Edelweiss Applied Science and Technology ISSN: 2576-8484 Vol. 9, No. 6, 873-893 2025 Publisher: Learning Gate DOI: 10.55214/25768484.v9i6.7972 © 2025 by the authors; licensee Learning Gate © 2025 by the authors; licensee Learning Gate History: Received: 3 April 2025; Revised: 23 May 2025; Accepted: 27 May 2025; Published: 11 June 2025 * Correspondence: ayugiantari@unud.ac.id Social media marketing-based brand engagement strategy in increasing purchasing decisions in fashion SMEs in Bali I Gusti Ayu Ketut Giantari1*, Tjok Gede Raka Sukawati2, Ni Wayan Ekawati3, Ni Nyoman Kerti Yasa4 1,2,3,4Economics and Business Faculty, Udayana University, Bali – Indonesia; ayugiantari@unud.ac.id (I.G.A.K.G). Abstract: The development of very fast fashion trends and the entry of foreign competitors have an impact on consumer purchasing decisions, especially for Generation (Gen) Z in fashion MSMEs in Bali. To encourage increased consumer purchasing decisions, social media marketing is used as a form of promotion using Instagram, Facebook, email marketing, WhatsApp, and TikTok. From several previous research studies on the impact of the use of social media marketing on purchasing decisions, the results of the study are still inconsistent (research gap). To fill this research gap, brand engagement, and brand trust strategies are used as mediators for fashion MSMEs to increase consumer purchasing decisions. The purpose of the study was to test and explain brand engagement strategies based on social media marketing to increase Gen Z purchasing decisions in fashion MSMEs in Bali. This study uses a quantitative approach with 200 respondents from Gen Z who made fashion product purchases using a non-probability sampling method, namely purposive sampling. Data collection uses a survey method, namely a questionnaire given to both offline and online respondents. The research instrument was tested for validity and reliability, and the data analysis technique used descriptive statistical analysis and inferential statistics (SEM-PLS). The research results imply that they can enrich the theory of planned behavior in the context of fast fashion. The practical implications are that fashion SMEs in Bali should design interesting content on social media, design their products well from quality materials, and always be the quality of ready-to-wear clothing and services so that they have a good image. Keywords: Brand engagement, Purchasing decisions, Social media marketing, Trust. 1. Introduction The development of MSMEs in ready-to-wear clothing (fashion) in Bali has fluctuated, especially with the presence of fashion products from abroad. The clothing industry offers the latest fashion trends at low prices and fast production times. Fast fashion, which is the current fashion trend that influences consumer purchasing decisions, especially Generation Z, is supported by social media marketing [1]. A purchasing decision is a condition where a consumer makes a selection and decides to purchase a product [2]. Many factors influence purchasing decisions when choosing fashion products, including social media marketing. Social media marketing is a platform for activities, practices, and behaviors among communities of people who gather online to share information, knowledge, and opinions using conversational media [3]. Several previous research studies have shown that social media marketing has a positive and significant effect on purchasing decisions [4-6]. However, there is research by Noviyana, et al. [7] that shows that, partially, social media marketing does not affect product purchasing decisions. This is an important research gap to be re-examined by using its mediating variable, namely brand engagement, to increase purchasing decisions. Brand engagement is a company's strategy to create an emotional connection between a brand and its customers. Various information and sales-related campaigns are https://orcid.org/0000-0001-7841-0526 https://orcid.org/0000-0002-9007-0218 https://orcid.org/0000-0001-6337-5983 https://orcid.org/0000-0003-1655-8220 874 Edelweiss Applied Science and Technology ISSN: 2576-8484 Vol. 9, No. 6: 873-893, 2025 DOI: 10.55214/25768484.v9i6.7972 © 2025 by the authors; licensee Learning Gate often used on brand social media accounts as a driver of attention and increased sales. Campaigns (promotions, contests, etc.) increase engagement between brands and consumers, leading to better relationships in the form of trust [8] and will have a positive impact on purchase intentions [9]. To increase purchasing decisions, it is not only because consumers are already involved in existing fashion brands (brand engagement) but also because they need trust in the brand (trust) [10, 11]. Trust is considered a potential consequence of brand engagement, especially for new customers, who are expected to first engage with the brand and then develop a relationship with the brand [11, 12]. Based on the existing background, this study aims to examine and explain the role of brand engagement and brand trust in mediating the influence of social media marketing on purchasing decisions. In addition, it develops basic strategies to improve Gen Z purchasing decisions for fashion MSMEs in Bali and adopts strategic policies to help Fashion MSMEs improve their business performance. 2. Literature Review 2.1. Previous Research and State-of-the-Art Research The position of this research is compared to previous research, namely the development of the Noviyana, et al. [7] model using social media marketing, which has not been able to increase purchasing decisions. By using the SOR (Stimulus-Response Theory), brand engagement and trust are expected to increase purchasing decisions. 2.2. Theory of Stimulus Organism Response The Stimulus Organism Response (SOR) theory was proposed by Woodworth [13] as an extension of the classical theory of the stimulus-response model suggested by Pavlov [14]. The SOR model consists of three constructs, namely stimulus, organism, and response, which determine the behavioral outcome of an event [15]. The stimulus in this study is found in social media marketing, which includes various forms of interaction, content, and promotion. Perceived social media marketing is a stimulus consisting of the characteristics of the e-commerce environment [16]. Organisms, when associated with this study, refer to brand trust and brand engagement, where consumer trust in the brand is an important emotional response. Consumers who trust the brand are more likely to respond positively to marketing content on social media, and consumer engagement with the brand through interactions on social media creates a stronger relationship between the brand and the consumer. Response is the next stage when the stimulus has been felt by someone, which can be in the form of actions, behavior, or changes in attitude; from the understanding of the response, it refers to the purchasing decision. 2.3. Social Media Marketing Social media marketing also facilitates interaction and collaboration between businesses and consumers, provides recommendations for consumers, and encourages information sharing and co- creation between users [17, 18]. Companies are usually more likely to use social media as a tool in their marketing because it has several unique features and can also reduce the costs used by companies for promotion. Social media marketing in this study is measured through several dimensions [19] including 1) entertainment. 2) customization. 3) interaction. 4) E-WOM. 5) trendiness. 2.4. Brand Engagement Brand engagement is a customer's behavior after repeat purchases [20]. Brand engagement is the level of personal motivation of consumers, which is related to the brand, and thoughts related to the context that is marked by certain stages, namely cognitive, emotional, and direct behavior interacting with the brand [21]. Brand engagement is a process of forming an emotional attachment that has a positive influence on the brand and the consumer so that it can create a person's intention to buy the 875 Edelweiss Applied Science and Technology ISSN: 2576-8484 Vol. 9, No. 6: 873-893, 2025 DOI: 10.55214/25768484.v9i6.7972 © 2025 by the authors; licensee Learning Gate product [22]. Building strong relationships with consumers can increase positive attitudes and behaviors toward the brand and encourage consumers to establish long-term relationships with the brand [23]. Brand engagement in this study is measured through five dimensions [24] including: 1) Enthusiasm. 2) Attention. 3) Absorption. 4) Interaction. 5) Identification 2.5. Brand Trust Brand trust is a consumer's belief before buying a product, and it is done by looking for information about the product to be purchased. This trust is formed through basic information provided by the brand, which then affects product performance. Maintained trust will result in satisfaction and purchasing decisions that increase consumer trust in a brand [25]. When customers feel confident and safe when using a brand, this can encourage the intention to buy, make repeat purchases, and build loyalty to the brand [26]. The indicators used to support brand trust in this study [27, 28] are: 1) experience. 2) empathy. 3) honesty. 4) trust in a good image. 2.6. Purchasing Decisions Purchase decisions are part of consumer behavior, namely the study of how individuals, groups, and organizations choose, buy, use, and use goods, services, ideas, or experiences to satisfy their needs and want [2]. Purchasing decisions are also final decisions that a consumer has to make to buy a good or service with various considerations, and consumer purchasing decisions describe how far marketers try to market a product to consumers [29]. The indicators used to measure purchasing decisions in this study [30] are 1) according to needs, 2) have benefits, 3) accuracy in buying products, and 4) repeat purchases. 2.7. Conceptual Framework The conceptual framework can be illustrated as follows, in accordance with the research objective, namely, to understand the role of brand engagement and brand trust in mediating the influence of social media marketing on purchasing decisions. Figure 1. Research Concept Framework. 2.8. Research Hypothesis H1: Social media marketing has a positive and significant effect on purchasing decisions. H2: Social media marketing has a positive and significant effect on brand engagement. H3: Brand engagement has a positive and significant effect on purchasing decisions. 876 Edelweiss Applied Science and Technology ISSN: 2576-8484 Vol. 9, No. 6: 873-893, 2025 DOI: 10.55214/25768484.v9i6.7972 © 2025 by the authors; licensee Learning Gate H4: Social media marketing has a positive and significant effect on brand trust. H5: Brand trust has a positive and significant effect on purchasing decisions. H6: Brand engagement has a positive and significant effect on brand trust. H7: Brand engagement is able to significantly mediate the effect of social media marketing on purchasing decisions. H8: Brand trust is able to significantly mediate the effect of social media marketing on purchasing decisions. H9: Brand trust is able to mediate the effect of brand engagement on purchasing decisions significantly. 3. Research Methods This study is included in causal research, which aims to analyze the relationship between variables. This study was conducted in Bali on Generation Z, born in 1997 - 2012, who purchased fashion products at Fashion UMKM through social media marketing. The variables to be tested in this study are social media marketing variables, brand trust, brand engagement, and purchasing decisions. The population in this study is Gen Z, who make purchases at fashion UMKM in Bali. The sample size is 200 people. The sampling technique uses non-probability sampling, namely purposive sampling, which is sampling with consideration. The considerations: respondents are Generation Z (born in 1997 - 2012) and have purchased fashion products at fashion UMKM in Bali through social media marketing. The variable indicators in this study were measured using a Likert scale by consumers who purchased fashion products on social media, where the measurements included strongly disagree = 1, disagree = 2, quite agree = 3, agree = 4, and strongly agree = 5. Data collection techniques were carried out by distributing questionnaires online and offline via Google Forms and by distributing links via WhatsApp groups. The instruments used were tested for validity and reliability to ensure that the instrument was able to measure what should be measured and to determine the consistency of respondents' responses. The testing criteria used on the instrument were said to be valid if the r value was 0.30 and the correlation significance value was 95% or = 0.05, with the cut-off point value accepted for the Cronbach Alpha level of 0.60, although this was not an absolute standard. The instrument is considered to have an acceptable level of reliability if the measured reliability coefficient value is 0.60. Both of these tests use the SEM-PLS approach. This analysis is used to describe the research variables without making generalizations. The data that has been collected is then tabulated in a table and analyzed descriptively. The causal relationship in this study is recursive and uses a complex model, so appropriate analytical tools are needed to explain the relationship. 4. Results and Discussion After conducting research and processing research data, the results can be presented as follows. The characteristics of respondents according to gender, age, level of formal education, and income are shown in table 1, as follows. 877 Edelweiss Applied Science and Technology ISSN: 2576-8484 Vol. 9, No. 6: 873-893, 2025 DOI: 10.55214/25768484.v9i6.7972 © 2025 by the authors; licensee Learning Gate Table 1. Respondent Characteristics. No Characteristic Classification Number of Respondents (people) Presentation of Respondents 1 Gender Male 78 39 Female 122 61 Total 200 100 2 Age 17 - 21 years 148 74 22 - 26 years 52 26 Total 200 100 3 Formal Education Level Secondary Education (SMA, SMK) 54 27 Diploma Education (D1, D2, D3) 26 13 Bachelor's Degree (S1) 120 60 Total 200 100 4 Income ≤ Rp 1.000.0000 104 52 > Rp 1.000.000 - ≤ Rp 3.000.000,- 55 27,5 >Rp 3.000.000,- ≤ Rp 6.000.000,- 22 11,0 >Rp 6.000.000,- - ≤ Rp 9.000.000,- 10 5,0 >Rp 9.000.000,- 9 4,5 Total 200 100 Table 1 explains that female respondents are more numerous than male respondents, with female respondents at 61 percent and male respondents at 39 percent. When viewed by age, most respondents are aged 17-21 years old, amounting to 74 percent; then 22-26 years old by 26 percent. When viewed from the level of education, respondents who have high school/vocational school education are 27 percent; those who have diploma education are 13 percent; those who have a bachelor's level are 60 percent. When viewed from their income, respondents who have income less than or equal to Rp 1,000,000 are 52 percent, occupying the highest position then followed by income of > Rp 1,000,000 - ≤ Rp 3,000,000, - by 27.5 percent; income > Rp 3,000,000, - ≤ Rp 6,000,000, - by 11 percent; income >Rp 6,000,000,- - ≤ Rp 9,000,000,- by 5 percent; and income >Rp 9,000,000,- by 4.5 percent. Validity and reliability testing of the instrument was carried out using SPSS for Windows 24.0 and Cronbach's Alpha. The results of the validity and reliability testing of the instrument for each variable can be presented in Table 2. The results of the validity and reliability testing of the instrument in Table 2 show that all variables are valid because the correlation of each factor is positive and the value is 0.361 and above, then the factor is a strong variable. The instrument can be said to be reliable if Cronbach Alpha> 0.6. 878 Edelweiss Applied Science and Technology ISSN: 2576-8484 Vol. 9, No. 6: 873-893, 2025 DOI: 10.55214/25768484.v9i6.7972 © 2025 by the authors; licensee Learning Gate Table 2. Recapitulation of validity and reliability test results of research instruments. Variables Indicators Correlation Coefficient Cronbach’s Alpha Information Social Media Marketing (X1) (X1.1) 0.880 0.920 Valid (X1.2) 0.798 (X1.3) 0.936 (X1.4) 0.895 (X1.5) 0.928 Brand engagement (Y1) (Y1.1) 0.873 0.914 Valid (Y1.2) 0.896 (Y1.3) 0.875 (Y1.4) 0.882 (Y1.5) 0.871 Trust (Y2) (Y2.1) 0.902 0.927 Valid (Y2.2) 0.964 (Y2.3) 0.828 (Y2.4) 0.938 Purchase Decision (Y3) (Y3.1) 0.943 0.966 Valid (Y3.2) 0.961 (Y3.3) 0.984 (Y3.4) 0.937 Furthermore, the results of the descriptive analysis of the variables explain the respondents' perceptions of the variables of social media marketing, brand engagement, brand trust, and purchasing decisions obtained through the distribution of questionnaires, both offline and online. Quantitative assessment uses an interval scale by calculating the average score according to the assessment category. Based on the results of the tabulation of respondents' answer data on five respondents' statements regarding social media marketing, 200 respondents answered. It is possible to tabulate the number of answers for all respondents for each category presented in the following table. 879 Edelweiss Applied Science and Technology ISSN: 2576-8484 Vol. 9, No. 6: 873-893, 2025 DOI: 10.55214/25768484.v9i6.7972 © 2025 by the authors; licensee Learning Gate Table 3. Description of Respondents' Answers to Social Media Marketing. No Statement Frequency of Respondents' Answers Average Criteria Strongly disagree Disagree Quite agree Agree Strongly agree 1 Fashion UMKM creates interesting social media content 0 1 9 77 113 4.51 Very Good 2 Fashion UMKM creates social media to connect with consumers. 0 0 6 70 124 4.59 Very Good 3 Fashion UMKM creates content (photos, videos) containing complete information for consumers 0 1 18 77 104 4.42 Very Good 4 Fashion UMKM is a place to build communities and exchange information 0 2 19 83 96 4.37 Very Good 5 I want to upload UMKM Fashion product content on my social media page 0 13 41 76 71 4.02 Good Overall average of social media marketing variables 4,38 Very Good Table 3 shows that overall, social media marketing is very good, with an average value of 4.38. The use of social media as the main link between fashion MSMEs and consumers has the highest value. In contrast, the lowest value shows that Gen Z customers in Bali are less interested in uploading content about fashion MSMEs to their social media. Table 4. Description of Respondents' Answers to Brand Engagement. No Statement Frequency of Respondents' Answers Average Criteria Strongly disagree Disagree Quite agree Agree Strongly agree 1 I feel very happy with the design of UMKM fashion clothes 0 1 24 96 78 4.26 Very Good 2 UMKM Fashion pays attention to maintaining good relations with its customers 0 1 25 87 87 4.30 Very Good 3 I feel happy wearing UMKM fashion clothes 0 0 18 99 83 4.33 Very Good 4 I participate in strengthening the UMKM fashion brand 1 4 31 97 68 4.13 Good 5 Using products from UMKM fashion has become my identity 1 8 42 83 66 4.03 Good Overall average of brand engagement variables 4.21 Very Good Table 4 shows that overall brand engagement is high, with an average value of 4.21. This reflects that 200 Gen Z respondents in Bali have a strong attachment to the UMKM Fashion brand. The highest value is for the statement "I feel happy wearing UMKM fashion clothes," and the lowest is for "Using UMKM fashion becomes my identity." This shows that UMKM fashion products do not yet reflect Gen Z's identity, so digital innovation and promotion are needed. 880 Edelweiss Applied Science and Technology ISSN: 2576-8484 Vol. 9, No. 6: 873-893, 2025 DOI: 10.55214/25768484.v9i6.7972 © 2025 by the authors; licensee Learning Gate Table 5. Description of Respondents' Answers to Brand Trust. No Statement Frequency of Respondents' Answers Average Criteria Strongly disagree Disagree Quite agree Agree Strongly agree 1 I believe in fashion UMKM because of their experience in designing clothes 0 2 37 97 64 4.11 High 2 I believe in fashion UMKM because they care about customers 0 0 25 103 72 4.24 Very High 3 I believe in fashion UMKM because of their honesty in serving customers 0 1 23 103 74 4.23 Very 4 I believe in fashion UMKM because they have a good image 0 2 19 107 72 4.25 High Overall average of brand trust variables 4,22 Very High Table 5 shows that overall brand trust is high, with an average of 4.22. The highest value is in the statement "I trust fashion SMEs because of their attention to customers" and "good image." Meanwhile, the lowest value is "I trust because of their experience in designing clothes," indicating that Gen Z has less trust in this aspect. Table 6. Description of Respondents' Answers to Purchasing Decisions. No Statement Frequency of Respondents' Answers Average Criteria Strongly disagree Disagree Quite agree Agree Strongly agree 1 I decided to buy products at UMKM Fashion because they fit my needs 0 1 17 99 83 4.32 Very High 2 The decision to buy clothes at UMKM Fashion that I made was because it fit the benefits I needed 0 0 19 90 91 4.36 Very High 3 The purchase of clothes at UMKM Fashion was the right decision 0 0 23 92 85 4.31 Very High 4 I want to buy clothes at UMKM Fashion again 0 0 21 95 84 4.32 Very High Overall average of purchasing decision variables 4.33 Very High Table 6 shows that overall purchasing decisions are high, with an average of 4.33. The highest statement is "The decision to purchase clothes from UMKM Fashion that I made because it was in accordance with the benefits needed," with an average of 4.36. The lowest statement is "Purchase of clothes from UMKM Fashion is the right decision," with an average of 4.31. 5. SEM PLS Result This study uses a two-stage approach to measuring the model before it is used for hypothesis testing. This aims to verify the validity and reliability of a research model by analyzing convergent validity first and discriminant validity second. 881 Edelweiss Applied Science and Technology ISSN: 2576-8484 Vol. 9, No. 6: 873-893, 2025 DOI: 10.55214/25768484.v9i6.7972 © 2025 by the authors; licensee Learning Gate 5.1. Convergent Validity Convergent validity is measured through the factor loading value on the latent variables and their indicators. This study uses a loading value between 0.50 and 0.60, which is considered adequate because it is in the early stages of developing a measurement scale. In addition, the number of indicators per construct is relatively small, ranging from three to five. Table 7. Convergent Validity Test Results. Social Media Marketing (X1) Brand engagement(Y1) Trust (Y2) Purchase Decision (Y3) Context (X1.1) 0.832 Practice sharing stories (X1.2) 0.788 Collaboration (X1.3) 0.824 Connection (X1.4) 0.829 Repeat purchases (X1.5) 0.801 Cognitive processing (Y1.1) 0.862 Affection (Y1.2) 0.863 Activation (Y1.3) 0.869 Brand reinforcement (Y1.4) 0.821 Brand identity (Y1.5) 0.869 Brand Reliability (Y2.1) 0.873 Brand Intentions (Y2.2) 0.885 Customer Partnership (Y2.3) 0.913 Good Image (Y2.4) 0.910 According to Needs (Y3.1) 0.911 Has Benefits (Y3.2) 0.920 Accuracy in purchasing products (Y3.3) 0.933 Repeat purchases (Y3.4) 0.913 Based on Table 7, all convergent validity test values are greater than 0.60, indicating that the data in this study are valid. This means that the reflective indicators have a good correlation with the latent variables they measure. 5.2. Discriminant Validity Using Cross-Loading Reflective indicator measurement is based on cross-loading with its latent variables. If the cross- loading value of each indicator from the relevant variable is greater than the cross-loading of other variables, then the indicator is said to be valid. If the discriminant validity value is greater than 0.5, then the latent variable has become a good comparison for the model. 882 Edelweiss Applied Science and Technology ISSN: 2576-8484 Vol. 9, No. 6: 873-893, 2025 DOI: 10.55214/25768484.v9i6.7972 © 2025 by the authors; licensee Learning Gate Table 8. Results of Discriminant Cross Loading Validity Test. Social Media Marketing (X1) Brand engagement(Y1) Trust (Y2) Purchase Decision (Y3) Context (X1.1) 0.832 0.655 0.589 0.598 Practice sharing stories (X1.2) 0.788 0.559 0.553 0.597 Collaboration (X1.3) 0.824 0.602 0.594 0.568 Connection (X1.4) 0.829 0.713 0.627 0.692 Repeat purchases (X1.5) 0.801 0.719 0.650 0.601 Cognitive processing (Y1.1) 0.701 0.862 0.681 0.682 Affection (Y1.2) 0.738 0.863 0.720 0.701 Activation (Y1.3) 0.708 0.869 0.727 0.786 Brand reinforcement (Y1.4) 0.619 0.821 0.660 0.624 Brand identity (Y1.5) 0.664 0.869 0.747 0.716 Brand Reliability (Y2.1) 0.619 0.714 0.873 0.634 Brand Intentions (Y2.2) 0.660 0.722 0.885 0.668 Customer Partnership (Y2.3) 0.676 0.766 0.913 0.707 Good Image (Y2.4) 0.698 0.755 0.910 0.713 According to Needs (Y3.1) 0.691 0.758 0.717 0.911 Has Benefits (Y3.2) 0.692 0.769 0.716 0.920 Accuracy in purchasing products (Y3.3) 0.719 0.759 0.703 0.933 Repeat purchases (Y3.4) 0.663 0.733 0.661 0.913 Based on Table 8, all cross-loading values for each indicator in each variable are greater than 0.5. Thus, the data in the study are valid, meaning that the latent variables have become a good comparison for the research model or that the combined set of indicators is not unidimensional. 5.3. Discriminant Validity using AVE Another method is to compare the average variance extracted (AVE) value of each construct with the correlation between constructs in the model. If the AVE value is greater, it can be concluded that the construct has good discriminant validity. Therefore, it is recommended that the AVE value should be more than 0.50. Table 9. Results of the AVE Convergent Validity Test. Average Variance Extracted (AVE) Social Media Marketing (X1) 0.664 Brand engagement (Y1) 0.734 Trust (Y2) 0.802 Purchase Decision (Y3) 0.845 Based on Table 9, all AVE values of convergent validity are greater than 0.5, indicating that the data is valid and that the latent variables explain more than half of the variance of their indicators. Discriminant validity can be seen from the RSAVE value of each construct, which is greater than the correlation between constructs. Table 10 shows that social media marketing, brand engagement, trust, and purchasing decisions meet the criteria of discriminant validity. 883 Edelweiss Applied Science and Technology ISSN: 2576-8484 Vol. 9, No. 6: 873-893, 2025 DOI: 10.55214/25768484.v9i6.7972 © 2025 by the authors; licensee Learning Gate Table 10. Root Square of Average Variance Extracted (RSAVE) and Construct Correlation. Brand Engagement Brand Trust Purchase Decision Social Media Marketing Brand Engagement 0.857 Brand Trust 0.826 0.895 Purchase Decision 0.821 0.761 0.919 Social Media Marketing 0.802 0.742 0.752 0.815 5.4. Reliability Block indicators that measure the internal fit of the construct-forming indicators indicate the extent to which the indicators reflect unobserved latent factors. Cronbach's Alpha can be used to measure reliability. In addition, composite reliability values are also used, with the same interpretation as Cronbach's Alpha. The accepted limit for composite reliability is 0.7, although this is not an absolute standard. Table 11. Results of Cronbach's Alpha and Composite Reliability Tests. Cronbach's Alpha Composite Reliability Social Media Marketing (X1) 0.874 0.908 Brand engagement (Y1) 0.857 0.933 Trust (Y2) 0.826 0.942 Purchase Decision (Y3) 0.939 0.956 Based on Table 11, all variables have Cronbach's alpha values and composite reliability above 0.7. This indicates that the study's data can be considered reliable. 5.5. Structural Model Evaluation Results (Inner Model) Measurement using R-Square of dependent latent variables, interpreted like regression, and Q- Square for predictive relevance of the model, assessing how well the model produces observation values. Q-Square > 0 indicates predictive relevance, while Q-Square < 0 indicates lack of predictive relevance. 5.5.1. R – Square The R-square value is used to calculate the Q-square, a test of the model's goodness of fit, and shows the percentage of exogenous variables' influence on endogenous variables. The R-square range is 0-1, with values approaching 0 indicating a weak exogenous influence while approaching 1 indicating a strong influence on endogenous variables. Table 12. R-square Test Results. R Square R Square Adjusted Brand engagement (Y1) 0.643 0.641 Trust (Y2) 0.700 0.697 Purchase Decision (Y3) 0.712 0.708 Based on Table 12, the R-square value of the social media marketing variable on brand engagement is 0.643, which means its influence is 64.3 percent, with 35.7 percent explained by other factors outside the model. For trust, the R-square value is 0.700, indicating an influence of 70 percent, with 30 percent explained by other factors. The R-square value for social media marketing, brand engagement, and trust in purchasing decisions is 0.712, indicating an influence of 71.2 percent. In comparison, other factors outside the model explain 28.8 percent. These models are in the fairly strong category. 884 Edelweiss Applied Science and Technology ISSN: 2576-8484 Vol. 9, No. 6: 873-893, 2025 DOI: 10.55214/25768484.v9i6.7972 © 2025 by the authors; licensee Learning Gate 5.5.2. Goodness of Fit Model (Q2) Inner model testing is done by looking at the Q-square value as a goodness of fit test. If the Q- square value is greater than 0, the model has predictive relevance, while if it is less than 0, the model is less predictively relevant. A positive Q-square value indicates a relevant predictive model. Q2 = 1 – [(1-R12) (1- R22) (1 – R22 ) = 1 – [(1-0,413) (1-0,49) (1-0,506) = 0,8522 Based on the Q-square calculation, the Q-square value of 0.8522 indicates that the model has strong predictive relevance. This result proves that the structural model is very good. Based on the Q² value, 85.22 percent of the endogenous construct is explained by variations in the exogenous construct, while the remaining 14.78 percent is explained by other variables outside the model. 5.6. Hypothesis Testing Results 5.6.1. Direct Effect Test Results Four direct effect hypotheses were tested using Partial Least Square (PLS). Testing was carried out using the t-test on each path between variables. The bootstrap method was used for each hypothesized relationship to reduce the problem of data abnormality. The results of the direct effect test are presented in Table 13 and Figure 2. Figure 2. Print out the full model. 885 Edelweiss Applied Science and Technology ISSN: 2576-8484 Vol. 9, No. 6: 873-893, 2025 DOI: 10.55214/25768484.v9i6.7972 © 2025 by the authors; licensee Learning Gate Table 13. Results of the Direct Influence Test. Path Coef. t statistics P Values Info. Social Media Marketing (X1) -> Purchase Decision (Y3) 0.217 2.273 0.023 Significant Social Media Marketing (X1) -> Brand Engagement (Y1) 0.802 32.969 0.000 Significant Social Media Marketing (X1) -> Brand Trust (Y2) 0.222 3.279 0.001 Significant Brand Engagement (Y1) -> Purchase Decision (Y3) 0.477 4.264 0.000 Significant Brand Engagement (Y1) -> Brand Trust (Y2) 0.648 10.157 0.000 Significant Brand Trust (Y2) -> Purchase Decision (Y3) 0.206 2.317 0.021 Significant The following is an explanation of the results of the direct influence hypothesis test, as presented in Table 4.15 and Figure 4.1. a. Hypothesis testing shows that social media marketing has a regression coefficient of 0.217, indicating a positive influence on purchasing decisions. The P-value of 0.023 (less than 0.05) indicates a significant influence. So, hypothesis 1 (H1), that social media marketing has a positive and significant influence on purchasing decisions, is accepted. b. Hypothesis testing shows that social media marketing has a regression coefficient of 0.802, which means it has a positive influence on brand engagement. With a P-value of 0.000 (less than 0.05), the influence is significant. So, hypothesis 2 (H2), that social media marketing has a positive and significant influence on brand engagement is accepted. c. Hypothesis testing shows that social media marketing has a regression coefficient of 0.222, which means it has a positive influence on brand trust. A P-value value of 0.001 (less than 0.05) indicates a significant influence. Therefore, hypothesis 3 (H3), that social media marketing has a positive and significant effect on brand trust, is accepted. d. Hypothesis testing shows that brand engagement has a regression coefficient of 0.477, which means it has a positive effect on purchasing decisions. P-values of 0.000 (less than 0.05) indicate a significant effect. Therefore, hypothesis 4 (H4), that brand engagement has a positive and significant effect on purchasing decisions, is accepted. e. Hypothesis testing shows that brand trust has a regression coefficient of 0.206, which means it has a positive effect on purchasing decisions. P-values of 0.000 (less than 0.05) indicate a significant effect. Therefore, hypothesis 5 (H5), that brand trust has a positive and significant effect on purchasing decisions, is accepted. f. Hypothesis testing shows that brand engagement has a regression coefficient of 0.468, indicating a positive effect on brand trust. With P-values of 0.000 (less than 0.05), the effect is significant. Therefore, hypothesis 6 (H6), that brand engagement has a positive and significant effect on brand trust is accepted. 5.6.2. Testing The Direct and Indirect Influence of Variables This study examines the mediating role of Brand trust on the indirect influence of Brand engagement on purchasing decisions, as well as the role of Brand engagement on the indirect influence of social media marketing on purchasing decisions, with the results of the analysis presented in Table 14. 886 Edelweiss Applied Science and Technology ISSN: 2576-8484 Vol. 9, No. 6: 873-893, 2025 DOI: 10.55214/25768484.v9i6.7972 © 2025 by the authors; licensee Learning Gate Table 14. Recapitulation of Mediating Variable Test Results. Path Effect Information (A) (B) (C) (D) Social media marketing (X1) -> Brand trust (Y2) -> Purchase Decision (Y3) 0.046 (Sig.) 0.217 (Sig.) 0.222 (Sig.) 0.206 (Sig.) Partial Mediation Social media marketing (X1) -> Brand engagement (Y1) -> Purchase Decision (Y3) 0.382 (Sig.) 0.217 (Sig.) 0.802 (Sig.) 0.477 (Sig.) Partial Mediation Brand engagement (Y1) -> Brand trust (Y2) -> Purchase Decision (Y3) 0.133 (Sig.) 0.477 (Sig.) 0.648 (Sig.) 0.206 (Sig.) Partial Mediation Based on Table 14, brand trust mediates the influence of social media marketing on purchasing decisions. Mediation testing shows that effects A, B, C, and D are significant, so brand trust acts as a partial mediator. This means that the better the social media marketing, the higher the brand trust, which ultimately increases purchasing decisions, meaning that hypothesis (H7) is accepted. Brand engagement partially mediates the influence of social media marketing on purchasing decisions. The results of the mediation test show that effects A, B, C, and D are significant. This shows that the better the social media marketing, the higher the brand engagement, which ultimately also increases purchasing decisions. This also means that hypothesis (H8) is accepted. Brand trust partially mediates the influence of brand engagement on purchasing decisions. Mediation testing shows that effects A, B, C, and D are significant. This means that the better the brand engagement, the higher the brand trust, which ultimately increases purchasing decisions. This indicates that hypothesis (H9) is accepted. 6. Discussion 6.1. The Influence of Social Media Marketing on Purchasing Decisions Based on the results of hypothesis testing, social media marketing has a positive and significant influence on Gen Z purchasing decisions in fashion MSMEs in Bali. This means that the more effective the use of social media marketing by fashion MSMEs, the more Gen Z purchasing decisions in Bali will increase, especially those reflected in the accuracy of purchasing products. In this study, the social media marketing variable was measured through five indicators, including creating interesting content, using social media as a liaison with consumers, providing complete product information, and uploading fashion MSME content on personal social media. The results of the outer model show that the main indicator of social media marketing is creating interesting content (X1.1), while purchasing decisions are reflected in the accuracy of purchasing products (Y3.3) with an outer loading of 0.933. This study enriches the Theory of Planned Behavior [31] which focuses on purchase intention by adding social media marketing as an exogenous variable and brand engagement and brand trust as mediating variables. These results are consistent with previous studies, such as Fahmi, et al. [32]; Duffett [33]; Duffett [34] and Ismail [17] which show that social media marketing increases purchasing decisions and influences brand perception [35]. This study is in line with the research of Arif [4]; Haryadi, et al. [5] and Nanda and Nilowardono [6] this is indicated by the increasing search for certain brands by customers using social media. 6.2. The Influence of Social Media Marketing on Brand Engagement The results of the hypothesis test show that social media marketing has a positive and significant influence on brand engagement. This means that the better the use of social media marketing by fashion MSMEs, the higher the brand engagement of fashion MSMEs in Bali. Brand engagement is measured through indicators of enthusiasm, attention, absorption, interaction, and identification, with identification as the main indicator with a loading factor of 0.690. Meanwhile, social media marketing is measured through the creation of interesting content, which significantly influences the brand identity 887 Edelweiss Applied Science and Technology ISSN: 2576-8484 Vol. 9, No. 6: 873-893, 2025 DOI: 10.55214/25768484.v9i6.7972 © 2025 by the authors; licensee Learning Gate of fashion MSMEs in Bali. This study is in line with previous studies by Buzeta, et al. [36]; Dolan, et al. [37]; Gavilanes, et al. [38] and Meire, et al. [39] who found that brand engagement is influenced by interesting and informative content on social media. In addition, research by Osei-Frimpong and McLean [40] and Kulikovskaja, et al. [41] also confirmed the positive relationship between social media marketing and brand engagement. 6.3. The Influence of Social Media Marketing on Brand Trust The results of the hypothesis test show that social media marketing has a positive and significant effect on brand trust. This means that the effective use of social media marketing by fashion MSMEs can increase customer trust in fashion brands in Bali. Brand trust is reflected in partnerships with customers, which have the highest outer loading (0.913), while social media marketing is reflected in the creation of interesting content. Thus, interesting content can increase customer trust in partnerships with brands. This study is consistent with the findings of Delgado-Ballester [42] and Primaskara, et al. [43] which state that social media marketing directly influences consumer trust in brands. Other studies also support that marketing through social media, such as Facebook, strengthens awareness and trust in Amazon and Flipkart brands [44]. In addition, a study in a Jordanian beauty center [45] showed a significant impact of social media marketing on brand trust. According to Mosavi and Kenarehfard [46] and Takaya, et al. [47] social media influences consumer marketing experiences and strengthens brand trust. Brand engagement through social media increases customer trust with interactive communication, product personalization, and price transparency [48]. 6.4. The Influence of Brand Engagement on Purchasing Decisions The results of the hypothesis test show that brand engagement has a positive and significant influence on Gen Z purchasing decisions in fashion MSMEs in Bali. This means that the better the brand engagement implemented by fashion MSMEs, the higher the Gen Z purchasing decisions. The self-identity indicator is the main reflection of the brand engagement variable with the highest loading factor, while the accuracy of the purchase reflects the purchasing decision. The stronger the consumer identity, the higher their intention to purchase. This study is consistent with the findings of Naeem and Ozuem [49]; Rosadi, et al. [50] and Malthouse, et al. [51] which state that engaged customers tend to show more positive purchasing behavior towards a brand's products. Barhemmati and Ahmad [52] added that customer engagement builds a sense of ownership of the brand, which then influences purchasing decisions. Prentice and Loureiro [53] and Prentice, et al. [54] also stated that strong brand engagement can create relationships with potential new consumers, offer benefits such as discounts, and encourage increased purchasing intentions in the future [55]. 6.5. The Influence of Brand Trust on Purchasing Decisions The results of the hypothesis test show that brand trust has a positive and significant influence on Gen Z's purchasing decisions in fashion MSMEs in Bali. This means that the higher the trust in the brand, the higher the purchasing decision of fashion MSME products by Gen Z in Bali. This study is in line with Takaya, et al. [47] which shows that brand trust has a positive effect on purchase intentions. Amron [56] also supports that brand trust influences purchasing decisions, as found by Ermawati [57]; Mahliza, et al. [58]; Punyatoya [59] and Limbu, et al. [60] who found a significant positive relationship between brand trust and purchasing decisions. 6.6. The Influence of Brand Engagement on Brand Trust The results of the hypothesis test show that brand engagement has a positive and significant influence on Gen Z's brand trust in fashion MSMEs in Bali. This means that the better the brand engagement implemented, the higher Gen Z's trust in fashion MSMEs in Bali. Kumar, et al. [61] found 888 Edelweiss Applied Science and Technology ISSN: 2576-8484 Vol. 9, No. 6: 873-893, 2025 DOI: 10.55214/25768484.v9i6.7972 © 2025 by the authors; licensee Learning Gate that increasing brand engagement can increase turnover by up to 23%. Strong relationships with consumers drive positive attitudes and behaviors toward brands and create long-term relationships [23]. Other studies such as Elfira and Budiono [62]; Sujana and Sari [63]; Sohail, et al. [64]; Chairunnisa and Ruswanti [65]; Aditya and Setyawan [66]; Mosavi and Kenarehfard [46]; Tuti and Sulistia [67]; Samarah, et al. [68] and Cahyadi and Tunjungsari [69] also support the positive influence of brand engagement on brand trust. 6.7. The Role of Brand Engagement in Mediating the Influence of Social Media Marketing on Purchasing Decisions The influence of social media marketing on purchasing decisions is mediated by brand engagement, which involves a direct relationship between social media marketing and brand engagement, as well as the influence of brand engagement on purchasing decisions. Research shows that social media marketing has a direct and significant effect on brand engagement. This means that the more effective social media marketing used by fashion MSMEs, the higher their brand engagement. Brand engagement also has a significant effect on increasing Gen Z purchasing decisions in fashion MSMEs in Bali. Brand engagement acts as a partial mediator in this research model. Sharma and Menka [70] and Ali and Shaiq [71] support this finding by stating that active engagement on social media increases loyalty and purchasing behavior. Malthouse, et al. [51] and Dankwa [72] also emphasized that brand engagement mediates social media interactions and purchasing decisions. 6.8. The Role of Brand Trust In Mediating the Influence of Social Media Marketing on Purchasing Decisions The influence of social media marketing on purchasing decisions is mediated by brand trust, involving a direct relationship between social media marketing and brand trust and its influence on purchasing decisions. Research shows that social media marketing has a significant direct effect on brand trust. Thus, the better the social media marketing strategy used by fashion MSMEs, the higher the brand trust formed. This brand trust also has a significant effect on increasing Gen Z purchasing decisions in fashion MSMEs in Bali. Brand trust acts as a partial mediator in this model, in accordance with research by Vidyanata [73] and Yusuf [74] and supported by Zanjabila, et al. [75]; Hartayani and Seminari [76] and Levina, et al. [77]. The role of brand trust in mediating the influence of brand engagement on purchasing decisions The influence of brand engagement on purchasing decisions is mediated by brand trust, with a direct relationship between engagement and brand trust and its impact on purchasing decisions. Research shows that brand engagement significantly increases brand trust. The stronger the brand involvement, the higher the brand trust. Brand trust has also been shown to significantly influence Gen Z purchasing decisions in fashion MSMEs in Bali. Brand trust acts as a partial mediator in this model. These results are consistent with the findings of Naeem and Ozuem [49]; Rosadi, et al. [50] and Malthouse, et al. [51] which state that customer involvement and brand trust play an important role in purchasing decisions. Other studies have also found that brand trust has a positive effect on purchasing decisions [57, 58, 60]. 7. Conclusions and Suggestions Based on the research results, it can be concluded that. Social media marketing has a significant positive effect on purchasing decisions, meaning that the better the social media marketing, the higher the Gen Z purchasing decisions in Balinese fashion MSMEs. Social media marketing also has a positive effect on the brand engagement of fashion MSMEs. The brand engagement has a significant effect on brand trust; the stronger the brand engagement, the higher the brand trust. Brand engagement increases purchasing decisions in fashion MSMEs. Brand trust also has a positive effect on Gen Z's 889 Edelweiss Applied Science and Technology ISSN: 2576-8484 Vol. 9, No. 6: 873-893, 2025 DOI: 10.55214/25768484.v9i6.7972 © 2025 by the authors; licensee Learning Gate purchasing decisions. Brand engagement strengthens Gen Z's trust in fashion MSMEs in Bali. Brand engagement partially mediates the effect of social media marketing on purchasing decisions. Brand trust mediates the effect of brand engagement on purchasing decisions. Brand trust mediates the effect of brand engagement on Gen Z purchasing decisions. In addition, several suggestions can be given based on the research results, namely: Design attractive products so that Gen Z is interested in sharing them on social media. Create unique designs that become the identity of Gen Z in Bali. Continue to innovate and follow fashion trends to increase Gen Z's trust. 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