<?xml version="1.0" encoding="UTF-8"?>
<!DOCTYPE article PUBLIC "-//NLM//DTD JATS (Z39.96) Journal Publishing DTD v1.3 20210610//EN"
  "https://jats.nlm.nih.gov/publishing/1.3/JATS-journalpublishing1-3.dtd">
<article xmlns:xlink="http://www.w3.org/1999/xlink" dtd-version="1.3" article-type="research-article">
  <front>
    <journal-meta>
      <journal-id journal-id-type="publisher-id">AJMA</journal-id>
      <journal-title-group>
        <journal-title>Asian Journal of Management and Accounting</journal-title>
      </journal-title-group>
      <issn pub-type="epub">2963-4547</issn>
      <publisher>
        <publisher-name>Formosa Publisher</publisher-name>
      </publisher>
    </journal-meta>
    <article-meta>
      <article-id pub-id-type="doi">10.55927/ajma.v4i3.14897</article-id>
      <title-group>
        <article-title>The Influence of Online Reviews and Online Ratings on Consumer Purchase Decisions of Somethinc Products in Pekanbaru Area with Korean Wave as a Moderating Variable</article-title>
      </title-group>
      <contrib-group>
        <contrib contrib-type="author" corresp="yes">
          <name>
            <surname>H</surname>
            <given-names>Putri Alisa</given-names>
          </name>
          <aff>Faculty of Economics and Business, Universitas Riau, Indonesia</aff>
          <email>putrialisahsb@gmail.com</email>
        </contrib>
        <contrib contrib-type="author">
          <name>
            <surname>Berampu</surname>
            <given-names>Lailan Tawila</given-names>
          </name>
          <aff>Faculty of Economics and Business, Universitas Riau, Indonesia</aff>
        </contrib>
        <contrib contrib-type="author">
          <name>
            <surname>Taufiqurrahman</surname>
            <given-names></given-names>
          </name>
          <aff>Faculty of Economics and Business, Universitas Riau, Indonesia</aff>
        </contrib>
      </contrib-group>
      <pub-date pub-type="epub">
        <day>28</day>
        <month>07</month>
        <year>2025</year>
      </pub-date>
      <history>
        <date date-type="received">
          <day>08</day>
          <month>06</month>
          <year>2025</year>
        </date>
        <date date-type="rev-recd">
          <day>23</day>
          <month>06</month>
          <year>2025</year>
        </date>
        <date date-type="accepted">
          <day>25</day>
          <month>07</month>
          <year>2025</year>
        </date>
      </history>
      <volume>4</volume>
      <issue>3</issue>
      <fpage>1097</fpage>
      <lpage>1112</lpage>
      <abstract>
        <p>In Indonesia's growing beauty industry, online reviews and online ratings are critical in shaping consumer purchase decisions. Local beauty brands like Somethinc leverage eWOM to build trust, while the Korean Wave (Hallyu) influences consumer preferences. This study explores the impact of online reviews and online ratings on Somethinc product purchases, with the Korean Wave as a moderating factor. This study designed using a quantitative research design, data was collected via structured questionnaires, and analyzed using Structural Equation Modeling (SEM). The results reveal that online ratings significantly influence purchase decisions, while online reviews show a weaker effect. The Korean Wave moderates the relationship between online ratings and purchase decisions, enhancing their effect, but has a negative moderating effect on online reviews. These results suggest that local beauty brands like Somethinc can benefit from aligning their marketing strategies with global cultural trends, especially those related to Korean beauty standards.</p>
      </abstract>
      <kwd-group>
        <kwd>Online Reviews</kwd>
        <kwd>Online Ratings</kwd>
        <kwd>Consumer Purchase Decisions</kwd>
        <kwd>Korean Wave</kwd>
      </kwd-group>
      <permissions>
        <license>
          <ali:license_ref xmlns:ali="http://www.niso.org/schemas/ali/1.0/">http://creativecommons.org/licenses/by/4.0/</ali:license_ref>
          <license-p>This is an open access article distributed under the terms of the Creative Commons Attribution 4.0 International License.</license-p>
        </license>
      </permissions>
    </article-meta>
  </front>

  <body>

<sec>
  <title>INTRODUCTION</title>
  <p>In the rapidly evolving beauty industry, particularly in emerging
  markets like Indonesia, digital platforms and e-commerce have reshaped
  how consumers make purchasing decisions. One of the most significant
  changes has been the rise of electronic word-of-mouth (eWOM), which
  includes online reviews and ratings, and their increasing influence on
  consumer behavior. Consumers now rely heavily on reviews and ratings
  provided by other users rather than traditional advertisements or
  marketing claims ((Donthu et al., 2021); (Filieri et al., 2021))This
  shift has significantly affected both global and local beauty brands,
  as the digital space provides an open forum for consumers to share
  their experiences and opinions. In markets like Indonesia, where
  online shopping is gaining rapid popularity, understanding the role of
  eWOM in consumer behavior is essential for brands aiming to stay
  competitive and build consumer trust ((Karinda &amp; Fajri, 2024);
  (Tanuwijaya et al., 2023))</p>
  <p>In Indonesia, a market characterized by a high percentage of
  internet penetration and active e-commerce participation, local beauty
  brands have leveraged online reviews and ratings as key tools to
  strengthen their market presence and build consumer trust. Somethinc,
  a local skincare brand, has rapidly emerged as a leader in the
  Indonesian beauty industry, effectively using eWOM through digital
  platforms to create a loyal consumer base (Somethinc Market Overview,
  2021). Somethinc's success can be attributed to both the quality of
  its products and the strategic use of online reviews and ratings,
  which help consumers make more informed purchase decisions.
  Furthermore, it has built a strong digital presence and engaged with
  younger generations who rely on social media and e-commerce platforms
  for their beauty-related needs (Karinda &amp; Fajri, 2024).</p>
  <p>However, despite the recognized significance of online reviews and
  ratings, there remains a gap in understanding the specific role of
  cultural influences— such as the Korean Wave (Hallyu) in amplifying or
  diminishing the effects of these online feedback mechanisms. The
  Korean Wave, which encompasses K- pop, K-dramas, and K-beauty, has
  become a powerful cultural force that has influenced consumer
  preferences globally, including in Southeast Asia ((Chae et al.,
  2020); (Halim &amp; Kiatkawsin, 2021)).</p>
  <p>The Korean Wave has had a profound impact on beauty standards,
  particularly among younger generations in Indonesia. Korean beauty
  products, which emphasize flawless skin, multi-step skincare routines,
  and a natural aesthetic, have gained immense popularity (Halim &amp;
  Kiatkawsin, 2021). Korean celebrities, K-pop idols, and K-drama stars
  play a crucial role in shaping these trends, creating a strong
  cultural appeal that resonates with Indonesian consumers. The
  influence of Korean beauty standards has made Korean-inspired products
  highly desirable, even among local brands like Somethinc, which
  incorporate K-beauty elements into their product offerings (Chae et
  al., 2020).</p>
  <p>The integration of the Korean Wave into digital marketing
  strategies has been shown to improve consumer engagement, as Korean
  beauty standards and products are often seen as symbols of beauty and
  aspiration (Scott, 2020). Studies show that Korean beauty standards
  and products have shaped consumer</p>
  <p>perceptions, particularly in Southeast Asia (Muskitta et al.,
  2022). Local brands such as Somethinc have capitalized on this trend
  by aligning their products with Korean-inspired beauty ideals, which
  resonate with Indonesian millennials and Gen Z consumers who are
  heavily influenced by global beauty trends (Halim &amp; Kiatkawsin,
  2021). However, while the influence of the Korean Wave on consumer
  behavior is well documented, its interaction with digital feedback
  mechanisms, such as online reviews and ratings, remains underexplored
  in the context of local beauty brands in Indonesia.</p>
  <p>This study aims to examine the role of online reviews and ratings
  in shaping consumer purchasing decisions for Somethinc products in
  Pekanbaru, Indonesia, while also investigating how the Korean Wave
  acts as a moderating factor in this relationship. By investigating how
  cultural trends like Hallyu affect consumer responses to online
  reviews and ratings, the study aims to provide a deeper understanding
  of the factors driving consumer behavior in the beauty industry.
  Positive eWOM, such as high ratings and favorable reviews, can enhance
  brand reputation and increase consumer trust, while negative feedback
  may deter potential buyers ((Macheka et al., 2024); (Zhao et al.,
  2020))</p>
  <p>The importance of this research is twofold: it contributes to the
  growing body of literature on eWOM by examining the moderating role of
  cultural phenomena like the Korean Wave, and it provides practical
  insights for local beauty brands, such as Somethinc, on how to better
  align their digital marketing strategies with cultural trends. As
  consumers increasingly rely on online feedback to make informed
  purchasing decisions, brands that effectively integrate global
  cultural influences with digital marketing strategies can build
  stronger consumer trust, enhance brand loyalty, and ultimately drive
  greater sales performance ((Zhao et al., 2020); (Leong et al.,
  2021)).</p>
</sec>












<sec>
  <title>LITERATURE REVIEW</title>
  <sec id="online-review">
    <title>Online Review</title>
    <p>Online reviews are a form of reviews given by consumers after
    they use a product or service, which is published through digital
    platforms such as e- commerce, social media, or online forums.
    According to (Mudambi &amp; Schuff, 2010), the quality and trust of
    online reviews affect consumer perception of products and brands.
    Online reviews function as an electronic word of mouth (e- WOM) that
    has a significant influence on shaping consumer purchase intentions,
    especially on cosmetic products that involve high
    considerations.</p>
    <p>Research by (Shankar et al., 2002) It shows that informative and
    credible reviews tend to be more trusted by consumers in making
    purchase decisions. In the midst of high competition for beauty
    products, consumers usually read reviews from previous users to
    minimize the risk of purchases.</p>
  </sec>
  <sec id="online-rating">
    <title>Online Rating</title>
    <p>Online rating refers to a numerical rating system (e.g. 1–5
    stars) on product quality based on user experience. According to
    (Zhu &amp; Zhang, 2010), ratings affect the perception of the value
    of a product in the eyes of consumers. A high</p>
    <p>rating creates a positive perception and increases the likelihood
    of a product to be chosen.</p>
    <p>Cosmetic consumers, including users of Somethinc products, tend
    to consider ratings as a form of &quot;heuristic cue&quot; or a
    brief clue in the decision-making process. A high rating is usually
    associated with customer satisfaction, while a low rating can
    indicate a quality problem.</p>
  </sec>
  <sec id="consumer-purchase-decision">
    <title>Consumer Purchase Decision</title>
    <p>Consumer purchasing decisions are a mental process that involves
    searching for information, evaluating alternatives, and selecting
    products that are considered to best meet their needs. According to
    (Kotler, n.d.), social, personal, and psychological factors
    influence a person's purchasing decision.</p>
    <p>In the digital context, purchasing decisions are increasingly
    influenced by information available online such as reviews and
    ratings. Research from (Nurbaety, 2024) stating that positive
    reviews and high ratings can speed up purchasing decisions,
    especially for cosmetic products that have variations and effects
    that are subjective to each individual.</p>
  </sec>
  <sec id="korean-wave-hallyu-as-a-moderation-variable">
    <title>Korean Wave (Hallyu) as a Moderation Variable</title>
    <p>Korean Wave or Hallyu is the spread of South Korean pop culture
    such as music (K-pop), drama (K-drama), and lifestyle that has a
    great influence on consumer preferences, including in the world of
    beauty. According to (Miko'ende, 2025), Korean Wave formed a new
    consumption trend in Asia, including Indonesia, where many consumers
    began to like products with Korean imagery or endorsements.</p>
    <p>As a moderation variable, Korean Wave can strengthen the
    relationship between online reviews and ratings and purchasing
    decisions. Study by (Lee, 2024) show that fans of Korean culture
    tend to be more interested in cosmetic products associated with
    Korean artists, even when the reviews and ratings are the same as
    other products. In the context of Somethinc's products, which adopt
    a Korean-style aesthetic and promotional style, interest in Korean
    Wave can be the main trigger for consumers in Pekanbaru to make
    purchase decisions, especially if online reviews and ratings are
    also supportive.</p>
  </sec>
</sec>














<sec>
  <title>METHODOLOGY</title>
  <p>This research employs a quantitative approach to examine the impact
  of online reviews and ratings on consumer purchase decisions for
  Somethinc products in Pekanbaru, with the Korean Wave acting as a
  moderating variable (Santoso &amp; Madiistriyatno, 2021). A survey
  method was used for data collection, targeting 134 respondents who
  have purchased Somethinc products and have been exposed to online
  reviews, ratings, and the Korean Wave. The respondents were selected
  using purposive sampling, which was chosen to ensure that participants
  had relevant experience and exposure to the factors being studied. A
  structured questionnaire was developed to assess the respondents'
  perceptions of online reviews, ratings, and cultural influences, and
  their impact on purchase decisions.</p>
  <p>The sample size was determined using the formula recommended by
  (Sarstedt et al., 2021), who suggest that the required sample size for
  structural equation modeling (SEM) is the product of the number of
  indicators for each latent construct and a multiplier of 5 to 10.
  Given that the study used 13 indicators, I selected a multiplier of
  10, resulting in a recommended sample size of 130 respondents (13
  indicators × 10). Thus, the final sample of 134 respondents exceeded
  the recommended minimum, ensuring the robustness and reliability of
  the data for analysis.</p>
  <p>Data collected from the respondents were analyzed using Structural
  Equation Modeling (SEM) to test the relationships between the
  independent variables (online reviews and ratings) and the dependent
  variable (consumer purchase decisions), as well as to evaluate the
  moderating effect of the Korean Wave. This method is suitable for
  investigating complex relationships and provides a comprehensive
  approach to testing the proposed hypotheses.</p>
  <disp-quote>
    <p>Table 1. Dimensions and Indicators of Research Variables</p>
  </disp-quote>
  <table-wrap>
    <label>Table 1. Dimensions and Indicators of Research Variables</label>
    <table>
      <thead>
        <tr>
          <th>Variable</th>
          <th>Dimension</th>
          <th>Indicator</th>
        </tr>
      </thead>
      <tbody>
        <tr>
          <td>Online Reviews</td>
          <td>Consumer Perception</td>
          <td>a) Clarity<break/>b) Credibility<break/>c) Usefulness<break/>d) Sentiment Alignment<break/>(Donthu et al., 2021; Ventre &amp; Kolbe, 2020)</td>
        </tr>
        <tr>
          <td>Online Ratings</td>
          <td>Consumer Evaluation</td>
          <td>a) Average Rating Score<break/>b) Rating Consistency<break/>c) Volume of Ratings<break/>(Gil-saura et al., 2020; Sun et al., 2020)</td>
        </tr>
        <tr>
          <td>Korean Wave</td>
          <td>Cultural Influence</td>
          <td>a) Cultural Affinity<break/>b) Perception of Korean Trends<break/>c) Influence of Korean Celebrities<break/>(Halim &amp; Kiatkawsin, 2021; Suwuh et al., 2022)</td>
        </tr>
        <tr>
          <td>Purchase Decision</td>
          <td>Decision Confidence</td>
          <td>a) Decision Confidence<break/>b) Transaction Frequency<break/>c) Post-Purchase Satisfaction<break/>(Darmatama &amp; Erdiansyah, 2021; Sri Gandari &amp; Seminary, 2024)</td>
        </tr>
      </tbody>
    </table>
  </table-wrap>
</sec>













<sec>
  <title>RESEARCH RESULTS</title>
  <sec id="respondent-demographics">
    <title>Respondent Demographics</title>
    <p>The sample for this study consisted of 134 respondents who were
    selected based on their experience with Somethinc products and their
    exposure to online reviews, online ratings, and the Korean Wave. The
    total initial number of respondents was 143, with 125 females and 18
    males. However, 7 females and 2 males were excluded from the study
    because they had not purchased Somethinc</p>
    <p>products, which was a necessary criterion for inclusion. After
    these exclusions, the final sample size consisted of 134
    respondents, with 118 females (88.1%) and</p>
    <p>16 males (11.9%). The demographic characteristics of the
    respondents were analyzed to provide a better understanding of the
    consumer profile and its potential impact on the research findings.
    The gender distribution reflects the predominant role of female
    consumers in the beauty industry, while the inclusion of male
    participants highlights the increasing interest of men in skincare
    products.</p>
    <disp-quote>
      <p>Table 2. Research Respondents</p>
    </disp-quote>
    <table-wrap>
      <label>Table 2. Research Respondents</label>
      <caption>
        <title><italic>Source: Processed Data</italic></title>
      </caption>
      <table>
        <thead>
          <tr>
            <th>Gender</th>
            <th>Frequency</th>
            <th>Percentage</th>
          </tr>
        </thead>
        <tbody>
          <tr>
            <td>Female</td>
            <td>118</td>
            <td>88.1%</td>
          </tr>
          <tr>
            <td>Male</td>
            <td>16</td>
            <td>11.9%</td>
          </tr>
          <tr>
            <td>Total</td>
            <td>134</td>
            <td>100%</td>
          </tr>
        </tbody>
      </table>
    </table-wrap>
    <p>As seen in table above, the majority of the respondents were
    female, comprising 88.1% of the total sample. This is consistent
    with the beauty and skincare market, where female consumers
    typically dominate. The remaining 11.9% were male respondents,
    reflecting a growing interest among male consumers in skincare
    products.</p>
  </sec>
  <sec id="outer-model">
    <title>Outer Model</title>
    <p>The outer model evaluation assesses the measurement model, which
    determines the relationships between observed variables (indicators)
    and latent constructs (variables). This evaluation was performed
    using Confirmatory Factor Analysis (CFA), with key metrics such as
    outer loading, Average Variance Extracted (AVE), Cronbach's Alpha
    and Composite Reliability to assess the reliability and validity of
    the model.</p>
    <disp-quote>
      <p><italic>Outer Loading</italic></p>
    </disp-quote>
    <p>Outer loadings represent the correlations between the indicators
    and their respective constructs. A higher outer loading that the
    indicator is a strong representative of the construct.</p>
    <disp-quote>
      <graphic mimetype="image" mime-subtype="jpeg" xlink:href="vertopal_8e5b882565734db4bda940f68ce32748/media/image3.jpeg" />
      <p>Figure 1. Result PLS SEM Loading Factor</p>
      <p><italic>Source: Processed Data</italic></p>
    </disp-quote>
    <disp-quote>
      <p>Table 3. Outer Loadin</p>
    </disp-quote>
    <table-wrap>
      <label>Table 3. Outer Loading</label>
      <caption>
        <title><italic>Source: Processed Data</italic></title>
      </caption>
      <table>
        <thead>
          <tr>
            <th>Variables</th>
            <th>Indicator</th>
            <th>Outer Loading</th>
            <th>Results</th>
          </tr>
        </thead>
        <tbody>
          <tr>
            <td rowspan="10">Online Review</td>
            <td>Usefulness2</td>
            <td>0.795</td>
            <td>Valid</td>
          </tr>
          <tr>
            <td>Usefulness1</td>
            <td>0.797</td>
            <td>Valid</td>
          </tr>
          <tr>
            <td>Feeling Alignment3</td>
            <td>0.780</td>
            <td>Valid</td>
          </tr>
          <tr>
            <td>Usefulness3</td>
            <td>0.801</td>
            <td>Valid</td>
          </tr>
          <tr>
            <td>Credibility2</td>
            <td>0.812</td>
            <td>Valid</td>
          </tr>
          <tr>
            <td>Sentiment Alignment1</td>
            <td>0.819</td>
            <td>Valid</td>
          </tr>
          <tr>
            <td>Feeling Alignment2</td>
            <td>0.821</td>
            <td>Valid</td>
          </tr>
          <tr>
            <td>Credibility1</td>
            <td>0.831</td>
            <td>Valid</td>
          </tr>
          <tr>
            <td>Clarity</td>
            <td>0.832</td>
            <td>Valid</td>
          </tr>
          <tr>
            <td>Quantity of Ratings1</td>
            <td>0.834</td>
            <td>Valid</td>
          </tr>
          <tr>
            <td rowspan="6">Online Rating</td>
            <td>Rating Consistency2</td>
            <td>0.754</td>
            <td>Valid</td>
          </tr>
          <tr>
            <td>Quantity of Ratings2</td>
            <td>0.782</td>
            <td>Valid</td>
          </tr>
          <tr>
            <td>Consistency Rating1</td>
            <td>0.819</td>
            <td>Valid</td>
          </tr>
          <tr>
            <td>Average Rating Score</td>
            <td>0.826</td>
            <td>Valid</td>
          </tr>
          <tr>
            <td>Consistency Rating3</td>
            <td>0.844</td>
            <td>Valid</td>
          </tr>
          <tr>
            <td rowspan="10">Korean Wave</td>
            <td>Influence of Korean Celebrities1</td>
            <td>0.769</td>
            <td>Valid</td>
          </tr>
          <tr>
            <td>Cultural Affinity3</td>
            <td>0.775</td>
            <td>Valid</td>
          </tr>
          <tr>
            <td>Perception of Korean Trends2</td>
            <td>0.779</td>
            <td>Valid</td>
          </tr>
          <tr>
            <td>Influence of Korean Celebrities2</td>
            <td>0.788</td>
            <td>Valid</td>
          </tr>
          <tr>
            <td>Perception of Korean Trends6</td>
            <td>0.792</td>
            <td>Valid</td>
          </tr>
          <tr>
            <td>Perception of Korean Trends5</td>
            <td>0.796</td>
            <td>Valid</td>
          </tr>
          <tr>
            <td>Cultural Affinity1</td>
            <td>0.802</td>
            <td>Valid</td>
          </tr>
          <tr>
            <td>Perception of Korean Trends1</td>
            <td>0.810</td>
            <td>Valid</td>
          </tr>
          <tr>
            <td>Cultural Affinity2</td>
            <td>0.814</td>
            <td>Valid</td>
          </tr>
          <tr>
            <td>Influence of Korean Celebrities3</td>
            <td>0.820</td>
            <td>Valid</td>
          </tr>
          <tr>
            <td rowspan="7">Purchase Decision</td>
            <td>Perception of Korean Trends3</td>
            <td>0.849</td>
            <td>Valid</td>
          </tr>
          <tr>
            <td>Perception of Korean Trends4</td>
            <td>0.863</td>
            <td>Valid</td>
          </tr>
          <tr>
            <td>Post-Purchase Decision2</td>
            <td>0.751</td>
            <td>Valid</td>
          </tr>
          <tr>
            <td>Post-Purchase Decision1</td>
            <td>0.772</td>
            <td>Valid</td>
          </tr>
          <tr>
            <td>Transaction Frequency1</td>
            <td>0.783</td>
            <td>Valid</td>
          </tr>
          <tr>
            <td>Decision Confidence1</td>
            <td>0.793</td>
            <td>Valid</td>
          </tr>
          <tr>
            <td>Post-Purchase Decision3</td>
            <td>0.812</td>
            <td>Valid</td>
          </tr>
          <tr>
            <td rowspan="3"></td>
            <td>Transaction Frequency2</td>
            <td>0.813</td>
            <td>Valid</td>
          </tr>
          <tr>
            <td>Decision Confidence3</td>
            <td>0.827</td>
            <td>Valid</td>
          </tr>
          <tr>
            <td>Decision Confidence2</td>
            <td>0.875</td>
            <td>Valid</td>
          </tr>
        </tbody>
      </table>
    </table-wrap>
    <p>Table above shows that all indicators demonstrated outer loadings
    above 0.7, indicating that the items are valid and robust in
    measuring their respective constructs.</p>
    <disp-quote>
      <p><italic>Average Variance Extracted (AVE)</italic></p>
    </disp-quote>
    <p>The Average Variance Extracted (AVE) measures the amount of
    variance captured by a construct in relation to the variance due to
    measurement error. A value above 0.5 indicates adequate convergent
    validity.</p>
    <disp-quote>
      <p>Table 4. Average Variance Extracted (AVE)</p>
    </disp-quote>
    <table-wrap>
      <label>Table 4. Average Variance Extracted (AVE)</label>
      <caption>
        <title><italic>Source: Processed Data</italic></title>
      </caption>
      <table>
        <thead>
          <tr>
            <th>Variables</th>
            <th>Average Variance Extracted (AVE)</th>
          </tr>
        </thead>
        <tbody>
          <tr>
            <td>Online Review (X1)</td>
            <td>0.656</td>
          </tr>
          <tr>
            <td>Online Rating (X2)</td>
            <td>0.657</td>
          </tr>
          <tr>
            <td>Korean Wave (M)</td>
            <td>0.649</td>
          </tr>
          <tr>
            <td>Purchase Decision (Y)</td>
            <td>0.647</td>
          </tr>
        </tbody>
      </table>
    </table-wrap>
    <p>Table shows that all constructs had AVE values higher than 0.5,
    indicates that the constructs effectively captured the majority of
    the variance in the indicators.</p>
    <disp-quote>
      <p><italic>Cronbach's Alpha and Composite Reliability</italic></p>
    </disp-quote>
    <p>Both Cronbach's Alpha and Composite Reliability are used to
    assess the internal consistency and reliability of the constructs. A
    value above 0.7 for both metrics indicates acceptable
    reliability.</p>
    <disp-quote>
      <p>Table 5. Construct Reliability Table</p>
    </disp-quote>
    <table-wrap>
      <label>Table 5. Construct Reliability Table</label>
      <caption>
        <title><italic>Source: Processed Data</italic></title>
      </caption>
      <table>
        <thead>
          <tr>
            <th/>
            <th>Cronbach's alpha</th>
            <th>Composite reliability (rho_a)</th>
            <th>Composite reliability (rho_c)</th>
          </tr>
        </thead>
        <tbody>
          <tr>
            <td>Korean Wave (M)</td>
            <td>0.951</td>
            <td>0.959</td>
            <td>0.957</td>
          </tr>
          <tr>
            <td>Online Rating (X2)</td>
            <td>0.896</td>
            <td>0.901</td>
            <td>0.920</td>
          </tr>
          <tr>
            <td>Online Review (X1)</td>
            <td>0.935</td>
            <td>0.942</td>
            <td>0.945</td>
          </tr>
          <tr>
            <td>Purchase Decision (Y)</td>
            <td>0.923</td>
            <td>0.937</td>
            <td>0.936</td>
          </tr>
        </tbody>
      </table>
    </table-wrap>
    <p>Reliability for each construct were all above the recommended
    threshold, confirming that the measurement model was reliable.</p>
    <sec id="inner-model">
      <title>Inner Model</title>
      <p>The inner model evaluation assesses the relationships between
      the latent constructs and the significance of the paths between
      them. This analysis was conducted using Structural Equation
      Modeling (SEM), focusing on model fit and hypothesis testing.</p>
    </sec>
    <sec id="model-fit">
      <title>Model Fit</title>
      <p>In assessing the fit of the structural model, R-squared (R²) is
      a key indicator of how well the model explains the variance in the
      dependent variables. R² represents the proportion of the variance
      in a dependent variable that can be explained by the independent
      variables in the model.</p>
      <disp-quote>
        <p>Table 6. Coefficient Determination (R-Square)</p>
      </disp-quote>
      <table-wrap>
        <label>Table 6. Coefficient Determination (R-Square)</label>
        <caption>
          <title><italic>Source: Processed Data</italic></title>
        </caption>
        <table>
          <thead>
            <tr>
              <th>Endogenous Variable</th>
              <th>R-square</th>
              <th>R-square adjusted</th>
              <th>Conclusion</th>
            </tr>
          </thead>
          <tbody>
            <tr>
              <td>Purchase Decision (Y)</td>
              <td>0.264</td>
              <td>0.236</td>
              <td>Weak to moderate explanatory model</td>
            </tr>
          </tbody>
        </table>
      </table-wrap>
    </sec>
  </sec>
    <p>The R-square value for purchase decision (Y) is 0.264, indicating
    that the model explains 26.4% of the variance in consumer purchase
    decisions. When adjusted for the number of predictors in the model,
    the adjusted R-square is 0.236, suggesting a slightly lower
    explanatory power. This implies that the model has a weak to
    moderate explanatory power, meaning that while online reviews,
    online ratings, and the Korean Wave do influence purchase decisions,
    there are other factors not captured by the model that also play a
    significant role in shaping consumer behavior.</p>
    <sec id="hypothesis-testing">
      <title>Hypothesis Testing</title>
      <p>Hypothesis testing was performed using the t-statistic test at
      a 5% significance level (α = 0.05). A path is considered
      statistically significant if the t- statistic is greater than
      1.96. Additionally, p-values are examined where p &lt; 0.05
      indicates significance.</p>
      <disp-quote>
        <p>Table 7. Path Coefficient</p>
      </disp-quote>
      <table-wrap>
        <label>Table 7. Path Coefficient</label>
        <caption>
          <title><italic>Source: Processed Data</italic></title>
        </caption>
        <table>
          <thead>
            <tr>
              <th>Path</th>
              <th>Original Sample (O)</th>
              <th>Sample Mean (M)</th>
              <th>Standard Deviation (STDEV)</th>
              <th>T-Statistic</th>
              <th>P Value</th>
            </tr>
          </thead>
          <tbody>
            <tr>
              <td>Korean Wave (M) → Purchase Decision (Y)</td>
              <td>0.010</td>
              <td>0.015</td>
              <td>0.119</td>
              <td>0.081</td>
              <td>0.935</td>
            </tr>
            <tr>
              <td>Korean Wave (M) x Online Rating (X2) → Purchase Decision (Y)</td>
              <td>0.235</td>
              <td>0.210</td>
              <td>0.118</td>
              <td>1.995</td>
              <td>0.046</td>
            </tr>
            <tr>
              <td>Korean Wave (M) x Online Reviews (X1) → Purchase Decision (Y)</td>
              <td>-0.263</td>
              <td>-0.243</td>
              <td>0.115</td>
              <td>2.291</td>
              <td>0.022</td>
            </tr>
            <tr>
              <td>Online Ratings (X2) → Purchase Decision (Y)</td>
              <td>0.174</td>
              <td>0.187</td>
              <td>0.081</td>
              <td>2.134</td>
              <td>0.033</td>
            </tr>
            <tr>
              <td>Online Review (X1) → Purchase Decision (Y)</td>
              <td>0.170</td>
              <td>0.189</td>
              <td>0.101</td>
              <td>1.674</td>
              <td>0.094</td>
            </tr>
          </tbody>
        </table>
      </table-wrap>
      <p>Based on table above, the path coefficients, T-statistic, and
      P-values are used to assess the significance of the relationships
      between the constructs in the model. The model are as follows:</p>
      <list list-type="bullet">
        <list-item>
          <p>Hypothesis Testing 1: Online reviews have a significant
          effect on consumer purchase decision on Somethinc products.
          The path coefficient is 0.170, with a T-statistic of 1.674 and
          a P-value of 0.094. Since the P-value is greater than 0.05,
          this path is not statistically significant, suggesting that
          online reviews alone do not have a direct significant effect
          on purchase decisions. This indicates that Hypothesis 1 is not
          supported.</p>
        </list-item>
        <list-item>
          <p>Hypothesis Testing 2: Online ratings have a significant
          effect on consumer purchase decision on Somethinc products.
          The path coefficient is 0.174, with a T-statistic of 2.134 and
          a P-value of 0.033. The P-value is less than 0.05, indicating
          that online ratings have a significant positive effect on
          purchase decisions. Thus, Hypothesis 2 is accepted.</p>
        </list-item>
        <list-item>
          <p>Hypothesis Testing 3: Korean Wave positively moderates the
          relationship between online reviews and purchase decision for
          Somethinc products. The interaction between Korean Wave on
          Online Review on Purchase Decision has a path coefficient of
          -0.263, with a t-statistic of 2.291 and a p-value of 0.022.
          Since the p-value is below 0.05, the moderating is
          statistically significant. However, the negative coefficient
          suggests that Korean Wave weakens the positive relationship
          between Online Review and Purchase Decision. Therefore,
          Hypothesis 3 is accepted, but the effect is in the negative
          direction.</p>
        </list-item>
        <list-item>
          <p>Hypothesis Testing 4: Korean Wave positively moderates the
          relationship between online ratings and purchase decision for
          Somethinc products. Regarding the interaction between Korean
          Wave and Online Rating onPurchase Decision, the path
          coefficient is 0.235, t-statistic 1.995, and p-value</p>
        </list-item>
      </list>
      <disp-quote>
        <p>0.046. The p-value is below than 0.05, indicating a
        significant moderating effect. Korean Wave strengthens the
        positive influence of Online Rating on Purchase Decision. Hence,
        Hypothesis 4 is accepted.</p>
      </disp-quote>
      <list list-type="bullet">
        <list-item>
          <p>Hypothesis Testing 5: Korean Wave influence has direct
          positive effect on purchase decision. The path coefficient is
          0.010 with a T-statistic of 0.081 and a P-value of 0.935.
          Since the P-value is greater than 0.05, this path is not
          statistically significant, meaning that online reviews do not
          significantly affect purchase decisions in this model.
          Therefore, Hypothesis 5 is rejected.</p>
        </list-item>
      </list>
    </sec>
</sec>






<sec>
  <title>DISCUSSION</title>
  <p>The results of this study offer significant insights into the
  factors influencing consumer purchase decisions, particularly in the
  beauty industry, and provide valuable implications for local brands
  like Somethinc in Pekanbaru. This research examined the effects of
  online reviews, online ratings, and the Korean Wave as a moderating
  variable in shaping consumer purchase decisions. The findings reveal
  that online ratings have a significant positive influence on purchase
  decisions, while online reviews did not show a statistically
  significant effect.</p>
  <p>The findings of this study provide deeper insight into the
  interplay between online reviews, online ratings, and cultural
  influences in shaping purchasing decisions. The significant of online
  ratings aligns with existing literature, such as (Gil-saura et al.,
  2020) and (Sun et al., 2020), which emphasize that numerical ratings
  offer quick and accessible evaluations for consumers. Consumers often
  perceive online ratings as reliable indicators of product quality,
  especially in high-involvement categories such as beauty and skincare.
  This support the notion that a high average rating can build consumer
  confidence and influence their purchase decision ((Ventre &amp; Kolbe,
  2020)).</p>
  <p>In contrast, the study found that online reviews do not
  significantly influence purchase decisions. This results diverges from
  some prior findings ((Donthu et al., 2021); (Sun et al., 2020)) which
  suggest that reviews enhance credibility and reduce uncertainty. A
  possible explanantion is that in markets like Pekanbaru, where beauty
  product purchases are frequently influenced by trends and peer
  behavior, consumers may prioritize easily digestible information like
  ratings over more elaborate written feedback. Moreover, the dominance
  of visual-based platform and influencer content reduce the relative
  impact of written reviews (Tanuwijaya et al., 2023).</p>
  <p>The Korean Wave plays a dual moderating role in this context. It
  positively moderates the relationship between online ratings and
  purchase decisions, suggesting that cultural affinity with Korean
  trends amplifies consumer trust in products that are highly rated.
  This reflects the view of (Halim &amp; Kiatkawsin, 2021) and (Chae et
  al., 2020), who found that the aesthetic appeal and celebrity
  endorsement in K-beauty significantly shape consumer behavior.
  Consumers</p>
  <p>influenced by Hallyu are more likely to associate high product
  ratings with alignment to Korean beauty standards, increasing their
  willingness to purchase. On the other hand, the Korean Wave negatively
  moderates the influence of online reviews. This counterintuitive
  result may be due to consumers' preconceived positive perceptions of
  Korean-influenced products, rendering textual reviews less necessary
  in their decision-making process. As suggested by (Suwuh et al.,
  2022), cultural admiration for Korea can lead to cognitive biases,
  where consumers assume quality based on brand image or trend
  conformity rather than detailed descriptions. This findings is
  supported by (BOUGUERN Hamida, 2023), who explored the impact of
  Korean Wave can alter consumers' perceptions and minimize the weight
  given to written reviews, as consumers increasingly rely on cultural
  signals and brand associations with Korean beauty trenfs. In this
  context, the Korean Wave reinforces the appeal of products that are
  perceived as culturally trendy or fashionable, even if the online
  reviews do not</p>
  <p>explicitly highlight the product's benefits.</p>
  <p>Interestingly, this study found that the Korean Wave does not have
  a direct significant effect on purchase decisions. This indicates that
  while cultural influence does shape perceptions, it is more impactful
  as a contextual enhancer rather than a standalone determinant of
  consumer behavior. This finding contributes to the growing body of
  literature that explores how global cultural phenomena indirectly
  shape market outcomes through interaction with other marketing
  variables (Macheka et al., 2024).</p>
  <p>From a practical perspective, these findings suggest that beauty
  brands like Somethinc should prioritize enhancing their online rating
  visibility and ensure consistency in consumer ratings. They should
  also consider embedding Korean aesthetics in their branding strategy
  to appeal to culturally influenced consumers. However, less emphasis
  may be needed on textual reviews, especially when targeting consumers
  who are highly familiar with K-beauty trends.</p>
  <p>Overall, this study offers a nuanced understanding of the
  effectiveness of eWOM elements and the moderating role of cultural
  influence. By situating the research in a specific regional
  context—Pekanbaru—this study adds localized insight to broader
  discussions on digital marketing and cross-cultural consumer
  behavior.</p>
</sec>









<sec>
  <title>CONCLUSIONS AND RECOMMENDATIONS</title>
  <p>This study provides valuable insights into the factors influencing
  consumer purchase decisions for Somethinc products in Pekanbaru,
  particularly in relation to online reviews, online ratings, and the
  Korean Wave as a moderating variable. The findings reveal several key
  insights that have practical implications for local beauty brands
  aiming to optimize their digital marketing strategies.</p>
  <p>First, the study found that online ratings have a significant
  positive effect on consumer purchase decisions, suggesting that
  ratings are a crucial factor in shaping consumers' trust and
  willingness to purchase. This supports the growing body of literature
  that emphasizes the importance of aggregated, numerical feedback in
  online decision-making processes. In contrast, online reviews did
  not</p>
  <p>show a significant direct effect, highlighting that consumers may
  prioritize quick, simple cues like ratings over more detailed,
  qualitative feedback when making purchasing decisions.</p>
  <p>Second, the Korean Wave was found to significantly moderate the
  relationship between online ratings and purchase decisions, amplifying
  the impact of positive ratings on consumer behavior. This finding
  suggests that cultural trends, such as the growing influence of Korean
  beauty standards, play a crucial role in shaping how consumers respond
  to online feedback. However, the Korean Wave did not significantly
  moderate the relationship between online reviews and purchase
  decisions, indicating that reviews may be less influential for
  consumers who are strongly influenced by cultural trends.</p>
  <p>The results of this study underscore the importance of leveraging
  both online ratings and cultural trends in digital marketing
  strategies. For brands like Somethinc, aligning their products with
  popular global beauty standards, such as those associated with the
  Korean Wave, could enhance the effectiveness of their eWOM strategies.
  While detailed online reviews are important for building credibility,
  focusing on optimizing online ratings and incorporating cultural
  elements in product positioning may yield greater results in driving
  consumer purchase decisions.</p>
  <p>In conclusion, while online reviews and ratings both play critical
  roles in shaping consumer behavior, ratings appear to have a more
  direct and powerful impact. Additionally, cultural influences like the
  Korean Wave can enhance the effectiveness of eWOM, especially in
  markets where consumers are highly attuned to global beauty trends.
  These findings offer valuable guidance for local beauty brands to
  refine their marketing approaches and better align their strategies
  with the evolving preferences of their target consumers.</p>
</sec>








<sec>
  <title>ADVANCED RESEARCH</title>
  <p>Building upon the findings of this study, future research can adopt
  a more advanced approach by exploring the dynamic interplay between
  different types of electronic word-of-mouth (eWOM) content—such as
  visual reviews (e.g., TikTok, Instagram Reels) and influencer
  endorsements—and their differential impacts on consumer purchase
  decisions in culturally influenced markets. Incorporating longitudinal
  data and behavioral tracking could offer deeper insights into how
  consumer trust evolves over time in response to fluctuating online
  ratings and culturally resonant marketing campaigns. Additionally,
  employing a cross-regional comparative framework, particularly between
  cities with varying levels of exposure to the Korean Wave, could
  illuminate the geographical boundaries of cultural influence and the
  scalability of digital marketing strategies across diverse consumer
  segments.</p>
</sec>









<sec>
<title>REFERENCES</title>
<ref-list>

<ref id="ref1">
  <element-citation publication-type="journal">
    <person-group person-group-type="author">
      <name><surname>Bouguern</surname><given-names>Hamida</given-names></name>
      <name><surname>Laifa</surname><given-names>T.</given-names></name>
    </person-group>
    <article-title>The Korean Wave Effect on American Popular Culture</article-title>
    <source></source>
    <year>2023</year>
  </element-citation>
</ref>

<ref id="ref2">
  <element-citation publication-type="journal">
    <person-group person-group-type="author">
      <name><surname>Chae</surname><given-names>H.</given-names></name>
      <name><surname>Park</surname><given-names>J. H.</given-names></name>
      <name><surname>Ko</surname><given-names>E.</given-names></name>
    </person-group>
    <article-title>The effect of attributes of Korean trendy drama on consumer attitude, national image, and consumer acceptance intention for sustainable Hallyu culture</article-title>
    <source>Journal of Global Fashion Marketing</source>
    <year>2020</year>
    <volume>11</volume>
    <issue>1</issue>
    <fpage>18</fpage>
    <lpage>36</lpage>
  </element-citation>
</ref>

<ref id="ref3">
  <element-citation publication-type="confproc">
    <person-group person-group-type="author">
      <name><surname>Darmatama</surname><given-names>M.</given-names></name>
      <name><surname>Erdiansyah</surname><given-names>R.</given-names></name>
    </person-group>
    <article-title>The Influence of Advertising in Tiktok Social Media and Beauty Product Image on Consumer Purchase Decisions</article-title>
    <source>Proceedings of the International Conference on Economics, Business, Social, and Humanities (ICEBSH 2021)</source>
    <year>2021</year>
    <volume>570</volume>
    <fpage>888</fpage>
    <lpage>892</lpage>
    <pub-id pub-id-type="doi">10.2991/assehr.k.210805.140</pub-id>
  </element-citation>
</ref>

<ref id="ref4">
  <element-citation publication-type="journal">
    <person-group person-group-type="author">
      <name><surname>Donthu</surname><given-names>N.</given-names></name>
      <name><surname>Kumar</surname><given-names>S.</given-names></name>
      <name><surname>Pandey</surname><given-names>N.</given-names></name>
      <name><surname>Pandey</surname><given-names>N.</given-names></name>
      <name><surname>Mishra</surname><given-names>A.</given-names></name>
    </person-group>
    <article-title>Mapping the electronic word-of-mouth (eWOM) research: A systematic review and bibliometric analysis</article-title>
    <source>Journal of Business Research</source>
    <year>2021</year>
    <volume>135</volume>
    <fpage>758</fpage>
    <lpage>773</lpage>
  </element-citation>
</ref>

<ref id="ref5">
  <element-citation publication-type="journal">
    <person-group person-group-type="author">
      <name><surname>Filieri</surname><given-names>R.</given-names></name>
      <name><surname>Lin</surname><given-names>Z.</given-names></name>
      <name><surname>Pino</surname><given-names>G.</given-names></name>
      <name><surname>Alguezaui</surname><given-names>S.</given-names></name>
      <name><surname>Inversini</surname><given-names>A.</given-names></name>
    </person-group>
    <article-title>The role of visual cues in eWOM on consumers’ behavioral intention and decisions</article-title>
    <source>Journal of Business Research</source>
    <year>2021</year>
    <volume>135</volume>
    <fpage>663</fpage>
    <lpage>675</lpage>
  </element-citation>
</ref>

<ref id="ref6">
  <element-citation publication-type="journal">
    <person-group person-group-type="author">
      <name><surname>Gil-Saura</surname><given-names>I.</given-names></name>
      <name><surname>Rodríguez-Orejuela</surname><given-names>A.</given-names></name>
      <name><surname>Pe</surname><given-names>N.</given-names></name>
    </person-group>
    <article-title>Purchase intention and purchase behavior online: A cross-cultural approach</article-title>
    <source>Heliyon</source>
    <year>2020</year>
    <volume>6</volume>
    <fpage></fpage>
    <lpage></lpage>
    <pub-id pub-id-type="doi">10.1016/j.heliyon.2020.e04284</pub-id>
  </element-citation>
</ref>

<ref id="ref7">
  <element-citation publication-type="journal">
    <person-group person-group-type="author">
      <name><surname>Halim</surname><given-names>T. M.</given-names></name>
      <name><surname>Kiatkawsin</surname><given-names>K.</given-names></name>
    </person-group>
    <article-title>Beauty and celebrity: Korean entertainment and its impacts on female Indonesian viewers’ consumption intentions</article-title>
    <source>Sustainability (Switzerland)</source>
    <year>2021</year>
    <volume>13</volume>
    <issue>3</issue>
    <pub-id pub-id-type="doi">10.3390/su13031405</pub-id>
  </element-citation>
</ref>

<ref id="ref8">
  <element-citation publication-type="thesis">
    <person-group person-group-type="author">
      <name><surname>Ingels</surname><given-names>L.</given-names></name>
    </person-group>
    <article-title>The Attraction of Korea: An empirical study on how country-of-origin affects consumers’ perception and purchase intentions of Korean beauty products</article-title>
    <source></source>
    <year>2020</year>
  </element-citation>
</ref>

<ref id="ref9">
  <element-citation publication-type="journal">
    <person-group person-group-type="author">
      <name><surname>Karinda</surname><given-names>R. M.</given-names></name>
      <name><surname>Fajri</surname><given-names>A.</given-names></name>
    </person-group>
    <article-title>Pengaruh Influencer dan Online Customer Review terhadap Keputusan Pembelian pada Produk Skincare Skintific di TikTok</article-title>
    <source>Journal of Information System, Applied, Management, Accounting and Research</source>
    <year>2024</year>
    <volume>8</volume>
    <issue>4</issue>
    <fpage>815</fpage>
    <lpage>823</lpage>
  </element-citation>
</ref>

<ref id="ref10">
  <element-citation publication-type="book">
    <person-group person-group-type="author">
      <name><surname>Kotler</surname><given-names>P.</given-names></name>
      <name><surname>Keller</surname><given-names>K. L.</given-names></name>
    </person-group>
    <article-title>Marketing Management</article-title>
    <source>Pearson</source>
    <year>2016</year>
  </element-citation>
</ref>

<ref id="ref11">
  <element-citation publication-type="journal">
    <person-group person-group-type="author">
      <name><surname>Lee</surname><given-names>J.</given-names></name>
    </person-group>
    <article-title>A study on the impact of Hallyu on the Korean national image and the image of cosmetics: Focusing on psychological distance theory</article-title>
    <source>Journal of Fashion Business</source>
    <year>2024</year>
    <volume>28</volume>
    <issue>2</issue>
    <fpage>33</fpage>
    <lpage>49</lpage>
  </element-citation>
</ref>

<ref id="ref12">
  <element-citation publication-type="journal">
    <person-group person-group-type="author">
      <name><surname>Leong</surname><given-names>C.-M.</given-names></name>
      <name><surname>Loi</surname><given-names>A. M.-W.</given-names></name>
      <name><surname>Woon</surname><given-names>S.</given-names></name>
    </person-group>
    <article-title>The influence of social media eWOM information on purchase intention</article-title>
    <source>Journal of Marketing Analytics</source>
    <year>2021</year>
    <volume>10</volume>
    <issue>2</issue>
    <fpage>145</fpage>
    <lpage></lpage>
  </element-citation>
</ref>

<ref id="ref13">
  <element-citation publication-type="journal">
    <person-group person-group-type="author">
      <name><surname>Macheka</surname><given-names>T.</given-names></name>
      <name><surname>Quaye</surname><given-names>E. S.</given-names></name>
      <name><surname>Ligaraba</surname><given-names>N.</given-names></name>
    </person-group>
    <article-title>The effect of online customer reviews and celebrity endorsement on young female consumers’ purchase intentions</article-title>
    <source>Young Consumers</source>
    <year>2024</year>
    <volume>25</volume>
    <issue>4</issue>
    <fpage>462</fpage>
    <lpage>482</lpage>
  </element-citation>
</ref>

<ref id="ref14">
  <element-citation publication-type="thesis">
    <person-group person-group-type="author">
      <name><surname>Miko’ende</surname><given-names>N. A.</given-names></name>
    </person-group>
    <article-title>Diplomasi Publik Korea Selatan: Studi Kasus Pengaruh Korean Wave Terhadap Industri Kecantikan di Indonesia</article-title>
    <source>Fakultas Hukum Sosial Politik</source>
    <year>2025</year>
  </element-citation>
</ref>

<ref id="ref15">
  <element-citation publication-type="journal">
    <person-group person-group-type="author">
      <name><surname>Mudambi</surname><given-names>S. M.</given-names></name>
      <name><surname>Schuff</surname><given-names>D.</given-names></name>
    </person-group>
    <article-title>What makes a helpful online review? A study of customer reviews on Amazon.com</article-title>
    <source>MIS Quarterly</source>
    <year>2010</year>
    <fpage>185</fpage>
    <lpage>200</lpage>
  </element-citation>
</ref>

<ref id="ref16">
  <element-citation publication-type="journal">
    <person-group person-group-type="author">
      <name><surname>Muskitta</surname><given-names>C. G.</given-names></name>
      <name><surname>Ade</surname><given-names>T.</given-names></name>
      <name><surname>Ulaen</surname><given-names>E. I.</given-names></name>
      <name><surname>Pangaribuan</surname><given-names>C. H.</given-names></name>
    </person-group>
    <article-title>The Influence of the Korean Wave Phenomenon on Male Customer Purchase Decisions for Korean Skincare Products in Indonesia</article-title>
    <source>Management, and Industry (JEMI)</source>
    <year>2022</year>
    <volume>5</volume>
    <issue>03</issue>
  </element-citation>
</ref>

<ref id="ref17">
  <element-citation publication-type="thesis">
    <person-group person-group-type="author">
      <name><surname>Nurbaety</surname><given-names>E.</given-names></name>
    </person-group>
    <article-title>Pengaruh Online Customer Review, Persepsi Manfaat, Dan Promosi Terhadap Keputusan Pembelian Pada Platform TikTok Shop Dikalangan Urban Muslim Di Kota Metro (Perspektif Ekonomi Syariah)</article-title>
    <source>IAIN Metro</source>
    <year>2024</year>
  </element-citation>
</ref>

<ref id="ref18">
  <element-citation publication-type="book">
    <person-group person-group-type="author">
      <name><surname>Santoso</surname><given-names>I.</given-names></name>
      <name><surname>Madiistriyatno</surname><given-names>H.</given-names></name>
    </person-group>
    <article-title>Metodologi penelitian kuantitatif</article-title>
    <source>Indigo Media</source>
    <year>2021</year>
  </element-citation>
</ref>

<ref id="ref19">
  <element-citation publication-type="book">
    <person-group person-group-type="author">
      <name><surname>Sarstedt</surname><given-names>M.</given-names></name>
      <name><surname>Ringle</surname><given-names>C. M.</given-names></name>
      <name><surname>Hair</surname><given-names>J. F.</given-names></name>
    </person-group>
    <article-title>Partial least squares structural equation modeling</article-title>
    <source>Handbook of Market Research</source>
    <year>2021</year>
    <fpage>587</fpage>
    <lpage>632</lpage>
    <comment>Springer</comment>
  </element-citation>
</ref>

<ref id="ref20">
  <element-citation publication-type="journal">
    <person-group person-group-type="author">
      <name><surname>Shankar</surname><given-names>V.</given-names></name>
      <name><surname>Urban</surname><given-names>G. L.</given-names></name>
      <name><surname>Sultan</surname><given-names>F.</given-names></name>
    </person-group>
    <article-title>Online trust: a stakeholder perspective, concepts, implications, and future directions</article-title>
    <source>The Journal of Strategic Information Systems</source>
    <year>2002</year>
    <volume>11</volume>
    <issue>3–4</issue>
    <fpage>325</fpage>
    <lpage>344</lpage>
  </element-citation>
</ref>

<ref id="ref21">
  <element-citation publication-type="journal">
    <person-group person-group-type="author">
      <name><surname>Sri Gandari</surname><given-names>N. N. M.</given-names></name>
      <name><surname>Seminari</surname><given-names>N. K.</given-names></name>
    </person-group>
    <article-title>The Role of Brand Image in Mediating the Effect of Brand Ambassador on Purchase Decision of Somethinc Products in Denpasar City</article-title>
    <source>Asian Journal of Management Analytics</source>
    <year>2024</year>
    <volume>3</volume>
    <issue>3</issue>
    <fpage>811</fpage>
    <lpage>824</lpage>
    <pub-id pub-id-type="doi">10.55927/ajma.v3i3.10031</pub-id>
  </element-citation>
</ref>

<ref id="ref22">
  <element-citation publication-type="journal">
    <person-group person-group-type="author">
      <name><surname>Sun</surname><given-names>L.</given-names></name>
      <name><surname>Zhao</surname><given-names>Y.</given-names></name>
      <name><surname>Ling</surname><given-names>B.</given-names></name>
    </person-group>
    <article-title>The Joint Influence of Online Rating and Product Price on Purchase Decision: An EEG Study</article-title>
    <source>Psychology Research and Behavior Management</source>
    <year>2020</year>
    <pub-id pub-id-type="doi">10.2147/PRBM.S238063</pub-id>
  </element-citation>
</ref>

<ref id="ref23">
  <element-citation publication-type="journal">
    <person-group person-group-type="author">
      <name><surname>Suwuh</surname><given-names>J. L. A.</given-names></name>
      <name><surname>Kindangen</surname><given-names>P.</given-names></name>
      <name><surname>Saerang</surname><given-names>R. T.</given-names></name>
    </person-group>
    <article-title>The Influence of Korean Wave, Brand Ambassador, and Brand Image on Purchase Intention of Somethinc Skincare Products in Manado</article-title>
    <source>Jurnal EMBA: Jurnal Riset Ekonomi, Manajemen, Bisnis dan Akuntansi</source>
    <year>2022</year>
    <volume>10</volume>
    <issue>4</issue>
    <fpage>1146</fpage>
    <lpage>1155</lpage>
  </element-citation>
</ref>

<ref id="ref24">
  <element-citation publication-type="journal">
    <person-group person-group-type="author">
      <name><surname>Tanuwijaya</surname><given-names>C. K.</given-names></name>
      <name><surname>Ellitan</surname><given-names>L.</given-names></name>
      <name><surname>Lukito</surname><given-names>R. S. H.</given-names></name>
    </person-group>
    <article-title>The effect of online customer reviews on purchase intention with customer trust as a variable in purchase decision on Sociolla consumers</article-title>
    <source>Journal of Entrepreneurship and Business</source>
    <year>2023</year>
    <volume>4</volume>
    <issue>3</issue>
    <fpage>192</fpage>
    <lpage>203</lpage>
  </element-citation>
</ref>

<ref id="ref25">
  <element-citation publication-type="journal">
    <person-group person-group-type="author">
      <name><surname>Ventre</surname><given-names>I.</given-names></name>
      <name><surname>Kolbe</surname><given-names>D.</given-names></name>
    </person-group>
    <article-title>The Impact of Perceived Usefulness of Online Reviews, Trust and Perceived Risk on Online Purchase Intention in Emerging Markets: A Mexican Perspective</article-title>
    <source>Journal of International Consumer Marketing</source>
    <year>2020</year>
    <volume>32</volume>
    <issue>4</issue>
    <fpage>287</fpage>
    <lpage>299</lpage>
    <pub-id pub-id-type="doi">10.1080/08961530.2020.1712293</pub-id>
  </element-citation>
</ref>

<ref id="ref26">
  <element-citation publication-type="journal">
    <person-group person-group-type="author">
      <name><surname>Zhao</surname><given-names>Y.</given-names></name>
      <name><surname>Wang</surname><given-names>L.</given-names></name>
      <name><surname>Tang</surname><given-names>H.</given-names></name>
      <name><surname>Zhang</surname><given-names>Y.</given-names></name>
    </person-group>
    <article-title>Electronic word-of-mouth and consumer purchase intentions in social e-commerce</article-title>
    <source>Electronic Commerce Research and Applications</source>
    <year>2020</year>
    <volume>41</volume>
    <fpage></fpage>
    <lpage></lpage>
    <pub-id pub-id-type="doi">10.1016/j.elerap.2020.100980</pub-id>
  </element-citation>
</ref>

<ref id="ref27">
  <element-citation publication-type="journal">
    <person-group person-group-type="author">
      <name><surname>Zhu</surname><given-names>F.</given-names></name>
      <name><surname>Zhang</surname><given-names>X.</given-names></name>
    </person-group>
    <article-title>Impact of online consumer reviews on sales: The moderating role of product and consumer characteristics</article-title>
    <source>Journal of Marketing</source>
    <year>2010</year>
    <volume>74</volume>
    <issue>2</issue>
    <fpage>133</fpage>
    <lpage>148</lpage>
  </element-citation>
</ref>

</ref-list>
</sec>
</body>
</article>
