control [41]. Koufaris [39] classified
flow into three dimensions: concentration, perceived control, and enjoyment. Based on
 JTAER 2023, 18, FOR PEER REVIEW

J. Theor. Appl. Electron. Commer. Res. 2023, 18 Flow refers to the feeling of a person when fully engaged in an activity 241 [36], suc
livestream shopping, which makes people feel happy and have a sense of control
Koufaris [39] classified flow into three dimensions: concentration, perceived control
the flow theory enjoyment.
and the concept
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consumers’ concentration and perceived control which leads to a purchase decision, while
ical presence facilitates consumers’ concentration and perceived control which leads
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Figure 1. A research model

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on presence and purchase intention.

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developed in the following sections to elaborate on the proposed relationships.
developed in the following sections to elaborate on the proposed relationships.

3. Hypotheses 3. Hypotheses
Presence, concentration,
Presence,perceived control,
concentration, and enjoyment.
perceived Pastenjoyment.
control, and research has
Pastshown that
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presence as a psychological
presence as astate can lead people
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computer-mediated environment [45,46].
computer‐mediated A feeling
environment of presence
[45,46]. A feelingoccurs when people
of presence con- people
occurs when
sider objects in mediated environments
sider objects in mediatedas environments
physically present ones, a perceptual
as physically illusion
present ones, [47],
a perceptual illu
and this perceptual
[47], illusion
and this created in mediated
perceptual environments
illusion created in mediatedcanenvironments
produce a feeling of
can produce a fe
immersion whereby people concentrate
of immersion whereby people on the focal activities
concentrate on the [46]. Biocca [48]
focal activities has
[46]. dis- [48] has
Biocca
covered that presence
coveredhas the
that ability to
presence hasshift
the users’
ability concentration from the real world
to shift users’ concentration from theto real wor
the virtual environment.
the virtualAgarwal and Karahanna
environment. Agarwal and [49]Karahanna
further revealed that people
[49] further revealedwhothat people
were immersed werein presence
immerseddemonstrated
in presence more cognitivemore
demonstrated absorption and
cognitive concentration.
absorption and concentra
Finneran and Zhang [50] also suggested that presence was an important factor that enabled
users to focus on computer-based tasks. More recently, Sajjadi et al. [51] pointed out that
both physical presence and social presence could influence concentration in entertaining
activities, which leads to people’s flow experience. Wang and Lee [18] have also shown
J. Theor. Appl. Electron. Commer. Res. 2023, 18 242

that high human–computer interaction can generate users’ presence and strengthen users’
concentration. Therefore, it is hypothesized that:
H1a. Physical presence is positively related to concentration in livestream shopping.
H1b. Social presence is positively related to concentration in livestream shopping.
Physical presence refers to the feeling of being located in a remote place when im-
mersed in a mediated environment [20]. In livestream shopping, the feeling of physical
presence depends on the degree of interaction between consumers and the virtual world [9].
Consumers can obtain a high sense of physical presence from those websites with high
information interaction and authenticity. With physical presence, consumers tend to forget
that they are using a medium and thus consider the virtual environment as a real one in
which they can control the focal activities, thanks to the quick and timely responses in the
mediated environment [52], and this physical presence can lead to a high level of perceived
control [53]. In addition, physical presence is able to motivate consumers to participate
and further engage more in the mediated environment [52], which also produces more per-
ceived control [54]. Pelet et al. [46] demonstrated that physical presence positively affected
perceived control. Wang and Yao [55] also found that there was a positive relationship
between physical presence and perceived control in the context of VR games. Hence, the
following hypothesis is proposed:
H2. Physical presence is positively related to perceived control in livestream shopping.
Social presence is the feeling of being together with others when people are interacting
with other people through a medium [56]. Social presence describes the situation when you
are communicating with others in the mediated environment, you can feel that the person
is at your side even though he or she may actually be far away [57]. Social presence gives
people a sense of psychological intimacy and warmth in the mediated environment [58],
which leads to enjoyment, similar to the experiences of being together with others in the
real world [59], and the stronger the sense of social presence in the virtual world, the more
enjoyment consumers can obtain [60]. Lombard and Ditton [20] pointed out that the most
significant psychological impact of social presence was enjoyment. Fortin and Dholakia [60]
also suggested that social presence can generate positive emotions and cognitions, such as
enjoyment. Cyr et al. [61] found that social presence positively affected people’s enjoyment
in the context of online shopping. Shen’s empirical study [62] on online commerce also
showed that social presence could stimulate consumers’ sense of enjoyment. Hence, it is
hypothesized that:
H3. Social presence is positively related to enjoyment in livestream shopping.
Concentration is defined as focusing on a limited stimulus field and it is one of the
most recognized dimensions in flow research [63]. Novak and his colleagues [64] showed
that concentration, as a critical part of flow, would have impact on other elements of flow.
Quinn [65] also demonstrated that some elements of flow may lead to other elements in the
flow experience. When consumers are concentrating on shopping activities in livestream
shopping, they tend to have high perceptions of their abilities to successfully navigate
through the virtual environment and of how the web responds to their inputs [66,67], i.e.,
a high level of perceived control. Therefore, we expect that high concentration leads to
high perceived control in livestream shopping. In addition, concentration also reflects the
degree of efforts devoted to the focal events such as livestream shopping activities [68].
When consumers devote themselves to livestream shopping, they constantly search for new
information on products or services to satisfy their needs, which often leads to happiness
and excitement [69]. For instance, Liu et al. [68] showed that people experienced the highest
level of enjoyment when they were intensely indulged in doing something. Liu et al. [68]
also found that consumers’ concentration significantly affected their enjoyment in mobile
commerce. Hence, it is proposed in this study:
H4. Concentration is positively related to perceived control in livestream shopping.
J. Theor. Appl. Electron. Commer. Res. 2023, 18 243

H5. Concentration is positively related to enjoyment in livestream shopping.

Concentration, perceived control, enjoyment, and purchase intention. Research has shown
that concentration as a key element of flow can positively affect an individual’s intention
to engage in certain activities by improving his or her overall experiences [69–71]. When
individuals concentrate on an activity, their attention will be focused on a narrow stimulus
field, which filters out other irrelevant thoughts and perceptions [72]. The consumers will
then become more intensely absorbed in their activities and further generate a stronger
desire to accomplish their current tasks [69], a behavioral intention. Empirical studies
have demonstrated that concentration can affect consumers’ purchase intentions. For
instance, Xia and Sudharshan [73] discovered that interruptions in concentration could
reduce consumers’ satisfaction with online shopping which in turn reduced their purchase
intentions. Koufaris [39] has shown that concentration had a positive effect on online
consumers’ purchase intentions. Wang and Hsiao [74] confirmed that concentration was
positively related to consumers’ intentions for future shopping in retail store shopping
activities. Hence, it is hypothesized in this study:
H6. Concentration is positively related to consumers’ purchase intentions in livestream shopping.
Perceived control is another important element in consumers’ purchase intentions.
When consumers are involved in a mediated environment, they often attempt to ob-
tain more control, less effort, and higher efficiency in the process of interactions [75–77].
Moreover, with better perceived control, consumers will be able to obtain higher quality
information [78], which is closely related to consumers’ purchase intentions. It is argued
that information quality can improve consumers’ purchase intentions [79]. Dedeke [80] con-
firmed that there was a positive relationship between information quality and consumers’
purchase intentions. Chen and Chang [29] also showed that information quality was an
important antecedent of consumers’ purchase intentions. Based on these analyses, it is
hypothesized that:
H7. Perceived control is positively related to consumers’ purchase intentions in livestream shopping.
Enjoyment is the intrinsic pleasure of being involved in an activity [39]. It is a positive
emotion that can trigger consumers’ purchase intentions. If consumers feel the enjoyment,
they are very likely to make purchase decisions [81]. Jarvenpaa and Todd [75] suggested that
enjoyment had a significant impact not only on offline shopping but also on online shopping.
Eighmey and McCord [82] further proved that the enjoyment of shopping had a significant
positive impact on consumers’ purchase intentions in online shopping. Enjoyment in
livestream shopping comes from the entertainment and excitement embedded in interactive
shopping activities [83]. The higher level of enjoyment can motivate consumers to spend
more time livestreaming which leads to increased purchase intentions [84]. Dholakia [85]
also contended that consumers’ purchase intentions are affected by emotional factors,
such as enjoyment generated in livestreaming. It is expected in this study that consumers
in livestream shopping are also more willing to make purchase decisions prompted by
intrinsic interests and enjoyment generated in livestream shopping [86,87]. Therefore, it is
hypothesized in this study:
H8. Enjoyment is positively related to consumers’ purchase intentions in livestream shopping.

4. Methods
4.1. Sample and Data Collection
To explore the impact of the feeling of presence on purchase intentions in livestream
shopping, data were collected with an online questionnaire in this exploratory study
through recruiting consumers who have the experience of livestream shopping. The data
were collected in China where livestream shopping is booming at an unprecedented scale.
An online questionnaire was made available in China’s main virtual communities including
Weibo, WeChat groups, and Baidu Tieba. Respondents were recruited from these virtual
J. Theor. Appl. Electron. Commer. Res. 2023, 18 244

communities with a monetary reward of 10 RMB for anyone who completed the survey to
participate in this project.
The questionnaire was available online for about a month in the summer of 2021,
during which a total of 500 responses were received. To ensure that all our participants
had the experiences of livestream shopping, we used a screening question in the survey.
Based on the screening question and after checking the completeness and accuracy, we
obtained 384 useable responses for analysis. Among the respondents included in the
analysis, 62% were female and 32% were male. Respondents between the ages of 18 and
45 accounted for 92.5% of the total sample. In terms of education background, about 77.6%
of the respondents had a bachelor’s degree and 13% of the respondents had a master’s
degree or above. The relatively younger respondents and the higher education distribution
are consistent with those in previous studies [7.10]. A detailed sample profile is reported in
Table 2.

Table 2. Descriptive Statistics.

Variables Category Number Percentage (%)

Male 146 38
Gender
Female 238 62
Under 18 12 3.1
18–30 226 58.9
Age
30–45 129 33.6
Above 45 17 4.4
High school or below 36 9.4
Education College or university 298 77.6
Postgraduate or above 50 13

4.2. Measures
The online questionnaire included all the key variables in the proposed research
model: physical presence, social presence, concentration, perceived control, enjoyment,
and purchase intention. In addition, there were three control variables: gender, age, and
education. All the scales in this study were adapted from previous literature and used a
5-point Likert scale (ranging from 1 = “Strongly disagree” to 5 = “Strong agree”). In order to
make them suitable for our research in China, we made necessary adaptation to the items.
These scales were originally in English and were first translated into Chinese and then back
into English by bilingual scholars to ensure equivalency before using in the questionnaire,
following the commonly prescribed procedures [88].
Physical Presence. The items of physical presence were adapted from Barfield et al. [33].
A four-item scale was developed to assess physical presence in the current study. Sample
items include “When shopping in live streaming, I felt as if I were shopping in a brick-
and-mortar store” and “While I was shopping in live streaming, I felt as if I were in a real
world created by the live streaming”. The Cronbach’s alpha for this measure was 0.80 in
this study.
Social Presence. The items of social presence were adapted from Gunawardena [89].
Example items of the six-item measure include “There is a sense of human contact in live
streaming shopping” and “There is a sense of sociability in live streaming shopping”. The
Cronbach’s alpha for this measure was 0.84, with one item dropped for its low factor loading.
Flow. The items of flow were adapted from Koufaris [39]. This scale had 12 items
that measure three dimensions of the flow: concentration, perceived control, and enjoy-
ment. Sample items include “I was absorbed intensely in the live streaming shopping”,
“I felt everything was under control when I was shopping in live streaming”, and “I
found the live streaming shopping was enjoyable”. The resulting Cronbach alphas for
J. Theor. Appl. Electron. Commer. Res. 2023, 18 245

these three dimensions in this study were 0.85, 0.81, and 0.87, respectively, all above the
recommended level.
Purchase Intention. The three-item scale for consumers’ purchase intention was adapted
from Dodds [90]. Sample items include “It is very likely that I will buy the product”, “I
intend to buy the product”, and “I would consider buying the product in future”. The
Cronbach’s alpha for this variable was 0.83 in this study. For the full list of questionnaire
items used in this study, please refer to the Appendix A.

4.3. Data Analysis and Results

We used AMOS 23.0 to conduct basic descriptive statistical testing and correlation
analysis and to assess the validity of the constructs examined in this study [91]. To test
the proposed hypotheses and the mediating roles of the flow, the SPSS process was used
for related analyses. Table 3 shows the means, standard deviations, and correlations of all
the variables.

Table 3. Mean, S.D., and correlations.

Variables Mean S.D. 1 2 3 4 5 6 7 8

1. Gender 1.62 0.49
2. Age 2.39 0.63 0.02
3. Education 2.04 0.47 0.14 ** 0.00
4. Physical Presence 3.35 0.84 0.11 * 0.25 ** 0.06
5. Social Presence 3.42 0.80 0.12 * 0.25 ** 0.11 * 0.77 ***
6. Concentration 3.42 0.86 0.17 ** 0.18 ** 0.09 0.75 *** 0.69 ***
7. Perceived Control 3.47 0.75 0.08 0.22 ** 0.01 0.40 *** 0.42 *** 0.36 ***
8. Enjoyment 3.67 0.82 0.25 ** 0.19 ** 0.10 0.73 *** 0.73 *** 0.78 *** 0.38 ***
9. Purchase Intention 3.45 0.88 0.23 ** 0.23 ** 0.11 * 0.71 *** 0.70 *** 0.74 *** 0.76 *** 0.76 ***
Notes: N = 384, * p < 0.05, ** p < 0.01, *** p < 0.001 (two-tailed).

4.3.1. Common Method Bias

Considering that all the data were collected using the same approach at the same
time, the common method bias might be a problem and may affect the validity of the
research [91]. To check for the problem of possible common method bias, we conducted
Harman’s single factor test and the result showed that the maximum variance explained
by any single factor in this study was 26.37%, which is less than the threshold value [91].
In addition, following the procedures recommended by Podsakoff et al. [91], we put a
common method factor into the CFA model and the result showed that the CFI changed
from 0.948 to 0.950, TLI changed from 0.939 to 0.942 and RMSEA changed from 0.055 to
0.053, which indicated that the fitting indices of the new model did not improve a lot. Thus,
the common method bias does not seem to be a major problem in this study. We also
calculated VIF (variance inflation factor) to check the potential problem of multicollinearity,
and none of the VIFs was greater than 5, indicating that multicollinearity is not a major
problem in this study.

4.3.2. Validity Test

Confirmatory factor analysis (CFA) was used to assess the convergent validity and
discriminant validity. AMOS 23.0 was first used to test whether the six-factor model is a
good fit with our data. The results show that, compared with all the alternative models
shown in Table 4, the six-factor model is the best fit with the data, which supports the
proposed research model for analysis in this study (please see Table 4). The criteria for
convergent validity require the AVE (Average Variance Extracted) to be greater than 0.5,
standardized factor loading of all items not less than 0.5, and composite reliability (CR) not
J. Theor. Appl. Electron. Commer. Res. 2023, 18 246

less than 0.7. The AVE values of all concepts in this study are above 0.5, all standardized
factor loadings are above 0.60, and the CR are all above 0.7. The results thus support the
convergent validity (please see Table 5). The discriminant validity was measured using the
chi-square difference as recommended by Zait and Bertea [92]. First, we created a model
in which two constructs did not correlate and conducted CFA. Then, we created a model
in which two constructs correlated and performed the CFA. Finally, we performed the
chi-square difference tests. Based on the prescribed advice [92], if the result of the difference
test is significant (p < 0.05), then the two constructs have discriminant validity. Table 6
reports the results of these analyses, which indicates the measurement model has good
discriminant validity.

Table 4. Confirmatory factor analysis results.

Models NFI IFI TLI CFI 2/df RMSEA DF

One-factor model 0.812 0.850 0.835 0.849 4.189 0.091 252
Two-factor model A
0.818 0.856 0.841 0.855 4.070 0.090 251
(PP + SP + C+PI + E, PI)
Two-factor model B
0.827 0.866 0.852 0.865 3.860 0.086 251
(PP + SP, C + PC + E+PI)
Three-factor model A
0.832 0.871 0.856 0.870 3.772 0.085 249
(PP + SP, C + PC + E, PI)
Four-factor model A
0.844 0.881 0.865 0.881 3.723 0.084 224
(PP + SP, C, PC + E, PI)
Four-factor model B
0.835 0.873 0.857 0.872 3.771 0.085 246
(PP, SP, C + PC + E, PI)
Five-factor model A
0.891 0.945 0.937 0.945 2.211 0.056 242
(PP + SP, C, PC, E, PI)
Five-factor model B
0.845 0.883 0.866 0.883 3.584 0.082 242
(PP, SP, C, PC + E, PI)
Six-factor model 0.908 0.948 0.939 0.948 2.175 0.055 260
Notes: N = 384, PP = physical presence, SP = social presence, C = concentration, PC = perceived control,
E = Enjoyment, PI = purchase intention.

Table 5. Convergent validity results.

Variables and Measurement Items Standardized Loading CR AVE

Social Presence
SP1 0.750
SP3 0.750
SP4 0.702 0.834 0.503
SP5 0.669
SP6 0.669
Physical Presence
PP1 0.728
PP2 0.726
0.802 0.503
PP3 0.676
PP4 0.706
J. Theor. Appl. Electron. Commer. Res. 2023, 18 247

Table 5. Cont.

Variables and Measurement Items Standardized Loading CR AVE

Concentration
C1 0.774
C2 0.785
0.855 0.597
C3 0.794
C4 0.736
Perceived Control
PC1 0.800
PC2 0.622
0.811 0.521
PC3 0.813
PC4 0.630
Enjoyment
E1 0.788
E2 0.712
0.869 0.624
E3 0.825
E4 0.830
Purchase Intention
PI1 0.824
PI2 0.773 0.831 0.621
PI3 0.766
Notes: N = 384, PP = physical presence, SP = social presence, C = concentration, PC = perceived control,
E = enjoyment, PI = purchase intention.

Table 6. Discriminant validity results.

Relationship Model Chi-Square df. Probability Level c1 c2 df1 df2

Model 1 416.7 27 0.000
PP & SP 343.5 1
Model 2 73.2 26 0.000
Model 1 324.4 27 0.000
SP &C 251.8 1
Model 2 72.6 26 0.000
Model 1 382.7 27 0.000
SP & E 313.5 1
Model 2 69.2 26 0.000
Model 1 307.3 20 0.000
SP & PI 264.5 1
Model 2 42.8 19 0.000
Model 1 354.4 20 0.000
PP &C 298 1
Model 2 56.4 19 0.000
Model 1 304.1 20 0.000
PP & E 286.8 1
Model 2 17.3 19 0.000
Model 1 281.1 14 0.000
PP & PI 270.8 1
Model 2 10.3 13 0.000
Model 1 147.4 20 0.000
PP & PC 73.9 1
Model 2 73.5 19 0.000
Model 1 184 27 0.000
SP & PC 75.1 1
Model 2 108.9 26 0.000
J. Theor. Appl. Electron. Commer. Res. 2023, 18 248

Table 6. Cont.

Relationship Model Chi-Square df. Probability Level c1 c2 df1 df2

Model 2 108.9 26 0.000
Model 1 144.3 20 0.000
C & PC 56.9 1
Model 2 87.4 19 0.000
Model 1 153.8 20 0.000
E & PC 69.4 1
Model 2 84.4 19 0.000
Model 1 154.2 14 0.000
PC & PI 77.3 1
Model 2 76.9 13 0.000
Model 1 396.9 20 0.000
C&E 341.6 1
Model 2 55.3 19 0.000
Model 1 331.5 14 0.000
C & PI 287.2 1
Model 2 44.3 13 0.000
Model 1 371.7 14 0.000
E & PI 348.6 1
Model 2 23.1 13 0.000
Notes: N = 384, PP = physical presence, SP = social presence, C = concentration, PC = perceived control,
E = enjoyment, PI = purchase intention.

4.3.3. Hypothesis Test

SPSS Process was used to test the hypotheses, as shown in Table 7. The results show
that physical presence and social presence were positively related to concentration ( = 0.75,
p < 0.001; = 0.73, p < 0.001; Model 1 and Model 2 in Table 7), which supports H1a and
H1b. When physical presence and concentration were considered as independent variables
and perceived control as a dependent variable, physical presence and concentration were
positively related to perceived control ( = 0.24, p < 0.01; = 0.12, p < 0.05, respectively;
Model 3 in Table 7), which supported H2 and H4. The results also showed that both
social presence and concentration were positively related to enjoyment ( = 0.38, p < 0.001;
= 0.47, p < 0.001; Model 4 in Table 7), which supports H3 and H5. Moreover, the results
also indicated that concentration, perceived control, and enjoyment were all positively
related to consumers’ purchase intentions as predicted (Model 5, Model 6, and Model 7 in
Table 7), which supports H6, H7, and H8.

Table 7. Results of regression analyses.

Variables Concentration Perceived Control Enjoyment Purchase Intention

Model 1 Model 2 Model 3 Model 4 Model 5 Model 6 Model 7
Gender 0.15 * 0.16 * 0.04 0.19 * 0.20 * 0.13 * 0.10
Age 0.00 0.02 0.05 0.01 0.07 0.08 0.08
Education Level 0.07 0.01 0.03 0.01 0.06 0.03 0.05
Physical Presence 0.75 *** 0.24 ** 0.34 ***
Social Presence 0.73 *** 0.38 *** 0.25 **
Concentration 0.12 * 0.47 *** 0.44 *** 0.30 *** 0.29 ***
Perceived Control 0.12 * 0.11 *
Enjoyment 0.36 *** 0.38 ***
Notes: N = 384, * p < 0.05, ** p < 0.01, *** p < 0.001 (two-tailed).

The SPSS Process Model 6 [93] was then used with bootstrapping to analyze the
mediating effects of concentration, perceived control, and enjoyment on the impact of
J. Theor. Appl. Electron. Commer. Res. 2023, 18 249

presence on consumers’ purchase intentions. We first tested the mediating effects of

concentration and perceived control on the relationship between physical presence and
purchase intentions (gender, age and education as control variables). The bootstrapping
results indicate that the indirect effect of concentration as a mediating variable is 0.33
JTAER 2023, 18, FOR PEER REVIEW 13
(95% CI = [0.2450, 0.4161]). The indirect effect of perceived control as a mediating variable
is 0.03 (95% CI = [0.0054, 0.0616]). The indirect effect of concentration and perceived control
together as mediating variables is 0.01 (95% CI = [0.0001, 0.0307]). All the indirect effects
Table 7. Results of regression analyses.
add up to 0.36 (95% CI = [0.2825, 0.4518]). Therefore, the proposed chain mediating effects
of concentration and perceived Concentration Perceived between physical presence and
control on the relationship
Variables Enjoyment Purchase Intention
Control
consumers’ purchase intentions are supported (please see Table 8).
Model 1 Model 2 Model 3 Model 4 Model 5 Model 6 Model 7
Gender 0.15 * 0.16 * 0.04 0.19 * 0.20 * 0.13 * 0.10
Table 8. Results on Indirect effect for different paths.
Age −0.00 0.02 0.05 0.01 0.07 0.08 0.08
Path Education a Indirect Effect 95% Confidence Interval
0.07 b
0.01 −0.03 −0.01 0.06 0.03 0.05
Level
PP!C!PI 0.75 0.44 0.33 (0.2450, 0.4161)
Physical
0.75 *** 0.24 ** 0.34 ***
PP!PC!PI 0.24
Presence 0.11 0.03 (0.0054, 0.0616)
PP!C!PC!PI Social 0.73 *** 0.01 0.38 *** (0.0001, 0.0307)
0.25 **
Presence
SP!C!PI 0.73 0.30 0.22 (0.1341, 0.3148)
Concentration 0.12 * 0.47 *** 0.44 *** 0.30 *** 0.29 ***
SP!E!PI 0.38
Perceived 0.36 0.14 (0.0872, 0.1959)
0.12 * 0.11 *
SP!C!E!PI Control 0.12 (0.0817, 0.1753)
Notes: N = 384, PP = Enjoyment 0.36 ***control,
physical presence, SP = social presence, C = concentration, PC = perceived 0.38 ***
E = enjoyment, PI = purchase
Notes: Nintention, = the**regression
= 384, * p <a0.05, coefficient
p < 0.01, *** p < 0.001 of the mediator variable with the antecedent
(two‐tailed).
variable, b = the regression coefficient of the criterion variable with the mediator variable.
Table 8. Results on Indirect effect for different paths.

We then tested thePathmediating effects

βa of concentration
βb Indirectand enjoyment
Effect on the relation-
95% Confidence Interval
ship between social presence
PP→C→PIand purchase 0.75 intentions
0.44 (gender,
0.33 age, and education (0.2450, as control
0.4161)
variables). The bootstrapping
PP→PC→PI results 0.24indicate that the indirect
0.11 0.03 effect of concentration
(0.0054, 0.0616) as
a mediating variable is 0.22 (95% CI = [0.1341, 0.3148]). 0.01
PP→C→PC→PI The indirect effect of enjoyment
(0.0001, 0.0307)
as a mediating variable
SP→C→PIis 0.14 (95%0.73CI = [0.0872,
0.30 0.1959]). 0.22The indirect effect (0.1341,of concen-
0.3148)
tration and enjoyment together as mediating
SP→E→PI 0.38 variables is0.14
0.36 0.12 (95% CI = [0.0817, 0.1753]).
(0.0872, 0.1959)
All the indirect effects add up to 0.48 (95% CI = [0.3924,0.12
SP→C→E→PI 0.5743]). Hence, the proposed
(0.0817, 0.1753)
Notes: N = 384, PP = physical presence, SP = social presence, C = concentration, PC = perceived con‐
chain mediating effects of concentration and enjoyment on the relationship between social
trol, E = enjoyment, PI = purchase intention, βa = the regression coefficient of the mediator variable
presence and consumers’ purchase
with the antecedent intentions
variable, βb = theare also supported
regression coefficient of (please seevariable
the criterion Table with
8). The
the medi‐
final model is shown in Figure 2.
ator variable.

Figure 2. Regression results on presence and purchase intention in livestream shopping. * p < 0.05,
Figure 2. Regression results on presence and purchase intention in livestream shopping. * p < 0.05,
** p < 0.01, *** p < 0.001 (two‐tailed).
** p < 0.01, *** p < 0.001 (two-tailed).
J. Theor. Appl. Electron. Commer. Res. 2023, 18 250

5. Discussion and Implications

This study is to use the flow theory to explore the impact of feeling of presence on
consumers’ purchase intentions in livestream shopping. The flow-based research model
provides an integrated picture on the effects of presence on consumers’ purchase intentions,
and further on the role of flow experience in the relationship between presence and purchase
intentions. The empirical results reveal different mechanisms through which physical
presence and social presence motivate consumers to indulge in livestream shopping and
make decisions to purchase.
More specifically, our study shows that both dimensions of presence have positive
impacts on consumers’ purchase intentions in livestream shopping. The results show
that social presence has a positive effect on consumers’ purchase intention, similar to the
findings in previous studies [16,94]. In addition, our study shows that physical presence
also has a positive impact on consumers’ purchase intentions with concentration as a
mediator, confirming the important role of physical presence in livestream shopping and is
consistent with Pelet’s [46] research findings on flow experiences in social media context.
In addition, this study shows that physical presence and social presence affect con-
sumers’ purchase intentions through different mechanisms. Physical presence positively
affects consumers’ purchase intention through concentration and perceived control while
social presence helps improve consumers’ purchase intention through concentration and
enjoyment. Therefore, this flow-based model provides a clearer picture on the relationship
between presence and consumers’ purchase behaviors in livestream shopping.

5.1. Theoretical Implications

This study can help enrich marketing research in particular online marketing in the age
of digitalization when more marketers and consumers have relied on mediated environment
to sell and buy products. First, this study develops an integrated model that incorporates
the feeling of presence and the flow theory to explore the dynamic process of livestream
shopping. While livestream shopping is fast emerging, relatively few studies have provided
an integrated model to examine the underlying reasons why consumers are so obsessed
with this form of shopping activities [7,8,35]. This study contends that the feeling of
presence can help consumers gain the flow experiences wherein consumers are so absorbed
in the virtual environment that concentration and perceived control as well as enjoyment are
generated, which then drives consumers to make purchase decisions, a flow-based process
on consumers’ experiences in livestream shopping. The empirical data collected from
Chinese consumers in livestream shopping substantiated the proposed research model.
As a result, this study can advance the literature on consumers’ purchase intention in
livestream shopping and consumer behaviors in general with a more robust theory. Second,
our study shows that both dimensions of presence including social presence and physical
presence positively affect consumers’ purchase intentions. While existing research has
proved that social presence has an impact on consumers’ purchase intentions [16,17,35], few
studies have examined the effect of physical presence on consumers’ purchase intentions [7],
not to mention in the context of livestream shopping. This study shows physical presence
is also positively related to consumers’ purchase intention, but with a different path.
Thus, this study sheds new lights on presence and its impact on consumer behaviors in
interactive marketing.
Third, this study examines the mediating roles of all three dimensions of flow ex-
perience including concentration, perceived control, and enjoyment in the relationship
between presence and consumers’ purchase intention. The proposed research model helps
debunk the black box on how presence affects purchase intentions [7,13,95]. Although
some studies on livestream shopping have suggested that flow plays an important role in
consumers’ purchase intentions [7], these studies only treated flow as a general variable
while ignoring that it is a multi-dimensional construct with each dimension playing dif-
ferent roles. Based on the research of Koufaris [39], this study divides the flow into three
dimensions—concentration, perceived control, and enjoyment, and then investigates their
J. Theor. Appl. Electron. Commer. Res. 2023, 18 251

unique mediating effects on presence and consumers’ purchase intention in the context of
livestream shopping. This study thus bridges the gap in existing literature on livestream
shopping and enhances our understanding of the role of flow in this dynamic process.
Moreover, previous studies often apply the flow theory to online gaming [96–98], online
shopping [99,100], and website design [29,30,101]. Few have used this theory to examine
livestream shopping. This study incorporates the feeling of presence and the flow theory
to explore livestream shopping for a better understanding of consumer behaviors in a
mediated environment, and thus helps broaden the research horizon for flow theory and
presence in virtual communities.

5.2. Practical Implications

This study also has important practical implications on how to engage consumers and
to increase their purchase intention in the increasingly digitalized consumer market, espe-
cially when the COVID-19 pandemic has driven more consumers to rely on enriched online
experiences to make shopping decisions. The findings of this study point to a new market-
ing strategy where consumers’ participation can be encouraged by improving the feeling of
presence in order to retain and develop customer base. First, a mediated environment that
conveys enough information with real-time updates and social elements in the interactions
can greatly increase the feeling of physical presence [47,102,103]. When consumers are
actively involved in such a virtual world, physical presence is likely to be generated [47,102].
Therefore, livestream marketers can engage consumers by constantly showing products in
front of live cameras and by describing products in meticulous detail to attract consumers.
In addition, physical presence can also be enhanced by representational fidelity in the vir-
tual world, such as realistic display of the environment and smooth change of views [104].
The livestream studio can be so arranged to resemble the layouts of offline stores to make
consumers feel like they are offline shopping, a perceptual illusion, which can generate
more feelings of physical presence. Social presence is the feeling of being with others in a
virtual environment which requires psychological participation including intimacy and
immediacy. Intimacy and immediacy can be enhanced by continuous interactions and
quality communications [95,105]. As a result, livestream anchors can encourage consumers
to ask questions and also respond to their questions in a timely manner so as to shorten the
psychological distance with consumers and enhance interactions with them.
Second, this study discovers that flow experiences mediate the relationship between
presence and consumers’ purchase intentions. Since concentration is one of the most
important dimensions of flow, livestream anchors can improve consumers’ concentration
by holding unscheduled flash sales or other events in the process of livestream to attract
consumers’ attention. Moreover, marketers or livestream anchors can improve consumers’
perceived control by fast response to consumers’ questions to make consumers feel valued
or increase consumers’ enjoyment by providing a happy hour such as lucky draws or
handing out red envelopes from time to time. The key to the flow-based marketing strategy
in the virtual world is to actively engage consumers to improve their feelings of presence
so that they could develop flow experiences to concentrate, form a sense of control, and
further enjoy these activities and then make purchase decisions.

5.3. Limitations and Future Research Directions

This study is exploratory and thus has its limitations and caution needs to be excised in
generalizing the findings. First, the sample used in this study is not a random sample. We
can only analyze the data from the people who responded to our survey and, consequently,
it is possible that the people who chose to complete the survey are different from those who
did not respond to the survey, a self-selection bias. The sample size is also small compared
with the large number of livestream users in China. Future research should use a random-
ized sample and also a larger sample to increase the generalizability. Second, this study
only surveyed Chinese consumers, while livestream shopping has become popular in many
other countries. Future research could replicate this study and test the proposed model
J. Theor. Appl. Electron. Commer. Res. 2023, 18 252

with data from consumers in other countries to investigate its applicability in other cultural
contexts. For example, previous research using European consumers has explored the
effects of influencer endorsement on consumer engagement and online store performance
and its results show that influencer endorsement negatively moderates the effects of con-
sumer engagement [8]. This is very interesting, as livestream shopping in China often uses
influencer endorsement to promote products and has achieved tremendous positive impact.
In fact, many livestream anchors are themselves influencers. Future research should explore
this intriguing difference. Third, livestream shopping is just one of the many forms of
livestream activities and livestream activities include livestream games, livestream concerts,
livestream tourism, and other cyberspace activities. More research is encouraged to explore
the impact of presence and flow experiences on participants’ motivation and behaviors in
other forms of livestream. In addition, the study lacks the consideration of moderating
variables. Because we focus on the mediating effects of the flow state on the relationships
between physical and social presence and purchase intentions, we did not specify boundary
conditions. Future research should consider possible moderating variables to examine
boundary conditions in this dynamic process for a more nuanced understanding.

Author Contributions: Conceptualization, J.Y. and Z.M.; methodology, J.Y.; software, J.Y., Y.H. and
Z.M.; validation, J.Y.; formal analysis, Y.H.; resources, J.Y.; data curation, J.Y. and Y.H.; writing—
original draft, Y.H.; writing—review and editing, Z.M.; supervision, J.Y.; project administration, Z.M.
All authors have read and agreed to the published version of the manuscript.
Funding: This research was supported by the Beijing Knowledge Management Institute (5212210983).
Institutional Review Board Statement: Not applicable.
Informed Consent Statement: Not applicable.
Data Availability Statement: Data available upon request from the first author.
Conflicts of Interest: The authors declare no conflict of interest.

Appendix A
Variables Items Sources
When shopping in live streaming, I felt as if I was shopping in a
brick-and-mortar store Barfield, W., Zeltzer, D., Sheridan,
While I was shopping in live streaming, I felt as if I were in a T.B., and Slater, M., Presence and
real world created by the live streaming performance within virtual
Physical Presence environments. In Barfield, W.,
When shopping in live streaming, although my body was in the
and Furness III, T.A. (eds.) Virtual
room, I felt that my mind was inside the world created by
Environments and Advanced
live streaming.
Interface Design, 1995, Oxford,
While I was shopping in live streaming, I felt the products Oxford University Press. [33]
presented by the anchor were right in front of me.
I felt a sense of sociability when shopping in live streaming.
I felt a sense of human warmth when shopping in live streaming.
Gunawardena, C. N., and Zittle, F.
I felt a sense of human contact when shopping in live streaming. J., Social presence as a predictor of
I was aware of the presence of anchor and other consumers satisfaction within a
Social Presence computer-mediated conferencing
when shopping in live streaming.
environment. American Journal of
The anchor and other consumers were aware of the presence of Distance Education, 1997, 11(3),
me when shopping in live streaming. 8–26. [89]
I was able to communicate with anchor and other consumers
when shopping in live streaming.
J. Theor. Appl. Electron. Commer. Res. 2023, 18 253

Variables Items Sources

When shopping in live streaming, I was absorbed intensely in
the activity.
When shopping in live streaming, my attention was focused on
the activity.
Concentration
When shopping in live streaming, I concentrated fully on
the activity.
When shopping in live streaming, I was deeply engrossed in Koufaris, M., Applying the
the activity. technology acceptance model and
Flow When shopping in live streaming, I felt confused. flow theory to online consumer
behavior. Information Systems
Perceived When shopping in live streaming, I felt calm.
Research, 2002, 13(2), 205–223. [39]
Control When shopping in live streaming, I felt in control.
When shopping in live streaming, I felt frustrated. SCIE
When shopping in live streaming, I found it interesting.
When shopping in live streaming, I found it enjoyable.
Enjoyment
When shopping in live streaming, I found it exciting.
When shopping in live streaming, I found it funny.
I will likely buy the products recommended in the live Dodds, W. B., Monroe, K. B., and
streaming shopping. Grewal, D., Effects of price, brand,
Purchase and store information on buyers’
I would recommend live streaming shopping to my friends.
Intention product evaluations. Journal of
I would prefer to use the products recommended in the live Marketing Research, 1991, 28(3),
streaming shopping. 307–319. [90]

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