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Download Between 20 and 90 charactersBetween 20 and 90 characters and more Exercises Business Informatics in PDF only on Docsity! Building A Theoretical Research Model for Trust Development: The Case of Mobile Financial Services in Myanmar Phyo Min Tun Assumption University, Thailand Abstract Research Aims - This research study focuses on the factors affecting customer trust in mobile fi- nancial services (MFS) in Myanmar by developing a research model that incorporates six different factors: perceived usefulness, perceived ease of use, social pressure, enabling conditions, service quality, and satisfaction. Design/Methodology/Approach - Exploratory Factor Analysis (EFA) and Confirmatory Factor Analysis (CFA) were employed to analyse the data. Subsequently, Structural Equation Modeling (SEM) was utilised to examine hypotheses. An analysis was performed on the survey data collected from 250 mobile phone users who are likely to use or currently using MFS in Myanmar. Research Findings - The results indicate that trust in MFS is significantly influenced by enabling conditions, service quality and satisfaction. The study also found that perceived usefulness, per- ceived ease of use and social pressure have statistically insignificant effects on trust-building in the MFS context. Theoretical Contribution/Originality - A finalised trust-development theoretical research model was formulated and proposed for utilisation in the investigation of customers’ trust in future research within a similar context. Managerial Implication in the South East Asian Context - The findings of this study are benefi- cial and valuable for Mobile Financial Services Providers (MFSP) in the ASEAN countries, ena- bling them to create suitable marketing strategies, business approaches and service infrastructures regarding their customers, thereby developing customer trust. Research Limitations and Implications - The conclusion is limited to the mobile financial services sector in Myanmar, and the opinions of non-adopters and rejectors are excluded. Keywords - Trust, Mobile Financial Services, Financial Technologies, Myanmar INTRODUCTION Mobile technologies have been increasingly used to apply additional value to exist- ing services because of the rapid development of mobile devices and apps. Mobile financial services (MFS) have become a popular trend among the digital industries because innovative customer services for mobile phone users can be evolved and improved rapidly. MFSPs are service providers in the financial institution that allow users to carry out various financial transactions remotely using a mobile app and smartphone device (Yen & Wu, 2016). Hence, MFS can be defined as the capability to conduct financial transactions, including fund transfers, balance management, bill payments and other mobile technologies-based financial services, via mobile devices. Although users have widely adopted mobile devices and their related tech- nologies, the adoption of MFS is relatively low (Rodrigo & Yujong, 2016). Innova- tions have become essential for businesses to remain competitive due to unpredict- able conditions and the complexity of the economic climate (Abdinoor & Mbamba, The South East Asian Journal of Management Vol. 14 No. 2, 2020 pp. 175-195*The corresponding author can be contacted at: phyomintun.sg@gmail.com Building A Theoretical Research Model for Trust Development 175 Revised 22 November 2020 Accepted 6 December 2020 SEAM 14, 2 176 2017). Users are facing more dynamic, safety-concerned, and rapid evolutions in the financial landscape because mobile technologies enable MFS to provide unique value and a variety of services to users. Thus, businesses have developed user- oriented innovation products and services, some of which failed to be accepted by users (Kleijnen et al., 2009). MFS have become important components in banking and non-banking financial institutions in Myanmar ever since the Central Bank of Myanmar (CBM) issued regulations on MFS in 2016. Since then, five mobile financial service providers remain in operation. Moreover, 27 private banks are operating according to the data provided by the CBM. The CBM also permitted 29 non-bank financial institutions to provide financial services to unbanked customers. Although the financial indus- try has been expanding its services, only 26% of the population has bank accounts, and 0.7% has a mobile money account in Myanmar (Kemp, 2020). Moreover, Ward (2018) reported that even though 89% of the population is using mobile phones, there is a lack of mobile payment adoption in Myanmar. The low rate of financial services adoption may be the cause of terrible experience during the financial crisis that occurred in 2003 (Turnell, 2003). As a consequence, customers might have less trust in financial services, and trust is an undoubtedly essential element in the financial institution of Myanmar (Tun, 2020). RESEARCH OBJECTIVE Many research studies have been conducted investigating the factors that influence users’ adoption of MFS. However, only a few researchers have conducted studies exploring the associated factors, mainly focusing on customer trust in MFS. Also, none has emphasised how the trio of aspects, quality, belief, and social, from wide- ly-used theoretical models associated with MFS, affect customers’ trust. Therefore, the main objective of this research study is to develop a comprehensive research model to study the factors that influence customers’ trust in MFS and report theo- retical and practical implications based on the findings of the factors associated with trust in MFS. Moreover, this research study attempts to fill the research gaps of the previous studies in the MFS context; therefore, the following research questions need to be addressed: RQ1: What are the possible factors that influence customer trust in MFS? RQ2: What are the relationships among these factors? RQ3: Which factors have significant effects on customer trust in MFS? RESEARCH GAPS IN PREVIOUS STUDIES Frist, Lee and Chung (2009) developed a research model by modifying the Infor- mation System Success (ISS) model of DeLone and McLean (2003). The model consists of five factors: system quality, information quality, interface design quality, trust, and satisfaction with mobile banking. The proposed model aimed to investi- gate the effects of interface design quality, system quality, and information quality on trust and satisfaction. The author considered interface design quality, system quality, and information quality as antecedent factors of the customers’ trust and ditions, which is one of the major factors in the unified theory of acceptance and use of technology (UTAUT). Enabling conditions refers to the extent to which a user thinks that existing conditions, environments and infrastructures will aid and enable him/her to access desired services or use intended technologies (Venkatesh et al., 2003). Users may change their attitudes accordingly in order to be consist- ent with the enabling conditions (Chan et al., 2010). Additionally, Venkatesh et al. (2012) considered enabling conditions as the resources that aid users in system use, such as training support and online tutorials and inadequate enabling conditions as those that lead to negative attitudes. Venkatesh et al. (2012) further stated that the supporting facilities accessible to each customer might differ depending on mobile devices, technology platforms, service providers and so on. Service Quality Kheiry and Alirezapou (2012) manifestly stated that service quality is the emotional difference between customer expectation and their awareness of service quality. According to their research result, increments in service quality awareness of cus- tomers positively influence perspectives of relationship quality such as trust and satisfaction in a mobile channel. Service quality was suggested to be measured us- ing five criteria: assurance, reliability, responsiveness, empathy and technical com- petence of the service personnel (Parasuraman et al., 1988; Petter et al., 2008). The study of Johannes et al. (2018) confirmed that supportive, high-quality customer service is an important circumstance that leads to customer satisfaction and trust in mobile banking. Their research results were also consistent with the study of Brown and Jayakody (2008) in the B2C e-commerce context. Furthermore, Routray et al. (2019) suggested service quality as a considerable component of MFS. Satisfaction Oliver (1981) formulated the expectancy-disconfirmation theory to describe cus- tomer satisfaction, which is defined as an agreeable level of caring for utilisation. The customers’ judgment of their satisfaction is a comparison between their ex- pectations and actual outcomes (Lin et al., 2020). Satisfaction is the evaluation of the current experience of interacting with a service provider and is employed by customers to determine their future activities (Kheiry & Alirezapou, 2012). On the other hand, Anderson and Sullivan (1993) argued that satisfaction overly depends on performance in the marketing aspect, but experience alone in a product or ser- vice does not reflect overall satisfaction. Also, satisfaction plays a critical role in the context of financial services and has been discussed widely in the relevant lit- erature (Mokhtar et al., 2018). Bahaddad (2017) explained that satisfaction could be focused on different aspects, such as information systems, smartphone applica- tions, and services. In this study, satisfaction is focused on the services received from MFS. Trust Ganesan (1994) identified that trust has two dimensions: credibility, the belief that stakeholders have adequate capability and reliability, and benevolence, the belief Building A Theoretical Research Model for Trust Development 179 SEAM 14, 2 180 that stakeholders have a willingness to provide benefits in new conditions. In con- trast, Benamati et al. (2010) argued that trust includes three aspects: benevolence, competence, and integrity. Benevolence means service providers confer priority to the interests of users, competence refers to the essential abilities and knowledge of service providers, and integrity is the assurance in service providers not deceiving users. Salam et al. (2003) explained that a trustee (service provider) develops trust that it has essential features necessary to protect the trustor (customer) in order to create positive opinions by the trustor. Moreover, an aura trust involves a critical role in the MFS context because it is directly relevant to monetary matters via on- line transactions (McKnight et al., 2002). Therefore, due to its significant role, a study on trust is mandatory in order to emphasise it in the MFS context. HYPOTHESES DEVELOPMENT Perceived usefulness was identified as the determinant construct of customer satis- faction in the financial service context. The nature of financial transactions conduct- ed through an online channel is different from those conducted through a traditional channel (Lin et al., 2020). Customers will have higher satisfaction with financial service if they have higher perceived usefulness. Likewise, other several studies also verified that perceived usefulness is antecedent of customer satisfaction with MFS (Kahandawa & Wijayanayake, 2014; Kim & Lee, 2013; Reji & Ravindran, 2012). Therefore, the following hypothesis can be proposed: H1: Perceived usefulness has a significant positive effect on satisfaction. A deeper understanding of the usefulness of prior experience in MFS may lead them to trust in MFS (Zhu et al., 2017). Several research studies confirmed that customers’ perceived usefulness is one of the critical predictors of customer trust in the mobile banking context (Ramos et al., 2018; Lokman et al., 2017; Maroofi et al., 2013) and mobile wallet (Chawla & Joshi, 2019). Li and Yeh (2010) also reported similar results that customers’ perceived usefulness has a positive effect on their trust in mobile commerce. Therefore, the following hypothesis is formulated: H2: Perceived usefulness has a significant positive effect on trust. In prior studies in mobile banking, the context has been proven that perceived ease of use is an independent factor that affects customer satisfaction (Jannat & Ahmed, 2015; Reji & Ravindran, 2012). Services on the mobile platform can improve their customer satisfaction if using their services are designed to be easy to use (Kim & Lee, 2013). (Lin et al., 2020) also stated that customers would be more satisfied with the services provided by financial businesses in case of easier to use. Thus, the following hypothesis is tested: H3: Perceived ease of use has a significant positive effect on satisfaction. Easy to use and clarity of processes in payment methods help in building trust (Maqableh et al., 2015). Ramos et al. (2018) also stated that an easily accessible MFS would reduce the effort of the customer, and it would help them to concentrate on their activities which are to conduct financial transactions. Customers thereby will have higher trust in MFS if they have higher perceived ease of use. Perceived ease of use has been hypothesised to have a positive effect on trust in prior studies, and it was found as a critical predictor of customer trust (Chawla & Joshi, 2019; Maroofi et al., 2013; Li & Yeh, 2010). Thus: H4: Perceived ease of use has a significant positive effect on trust. If customers find out the opinions of their relatives and friends about the product or service, it will directly affect their satisfaction level (Mokhtar et al., 2018). Moreo- ver, social pressure has a significant effect on the satisfaction of payment systems users has been confirmed in the study of Qais and Emad (2017). Hsiao et al. (2016) also reported that social influence has a strong impact on user satisfaction of mobile technology. As a result, the following hypothesis is considered in the current study. H5: Social Pressure has a significant positive effect on satisfaction. The study of Malaquias and Hwang (2016) asserted that social pressure is criti- cal to developing trust in MFS because users think MFS are trustworthy when the individuals who are important to them also use it. Several prior studies have been proven that social pressure has a significant positive effect on trust (Sonia, 2018). Therefore, this study argues that when influencers use MFS, they might enhance trust within their social circles. This leads to the following hypothesis: H6: Social Pressure has a significant positive effect on trust. The study of Rodrigues et al. (2016) has been proven that enabling conditions have a significant effect on the overall satisfaction of users. A solid infrastructure ena- bles users to feel that they have resourceful conditions when it comes to using technological services. The research results also demonstrated that enabling condi- tions considerably improve the satisfaction level of customers in an online context (Almarri et al., 2019). Further, Chan et al. (2010) asserted that enabling conditions have a positive influence on user satisfaction according to their research result, which leads to the following hypothesis: H7: Enabling Conditions have a significant positive effect on satisfaction. Lu et al. (2005) claimed that enabling conditions enhance the trustworthiness of the mobile environment. Certain enabling conditions such as a supportive technical en- vironment, effective training programs, and clarity of procedures are required regu- larly to develop trust. In the context of this research, the trustworthiness of MFS can only be perceived when customers apprehend that the existing environment and infrastructure are supportive of them. Some prior studies have been proven enabling conditions have a positive impact on the trust of online businesses (Singh et al., 2017; Gu et al., 2016). These issues lead to the following hypothesis: H8: Enabling Conditions have a significant positive effect on trust. Service quality can enhance the satisfaction level of customers and has been con- firmed as an essential antecedent of satisfaction in the mobile service industry (Kheiry & Alirezapou, 2012). Service quality has been identified as an important role in ensuring customer satisfaction. Moreover, several previous studies also postulated that customer satisfaction is affected by the quality of service provided Building A Theoretical Research Model for Trust Development 181 SEAM 14, 2 184 Construct Validity An EFA was conducted to confirm the correspondence indicators for individual constructs in the proposed research model by using a Principal Components Analy- sis (PCA) method with a Varimax rotation for all the indicators in SPSS software. The indicator with a loading coefficient of at least 0.5 was determined as its respec- tive constructs (Kline, 2011). The factor analysis confirmed seven factors affiliated from 20 indicators (Table 3). Therefore, all these indicators were considered to be suitable for further examination with CFA. Correlations of Factors The matrices of Pearson correlation coefficients were examined to analyse the rela- tionship between the constructs. The results confirmed that all the factors from the research model correlate with each other positively at a 0.01 level, with each Pear- son correlation coefficient ranging from minimum 0.374 to a maximum of 0.691 (Table 4). Factor Loading and Construct Reliability Hair et al. (2010) recommended that if the factor loading is higher than 0.50, the indicators can be considered as very significant. All indicators of standardised re- Table 3 Analysis Result of Construct Validity Indicators Factors PU SQ TR ST EC PE SP PU1 0.803 0.027 0.088 0.138 0.279 0.155 0.155 PU2 0.777 0.125 0.141 0.236 0.267 0.248 0.119 PU3 0.761 0.111 0.128 0.108 0.157 0.376 0.138 SQ1 0.046 0.797 0.203 0.080 0.203 0.177 0.138 SQ2 0.101 0.748 0.197 0.373 0.164 0.148 0.229 SQ3 0.108 0.718 0.270 0.346 0.048 0.143 0.146 TR3 0.096 0.123 0.809 0.175 0.146 0.088 0.103 TR2 0.104 0.296 0.740 0.283 0.166 0.130 0.196 TR1 0.131 0.296 0.690 0.195 0.159 0.202 0.169 ST2 0.080 0.284 0.235 0.740 0.246 0.264 0.130 ST1 0.246 0.256 0.281 0.684 0.234 0.121 0.154 ST3 0.215 0.226 0.236 0.677 0.186 0.276 0.235 EC2 0.245 0.173 0.087 0.142 0.819 0.166 -0.023 EC1 0.248 0.093 0.181 0.184 0.690 0.172 0.267 EC3 0.138 0.140 0.237 0.247 0.689 0.324 0.193 PE2 0.156 0.123 0.156 0.214 0.169 0.849 0.148 PE1 0.297 0.168 0.068 0.120 0.229 0.815 0.123 SP3 -0.033 0.098 0.073 0.075 0.067 0.082 0.865 SP2 0.248 0.160 0.197 0.142 0.152 0.219 0.737 SP1 0.385 0.230 0.166 0.260 0.115 0.105 0.569 Table 4 Analysis Result of Factors Correlations Factors PU SQ ST EC TR SP PE Perceived Usefulness 1 Service Quality 0.374** 1 Satisfaction 0.547** 0.691** 1 Enabling Conditions 0.610** 0.489** 0.628** 1 Trust 0.416** 0.633** 0.668** 0.527** 1 Social Pressure 0.477** 0.503** 0.540** 0.469** 0.490** 1 Perceived Ease of Use 0.590** 0.460** 0.562** 0.576** 0.434** 0.443** 1 Note: **. Correlation is significant at the 0.01 level. gression weight were greater than 0.50 and ranged from a minimum of 0.57 to a maximum of 0.91. Besides, construct reliability was evaluated using Cronbach’s al- pha coefficient, and all the values are above the acceptable value of 0.7. Therefore, all the factors and indicators are highly reliable for investigating customer trust in MFS (Table 5). Average Variance Extracted, Composite Reliability and Discriminant Validity Convergent validity and discriminant validity were examined by analysing com- posite reliability (CR) and average variance extracted (AVE). All the values of CR and AVE exceed more than acceptable values (Hair et al., 2010), CR ranging from 0.77 to 0.89, and AVE ranging from 0.54 to 0.76. Moreover, all the values of the square root of AVE are larger than the correlations coefficients between factors (Ta- ble 6). Thus, the analysis results can be asserted that discriminant validity meets a satisfactory level (Fornell & Larcker, 1981). Fit Indices of Research Model For a goodness-of-fit model, Kline (2011) proposed that GFI, CFI, and NFI must exceed 0.90 for acceptable model fitness while the recommended fit values for AGFI should be more than 0.80. Further, if the value of x2/df is less than 3 and RMSEA is less than 0.08, the model is considered to be a good fit. In this study, the results indicated that x2/df = 1.50, GFI = 0.916, AGFI = 0.882, CFI = 0.975, NFI = Building A Theoretical Research Model for Trust Development 185 Factors Indicators Std. Regression Weight Cronbach’s Alpha Table 5 Analysis Result of Factor Loading and Construct Reliability Perceived Usefulness PU1 0.81 0.88PU2 0.91 PU3 0.83 Service Quality SQ1 0.72 0.85SQ2 0.92 SQ3 0.82 Satisfaction ST1 0.81 0.87ST2 0.85 ST3 0.83 Enabling Conditions EC1 0.75 0.82EC2 0.74 EC3 0.84 Trust TR1 0.80 0.83TR2 0.90 TR3 0.68 Social Pressure SP1 0.57 0.76SP2 0.83 SP3 0.77 Perceived Ease of Use PE1 0.90 0.86PE2 0.85 Overall (N of Items = 20) 0.94 Factors CR AVE PU SQ ST EC TR SP PE Table 6 Analysis Results of CR, AVE and Discriminant Validity PU 0.89 0.72 0.85 SQ 0.86 0.68 0.44 0.82 ST 0.87 0.69 0.63 0.80 0.83 EC 0.82 0.61 0.71 0.58 0.75 0.78 TR 0.84 0.64 0.48 0.73 0.77 0.63 0.80 SP 0.77 0.54 0.61 0.62 0.67 0.62 0.61 0.73 PE 0.86 0.76 0.68 0.52 0.64 0.69 0.49 0.56 0.87 SEAM 14, 2 186 0.928, and RMSEA = 0.046 (Table 7). All the values of model fit indices meet the acceptable values, and it can be assumed the research model is a very good fit to collected data. Analysis Results of Hypothesis The hypotheses were validated as proposed in Figure 1. The results of hypothesis testing are presented in Table 7. Service quality (β=0.301, p<0.01) and satisfac- tion (β=0.422, p<0.01) with regard to MFS, all evidenced a positive relationship with trust. Therefore, H10 and H11 were accepted. Enabling conditions (β=0.285, p<0.01) and service quality (β=0.478, p<0.001) positively affected satisfaction. Therefore, H7 and H9 were endorsed as well. The results, however, indicated that H1, H3, and H5 were rejected. Therefore, perceived usefulness, perceived ease of use, and social pressure did not significantly affect the satisfaction of users. Also, H2, H4, H6, and H8 were not accepted, which means that perceived usefulness, perceived ease of use, social pressure, and enabling conditions to have statistically insignificant effects on trust in MFS. All the results of hypothesis testing are listed in Table 8. FINAL THEORETICAL RESEARCH MODEL DEVELOPMENT Model Modification The final theoretical research model development procedure was conducted ac- cording to the recommendation of Kline (2011). In the analysis results of each hy- pothesis in the research model, it is seen that seven direct effects are statistically insignificant. Therefore, these effects are eliminated from the research model. In addition, from the analyses of correlations among the factors (Table 4), there is an additionally plausible direct effect between SQ and EC. Each of these five direct effects was made optional in an analysis using the Specification Search Facility feature in the AMOS Software. The model in the hierarchy results with the smallest value for normed Chi-square was chosen as the final model (Figure 2). Table 7 Model Fit Indices of Research Model x2/df GFI AGFI CFI NFI RMSEA Acceptable Value < 3.0 > 0.90 > 0.80 > 0.90 > 0.90 < 0.080 Final Model 1.50 0.916 0.882 0.975 0.928 0.046 Table 8 Analysis Result of Hypothesis Hypothesis Causal Effect Path Coefficient Result H1 PU → ST 0.103 NS (0.125) Rejected H2 PU → TR -0.041 NS (-0.046) Rejected H3 PE → ST 0.046 NS (0.052) Rejected H4 PE → TR -0.078 NS (-0.081) Rejected H5 SP → ST 0.060 NS (0.076) Rejected H6 SP → TR 0.110 NS (0.131) Rejected H7 EC → ST 0.285 ** (0.285) Accepted H8 EC → TR 0.187 NS (0.174) Rejected H9 SQ → ST 0.478 *** (0.506) Accepted H10 SQ → TR 0.301 ** (0.296) Accepted H11 ST → TR 0.422 ** (0.392) Accepted Note: NS means Not Significant, *** means p < 0.001, ** means p < 0.01 easiness of the system does not improve customers’ trust. MFSP should also note that customers do not evaluate the reliability and confidence of MFS based on opin- ions and recommendations of their friends, family members and colleagues. Furthermore, suggested managerial practices are applicable not only in Myanmar, one of the least developed countries (LDC) according to the World Bank, but also other ASEAN countries that have a similar economic situation, such as Laos and Cambodia. Despite the managerial implications, which notably intend to deliver managerial solutions for LDC, other ASEAN countries that are not listed as LDC but which have a similar business culture and customer behaviours are also fit to adopt these practices. Particularly, FinTech businesses which plan to launch MFS within the ASEAN region are urged to utilise the presented practices to build sus- tainable customers’ trust in their services. CONCLUSION In summary, this study initially began with the premise that the successful practice of building trust depends on the extent of beliefs, quality and social perspectives. This research fills the gaps in previous studies and practices in the mobile technol- ogy industry, in general, and mobile financial services, specifically. The findings of this study provide insights for MFSP to realise the reasons why certain customers have less trust in MFS. From this study, MFSP can identify why customers hesitate to trust their services and/or which factors cause customers to perceive MFS as trustworthy. It is essential that MFSP realise what is lacking in the implementation of current services and understand the components affecting or influencing custom- er trust in MFS. The infrastructure itself is not enough for the successful building of customer trust; instead, high-quality service and acceptable satisfaction levels must be attained in order to ensure customers’ confidence in MFS. LIMITATIONS AND DIRECTION FOR FUTURE RESEARCH Only studying the perspective of customers of MFS can be viewed as one of the limitations of this study. The perceptions of non-adopters and rejectors are ne- glected, although understanding what motivates them to trust in MFS could prove equally important (Laukkanen et al., 2008). The results of this research may also be unreflective of other contexts because this study mainly focuses on customer trust in MFS. The data sample size can be considered another limitation; a larger sample size is required to improve the quality of data in order to avoid result bias in future studies. Another limitation of this study is the emergence of the final research model from this study, which attempted to fill the research gaps of previous studies mainly conducted in Asian countries. Additionally, this research study was con- ducted in Myanmar, an ASEAN country; therefore, oriental perspectives may have influenced the research model. For instance, Damabi et al. (2018) conducted a study in Iran, a Middle East country, using the research model of Lee and Chung (2009) but obtained different results. Hence, researchers who intend to conduct studies in the Western world or different continents using the final model of this study may need to modify or add additional factors. Despite TAM being highly capable of predicting the adoption behaviour of users, in this study, other major factors (PU Building A Theoretical Research Model for Trust Development 189 SEAM 14, 2 190 and PE) do not have significant effects on improving satisfaction and building trust. The results also show that SI is insignificant and has a minimal effect on trust and satisfaction. In future studies, PU, EU and SI can be considered to exclude if the study is conducted to investigate the context relevance of trust. REFERENCES Abdinoor, A., & Mbamba, U. O. (2017). Factors influencing consumers’ adoption of mobile financial services in Tanzania. Cogent Business and Management, 4(1), 1-19. Almarashdeh, I. (2018). 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APPENDIX Building A Theoretical Research Model for Trust Development 195 Indicators Statements Mean Std. Deviation Appendix A Questionnaire and descriptive statistic PU1 MFS is useful in my daily life. 3.75 1.020 PU2 MFS is very helpful for my tasks. 3.98 0.837 PU3 MFS make my works become easier. 3.93 0.891 SQ1 The customer service provides immediate attention when I experience problems with MFS. 3.29 1.000 SQ2 The customer service provides services related to MFS at the promised time. 3.24 0.909 SQ3 The customer service has sufficient knowledge to answer my questions regarding MFS. 3.43 0.851 ST1 MFS has met my expectations. 3.57 0.846 ST2 I am satisfied with the service I have received from MFS. 3.67 0.848 ST3 Overall, I am satisfied with MFS. 3.75 0.816 EC1 I have the resources necessary to use MFS. 3.77 0.906 EC2 I have the knowledge necessary to use MFS. 4.00 0.837 EC3 MFS is compatible with the technologies I currently use. 3.86 0.840 TR1 MFS has adequate features to protect my security. 3.40 0.920 TR2 MFS keeps my financial information secure and personal data safe. 3.43 0.905 TR3 Overall, MFS is trustworthy. 3.40 0.853 SP1 People who are important to me think that I should use MFS. 3.47 1.126 SP2 People who are important to me would recommend to use MFS. 3.28 1.168 SP3 People who are important to me influence my decision to use MFS. 2.81 1.311 PE1 MFS is easy to use. 4.00 0.852 PE2 MFS use is clear and understandable. 3.82 0.912