Factors Affecting Customer's Purchase Decision of Makeup Products From Local Brands On TikTok Live Streams

Social media platforms have drastically reshaped communication, content sharing, and consumption in the fast-evolving digital era. TikTok, a prominent platform, has gained substantial influence in Indonesia, becoming a significant force in the business world. This study examines the factors that affect consumer purchase decisions for local makeup products during TikTok live-streaming sessions. Utilizing a mixed-methods approach, the research integrates qualitative and quantitative methods to understand consumer behavior comprehensively. Qualitative data is analyzed through manual coding, offering detailed insights into consumer perceptions and motivations. Quantitative data is assessed using Partial Least Squares Structural Equation Modeling (PLS-SEM) to identify statistical relationships and patterns. The study involves a minimum of 12 participants for qualitative analysis and 200 for quantitative analysis, focusing on beauty enthusiasts familiar with TikTok's live-streaming features. The research aims to uncover how live streaming influences purchasing decisions and provides actionable insights for local beauty brands. By leveraging TikTok's interactive capabilities, the findings will help these brands enhance their marketing strategies and engage more effectively with their target audience. This study contributes to understanding the impact of social media on consumer behavior and offers practical recommendations for maximizing the potential of live streaming in the beauty industry.


A. INTRODUCTION
Social media platforms have fundamentally transformed communication, content sharing, and consumption in today's digital era.TikTok, in particular, has emerged as a significant player, especially in Indonesia, where it substantially influences the business landscape.Indonesia is the second-largest market globally for TikTok users, with the platform's user base increasing from 38.7% to 63.1% in the past year.Tech Wire Asia highlights that Indonesia is home to approximately 125 million TikTok users and hosts about two million small businesses on TikTok Shop, underscoring the platform's growing impact.Factors driving this growth include widespread cellphone usage, a tech-savvy youth demographic, and effective localization strategies.

Figure 1. Countries With the Most TikTok Users Worldwide
The image depicts a remarkable surge in global consumer spending on TikTok, reaching $3 billion within a year, highlighting the platform's growing significance and influence on digital consumer behavior.This rapid increase underscores TikTok's ascent as a major global player, with users increasingly engaging with its diverse features and content.TikTok's swift rise to $3 billion in consumer spending reflects its immense appeal and substantial impact on global digital consumption trends.
TikTok continually updates its features to enhance user experience, such as introducing "TikTok Live" in late 2019.This feature allows users to participate in live audio and video broadcasts with interactive chat, merging live streaming and e-commerce.Live streaming enables brands to dynamically showcase products, demonstrate application techniques, display real-time results, and address customer queries, fostering trust and deeper customer connections.TikTok Shop's seamless integration with live streaming facilitates effortless purchases during broadcasts.This integration, flash sales, and discounts create a compelling online shopping experience for beauty enthusiasts (Kim et al., 2021).The platform's short-form video format and viral content algorithm drive impulsive buying (Zhang et al., 2023).TikTok Shop leverages a network of Key Opinion Leaders (KOLs) and live-stream hosts who enhance sales through dedicated followings and bolster trust and authenticity (Chen et al., 2021).
The recent closure of TikTok Shop and the acquisition of Tokopedia mark significant shifts in the digital commerce landscape, reflecting TikTok's strategic push to expand its market share in Southeast Asia.
Local beauty brands can capitalize on TikTok Shop's live streaming to directly engage with targeted audiences, build authenticity, and foster trust.This study analyses factors influencing consumer purchase decisions for local makeup products during TikTok live sessions, focusing on developing a decision-making model for online shoppers.The research from October 2023 to July 2024 will investigate the impact of TikTok Shop's live streaming on consumer behavior towards local cosmetic brands.

B. RESEARCH METHOD
This study uses quantitative and qualitative approaches to investigate the factors influencing consumers' decisions to purchase cosmetics from regional brands during TikTok Shop live streaming.The qualitative component involves conducting in-depth interviews to understand better the specific aspects affecting consumer behavior and preferences during live streaming sessions.These interviews aim to uncover the critical elements influencing consumer decision-making processes related to TikTok live streaming.Quantitative surveys validate and expand upon the interview findings following the qualitative phase.These surveys will assess how the identified factors impact consumer purchase decisions and comprehensively evaluate these influences.The study focuses on individuals aged 18 to 34, particularly those who have made cosmetic purchases through TikTok Live Streaming.
Quantitative data will be analyzed using descriptive statistics to summarize and identify relationships between variables within the sample (Trochim, 2006).This method is crucial for coding and organizing data for further examination (Field, 2013).Additionally, the study will employ Partial Least Squares (PLS) analysis to build predictive models and explore the relationships between multiple correlated variables (Wold, 1982).PLS is chosen for its flexibility in handling exploratory research models, allowing for testing theories, identifying correlations, and suggesting areas for further research (Lohmöller, 1989).This dual approach aims to provide a nuanced understanding of consumer behavior in the context of TikTok Shop live streaming.

Qualitative Approach Analysis
As previously mentioned, the qualitative data collection for this study employs semi-structured interviews.Non-probability sampling, specifically purposeful selection, targets respondents who meet specific criteria.The focus is on individuals aged 18 to 34 who have purchased local beauty products and have engaged with TikTok live streaming.This demographic is crucial due to its significant influence on consumer patterns and behaviors in the digital economy.

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The study interviewed twelve female residents of Jabodetabek, aged 18 to 21, who met these criteria.This group was selected because they represent the target demographic of young adults with experience purchasing makeup from local brands and interacting with TikTok live streams.Interviews were conducted between May 31 and June 2, 2024.The researcher determined that data saturation was achieved, as additional interviews did not provide new insights beyond what was already gathered.This indicates that the volume and quality of information collected were sufficient to address the study's objectives.

Interview Result
Based on the interviews, ten out of twelve respondents indicated that the quality of the argument presented by the host plays a significant role in their decision-making process.Respondents prefer straightforward, informative hosts and provide comprehensive details, including product cost, quality, materials, availability, and shade variations.Additionally, ten respondents noted that the host's credibility positively impacts their trust and acceptance of the information.They valued hosts with expertise, in-depth product knowledge, and the ability to offer practical advice.Hosts with a strong background in the beauty industry, professionalism, and experience are seen as more trustworthy.The ability of hosts to engage viewers, provide personalized recommendations, and effectively demonstrate product use enhances viewer trust and increases the likelihood of purchase.
Conversely, seven respondents mentioned that the physical appearance of TikTok presenters did not significantly affect their purchasing decisions or acceptance of information.Instead, respondents valued knowledge, clarity, and the host's interactive and entertaining abilities more.All twelve respondents agreed that their perception of the host significantly influences their information absorption during live shopping streams.Trust in the presenter is crucial in persuading viewers and influencing their purchase decisions.Hosts perceived as genuine and reliable are more likely to have their information accepted.
Moreover, twelve out of twelve respondents confirmed that the information provided by TikTok live shopping hosts greatly affects their buying decisions.Viewers trust knowledgeable, transparent, and responsive hosts, especially when discussing beauty products and potential concerns.The interviews revealed that nine respondents make immediate purchases after forming an intention during live streams, indicating a direct influence of live streaming on their buying decisions.Even those who conducted further research acknowledged that live streaming had a preliminary impact on their purchasing intentions.

Pilot Test
A pilot test will be conducted to refine the research process and improve the questionnaire prior to the full-scale data collection.This crucial step allows researchers to identify potential issues with the tool, assess participant comprehension, and address logistical challenges.By proactively addressing these aspects, the final study is more likely to achieve high internal validity and reliability [5].The pilot study was carried out on May 23, 2024, involving 41 participants.The researcher evaluated the reliability and validity of the collected data using the SmartPLS program.

Validity Test for Framework
A validity test in research determines how effectively an instrument measures the intended constructs.This is commonly assessed using structural equation modeling (PLS-SEM).Specifically, the Average Variance Extracted (AVE) value is used to evaluate convergent validity with the SmartPLS program [6].AVE is calculated by squaring and averaging each indicator's loadings on its respective construct.An AVE value of 0.50 or greater suggests that the construct explains at least 50% of the item variance.The results of the validity test for the theoretical framework in this study, which involved 41 respondents, are as follows: Source: Research data, 2024 The computation shows that all variables, except the Source Credibility variable, are considered valid (above 0.50).Upon examining the indicators contributing to the Source Credibility variable, the researcher identified one indicator with the weakest association with the latent variable.In reflective measurement models, these associations-represented by the arrows connecting the latent variable to its indicators-are known as outer loadings.These outer loadings highlight the specific impact of each indicator on its respective construct.The indicators are listed below: Table 2. Outer Indicators Label Indicator Outer Loading SC1 I believe the information given by makeup experts who present live streams.0,690 SC2 I believe TikTok live-streaming hosts are truthful about the products they advertise.0,654 SC3 Information from livestream hosts with a lot of product experience is more likely to be accepted by me.0,892 SC4 Regarding TikTok live streaming, the reliability of the live-stream hosts affects my purchasing decision.0,698 SC5 I trust live stream hosts that frequently give reliable information.0,733 SC6 I depend on live-stream hosts that have a solid track record of honesty.0,737 SC7 I find live-stream hosts that talk about their own experiences with the product to be more trustworthy.0,729 SC8 Regarding live-stream hosts, I like those who are knowledgeable about the products they recommend.0,793 SC9 I trust live-stream hosts who are open about their endorsements and sponsorships.0,478 SC10 My acceptance of the information given by the livestream host largely depends on their credibility.0,583 Source: Research data, 2024 When an indicator is removed, the Average Variance Extracted (AVE) may increase, suggesting that the removed indicator might have had a weak relationship with the underlying construct.Indicators with outer loadings between 0.40 and 0.70 fall into a "grey area."Although these indicators contribute less to the construct, those with higher loadings may more effectively capture its essence.Therefore, the researcher considered removing an indicator if doing so would enhance the overall construct validity, as measured by AVE, especially if the indicator had an outer loading of less than 0.50.After deciding to exclude SC9, the researcher's findings are presented below.

Qualitative Analysis
The age distribution of the responses shows that 43% of the sample, the majority, falls within the 22 to 25 age range.The remaining age categories are 18-21 (33.9%), 26-30 (21.3%), and a small percentage (1.8%) in the 31-34 age group.This suggests that the survey primarily targeted a younger audience, with a substantial representation of early adult age groups.The gender breakdown reveals that 77.4% of respondents are women, while 22.6% are men, indicating that women may be more interested in beauty products, especially in TikTok Shop live streams.
The data presents a geographically diverse sample, with respondents from various regions.Jakarta accounts for the highest percentage (21.3%),followed by Bandung (20.4%),Depok (17.2%),Bogor (16.3%),Tangerang (14.5%), and Bekasi (10.4%).This geographic variation aids in understanding regional preferences and behaviors related to TikTok Shop live streaming.The occupation distribution shows that 61.1% of respondents are employees, while 37.1% are students, with smaller percentages being entrepreneurs and university students.This suggests that most viewers interacting with TikTok Shop live streams for beauty products are students or working-age individuals.Additionally, 54.3% of respondents reported watching live streams on TikTok more than four times per week, 15.4% watch three to four times per week, and 30.3% watch one to two times per week.This high level of engagement with live-streaming content indicates the platform's growing influence on purchase decisions.

Descriptive Analysis for Framework
The factors with the highest average scores across all categories influence customers' decisions to purchase beauty products during TikTok live streaming.The statement "I believe the information from livestream hosts who align with my preferences and principles" received the highest mean score of 4.26, indicating that viewers are more likely to trust information from hosts who share similar beliefs and interests.This alignment fosters a stronger bond and sense of trust, enhancing the persuasiveness and credibility of the information provided.Similarly, the statement "When I consider the live stream to be persuasive and informative, my desire to buy is increased" also received a high mean score of 4.26.This suggests that both the persuasiveness of the live stream and the quality of its content are key factors influencing consumers' purchase intentions.Viewers who find a live stream convincing and informative are more inclined to purchase.
On the other hand, the areas with the greatest response variability, as indicated by the highest standard deviation scores, highlight the diversity of opinions among respondents.The statement "TikTok live streaming with timely and well-structured information is more convincing in my opinion" had a standard deviation of 1.08, suggesting that while many respondents find well-organized content persuasive, there is significant variation in how strongly this opinion is held.Additionally, "I often turn to TikTok live streaming for information when I am thinking about buying new makeup" had a standard deviation of 1.07, indicating that respondents' reliance on information from live streams varies considerably.This variation reflects different levels of trust and dependence on electronic word of mouth (eWOM) when making purchase decisions.The researcher will analyze the quantitative data using PLS-SEM, which will also be employed to demonstrate the investigation's findings within the conceptual framework.This approach will help determine whether electronic word-of-mouth (eWOM) and information acceptance influence consumers' decisions to purchase local beauty products on TikTok.The PLS-SEM model developed for this investigation is shown above.│ 173

Statistical Analysis for Framework
The structural path significance test results reveal that Argument Quality significantly and positively impacts Electronic Word of Mouth (E-WOM), with an original sample coefficient of 0.382 and a p-value of 0.000.Source Credibility also substantially and positively affects E-WOM, with an original sample coefficient of 0.179 and a p-value of 0.026.Source Attractiveness significantly influences E-WOM, with an original sample coefficient of 0.241 and a p-value of 0.010.Source Perception positively affects E-WOM, with an original sample coefficient of 0.202 and a p-value of 0.036.Additionally, E-WOM significantly increases Purchase Intention, with an original sample coefficient of 0.347 and a p-value of 0.000.Finally, Purchase Intention substantially and positively impacts Purchase Decision, with an original sample coefficient of 0.497 and a p-value of 0.000.

Coefficient of Determination (R2)
The coefficient of determination values in the table provide insight into how well the independent variables explain the variance in the dependent variables.For Electronic Word of Mouth (E-WOM), the R² value of 0.644 indicates that the independent variables account for 64.4% of E-WOM variance.In the case of Purchase Intention (PI), the R² value of 0.12 shows that the independent variable, IA E-WOM, explains 12% of the variation in Purchase Intention.For Purchase Decision (PD), an R² value of 0.247 indicates that 24.7% of the variance in Purchase Decision is attributed to Purchase Intention.These findings suggest that the model explains a substantial portion of E-WOM variance, a moderate amount in PD, and a smaller but still meaningful portion in PI.Source: Research data, 2024 The effect sizes (f²) of the linkages between the model's constructs reveal the impact of each independent variable on the dependent variables.In this study, Argument Quality (AQ) has a moderate effect on Information Acceptance (IA E-WOM), with a medium effect size of 0.243.In contrast, Source Credibility (SC) shows a minimal effect size of 0.057 on IA E-WOM, indicating a negligible contribution.Similarly, Source Attractiveness (SA) and Source Perception (SP) have relatively small yet significant effects on IA E-WOM, with effect sizes of 0.104 and 0.075, respectively.The impact of IA E-WOM on Purchase Intention (PI) is significant, as demonstrated by its medium effect size of 0.329.Conversely, the effect of PI on Purchase Decision (PD) is marginal, with a small effect size of 0.137.While SC, SA, SP, and PI have minor but significant effects on their respective outcomes, Argument Quality, and IA E-WOM have larger overall impacts.
Mediation analysis, which examines the effect of a third variable on the relationship between two other variables, helps to understand how a mediator variable explains the phenomenon.This approach assesses how well a mediator variable, such as IA E-WOM, explains the relationship between independent variables (source attractiveness, argument quality, source perception, and source credibility) and the dependent variable, Purchase Intention (PI).Following the mediation analysis requirements ensures a comprehensive understanding of how the mediator indirectly affects the outcome of the predictor variable.9's findings highlight the overall impact of the independent factors-Argument Quality (AQ), Source Credibility (SC), Source Attractiveness (SA), and Source Perception (SP)-on the dependent variable, Purchase Intention.The results reveal that the combined effect of AQ, SC, and SA on Purchase Intention is significant, indicating that these factors collectively influence buying intention.However, Source Perception (SP) did not significantly impact Purchase Intention, as its p-value exceeded 0.05.This suggests that while AQ, SC, and SA play a crucial role in shaping Purchase Intention, Source Perception does not significantly contribute to this outcome in the context of this study.10's conclusions reveal that the mediating variable, Information Acceptance (IA) in electronic Word of Mouth (eWOM), is significantly influenced by the independent factors-Argument Quality (AQ), Source Credibility (SC), Source Attractiveness (SA), and Source Perception (SP).The results demonstrate that Source Attractiveness (T = 2.572, P = 0.000), Source Credibility (T = 2.226, P = 0.000), and Argument Quality (T = 3.794, P = 0.000) all have significant positive effects on IA in eWOM.With T-statistics exceeding 1.96 and p-values below 0.05, these findings indicate strong and statistically significant relationships between the independent and mediating variables.The significance of these correlations supports the progression of the mediation analysis to the next phase.11's conclusion highlights the role of Information Acceptance (IA) in eWOM as a mediating variable in the relationship between the independent factors and Purchase Intention (PI).The findings indicate that IA in eWOM is significantly influenced by Argument Quality (AQ) (T = 3.794, P = 0.000), Source Credibility (SC) (T = 2.194, P = 0.028), and Source Attractiveness (SA) (T = 2.572, P = 0.010).Additionally, IA in eWOM substantially affects Purchase Intention (T = 4.309, P = 0.000).These results underscore that IA in eWOM is crucial for transmitting the effects of the independent factors on Purchase Intention.The mediation analysis confirms that the independent variables influence Purchase Intention through IA in eWOM, validating the mediation effect.The second mediation path examines IA in eWOM as an independent variable, Purchase Intention as a mediating variable, and Purchase Decision (PD) as a dependent variable.12's conclusion confirms a significant positive relationship, as evidenced by a T-statistic of 3.119, which exceeds the critical value of 1.96 and a P-value of 0.001, below 0.05.This result validates the hypothesis that Information Acceptance (IA) in eWOM positively influences Purchase Decisions (PD).
│ 175 Consequently, the mediation test can proceed to the next phase, supported by these findings that affirm the mediating role of IA in eWOM on the impact of independent variables on purchase decisions.Source: Research data, 2024 Table 13's conclusion illustrates the effect of the mediating variable, Information Acceptance (IA) in eWOM, on Purchase Intention (PI) in the second path of the mediation test.The results indicate a highly significant and positive association, with a P-value of 0.000 and a T-statistic of 4.309, well above the critical value of 1.96.This confirms the strong impact of IA in eWOM on Purchase Intention, supporting the mediation effect in the model.Source: Research data, 2024 Table 14's conclusion presents the results from the final stage of the mediation test for the second path.The findings reveal that Purchase Intention (PI) remains significantly impacted by Information Acceptance (IA) in eWOM, with a T-statistic of 3.199 and a P-value of 0.010.Additionally, Purchase Intention exerts a crucial effect on Purchase Decision (PD), evidenced by a T-statistic of 6.578 and a P-value of 0.000.These results demonstrate that IA in eWOM, as the mediating variable, effectively channels its influence on Purchase Decision through Purchase Intention.The significant outcomes for both pathways validate the mediation effect, highlighting the critical roles of IA in eWOM and PI in purchasing decisions.

Discussion
The analysis results provide robust support for several key hypotheses regarding the influence of various factors on information acceptance and purchase decisions.The data confirms the hypothesis that well-structured and coherent arguments significantly enhance the acceptability of information via electronic word-of-mouth (eWOM).With a T-value of 3.794, surpassing the critical value of 1.96, and a p-value of 0.000, the path coefficient of 0.382 indicates that convincing and well-organized arguments greatly improve consumers' likelihood of accepting product information presented during TikTok live streams.
Similarly, the impact of source credibility on information acceptance is validated by a path coefficient of 0.179, a T-value of 2.226 (greater than 1.96), and a p-value of 0.000.This suggests that information from credible and knowledgeable live-stream hosts is more likely to be trusted and accepted by viewers.The attractiveness of live-stream hosts also plays a significant role, with a path coefficient of 0.241 and a T-value of 2.572, exceeding the critical value of 1.96 and a p-value of 0.01.This indicates that likable and appealing hosts enhance the adoption of information via eWOM.
Moreover, the analysis supports the positive effect of source perception on information acceptance, as evidenced by a path coefficient of 0.202, a T-value of 2.095 (greater than 1.96), and a p-value of 0.01.This suggests that viewers' perceptions of a source's sincerity and authenticity significantly impact their acceptance of information.The hypothesis that higher information acceptance leads to increased purchase intention is also confirmed, with a path coefficient of 0.347, a T-value of 4.309, and a p-value of 0.022.This implies that their purchase intention increases when viewers find the information credible and reliable.
Finally, the analysis shows a substantial positive correlation between purchase intention and actual purchase decisions, with a path coefficient of 0.497, a T-value of 6.578, and a p-value of 0.037.This indicates that viewers with higher purchase intentions are likelier to follow through with actual purchases after engaging with TikTok live stream content.These findings underscore the significant roles of argument quality, source credibility, source attractiveness, and source perception in influencing information acceptance and purchase decisions through TikTok live streaming.

D. CONCLUSION
The survey's findings reveal that the antecedents of information acceptance in electronic word-ofmouth (eWOM) significantly impact consumer decisions regarding beauty products on TikTok live streaming.The analysis shows that Argument Quality (AQ) plays a crucial role, with a T-value of 3.794 and a p-value of 0.000, indicating a significant positive effect on Information Acceptance (IA).This suggests that coherent and persuasive arguments during live streaming enhance users' trust and acceptance of product information.Viewers are more inclined to accept and believe in product details when presented well-organized and compellingly.
Additionally, Source Credibility (SC) demonstrates a favorable impact on IA in eWOM, with a Tvalue of 2.226 and a p-value of 0.000.This underscores the importance of the host's expertise and reliability in gaining viewers' trust and acceptance.Similarly, Source Attractiveness, with a T-value of 2.572 and a pvalue of 0.000, positively influences information acceptance, highlighting the role of engaging and appealing hosts in boosting viewers' acceptance of information.Furthermore, Source Perception-encompassing the host's authenticity and sincerity-also has a significant positive effect on information acceptance, as indicated by a T-value of 2.095 and a p-value of 0.01.This emphasizes that viewers are likelier to accept information from hosts they perceive as genuine and trustworthy.
Overall, the study underscores the substantial impact of host behavior on TikTok Shop's live streaming, particularly for local beauty brands.Source Credibility is crucial in securing viewers' trust and ensuring the acceptance of presented information.The professionalism and dependability of live-stream hosts are key factors in influencing consumers' purchasing decisions.Consumers are more likely to trust and act on advice and information provided by hosts perceived as knowledgeable and credible..

Figure 2 .
Figure 2. PLS-SEM Result Source: Research data, 2024The researcher will analyze the quantitative data using PLS-SEM, which will also be employed to demonstrate the investigation's findings within the conceptual framework.This approach will help determine whether electronic word-of-mouth (eWOM) and information acceptance influence consumers' decisions to purchase local beauty products on TikTok.The PLS-SEM model developed for this investigation is shown above.Table5.Indicator Reliability Result

Figure 3 .
Figure 3. Discriminant Validity Result Source: Research data, 2024 The computation results indicate that the model satisfies the requirements for discriminant validity, as evidenced by the Fornell-Larcker criterion, where the values in the top row are greater than those in the rows below.Collinearity testing, a statistical technique used to assess the extent of multicollinearity among predictor variables, is crucial in evaluating the measurement model, which examines the relationship between latent components and observed indicators.The test results suggest the model is free of multicollinearity issues, as all VIF coefficients are below five.

Figure 3 .
Figure 3. Bootstrapping Result Source: Research data, 2024 The structural paths in the model illustrate the proposed directions or causal relationships between the latent variables.T-statistics for both the outer and inner models are generated using the bootstrapping procedure in PLS-SEM to assess these paths' statistical significance and relevance.A T-statistic value greater than 1.96 indicates the importance of the model.Once the indicator weights' statistical significance is confirmed, each indicator's relevance is evaluated.Bootstrapping also helps determine the relevance of path coefficients, which typically range from -1 to +1.Weights close to +1 or -1 indicate strong positive or negative correlations.Following a thorough assessment of the measurement model, the focus shifts to evaluating the structural model.Key evaluation criteria include the blindfolding-based cross-validated redundancy measure (Q2), the coefficient of determination (R2), and the statistical significance and applicability of the path coefficients.Higher R2 values, ranging from zero to one, indicate greater explanatory power, with values of 0.75, 0.50, and 0.25 typically considered substantial, moderate, and weak, respectively.Smaller differences between expected and observed values, reflected in larger Q2 values, indicate stronger predictive accuracy.Q2 values for endogenous constructs should be greater than zero to demonstrate the structural model's prediction accuracy.

Table 1 .
First Validity Pilot Test

Table 3 .
First Validity Pilot TestReliability Test for Framework DevelopmentSince this study is exploratory and the investigator is developing a new scale or instrument, a Cronbach's alpha of 0.50 to 0.70 may be deemed acceptable.The researcher can conclude that the questionnaire data is sufficiently reliable based on Cronbach's alpha ratings.As a result, additional samples can be collected using the same questionnaire.

Table 5 .
Indicator Reliability Result The data in the above table indicates that every indicator appears to have values higher than 0.7.This suggests that every indication is credible.The results for each construct, as indicated by Cronbach's alpha and composite reliability table, are greater than 0.70.This suggests that all the constructs in the calculated model are reliable.

Table 11 .
Mediation Test Step 3 Result (First Path)

Table 13 .
Mediation Test Step 2 Result (First Path)

Table 14 .
Mediation Test Step 2 Result (First Path)