Edelweiss Applied Science and Technology ISSN: 2576-8484 Vol. 8, No. 6, 3886-3901 2024 Publisher: Learning Gate DOI: 10.55214/25768484.v8i6.2845 © 2024 by the authors; licensee Learning Gate © 2024 by the authors; licensee Learning Gate * Correspondence: tyaswidiautami@student.telkomuniversity.ac.id The effect of e-service quality on customer satisfaction with repurchase intention as a moderating variable in the Soco by Sociolla application Tyas Widia Utami1, Agus Maolana Hidayat2* 1,2School of Economics and Business Telkom University, Indonesia; agusmh@telkomuniversity.ac.id (T.W.U.) tyaswidiautami@student.telkomuniversity.ac.id (A.M.H.). Abstract: This study investigates the influence of e-service quality on customer satisfaction with repurchase intention as a moderating variable, focusing on the SOCO by Sociolla app. Using a quantitative approach and a sample of 400 respondents, this research applies Partial Least Squares (PLS) analysis to assess the relationships among e-service quality, customer satisfaction, and repurchase intention. The results reveal that e-service quality significantly impacts customer satisfaction, indicating that higher service quality fosters customer contentment in digital shopping experiences. Additionally, repurchase intention slightly moderates this relationship, suggesting that consumers' likelihood to repurchase may influence their satisfaction levels derived from service quality. These findings highlight the need for e-commerce platforms, particularly in the beauty industry, to optimize e-service quality to boost satisfaction and repurchase rates. This research contributes to understanding digital consumer behavior and offers practical insights for enhancing service quality in online retail. Keywords: Customer satisfaction, E-service quality, Repurchase intention. 1. Introduction In today's globalization era, lifestyle patterns are increasingly transitioning from offline to online for various activities, largely due to the essential role of internet-based technology, which has become a fundamental necessity for everyone. The internet (interconnected network) plays a very diverse role, ranging from searching or exchanging information with a wider range, as a medium of education, business media, and entertainment, to interact, facilitating transactions, and much more. With the rapidly growing digital transformation, humans are required to follow an increasingly modern lifestyle by utilizing the sophistication of technology that continues to develop endlessly (Yusuf et al., 2020). The development of internet-based technology not only changes the lifestyle of individuals but also encourages the growth of business sectors, giving a positive impact on business people, especially those who have creative ideas to continue to improve their quality. Internet-based technology is very supportive of business growth because with this technology, businesses can be maximized and work can be optimized with an online system. (Shabrina, 2019). Doing business by utilizing the internet opens up wider market opportunities, facilitates product promotion, and helps find consumers or customers. Sari et al. (2018) emphasize that online customer reviews provide a faster methodology to gauge customer satisfaction compared to traditional sampling methods. People in the modern era are more interested in practical and efficient products and services, such as the use of online purchasing services (Kehista et al., 2023). Seeing the number of internet users in Indonesia, the internet now has a big role in helping every activity of society, especially in fulfilling daily needs. The development of Internet technology also affects consumer shopping patterns, so both small businesses and large companies are turning to the digital world to grow their businesses. Currently, the number of e-commerce players in Indonesia is also increasing. The growth of e-commerce continues to show the potential to develop various 3887 Edelweiss Applied Science and Technology ISSN: 2576-8484 Vol. 8, No. 6: 3886-3901, 2024 DOI: 10.55214/25768484.v8i6.2845 © 2024 by the authors; licensee Learning Gate business fields. (Mufidatul Himmah & Sania, 2023).. All industries are starting to transform to implement digital-based businesses, including the beauty industry which is starting to develop its business digitally. This is evidenced by the increasing growth of e-commerce, which is competing to offer the advantages of their products in various ways to attract consumer attention (Wiryana & Erdiansyah, 2020). In the early days of online retail, website presence and low prices were believed to be the main success factors for online stores. However, the absence of physical instruments and direct interaction between sellers and buyers requires companies to prove that they are worthy of being the choice of consumers who want to buy products, by improving the quality of their services. Cronin & Taylor (1992) in (Ayu & Praneta, 2023) suggests that service quality is a concept that is difficult to explain and measure. The assessment of good and bad service quality depends on consumer assessments during the process of obtaining services from the company. In 1988, Parasuraman proposed a model used to measure service quality using five measurement dimensions - tangible, reliability, responsiveness, assurance, and empathy (Girsang, 2022). However, with the increasing application of online services in the business world, the measurement of e-service quality is getting more attention. Experts feel the need for adjustments to the SERVQUAL model so that it can be used to measure e-service quality. This is due to the difference between service quality and e-service quality, namely the absence of serving officers and physical elements that can be seen or felt by consumers themselves. (Wiatna & Sanaji, 2022).. From the adjustment of the SERVQUAL model, a model that can be used to measure online service quality called e-SERVQUAL emerged. This model consists of seven dimensions: efficiency, reliability, fulfillment, privacy, responsiveness, competence, and contact. Good electronic service quality and in accordance with consumer expectations show that the company is consumer-oriented. Companies will try to understand the desires of their consumers by increasing their customer satisfaction (Kusherawati et al., 2023). According to Heiller et al. (2003) in (Wungkana & Santoso, 2021)According to Heiller et al. (2003) in (Wungkana & Santoso, 2021), overall customer satisfaction is related to the intensity of reuse of services from the same provider. Satisfactory service quality will encourage consumers to return to visit the company's website, which in turn will increase consumer loyalty to the company. E-satisfaction refers to the feeling of customer satisfaction derived from prior shopping experiences on a specific e-commerce platform, which results in positive responses such as purchases and repurchases. (Carla M. R. Da et al., 2023).. According to (Rizal Nur Qudus & Sri Amelia, 2022)(Rizal Nur Qudus & Sri Amelia, 2022), repurchase intention refers to the possibility or opportunity to use the same service provider or service in the future. “Expectation-confirmation theory (ECT)” helps explain the relationship between e-satisfaction and repurchase intentions. According to this theory, buyers' intention to repurchase or continue using a service depends on the extent to which they are satisfied with their previous usage experience. (Wiatna & Sanaji, 2022). Various factors influence repurchase intentions, including “e-service quality”, which has been shown to have a significant impact on such intentions (Anggraini et al., 2020). Findings of the study (Sugiharto & Wijaya, 2020) and (Zakiyah, 2024) mentioned similar research results reinforcing the factor of service quality. According to the findings from the research conducted by Statista in 2022, the results indicate that Sociolla was ranked as the most popular cosmetics e-commerce site in Indonesia in the second quarter of 2022. This research is based on total visits to the website, where Sociolla recorded around 1.426 million visits, far ahead of Sephora which gained around 313 thousand visits. The rapid growth of e-commerce has caused competition among them to become increasingly fierce. To be able to compete, the company provides sales through the SOCO website and application. (Putri & Patrikha, 2021). In addition, companies also should focus on enhancing the quality of their electronic services, because these platforms are the media that consumers will use to make purchases. In the business environment in this era of globalization, service quality is an important key to competition. Business actors must provide optimal satisfaction to customers. If the company cannot meet customer 3888 Edelweiss Applied Science and Technology ISSN: 2576-8484 Vol. 8, No. 6: 3886-3901, 2024 DOI: 10.55214/25768484.v8i6.2845 © 2024 by the authors; licensee Learning Gate expectations, they are likely to feel disappointed. Conversely, if the company can meet or even exceed customer expectations, they will feel satisfied. Shopping behavior is currently also changing, with people preferring to make purchases online. Online shopping is increasingly popular because it is considered more time-saving and provides more flexibility in choosing goods. The current changes in the cosmetics industry show that companies are not only focusing on creating new and exciting products, but also realizing the importance of how they market these products. Many cosmetic companies follow the market trend by making sales online and through e- commerce. One of the cosmetic sales applications that are in great demand by consumers is SOCO by Sociolla, which was founded by PT Social Bella Indonesia. SOCO by Sociolla e-commerce attracts many consumers because the products sold are BPOM certified and the company is able to guarantee the authenticity of the products offered. This also attracts investors to invest in this company. According to research conducted by (Wulandari, 2021), during the COVID-19 pandemic, Sociolla received funding of USD 58 million (around IDR 837 billion), with the potential for the beauty care market to grow to USD 8.5 billion (around IDR 122.7 trillion) by 2022. The advantages of SOCO by Sociolla e-commerce are not limited to guaranteeing product authenticity. This application also provides a beauty journal feature that contains articles and personal experiences of consumers after purchasing products in the application. In addition, SOCO by Sociolla also offers a beauty profile feature, where users are asked to enter their data according to their skin type before using the application. This feature aims to provide product recommendations matching the user's entered data. This functionality simplifies the process for consumers to find beauty products that suit their preferences. In the SOCO by Sociolla application, all application users can provide reviews related to the experience or online shopping experience carried out in the application. Based on the Ratings and Complaints of SOCO by Sociolla App Store and Play Store Users (accessed October 15, 2023), SOCO by Sociolla still has several shortcomings and obstacles. This can be seen from the App Store and Play Store ratings. In the App Store application, Soco by Sociolla gets a review of 3.4 stars out of 5; this shows obstacles and shortcomings in the Soco by Sociolla application. On the Play Store, Soco by Sociolla gets a review with 4.1 out of 5 stars, the rating system looks at the number of stars, where a higher star value indicates better app performance. The satisfaction of customers who shop through e-commerce can also be influenced by the e- service quality provided by the company. E-service quality is defined as "the extent to which a website facilitates shopping, purchasing, and delivering products and services effectively and efficiently". (Wiryana & Erdiansyah, 2020). In a competitive digital world, high-quality service is a key factor to attract and retain customers. Customer satisfaction, which is a key indicator of business success, largely depends on how well companies meet customer expectations and needs through their services. If the company is able to provide good service, customers will feel satisfied. Previous research from (Dewantara, 2022) and (Kurniawan & Remiasa, 2022) states “e-service quality variables have a significant influence on customer satisfaction”. (Hariansyah et al., 2019) emphasize the importance of improving service quality systems to ensure business continuity, because quality services not only provide better value for customers but also contribute to higher levels of satisfaction. Based on (Gultom et al., 2020), customer satisfaction can be measured through repeat purchases on the website, making the right choices when purchasing, and feeling satisfied every time you buy through the website. Hence, it is essential to properly consider e-service quality to achieve customer satisfaction when shopping via e-commerce. Even though earlier studies have demonstrated that “e-service quality has a significant effect on customer satisfaction” (Dewantara, 2022; Kurniawan & Remiasa, 2022), there are still many customer complaints about the SOCO by Sociolla application, such as stock availability problems, delivery errors, and suboptimal application performance after updates (Putri & Patrikha, 2021). Thus, it is important to investigate the specific factors within e-service quality that have the greatest impact on customer satisfaction on the SOCO by Sociolla platform, as well as how improvements in these aspects can increase buyer satisfaction and repurchase intentions. Customer satisfaction is significantly affected by previous shopping experiences, but there is 3889 Edelweiss Applied Science and Technology ISSN: 2576-8484 Vol. 8, No. 6: 3886-3901, 2024 DOI: 10.55214/25768484.v8i6.2845 © 2024 by the authors; licensee Learning Gate significant dissatisfaction with e-service in the SOCO by Sociolla app, as reflected by inconsistent ratings between the App Store and Play Store (Wungkana & Santoso, 2021). And although e-service quality and customer satisfaction have a significant relationship with repurchase intentions, there is still uncertainty about the extent to which customer satisfaction in the SOCO by Sociolla app drives repurchase intentions, especially given the various complaints filed by users (Zakiyah, 2024). In the competitive e-commerce business, there are tons of websites and apps that sell a variety of needs. Some e-commerce sells all the products needed, while others focus on one product category, such as electronics, fashion, or beauty. One e-commerce that focuses on one product category is Sociolla, which has been selling beauty products since 2015 and was founded by John Rasjid. According to the data on the largest "E-Commerce platforms by visitor count in the third quarter of 2019" (Databoks Katadata, 2019), Sociolla ranks among the top 10, securing the 8th position in visitor numbers and is the leading beauty e-commerce site with the highest traffic. Therefore, according to the phenomena contained in the background, the researcher is interested in conducting research entitled "The Effect of E-Service Quality on Customer Satisfaction with Repurchase Intention as a Moderating Variable in the Oco by Sociolla Application". The problem formulation will identify two key questions to be answered in the research. First, the research will investigate whether there is a “significant relationship between e-service quality and customer satisfaction in the SOCO app?” This is important to understand how much influence service quality has on user experience. Second, the study will examine the role of repurchase intention as a moderating factor. This is done to determine whether customers repurchase intentions strengthen or weaken the relationship. The focus of the research aims to: 1) identify the impact of e-service quality in influencing customer satisfaction in the SOCO application by Sociolla. 2) To find out whether moderation of repurchase intention can strengthen or weaken e-service quality on customer satisfaction in the SOCO by Sociolla application. This research has theoretical benefits in the form of contributions in the development consumer habits theory through the analysis of variables including “e-service quality, customer satisfaction, and repurchase intentions”. Practically, this research provides the author with additional insight and application of knowledge in the world of work, provides input companies to achieve targets, and enriches references at Telkom University, especially for students and related parties in need. 2. Literature Review 2.1. Digital Marketing As stated by Rauf et al. (2021), "Digital marketing refers to the use of the internet and associated digital technologies alongside traditional communication methods to meet marketing goals." This means that digital marketing encompasses the utilization of the internet and related digital tools in combination with conventional communication strategies to fulfill marketing objectives. Lara (2022) further explains that digital marketing fundamentally involves marketing activities that leverage digital media and the internet. This approach includes utilizing platforms such as websites, social media, email, databases, mobile technologies, and digital television to engage target consumers and achieve marketing goals. From some of the experts' opinions, it can be concluded that digital marketing is a marketing or promotional activity that utilizes digital media such as web, social media, email, database, mobile- wireless, and digital TV. The purpose of digital marketing is to make it easier for businesses or marketers to reach consumers or potential consumers, as well as increase marketing and target consumers. Digital marketing methods include: (1) Content Marketing – reaching and retaining customers through content tailored to their interests; (2) Search Engine Marketing – finding product information through search engines; (3) Social Media Strategy – marketing via platforms like Facebook and Twitter; (4) Pull Concept – consumers actively seek product information; (5) Push Concept – marketers reach customers via email, SMS, etc.; (6) Pay-Per-Click (PPC) – paid clicks to drive traffic to websites (e.g., Google Adwords); (7) Influencer Marketing – using individuals with 3890 Edelweiss Applied Science and Technology ISSN: 2576-8484 Vol. 8, No. 6: 3886-3901, 2024 DOI: 10.55214/25768484.v8i6.2845 © 2024 by the authors; licensee Learning Gate significant social influence; (8) Google My Business – provides business information for easy customer access; and (9) Marketing Automation – automating repetitive tasks like content scheduling on various platforms. Electronic word-of-mouth (eWOM) has become a significant influence in digital marketing, where peer reviews and user-generated content on social media play a pivotal role in shaping purchase intention (Yones & Muthaiyah, 2023). 2.2. E-Service Quality E-Service Quality, or electronic service quality, refers to how well a website enables shopping, purchasing, and the delivery of products and services through efficient and effective services (Pramesti et al., 2023). Parasuraman et al. (2005) in (Dian & Rusfian, 2023) added that consumer assessment of a site is not only based on the experience of interaction with the site but also includes aspects of service after interaction. Rabbani (2021) utilized text mining methods such as multiclass classification and sentiment analysis to identify key dimensions of e-service quality in beauty e- commerce. The study, which focused on Sociolla, relevead that effiecny, system availability, fulfillment, and responsiveness. (Damayanti, 2021), which states that the evaluation of service quality results from a comparison between the perception of the service received and the previous expectations of what the service should provide. Generally, online customers always expect the same or higher level of service quality compared to traditional channel customers. (Yusuf et al., 2020). Based on the above explanation, it can be concluded that electronic service quality refers to the actions and competencies of employees within a company, performed with complete dedication to delivering superior service to consumers via electronic channels. The quality of e-services can be assessed through the concept of e-ServQual, developed by Parasuraman, which consists of seven dimensions: efficiency, fulfillment of needs, system availability, privacy, responsiveness, compensation, and service contact. The seven indicators of E-SERVQUAL, as described by Parasuraman et al. (2005) in (Al-Araj et al., 2022) include several key aspects that contribute to effective online service quality. Efficiency refers to how easily customers can navigate the website, search for information, and access it quickly, making the process more efficient. Fulfillment measures how well the site meets its promises regarding product availability and order completion. System availability addresses whether the system provides accurate and relevant payment options and information to customers. Privacy ensures the security of customer data, protecting personal and transactional information, and offering guarantees where necessary. Responsiveness highlights the ease with which customers can seek assistance when they encounter issues or have inquiries. Compensation relates to the correct and appropriate use of guarantees and the reliability of such features. Lastly, Contact focuses on providing customers with accessible ways to reach customer service when needed. 2.3. E-Satisfaction According to Oliver in the research conducted by Dewantara (2022), E-Satisfaction refers to a psychological state achieved when a customer feels satisfied enough that they no longer seek alternatives to the current website they are using. Girsang (2022) defines E-Satisfaction as the experience one feels after using a product, which involves comparing the perceived quality to the expected quality. Chandra et al. (2022) state that E-Satisfaction arises when products and services exceed consumer expectations, representing the level of buyer satisfaction after comparing their actual experiences with their pre-purchase expectations. Rita et al. (2019) characterize E-Satisfaction as the feelings consumers have towards a website, stemming from various factors that shape the consumer's relationship with the company. From these definitions, it can be concluded that E- Satisfaction is a psychological state in which consumers feel content after using a website and do not search for alternatives during that time. According to Irawan (2003: 24) there are 3 dimensions of customer satisfaction, namely; a. Satisfaction Toward Quality, which is satisfaction with product quality and for industrial services, quality refers to service quality. b. Staisfaction toward Value, namely satisfaction with the price with the level of quality received. 3891 Edelweiss Applied Science and Technology ISSN: 2576-8484 Vol. 8, No. 6: 3886-3901, 2024 DOI: 10.55214/25768484.v8i6.2845 © 2024 by the authors; licensee Learning Gate c. Perceived Best, which is to determine the belief whether the product brand used is the best quality compared to other competing product brands. Measurement of customer satisfaction according to Tjiptono & Gregorious (2011: 453) in (Subarto & Kurniawaty, 2021) formulated as follows: 1. Overall satisfaction, which is the overall satisfaction with a customer experience after consuming or using a product. 2. Confirmation Expectation, namely the suitability of the product or service offered with customer expectations as perceived by the customer, meaning that the customer does not regret using a product. 3. Comparison to Ideal, namely the level of satisfaction experienced by customers after consuming or using the product. 2.4. Repurchase Intention Doosti et al., (2016) in (Norhermaya & Soesanto, 2019) defines Repurchase intention as a situation where consumers tend to buy certain products under certain conditions. (Kotler & Keller, 2016) defines intention as a consumer's decision about brand preference in the choice set. (Keller & Kotler, 2012) defines intention as all consumer actions to receive and use goods and services. Based on several definitions of intention above, it can be concluded that intention is everything that encourages someone to act or do something, such as buying a product or service. From these definitions, it can be interpreted that repurchase intention is a tendency and desire that strongly encourages individuals to buy a product. Repurchase intention is a type of decision making that studies the reasons for buying a particular brand by consumers. (Sari Mulia, 2023). Repurchase intention is usually related to consumer behavior, perceptions and attitudes. (Ratna Siwi & Management Studies, 2023)said that Repurchase intention provides a fairly acceptable approach to online shopping behavior. Purchasing behavior is a key point for consumers to access and evaluate certain products.(Wigati, 2019) states that repurchase intention is an effective tool for predicting the buying process. Repurchase intention can change under the influence of price or perceived quality and value. In addition, consumers are influenced by internal or external motivations during the buying process. Repurchase intention can be measured by asking the likelihood of consumers buying the advertised product. Fishbein and Ajzen (1975) in (Wuisan et al., 2020) argue that repurchase intention can be used as an indicator to predict consumer consumption behavior, which reflects subjective awareness or the likelihood of customer purchases. (Anastasia, 2022) also argues that repurchase intention provides a measure of the likelihood of customers buying a particular product, and that there is a positive correlation between repurchase intention and actual purchase. Repurchase intention is related to service quality, because service quality is one of the predictors of repurchase intention. Furthermore, repurchase intention is an important factor in determining whether a product meets customers' expectations and needs to further explore their assessment of goods and services. This concept emphasizes that customers will be more satisfied when the quality of products and services meets their expectations. On the other hand, customers will be more dissatisfied if the quality of products and services is below their expectations. According to Margee and Mort (2008: 174) in (Pramesti et al., 2023)According to Margee and Mort (2008: 174) in (Pramesti et al., 2023), Repurchase Intention is defined as an individual's assessment of the purchase of services again and the decision to engage in future activities with that service provider. The desire to repurchase a product or service will arise when the customer feels that the service, he receives can provide satisfaction and trust in him. If the customer is satisfied and trusts the first purchase, then the next purchase tends to be made repeatedly on one brand, so that decision making is no longer needed because the customer already knows deeply about the brand. According to Ferdinand (2006) in (Wiryana & Erdiansyah, 2020), purchase interest can be identified through several indicators. First, transactional interest, which reflects the tendency to buy a product. Second, referential interest, which is a person's tendency to recommend a product to others. Third, preferential interest, which describes the behavior of someone who has a primary 3892 Edelweiss Applied Science and Technology ISSN: 2576-8484 Vol. 8, No. 6: 3886-3901, 2024 DOI: 10.55214/25768484.v8i6.2845 © 2024 by the authors; licensee Learning Gate preference for a particular product, and this preference will only change if something happens to the selected product. Finally, explorative interest, which shows the behavior of individuals who continue to seek information about the product of interest and seek support for the positive properties of the product. 3. Research Hypothesis A hypothesis is a provisional answer to a research problem, formulated as a question. It is considered provisional because the answer is based solely on relevant theories and has not yet been supported by empirical evidence collected through data (Sugiyono, 2020). Based on the explanation and background of the problem above, the researcher formulates the hypothesis as follows: H1: There is an influence between E-Service Quality on customer satisfaction in the SOCO by Sociolla application. H2: Repurchase Intention is able to moderate the effect of Overall E-Service Quality on customer satisfaction in the SOCO by Sociolla application. 4. Methods 4.1. Type of Research Based on the problem under study, the type of research used is quantitative research. This research uses quantitative methods. This study aims to determine the effect of e-service quality on customer satisfaction with repurchase intention as a moderating variable in the Soco by Sociolla application. 4.2. Population and Sample The study or research is also called a population study or census study. The population in this study are customers or users of the Soco by Sociolla application. The Lemeshow formula is a formula used to determine the number of unknown samples. The sample will greatly affect the representation of the population in a research process. If the population size (N) is unknown, the Lemeshow formula will be used.7 The Lemeshow formula for determining the sample size in an unknown population. 5. Results 5.1. Description of the Research Object This study was carried out in the user environment of the Soco by Sociolla application, which is a rapidly growing e-commerce platform in Indonesia. The participants in this study include customers or users of the Soco application without any particular criteria. The research aims to investigate users' behaviors and attitudes towards the application, as well as the elements that affect their shopping choices. The sample for this study consisted of 400 respondents, all of whom are users of the Soco by Sociolla application First, primary data is collected directly from respondents through questionnaires, which aim to obtain information directly from users about their experiences and preferences of the Soco app. Secondary data, meanwhile, includes information taken from other previously published sources, to provide additional issues or background for the research. The subsequent section presents a summary of the data collected from the participants in this study, such as: Table 1. Gender distribution of participants. No. Gender Total Percentage 1 Men 132 33% 2 Women 268 67% Total 400 100% Referring to the table above, the results show that if respondents in this study were mostly women with 268 respondents or as many as 67%, while male respondents only totaled 132 respondents or 33%. 3893 Edelweiss Applied Science and Technology ISSN: 2576-8484 Vol. 8, No. 6: 3886-3901, 2024 DOI: 10.55214/25768484.v8i6.2845 © 2024 by the authors; licensee Learning Gate Table 2. Age of respondents. No. Gender Total Percentage 1 17-23 years 320 80% 2 24-28 years 79 19.75% 3 >29 years 1 0.25% Total 400 100% Based on Table 2 above, it shows that respondents with an age range of 17-23 years dominate with 320 or 80% of respondents. Followed by respondents with an age range of 24-28 years, totaling 79 or 19.75%. And the lowest is respondents with an age range ≥ 29 years which only amounted to 1 or 0.25%. 5.2. Data Analysis Measurement Model (Outer Model) Table 3. Outer loading. Variables Average variance extracted (AVE) Repurchase intention o.528 Customer satisfaction 0.540 E-service quality 0.589 5.2.1. Convergent Validity The outer loading output indicates that all indicators for each construct have achieved convergent validity, as the loading factors for each indicator are above 0.50. Table 4. Fornell-larcker criterion for discriminant validity. Repurchase intention (M) Customer satisfaction (Y) E-service quality (X) M.1 0.729 M.2 0.634 M.3 0.641 M.4 0.612 M.5 0.603 M.6 0.643 M.7 0.690 M.8 0.672 X1.1 0.644 X1.10 0.650 X1.11 0.627 X1.12 0.662 X1.13 0.633 X1.14 0.665 X1.2 0.577 3894 Edelweiss Applied Science and Technology ISSN: 2576-8484 Vol. 8, No. 6: 3886-3901, 2024 DOI: 10.55214/25768484.v8i6.2845 © 2024 by the authors; licensee Learning Gate X1.3 0.541 X1.4 0.633 X1.5 0.581 X1.6 0.680 X1.7 0.607 X1.8 0.550 X1.9 0.659 Y.1 0.736 Y.2 0.700 Y.3 0.676 Y.4 0.639 Y.5 0.619 Y.6 0.599 5.2.2. Discriminant Validity Seen from the table above, the AVE values for Repurchase Intention (0.528), Customer Satisfaction (0.540), and E-Service Quality (0.589) are all above 0.5. This indicates strong convergent validity, suggesting that the latent variables can, on average, explain more than half of the variance of their respective indicators. These values demonstrate that the construct effectively accounts for the variation in the associated indicators. 5.2.3. Reliability Test Reliability tests in research are useful for ensuring that measurement instruments, such as questionnaires, provide consistent and reliable results. The methods used to measure this reliability include, first, the “Cronbach's alpha” value to determine the minimum level of reliability of the measured construct. While “Composite reliability” provides a more accurate picture of how reliable variable indicators are in describing a larger construct. As a guideline, a construct is considered reliable if its composite reliability value is above 0.7 (Prayudi, 2022). Table 5. Reliability test with cronbach's alpha and composite reliability methods. Cronbach's alpha Composite reliability Repurchase intention 0.808 0.856 Customer satisfaction 0.743 0.824 E-service quality 0.880 0.899 The findings of the reliability test show that each variable in this study has a Composite Reliability value and the Cronbach's alpha value for each variable is above 0.7. Based on these findings, it can be concluded that all variables in this study are considered reliable. Table 6. Multicollinearity test (VIF). Repurchase intention Customer satisfaction E-service quality Repurchase intention 2.407 Customer satisfaction E-service quality 2.833 5.2.4. Multicollinearity Test From the results of the tests carried out, it is known that the “VIF value for the e-service quality variable on customer satisfaction is 2.833”, while the “VIF value for the customer satisfaction variable 3895 Edelweiss Applied Science and Technology ISSN: 2576-8484 Vol. 8, No. 6: 3886-3901, 2024 DOI: 10.55214/25768484.v8i6.2845 © 2024 by the authors; licensee Learning Gate on repurchase intention is 2.407”. From the VIF value, it can be concluded that all variables have passed the multicollinearity test, because the VIF value obtained is below the threshold of 10, which indicates the absence of multicollinearity. Figure 1. Structural model bootstrapping results. 5.3. Structural Model (Inner Model) The relationship between the constructs' significance values and the R-Square of the research model is evaluated using the inner model or structural model. The structural model is assessed by analyzing the significance of the structural path parameter coefficients, performing a t-test, and examining the R- Square value for the dependent constructs. Table 7. R square. Variables R Square R square adjusted Customer satisfaction 0.742 0.740 5.3.1. Value of Coefficient of Determination (R2) According to Table 7, the R Square value for the customer satisfaction variable is 0.742, indicating that this model is effective in the research context, as it successfully accounts for variability. This means that e-service quality and other factors can explain 74.2% of the variability in the customer satisfaction construct, while the remaining 25.8% is attributed to other constructs not included in this research model. Additionally, the Adjusted R value of 0.740 reflects an appropriate adjustment for the model. 3896 Edelweiss Applied Science and Technology ISSN: 2576-8484 Vol. 8, No. 6: 3886-3901, 2024 DOI: 10.55214/25768484.v8i6.2845 © 2024 by the authors; licensee Learning Gate Table 8. Q2 value results. SSO SSE Q² (=1-SSE/SSO) Repurchase intention 3200.000 3200.000 Customer satisfaction 2400.000 1663.610 0.307 E-service quality 5600.000 5600.000 5.3.2. Predictive Relevance Value (Q2) Based on the blindfolding test results in Table 8 above, Q2 for the customer satisfaction variable is 0.307. Based on these calculations, it can be said that Q2 predictive relevance is considered good because it has a value above 0.307. 5.3.3. Goodness of Fit (GoF) The goodness of fit (GoF) measurement is used to validate the overall performance of a model (Creswell, 2014). Table 9. Goodness of fit. Based on the results of the GoF analysis in this study, it can be concluded that the model used in this study has a GoF of 0.633 so that it can be said that this research model has a high Gof value and can be used to conclude that the model has a high level of ability to interpret empirical data (research samples). 5.3.4. Hypothesis Test Analysis Hypothesis testing findings are examined using t-statistic values and parameter coefficients to see how a construct affects other constructs (Ghozali & Latan, 2015). Table 10. Path coefficients. Original sample (O) Sample mean (M) Standard deviation (STDEV) T statistics (|O/STDEV|) P values E-service quality*repurchase Intention -> Customer satisfaction -0.034 -0.034 0.014 2.514 0.012 E-service quality -> Customer satisfaction 0.430 0.439 0.056 7.673 0.000 5.4. Hypothesis 1 The analysis findings show that the t-statistic for the effect of “E-Service Quality on Customer Satisfaction on the SOCO by Sociolla application” is 7.673, accompanied by a p-value of 0.000. Given that the t-statistic exceeds 1.966 (for a two-sided test), it can be concluded that the first hypothesis (H1) is accepted. The findings confirm that E-Service Quality has an effect on Customer Satisfaction in the SOCO by Sociolla application, thus implying that as the quality of electronic services provided by the SOCO application increases, customer satisfaction also increases. 3897 Edelweiss Applied Science and Technology ISSN: 2576-8484 Vol. 8, No. 6: 3886-3901, 2024 DOI: 10.55214/25768484.v8i6.2845 © 2024 by the authors; licensee Learning Gate 5.5. Hypothesis 2 The moderating effect of “Repurchase Intention on the relationship between E-Service Quality and Customer Satisfaction” shows that the Original Sample (O) value of -0.034 indicates that Repurchase Intention serves as a moderator, which slightly weakens the impact of E-Service Quality on Customer Satisfaction. Although this moderating effect is minimal and negative, the T-statistic of 2.514 (exceeds 1.966) and the p-value of 0.012 (below 0.05) indicate that this effect is statistically significant. Therefore, the second hypothesis (H2) was tested. Indicating that although Repurchase Intention slightly reduces the effect of E-Service Quality on Customer Satisfaction, the moderating effect remains statistically significant. 6. Discussion 6.1. The Effect of E-Service Quality (X1) on Customer Satisfaction (Y) The first hypothesis (H1) states that there is a positive influence between E-Service Quality and Customer Satisfaction. E-Service Quality refers to the quality of service provided through digital or electronic platforms, which includes various aspects such as efficiency, reliability, ease of use, and responsiveness to customer needs. Acceptance of this hypothesis indicates that the better the quality of electronic service provided by an application or website, the higher the level of satisfaction felt by customers. This can be interpreted that customer tend to feel more satisfied when they experience fast, easily accessible services that can meet their expectations when making online transactions. The positive impact observed suggests that as the quality of electronic services offered by the SOCO application improves, customer satisfaction levels also rise. Electronic service quality encompasses various factors, including interface design, responsiveness, transaction security, and the application's usability. When these elements are effectively addressed, customers are likely to feel satisfied, which can enhance their loyalty and willingness to make repeat purchases. In the competitive landscape of e-commerce, customer satisfaction plays a vital role. Research conducted by Dian & Rusfian (2023) indicates that e-service quality significantly boosts repurchase intention through its effect on customer satisfaction, highlighting the essential link between service quality, satisfaction, and repeat purchases. Likewise, the study by Wiatna & Sanaji (2022) demonstrates a mutual influence between e-service quality and e-satisfaction, emphasizing the critical role of service quality in fostering a positive customer experience. The research conducted by Sugiharto & Wijaya (2020) corroborates these findings by demonstrating that service quality influences both customer satisfaction and repurchase intention. This indicates that enhancing service quality not only boosts customer satisfaction but also increases the likelihood of repeat purchases. Additionally, the study by Chandra et al. (2022) highlights that all tested hypotheses related to e-service quality and customer experience significantly affect repurchase intention, reinforcing the critical role of customer satisfaction in this context. By providing high E-Service Quality, the SOCO app successfully meets customer expectations and fosters a positive shopping experience. This contributes to a favorable reputation among users, builds trust, and attracts more new customers. This aligns with the findings of Purnamasari & Suryandari (2023), which identified a positive correlation between e-service quality and customer behavior. Consequently, it can be concluded that e-service quality is vital in shaping customer satisfaction and loyalty. Therefore, the results of this study clearly illustrate the significance of E-Service Quality in influencing Customer Satisfaction, ultimately impacting purchasing decisions and customer loyalty within the SOCO by Sociolla application. 6.2. The Effect of E-Service Quality (X1) on Customer Satisfaction (Y) With Repurchase Intention (Xmod) as Moderation The second hypothesis (H2) highlights the role of Repurchase Intention (Xmod) as a moderating variable in the relationship between E-Service Quality (X1) and Customer Satisfaction (Y). This means that Repurchase Intention can affect the strength or direction of the relationship between the two variables. If Repurchase Intention is high, there may be a stronger impact of E-Service Quality on 3898 Edelweiss Applied Science and Technology ISSN: 2576-8484 Vol. 8, No. 6: 3886-3901, 2024 DOI: 10.55214/25768484.v8i6.2845 © 2024 by the authors; licensee Learning Gate Customer Satisfaction. Conversely, if Repurchase Intention is low, the effect of E-Service Quality on Customer Satisfaction may be reduced. In other words, Repurchase Intention can serve as a factor that strengthens or weakens the positive effect resulting from good e-service quality on customer satisfaction. Further research is needed to identify the extent of this moderating influence and how other factors may interact in this relationship. This finding underscores the crucial role of Repurchase Intention in the connection between E- Service Quality and Customer Satisfaction. In practical terms, while high E-Service Quality is expected to enhance customer satisfaction, the presence of moderate repurchase intentions indicates that customers may adopt a more critical perspective on their experiences. This implies that customers familiar with the app may have elevated expectations, potentially diminishing the positive effects of good e-service quality on their overall satisfaction. Supporting this, previous research by Wiatna & Sanaji (2022) revealed that e-service quality influences both e-satisfaction and repurchase intention, confirming that moderating factors can shape customer perceptions. Additionally, findings from Chandra et al. (2022) indicate that customer experience significantly affects repurchase intention, aligning with the hypothesis that repurchase intention can alter the impact of e-service quality on customer satisfaction. The results of this study demonstrate that while E-Service Quality positively contributes to Customer Satisfaction, the moderating effect of Repurchase Intention introduces complexities in this relationship. High customer expectations can significantly influence their experiences and overall satisfaction. Research by Rita et al. (2019) shows that e-service quality significantly impacts customer behavior. Similarly, Wilson et al. (2019) emphasizes the varying importance of service quality in the e- commerce sector across different geographical regions. Furthermore, studies by Precia et al. (2022) and Purnamasari & Suryandari (2023) affirm that e-service quality and customer satisfaction significantly influence repurchase intentions, with satisfaction serving as a mediator in this dynamic. Overall, this study's findings indicate that while E-Service Quality positively affects Customer Satisfaction, the moderating role of Repurchase Intention highlights the relationship's complexity. Customers with prior experiences may develop higher expectations, which service providers must consider to improve customer satisfaction and encourage future loyalty. 7. Conclusion Several conclusions can be drawn from this study. Firstly, E-Service Quality significantly influences Customer Satisfaction in the SOCO by Sociolla application. 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