Commerce Platform Research Articles

Navigating the Social Shift: A Preliminary Study of Consumer Behavior on Malaysia's Social Commerce Platforms

The proliferation of online businesses coupled with the advancement of information and communication technologies (ICT) has led to the emergence of social commerce. The integration of social media platforms into e-commerce offers businesses a convenient avenue for engaging with consumers and a novel method for capturing additional sales volume. This seamless integration of social media platforms into current e-commerce practices has significantly increased its success. Research on the factors that affect purchase intentions in social commerce is still sparse, especially in the context of Malaysian consumers. In general, the causal model of purchase intentions on social commerce in this study aims to investigate the impact of the constructs of visibility and metavoicing on purchase intentions among Malaysian millennial consumers. Henceforth, this initial study specifically aims to evaluate the reliability and validity of the IT affordance constructs of visibility and metavoicing through rigorous assessments. At the items-construct level, the internal consistency assessment was conducted using McDonald’s Omega, which is known for its robustness in measuring the reliability of multi-item constructs. At the construct level, discriminant validity and the strength of linear relationships among variables were assessed using Pearson correlation analysis. The pilot dataset gathered was analyzed with SPSS 29, and the results have validated that the predictive model achieved high levels of reliability and validity at both the item and construct levels. Furthermore, the analysis revealed that the independent variables, metavoicing and visibility, have a significant association with purchase intentions, underscoring their importance in understanding consumer behavior.

Predicting user behavior on s-commerce platforms: a novel model

PurposeThis study investigates the influence of the wisdom of the crowd (WSC), trust and perceived value on consumer purchase intentions within social commerce (s-commerce) platforms. By constructing a novel theoretical model, the research aims to delineate the interrelationships among these variables, addressing an emerging area in social interactions and information technology.Design/methodology/approachTo empirically test and validate the proposed model, the study collected data from 442 Facebook users familiar with online shopping. The analysis employed Structural Equation Modeling – Partial Least Squares (SEM-PLS) to test the hypotheses and examine the relationships between WSC, trust, perceived value and purchase intentions.FindingsThe findings confirm that WSC significantly influences trust, perceived value and the intention to purchase on s-commerce platforms. Both perceived value and trust are substantial determinants of purchase intentions. Notably, the PLS analysis revealed that WSC accounts for 36.8% of the variance in trust and 33.1% of the variance in perceived value related to purchasing decisions on s-commerce platforms.Originality/valueThis research contributes uniquely to the ongoing discourse on s-commerce adoption by integrating WSC as a pivotal factor in understanding perceived value and consumer adoption intentions. It provides a fresh perspective on how collective intelligence affects consumer behavior in digital marketplaces, enriching the theoretical and practical understanding of s-commerce dynamics.

The effect of the product categories diversity recommended on cross‐buying in electronic commerce platforms: The moderating role of user navigation heterogeneity

AbstractE‐commerce platforms encourage consumers' cross‐buying behavior to boost user traffic and trading volume. However, balancing the precision and richness of recommended information with the mechanisms influencing consumer cross‐buying remains unclear, which also poses challenges to the specific operation of these platforms. Therefore, this study leverages extensive online behavioral data from an e‐commerce platform, encompassing detailed records of 26,034 consumers. By employing unsupervised machine learning algorithms to distinguish the heterogeneity of consumer browsing, we apply clickstream data to explore the mechanisms of the impact of information diversity, specifically the breadth and depth of recommended product categories, on cross‐buying. This study reveals that the effect of diverse recommendations on online decision‐making undergoes marginal variations due to alterations in both the breadth and depth of these recommendations. Specifically, the depth and breadth of recommended product categories exhibit an inverted U‐shaped relationship with cross‐buying, initially promoting, and subsequently suppressing it. Additionally, consumers with different browsing behavior characteristics respond differently to recommendation diversity. Confused visitors and hedonic visitors positively moderate the depth of information and negatively moderate the breadth of recommendations with the inverted U‐shaped effect on cross‐buying. Search‐oriented visitors positively adjust the inverted U‐shaped relationship between the depth of information and the breadth of recommendations on consumer cross‐buying. This study enriches research on cross‐buying in the domain of recommendations on e‐commerce platforms from the perspective of information diversity, providing valuable insights for optimizing recommendation strategies, promoting cross‐buying behavior, and enhancing consumer loyalty.

What drives social shopping in social commerce platform? The effects of affordance, self-congruity and functional-congruity

PurposeSocial group system and social tagging system, which leverage the psychological mechanisms underlying group influence and social tags to drive consumer behaviors, have been prevalent in the social commerce platform. However, limited studies have examined how the affordances of social group system and social tagging system influence consumers’ social shopping behavior. The purpose of this study is to examine the formation of social shopping behavior in the social commerce platform.Design/methodology/approachCombining affordance theory with dual-congruity theory, we develop a model to examine how the affordances of social group system and social tagging system influence consumers’ social shopping behavior through the underlying self-congruity and functional-congruity processes. We empirically validate the research model using a multimethod approach, including an instrument development study and a field survey study.FindingsOur empirical findings show that social support positively influences relational identity, while it has a nonsignificant effect on social identity. Social interactivity positively influences relational identity and social identity. Furthermore, social tagging quality and social endorser credibility positively affect perceived diagnosticity and perceived serendipity. Finally, relational identity, social identity, perceived diagnosticity and perceived serendipity collectively determine consumers’ social shopping intention.Originality/valueThis study contributes to the theoretical understanding of social shopping in social commerce and offers practical implications for designing an effective social group system and social tagging system to boost product sales.

Construction of Cross-Border E-Commerce Supply Chain of agricultural food products Based on Blockchain Technology

The European Union has for several years been a critical export market and a significant source of imports for us, and the US has, in general, kept closed domestic players vis-à-vis the EU. However, given the variety of alternative market conditions and EU forms, the attractiveness of cross-border electronic commerce (CBEC) between China and the EU has fallen far short, and there is an urgency to create a harmonious and uniform environmental environment for the exchange of information to facilitate the convenience of cross border electronic commerce. This study examines the CBEC of agricultural goods and its cooperative management technique inside the logistical supply chain. It details the complete transaction model and fundamental components and presents a theoretical framework for the CBEC distribution network. The Block Chain can effectively bridge the obstacles to CBEC in Chinese and European countries by providing a valuable source of benefits from decentralization, trust, anti-counterfeiting, consensus, innovative procurement, and extraordinary techniques, which will provide the basis for building an Embedded Provider Platform for Electronic Commerce, Risk Management System for Deposit Risk Management, Supply Chain (SC) Management System, Cross Border Logistic System, Customs Supervisory Computer, etc. The paper examines how blockchain science can assemble CBEC SC computing devices for agricultural goods between global places in Central Europe. Firstly, it expounds on the theory and characteristics of the blockchain. Then, the paper introduces the troubles that arise in the CBEC supply chain. Then, the thesis proposes a blockchain-based CBEC SC structure, analyzes the aspects and relations among each other, and provides a framework for developing a China-European blockchain cross-border electronic Commerce. The test findings indicate that the system satisfies the criteria for tracking agricultural items and enhances fresh farm commodities' quality and security.

The Role of Insecurity in Shaping Consumer Purchase Intentions: Mediating Effects of Perceived Usefulness and Ease of Use in Live Commerce

Live commerce platforms facilitate real-time interactions between sellers and buyers, but challenges related to consumer uncertainty can negatively impact their intention to purchase. This study examines how uncertainty affects perceptions of usefulness, ease of use, and the intention to purchase. Additionally, it investigates whether perceived usefulness and ease of use serve as mediators in these relationships. The research adopts a quantitative methodology, collecting data from 150 respondents in Banjarmasin using a questionnaire based on a 5-point Likert scale. The analysis employed Structural Equation Modeling with Partial Least Squares (PLS-SEM) to understand the interrelations among the variables. The findings reveal that insecurity does not significantly impact perceived usefulness, ease of use, or purchase intention, and these perceptions do not act as mediators in the relationship. However, both perceived ease of use and perceived usefulness have a strong and positive effect on purchase intention. These results underscore the need to focus on technology's ease of use and functionality to encourage purchasing behaviour, even when insecurity is present. This suggests that e-commerce businesses should improve their platforms' functional aspects and user-friendliness to enhance consumer engagement. Furthermore, the study encourages future research to delve into more profound psychological aspects and beliefs surrounding consumer insecurity that may influence decision-making in live commerce environments.

A Mediating Effect of Customer Experience on the Relationship between Metaverse Usage and Purchase Intention: A Conceptual Development

This study examines the mediating effect of customer experience on the relationship between metaverse usage and purchase intention, providing a conceptual framework to understand consumer behavior within virtual environments. As the metaverse rapidly evolves into a significant platform for interaction and commerce, understanding how user engagement translates into purchasing decisions is crucial for businesses and marketers. The framework posits that metaverse usage encompasses the frequency and depth of interactions users have with virtual spaces, which significantly influences their overall customer experience. A positive customer experience is characterized by factors such as satisfaction, emotional connection, and engagement, all of which are critical in shaping consumers' purchase intentions. When users perceive their interactions in the metaverse as enjoyable and meaningful, they are more likely to develop a favorable attitude towards the brands and products featured in these environments. The study integrates insights from established models, including the Technology Acceptance Model (TAM) and the Stimulus-Organism-Response (SOR) model, to highlight how various elements of the metaverse such as perceived usefulness, perceived ease of use, and perceived enjoyment which is affect customer experience. By establishing customer experience as a mediator, this research illustrates how metaverse usage not only influences direct purchasing behavior but also shapes the emotional and cognitive processes that underpin decision-making. Ultimately, this conceptual development aims to provide actionable insights for businesses looking to optimize their strategies in the metaverse. By understanding the pathways through which customer experience mediates the relationship between metaverse engagement and purchase intention, companies can create more compelling virtual experiences that foster customer loyalty and drive sales. This research contributes to the growing body of literature on digital consumer behavior, emphasizing the importance of customer experience in shaping purchasing decisions in virtual environments.

Optimalisasi Media Sosial Youtube sebagai Media Berwirausaha

YouTube is a website that allows people to upload and exchange videos. YouTube is an effective social media platform for companies to introduce their products through video content. YouTube is developing into an effective tool for business. YouTube offers live broadcasts of product or service demos, YouTubers can record and post videos about the offers they want, and these offers can attract clients. With millions of videos produced every day, YouTube social media has a good chance of getting videos seen, so you have the opportunity to succeed in online business using YouTube media. Another advantage of social media is that YouTube can improve their marketing techniques and gain a better understanding of their audience by using the analytical tools that YouTube offers. Therefore, YouTube serves as an important tool for doing business online, besides being a place to share YouTube videos. Considering the background information provided, optimizing YouTube social media aims to motivate and improve the abilities of Dawis mothers who want or are currently entrepreneurship in utilizing YouTube as an online business medium. Mrs. Dawis can improve viewers' understanding and retention of knowledge by producing more visually interesting informational material or videos on YouTube. People are more likely to understand and retain knowledge when it is presented on YouTube in an original and engaging way. Therefore, optimizing social media is needed to help Dawis mothers develop their capacity to produce interesting and successful YouTube videos. Thus, Dawis women can use YouTube as a platform for online commerce and entrepreneurship more effectively. This community service aims to optimize the use of YouTube social media as an entrepreneurial tool for Dasa Wisma (Dawis) women in Amposari Village, Pedurungan District, Semarang City. This program was implemented by the Community Service (PKM) team from the Muhammadiyah Semarang Institute of Statistics and Business Technology in March 2024. This activity included theoretical and practical training involving 25 participants from various RTs in the village. The methods used include interviews, discussions, lectures, and questions and answers, with the aim of exploring online business ideas and improving the entrepreneurial spirit of participants

An integrated analysis of consumer purchase decision-making on second-hand trading platforms: evidence from china

ABSTRACT In the context of circular economy and sustainable development, second-hand trading platforms are in the preliminary stages of development, revealing the consumer behavior of second-hand trading platform consumers has become a challenging topic. Previous studies have often used technology acceptance models to analyze consumers’ acceptance of electronic commerce platform technologies. However, these studies have not analyzed consumer purchase decision-making well, lacked affective explanations of the logic of consumer decisions, and lacked discussions of multiple stakeholders. Therefore, this study proposes a comprehensive framework model for consumer decision making on second-hand trading platforms. We analyzed consumer purchase decision process, identified three key dimensions eight factors. Through a combination of the ABC attitude model and the technology acceptance model, we sorted out a hypothetical model consisting of cognitive, affective, and behavioral. Then, we validated and analyzed the empirical results in China using the partial least squares structural equation technique. The findings underscore the significant impact of product and platform dimensions on consumer sentiment and behavior. Theoretically, this study advances the understanding of consumer decision-making in the context of second-hand platforms, particularly within the framework of the circular economy. Practically, it offers actionable insights for merchants and platform operators to enhance user experience and service quality, thereby supporting the sustainable growth of e-commerce.

Gillette’s Expansion to India through the Lens of Porter’s Diamond Model and Dunning’s Eclectic Paradigm

In 2005, Procter & Gamble (P&G) acquired Gillette for $57 billion, marking a significant milestone in consumer goods history. This analysis explores Gillette's strategic expansion into India, leveraging Porter's Diamond Model and Dunning's Eclectic Paradigm to evaluate its success and challenges. The study delves into the skilled workforce, local manufacturing, and innovative marketing strategies that facilitated Gillette's penetration into India's diverse and rapidly urbanizing market. Through local R&D and collaborations with e- commerce platforms, Gillette tailored its products to Indian consumer preferences, achieving substantial market share. The frameworks reveal how Gillette's global efficiency and local responsiveness enabled it to thrive amidst intense competition. The paper concludes with recommendations for sustaining this success through continuous innovation, vigilant market monitoring, and eco-friendly practices, while suggesting the applicability of these insights to other emerging markets.

Driving Word of Mouth in E-commerce: The Impact of Service Quality, Customer Experience, and Repurchase Intention on TikTok Shop

The rapid growth of e-commerce and social commerce platforms demands a thorough understanding of customer behavior, which is vital for business success. This study examines the impact of e-service quality, customer satisfaction, customer trust, and repurchase intention on word of mouth among TikTok Shop customers. A quantitative approach was employed, with data collected through online questionnaires distributed to 220 respondents via Google Forms, using non-probability convenience sampling. Data were analyzed using Structural Equation Modeling (SEM) with the PLS program. The findings reveal that e-service quality positively and significantly influences customer trust, customer satisfaction, repurchase intention, and word of mouth. Furthermore, customer trust has a positive and significant effect on repurchase intention and word of mouth (β = 0.724, P = .001). Additionally, customer satisfaction significantly enhances customer trust, repurchase intention, and word of mouth. Finally, repurchase intention has a positive and significant impact on word of mouth. These results highlight the importance of e-service quality in driving customer satisfaction and positive word of mouth in social commerce platforms. The study focuses solely on TikTok Shop, which may limit generalizability to other e-commerce platforms.

Perilaku Impulse Buying Sebagai Dampak Hedonic Shopping Motivation Dan Shopping Lifestyle Case Study On Tiktok Shop Feature Users In The City Of Bandung

Information technology in Indonesia has experienced significant growth with the emergence of e-commerce and social commerce as platforms for online sales transactions. One of the leading social commerce platforms in Indonesia is TikTok Shop. It is no wonder that consumers in Bandung use TikTok Shop as a venue for online sales and transactions. Promotions, offers, and free shipping provided by TikTok Shop, along with its user-friendly interface, can foster hedonic shopping tendencies, supported by a shopping lifestyle that disregards whether the purchased product is needed or not, and involves impulse buying during window shopping. This study aims to determine the extent to which Hedonic Shopping Motivation and Shopping Lifestyle influence Impulse Buying Behavior among TikTok Shop users in Bandung. The population of this study includes all consumers using TikTok Shop who reside in Bandung. This research employs a quantitative approach with descriptive analysis. The sampling technique used is Purposive Sampling, targeting TikTok Shop users living in Bandung. Data analysis is conducted using multiple linear regression analysis. The results of this study indicate that Hedonic Shopping Motivation has a positive and significant influence on impulse buying behavior, and Shopping Lifestyle also has a positive and significant influence on impulse buying behavior. Moreover, Hedonic Shopping Motivation and Shopping Lifestyle together have a positive and significant influence on impulse buying behavior.

Understanding purchase intentions in crisis: The role of trust and perceived value in Sudan's F-commerce during the COVID-19 pandemic

This study investigates how purchase intentions on Facebook's commerce platform (F-commerce) are shaped during crises. Focusing on Sudanese customers, the research examines the roles of perceived value, trust, and consumption value in influencing purchase intentions. The study specifically looks at how trust mediates the relationship between perceived value and purchase intentions, as well as how perceived value mediates the relationship between cosmopolitanism value and purchase intentions. The goal is to better understand the mechanisms that enhance purchase intentions in Sudan, a developing country facing crises during and after the COVID-19 pandemic. An analysis of 355 responses reveals that trust mediates some aspects of perceived value's influence on purchase intentions but not others. Notably, the mediation of cosmopolitanism's impact on purchase intentions only occurs when perceived security, safety, and logistics values (affected by fuel shortages) are considered. The findings provide a basis for future research using this mediation model to explore the drivers of e-commerce purchase intentions in similar underdeveloped countries during crises where the use of digital technology for commerce is limited.

Examining how emotions affect online audience retention: Empirical evidence from livestreaming electronic commerce platforms

The retention of audiences has become a pressing issue in the paradigm of livestreaming electronic commerce. Embracing the cognitive appraisal theory of emotions, this study develops a research model to gauge the relationship between emotion and audience retention. The results from 1,218,692 bullet comments from 491,348 users in 946 livestreaming sessions indicate that users’ valence and arousal affect retention positively, while the two dimensions of streamers’ emotions exert impacts in opposite directions. We further discover that intimacy has significant moderating effects in the research model. These findings emphasize the importance of understanding emotional dynamics in LSE in promoting audience retention.

Unveiling the optimal configuration of impulsive buying behavior using fuzzy set qualitative comparative analysis and multi-criteria decision approach

Sudden and unplanned purchasing behavior is considered impulsive buying behavior. With the increasing popularity of social commerce platforms and shopping automation, people's tendency towards impulsive purchases has grown significantly. In this connection, the role of marketing influencers has crucially impacted the customers' purchasing decisions over the last decade. This study aims to investigate the effect of marketing influencers on impulsive buying behavior. In addition, the current study addresses a critical methodological problem by highlighting the optimal configuration provided by fuzzy set qualitative comparative analysis (fsQCA) using a multi-criteria decision approach (MCDM). Based on a survey of 672 users of live streaming commerce platforms in Malaysia, we examined impulsive buying behavior from the perspective of influencer marketing, cognitive trust, and affective trust in influencer. Partial Least Squares Structural Equation Modeling (PLS-SEM) results confirmed the influence of parasocial relationship, authenticity, expertise, trustworthiness, attractiveness, and influencer–follower congruence on impulsive buying behavior through cognitive trust in influencer, affective trust in influencer, and behavioral inertia. The fsQCA results provided 15 different configurations confirming the role of marketing influencers' characteristics in impulsive buying behavior. However, fsQCA analysis is unable to determine the optimal solution or configuration. To this end, the MCDM analysis complemented the fsQCA analysis by unveiling the optimal configuration, which was the ninth configuration. Furthermore, the combination of authenticity, expertise, trustworthiness, cognitive trust, affective trust is considered a key concept to increase impulsive buying behaviour regardless of the presence of a parasocial relationship.

Research on the Purchase Intention of Social Commerce Consumers in Video Streams: Dual Pathways of Affection and Rationality.

Social commerce blurs the boundary between online social interaction and online shopping. The emergence of video streams introduces novel marketing modalities to social commerce. However, there is a paucity of comprehensive studies investigating the impact of emerging marketing techniques such as short videos and live streaming on consumer purchase intention. This study employs Bourdieu's conceptual framework to construct a Field Theory-based model, investigating the impact of atmospheric and capital characteristics of social commerce platforms on consumer purchase intention through affective and rational pathways, respectively. A survey involving 515 Chinese social commerce consumers demonstrates that atmospheric characteristics (emotion and social presence) and capital characteristics (information quality and quantity) in video streams enhance similarity and power. Both similarity and power are associated with an increase in consumer purchase intention. This study validates the dual-path influence of social commerce characteristics and discusses theoretical and managerial implications.

GEN Z’S IMPULSE BUYING BEHAVIOR OF SHOPPING THROUGH LIVE-STREAMING SOCIAL COMMERCE PLATFORMS:

In social commerce, consumers receive emotional motivation to purchase products because they feel familiar and bonded with the promoter, often losing track of time and self-awareness in a flow state, leading to impulse buying. As Gen Z are often presents more tendency toward impulse shopping behaviors compared to other generations, this study aims to investigate the impulse buying behavior of Generation Z (Gen Z) on live-streaming social commerce platforms, focusing on the roles of Parasocial Interaction (PSI) and Social Commerce Emotional Motivation (SCEM). Using a quantitative approach, data were collected via online surveys from individuals born between 1998 and 2007 who had made at least two unplanned purchases after watching live-streamed shopping events within four weeks. Statistical regression analysis was conducted using IBM SPSS 26.0 to explore the relationships between PSI, SCEM, and impulse buying behavior (IBB). The findings reveal that both PSI and SCEM significantly influence IBB among Gen Z consumers. Strong parasocial relationships with live-stream hosts enhance trust and connection, while emotional engagement through SCEM motivates spontaneous purchases. The study highlights the synergistic effect of PSI and SCEM, suggesting that a combined approach is most effective in driving impulse buys. This study contributes to the understanding of consumer behavior in the context of emerging social commerce trends, providing actionable insights for enhancing marketing strategies targeted at Gen Z.

A Study on Retailers’ Behavior Intention to Accept and Use the Omni channel Commerce Platforms

Research on retailers’ behavioral intention to accept and use the omnichannel commerce platforms (OCPs) in the Vietnam context used the Unified Theory of Acceptance and Use of Technology (UTAUT2) model and supplemented the other factors such as omnichannel capability, omnichannel integration. The results of this study show Effort Expectation, Social Influence, Hedonic Motive, Professional Capacity, Seamlessly Linking have a positive impact on retailers' behavior intention to accept and use OCPs. Behavioral Intention and Favorable Conditions have a positive impact on use behavior. Meanwhile, Habits and Omnichannel Integration have a negative impact on the use behavior of OCPs in Vietnam. The findings of this model help managers and OCPs providers identify factors that influence OCPs' behavioral intention and use behavior of retailers in Vietnam.

Comprehensive review of machine learning models for sql injection detection in e-commerce

With the steady expansion of online commerce, e-commerce sites have become increasingly attractive targets for hackers. These sites serve millions of customers and often hold valuable, confidential, and sometimes financial information in their databases. One particularly dangerous type of attack is SQL injection, which exploits vulnerabilities in web applications to influence backend databases, posing significant threats to such platforms. Traditional defenses like desktop firewalls, input validation, and parameterized queries provide some level of protection but are often insufficient against newer injection variations and sophisticated attackers. The utilization of machine learning to enhance cybersecurity against more advanced threats has been demonstrated as a promising approach. This systematic review examines how various machine learning algorithms are applied to detect SQL injection attacks that could potentially harm e-commerce systems. By identifying and analyzing the relevant literature, this review highlights the effectiveness of different algorithms and their practical applications in enhancing the security of online commerce platforms. More specifically, five techniques were assessed on both real and synthetic datasets: Logistic Regression, Naive Bayes, Random Forest, Artificial Neural Network, and two combined models (Logistic Regression & Naive Bayes, and Artificial Neural Network & Random Forest). The findings indicate that Random Forest performed better than other algorithms in the decision tree family, attributed to its ability to balance precision and recall effectively. However, limitations such as using a single dataset and the computational complexity of some models were noted. This review provides insights for practitioners on selecting appropriate detection models and outlines approaches to address current limitations through future work. Addressing these limitations could involve using more diverse datasets, optimizing computational efficiency, and exploring advanced ensemble methods and neural network architectures.

Shaping Trust through Argument Quality: Exploring its Impact on Purchase Intentions in Social Commerce

The research aimed to investigate the influence of argument quality, namely perceived informativeness and persuasiveness, on trust and purchase intention within a social commerce context, focusing on TikTok. A quantitative method was applied, including 150 respondents. Participants were selected based on specific criteria of being active social commerce users. Additionally, the participants’ age was restricted to between 18 and 23 years old since data indicated that Generation Z with a strong tendency to shop online, used TikTok more than other social media platforms. Data collection included distributing questionnaires through Google Forms, using a 5-point Likert scale. Data analysis was conducted using Partial Least Squares-Structural Equation Modeling (PLS-SEM). The results show that perceived informativeness and persuasiveness affect trust towards both members of TikTok and the platform. It has a positive impact on purchase intention due to higher levels of trust in social commerce members and the platform. Meanwhile, trust towards members significantly affects the TikTok platform, and the relationship is non-significant. A potential differentiation is reported concerning the formation of trust. In this context, trust in individual users does not necessarily influence the platform within the context of TikTok social commerce. These insights are valuable for marketers and platform developers seeking to improve user engagement and transaction rates on social commerce platforms. The implications suggest that enhancing the informativeness and persuasiveness of content can be a strategic method for enhancing trust and promoting purchase intention.