International Journal of Sustainable Development and

Planning
Vol. 17, No. 8, December, 2022, pp. 2631-2639
Journal homepage: http://iieta.org/journals/ijsdp

Live Shopping Interactivity, Social Presence and Sustainable Consumer Purchase Intention:
Based on TAM Model
Chao Xu1, Zhongwu Li1*, Jiafu Su2
1
National Institute of Development Administration, International College, Bangkok 10240, Thailand
2
International College, Krirk University, Bangkok 10220, Thailand

Corresponding Author Email: zhongwu.li@nida.ac.th

https://doi.org/10.18280/ijsdp.170832 ABSTRACT

Received: 10 October 2022 E-commerce platforms are in the development trend of differentiation and vertical
Accepted: 11 December 2022 segmentation, and quality content output will become the core competitiveness of new e-
commerce platforms. This study investigated data from 226 consumers of the Taobao live
Keywords: streaming shopping platform. This study incorporates the Technology Acceptance Model
live streaming shopping, social presence, (TAM) with Social Presence Theory to investigate the experiential factors and system
technology acceptance model, sustainable characteristics that psychologically influence users' behavioral intentions. The empirical
purchase intention results show that interactivity has a significant positive effect on purchase intention, and social
presence, perceived ease of use and perceived usefulness play a mediating role in the process
of interactivity affecting purchase intention. This research can help enterprises and merchants
innovate system features and improve the user experience for their customers.

1. INTRODUCTION behavior and can reflect the consumer's own behavioral

tendencies more clearly. To this end, this study proposes a
Live streaming shopping brings the upgrade of the shopping theoretical model that can more effectively measure the factors
scene, from the traditional e-commerce offers text and pictures, that influence consumers' purchase intention in live streaming
to today's new live streaming shopping with real-time video shopping. In addition, the study aims to explain the impact of
display and interaction, consumers' shopping needs continue the features of live streaming shopping on consumer
to improve. Live streaming shopping to a certain extent to experience and purchase intentions, and to provide useful
make up for the shortcomings of the lack of realism in the suggestions for anchors and merchants in online marketing to
virtual shopping scene, to create a "buy while you watch" improve consumers' purchase intentions in live streaming
shopping experience for consumers. The interactivity of live shopping.
streaming shopping allows consumers to simulate to "feel,
touch and use" the product, thus making the product display
more realistic, just like in a physical shopping environment, 2. LITERATURE REVIEW AND RESEARCH
users can enhance consumers' perception of the product by HYPOTHESIS
understanding the details of the product through the anchor [1].
Live streaming shopping makes the offline real economy no 2.1 Relationship between interactivity, perceived ease of
longer bound to stores, regions and distances, and breaks the use, perceived usefulness, social presence, and purchase
traditional "transmission-reception" propagation mode, intention
stimulating the audience with rich emotions in the propagation
process so as to achieve the propagation effect [2]. Good Interaction is very effective for the transmission of
interactivity leads to a certain level of cognitive immersion, information, so that consumers do not have to spend too much
which enhances consumers' shopping enjoyment and overall effort to understand the information transmitted by the anchor,
attitude and involvement in the online store, thus helping to which improves the effectiveness of communication, reduces
increase consumers' purchase intentions [3]. On the one hand, the communication barriers brought about by the different
the live streaming scene penetrates upstream of the industry knowledge backgrounds of communication subjects, and
chain, such as live streaming of origin and factory, to shorten makes it easier for consumers to understand and master live
the industrial chain and improve industrial efficiency; on the streaming shopping [4]. Cyr et al. [5] also found that for most
other hand, it penetrates into the offline retail industry, such as consumers, the ability to get a better sense of interactivity is
live streaming of shopping areas and stalls, to promote online associated with higher ratings of features such as ease of use
and offline integration and accelerate the pace of digital of the website. Islam et al. [6] found that high levels of
transformation of the offline retail industry. interaction positively influenced consumer perceptions and
As the final psychological decision before the consumer's that the virtual shopping environment was more useful, easier
purchase behavior, the consumer's purchase intention is to use, and enjoyable. Therefore, the following hypothesis is
crucial for the consumer itself, which is an extension of the proposed:

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 H1: Interactivity has a positive impact on perceived ease of acceptance model, where perceived ease of use influences
use in live streaming shopping. perceived usefulness [17], and both perceived usefulness and
In the live streaming shopping scenario, anchors provide perceived ease of use influence intention to use through
timely feedback and targeted answers based on users' attitudes in the technology acceptance model [18]. Convenient
questions, and users share product details and usage plays an important role in helping to achieve marketing goals,
experiences through comments among themselves, and the and Internet experience and Convenient are drivers of Internet
effective information interaction among them promotes the use [19, 20]. Technology acceptance pioneers who maintain a
sharing of product knowledge and information [7], reduces positive attitude towards new technologies and services are
users' anxiety about product uncertainty, and enhances users' more like pragmatists, people tend to focus more on ease of
perception of the usefulness of live streaming shopping [8]. use [21] and users are more likely to shift their goals when the
Zhou et al. [9] also found that effective interaction between content and functionality are too complex [22]. Therefore, the
users and anchors not only increases consumers' interest in following hypothesis is proposed:
shopping, but also satisfies consumers' sense of involvement, H5: Perceived ease of use has a positive impact on the
and the pleasant experience obtained through interaction helps perceived usefulness of live streaming shopping.
to maintain a good relationship between anchors and H6: Perceived ease of use has a positive effect on purchase
consumers and form perceived usefulness of consumers. For intention for live streaming shopping.
most consumers, a better sense of interactivity will increase H7: Perceived ease of use mediates the effect of interactivity
consumers' evaluation of the usefulness and ease of use of the on purchase intention.
website [10], which will also lead to consumer loyalty to the When customers visit a website, the information, pictures,
website. Therefore, the following hypothesis is proposed: videos, website helpers, online reviews or online customer
H2: Interactivity has a positive effect on perceived service, etc., all trigger different levels of social presence. If
usefulness in live streaming shopping. consumers can experience a high-quality website presence and
At the level of interpersonal interactions, social presence is feel relaxed, easy, free or stress-free when browsing products,
described as a warm sense of socialization that the medium this will inevitably make consumers feel that the website is
brings to the user [11], i.e., a psychological perception that the real and useful [11]. Consumers' perceptions of shopping
user interacts with others in the virtual space and perceives the websites are no longer limited to time and cost savings; their
presence of others. In the bidirectional interaction scenario of needs have increased to the level of social presence such as
live streaming shopping, anchors can display products in friendliness, sensitivity, friendliness, and sociability. The
multi-dimensional and multi-angle, and exchange product ability to make consumers perceive a shopping website not
information with users to create a face-to-face shopping only as an emotionless computer system but also as a sentient
scenario, allowing users to experience the reality of being and independent individual can greatly influence consumers'
there, seeing is believing, which can gradually instill a sense purchase intentions [23]. Fan et al. [24] point out that social
of warmth and socialization between people and create a presence makes users of live streaming rooms feel connected
strong atmosphere of social presence [12], giving users a good to others, satisfies their need for social interaction, and gives
immersive experience [13]. It can also create an "immersive" them a satisfying live streaming viewing experience, which in
shopping situation and a unique "virtual touch" perception [9]. turn promotes their willingness to continue using it. Ou et al.
Ou et al. [14] also found that interactions promote social [14] found that interactions promote social presence and to
presence and to some extent influence consumer trust building some extent influence consumer trust building and repeat
and repeat transaction forming. Therefore, the following transaction formation. Therefore, the following hypothesis is
hypothesis is proposed: proposed:
H3: Interactivity has a positive impact on social presence H8: Social presence has a positive effect on the perceived
in live streaming shopping. usefulness of live streaming shopping.
The instant interaction through pop-up information during H9: Social presence has a positive effect on purchase
the live broadcast provides a channel for the anchor to intention for live streaming shopping.
understand users' consumption needs, and the anchor H10: Social presence mediates the effect of interactivity on
consciously adjusts the recommended products to meet their purchase intention.
consumption needs according to the users' demands. Users can Live streaming shopping offers consumers a wealth of
also send pop-ups to communicate with other users to ask product information, competitive product prices, a large
questions or express their opinions about the product. The variety of products, and flexible shopping options. All features
bidirectional information exchange between users and anchors that increase the benefits or reduce the costs of shopping for
and between users and users is not bound by time and space, consumers are relative advantages offered by online shopping,
which can arouse users' desire to participate [15]. Online which can make consumers perceive the usefulness of live
shopping is a social process. During the interaction, users can streaming shopping and thus increase their intention to shop
obtain information, experience and advice from others to online [25]. The perceived usefulness of live streaming
complete their shopping decisions, which stimulates shopping emphasizes the shopping experience of consumers
consumers' purchase intentions and triggers their purchase in the shopping process and the results of accomplishing
behavior [16]. Therefore, the following hypothesis is proposed: shopping goals, and the perceived Convenient of live
H4: Interactivity has a positive impact on purchase streaming shopping places more emphasis on the shopping
intention in live streaming shopping. process of achieving shopping goals, i.e., the ease of use of
The shopping site itself is a form of information technology, live streaming shopping. The easier consumers perceive the
and for consumers who visit online stores, their perception of operation of online shopping, the more likely they are to have
the system determines their willingness to try out this new way the intention to shop [26]. Also, the stronger the consumers'
of shopping. The cognitive factors of both perceived ease of perception of ease of use of online shopping, the more their
use and perceived usefulness are derived from the technology perception of usefulness of online shopping increases [27].

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Therefore, the following hypothesis is proposed: In addition, social presence was measured in the study by
H11: Perceived usefulness has a positive effect on purchase Algharabat et al. [30] to determine the psychological
intention for live streaming shopping. experience of users. Four purchase intention question items
H12: Perceived usefulness mediates the effect of vividness from Ventre and Kolbe [31] were used. All of the established
on purchase intention. scales from previous studies were used in this study. In this
paper, all question items were measured using the Likert five-
2.2 Research model level scale.

Based on the above literature review and hypotheses, the 3.2 Data collection and analysis
following theoretical model was constructed in this study. As
shown in the Figure 1 below, interactivity is the variable of In this study, the purchase intention of live streaming
external stimuli. The model is used to test the mediating effects shopping consumers is studied by users who have used live
of perceived usefulness, perceived ease of use, and social streaming shopping.Convenient sampling was used in this
presence. In addition, the model identifies the relationship study and non-probability sampling method is the most
between perceived ease of use, perceived usefulness, and commonly used method because it is less costly than
social presence. probability sampling and saves time in implementation [32].
Electronic questionnaires are a common questionnaire survey
method [33], and online questionnaires can improve the speed
of questionnaire survey and get the questionnaires to the
respondents in a short period of time. In this study, social
media such as WeChat, QQ and email were used to distribute
and collect electronic questionnaires from consumers who use
live streaming shopping.
To effectively measure the model and identify relationships
between variables, Amos 24.0 software was used to analyze
the data and help draw conclusions from the study. Structural
Figure 1.Conceptual framework of this study equation modeling (SEM) is a statistical data analysis tool that
combines multiple regression analysis, path analysis, and
confirmatory factor analysis methods and can be used to
3. RESEARCH METHODOLOGY explain the relationship between one or more independent
variables and one or more dependent variables [34]. SEM is a
3.1 Questionnaire powerful and important research method [35], which can
ensure the quality of research results. Therefore, SEM is used
This study reviewed previous studies and developed a in order to analyze data information and to determine research
questionnaire on consumers' purchase intention in live results.
streaming shopping. Five interactive question items from Le
et al. [28] were used to represent the characteristic factors of
live streaming shopping. The items of perceived ease of use 4. RESEARCH RESULTS
and perceived usefulness were adapted from Vahdat et al. [29].

Table 1. Reliability analysis

Title Corrected term to total Cronbach's Alpha after Cronbach's Total Cronbach's
Dimensions
items correlations deleting items Alpha Alpha
I1 .674 .873
I2 .795 .846
I I3 .703 .866 .886
I4 .726 .861
I5 .728 .860
PEU1 .711 .807
PEU2 .716 .806
PEU .854
PEU3 .652 .832
PEU4 .706 .810
PU1 .715 .864
PU2 .705 .869 .934
PU .884
PU3 .835 .817
PU4 .743 .853
SP1 .671 .834
SP2 .700 .822
SP .859
SP3 .782 .789
SP4 .666 .835
PI1 .751 .864
PI2 .790 .850
PI .892
PI3 .736 .870
PI4 .782 .856
Note: I is Interactivity, PEU is Perceived Ease of Use, PU is Perceived Usefulness, SP is Social Presence, and PI is Purchase Intention.

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 Table 2. Structural validity analysis

Components
1 2 3 4 5
I1 0.671
I2 0.826
I3 0.769
I4 0.793
I5 0.740
PEU1 0.773
PEU2 0.811
PEU3 0.700
PEU4 0.834
PU1 0.739
PU2 0.722
PU3 0.810
PU4 0.794
SP1 0.729
SP2 0.770
SP3 0.838
SP4 0.758
PI1 0.725
PI2 0.764
PI3 0.739
PI4 0.712
total 9.176 2.013 1.673 1.302 1.088
Cumulative % 16.428 30.809 44.898 58.960 72.627
KOM 0.929
Bartlett’s Test 2913.023 (p=0.000)
Note: I is Interactivity, PEU is Perceived Ease of Use, PU is Perceived Usefulness, SP is Social Presence, and PI is Purchase Intention.

Table 3. Model fit indices

Parameters CMIN/DF RMR GFI AGFI NFI TLI CFI RMSEA

Estimated values 1.183 0.038 0.919 0.896 0.930 0.986 0.988 0.028
Reference values <3 <0.05 >0.8 >0.8 >0.9 >0.9 >0.9 <3

In this study, the reliability and validity of the recovered test; it can also be seen that the approximate chi-square value
samples were analyzed using SPSS24.0 software. Then, obtained by Bartlett's test is 2913.023, and the Bartlett's test
AMOS24.0 was used to construct a structural SEM to test the significance sig<0.001, which rejects the original hypothesis.
relationship between variables and verify the hypotheses. It indicates that it is suitable for factor extraction. In this study,
Finally, the reasons affecting the relationship between factors with eigenvalues greater than 1 were extracted using
variables were revealed and the results were analyzed to find Principal Component Analysis(PCA), 5 common factors were
a scientific solution. extracted, and the Cumulative rotated square sum was
72.627%, which was greater than 60%. After rotation by
4.1 Reliability and validity orthogonal rotational method, the 21 question options can be
divided into 5 categories of factors, and the loading of each
As shown in Table 1, the Cronbach's α coefficients under item is greater than 0.5, which indicates that each measured
different dimensions were all above 0.8, indicating good variable can effectively reflect the factor construction. Based
dimensional reliability results. Among them, the correlations on this analysis, it indicates that the questionnaire designed in
between the corrected terms of the question items and the total this study has good structural validity.
are all greater than 0.6, indicating that there is a correlation As shown in Table 3, the ratio of chi-square values to
between the question items. Based on this analysis, it indicates degrees of freedom was 1.183, indicating a good model fit.
that the reliability of the questionnaire is good. GFI = 0.885, AGFI = 0.860, NFI = 0.888, TLI = 0.940, CFI =
As shown in Table 2, Different questionnaire items 0.946, and RMSEA = 0.051, indicating a good model fit.
belonging to the same concept are clustered in the same Based on this analysis, it indicates that all the indicators of the
common factor as predicted by the theory. The variance of the exploratory factor analysis in this study met the criteria and the
6 common factors is all greater than 0.4, and the concepts are overall model fit was good.
clearly delimited. Factor loads for all measured items were In order to further verify the rationality of dimensions, it is
between 0.5 and 0.95, indicating that each measured variable necessary to test the measurement model before evaluating
could effectively reflect factor construction. To sum up, the and verifying the structural model in the SEM operation
questionnaire designed in this study has good structural process, so as to ensure whether all items in the measurement
validity. model can accurately reflect the required factors. As shown in
As shown in Table 3, the Kaiser-Meyer Olkin measure is the Figure 2 below, All factor loads were greater than 0.6, and
0.929, which is already much greater than 0.7, and can prove SMC was greater than 0.36
that there is a strong correlation between the questions in the

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 Figure 2. Validation factor analysis

Table 4. Results of validation factor analysis

Dimensions items Unstd. S.E. t-value P Std. SMC CR AVR

I I1 1.000 .718 .516 .887 .613
I2 1.116 .092 12.125 *** .866 .750
I3 1.028 .096 10.740 *** .758 .575
I4 1.066 .096 11.122 *** .786 .618
I5 1.108 .101 11.008 *** .778 .605
PEU PEU1 1.000 .786 .618 .854 .595
PEU2 1.084 .092 11.776 *** .803 .645
PEU3 .864 .082 10.483 *** .713 .508
PEU4 .974 .085 11.503 *** .781 .610
PU PU1 1.000 .761 .579 .887 .664
PU2 1.072 .091 11.734 *** .764 .584
PU3 1.219 .087 14.000 *** .922 .850
PU4 1.012 .082 12.409 *** .802 .643
SP SP1 1.000 .734 .539 .861 .610
SP2 1.049 .096 10.906 *** .768 .590
SP3 1.127 .094 12.031 *** .880 .774
SP4 .976 .094 10.420 *** .733 .537
PI PI1 1.000 .810 .656 .894 .678
PI2 1.036 .073 14.214 *** .855 .731
PI3 .913 .071 12.832 *** .786 .618
PI4 1.194 .086 13.961 *** .841 .707
Note: I is interactivity, PEU is perceived ease of use, PU is perceived usefulness, and SP is social presence proximity. *** means P < 0.001

As shown in Table 4, the standardized factor loadings for convergent validity.

each item in the questionnaire were greater than 0.6, indicating AVE is used to measure the convergent validity and
that the question item had good explanatory power for the discriminant validity of the latent variables, reflecting the
dimension in which it was included. The component reliability changes in the latent variables due to errors and revealing the
(CR) was all greater than the criterion of 0.7, indicating that explanatory power of the questionnaire items on the variables
the items included in each dimension explained the latent [36]. The larger the AVE, the smaller the measurement error.
variables well. The AVE values of each dimension were all As shown in Table 5, the AVE values of each dimension are
greater than 0.5, p<0.001, which met the reference values for greater than 0.5, and the square root of AVE is greater than the
validity evaluation. Based on this analysis, it showed that the correlation coefficient between the dimensions, based on this
five latent variables had significant relationships with each analysis, it indicates that the scale has good discriminant
measured question item, indicating that the scale had good validity.

2635
 Table 5. Discriminant validity analysis table as mediator, and purchase intention (PI) as the dependent
variable, a structural equation model was developed using
AVE PI SP PU PEU I AMOS 24.0 software (Figure 3).
PI .678 .823 As shown in Table 6, if the p is less than 0.05, the hypothesis
SP .610 .627 .781 is valid; however, if it is greater than 0.05, the hypothesis is
PU .664 .709 .566 .815 not supported. Interactivity has a significant positive effect on
PEU .595 .597 .353 .546 .771
perceived ease of use, perceived usefulness, social presence,
I .613 .629 .551 .560 .474 .783
Note: I is Interactivity, PEU is Perceived Ease of Use, PU is Perceived
and purchase intention. Observing the path coefficients of each
Usefulness, SP is Social Presence, and PI is Purchase Intention. path, the path coefficient of interactivity to social presence
reached 0.56, indicating that interactivity has a strong
4.2 Structural equation influence on social presence. In addition, on the influence of
perceived usefulness, social presence is stronger than
Based on the conceptual framework (Figure 1) with perceived ease of use and interactivity; perceived usefulness
interactivity (I) as the independent variable, perceived ease of has the strongest influence on purchase intention, and social
use (PEU), perceived usefulness (PU) and social presence (SP) presence also has a strong influence on purchase intention.

Figure 3. Structural equation model

Table 6. Path coefficients between latent variables

Estimate S.E. C.R. P Std. Results

PEU <--- I 0.432 0.069 6.235 *** 0.481 Supported
SP <--- I 0.45 0.064 7.011 *** 0.556 Supported
PU <--- I 0.186 0.07 2.665 0.008 0.223 Supported
PU <--- PEU 0.306 0.068 4.475 *** 0.33 Supported
PU <--- SP 0.344 0.081 4.261 *** 0.334 Supported
PI <--- PU 0.33 0.079 4.193 *** 0.328 Supported
PI <--- SP 0.263 0.075 3.509 *** 0.254 Supported
PI <--- PEU 0.227 0.064 3.535 *** 0.242 Supported
PI <--- I 0.163 0.062 2.62 0.009 0.194 Supported
Note: *** means p < 0.001

Table 7. Analysis of mediating effects

Bootstrapping
Parameter Estimate Bias-corrected 95% CI Percentile 95% CI
Lower Upper P Lower Upper P
I-PEU-PI 0.098 0.039 0.17 0.001 0.036 0.165 0.002
I-PU-PI 0.061 0.016 0.138 0.004 0.011 0.127 0.009
I-SP-PI 0.119 0.043 0.224 0.002 0.041 0.217 0.002
I-PEU-PU-PI 0.044 0.019 0.087 *** 0.017 0.082 ***
I-SP-PU-PI 0.051 0.021 0.101 *** 0.02 0.097 ***
Note: *** means p < 0.001

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 The mediating effects are shown in Table 7, and motivation variables in their TAM, cognitive attentiveness and
Bootstrapping test was adopted to test all mediating paths in popular involvement, and other introduced variables include
the study model. In the analysis 5000 samples were repeated subjective criteria, perceived behavioral control, and self-
and 95% confidence intervals were designed. If the p is higher efficacy, among others [38, 39]. Capturing social presence is
than 0.05, 0 is not included between the upper and lower intended to extend the theoretical framework of TAM and has
intervals of the test results, which means that the mediation a stronger effect on purchase intention of consumption
effect is significant. In addition to the three mediator variable compared to other mediators.
of perceived ease of use, perceived usefulness, and social The theoretical implications, this study integrated external
presence that hold, the chain mediating effects of interactivity factors into the TAM model and identified the main external
in turn through perceived ease of use, perceived usefulness to factors. This study used social presence as a mediator of
purchase intention and interactivity in turn through social intrinsic motivation and extended TAM. In addition, the
presence, perceived usefulness to purchase intention are both mediating effects of perceived usefulness, perceived ease of
significant, suggesting that interactivity indirectly affects use, and social presence are verified, and the optimized TAM
purchase intention. is more suitable for the current situation, which is conducive
to extending the current research results in the field of e-
commerce. The combing and analysis reveal that the influence
5. DISCUSSION of the features of live streaming shopping on consumers
continues to exist in the field of live streaming shopping,
The results of this study validate the impact of interactivity forming a validation with previous scholars' studies. It also
and expand the influence of systemic characteristic factors on provides insights into the differences between the research
behavioral intention, indicating that live streaming shopping findings and previous studies to help explore the continued
with good interactivity gives consumers a very convenient and exploration of the features of live streaming shopping in the
realistic feeling, which is conducive to increasing their area of consumer purchase intentions.
purchase intentions. Similar to previous studies, Lee et al. [10] The practical implications, the study results provide
also found that high levels of interaction positively influenced valuable recommendations for anchors and live merchants. By
consumer perceptions and that virtual shopping environments considering social presence, they can identify better marketing
were more useful and easier to use. The mediating role of methods to improve the effectiveness of live streaming. In
perceived ease of use and perceived usefulness was addition, anchors and live merchants should pay more
demonstrated. Both perceived ease of use and perceived attention to the interactivity of live streaming and should
usefulness have a significant positive effect on purchase consider how to bring convenient and effective shopping to
intention. The effect of perceived usefulness on purchase consumers. In short, this study promotes TAM and helps
intention is greater than that of perceived ease of use, which anchors and merchants improve their marketing methods and
indicates that consumers pay more attention to the help that enhance the effectiveness of live streaming.
live streaming shopping brings to shopping than to ease of use. This study also suffers from some limitations. First, for the
This study explains the importance of intrinsic motivation selection of live streaming shopping features, which were
in consumers' purchase intentions. The mediating role of chosen to have targeted interactivity, there may be more
social presence is demonstrated. Consumers' perceptions of diggable points and research points on whether there will be
shopping websites are no longer limited to time and cost other more special features of live streaming shopping
savings, this can greatly influence consumers' willingness to purchases that can better explain current consumer behavior.
purchase [23]. Even though live streaming shopping helps In addition, this study did not consider the effects of
people experience better shopping and is easy to use, consumption scenario and type of product purchased; product
consumers' psychological experiences have a mediating role factors may influence consumers' use of specific interactive
and may influence behavioral decisions. Consumers value the features, whereas situational factors may influence consumer
psychological experience of using live streaming shopping, experience value perception [40].
and this should be noted when anchors and merchants are live.

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