p-ISSN
2980-4868 | e-ISSN 2980-4841
https://ajesh.ph/index.php/gp
Discover
Your Perfect Look: Virtual Makeup Try-On Revolutionizes Shopping Experience on
Shopee!
Universitas Indonesia, Depok, DKI Jakarta, Indonesia
Email: puput.ria@ui.ac.id
ABSTRACT
Competition
in the e-commerce industry is becoming increasingly fierce with the emergence
of various platforms offering similar products and services. In response to
this competition, Shopee, one of the e-commerce platforms with the highest
number of site visits, has adopted augmented reality (AR) technology in its BeautyCam and SkinCam features.
These mobile applications, which support AR features, enable marketers and
companies to provide detailed information to consumers about products and
services, thereby influencing consumer perceptions. The purpose of this study
was to evaluate behavioral intention towards the
AR-based Shopee application feature using the Technology Acceptance Model
(TAM). In this study, TAM was used to measure perceptions of the usefulness of
information technology (Perceived Usefulness), ease of use (Perceived Ease of Use),
and perceived enjoyment, which affect individual attitudes toward using
information technology (Attitude Towards Using). This, in turn, determines the
degree of a person's intention to use information technology (Behavioral Intention). The research employed a quantitative
approach by distributing questionnaires to users of Shopee's BeautyCam and SkinCam features.
Data analysis was conducted using Partial Least Squares - Structural Equation Modeling (PLS-SEM).
Keywords:
augmented
reality, beauty product, behavioral intention,
consumer behavior, e-commerce, Shopee.
INTRODUCTION
Digitalization
has swept the global economy over the past three decades. This led to a shift
from a traditional management approach to one based on technology
Internet-enabled
mobile devices give consumers online access to a wider market where they can
shop at their convenience, anytime and from anywhere. Consumers can now reach a
wide variety of brands and products both expensive and cheap. In addition, they
can now quickly compare different products over long distances based on quality
and price. Most retail businesses have implemented technology to maintain a
competitive advantage and start online retail or electronic commerce (EC).
E-commerce refers to businesses where technology and the Internet are used to
complete business activities. It allows customers to exchange goods and
services electronically though over long distances and at any time. E-commerce
has increased rapidly over the past five years and has become an important part
of the internet and technology, even projected to continue with higher
development. The retail space has shown a transformation supported by increased
digitalization and the explosion of online channels. Technology has revolutionized
traditional retail practices and opened up new possibilities for retailers to
offer dynamic experiences to consumers in the online region
Retail
businesses will adapt technology to a more advanced level, increasing reliance
on standard internet technology to smart technologies such as the utilization
of augmented reality in marketing communications. However, in the context of
e-commerce, the main challenges retailers face are that customers can abandon
online shopping carts and high return rates, so many customers refuse to shop
online and complain of lack of direct contact with products, thus losing
sensory shopping cues, such as touch and taste, which help in shopping decision
making. The gap between physical and online experiences can be effectively
bridged by introducing augmented reality (AR) technology that supports the
senses in online shopping
Retailers
have realized the substantial benefits of AR during the COVID-19 pandemic. The
pandemic has posed rigorous challenges for offline retailers as customers
around the world worry about shopping in-store due to social distancing norms.
Furthermore, retailers have invested in AR features in mobile shopping apps
(apps)/web stores to facilitate customers' purchase decisions and drive sales.
The ability of AR technology to dramatically transform businesses has been
realized globally. However, existing research claims that managers still lack
insight and need guidance to explore AR to its full potential. For example,
reporting that strong consumer expectations and resistance have led to the
failure of AR technologies in the early stages, such as Google Glass products.
Therefore, marketers must understand the major barriers in adopting AR in
e-commerce
Previous
research entitled "An Empirical Evaluation of Technology Acceptance Model
for Artificial in E-Commerce", had limitations in exploring AR
applications targeting female consumers, especially in the context of beauty
and cosmetics. Previous research has focused on demographic distribution of
male respondents, ignoring the unique perspectives and preferences of female
consumers. This underscores the need for research specifically designed to
understand female users' attitudes, behaviors, and
experiences regarding AR technologies, such as BeautyCam
and SkinCam, in the e-commerce landscape
Indonesia
is one of the countries with the largest population in the world with the use
of digital technology that is growing rapidly. The increase in internet usage
and adoption of other digital technologies in Indonesia, such as social media
and e-commerce have increased in recent years. The increasing use of mobile
devices and the increasing demand for digital content are also attracting
attention, and can be an important strategy for marketers and companies in
Indonesia.
During
the pandemic, Indonesians have experienced an increase in online shopping. The
Association of Indonesian E-commerce (idEA) shows an
increase in online shopping between 25% to 30% in Indonesia, caused by the PPKM
government policy that encourages people to switch to e-commerce.
E-commerce
will continue to evolve at a rapid pace as the world becomes more digital and
connected. Figure 1.2. shows that as many as 62.6% of active e-commerce users
in Indonesia in 2023 buy products online. Global e-commerce sales have reached
$4.2 trillion by 2020, and will be expected to continue to rise. Amidst the
ever-changing e-commerce landscape, it is crucial to stay ahead and understand
the latest trends shaping the industry
Indonesia's
e-commerce market penetration rate is expected to continue to increase by a
total of 11.1% between 2024-2028. With a ten-year increase in a row, the
indicator is expected to reach 46.5%, reaching a new peak in 2028. The increase
will also be accompanied by the development of the number of e-commerce market
users.
Shopee, which was launched in 2015,
provides an easy, secure, and fast online shopping experience through strong
payment and logistics support. In the first quarter of 2023, Shopee is the
e-commerce with the highest number of site visits in Indonesia based on SimilarWeb data. From January to March of 2023, Shopee
receives an average of 157.9 million visits per month, far surpassing its
competitors. During the same period Tokopedia received 117.2 million monthly
visits, Lazada 83.2 million visits, Blibli 25.4 million visits, and Bukalapak 18.1 million visits per month. Visits to the five
e-commerce websites will increase in March 2023 due to the arrival of Ramadan
as well as the lead-up to Eid al-Fitr. Based on
wearesocial.com data for ranking applications with the most active users,
Shopee became the first e-commerce to have the most active users in 4th place,
and the most downloaded applications in 5th place, even the most shopping
search keywords on Google with 6th place.
According to the data, the AR market is expected to
reach USD 50 billion by 2024, with 61% of consumers stating that they will shop
more often than retailers using AR, and 71% of consumers feel increased
confidence in purchasing decisions of a product if they use AR and will shop
more often. Then, 66% of consumers in Japan want offline stores also to be able
to offer AR, and 40% of consumers stated that they would be willing to pay more
for products offered through AR. As a result of this demand, many brands are
starting to build mobile Apps that use AR. For example, Maybelline New York allows
women to see cosmetic products of their own choosing virtually. In addition,
Converse, through its mobile app, allows people to try virtual variations of
shoe models on their own feet without going to a store
Shopify
is an integrated e-commerce platform that allows anyone to start, develop,
manage and scale a business to build an online store. To enhance the
interactive shopping experience, Shopify has acquired Primer, an AI-powered
styling app, to help personalize and create a more immersive customer
experience. Another big e-commerce player, Walmart also acquired Zeekit. The virtual
fitting room technology uses AI to create realistic simulations of the
appearance of clothes on various body types. Through the AI technology,
customers can use the "Choose my model" feature for certain clothing
items such as Levi's, Athletics Works, Terra & Sky and can choose around 50
different models with a height between 5'2" – 6'0" and sizes XS –
XXXL that reflect the customer's physical posture.
The
application of AR is also
applied to IKEA Place is an application that allows users to when
making IKEA simulation equipment placed in the user's home. This application
helps customers to place furniture based on the dimensions of their room with
an accuracy rate of 98%.
Shopee
is one of the e-commerce that often develops its technology. Based on data,
this application has the fourth most active users and the fifth most downloads
in Indonesia in 2020. Shopee strives to become the most popular e-commerce
platform in Indonesia by making marketing efforts and paying attention to how
easy it is to use its app. The customer's online shopping experience must be
improved along with the development of technology, to meet customer needs.
Shopee offers an attractive shopping experience for consumers through Shopee SkinCam and BeautyCam which are supported by advanced AR features,
namely Virtual Try-On on certain cosmetic products such as L'Oreal,
Maybelline, DAZZLE ME, and others
The BeautyCam and SkinCam
features, which were launched in 2019, are marketing campaigns carried out by
Shopee using AR so that consumers can do interactive makeup to reduce consumer
doubts or confusion when shopping for cosmetic products online, which initially
arose due to uncertainty in choosing product colors
and types of products that suit facial conditions. However, because of the
support of advanced, clear, detailed, and convincing AR features, consumers can
be easier and more confident when shopping online.
The
increasing online shopping behavior of customers
along with the customer experience, has increased the demand for the addition
of technology into a business. To assess whether TAM models are outdated or
still worth using, a study was conducted by Ref., which examined 2,399 papers
published in Web of Science from 2010 to 2020. Significant conclusions indicate
that more research is being done on TAM and its applications, showing that the
model can still be used, modified, and expanded across many applications and
domains. With increasing research on recently developed applications such as
augmented reality and e-commerce are at the top of the list of TAM applications
Although
several previous studies have investigated the use of AR apps in the e-commerce
landscape, they have focused on demographic distribution towards male
respondents, thus ignoring the unique perspectives and preferences of female
consumers. Previous research also had limitations in geographical data
analysis, mainly focusing in the context of e-commerce in Pakistan, thereby
ignoring potential insights and phenomena in different geographical contexts,
to understand e-commerce behavior among Indonesian users.
It emphasizes the need for tailored research to understand female users'
attitudes, behaviors, and experiences about AR
technologies in the context of body and beauty treatments, such as BeautyCam. Researchers will therefore further explore the
use of AR apps specifically for female consumers, focusing on their
preferences, needs, and perceptions of those apps.
In
this study, AR technology testing is used as a communication and marketing
medium based on the theory of Technology Acceptance Model (TAM). TAM is
a theory of reasoned action that argues that a person's reactions and
perceptions of something, will determine that person's attitude and behavior. TAM consists of external variables namely
Subjective Norm and Trust, Perceived Usefulness (PU), Perceived Ease of Use
(PEU), Perceived Enjoyment (ENJ), Attitude toward Using (AU), Behavioral Intention (BIU), and Actual Use (AU).
This study aims to evaluate the influence of subjective
norm (SN), trust (T), perceived usefulness (PU), perceived ease of use (PEU),
and perceived enjoyment (ENJ) on attitude toward using (AU) and behavioral intention (BI) in using augmented reality
(AR)-based Shopee application features using Technology Acceptance Model (TAM).
This research will identify how user acceptance from the perspective of these
various factors affects user attitudes and behavioral
intentions. In addition, this research also provides benefits for academics as
a reference to expand knowledge about consumer behavior
in the context of AR technology, for service users to improve the experience of
using AR features, and for business people to optimize AR features and follow
the latest technology trends to maintain the relevance of their applications in
the market.
RESEARCH METHODS
This research method was carried out
using cross-sectional design and statistical methods of Structural Equation Modeling (SEM). This study aims to find out how the
features of the Shopee application based on augmented reality (AR) affect user behavior. The object of this study is AR-based Shopee
application users, focusing on variables such as trust, perceived ease of use,
perceived usefulness, perceived enjoyment, attitude towards using, and behavioral intention to use. The source of this study's
data was a questionnaire distributed online using Google Form. The
questionnaire consists of four parts: an opening, a screening question, a core
question, and a respondent profile. Filter questions are used to ensure that
respondents meet the criteria that have been set for inclusion in the study.
The population of this study is AR-based Shopee application users in Indonesia,
with the following inclusion criteria: Indonesian nationality, domiciled in
Indonesia, belonging to generation Y (born 1981 - 1995) or generation Z (born
1996 - 2010), and have tried the Shopee Augmented Reality-Based application in
the last 3 months.
The sample of this study was not
specifically mentioned, but was distributed online using Google Form. These
research techniques and tools include the use of structured, logical, and
four-part questionnaires, as well as SEM methods to examine relationships
between complex latent variables. The analysis technique used in this study is
SEM to test models that include several relationships between variables
simultaneously. SEM allows researchers to test more complex models than
traditional regression analysis techniques and can identify causal
relationships between measured variables.
RESULTS AND DISCUSSION
Researchers
conduct hypothesis testing that aims to determine whether there is enough
statistical evidence to support the research hypothesis that has been
formulated. In this study, we used a statistical test method by utilizing
T-value and P-value with a significant limit (α) used is 0.05. If the T-value
obtained is greater than 1.645, then the relationship between these variables
is considered positively significant. And vice versa, the relationship between
variables will be considered negatively significant if the value of T is less
than -1.645. Therefore, we can compare the value of T with the table T to find
out whether the null hypothesis (H0) can be rejected or not. In addition, we
can see the significance of the P-value, where the null hypothesis is rejected
and the alternative hypothesis is accepted if the P-value is less than the
significance level (α).
|
Hipotesis |
Hypothesis
Statement |
Original
sample (O) |
Sample
mean (M) |
Standard
deviation (STDEV) |
T
statistics (|O/STDEV|) |
P
values |
Research
Results |
|
H1a |
Subjective
norm Influential positive to perceived Usefulness |
0,294 |
0,292 |
0,080 |
3,682 |
0,000 |
Accepted |
|
H1b |
Subjective
norm Influential positive to perceived ease of use |
0,392 |
0,391 |
0,070 |
5,560 |
0,000 |
Accepted |
|
H1c |
Subjective
norm Influential positive to perceived enjoyment |
0,263 |
0,261 |
0,070 |
3,746 |
0,000 |
Accepted |
|
H2a |
Trust
has a positive effect on perceived usefulness |
0,309 |
0,311 |
0,084 |
3,691 |
0,000 |
Accepted |
|
H2b |
Trust
Influential positive to Perceived ease of use |
0,432 |
0,432 |
0,069 |
6,293 |
0,000 |
Accepted |
|
H2c |
Trust
Influential positive to perceived enjoyment |
0,328 |
0,327 |
0,080 |
4,092 |
0,000 |
Accepted |
|
H3a |
Perceived
ease of use Influential positive to perceived usefulness |
0,211 |
0,212 |
0,077 |
2,745 |
0,003 |
Accepted |
|
H3b |
Perceived
ease of use Influential positive to perceived enjoyment |
0,194 |
0,195 |
0,080 |
2,412 |
0,008 |
Accepted |
|
H3c |
Perceived
ease of use Influential positive to attitude towards use |
0,237 |
0,237 |
0,068 |
3,482 |
0,000 |
Accepted |
Table 2. Hypothesis Testing Results (Advanced)
|
H4 |
Perceived
usefulness Influential positive to attitude towards use |
0,278 |
0,282 |
0,071 |
3,920 |
0,000 |
Accepted |
|
H5 |
Perceived
enjoyment Influential positive to attitude towards use |
0,329 |
0,324 |
0,073 |
4,503 |
0,000 |
Accepted |
|
H6 |
Attitude
towards use Influential positive to behavioural intention |
0,702 |
0,704 |
0,035 |
19,941 |
0,000 |
Accepted |
Based
on Figure 1, testing the direct effect hypothesis with t statistics shows that
the causality of the measurement model, namely the relationship of indicators
with measurement items other than valid, is also significant, as shown by
statistical t values above 1.645. All direct effect hypotheses are significant
(p<0.05). Subjective norm and trust variables have a significant positive
effect on increasing perceived ease of use, usefulness and enjoyment
(p<0.05). Furthermore, perceived ease of use, perceived usefulness and
perceived enjoyment have a direct positive effect on attitude toward using. The
attitude toward using is also significantly positive for the increase in behavior intention (p<0.05).
Based
on the results of direct effect testing in Table 1, the influence between
variables can be concluded as follows:
H1a:
Subjective Norm Positively Affects Perceived Usefulness
The
results of testing the first hypothesis (a) show that the relationship between
subjective norm dimensions and perceived usefulness has a value with a path
coefficient of 0.294 and statistical t of 3.682 > 1.645 or a p-value of <
0.05. The results are in line with previous research that underscores the role
of subjective norms in reducing product uncertainty. In the context of Shopee,
if consumers see that others around them are using AR features to get better
product information, they will be more likely to find those features useful in
the purchase decision-making process. From this value, it can be concluded that
the
H1b:
Subjective Norm Influential Positive to Perceived Ease of Use
The
results of testing the first hypothesis (b) show that the relationship between
subjective norm dimensions and perceived ease of use with path coefficients
0.392 and statistical t 5.560 > 1.645 or p-value < 0.05. Therefore, it
can be concluded that the subjective norm positively influences perceived ease
of use in the use of augmented
reality-based Shoppee features in accordance with the
first hypothesis (b) or HYPOTHESIS 1B ACCEPTED.
H1c:
Subjective Norm Influential Positive to Perceived Enjoyment
The
results of testing the first hypothesis (c) show that the relationship between
subjective norm and perceived enjoyment dimensions has a path coefficient value
of 0.263 and statistical t of 3.746 > 1.645 or a p-value of < 0.05. This
suggests that a person's subjective norms and perception of pleasure influence
their decision to purchase a good or service. In general, it has been observed
that a product or service used by an ideal person will be easily used by other
products or services. From these results, it can be concluded that the
subjective norm positively influences perceived enjoyment in the use of
augmented reality-based Shoppee features in
accordance with the first hypothesis (c) or HYPOTHESIS 1C ACCEPTED.
H2a:
Trust Influential Positive to Perceived Usefulness
The
results of testing the second hypothesis (a) show that the relationship between
the dimensions of trust and perceived usefulness dimensions has a path
coefficient value of 0.309 and a statistical t of 3.691 > 1.645 or a p-value
of < 0.05. From these results, it can be concluded that the Trust dimension positively
influences Perceived Usefulness in the use of augmented reality-based Shoppee features in accordance with the second hypothesis
(a) or HYPOTHESIS 2A ACCEPTED.
H2b:
Trust Influential Positive to Perceived Ease of Use
The
results of testing the second hypothesis (b) show that the relationship between
the trust dimension and perceived ease of use has a value with a path
coefficient of 0.432 and a statistical t of 6.293 > 1.645 or a p-value of
< 0.05. From these results, it can be concluded that the Trust dimension has
a positive influence on Perceived Ease of Use in the use of augmented
reality-based Shoppee features in accordance with the
second hypothesis (b) or HYPOTHESIS 2B ACCEPTED.
H2c:
Trust Influential Positive to Perceived Enjoyment
The
results of testing the second hypothesis (c) show that the relationship between
the dimensions of trust and perceived enjoyment dimensions has a path
coefficient value of 0.328 and a statistical t of 4.092 > 1.645 or a p-value
of < 0.05. From these results, it can be concluded that the Trust dimension
has a positive influence on Perceived Enjoyment in the use of augmented
reality-based Shoppee features in accordance with the
second hypothesis (c) or HYPOTHESIS 2C ACCEPTED.
H3a:
Perceived Ease of Use Influential positive to Perceived Usefulness
The results of testing the third
hypothesis (a) show that the relationship between the dimensions of perceived
ease of use and perceived usefulness has a path coefficient value of 0.211 and
a statistical t of 2.745 > 1.645 or a p-value of < 0.05. From these
results, it can be concluded that the Perceived Ease of Use dimension has a
positive influence on Perceived Usefulness in the use of augmented
reality-based Shoppee features in accordance with the
third hypothesis (a) or HYPOTHESIS 3A ACCEPTED.
H3b:
Perceived Ease of Use Influential positive to Perceived Enjoyment
The
results of testing the third hypothesis (b) show that the relationship between
the dimensions of perceived ease of use and perceived enjoyment has a path
coefficient value of 0.194 and a statistical t of 2.412 > 1.645 or a p-value
of < 0.05. From these results, it can be concluded that the Perceived Ease
of Use dimension has a positive influence on Perceived Enjoyment in the use of
augmented reality-based Shoppee features in
accordance with the third hypothesis (b) or HYPOTHESIS 3B ACCEPTED.
H3c:
Perceived Ease of Use Influential Positive to Attitude Toward Using
The results of testing the third
hypothesis (c) show that the relationship between the dimensions of perceived
ease of use and attitude toward using has a path coefficient value of 0.237 and
a statistical t of 3.482 > 1.645 or a p-value of < 0.05. From these
results, it can be concluded that the Perceived Ease of Use dimension has a
positive influence on attitudes toward Using in the use of augmented
reality-based Shoppee features in accordance with the
third hypothesis (c) or ACCEPTED 3C HYPOTHESIS.
H4:
Perceived Usefulness Influential Positive to Attitude Towards Using
The results of testing the fifth
hypothesis show that the relationship between the dimensions of perceived
usefulness and attitude toward use has a path coefficient value of 0.278 and a
statistical t of 3.920 > 1.645 or a p-value of < 0.05. From these
results, it can be concluded that the Perceived Usefulness dimension has a
positive influence on Attitude Toward Using in the use of augmented
reality-based Shoppee features in accordance with the
fourth hypothesis or HYPOTHESIS 4 ACCEPTED.
H5:
Perceived Enjoyment Influential Positive to Attitude Towards Using
The results of testing the fifth
hypothesis show that the relationship between the dimensions of perceived
enjoyment and attitude toward use has a path coefficient value of 0.329 and a
statistical t of 4.503 > 1.645 or a p-value of < 0.05. From these
results, it can be concluded that the Perceived Enjoyment dimension has a
positive influence on Attitude Toward Using in the use of augmented
reality-based Shoppee features in accordance with the
fourth hypothesis or HYPOTHESIS 5 ACCEPTED.
H6:
Attitude towards use Influential positive to behavioural intention to use
The results of testing the sixth
hypothesis show that the relationship between the dimensions of attitude toward
use and behavioural intention to use has a path coefficient value with a path
coefficient of 0.702 and a statistical t of 19.941 > 1.645 or a p-value of
< 0.05. From these results, it can be concluded that the Attitude Toward
Using dimension has a positive influence on behavioral
intention to use in the use of augmented reality-based Shoppee
features in accordance with the fourth hypothesis or HYPOTHESIS 6 ACCEPTED.
CONCLUSION
This study found that subjective norm and trust
positively affect perceived usefulness, perceived ease of use, and perceived
enjoyment in the use of augmented reality (AR)-based Shopee features. Perceived
ease of use also positively affects perceived usefulness, perceived enjoyment,
and attitude toward using, which in turn affects behavioral
intention. This research reinforces the validity of the Technology Acceptance
Model (TAM) in the context of AR technology in e-commerce, suggesting that
perceived usefulness and perceived ease of use remain important predictors,
while perceived enjoyment also plays a significant role in the acceptance of AR
technology. For practical implications, e-commerce companies like Shopee need
to develop AR features that are interactive and fun, build user trust, and
provide personalized shopping experiences. This study has limitations in terms
of generalization of results and data collection methods, so follow-up research
is recommended to cover a more diverse sample, use more objective data
collection methods, and consider external factors. Qualitative methods such as
case studies or in-depth interviews can provide richer insights into user
perceptions and experiences.
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