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php/mgt The Influence of Content Marketing and Live Streaming on Purchase Decisions on TikTok Shop through Purchase Interest as an Intervening Variable (A Case Study of TikTok Shop Users among Students of ITB Widya Gama Lumajan.
Zainul Arifin1.
Noviansyah Rizal2.
Emmy Ermawati3 Departmen of Magister Management.
Institut Teknologi dan Bisnis Widya Gama Lumajang.
Indonesia1,2,3 Corresponding Author: zainularifiin44@gmail.
ARTICLE INFO
ABSTRACT
Date of entry:
16 October 2025 Revision Date:
22 October 2025 Date Received:
01 November 2025 This study aims to examine the effects of content marketing and live streaming on purchase decisions on TikTok Shop, using purchase intention as an intervening variable .
case study of TikTok Shop users who are students at ITB Widya Gama Lumajan.
This research uses a quantitative, explanatory research design.
The population consists of TikTok Shop users who are students at ITB Widya Gama Lumajang.
Data were collected via an online questionnaire using a nonprobability sampling technique, with 102 respondents.
Data analysis was conducted using Partial Least Squares (PLS) version 4.
The results show that content marketing, live streaming, and purchase intention significantly influence purchase decisions.
Additionally, content marketing and live streaming also have a significant effect on purchase Content marketing and live streaming significantly affect purchase decisions on TikTok Shop through purchase intention as an intervening variable.
These findings highlight the importance of optimizing content marketing and live streaming strategies to increase purchase intention and consumer purchase decisions on digital Keywords: Content Marketing.
Live Streaming.
Purchase Decision.
Purchase Interest Cite this as: Arifin.
Rizal.
, & Ermawati.
The Influence of Content Marketing and Live Streaming on Purchase Decisions on TikTok Shop through Purchase Interest as an Intervening Variable (A Case Study of TikTok Shop Users among Students of ITB Widya Gama Lumajan.
Magister: Manajemen Strategis Dan Terapan, 1.
, 85Ae95.
https://doi.
org/10.
30741/mgt.
INTRODUCTION
The continuous advancement of technology has transformed the way people shop, including through social media platforms.
TikTok, which was initially intended solely for entertainment, can now be used for shopping through the TikTok Shop, launched in the United Kingdom in December 2021.
According to Rahmayanti & Dermawan .
, this feature makes it easier for users to purchase products directly in the app without switching platforms and also helps sellers and creators reach a wider audience.
As TikTok continues to grow, the TikTok Shop feature has brought significant changes to shopping habits.
According to a survey of students at ITB Widya Gama Lumajang .
TikTok is now used not only for entertainment but also for shopping.
Students have begun searching for and purchasing products directly in the application without leaving the platform.
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php/mgt products offered are highly diverse, including daily necessities, clothing, and cosmetics, which influencers or sellers often promote.
In this way.
TikTok has made shopping easier, more practical, and enjoyable for students.
The actions customers take to decide whether to purchase a product are known as the buying decision (Ramadayanti, 2.
Numerous elements, including financial situation, technology, culture, pricing, location, promotion, product, service, and the individuals involved in the process, all impact this choice, according to Alma .
One factor influencing purchasing decisions is content Content marketing is a way to attract and engage customers through various types of content, such as writing, images, videos, or audio.
This content is usually shared through websites, blogs, or social media to support business objectives.
(Chaffey dalam Ashari & Sitorus, 2.
Purchase decisions are also influenced by live streaming.
Live streaming refers to real-time broadcasts viewed simultaneously by many people over the internet, either through wired or wireless connections (Yuddin & Musfikar, 2.
Live streaming can enhance interaction between sellers and buyers, mainly when used to promote products or services, thereby encouraging consumers to make a purchase (Febriah & Febriyantoro, 2.
(Febriah & Febriyantoro, 2.
Purchase decisions are also influenced by buying Interest.
Buying Interest means that consumers begin to show Interest in a product before deciding to purchase it.
(Indika & Jovita, 2.
This Interest arises after consumers become aware of the product and its benefits.
Companies can influence buying Interest by capturing consumers' attention.
(Ayumi & Budiatmo, 2.
LITERATURE REVIEW
Purchase Decision Ramadayanti .
states that the purchase decision is the step consumers take to determine whether to buy a product.
Purchase decision is the desire of an individual to buy or use a product, whether goods or services, based on the belief that the product will provide satisfaction and the readiness to face potential risks (Deccasari, 2.
Purchase Interest Indika & Jovita .
Purchase Interest is the stage where consumers begin to show curiosity or attraction toward a product before making a buying decision.
This stage occurs after consumers become aware of the product and its benefits, leading them to develop a positive perception or Interest, but they have not yet formed a firm intention to purchase.
Purchase Interest refers to consumer behavior that reflects the extent of their desire to purchase a product (Anisa & Marlena.
Content Marketing According to Misbakhudin et al.
, content marketing is a marketing strategy that involves creating, planning, and producing high-quality content to engage an active audience or potential Additionally, content marketing can be understood as a management process where marketers identify and reevaluate public preferences by leveraging digital content, which is then distributed through electronic media (Maulidya Nurivananda et al.
, 2.
Live Streaming According to Yuddin and Musfikar .
, live streaming is an engaging and interactive medium that provides a user-centered experience by enabling real-time communication between customers and sellers.
It is considered a highly effective method for interacting with customers because it fully captures their attention and generates a high level of engagement (Deccasari, 2.
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php/mgt Relevance .
Accuracy .
Valuable .
Easy to .
Easy to find .
Consistent .
Content Marketing (X.
Exploratory Interest (Y1.
Preferential Interest (Y1.
Purchase Interest (Y.
Transaction al Interest (Y1.
Interaction .
Real-time .
Preferential Interest (Y1.
Meeting the (Y2.
Purchase Decision (Y.
Beneficial (Y2.
Product Commitment (Y2.
Purchase Speed (Y2.
Live Streaming (X.
Promotion Tool .
Source: Ferdinand .
Figure 1.
Conceptual Framework Hyphotesis H1: The Influence of Content Marketing on Purchase Decisions H2: The Influence of Live Streaming on Purchase Decisions H3: The Influence of Purchase Intention on Purchase Decisions H4: The Influence of Content Marketing on Purchase Interest H5: The Influence of Live Streaming on Purchase Interest H6: The Influence of Content Marketing on Purchase Decisions through Purchase Interest as an Intervening Variable H7: The Influence of Live Streaming on Purchase Decisions through Purchase Interest as an Intervening Variable METHODS This study employs a quantitative research approach and utilizes descriptive statistical methods to analyze the data collected through purposive sampling.
The sample size was determined based on the formula proposed by Hair et al.
, which suggests using 5 to 10 respondents for each indicator in multivariate analysis.
In this study, the researcher used the midpoint value of 6 and applied it to a total of 17 indicators, resulting in a sample size of 6 y 17 = 102 respondents.
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php/mgt RESULTS AND DISCUSSION Measurement Model Evaluation (Outer Mode.
The link between latent variables .
ependent or independen.
and their measurement indicators is the focus of measurement model analysis, often known as the outer model.
Convergent validity, discriminant validity, and composite reliability are used to assess the measurement model.
(Hair et , 2.
Source: SmartPLS Output .
Source: SmartPLS Output .
Figure 2.
Outer Model Testing Convergent Validity In PLS-SEM (Partial Least Squares Structural Equation Modelin.
, convergent validity is assessed through two leading indicators: outer loadings and Average Variance Extracted (AVE).
Outer Loading According to Hair et al.
, an outer loading greater than 0.
70 indicates that the indicator is valid because it has a strong relationship with the latent construct being measured.
Table 1.
Convergent Validity Based on Factor Loadings Indicator Outer Loading P-Value Outer
VIV
Content Marketing CM.
0,747
2,221
CM.
0,802
0,000
2,480
CM.
0,751
0,000
1,952
CM.
0,738
0,000
2,292
CM.
0,719
0,000
2,045
CM.
0,758
0,000
1,866
Live Streaming LS.
0,841
0,000
1,758
LS.
0,897
0,000
2,057
LS.
0,802
0,000
1,603
Purchase Decision KP.
0,767
0,000
1,628
KP.
0,801
0,000
1,798
KP.
0,906
0,000
3,340
KP.
0,891
0,000
3,258
Purchase Interest MB.
0,752
0,000
1,817
MB.
0,751
0,000
1,828
MB.
0,824
0,000
1,722
Variable Magister : Manajemen Strategis dan Terapan Result Valid Valid Valid Valid Valid Valid Valid Valid Valid Valid Valid Valid Valid Valid Valid Valid Volume 1.
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php/mgt Variable Indicator MB.
Source: Data processed .
Outer Loading P-Value 0,799 0,000 Outer
VIV
1,596
Result Valid Based on Table 2, all instruments have outer loadings above 0.
7, indicating that the indicators are valid measures of their constructs.
The P-values are less than 0.
05, showing that the indicators are statistically significant.
Additionally, the outer VIF values are below 5, indicating no multicollinearity among the indicators.
Average Variance Extracted (AVE) If the AVE is greater than 0.
50, the construct is considered to have good convergent validity because the indicators explain most of the variance in the latent construct.
Table 2.
Convergent Validity Based on Average Variance Extracted (AVE) Item Average Variance Extracted (AVE) Note Content Marketing Live Streaming Purchase Decision Purchase Interest Source: Data processed .
Valid Valid Valid Valid The test results show that all constructs have AVEs above 0.
5, indicating that the variables in this study have good convergent validity.
Discriminant Validity According to Hair et al.
, there are two common approaches to test discriminant validity:
cross-loading and the Fornell-Larcker criterion.
Cross Loading Discriminant validity is considered achieved when an indicator's loading on its original construct is higher than its loading on any other construct.
(Hair et al.
, 2.
Table 3.
Discriminant Validity Based on Cross-Loading Indicator Content Live Purchase Marketing Streaming Decision Content Marketing CM.
CM.
CM.
CM.
CM.
CM.
Live Streaming LS.
LS.
LS.
Purchase Decision KP.
KP.
KP.
KP.
Purchase Interest MB.
MB.
MB.
Variable Magister : Manajemen Strategis dan Terapan Purchase Interest Volume 1.
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php/mgt Variable Indicator MB.
Source: Data processed .
Content Marketing Live Streaming Purchase Decision Purchase Interest Based on Table 4 (Fornell-Larcke.
, the square root of the AVE for each variable is higher than its correlation with other variables.
This indicates that each construct has good discriminant validity.
Fornell-Larcker Criterion By comparing the square root of a concept's AVE (Average Variance Extracte.
with the correlations between that construct and other constructs, the Fornell-Larcker criterion assesses discriminant validity.
Table 4.
Discriminant Validity Based on the Fornell-Larcker criterion Variable Content Live Purchase Purchase Marketing Streaming Decision Interest Content Marketing Live Streaming Purchase Decision Purchase Interest Source: Data processed .
Table 4, (Fornell-Larcke.
shows that the square root of AVE for each variable is higher than its correlation with other variables.
This means each construct has good discriminant validity.
Composite Reliability dan CronbachAos Alpha A good Composite Reliability (CR) value is Ou 0.
70, while values between 0.
60 and 0.
70 are still acceptable for exploratory research.
A good CronbachAos Alpha value is also above 0.
70, and values 60 and 0.
70 are acceptable in the early stages of research.
Table 5.
Composite Reliability and CronbachAos Alpha Variable Composite Reliability CronbachAos alpha Content Marketing Live Streaming Purchase Decision Purchase Interest Source: Data processed .
Note Reliable Reliable Reliable Reliable The Composite Reliability and CronbachAos Alpha values indicate that all constructs meet the reliability criteria based on both measures.
Structural Model Analysis (Inner Mode.
The structural model analysis .
nner mode.
reveals that the relationships among variables align with the theoretical framework and are supported by previous research findings.
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php/mgt Source: SmartPLS Output .
Figure 3.
Pengujian Inner Model R-Square (RA) Model R-Square (RA) shows how well the independent variables explain the dependent variable in a model.
According to Hair et al.
, 0.
75 indicates a strong prediction, 0.
50 a moderate one, and 0.
weak one.
Table 6.
Inner Model Using R-Square (RA) Variable R-Square Purchase Decision Purchase Intention Source: Data processed .
Based on Table 6.
Purchase Decision has an R-Square of 69.
1%, indicating that it is explained by Purchase Intention, which Content Marketing and Live Streaming influence.
Other factors explain the remaining 30.
Purchase Intention has an R-Square of 47.
9%, showing that Content Marketing and Live Streaming explain almost half of its variation.
According to Hair et al.
these values indicate that the model has a good explanatory power.
Hypothesis Testing Hypothesis testing in the PLS-SEM model is conducted using bootstrapping, a resampling method that estimates parameter distributions.
The t-statistic and p-value determine if the relationships between constructs are significant.
According to Hair et al.
, an effect is significant if t > 1.
or p-value < 0.
This study also employs mediation analysis following Zhao et al.
and Nitzl et al.
Variable Content Marketing> Purchase Decision Live Streaming> Purchase Decision Purchase Interest> Purchase Decision Original Sample (O) Table 7.
Hypothesis Testing T statistics P values (|O/STDEV|) Hypothesis Result
3,839
Accepted 2,585 Accepted 3,493 0,000 Accepted Magister : Manajemen Strategis dan Terapan Volume 1.
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php/mgt Variable Original Sample (O) Content Marketing > Purchase Interest Live Streaming> Purchase Interest Content Marketing> Purchase Interest > Purchase Decision Live Streaming> Purchase Interest > Purchase Decision Source: Data processed .
T statistics (|O/STDEV|) P values Hypothesis Result
3,295
0,000
Accepted 4,689 0,000 Accepted 2,133 Accepted 2,728 Accepted Based on the detailed hypothesis testing, the following conclusions can be drawn:
Content Marketing has a significant effect on Purchase decisions.
With a T-statistic of 3.
839 and a p-value of 0.
000 (< 0.
, hypothesis H1 is accepted.
This means that better Content Marketing strategies tend to increase consumersAo Purchase Decisions.
Live Streaming has a significant effect on Purchase decisions.
Live Streaming shows a positive and significant influence on Purchase decisions.
The test results show a T-statistic of 2.
585 and a p-value of 0.
005 (< 0.
Therefore, hypothesis H2 is accepted.
This indicates that more effective use of Live Streaming tends to boost consumers' Purchase Decisions.
Purchase Interest significantly affects the Purchase Decision.
The test yielded a T-statistic of 493 and a p-value of 0.
000 (< 0.
, leading to acceptance of hypothesis H3.
This means that higher Purchase Intention increases the likelihood that consumers will make a Purchase Decision.
Content Marketing has a significant effect on Purchase Interest.
With a T-statistic of 3.
295 and a p-value of 0.
000 (< 0.
, hypothesis H4 is accepted.
Better Content Marketing tends to increase consumersAo Purchase Intention.
Live Streaming has a significant effect on Purchase Interest.
The analysis shows a T-statistic of 689 and a p-value of 0.
000 (< 0.
, so hypothesis H5 is accepted.
This means more effective Live Streaming use tends to raise consumersAo Purchase Intention.
Content Marketing influences Purchase Decision on TikTok Shop through Purchase Interest as an intervening variable.
The indirect effect of Content Marketing on Purchase Decision via Purchase Intention is significant .
-value = 0.
T-statistic = 2.
The direct effect is also significant and positive.
According to Zhao et al.
, this is complementary partial mediation, meaning Purchase Intention partially mediates the effect of Content Marketing on Purchase Decision.
Hence, hypothesis H6 is accepted.
Live Streaming affects Purchase decisions on TikTok Shop through Purchase Interest.
The indirect effect of Live Streaming on Purchase Decision through Purchase Intention is significant .
= 0.
T = 2.
, and the direct effect is also significant and positive.
This means Purchase Intention partially mediates the relationship between Live Streaming and Purchase Decision.
Therefore, hypothesis H7 is accepted.
The Influence of Content Marketing on Purchase Decisions Research findings indicate that content marketing plays an important role in influencing purchasing decisions on TikTok Shop, particularly among students at ITB Widya Gama Lumajang.
This strategy has proven effective in shaping positive perceptions of products and encouraging consumers to purchase, especially when the content is informative, engaging, and relevant to their needs.
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php/mgt aligns with the views of Maulana & Roosdhani .
, who state that content marketing can increase consumer confidence and reduce uncertainty in the decision-making process, as consumers feel more assured about the benefits and quality of the products offered.
However, a different perspective is presented by Abdjul et al .
, who argue that content marketing does not directly influence purchasing decisions.
Its impact largely depends on supporting factors such as content quality, source credibility, and alignment with consumer needs and preferences.
Therefore, while content marketing has great potential to influence purchasing decisions, its effectiveness cannot be separated from the context and characteristics of the target audience.
The Influence of Live Streaming on Purchase Decision Research findings show that live streaming significantly influences purchasing decisions on TikTok Shop, especially among students at ITB Widya Gama Lumajang.
Effective live streaming helps create positive perceptions of products and encourages consumers to buy by providing real-time interaction and clear product demonstrations.
This supports Yuddin & Musfikar's .
view that live streaming is an engaging medium that allows direct communication between sellers and buyers, increasing consumer trust and involvement.
According to Ramadayanti .
, purchasing decisions depend on consumersAo confidence in the productAos ability to satisfy their needs and their readiness to accept risks.
Live streaming helps build this confidence through honest, interactive presentations.
However.
Zahro .
argues that live streaming does not always directly affect purchasing decisions, as its impact depends on factors such as content quality and consumer preferences.
Therefore, while live streaming can strongly influence buying decisions, its effectiveness varies based on how well it is executed and who the target audience is.
The Influence of Purchase Interest on Purchase Decisions Research findings show that purchase intention significantly affects purchasing decisions on TikTok Shop, especially among students at ITB Widya Gama Lumajang.
Higher purchase intention directly encourages consumers to buy.
This aligns with Indika & Jovita .
, who define purchase intention as the consumer's Interest in a product before deciding to buy.
This Interest develops after consumers recognize the product and its benefits.
Anisa & Marlena .
add that firm purchase intention makes the buying decision easier, supported by Ramadayanti .
, who explains that purchasing decisions depend on whether consumers decide to buy or not.
Deccasari .
states that this decision is influenced by confidence in product satisfaction and readiness to face risks.
Therefore, high purchase intention acts as a bridge between initial perception and the final buying decision on platforms like TikTok Shop.
This is supported by Mukarromah .
and Iriani .
, who found a positive effect of purchase intention on buying decisions.
However.
Yuliviona .
argues that purchase intention does not significantly influence purchasing decisions, suggesting that its impact may vary based on other factors.
The Influence of Content Marketing on Purchase Interest Research findings show that content marketing significantly affects purchase intention among TikTok Shop users, especially students at ITB Widya Gama Lumajang.
Effective content marketing increases consumers' Interest in buying products by providing accurate and relevant information.
This supports Misbakhudin et al.
, who explain that content marketing involves creating and sharing quality content that attracts and engages potential buyers.
Indika & Jovita .
also state that purchase intention occurs when consumers recognize a product and see its benefits.
Therefore, good content marketing not only informs but also encourages consumers to want to buy.
This is supported by Antika and Maknunah .
and Iriani .
, who found a positive link between content marketing and purchase intention.
However.
Sholihin et al.
argue that content marketing does not always significantly influence purchase intention, depending on other factors.
The Influence of Live Streaming on Purchase Interest Research shows that live streaming on TikTok Shop significantly affects purchase intention, especially among students at ITB Widya Gama Lumajang.
When live streaming effectively demonstrates products and answers questions in real Time, it increases users' Interest in buying.
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php/mgt Yuddin & Musfikar .
explain that live streaming allows direct interaction between sellers and buyers, making the experience more engaging and building trust.
Students feel more confident to buy after seeing live demos and getting answers during the stream.
This trust boosts their purchase According to Deccasari .
, when purchase intention is firm, consumers decide if the product will satisfy them and if they are ready to take risks.
Live streaming helps speed up this decision by providing clear information and real-time interaction.
Fakri & Astuti .
support this positive effect, but Ginting & Harahap .
argue that live streaming does not always influence purchase intention, depending on other factors.
The Influence of Content Marketing on Purchase Decisions Through Purchase Interest Research shows that purchase intention acts as a bridge between content marketing and buying Effective content marketing with accurate and interesting information not only influences decisions directly but also increases purchase intention, which then leads to buying.
This is seen among TikTok Shop users, especially students at ITB Widya Gama Lumajang, who are more likely to buy after being drawn to high-quality content.
According to Ashari & Sitorus .
, content marketing involves creating and sharing media to attract and engage consumers.
When content is trusted and relevant, it increases Interest and drives purchase intention, as explained by Indika & Jovita .
Deccasari .
adds that buying decisions depend on the belief that the product will satisfy and the readiness to take risks.
Therefore, content marketing helps shape purchase intention, which in turn encourages actual purchases.
This is supported by Deccasari .
and Iriani .
, though Zahro .
argues that content marketing may not always affect purchase intention The Influence of Live Streaming on Purchase Decisions Through Purchase Interest Research shows that purchase intention plays an important role in live streaming and buying Live streaming offers real-time interaction that makes consumers feel more involved, increasing their Interest and encouraging them to buy.
This is seen among TikTok Shop users, especially students at ITB Widya Gama Lumajang, who are more likely to buy after watching live product demonstrations.
According to Yuddin and Musfikar .
, live streaming enables direct communication, thereby building consumer engagement.
Purchase intention happens when consumers recognize and value the product, as explained by Anisa & Marlena .
Deccasari .
adds that buying decisions are driven by the belief that the product will satisfy needs and by the willingness to take risks.
Thus, live streaming helps build confidence and drives purchases.
This is supported by Deccasari .
and Diany & Yuliyanti .
, although Zahro .
suggests purchase intention may not always mediate this effect.
CONCLUSION
Based on the research findings regarding the influence of content marketing and live streaming on purchase decisions, with purchase intention as an intervening variable among TikTok Shop users who are students at ITB Widya Gama Lumajang, it can be concluded that both content marketing and live streaming have a positive and significant effect on purchase intention and purchase Purchase intention also plays an important role, showing a positive and significant impact on purchase decisions.
Furthermore, content marketing and live streaming influence purchase decisions not only directly but also indirectly through purchase intention as an intervening variable.
This indicates that these marketing strategies are effective in increasing consumer interest and confidence in the TikTok Shop platform, especially among ITB Widya Gama Lumajang students.
REFERENCES