GOLDEN RATIO OF MARKETING AND APPLIED PSYCHOLOGY OF BUSINESS
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MARKETING | RESEARCH ARTICLE
The EAect of Promotion.
Online Customer Reviews, and Rating Perceptions on the Decision to Use the Tokopedia Application: Evidence from Surabaya.
Indonesia Linc Adhara1.
Supriyono2 Department of Management.
Faculty of Economics and Business.
Universitas Pembangunan Nasional "Veteran" Jawa Timur.
Surabaya.
Indonesia.
Email: 21012010150@student.
id1, supriyono.
ma@upnjatim.
ARTICLE HISTORY
Received: May 22, 2025
Revised: July 11, 2025
Accepted: July 30, 2025
DOI
https://doi.
org/10.
52970/grmapb.
ABSTRACT
This study analyzes the influence of promotion, online customer reviews, and customer rating perception on users' decisions to use the Tokopedia application in Surabaya.
The research addresses a gap in previous studies that have not explicitly focused on Tokopedia users in this region.
A quantitative research method was employed using a survey approach.
Data were collected from 105 Tokopedia users in Surabaya through a Likert-scale questionnaire and analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM) with SmartPLS The results show that all three independent variables, promotion, online customer review, and online customer rating perception, positively and significantly impact the decision to use the Tokopedia application.
These findings highlight the importance of digital promotions, credible user reviews, and high user ratings in influencing consumer decisions.
Tokopedia is encouraged to optimize its digital marketing and online reputation management strategies to enhance user trust, retention, and competitive advantage in the Indonesian ecommerce market.
Keywords: Usage Decision.
Online Customer Rating.
Online Customer Review.
Promotion.
JEL Code: M31.
L81.
D12.
C83.
Introduction The rise of digital technology and internet accessibility has fundamentally transformed consumer behavior, particularly in how people shop and make purchasing decisions.
E-commerce platforms have become essential for meeting daily needs, driven by increased smartphone usage, internet penetration, and access to digital information.
Tokopedia is one of Indonesia's leading e-commerce platforms, acting as an online marketplace connecting buyers and sellers.
Despite its strong market presence, recent data from Top Brand Indonesia and user traEc statistics during Q4 2023Ae2024 indicate a decline in Tokopedia's brand perception and user activity.
The platform has also seen an uptick in customer complaints related to ineAective promotions, unfavorable reviews, and technical issues, which can negatively aAect user trust and decision-making.
Several factors are known to influence consumer decisions when using an e-commerce Promotional strategies such as discounts, cashback, and free shipping can attract attention and drive At the same time, online customer reviews provide valuable insights from other users, helping The Author.
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Furthermore, customer ratings oAer a visual summary of user satisfaction and quality perception, which can quickly influence user choices.
A review of existing studies reveals a gap in the literature concerning the Tokopedia platform, especially in Surabaya.
Prior research has primarily focused on other platforms or broader geographic areas.
Therefore, this study analyzes how promotion, online customer reviews, and perceptions of online customer ratings aAect the decision to use Tokopedia in Surabaya.
The findings are intended to support Tokopedia's strategy in improving user engagement and sustaining competitiveness in Indonesia's dynamic e-commerce landscape.
II.
Literature Review and Hypothesis Development Promotion Promotion has long been recognized as a crucial marketing tool influencing consumer behavior.
Kotler and Armstrong .
emphasize that promotional eAorts, such as discounts, cashback, and free shipping, serve not only to attract attention but also to create a sense of urgency in digital platforms.
In the ecommerce context, these incentives can significantly enhance the appeal of an application, especially among price-sensitive consumers.
However, while previous studies have acknowledged the eAectiveness of promotions (Melita & Astuti, 2.
, they often overlook the interaction between frequency and user trust.
Therefore, this study employs indicators such as in-app oAers, promotion timing, and promotion frequency to capture both the design and consistency of promotional eAorts.
These indicators are selected based on their relevance to short-term engagement and long-term platform usage.
Online Customer Review Online customer reviews (OCR) have evolved into a critical digital word-of-mouth mechanism.
Schepers .
outlines that the quality, credibility, timeliness, valence, and volume of reviews can shape consumer attitudes and reduce uncertainty in decision-making.
Recent findings by Bella & Supriyono .
confirm that consumers actively seek peer feedback as a risk-reduction strategy before using digital platforms.
Despite this, most prior research focuses on the presence of reviews rather than their structural attributes.
This study addresses that gap by integrating multiple dimensions of reviews to assess what is said and how well and by whom, reflecting their influence on user confidence.
Online Customer Rating Perception Customer rating perception refers to users' interpretations of aggregated feedback, typically displayed in star formats or numeric scores.
According to Priangga and Munawar .
, these ratings act as heuristics, simplifying decision-making in environments saturated with choices.
Higher ratings often signal trustworthiness and functionality.
This study builds upon this concept by adopting indicators such as perceived usefulness, trustworthiness, and enjoyment, which have been underexplored in previous models.
These indicators are crucial in assessing the emotional and cognitive resonance users experience when interpreting customer ratings.
Usage Decision The decision to use an e-commerce platform is a multi-stage process involving evaluation, trust formation, and final action.
Kotler and Keller .
argue that usage decisions reflect rational assessments and emotional responses to perceived benefits.
Prior literature frequently simplifies this process as a singular This study adopts indicators such as confidence in using the application, preference strength, goal fulfillment, and peer recommendation influence to provide a more nuanced understanding.
These dimensions capture the depth of the decision-making process, particularly in mobile app environments where The Author.
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Based on the theoretical framework and previous studies, the following hypotheses are proposed:
= Promotion positively influences the decision to use the Tokopedia application in Surabaya.
= Online customer reviews positively influence the decision to use the Tokopedia application in Surabaya.
= Perception of online customer rating positively influences the decision to use the Tokopedia application in Surabaya.
Promotion (X.
Online Customer Review (X.
Decision to Use the Tokopedia Application (Y) Perception of Online Customer Rating (X.
Figure 1.
Conceptual Framework i.
Research Method This study adopts a quantitative approach with a survey method to examine the influence of promotion, online customer reviews, and customer rating perception on Tokopedia usage decisions in Surabaya.
The structured questionnaire, developed using validated indicators from prior studies, utilized a 5point Likert scale and was distributed online via Google Forms through social media, university networks, and online communities during JanuaryAeFebruary 2025.
A pilot test with 15 respondents was conducted to ensure question clarity and reliability, and adjustments were made based on Cronbach's Alpha results.
Despite potential bias, convenience sampling was used for its practicality in exploratory research.
To minimize this, the sample was diversified.
One hundred five valid responses were collected, meeting the minimum requirement for PLS-SEM analysis.
Variable indicators include in-app oAers, promotion timing and frequency .
argument quality, credibility, timeliness, valence, and volume .
perceived usefulness, trust, and enjoyment .
ating perceptio.
and confidence, preference, fulfillment, and recommendation .
sage decisio.
Data analysis used SmartPLS software with PLS-SEM due to its suitability for small samples and complex models.
This method allows for simultaneous assessment of measurement and structural models, making it appropriate for predictive and exploratory analysis in e-commerce behavior studies.
The Author.
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Results and Discussion Outer Model ISSN [Onlin.
: 2776-6349 Promotion (X.
Online Customer Review (X.
Usage Decision (Y) Online Customer Rating (X.
Figure 2.
Outer Model with factor loading.
Path CoeEcient, and R-Square Outer Loading Based on the results in the outer loading table, all reflective indicators of the variables Price Perception (X.
Online Customer Review (X.
Perception of Online Customer Rating (X.
, and Purchase Decision (Y) have factor loading values above 0.
50 and T-statistics above 1.
Therefore, it can be concluded that all indicators meet the criteria for convergent validity and possess good validity.
Table 1.
Outer Loading Promotion (X.
Indicator Promotion (X.
Online Customer Review (X.
Online Customer Rating (X.
Usage Decision (Y) X1.
X1.
X1.
X2.
X2.
X2.
X2.
X2.
X3.
X3.
X3.
Online Customer Review (X.
Online Customer Rating Perception (X.
Usage Decision (Y) 0,796 0,746 0,801 0,601 0,807 0,823 0,629 0,856 0,769 0,860 0,750 The Author.
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0,767
0,747
0,721
0,871
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Online Customer Review (X.
Perception of Online Customer Rating (X.
, or Purchase Decision (Y)Aishow loading values above 0.
6 and are higher than their loadings on other variables.
Therefore, it can be concluded that all indicators in this study are valid.
Indicator X1.
X1.
X1.
X2.
X2.
X2.
X2.
X2.
X3.
X3.
X3.
Promotion (X.
0,796 0,746 0,801 0,537 0,731 0,767 0,596 0,781 0,655
0,707
0,638
0,640
0,661
0,632
0,802
Table 2.
Cross Loading Online Customer Online Customer Review (X.
Rating Perception (X.
0,731 0,626 0,716 0,687 0,704 0,660 0,601 0,578 0,807 0,678
0,823
0,639
0,629
0,636
0,856
0,665
0,619
0,769
0,718
0,860
0,691
0,750
0,660
0,667
0,702
0,657
0,620
0,631
0,797
0,753
Usage Decision (Y) 0,714 0,665 0,689 0,563 0,732 0,706 0,583 0,756 0,695 0,751 0,623 0,767 0,747 0,721 0,871 Average Variance Extracted (AVE) The results of the Average Variance Extracted (AVE) test in Table 5 show that the AVE value for the Promotion variable (X.
611, the Online Customer Review (X.
564, the Perception of Online Customer Rating (X.
631, and the Purchase Decision (Y) is 0.
Since all AVE values exceed 0.
5, it can be concluded that all four variables in this study have good validity.
Table 3.
AVE
Promotion (X.
Online Customer Review (X.
Online Customer Rating Perception (X.
Usage Decision (Y) Average Variance Extracted (AVE) 0,611 0,564 0,631 0,606 Composite Reliability The results of the Composite Reliability test in Table 6 show that the Promotion variable (X.
has a value of 0.
825, the Online Customer Review variable (X.
864, the Perception of Online Customer Rating variable (X.
836, and the Usage Decision variable (Y) is 0.
Since all four variables have Composite Reliability values above 0.
70, it can be concluded that all variables in this study are reliable.
Table 4.
Composite Reliability Composite Reliability Promotion (X.
0,825 Online Customer Review (X.
0,864 Online Customer Rating Perception (X.
0,836 Usage Decision (Y) 0,860 The Author.
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: 2776-6349 Latent Variable Correlations Based on the table of correlations among latent variables, the average correlation values indicate a relatively strong and varied level of correlation among the variables.
The highest correlation is found between the Promotion variable (X.
and the Online Customer Review (OCR) variable (X.
This indicates that the relationship between promotion and OCR is the strongest among all variables in the research model.
Promotion (X1 Online Customer Review (X.
Online Customer Rating Perception (X.
Usage Decision (Y) Table 5.
Correlation Test Result Online Online Customer Promotion Customer Rating Perception (X.
Review (X.
(X.
1,000 0,918 0,840 0,918 1,000 0,850 Usage Decision (Y) 0,883 0,896 0,840 0,850 1,000 0,872 0,883 0,896 0,872 1,000 Inner Model RA measures the extent to which independent variables can explain the dependent variable.
An RA value Ou 0.
5 indicates a good model, and the closer the value is to 1, the stronger the model is.
An RA value of 856 indicates that the model can explain 85.
6% of the variation in Purchase Decision, which is influenced by the independent variables: Promotion.
Online Customer Review, and Perception of Online Customer Rating.
Meanwhile, the remaining 14.
4% is explained by other variables not included in this study.
Table 6.
R-Square R Square Usage Decision (Y) Hypothesis Testing The hypothesis testing process is carried out by examining the results of the inner model, which includes the R-square value, path coeEcients, and T-statistics.
A reference value of T-statistic > 1.
64 with a significance level of p-value < 0.
05 is used to determine whether a hypothesis is accepted or rejected.
addition, the beta coeEcient must be positive and significant to confirm a significant influence between the Table 7.
Hypothesis Testing (X.
-> (Y) (X.
-> (Y) (X.
-> (Y) Original Sample (O) 0,252 0,375 0,341 T Statistics P Values Conclusion 1,946 2,556 4,410 0,026 0,005 0,000 Accepted Accepted Accepted Based on Table 8, the following conclusions can be drawn:
Hypothesis 1: Promotion has a positive eAect on the decision to use the Tokopedia application and is accepted, with a path coeEcient of 0.
252 and a T-statistic value of 1.
946 > 1.
64, or a P-value of 0.
< 0.
05, indicating a significant .
result Hypothesis 2: Online Customer Review has a positive eAect on the decision to use the Tokopedia application and is accepted, with a path coeEcient of 0.
375 and a T-statistic value of 2.
556 > 1.
64, or a P-value of 0.
005 < 0.
05, indicating a significant .
result The Author.
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: 2776-6349 Hypothesis 3: Perception of Online Customer Rating has a positive eAect on the decision to use the Tokopedia application and is accepted, with a path coeEcient of 0.
341 and a T-statistic value of 4.
> 1.
64, or a P-value of 0.
000 < 0.
05, indicating a significant .
Discussion The Influence of Promotion on Usage Decision The influence of promotion on usage decision supports the findings of Agustiningsih & Hartati .
, where promotional frequency and timing influenced shopping behavior across digital platforms.
In this study.
Tokopedia's frequent use of cashback oAers, discount vouchers, and free shipping appealed to young consumers, especially Gen Z users aged 17Ae25.
These users, who are more digitally literate and value cost savings, are highly responsive to time-sensitive and visually appealing promotional strategies.
This reinforces the strategic role of targeted digital marketing in increasing user engagement and encouraging repeated The Influence of Online Customer Review on Usage Decision Online customer reviews were also found to significantly impact user confidence and preference, especially when the reviews were detailed, timely, and perceived as credible and authentic.
These findings are aligned with the conclusions of Schepers .
, who emphasized that user-generated content, such as peer reviews, can substantially reduce uncertainty in digital environments.
Consumers tend to trust the experiences of other users more than promotional claims made by the platform itself.
Therefore, numerous and balanced reviews help prospective users assess the application's strengths and weaknesses before using The Influence of Perceived Online Customer Rating on Usage Decision Customer rating perception played a similarly strong role in influencing user decisions, as most users interpreted higher ratings as indicators of trustworthiness, reliability, and user satisfaction.
This is consistent with the findings of Ovaliana & Mahfudz .
, who noted that visual cues such as star ratings and numerical scores act as heuristics that simplify decision-making.
Among the various indicators measured, "perceived trust" emerged as the most influential factor.
When consumers perceive a high degree of trust in a platform, they are more likely to use it repeatedly and recommend it to others.
Practical Implications for E-Commerce Regarding implications.
Tokopedia should strengthen its reputation management strategy by promoting transparency in customer reviews and maintaining consistent service quality to preserve high customer ratings.
Furthermore, the platform is advised to personalize promotional strategies by leveraging user data to send relevant and timely oAers.
In doing so.
Tokopedia can increase user retention, drive conversion rates, and enhance its competitive advantage in the increasingly saturated e-commerce market.
These findings are highly relevant for stakeholders in the e-commerce industry, especially in markets where customer perception, trust, and convenience play crucial roles in determining platform loyalty and repeat This study's results support previous findings and oAer practical guidance for improving platform Limitations of this study include the reliance on convenience sampling, which may limit the generalizability of the results to a broader population.
Additionally, since the sample was restricted to Tokopedia users in Surabaya, the results may not reflect users' perceptions from other regions or cities.
Cultural, economic, and regional diAerences could influence consumer behavior and preferences in ways not The Author.
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Future studies should apply probability sampling techniques and expand the geographic scope to test the model's validity in diverse settings.
Incorporating qualitative methods such as interviews or focus groups may also yield more profound insights into the motivations behind consumer decision-making.
Conclusion In conclusion, the research confirms that promotion, online customer reviews, and customer rating perception significantly influence the decision to use the Tokopedia application in Surabaya.
These findings directly address the research questions in the introduction and highlight the critical importance of usergenerated content and platform-driven marketing in shaping consumer behavior.
The study extends prior literature by demonstrating the combined impact of perceived promotional value, review credibility, and rating trustworthiness on usage decisions.
This has important implications for Tokopedia and other ecommerce platforms seeking to optimize user experience and gain a competitive edge.
References