Abstract

General Background: With the rapid evolution of technology and increasing reliance on the internet, mobile commerce (M-Commerce) has become a dominant channel for consumer transactions. Specific Background: Within this context, the quality of electronic services (E-Service Quality) and associated factors such as E-Trust, Complaint Handling, and Relationship Quality have become critical to fostering consumer loyalty. Knowledge Gap: However, limited research has examined the simultaneous effects of these factors alongside Consumers’ Negative Emotions and Forgiveness on Repurchase Intention in M-Commerce. Aims: This study aims to investigate the influence of E-Service Quality, E-Trust, Complaint Handling, Relationship Quality, Negative Emotions, and Forgiveness on Repurchase Intention among M-Commerce users. Results: Using a quantitative survey of 384 respondents in West Sumatra, Indonesia, and analysis tools including SmartPLS and SPSS 26, the findings reveal that E-Service Quality significantly enhances E-Trust and Repurchase Intention. E-Trust itself is a pivotal predictor of repurchase behavior. Negative emotions harm Relationship Quality and subsequently repurchase intentions, although strong relationship quality can mitigate these effects. Novelty: This study integrates emotional and relational variables in a unified M-Commerce model. Implications: The results underscore the importance of maintaining high service quality, trust, and complaint management strategies to retain customers and counteract emotional disruptions.

Highlights:

• Highlights the role of E-Trust in driving repurchase behavior.

• Integrates emotional and relational factors into M-Commerce research.

• Emphasizes complaint handling as a trust-building strategy.

Keywords: E-Service Quality, E-Trust, Complaint Handling, Repurchase Intention, M-Commerce

Introduction

M-Commerce is a place to sell goods or services via mobile devices[1]. Sellers and buyers who use m-commerce can make buying and selling transactions freely anytime and anywhere, as long as their personal devices are connected to the internet. [2]In comparison to e-commerce, mcommerce has additional advantages in terms of accessibility and flexibility. Mobile devices and smartphones have now become an inseparable part of everyday life. Currently, as many as 5.78 billion people in the world use mobile phones, which is equivalent to Over the last year, mobile phone subscriptions have grown by 112 million, reaching coverage of 70.5% of the global population, reflecting an annual This reflects a 2.0 percent growth. In addition, the data reveals that almost 87 percent of the total mobile phones used worldwide are smartphones . [3] The growing utilization of mobile applications has emerged as a major factor in driving the growth of

merchant revenues, especially in the Millennial and Generation Z consumer segments that have large purchasing power. In addition, consumer behavior that is increasingly skilled in using technology also supports the increase in purchase volume, given their tendency to make transactions via mobile devices [4].

In the midst of trade competition between offline and online, the shopping experience will greatly influence customers to show a propensity for future buying decisions [5]. Maintaining customer satisfaction represents a critical challenge for online shopping platforms.. Amidst the tight competition in the digital environment, the key to success lies in a service-oriented strategy. Companies need to provide a superior service experience so that customers are encouraged to make repeat purchases and remain loyal [5]

Various studies have examined the concept of e-service quality. Various attributes in eservice have been shown to have a significant relationship with the perception of overall e-service quality, customer satisfaction, and repurchase intentions, but not with consumer negative emotions[6]. Then the research conducted by Nega [7]which shows a significant The influence of consumers' negative emotions on repurchase intentions mediated by Relationship Quality, as well as . Research conducted by [8]which discusses the significant relationship between consumer forgiveness and repurchased intention. Then [9]based on the research conducted stated a significant influence between complaint handling with trust and also repurchase intention. In Indonesia itself, there are various cases, including cases of The number of transactions may diminish due to customers’ assessment of the service or E- service Quality carried out by Mcommerce to determine whether they will continue to shop or become a subscriber to the platform, and if the service provided to customers is good, the company is also said to be good[10]. With good service, customers will be motivated again to shop on the same platform [11], Hence, providing excellent service quality in m-commerce is crucial to foster customer confidence and comfort during mobile transactions. Trust plays a vital role in m-commerce and is strongly associated with E-Service Quality [5] . Service failure can trigger uncertainty about the company's future performance. In this context, trust plays an important role because it can reduce uncertainty and encourage consumers to make repeat purchases. Trust also shapes individual perceptions of the company, thus becoming an An important determinant in maintaining lasting relationships between consumers and essential element in establishing sustainable relationships between consumers and business actors. As a result, the connection between repurchase intentions and corporate trust represents a key managerial focus.. They need to understand how to rebuild consumer trust after a service failure, which emphasizes the importance of research on effective complaint handling strategies [9]. In the context of online sales, building trust will be much more challenging than in a conventional environment, because it is separated by a long distance, this is where complaint handling is important so that customers remain loyal and return to make purchases or repurchases.

Complaint Handling or complaint handling is a very important part, because in this technological era if the complaint handling is bad, customers can be disappointed and make posts on social media which is an outburst of negative emotions that arise due to poor handling which affects the customer's willingness to make repeat purchases or repurchase, and customers will only be satisfied if complaints are handled according to their preferences, and this study will discuss how to handle complaints online and how to evaluate the willingness to repeat purchases or repurchase. Because this is related to building trust between companies or mcommerce and customers [9].

Consumer Negative Emotion or negative emotions felt by consumers because the service provided does not match what consumers expect, and after consumers complain about the complaint to the company, instead of a solution being provided, customers are disappointed, As exemplified by the case of OTAs operating in China, where the room provided does not match the facilities offered, which makes customers disappointed, when complaints and refunds are made, the company only returns 20% and gets a very bad reaction from the hotel which causes customers to be even more disappointed and make complaints and make posts on social media about the disappointment and losses they experience [7]. As a result of this case, there has been a decrease in the number of online travel agency users due to poor complaint handling management of negative emotions felt by customers. Currently, there is still little research that discusses how these consumer negative emotions can make repeat purchases, namely by carrying out service recovery satisfaction so that complaints and negative emotions can turn into satisfaction. This research aims to achieve two primary objectives: (i) to examine the antecedent factors affecting E-trust in Mcommerce and their impact on repurchase intentions within the West Sumatra region; and (ii) to investigate the mediating function of Relationship Quality in linking Repurchase Intention with EService Quality, Complaint Handling, and Consumers' Negative Emotions through E-Trust. The study is anticipated to make valuable theoretical contributions by extending the Post-Acceptance Model (PAM) within the M-commerce context. Beyond theoretical insights, the findings are also expected to offer practical guidance for managers, industry practitioners, policymakers, and Mcommerce service providers, particularly those operating in the Indonesian market.

Method

A. Approach to Data Collection and Variable Measurement

A quantitative research methodology was applied in this study, with data collected via a Google Form questionnaire disseminated in printed form and through digital platforms, including WhatsApp and Instagram. The sampling method employed in this study is non-probability sampling using a purposive sampling technique where respondents are selected based on the criteria, namely Indonesian citizens who have made purchases through m-commerce. Of the total 400 respondents who participated, only 384 questionnaires were declared valid for analysis, Sixteen respondents were excluded for not meeting the specified criteria. - namely never having shopped through m-commerce. The number of samples used has met the minimum size requirements as recommended by the Cohran formula, Based on a A confidence level of 95% with a margin of error of 5%, the corresponding z-score is 1.96. By assuming an equal proportion of acceptance and rejection (0.5), the required sample size was determined to be 384 respondents. The data were analyzed employing the Partial Least Squares Structural Equation Modeling (PLSSEM) technique, supported by SmartPLS software, as this method is widely recognized for its effectiveness in assessing mediation effects [12]

Most of the respondents in this study were female (71.09%) and were in the age range of 17–25 years (67.02%), with more than half of them being students. Respondents were asked to choose the most frequently used m-commerce platform from several options provided, such as Shopee, Tokopedia, Lazada, Blibli. The results showed that Shopee was the most dominant platform used, followed by Tokopedia. Regarding the frequency of use, around 80% of respondents were classified as active m-commerce users. 28.81%.

The measurement in this research A 5-point Likert scale was used, with responses ranging from 1 (strongly disagree) to 5 (strongly agree) for each statement. The study was carried out in to see users in online shopping through M- Commerce. This study is to measure the intention of continuity or repeat purchases of customers through 6 variables with their dimensions and indicators. For the E-ServiceQuality variable, it is measured using 6 dimensions [5], for the ETrsut variable with 4 indicators, the complaint handling variable with 4 dimensions [12], the consumers negative emotion variable with 4 indicators[13], the consumers forgiveness variable with 4 indicators [8], and the relationship quality variable with 4 indicators[14], and the repurchase variable with 4 indicators [15].

Result and Discussion

A. Data Analysis and Empirical Evidence

As previously mentioned, this study employs the PLS-SEM technique, utilizing SmartPLS software to examine the relationships among variables. Following the a two-step process as recommended by [12], the initial phase involved testing the model using reflective measurement indicators (see Table 1). This stage aims to assess the validity and reliability of the measurement instruments. All items demonstrated factor loadings exceeding 0.7, indicating that the questionnaire items satisfy the criteria for convergent validity. The convergent validity test results confirm that all items are valid, with factor loading values above the 0.7 threshold. To evaluate internal consistency, Cronbach’s Alpha and Composite Reliability were analyzed. As shown in Table 1, these reliability coefficients exceeded 0.7 across all constructs, confirming the instrument’s reliability and consistency. Convergent validity was confirmed through Average Variance Extracted (AVE) values, all exceeding the threshold of 0.5. Discriminant validity was assessed using two approaches: the Fornell–Larcker criterion, which compares the square root of AVE, and the Heterotrait–Monotrait ratio (HTMT). Results demonstrated adequate discriminant validity for all constructs, as the square root of AVE values were higher than the correlations with other constructs, and all HTMT values fell below the recommended cutoff. 0.90. Detailed results are presented in Table 2. In the second phase, following the validation of the measurement model, the analysis proceeded to evaluate the structural model the structural model. Important aspects considered in this stage include path coefficients, determination values (R²), possible multicollinearity and the predictive accuracy (Q²)[12]

The bootstrapping technique is used to estimate path coefficients at a 5% significance level. To evaluate how well The coefficient of determination (R²) serves as the primary measure to assess how well the independent variables predict the dependent variable. In this study, the E-Trust variable. shows an R² value of 0.595, while the R² value for the variable intention to repurchase is recorded at 0.543 and Relationship Quality 0.477. According to [16]A higher R² value indicates a stronger predictive capability of the model for the dependent variable.

E-Trust (R²=0.595; Q²=0.358), Relationship Quality (R²= 0.477; Q²=0.271 ), Repurchase Intention (R²= 0.543; Q²=0.277 )

The higher the R² value, A higher influence of the independent variable on the dependent variable indicates a more robust explanatory capability of the model. This study found that the independent variable had a greater predictive impact on E-Trust compared to Repurchase Intention and Relationship Quality. It is known that the independent variable is only able to explain 47.7% of the variability of Relationship Quality (R2 ⁼ 0.477) . To evaluate the predictive relevance, a blindfolding analysis was conducted to obtain the Q² value. The results showed that E-Trust (Q² = 0.358), Repurchase Intention (Q² = 0.277), and Relationship Quality (Q² = 0.271) had positive Q² values, indicating that exogenous constructs such as perceptions of E-Service Quality, Complaint Handling, Consumers Negative Emotion, Consumer Forgiveness have predictive relevance to endogenous constructs. Next, the path coefficients are displayed in Tables 3 and 4, where approximately 100% of the hypotheses are proven to be statistically significant with p values < 0.05 and t > 1.96.

B. Empirical Discussion

1. Antecedent E - Trust

Based on Hypothesis H1, where good service perceived by customers influences trust in the company, the path coefficient value shows that E-Service Quality affects E-Trust, with a path value of (β = 0.541, p-value = 0.000), indicating a positive influence on E-Trust. This finding is consistent with the study conducted by [5], which stated that good service enhances customer trust in the company, in this case, M-Commerce platforms. Several dimensions that contribute to building customer trust include Responsiveness, Privacy/Security, Assurance, Reliability, and Empathy. One of the main concerns for customers is the guarantee when making purchases through M-Commerce. Therefore, M-Commerce companies must be able to provide adequate guarantees so that customers feel secure and can develop a high level of trust in the platform. It is expected that by offering satisfactory guarantees, customers will place greater trust in M-Commerce services.

Furthermore, Hypothesis H5 (β = 0.301, p-value = 0.000) indicates that Complaint Handling has a significant positive effect on E-Trust. This is in line with research conducted by [9], which found that if M-Commerce companies are able to handle complaints effectively, it will have a positive impact on the company, increasing customer trust and reducing customers’ negative emotions [17].

The results of (β=0.247, p -value= .000) on repurchase indicate that customer trust has a positive value or has a positive impact on repurchase. This supports H2 where when high trust is held by customers, it will make customers tend to make repeat purchases or repurchase the same m-commerce in their next purchase [5][9].

2. Antecedents of Relationship Quality

The results for Hypothesis H3, with a coefficient of β = -0.691 and p-value = 0.000, reveal that consumers’ negative emotions significantly and adversely affect the quality of the relationship. This implies that negative feelings experienced by customers lead to a deterioration in the positive relationship between the customers and the m-commerce company [19]

3. Antecedents of Repurchase Intention

In Hypothesis H4, with a value of (β = 0.220, p-value = 0.000), it shows a positive and significant influence of consumer forgiveness on repurchase intention. This indicates that forgiveness from customers towards the m-commerce company will impact customers to make repeat purchases from the same m-commerce company [8].

Then, in Hypothesis H6, the value of (β = 0.187, p-value = 0.000) shows that complaint handling has a positive and significant effect on repurchase intention. This result aligns with the study conducted by [9], where good complaint handling encourages customers to make repeat purchases on the same m-commerce platform. There are four dimensions in complaint handling, namely Encompassing prompt responses, remedial efforts, sincere apologies, and company credibility.

Then in H7 there is (β = 0.211, p -value = .000) which shows that relationship quality has a positive and significant effect on Repurchase, because if the company can maintain good relationships or improve relationships to be better between customers and m-commerce companies, customers will tend to make repeat purchases or repurchase on the same m-commerce [17]. Then in H8 where (β = 0.055 value = .000) which shows that complaint handling has an effect on repurchase through etrust, when customers experience negative emotions then with good complaint handling which causes customers to have high trust in the company which leads to customers making repeat purchases or repurchasing back to the m-commerce company so that H8 is accepted [9]. Then in

H9 where (β = 0.097 value = .000) where we know that E-Service Quality has a positive and significant effect on repurchase through E-Trust [5]. If good and quality service will increase customer trust which leads to repeat purchases, so this H9 hypothesis is accepted. Then in H10 where (β = -0.130 value = .000) where consumers negative emotion has a significant negative impact on repurchase intention through relationship quality [18]. Bad experiences felt by customers will have an impact on the relationship between customers and the company, negative emotions will reduce customers' desire to shop at m-commerce.

4. Mediating Role of E-Trust

Based on H8: (β=0.055 value= .000) , and H9: (β=0.097 value= .000) where Complaint Handling and E-Service Quality indirectly affect repurchase intention through E-Trust. From this study we know that there is an indirect influence of the E-trust variable that affects customers who eventually make repeat purchases, the Complaint handling variable both directly and indirectly affects the repurchase variable, while the E-Service Quality variable affects the repurchase variable indirectly because it is through E-Trust. Previous studies that discuss the importance of e-trust in its role so that customers continue to make repeat purchases or repurchases.

5. Mediating Role of Relationship Quality

Based on (H10: β = 0.055 value = . 000) where consumer negative emotions indirectly affect Repurchase intention which is through Relationship Quality. Where the results of this study indicate that negative emotions reduce repurchase intentions or repurchase in m-commerce even though they have been mediated by relationship quality. This result is different from the results of the study conducted [18], where in previous studies it was found that there was a positive influence between negative consumer emotions and repurchase mediated by relationship quality, because in my study I found a negative influence even though it had been mediated by relationship quality.

Conclusion

Summary, Practical Applications, Research Limitations, and Recommendations for Future Studies

With the growing use of m-commerce, this study provides important insights for practitioners, contributes to academic knowledge, and supports existing theoretical frameworks. The research focuses on consumer behavior following m-commerce usage, particularly on

Repurchase Intention, as well as on managing customer complaints and negative emotions. ETrust and Relationship Quality serve as mediating variables between E-Service Quality, Complaint

Handling, and consumer forgiveness, all of which influence customers’ decisions to make repeat purchases. The key findings include: (i) E-Service Quality has a positive and significant impact on E-Trust and indirectly influences Repurchase Intention through E-Trust, (ii) E-Trust has a direct, positive, and significant effect on Repurchase Intention, and (iii) Consumers’ Negative Emotion which has a significant negative effect on Relationship Quality, and indirectly affects repurchase through Relationship Quality, (iv) Consumers Forgiveness which directly affects Relationship Quality, (v) Complaint Handling which affects E-trust positively and significantly, (vi) Complaint Handling which directly affects Repurchase Intention, and indirectly also affects repurchase through E-Trust, (vii) Relationship Quality which has a positive and significant relationship with repurchase intention.

Theoretical Contribution

This study enhances the theoretical development of consumer expectation models in mcommerce, especially in emerging markets such as Indonesia. By extending the Post-Adoption Model (PAM), this research enriches the existing m-commerce literature. The empirical findings support the significant relationships between E-Service Quality, E-Trust, Complaint Handling,

Consumers’ Negative Emotions, and Relationship Quality within the m-commerce environment.

Additionally, the study expands the PAM framework by integrating new constructs including

Consumers’ Negative Emotions, Consumers’ Forgiveness, Relationship Quality, Complaint Handling, and E-Service Quality. The comprehensive model provides valuable empirical insights into the determinants of repurchase intentions in m-commerce, encompassing factors that influence consumers’ intentions to repurchase in this context.

This study also seeks to investigate consumer Repurchase Intention within the framework of the Post-Adoption Model (PAM), acknowledging that cultural differences may lead to varying outcomes across contexts. The findings reveal that both E-Trust and Relationship Quality have a positive and significant impact on Repurchase Intention in the m-commerce setting. Furthermore, the occurrence of customers who do not repurchase does not necessarily indicate a lack of trust in m-commerce; rather, it highlights the importance for m-commerce providers to proactively manage complaints through timely responses, appropriate redress, and sincere apologies, and credibility, and the existence of satisfactory service by providing adequate guarantees. These findings also contribute to enhancing knowledge about how mediation functions in m-commerce, especially in explaining the effect of Complaint Handling on Repurchase Intention mediated by ETrust, then Consumers Negative Emotion mediated by Relationship Quality. In addition, functional benefits are also proven to indirectly influence Repurchase Intention through these two mediators.

Practical Applications

Within the scope of the m-commerce industry, the results of this study provide important insights for the management of managerial and marketing strategies related to E-Service Quality,

E-Trust, Complaint Handling, Consumers Forgiveness, Consumers Negative Emotion, Relationship Quality, and Repurchase Intention. Managers are advised to focus on building consumer trust, as well as improving the Relationship Quality of the m-commerce platforms they manage. This can be realized through the development of an integrated and reliable system, which is oriented towards user convenience and comfort, provides clear instructions, resolves complaints quickly, and is designed responsively according to consumer needs. M-commerce platforms must also be ready to adopt the latest technology with comprehensive functions, intuitive interfaces, a variety of product and service choices, and responsive customer support. In addition, protection of user data and privacy is a priority, so service providers need to implement a comprehensive and trusted digital security system.

In addition, in order to prevent a decline in the number of customers, effective m-commerce management needs to maintain supporting elements such as discounts and shipping cost policies. This is because consumers who were previously satisfied and had the intention to continue using m-commerce services, These findings indicate that providing high-quality E-Service is essential for customers. In the context of m-commerce, customer retention plays a vital role in ensuring the platform's sustainability and growth. Consistent with , customers who experience high satisfaction and maintain their intention to use m-commerce applications are more likely to remain loyal to the platform. Losing customers to competitors can result in significant losses for mcommerce businesses. Therefore, it is critical for service providers to guarantee the reliability of features that encourage repurchase. Strategies such as enhancing the customer experience through exclusive discounts, delivering excellent service, and effective complaint management are fundamental to expanding the user base and strengthening customer loyalty.

Scope, Limitations, and Directions for Future Research

This study advances the theoretical framework by extending the Post-Acceptance Model (PAM) and enriching the literature on E-Service Quality, E-Trust, Complaint Handling, Consumer Forgiveness, Consumers' Negative Emotions, Relationship Quality, and Repurchase Intention. Despite its valuable contributions to digital marketing research, several limitations remain. A key limitation is the study’s scope, which does not thoroughly examine the direct effect of E-Service Quality on Repurchase Intention. Future research is therefore encouraged to explore this relationship in greater detail. Additionally, investigating other potential factors influencing repurchase intention would be beneficial. Future studies should also incorporate control variables such as age, gender, and employment status as moderators to deepen the understanding of the link between E-Trust and Repurchase Intention. This approach is expected to enhance both the exploratory depth and comprehensiveness of future research.

Acknowledgements

The author extends heartfelt thanks to Universitas Negeri Padang, the institution where academic knowledge was obtained

References

1. L. C. A. Yee, “Understanding Mobile Commerce Continuance Intentions: An Empirical Analysis of Chinese Consumers,” Journal of Computer Information Systems, vol. 53, no. 4, pp. 22–30, 2013, doi: 10.1080/08874417.2013.11645647.
2. P. Susanto, M. E. Hoque, V. Nisaa, M. A. Islam, and Y. Kamarulzaman, “Predicting M-Commerce Continuance Intention and Price Sensitivity in Indonesia by Integrating of Expectation-Confirmation and Post-Acceptance Model,” SAGE Open, vol. 13, no. 3, pp. 1–22, 2023, doi: 10.1177/21582440231188019.
3. S. Kemp, “Digital 2025: Global Overview Report,” 2025. [Online]. Available: https://datareportal.com/reports/digital-2025-global-overview-report
4. G. M. Meghisan-Toma, S. Puiu, N. M. Florea, F. Meghisan, and D. Doran, “Generation Z’ Young Adults and M-Commerce Use in Romania,” Journal of Theoretical and Applied Electronic Commerce Research, vol. 16, no. 5, pp. 1458–1471, 2021, doi: 10.3390/jtaer16050082.
5. P. Rita, T. Oliveira, and A. Farisa, “The Impact of E-Service Quality and Customer Satisfaction on Customer Behavior in Online Shopping,” Heliyon, vol. 5, no. 10, p. e02690, 2019, doi: 10.1016/j.heliyon.2019.e02690.
6. J. Wei, “The Impacts of Perceived Risk and Negative Emotions on the Service Recovery Effect for Online Travel Agencies: The Moderating Role of Corporate Reputation,” Frontiers in Psychology, vol. 12, May 2021, doi: 10.3389/fpsyg.2021.685351.
7. J. Wei, Z. Hou, and X. A. Zhou, “Research on the Impact of Consumer Forgiveness on Consumer Continuous Trust,” Journal of Business and Management, vol. 34, 2022.
8. A. Ibrahim, Metode Penelitian Ekonomi dan Bisnis Islam, Aceh: Ar-Raniry Press, 2021.
9. J. F. Hair, J. J. Risher, M. Sarstedt, and C. M. Ringle, “The Results of PLS-SEM Article Information,” European Business Review, vol. 31, no. 1, pp. 2–24, 2019.
10. R. Vázquez-Casielles and V. Iglesias, “Explaining Customer Satisfaction with Complaint Handling,” International Journal of Bank Marketing, vol. 28, pp. 1–14, 2009, doi: 10.1108/02652321011018305.
11. D. Istanbulluoglu and E. Sakman, “Successful Complaint Handling on Social Media Predicts Increased Repurchase Intention: The Roles of Trust in Company and Propensity to Trust,” European Management Journal, vol. 42, no. 1, pp. 11–22, 2024, doi: 10.1016/j.emj.2022.06.004.
12. P. Kaur, S. Talwar, N. Islam, J. Salo, and A. Dhir, “The Effect of the Valence of Forgiveness to Service Recovery Strategies and Service Outcomes in Food Delivery Apps,” Journal of Business Research, vol. 147, pp. 142–157, 2022, doi: 10.1016/j.jbusres.2022.04.020.
13. M. Rizal, A. F. Mustapita, and A. F. K. Sari, “Pelatihan untuk Pengajuan Pembiayaan Mudharabah Perbankan Syariah sebagai Peningkatan Kinerja UMKM,” Jurnal Inovasi Hasil Pengabdian, vol. 3, no. 1, 2020. [Online]. Available: https://riset.unisma.ac.id/index.php/jipemas/article/view/2569
14. S. Aren, M. Güzel, E. Kabadayı, and L. Alpkan, “Factors Affecting Repurchase Intention to Shop at the Same Website,” Procedia - Social and Behavioral Sciences, vol. 99, pp. 536–544, 2013, doi: 10.1016/j.sbspro.2013.10.523.
15. C. Wei, M. W. Liu, and H. T. Keh, “The Road to Consumer Forgiveness Is Paved with Money or Apology? The Roles of Empathy and Power in Service Recovery,” Journal of Business Research, vol. 118, pp. 321–334, 2020, doi: 10.1016/j.jbusres.2020.06.061.
16. J. Wei et al., “The Impact of Negative Emotions and Relationship Quality on Consumers’ Repurchase Intention: An Empirical Study Based on Service Recovery in China’s Online Travel Agencies,” Heliyon, vol. 9, no. 1, 2023, doi: 10.1016/j.heliyon.2023.e12919.
17. P. Hafidz and D. T. Sitorus, “Analysis of Factors That Can Increase Repurchase Intention, WOM, and Site Revisit in E-Commerce Applications,” Journal of Business and Management Review, vol. 12, no. 1, pp. 840–849, 2023.
18. D. Sirdeshmukh, N. B. Ahmad, M. S. Khan, and N. J. Ashill, “Drivers of User Loyalty Intention and Commitment to a Search Engine: An Exploratory Study,” Journal of Retailing and Consumer Services, vol. 44, pp. 71–81, 2018, doi: 10.1016/j.jretconser.2018.06.002.