Factors Influencing Continuance Intentions of Unified Payment Interface (UPI) users

Factors Influencing Continuance Intentions of Unified Payment Interface (UPI) users | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Factors Influencing Continuance Intentions of Unified Payment Interface (UPI) users sandeep kaur This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-1966920/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract The with development of smartphones, technology has played a greater role in recent years, drastically altering how we trade in daily life. Now that all payments and transactions take place online, life has gotten more simpler. This accelerated the development of the UPI platform. The goal of the current study is to gauge user satisfaction and continuance intentions for UPI. This study develops a research model using personal innovativeness and pace of innovation to predict the continuance intention toward UPI based on the Unified theory of acceptance and use of technology (UTAUT). We conduct an online survey to collect data from participants who have used UPI. The research model is tested in this study utilising a partial least squares structural equation model with 651 valid replies. According to our findings, satisfaction with UPI serves as a mediator between antecedents and continuing intentions by positively affecting them. This paper explores theoretical implications for the UTAUT and offers an insight of how to manage UPI in India on a practical level. Digital payments UPI Satisfaction UTAUT personal innovativeness Continuance Intention Figures Figure 1 Figure 2 1. Introduction Unified Payments Interface (UPI) system gives power to multiple bank accounts into a single mobile application with several banking features on a single platform. It is peer to peer collect request which can be done as per requirement and convenience. UPI is an instant real time payment system launched by National payments corporation of India (NPCI), regulated by Reserve Bank of India. Using a UPI enabled app the users can perform financial transactions instantly between two bank accounts on a mobile platform. The user should frame-up a Personal Identification Number (MPIN) for UPI ID for a bank account while setting up the UPI enabled App. Additional banks details like bank account number, branch IFSC code are not required. As on March2019 there were 142 banks(at present 189) live on UPI with a monthly volume of 799.54 million transactions and a value of ₹1.334 trillion (US$19 billion). UPI witnessed 180 crore (207 crore in October) transactions worth 3.29 lakh crore in September 2020 (3.86 lakh crore in October 2020).The pilot launch was done by Dr Raghuram G Rajan, former governor of RBI Mumbai on 11 th April 2016; from 25 th August 2016 Banks have started to upload their UPI apps on Google Play store. UPI facilitates the round-the-clock financial transaction services. The UPI needs only to authenticate the identity of the user like debit card does using the phone as a tool instead of a separate card. The banks, consumers, merchants are the users of the UPI. The UPI platform helps the banks to remove infrastructural cost, and providing safe and secure transactions to its customers. The unique transaction number facilitates the banks to check where fraudulent transactions are located. Making transactions with smartphones are effortless, reduces the time and cost, UPI service 24hours available on a single application. The merchants used UPI to receive payments from the customers and the risk of storing their financial information is very less. The Ecosystem of UPI includes three players- Payment service providers, Banks, NPCI. Payment service providers act as a link between the payer and payee where banks maintain accounts for the payer and payee. NPCI as a central body control their virtual payment address. (Thomas and Chatterjee, 2017).It enables in reducing the cash-based economy and promotes digital economy in India. Benefits of the UPI: It is very simple, safe and convenient payment method for both- Sender and Receiver. It is instant and secures validation, can be done anywhere. Customers can make payments of school fees, utility bills via Smartphones and internet. There is no need to use multistep processes like Net-banking, also eliminates the use of debit cards, credit cards. It helps in the growth of e-commerce and other trading activities. Is provides financial inclusion in the economy, reducing cash -based activities, promotes digital economy in India. The aim of the study is to explore the User satisfaction and continuance usage intention towards UPI through proposed model. 2. Conceptual Model Development Various theories and models were deployed in previous studies of user satisfaction and continuance usage intentions in different areas. Expectations Confirmation model deployed to find the satisfaction and continue intentions among Chinese consumers (Chong, 2013); User satisfaction regarding smartphones studied with the help of Bhattacherjee’s post acceptance model (Liang et al, 2018); continued intention in purchase of mobile phones used flow theory (Gao et al, 2015); Contingency and task technology theories employed to find the variables of consumer satisfaction in mobile tourism shopping (Kim et al.,2 015). Modified TAM extended with additional variable- perceived enjoyment to explore the user satisfaction and continuance intention to use smartphone for shopping by (Agrebi and jallais, 2015); TAM was also used to find the variables of user satisfaction of mobile App services in life insurance (Lee et al., 2015); (Shang and Wu., 2017) study used combination of TAM and ECM model in mobile shopping to find their influence on consumer satisfaction and continuance intention. (Cao et al., 2018) used Trust transfer theory to predict the trust construct in mobile payment and their effect on satisfaction and continued intentions. (Marinkovic et al., 2017) combined various models perceived usefulness (TAM), perceived enjoyment (flow theory), and social influence (UTAUT) to investigate the customer satisfaction. UTAUT model was used to measure the behavioural intentions of users and UTAUT also used to identify the customers usage intentions in different technologies that include Mobile banking, Mobile commerce, and Internet banking etc. researchers deployed UTAUT in different domains such as Internet banking (Rahmath Safeena et al., 2017); education (Rinku Dulloo and M. M Puri, 2019; Setiani, N. et al., 2020; Jalal Sarabdani et al., 2017); government services (Faaeq M. A. et al, 2014; Saxena, S., 2018; Olabode Olatubosun and K.S. Madhavarao, 2012) and health care (Sreejesh, S et al., 2021; W.B. Arfi et al., 2021; Plotzky C et al., 2021) domains. In this paper, it is used to check the continuance intention and recommendation intentions to use UPI.UTAUT has been used in mobile technology studies related to Mobile banking (Zhou et al, 2010; Mohamad saparudin et al., 2020; OslyUsman et al., 2020); Mobile tourism shopping (Tan et al, 2018); Mobile commerce (Chong, 2013;Veljko Marinkovic et al., 2019); Mobile advertising (Wong et al., 2015); Mobile learning (Chao, 2019). UTAUT model was used to measure the behavioural intentions of users, in this paper it is used to check the continuance intention and recommendation intentions to use UPI. The research model was developed by modifying UTAUT with additional variables as shown in the figure 1. Performance Expectancy (PE) - It is degree to which using a technology will provide benefits to its users in performing certain activities. Studies explored the impact of PE on consumer satisfaction in mobile shopping (Shang and Wu, 2017; Agrebi and Jallais, 2015); Mobile learning (Chao, 2019). PE has affected satisfaction positively in mobile learning (Chao, 2019); mobile Apps (Tam et al, 2018); mobile commerce (Chong, 2013; Marinkovic et al, 2017). In this study, it is defined as the extent to which consumers think utilising UPI will achieve a specific goal. PE will effect user satisfaction and have an impact on users' intentions to continue using UPI. H1: Performance Expectancy is positively related to user satisfaction. Effort Expectancy (EE) - The degree of easiness involved with using technology is a key variable in the UTAUT paradigm. A person's perception of how easy it would be to utilise a technology is referred to as perceived ease of use. Studies have conflicting results that: EE affects consumer satisfaction positively in mobile commerce (Yeh and Li, 2009); mobile insurance (Lee et al., 2015); mobile shopping (Agrebi and Jallais, 2015; Shang and Wu, 2017). It is suggested that EE will affect satisfaction with the usage of UPI in this study, where it is defined as the level of ease associated with using UPI. H2: Effort Expectancy is positively related to user satisfaction Social Influence (SI) - refers to degree that users perceive that family and friends believe they should use a particular technology. Social influence denotes the effect of important people’ believes on user behaviour, their reviews can be affecting the usage of mobile technologies (Tao Zhou, 2011). So that electronic payment providers should use Word of mouth to facilitate user’s intentions. A study found that social ties have significant impact on satisfaction and continued intention in mobile social apps (Hsiao et al, 2016); satisfaction had also affected significantly by Social Influence in mobile shopping (San-Martin et al., 2016). It is defined in this study as the extent to which a person believes that another significant person encourages him or her for using UPI. H3: Social Influence is positively related to user satisfaction. Facilitating Conditions (FC) - someone’ believes that available organisational and technical infrastructural support to use of a system. We can say that Facilitating conditions mean users have necessary resources and knowledge to operate UPI services. In this perspective, the availability of customer support, mobile devices, an internet connection, and QR codes are facilitating conditions for employing UPI services. The degree to which a person believes that an administrative and technological framework is in place to facilitate the usage of UPI is what it is referred to as in this study. In massive open online courses Facilitating conditions affected User satisfaction significantly (Liyong Wan et al., 2020). FC also found significant influence on consumer satisfaction in online services in South Korea. (Gholami et al,2012; Minki Park, 2020). H4: Facilitating Conditions is positively related to user satisfaction. Personal Innovativeness (PI) : personal innovativeness can be referring as individual’s adoption of new things/ products as compare to others in the community of which they belong (Leavitt and Walton, 1975). Innovativeness has great role to know the users intentions to use new electronic technologies, but people have not so great experience about new mobile innovations (Kim et al., 2010). The studies found that personal innovativeness has positive and significant effect on user’s satisfaction (Khan et al., 2019). Personal innovativeness affected satisfaction positively but personal innovativeness was not associated with continuance intention in IT (Chou and Chen, 2009). In m-commerce context personal innovativeness has positive influence on continuance intention (Lu June, 2014). Mobile tourism studies showed that more satisfied tourists with use of innovative technology likely to have usage intentions of it (T. Jung et al., 2015). H5 and H6: personal innovativeness is positively related to user satisfaction and Continuance intention to use UPI. Satisfaction (SAT) - Satisfaction means the fulfilment of expectations. It is one of the pillars in marketing and an important factor that affects trustworthiness of the consumer (Marinkovic et al., 2017). Satisfaction increases if after purchasing the consumer is experiencing improved product or service than his expectations (Yeh and Li 2009). Satisfied customers normally repurchase the products and take part in constructive spread of information (Wang and Liao, 2007). Continuance Intention (CI) - refers to a person's long-term or continuing purpose to use a technology (Bhattacherjee,2001). The main factor affecting users' intention to continue using a service is their level of satisfaction. Users are more satisfied with the community when they have had positive experiences utilising it, when problems are successfully solved, or when they feel like they belong there (Han et al, 2018). In mobile commerce (Chong, 2013), (Luqman. A. et al., 2016), mobile shopping (Shang and Wu, 2017), mobile purchases (Gao et al., 2015), mobile banking (Liébana et al., 2017), mobile utilities (Kuo et al., 2009; Susanto et al., 2016), and mobile apps (Kuo et al., 2009), satisfaction was discovered to be a significant factor (Hsiao et al., 2016; Tam et al., 2018). H7: User’s satisfaction is positively related to continuance intention. Pace of Innovation (POI) : It is the pace at which innovations in the technology are occurring at which pace. The digital payments technologies are moving forward at revolutionary speed; users are willing to use new digital payment systems (Cabanillas et al, 2017). In India, As compared to other technologies UPI is changing fast and innovations in UPI occurring frequent. (Camilleri, 2019) Study found that pace of technological innovation has no relationship with intention to use social media. H8: the pace of innovation has positive and significant effect on their continuance intention to use UPI Intention to recommend (IR) : Word of Mouth (WOM) has a great influence on intention to recommend in firm performance (Keiningham et al., 2007; Morgan and Rego, 2006; Reichheld, 2003). Literature depicted that Continuance intention as well as intention to recommend were both influenced by satisfaction, moreover, various factors such as quality of system, perceived usefulness perceived enjoyment, confirmation, quality of information and satisfaction affected continuance intention and intention to recommend in information based mobile application (Setyawan et al., 2017). Higher satisfaction towards technology usually has more continuance intentions to use it and go in for positive word of mouth (Wang and Liao, 2007). H9 Continuance intention of using UPI is positively associated with Intention to recommend. 3. Research Methodology This study adapted items from previously validated measures for use with the framework of IT/IS in order to ensure the validity and reliability of the questionnaire. To evaluate performance expectancy, effort expectancy, social influence, and facilitating conditions, we used the questions from Venkatesh et al. (2003). In order to analyse personal innovativeness and ongoing intention (Kim et al., 2007 and Indrawati, 2018) as well as pace of innovation from Grewal et al., we employed the items from Aygul Turan, (2015) and Goldsmith & Hofacker (1991). (2004). To test respondents' intention to recommend and satisfaction, we modified the Gupta et al. (2020), Goldsmith and Hofacker (1991), and Hofacker et al. To measure each item, we applied a Likert seven-point scale. To guarantee the questionnaire validity and reliability, this study adapted items from previously validated instruments to use with the context of IT/IS. We adopted the items from Venkatesh et al (2003) to measure performance expectancy, effort expectancy, social influence, and facilitating conditions. We used the items from Aygul Turan, (2015) and Goldsmith & Hofacker (1991) to examine personal innovativeness and continued intention (Kim et al., 2007 and Indrawati, 2018) and pace of innovation from Grewal et al. (2004). We adapted the items from Gupta et al, (2020), Goldsmith and Hofacker (1991) to examine intention to recommend and satisfaction. We used a Likert seven–point scale to take the measurements of all items. Ambiguous items were examined twice before being included in an online survey: during the expert review and the pilot trial. Five experts were invited to the first stage to check that the measuring tools suited the UPI context and examine the tools to ensure that they appropriately reflected the model. The style of writing and viability of the measurement tools of the constructs have fit the context of UPI and are correct, according to all specialists. In the second stage, we conducted a pilot research with 79 respondents and changed unclear items in response to issues found. There were two sections to the questionnaire. The demographics of this study, including age, gender, and occupation, were first described. The research model's chosen constructs are measured in the second portion. Data Collection We gathered information via an online survey. It was a requirement that everyone use UPI apps. First, we checked that the participants had knowledge of and experience with UPI apps before sending out the questionnaire. Second, a Google platform was used to distribute the questionnaire online. They have willingly refused payment or gifts in order to prevent any potential biases and provided the researchers with accurate answers. 651 individuals who have used UPI apps completed the online survey between September 2021 and March 2022. The demographic traits that we estimated are shown in Table 1 below. Males made up 57.3% of all respondents, while females made up 42.7% of all participants. 39.8% of participants were under the age of 30, 42.5% were between the ages of 31 and 45, and 17.7% were over the age of 45. The majority of participants in this study (83.5%) were workers. The participants are mostly from urban areas. Table 1: Demographic profile Gender Frequency Percentage (%) Male 373 57.3 Female 278 42.7 Age Less than 30 years 259 39.8 31-45 years 277 42.5 More than 45 years 115 17.7 Occupation Service class- (Employees) 279 42.9 Businessmen 110 16.9 Professional-(CA, DR., Lawyers etc.) 58 8.9 Retired people 49 7.5 Student 155 23.8 Location Rural 151 23.2 Urban 500 76.8 Data Analysis This study used a three-step analysis procedure to test the given hypotheses. First, a confirmatory factor analysis was performed in this study using SPSS Statistics 25 to test the measurement model. Second, this work employed the structural equation model technique using SmartPLS to test the structural model. Third, this study tested the mediating function of satisfaction using the bootstrapping analysis method Results The conceptual framework, which consists of measuring tools and components, derives from the structural equation model. Table 2 contains the means and standard deviations for each construct. Based on the sample examination, we evaluate each construct's validity, reliability, and content. We carry out a verifying factor analysis. The validity of the questionnaire's content is guaranteed because every scale is based on previously conducted research. The reliability of the questionnaire is supported by Cronbach's alpha and composite reliability, both of which are greater than 0.7 [74]. Additionally, the results and all factor loadings over 0.7 demonstrate the strong convergent validity of our scales [74]. Average variance extracted from all constructs (AVE) was higher than the permitted level. Table2: Results of Constructs Validity and Reliability Construct Item Code Mean SD Loadings CA CR AVE Continuance Intention CI1 4.91 1.612 0.85 0.912 0.912 0.636 CI2 4.81 1.568 0.758 CI3 4.79 1.567 0.72 CI4 4.72 1.542 0.772 CI5 4.73 1.496 0.762 CI6 4.97 1.717 0.907 Effort Expectancy EE1 4.90 1.545 0.797 0.908 0.908 0.664 EE2 5.02 1.550 0.807 EE3 4.92 1.620 0.814 EE4 4.86 1.660 0.83 EE5 4.70 1.605 0.825 Facilitating Conditions FC1 5.33 1.513 0.782 0.864 0.864 0.56 FC2 5.21 1.495 0.799 FC3 5.03 1.625 0.709 FC4 5.11 1.499 0.713 FC5 5.11 1.575 0.734 Performance Expectancy PE1 5.15 1.641 0.823 0.891 0.893 0.625 PE2 5.01 1.558 0.755 PE3 5.04 1.620 0.722 PE4 4.85 1.583 0.807 PE5 5.09 1.642 0.84 Personal Innovativeness PII1 4.86 1.690 0.79 0.882 0.881 0.554 PII2 4.30 1.700 0.665 PII3 4.73 1.675 0.8 PII4 4.63 1.612 0.695 PII5 4.73 1.592 0.757 PII6 4.90 1.661 0.749 Pace of Innovation POI1 4.85 1.644 0.821 0.918 0.918 0.652 POI2 4.77 1.676 0.772 POI3 4.59 1.602 0.786 POI4 4.74 1.669 0.818 POI5 4.66 1.668 0.805 POI6 4.68 1.636 0.841 Intention to Recommend RI1 5.03 1.528 0.848 0.904 0.904 0.701 RI2 4.96 1.593 0.826 RI3 5.07 1.529 0.821 RI4 5.17 1.568 0.855 Satisfaction SAT1 5.13 1.498 0.83 0.892 0.893 0.625 SAT2 5.03 1.560 0.72 SAT3 4.96 1.519 0.801 SAT4 5.13 1.519 0.775 SAT5 5.10 1.589 0.823 Social Influence SI1 4.67 1.670 0.853 0.912 0.912 0.676 SI2 4.57 1.640 0.805 SI3 4.67 1.655 0.915 SI4 4.98 1.657 0.785 SI5 4.57 1.677 0.742 Discriminant validity - The degree to which assessment tools are uncorrelated with other different constructs is known as discriminant validity. If a construct's square roots of AVE are higher than its correlation coefficient with any other construct, discriminant validity is demonstrated [75]. The constructs' strong discriminant validity is demonstrated in Table 3. Table 3: Discriminant validity CI EE FC RI POI PE PI SAT SI CI 0.797 EE 0.624 0.815 FC 0.662 0.685 0.749 RI 0.761 0.569 0.567 0.837 POI 0.75 0.802 0.657 0.66 0.807 PE 0.518 0.647 0.64 0.512 0.624 0.791 PI 0.677 0.605 0.601 0.599 0.632 0.561 0.744 SAT 0.696 0.638 0.644 0.594 0.66 0.643 0.578 0.791 SI 0.451 0.633 0.61 0.492 0.559 0.543 0.521 0.505 0.822 Structural Model Analysis - Table 4 and Figure 2 display the findings of the hypothesis testing, including standardised path coefficients and the percentage of variance explained. Results demonstrate that, with the exception of social influence, all hypotheses were supported (H3). The statistical significance of the association between performance expectations and satisfaction supports hypothesis H1. The findings demonstrate the importance of EE, FC and PI on users' satisfaction with UPI apps. H1, H2, H4, and H5 were supported as a result of this study's identification of the impacts of antecedents on satisfaction. Additionally, this study discovered that H7 was supported and that satisfaction significantly influences continuing usage intention. This study also confirmed the favourable association between continuing intention and intention to recommend. In addition, as displayed on Table 4 and Figure 2 we found effect of personal innovativeness and pace of innovation on continued usage intention with UPI. Hence, H6 and H8 were supported. 5000 bootstrap samples, which have been shown to be more accurate than the Sobel test [73, 77], were used in this investigation to investigate the mediating model. The estimates of the estimated mediation effects have a 95% confidence interval that excludes zero, as shown in Table 5, and all indirect effects are significant [27]. As a result, the bootstrapping findings demonstrated that the mediation effects of satisfaction were significant. Table 4: Results of the Hypotheses Testing. Hypothesis Endogenous Construct Exogeneous Construct Path Coefficients Standard Deviation T Stats R Square Remark H1 SAT PE 0.247 0.04 6.114** 47.1% Supported H2 EE 0.203 0.034 5.889** Supported H3 SI 0.035 0.037 0.934 Not Supported H4 FC 0.202 0.038 5.296** Supported H5 PI 0.159 0.035 4.485** Supported H6 PI 0.132 0.041 3.256 48.0% Supported H8 POI 0.261 0.047 5.551** Supported H7 SAT 0.144 0.039 3.655** Supported H9 IR 0.693 0.026 26.878** Supported Table 5: Bootstrapping analysis of the mediation effect of satisfaction. Type of Effect Relationship Standardized Path Coefficient P value Remarks Total Effect PE EE SI FC PI 0.518 0.626 0.452 0.664 0.609 12.974*** 16.748*** 11.618*** 19.844*** 18.750*** Significant total effect Indirect Effect PE EE SI FC PI 0.398 0.320 0.317 0.295 0.221 10.599*** 9.142*** 8.75*** 8.321*** 8.445*** Significant indirect effect found Direct Effect PE EE SI FC PI 0.120 0.306 0.135 0.369 0.388 2.630*** 6.211*** 3.003*** 7.164*** 9.418*** Significant direct effect found 4. Discussion The objective of the research is to explore the impact of users continuance intentions of UPI usage from the perspective of extension of the UTAUT model with personal innovativeness and pace of innovation. Our results proved that performance expectancy, effort expectancy, social influence, facilitating conditions, personal innovativeness have positively and significantly influenced the users continuance intentions through the mediation role of satisfaction Moreover, users’ continuance intention positively affects the intention to recommend the UPI apps. It is also found identified that personal innovativeness of using UPI increases the significant effect on continuance intention. This study identifies that personal innovativeness of using UPI directly affects users’ continuous intentions and users should be try out to use new UPI features. Personal innovativeness described that personal trait are the significant factors of continuance intentions towards using UPI payments system. Pace of innovation in this study affects the continuance intentions of UPI users. Pace of innovation is repetitive because it is continuously committed with new emerging innovations. The empirical findings of this study demonstrate that all predictions have been supported, and the extended UTAUT is a crucial theoretical model for estimating the future use of UPI. Practical implications of the study This study aims to explore the influences of users’ continued intentions of UPI usage from the perspective of UTAUT. The majority of studies focused on digital payments, as adoption of digital payments, as continuation and recommendation intentions of UPI users, has not been explored in the Indian context. The results of the study will be vital for UPI service providers and banking institutions to provide different services to their users. The UPI service providers should focus on performance and effort expectations, facilitating conditions that enhance user satisfaction. To increase the continued intention of using UPI, service providers must pay attention to making and communicating useful and non-useful benefits of new features of UPI. They must emphasize the useful aspect of new UPI apps, features, etc. promoting or advertising new products of UPI can create more opportunities for users to experience new things which can increase their continuance intention towards using UPI. The UPI service providers must provide advanced technology and infrastructure on the UPI platform. Constant professional growth and progressive training are essential for successful and well-organized use of UPI services. 5. Theoretical Implications Of The Study The UTAUT model has been used with additional variables personal innovativeness, pace on innovation, continuance intentions, and intention to recommend. A comprehensive study framework has been drawn representing relationship between user satisfaction and continuance intention. The proposed comprehensive research framework is empirically tested in the context of UPI. The findings provide evidence supporting the validity and reliability of the framework. Therefore, it could be claimed that this comprehensive research framework can be used as a research tool in examining determinant factors in decision to continue and recommend in technological innovations. This study investigates the impact of performance expectancy, effort expectancy, social influence, facilitating conditions, and personal innovativeness on users’ satisfaction. It examines the influence of personal innovativeness, and pace of innovation on continued intentions. It also examined the influence of performance expectancy, effort expectancy, social influence, facilitating conditions, and personal innovativeness on the continuance intentions of the UPI system through the mediating role of user satisfaction. The study has used the validated instrument which will be extremely useful for future researchers in understanding the users' retention and recommendation intentions 6. Conclusion In order to investigate the effects of factors on the continuing use of UPI, we offer a research model based on the suitable theoretical model that adds two factors, personal innovativeness and pace on innovation, to the original UTAUT. Our findings demonstrate that, via the mediating effect of satisfaction, users' intentions to continue using a product or service are significantly positively impacted by performance expectations, effort expectations, social influence, facilitating conditions, and individual inventiveness. Additionally, consumers' intention to continue around influences their intention to recommend. References Agrebi, S., and J. Jallais. 2015. “Explain the Intention to use Smartphones for Mobile Shopping.” Journal of Retailing and Consumer Services , 22: 16–23. Bhattacherjee, A. 2001a. “An Empirical Analysis of the Antecedents of Electronic Commerce Service Continuance.” Decision Support Systems , 32 (2): 201–214. 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Consumers' Continuance Intention Use of Mobile Banking in Jakarta: Extending UTAUT Models with Trust. In 2020 International Conference on Information Management and Technology (ICIMTech) (pp. 50–54). IEEE. Usman, O., Monoarfa, T., &Marsofiyati, M. (2020). E-Banking and mobile banking effects on customer satisfaction. Accounting , 6 (6), 1117–1128. VeljkoMarinković, AleksandarĐorđević&ZoranKalinić (2019): The moderating effects of gender on customer satisfaction and continuance intention in mobile commerce: a UTAUT-based perspective, Technology Analysis & Strategic Management, DOI: 10.1080/09537325.2019.1655537 RinkuDulloo and M. M Puri, (2019), Using Unified Theory of Acceptance and Use of Technology in Higher Education through Smartphone. International Journal of Recent Technology and Engineering (IJRTE), Volume-X, Issue-X. DOI: 10.35940/ijrte.B1049.0782S419 Plotzky, C., Lindwedel, U., Bejan, A., König, P., &Kunze, C. (2021). 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Examining protection motivation and network externality perspective regarding the continued intention to use m-health apps. International Journal of Environmental Research and Public Health , 18 (11), 5684. Yan, Z., Wang, T., Chen, Y., & Zhang, H. (2016). Knowledge sharing in online health communities: A social exchange theory perspective. Information & management , 53 (5), 643–653. Zhang, X., Han, X., Dang, Y., Meng, F., Guo, X., & Lin, J. (2017). User acceptance of mobile health services from users’ perspectives: The role of self-efficacy and response-efficacy in technology acceptance. Informatics for Health and Social Care , 42 (2), 194–206. Fornell, C., & Larcker, D. F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of marketing research , 18 (1), 39–50. Hayes, A. F. (2017). Introduction to mediation, moderation, and conditional process analysis: A regression-based approach . Guilford publications. Wu, P., Zhang, R., Zhu, X., & Liu, M. (2022, January). Factors Influencing Continued Usage Behavior on Mobile Health Applications. In Healthcare (Vol. 10, No. 2, p. 208). MDPI. Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-1966920","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":129640369,"identity":"c0078da8-5e01-4fc1-bc4c-44609f4f1d1d","order_by":0,"name":"sandeep kaur","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA7UlEQVRIiWNgGAWjYDACHhDBBuUkVAAJZuYGUrScAWlhJEULYxuYxK9Fvuf4w88FZTZy5mKHj254OK82mr8dqOVHxTacWgzO9hhLzziXZmw5Oy3tRuK247kzDjM2MPacuY1bCz8PgzRv2+HEDbdzzIBajuU2ALUwM7bh1iLfz/74N2/b/3qIljnHcucT0sJwtsEMaMuBBAOwloaa3A2EtBicOWNmzXMu2XAnyC8Jxw7kbgRqOYjPL/I96Y9v85TZyZtLJx+7+aOmLnfe+cMHH/yowOMwuHUQ6jCYPEBYPUJLHVGKR8EoGAWjYGQBALNeXv5hhvbUAAAAAElFTkSuQmCC","orcid":"","institution":"Lovely Professional University","correspondingAuthor":true,"submittingAuthor":false,"prefix":"","firstName":"sandeep","middleName":"","lastName":"kaur","suffix":""}],"badges":[],"createdAt":"2022-08-16 10:14:27","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-1966920/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-1966920/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":25432587,"identity":"184f23f2-c955-4fde-bcdd-a22b320e8926","added_by":"auto","created_at":"2022-08-19 17:54:36","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":54914,"visible":true,"origin":"","legend":"\u003cp\u003eResearch model.\u003c/p\u003e\u003cp\u003e\u003cbr\u003e\u003c/p\u003e","description":"","filename":"Figure1.png","url":"https://assets-eu.researchsquare.com/files/rs-1966920/v1/c0dceec48b1289b0bd50f0a0.png"},{"id":25432586,"identity":"601fe10d-9853-478d-87a1-9640d06decce","added_by":"auto","created_at":"2022-08-19 17:54:36","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":126543,"visible":true,"origin":"","legend":"\u003cp\u003eResults of hypothesis testing\u0026nbsp;\u003c/p\u003e\u003cp\u003e\u003cbr\u003e\u003c/p\u003e","description":"","filename":"Figure2.png","url":"https://assets-eu.researchsquare.com/files/rs-1966920/v1/2fb5aea8918f9ed77a899755.png"},{"id":26386546,"identity":"600f5a50-1b13-4832-88d8-1fae0b28e799","added_by":"auto","created_at":"2022-09-13 09:29:28","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":525998,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-1966920/v1/60814e0e-05dd-4120-b510-5d351329ba99.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Factors Influencing Continuance Intentions of Unified Payment Interface (UPI) users","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eUnified Payments Interface (UPI) system gives power to multiple bank accounts into a single mobile application with several banking features on a single platform. It is peer to peer collect request which can be done as per requirement and convenience. UPI is an instant real time payment system launched by National payments corporation of India (NPCI), regulated by Reserve Bank of India. Using a UPI enabled app the users can perform financial transactions instantly between two bank accounts on a mobile platform. The user should frame-up a Personal Identification Number (MPIN) for UPI ID for a bank account while setting up the UPI enabled App. Additional banks details like bank account number, branch IFSC code are not required. As on March2019 there were 142 banks(at present 189) live on UPI with a monthly volume of 799.54 million transactions and a value of ₹1.334 trillion (US$19 billion). UPI witnessed 180 crore (207 crore in October) transactions worth 3.29 lakh crore in September 2020 (3.86 lakh crore in October 2020).The pilot launch was done by Dr Raghuram G Rajan, former governor of RBI Mumbai on 11\u003csup\u003eth\u003c/sup\u003e April 2016; from 25\u003csup\u003eth\u003c/sup\u003e August 2016 Banks have started to upload their UPI apps on Google Play store.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eUPI facilitates the round-the-clock financial transaction services. The UPI needs only to authenticate the identity of the user like debit card does using the phone as a tool instead of a separate card. The banks, consumers, merchants are the users of the UPI. The UPI platform helps the banks to remove infrastructural cost, and providing safe and secure transactions to its customers. The unique transaction number facilitates the banks to check where fraudulent transactions are located. Making transactions with smartphones are effortless, reduces the time and cost, UPI service 24hours available on a single application. \u0026nbsp;The merchants used UPI to receive payments from the customers and the risk of storing their financial information is very less.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe Ecosystem of UPI includes three players- Payment service providers, Banks, NPCI. Payment service providers act as a link between the payer and payee where banks maintain accounts for the payer and payee. NPCI as a central body control their virtual payment address. (Thomas and Chatterjee, 2017).It enables in reducing the cash-based economy and promotes digital economy in India.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eBenefits of the UPI:\u0026nbsp;\u003c/p\u003e\n\u003col\u003e\n \u003cli\u003eIt is very simple, safe and convenient payment method for both- Sender and Receiver.\u003c/li\u003e\n \u003cli\u003e\u0026nbsp;It is instant and secures validation, can be done anywhere.\u003c/li\u003e\n \u003cli\u003eCustomers can make payments of school fees, utility bills via Smartphones and internet.\u003c/li\u003e\n \u003cli\u003eThere is no need to use multistep processes like Net-banking, also eliminates the use of debit cards, credit cards.\u0026nbsp;\u003c/li\u003e\n \u003cli\u003eIt helps in the growth of e-commerce and other trading activities.\u003c/li\u003e\n \u003cli\u003eIs provides financial inclusion in the economy, reducing cash -based activities, promotes digital economy in India.\u0026nbsp;\u003c/li\u003e\n\u003c/ol\u003e\n\u003cp\u003eThe aim of the study is to explore the User satisfaction and continuance usage intention towards UPI through proposed model.\u0026nbsp;\u003c/p\u003e"},{"header":"2. Conceptual Model Development","content":"\u003cp\u003eVarious theories and models were deployed in previous studies of user satisfaction and continuance usage intentions in different areas. Expectations Confirmation model deployed to find the satisfaction and continue intentions among Chinese consumers (Chong, 2013); User satisfaction regarding smartphones studied with the help of Bhattacherjee\u0026rsquo;s post acceptance model (Liang et al, 2018); continued intention in purchase of mobile phones used flow theory (Gao et al, 2015); Contingency and task technology theories employed to find the variables of consumer satisfaction in mobile tourism shopping (Kim et al.,2 015). Modified TAM extended with additional variable- perceived enjoyment to explore the user satisfaction and continuance intention to use smartphone for shopping by (Agrebi and jallais, 2015); TAM was also used to find the variables of user satisfaction of mobile App services in life insurance (Lee et al., 2015); (Shang and Wu., 2017) study used combination of TAM and ECM model in mobile shopping to find their influence on consumer satisfaction and continuance intention. \u0026nbsp;(Cao et al., 2018) used Trust transfer theory to predict the trust construct in mobile payment and their effect on satisfaction and continued intentions. (Marinkovic et al., 2017) combined various models perceived usefulness (TAM), perceived enjoyment (flow theory), and social influence (UTAUT) to investigate the customer satisfaction.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eUTAUT model was used to measure the behavioural intentions of users and UTAUT also used to identify the customers usage intentions in different technologies that include Mobile banking, Mobile commerce, and Internet banking etc. \u0026nbsp; researchers deployed UTAUT in different domains such as Internet banking (Rahmath Safeena et al., 2017); education (Rinku Dulloo and M. M Puri, 2019; Setiani, N. et al., 2020; Jalal Sarabdani et al., 2017); government services (Faaeq M. A. et al, 2014; Saxena, S., 2018; Olabode Olatubosun and K.S. Madhavarao, 2012) and health care (Sreejesh, S et al., 2021; W.B. Arfi et al., 2021; Plotzky C et al., 2021) domains. In this paper, it is used to check the continuance intention and recommendation intentions to use UPI.UTAUT has been used in mobile technology studies related to Mobile banking (Zhou et al, 2010; Mohamad saparudin et al., 2020; OslyUsman et al., 2020); Mobile tourism shopping (Tan et al, 2018); Mobile commerce (Chong, 2013;Veljko Marinkovic et al., 2019); Mobile advertising (Wong et al., 2015); Mobile learning (Chao, 2019). UTAUT model was used to measure the behavioural intentions of users, in this paper it is used to check the continuance intention and recommendation intentions to use UPI. The research model was developed by modifying UTAUT with additional variables as shown in the figure 1.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ePerformance Expectancy (PE) -\u003c/strong\u003e It is degree to which using a technology will provide benefits to its users in performing certain activities. Studies explored the impact of PE on consumer satisfaction in mobile shopping (Shang and Wu, 2017; Agrebi and Jallais, 2015); Mobile learning (Chao, 2019). PE has affected satisfaction positively in mobile learning (Chao, 2019); mobile Apps (Tam et al, 2018); mobile commerce (Chong, 2013; Marinkovic et al, 2017). In this study, it is defined as the extent to which consumers think utilising UPI will achieve a specific goal. PE will effect user satisfaction and have an impact on users\u0026apos; intentions to continue using UPI.\u003c/p\u003e\n\u003cp\u003eH1: Performance Expectancy is positively related to user satisfaction.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEffort Expectancy (EE)\u0026nbsp;\u003c/strong\u003e- The degree of easiness involved with using technology is a key variable in the UTAUT paradigm. A person\u0026apos;s perception of how easy it would be to utilise a technology is referred to as perceived ease of use.\u0026nbsp;Studies have conflicting results that: EE affects consumer satisfaction positively in mobile commerce (Yeh and Li, 2009); mobile insurance (Lee et al., 2015); mobile shopping (Agrebi and Jallais, 2015; Shang and Wu, 2017).\u0026nbsp;It is suggested that EE will affect satisfaction with the usage of UPI in this study, where it is defined as the level of ease associated with using UPI.\u003c/p\u003e\n\u003cp\u003eH2: Effort Expectancy is positively related to user satisfaction \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSocial Influence\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;(SI)\u003c/strong\u003e - refers to degree that users perceive that family and friends believe they should use a particular technology. Social influence denotes the effect of important people\u0026rsquo; believes on user behaviour, their reviews can be affecting the usage of mobile technologies (Tao Zhou, 2011). So that electronic payment providers should use Word of mouth to facilitate user\u0026rsquo;s intentions. A study found that social ties have significant impact on satisfaction and continued intention in mobile social apps (Hsiao et al, 2016); satisfaction had also affected significantly by Social Influence in mobile shopping (San-Martin et al., 2016). It is defined in this study as the extent to which a person believes that another significant person encourages him or her for using UPI.\u003c/p\u003e\n\u003cp\u003eH3: Social Influence is positively related to user satisfaction.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFacilitating Conditions (FC)\u003c/strong\u003e - someone\u0026rsquo; believes that available organisational and technical infrastructural support to use of a system. We can say that Facilitating conditions mean users have necessary resources and knowledge to operate UPI services. In this perspective, the availability of customer support, mobile devices, an internet connection, and QR codes are facilitating conditions for employing UPI services. The degree to which a person believes that an administrative and technological framework is in place to facilitate the usage of UPI is what it is referred to as in this study. In massive open online courses Facilitating conditions affected User satisfaction significantly (Liyong Wan et al., 2020). FC also found significant influence on consumer satisfaction in online services in South Korea. (Gholami et al,2012; Minki Park, 2020).\u003c/p\u003e\n\u003cp\u003eH4: Facilitating Conditions is positively related to user satisfaction.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ePersonal Innovativeness (PI)\u003c/strong\u003e: personal innovativeness can be referring as individual\u0026rsquo;s adoption of new things/ products as compare to others in the community of which they belong (Leavitt and Walton, 1975). Innovativeness has great role to know the users intentions to use new electronic technologies, but people have not so great experience about new mobile innovations (Kim et al., 2010). \u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe studies found that personal innovativeness has positive and significant effect on user\u0026rsquo;s satisfaction (Khan et al., 2019). Personal innovativeness affected satisfaction positively but personal innovativeness was not associated with continuance intention in IT (Chou and Chen, 2009). \u0026nbsp;In m-commerce context personal innovativeness has positive influence on continuance intention (Lu June, 2014). Mobile tourism studies showed that more satisfied tourists with use of innovative technology likely to have usage intentions of it (T. Jung et al., 2015).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eH5 and H6: personal innovativeness is positively related to user satisfaction and Continuance intention to use UPI.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSatisfaction (SAT)\u003c/strong\u003e- Satisfaction means the fulfilment of expectations. It is one of the pillars in marketing and an important factor that affects trustworthiness of the consumer (Marinkovic et al., 2017). Satisfaction increases if after purchasing the consumer is experiencing improved product or service than his expectations (Yeh and Li 2009). Satisfied customers normally repurchase the products and take part in constructive spread of information (Wang and Liao, 2007).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eContinuance Intention (CI)\u0026nbsp;\u003c/strong\u003e-\u0026nbsp;refers to a person\u0026apos;s long-term or continuing purpose to use a technology (Bhattacherjee,2001). The main factor affecting users\u0026apos; intention to continue using a service is their level of satisfaction. Users are more satisfied with the community when they have had positive experiences utilising it, when problems are successfully solved, or when they feel like they belong there (Han et al, 2018). In mobile commerce (Chong, 2013), (Luqman. A. et al., 2016), mobile shopping (Shang and Wu, 2017), mobile purchases (Gao et al., 2015), mobile banking (Li\u0026eacute;bana et al., 2017), mobile utilities (Kuo et al., 2009; Susanto et al., 2016), and mobile apps (Kuo et al., 2009), satisfaction was discovered to be a significant factor (Hsiao et al., 2016; Tam et al., 2018).\u003c/p\u003e\n\u003cp\u003eH7: User\u0026rsquo;s satisfaction is positively related to continuance intention.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ePace of Innovation (POI)\u003c/strong\u003e: It is the pace at which innovations in the technology are occurring at which pace. \u0026nbsp;The digital payments technologies are moving forward at revolutionary speed; users are willing to use new digital payment systems (Cabanillas et al, 2017). In India, As compared to other technologies UPI is changing fast and innovations in UPI occurring frequent. (Camilleri, 2019) Study found that pace of technological innovation has no relationship with intention to use social media. \u0026nbsp;\u003c/p\u003e\n\u003cp\u003eH8: the pace of innovation has positive and significant effect on their continuance intention to use UPI\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eIntention to recommend (IR)\u003c/strong\u003e: Word of Mouth (WOM) has a great influence on intention to recommend in firm performance (Keiningham et al., 2007; Morgan and Rego, 2006; Reichheld, 2003). \u0026nbsp;Literature depicted that Continuance intention as well as intention to recommend were both influenced by satisfaction, moreover, various factors such as quality of system, perceived usefulness perceived enjoyment, confirmation, quality of information and satisfaction affected continuance intention and intention to recommend in information based mobile application (Setyawan et al., 2017). Higher satisfaction towards technology usually has more continuance intentions to use it and go in for positive word of mouth (Wang and Liao, 2007).\u003c/p\u003e\n\u003cp\u003eH9 Continuance intention of using UPI is positively associated with Intention to recommend.\u003c/p\u003e"},{"header":"3. Research Methodology","content":"\u003cp\u003eThis study adapted items from previously validated measures for use with the framework of IT/IS in order to ensure the validity and reliability of the questionnaire. To evaluate performance expectancy, effort expectancy, social influence, and facilitating conditions, we used the questions from Venkatesh et al. (2003). In order to analyse personal innovativeness and ongoing intention (Kim et al., 2007 and Indrawati, 2018) as well as pace of innovation from Grewal et al., we employed the items from Aygul Turan, (2015) and Goldsmith \u0026amp; Hofacker (1991). (2004). To test respondents\u0026apos; intention to recommend and satisfaction, we modified the Gupta et al. (2020), Goldsmith and Hofacker (1991), and Hofacker et al. To measure each item, we applied a Likert seven-point scale.\u003c/p\u003e\n\u003cp\u003eTo guarantee the questionnaire validity and reliability, this study adapted items from previously validated instruments to use with the context of IT/IS. We adopted the items from Venkatesh et al (2003) to measure performance expectancy, effort expectancy, social influence, and facilitating conditions. We used the items from Aygul Turan, (2015) and Goldsmith \u0026amp; Hofacker (1991) to examine personal innovativeness and continued intention (Kim et al., 2007 and Indrawati, 2018) and pace of innovation from Grewal et al. (2004). We adapted the items from \u0026nbsp;Gupta et al, (2020), \u0026nbsp;Goldsmith and Hofacker (1991) to examine intention to recommend \u0026nbsp;and satisfaction. We used a Likert seven\u0026ndash;point scale to take the measurements of all items. Ambiguous items were examined twice before being included in an online survey: during the expert review and the pilot trial. Five experts were invited to the first stage to check that the measuring tools suited the UPI context and examine the tools to ensure that they appropriately reflected the model. The style of writing and viability of the measurement tools of the constructs have fit the context of UPI and are correct, according to all specialists. In the second stage, we conducted a pilot research with 79 respondents and changed unclear items in response to issues found. There were two sections to the questionnaire. The demographics of this study, including age, gender, and occupation, were first described. The research model\u0026apos;s chosen constructs are measured in the second portion.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData Collection\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe gathered information via an online survey. It was a requirement that everyone use UPI apps. First, we checked that the participants had knowledge of and experience with UPI apps before sending out the questionnaire. Second, a Google platform was used to distribute the questionnaire online. They have willingly refused payment or gifts in order to prevent any potential biases and provided the researchers with accurate answers. 651 individuals who have used UPI apps completed the online survey between September 2021 and March 2022.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;The demographic traits that we estimated are shown in Table 1 below. Males made up 57.3% of all respondents, while females made up 42.7% of all participants. 39.8% of participants were under the age of 30, 42.5% were between the ages of 31 and 45, and 17.7% were over the age of 45. The majority of participants in this study (83.5%) were workers. The participants are mostly from urban areas.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 1: Demographic profile\u003c/strong\u003e\u003c/p\u003e\n\u003cdiv align=\"Left\"\u003e\n \u003ctable border=\"0\" cellpadding=\"0\" cellspacing=\"0\" width=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"50.160771704180064%\"\u003e\n \u003cp\u003e\u003cstrong\u003eGender\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"28.617363344051448%\"\u003e\n \u003cp\u003e\u003cstrong\u003eFrequency\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"21.221864951768488%\"\u003e\n \u003cp\u003e\u003cstrong\u003ePercentage (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"50.160771704180064%\"\u003e\n \u003cp\u003eMale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"28.617363344051448%\"\u003e\n \u003cp\u003e373\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"21.221864951768488%\"\u003e\n \u003cp\u003e57.3\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"50.160771704180064%\"\u003e\n \u003cp\u003eFemale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"28.617363344051448%\"\u003e\n \u003cp\u003e278\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"21.221864951768488%\"\u003e\n \u003cp\u003e42.7\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"3\" valign=\"top\" width=\"100%\"\u003e\n \u003cp\u003e\u003cstrong\u003eAge\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"50.160771704180064%\"\u003e\n \u003cp\u003eLess than 30 years\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"28.617363344051448%\"\u003e\n \u003cp\u003e259\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"21.221864951768488%\"\u003e\n \u003cp\u003e39.8\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"50.160771704180064%\"\u003e\n \u003cp\u003e31-45 years\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"28.617363344051448%\"\u003e\n \u003cp\u003e277\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"21.221864951768488%\"\u003e\n \u003cp\u003e42.5\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"50.160771704180064%\"\u003e\n \u003cp\u003eMore than 45 years\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"28.617363344051448%\"\u003e\n \u003cp\u003e115\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"21.221864951768488%\"\u003e\n \u003cp\u003e17.7\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"3\" valign=\"top\" width=\"100%\"\u003e\n \u003cp\u003e\u003cstrong\u003eOccupation\u003c/strong\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"50.160771704180064%\"\u003e\n \u003cp\u003eService class- (Employees)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"28.617363344051448%\"\u003e\n \u003cp\u003e279\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"21.221864951768488%\"\u003e\n \u003cp\u003e42.9\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"50.160771704180064%\"\u003e\n \u003cp\u003eBusinessmen\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"28.617363344051448%\"\u003e\n \u003cp\u003e110\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"21.221864951768488%\"\u003e\n \u003cp\u003e16.9\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"50.160771704180064%\"\u003e\n \u003cp\u003eProfessional-(CA, DR., Lawyers etc.)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"28.617363344051448%\"\u003e\n \u003cp\u003e58\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"21.221864951768488%\"\u003e\n \u003cp\u003e8.9\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"50.160771704180064%\"\u003e\n \u003cp\u003eRetired people\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"28.617363344051448%\"\u003e\n \u003cp\u003e49\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"21.221864951768488%\"\u003e\n \u003cp\u003e7.5\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"50.160771704180064%\"\u003e\n \u003cp\u003eStudent\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"28.617363344051448%\"\u003e\n \u003cp\u003e155\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"21.221864951768488%\"\u003e\n \u003cp\u003e23.8\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"3\" valign=\"top\" width=\"100%\"\u003e\n \u003cp\u003e\u003cstrong\u003eLocation\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"50.160771704180064%\"\u003e\n \u003cp\u003eRural\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"28.617363344051448%\"\u003e\n \u003cp\u003e151\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"21.221864951768488%\"\u003e\n \u003cp\u003e23.2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"50.160771704180064%\"\u003e\n \u003cp\u003eUrban\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"28.617363344051448%\"\u003e\n \u003cp\u003e500\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"21.221864951768488%\"\u003e\n \u003cp\u003e76.8\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003e\u003cstrong\u003eData Analysis\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study used a three-step analysis procedure to test the given hypotheses. First, a confirmatory factor analysis was performed in this study using SPSS Statistics 25 to test the measurement model. Second, this work employed the structural equation model technique using SmartPLS to test the structural model. Third, this study tested the mediating function of satisfaction using the bootstrapping analysis method\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe conceptual framework, which consists of measuring tools and components, derives from the structural equation model. Table 2 contains the means and standard deviations for each construct. Based on the sample examination, we evaluate each construct\u0026apos;s validity, reliability, and content. We carry out a verifying factor analysis. The validity of the questionnaire\u0026apos;s content is guaranteed because every scale is based on previously conducted research. The reliability of the questionnaire is supported by Cronbach\u0026apos;s alpha and composite reliability, both of which are greater than 0.7 [74]. Additionally, the results and all factor loadings over 0.7 demonstrate the strong convergent validity of our scales [74]. Average variance extracted from all constructs (AVE) was higher than the permitted level.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable2: Results of Constructs Validity and Reliability\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellpadding=\"0\" cellspacing=\"0\" width=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"17.739403453689167%\"\u003e\n \u003cp\u003e\u003cstrong\u003eConstruct\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"7.221350078492936%\"\u003e\n \u003cp\u003e\u003cstrong\u003eItem Code\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"10.204081632653061%\"\u003e\n \u003cp\u003e\u003cstrong\u003eMean\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"8.634222919937205%\"\u003e\n \u003cp\u003e\u003cstrong\u003eSD\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"13.657770800627944%\"\u003e\n \u003cp\u003e\u003cstrong\u003eLoadings\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"11.930926216640502%\"\u003e\n \u003cp\u003e\u003cstrong\u003eCA\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"16.16954474097331%\"\u003e\n \u003cp\u003e\u003cstrong\u003eCR\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"14.442700156985872%\"\u003e\n \u003cp\u003e\u003cstrong\u003eAVE\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"6\" valign=\"top\" width=\"17.739403453689167%\"\u003e\n \u003cp\u003eContinuance Intention\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"7.221350078492936%\"\u003e\n \u003cp\u003eCI1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"10.204081632653061%\"\u003e\n \u003cp\u003e4.91\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"8.634222919937205%\"\u003e\n \u003cp\u003e1.612\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"13.657770800627944%\"\u003e\n \u003cp\u003e0.85\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"6\" valign=\"top\" width=\"11.930926216640502%\"\u003e\n \u003cp\u003e0.912\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"6\" valign=\"top\" width=\"16.16954474097331%\"\u003e\n \u003cp\u003e0.912\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"6\" valign=\"top\" width=\"14.442700156985872%\"\u003e\n \u003cp\u003e0.636\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"18.181818181818183%\"\u003e\n \u003cp\u003eCI2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"25.691699604743082%\"\u003e\n \u003cp\u003e4.81\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"21.73913043478261%\"\u003e\n \u003cp\u003e1.568\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"34.387351778656125%\"\u003e\n \u003cp\u003e0.758\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"18.181818181818183%\"\u003e\n \u003cp\u003eCI3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"25.691699604743082%\"\u003e\n \u003cp\u003e4.79\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"21.73913043478261%\"\u003e\n \u003cp\u003e1.567\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"34.387351778656125%\"\u003e\n \u003cp\u003e0.72\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"18.181818181818183%\"\u003e\n \u003cp\u003eCI4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"25.691699604743082%\"\u003e\n \u003cp\u003e4.72\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"21.73913043478261%\"\u003e\n \u003cp\u003e1.542\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"34.387351778656125%\"\u003e\n \u003cp\u003e0.772\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"18.181818181818183%\"\u003e\n \u003cp\u003eCI5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"25.691699604743082%\"\u003e\n \u003cp\u003e4.73\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"21.73913043478261%\"\u003e\n \u003cp\u003e1.496\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"34.387351778656125%\"\u003e\n \u003cp\u003e0.762\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"18.181818181818183%\"\u003e\n \u003cp\u003eCI6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"25.691699604743082%\"\u003e\n \u003cp\u003e4.97\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"21.73913043478261%\"\u003e\n \u003cp\u003e1.717\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"34.387351778656125%\"\u003e\n \u003cp\u003e0.907\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"5\" valign=\"top\" width=\"17.739403453689167%\"\u003e\n \u003cp\u003eEffort Expectancy\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"7.221350078492936%\"\u003e\n \u003cp\u003eEE1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"10.204081632653061%\"\u003e\n \u003cp\u003e4.90\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"8.634222919937205%\"\u003e\n \u003cp\u003e1.545\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"13.657770800627944%\"\u003e\n \u003cp\u003e0.797\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"5\" valign=\"top\" width=\"11.930926216640502%\"\u003e\n \u003cp\u003e0.908\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"5\" valign=\"top\" width=\"16.16954474097331%\"\u003e\n \u003cp\u003e0.908\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"5\" valign=\"top\" width=\"14.442700156985872%\"\u003e\n \u003cp\u003e0.664\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"18.181818181818183%\"\u003e\n \u003cp\u003eEE2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"25.691699604743082%\"\u003e\n \u003cp\u003e5.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"21.73913043478261%\"\u003e\n \u003cp\u003e1.550\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"34.387351778656125%\"\u003e\n \u003cp\u003e0.807\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"18.181818181818183%\"\u003e\n \u003cp\u003eEE3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"25.691699604743082%\"\u003e\n \u003cp\u003e4.92\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"21.73913043478261%\"\u003e\n \u003cp\u003e1.620\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"34.387351778656125%\"\u003e\n \u003cp\u003e0.814\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"18.181818181818183%\"\u003e\n \u003cp\u003eEE4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"25.691699604743082%\"\u003e\n \u003cp\u003e4.86\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"21.73913043478261%\"\u003e\n \u003cp\u003e1.660\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"34.387351778656125%\"\u003e\n \u003cp\u003e0.83\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"18.181818181818183%\"\u003e\n \u003cp\u003eEE5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"25.691699604743082%\"\u003e\n \u003cp\u003e4.70\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"21.73913043478261%\"\u003e\n \u003cp\u003e1.605\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"34.387351778656125%\"\u003e\n \u003cp\u003e0.825\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"5\" valign=\"top\" width=\"17.739403453689167%\"\u003e\n \u003cp\u003eFacilitating Conditions\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"7.221350078492936%\"\u003e\n \u003cp\u003eFC1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"10.204081632653061%\"\u003e\n \u003cp\u003e5.33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"8.634222919937205%\"\u003e\n \u003cp\u003e1.513\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"13.657770800627944%\"\u003e\n \u003cp\u003e0.782\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"5\" valign=\"top\" width=\"11.930926216640502%\"\u003e\n \u003cp\u003e0.864\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"5\" valign=\"top\" width=\"16.16954474097331%\"\u003e\n \u003cp\u003e0.864\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"5\" valign=\"top\" width=\"14.442700156985872%\"\u003e\n \u003cp\u003e0.56\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"18.181818181818183%\"\u003e\n \u003cp\u003eFC2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"25.691699604743082%\"\u003e\n \u003cp\u003e5.21\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"21.73913043478261%\"\u003e\n \u003cp\u003e1.495\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"34.387351778656125%\"\u003e\n \u003cp\u003e0.799\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"18.181818181818183%\"\u003e\n \u003cp\u003eFC3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"25.691699604743082%\"\u003e\n \u003cp\u003e5.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"21.73913043478261%\"\u003e\n \u003cp\u003e1.625\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"34.387351778656125%\"\u003e\n \u003cp\u003e0.709\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"18.181818181818183%\"\u003e\n \u003cp\u003eFC4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"25.691699604743082%\"\u003e\n \u003cp\u003e5.11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"21.73913043478261%\"\u003e\n \u003cp\u003e1.499\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"34.387351778656125%\"\u003e\n \u003cp\u003e0.713\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"18.181818181818183%\"\u003e\n \u003cp\u003eFC5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"25.691699604743082%\"\u003e\n \u003cp\u003e5.11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"21.73913043478261%\"\u003e\n \u003cp\u003e1.575\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"34.387351778656125%\"\u003e\n \u003cp\u003e0.734\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"5\" valign=\"top\" width=\"17.739403453689167%\"\u003e\n \u003cp\u003ePerformance Expectancy\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"7.221350078492936%\"\u003e\n \u003cp\u003ePE1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"10.204081632653061%\"\u003e\n \u003cp\u003e5.15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"8.634222919937205%\"\u003e\n \u003cp\u003e1.641\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"13.657770800627944%\"\u003e\n \u003cp\u003e0.823\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"5\" valign=\"top\" width=\"11.930926216640502%\"\u003e\n \u003cp\u003e0.891\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"5\" valign=\"top\" width=\"16.16954474097331%\"\u003e\n \u003cp\u003e0.893\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"5\" valign=\"top\" width=\"14.442700156985872%\"\u003e\n \u003cp\u003e0.625\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"18.181818181818183%\"\u003e\n \u003cp\u003ePE2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"25.691699604743082%\"\u003e\n \u003cp\u003e5.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"21.73913043478261%\"\u003e\n \u003cp\u003e1.558\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"34.387351778656125%\"\u003e\n \u003cp\u003e0.755\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"18.181818181818183%\"\u003e\n \u003cp\u003ePE3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"25.691699604743082%\"\u003e\n \u003cp\u003e5.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"21.73913043478261%\"\u003e\n \u003cp\u003e1.620\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"34.387351778656125%\"\u003e\n \u003cp\u003e0.722\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"18.181818181818183%\"\u003e\n \u003cp\u003ePE4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"25.691699604743082%\"\u003e\n \u003cp\u003e4.85\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"21.73913043478261%\"\u003e\n \u003cp\u003e1.583\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"34.387351778656125%\"\u003e\n \u003cp\u003e0.807\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"18.181818181818183%\"\u003e\n \u003cp\u003ePE5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"25.691699604743082%\"\u003e\n \u003cp\u003e5.09\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"21.73913043478261%\"\u003e\n \u003cp\u003e1.642\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"34.387351778656125%\"\u003e\n \u003cp\u003e0.84\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"6\" valign=\"top\" width=\"17.739403453689167%\"\u003e\n \u003cp\u003ePersonal Innovativeness\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"7.221350078492936%\"\u003e\n \u003cp\u003ePII1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"10.204081632653061%\"\u003e\n \u003cp\u003e4.86\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"8.634222919937205%\"\u003e\n \u003cp\u003e1.690\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"13.657770800627944%\"\u003e\n \u003cp\u003e0.79\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"6\" valign=\"top\" width=\"11.930926216640502%\"\u003e\n \u003cp\u003e0.882\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"6\" valign=\"top\" width=\"16.16954474097331%\"\u003e\n \u003cp\u003e0.881\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"6\" valign=\"top\" width=\"14.442700156985872%\"\u003e\n \u003cp\u003e0.554\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"18.181818181818183%\"\u003e\n \u003cp\u003ePII2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"25.691699604743082%\"\u003e\n \u003cp\u003e4.30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"21.73913043478261%\"\u003e\n \u003cp\u003e1.700\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"34.387351778656125%\"\u003e\n \u003cp\u003e0.665\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"18.181818181818183%\"\u003e\n \u003cp\u003ePII3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"25.691699604743082%\"\u003e\n \u003cp\u003e4.73\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"21.73913043478261%\"\u003e\n \u003cp\u003e1.675\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"34.387351778656125%\"\u003e\n \u003cp\u003e0.8\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"18.181818181818183%\"\u003e\n \u003cp\u003ePII4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"25.691699604743082%\"\u003e\n \u003cp\u003e4.63\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"21.73913043478261%\"\u003e\n \u003cp\u003e1.612\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"34.387351778656125%\"\u003e\n \u003cp\u003e0.695\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"18.181818181818183%\"\u003e\n \u003cp\u003ePII5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"25.691699604743082%\"\u003e\n \u003cp\u003e4.73\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"21.73913043478261%\"\u003e\n \u003cp\u003e1.592\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"34.387351778656125%\"\u003e\n \u003cp\u003e0.757\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"18.181818181818183%\"\u003e\n \u003cp\u003ePII6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"25.691699604743082%\"\u003e\n \u003cp\u003e4.90\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"21.73913043478261%\"\u003e\n \u003cp\u003e1.661\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"34.387351778656125%\"\u003e\n \u003cp\u003e0.749\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"6\" valign=\"top\" width=\"17.739403453689167%\"\u003e\n \u003cp\u003ePace of Innovation\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"7.221350078492936%\"\u003e\n \u003cp\u003ePOI1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"10.204081632653061%\"\u003e\n \u003cp\u003e4.85\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"8.634222919937205%\"\u003e\n \u003cp\u003e1.644\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"13.657770800627944%\"\u003e\n \u003cp\u003e0.821\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"6\" valign=\"top\" width=\"11.930926216640502%\"\u003e\n \u003cp\u003e0.918\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"6\" valign=\"top\" width=\"16.16954474097331%\"\u003e\n \u003cp\u003e0.918\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"6\" valign=\"top\" width=\"14.442700156985872%\"\u003e\n \u003cp\u003e0.652\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"18.181818181818183%\"\u003e\n \u003cp\u003ePOI2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"25.691699604743082%\"\u003e\n \u003cp\u003e4.77\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"21.73913043478261%\"\u003e\n \u003cp\u003e1.676\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"34.387351778656125%\"\u003e\n \u003cp\u003e0.772\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"18.181818181818183%\"\u003e\n \u003cp\u003ePOI3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"25.691699604743082%\"\u003e\n \u003cp\u003e4.59\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"21.73913043478261%\"\u003e\n \u003cp\u003e1.602\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"34.387351778656125%\"\u003e\n \u003cp\u003e0.786\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"18.181818181818183%\"\u003e\n \u003cp\u003ePOI4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"25.691699604743082%\"\u003e\n \u003cp\u003e4.74\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"21.73913043478261%\"\u003e\n \u003cp\u003e1.669\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"34.387351778656125%\"\u003e\n \u003cp\u003e0.818\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"18.181818181818183%\"\u003e\n \u003cp\u003ePOI5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"25.691699604743082%\"\u003e\n \u003cp\u003e4.66\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"21.73913043478261%\"\u003e\n \u003cp\u003e1.668\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"34.387351778656125%\"\u003e\n \u003cp\u003e0.805\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"18.181818181818183%\"\u003e\n \u003cp\u003ePOI6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"25.691699604743082%\"\u003e\n \u003cp\u003e4.68\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"21.73913043478261%\"\u003e\n \u003cp\u003e1.636\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"34.387351778656125%\"\u003e\n \u003cp\u003e0.841\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"4\" valign=\"top\" width=\"17.739403453689167%\"\u003e\n \u003cp\u003eIntention to Recommend\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"7.221350078492936%\"\u003e\n \u003cp\u003eRI1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"10.204081632653061%\"\u003e\n \u003cp\u003e5.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"8.634222919937205%\"\u003e\n \u003cp\u003e1.528\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"13.657770800627944%\"\u003e\n \u003cp\u003e0.848\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"4\" valign=\"top\" width=\"11.930926216640502%\"\u003e\n \u003cp\u003e0.904\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"4\" valign=\"top\" width=\"16.16954474097331%\"\u003e\n \u003cp\u003e0.904\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"4\" valign=\"top\" width=\"14.442700156985872%\"\u003e\n \u003cp\u003e0.701\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"18.181818181818183%\"\u003e\n \u003cp\u003eRI2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"25.691699604743082%\"\u003e\n \u003cp\u003e4.96\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"21.73913043478261%\"\u003e\n \u003cp\u003e1.593\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"34.387351778656125%\"\u003e\n \u003cp\u003e0.826\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"18.181818181818183%\"\u003e\n \u003cp\u003eRI3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"25.691699604743082%\"\u003e\n \u003cp\u003e5.07\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"21.73913043478261%\"\u003e\n \u003cp\u003e1.529\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"34.387351778656125%\"\u003e\n \u003cp\u003e0.821\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"18.181818181818183%\"\u003e\n \u003cp\u003eRI4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"25.691699604743082%\"\u003e\n \u003cp\u003e5.17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"21.73913043478261%\"\u003e\n \u003cp\u003e1.568\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"34.387351778656125%\"\u003e\n \u003cp\u003e0.855\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"5\" valign=\"top\" width=\"17.739403453689167%\"\u003e\n \u003cp\u003eSatisfaction\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"7.221350078492936%\"\u003e\n \u003cp\u003eSAT1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"10.204081632653061%\"\u003e\n \u003cp\u003e5.13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"8.634222919937205%\"\u003e\n \u003cp\u003e1.498\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"13.657770800627944%\"\u003e\n \u003cp\u003e0.83\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"5\" valign=\"top\" width=\"11.930926216640502%\"\u003e\n \u003cp\u003e0.892\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"5\" valign=\"top\" width=\"16.16954474097331%\"\u003e\n \u003cp\u003e0.893\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"5\" valign=\"top\" width=\"14.442700156985872%\"\u003e\n \u003cp\u003e0.625\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"18.181818181818183%\"\u003e\n \u003cp\u003eSAT2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"25.691699604743082%\"\u003e\n \u003cp\u003e5.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"21.73913043478261%\"\u003e\n \u003cp\u003e1.560\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"34.387351778656125%\"\u003e\n \u003cp\u003e0.72\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"18.181818181818183%\"\u003e\n \u003cp\u003eSAT3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"25.691699604743082%\"\u003e\n \u003cp\u003e4.96\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"21.73913043478261%\"\u003e\n \u003cp\u003e1.519\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"34.387351778656125%\"\u003e\n \u003cp\u003e0.801\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"18.181818181818183%\"\u003e\n \u003cp\u003eSAT4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"25.691699604743082%\"\u003e\n \u003cp\u003e5.13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"21.73913043478261%\"\u003e\n \u003cp\u003e1.519\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"34.387351778656125%\"\u003e\n \u003cp\u003e0.775\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"18.181818181818183%\"\u003e\n \u003cp\u003eSAT5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"25.691699604743082%\"\u003e\n \u003cp\u003e5.10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"21.73913043478261%\"\u003e\n \u003cp\u003e1.589\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"34.387351778656125%\"\u003e\n \u003cp\u003e0.823\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"5\" valign=\"top\" width=\"17.739403453689167%\"\u003e\n \u003cp\u003eSocial Influence\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"7.221350078492936%\"\u003e\n \u003cp\u003eSI1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"10.204081632653061%\"\u003e\n \u003cp\u003e4.67\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"8.634222919937205%\"\u003e\n \u003cp\u003e1.670\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"13.657770800627944%\"\u003e\n \u003cp\u003e0.853\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"5\" valign=\"top\" width=\"11.930926216640502%\"\u003e\n \u003cp\u003e0.912\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"5\" valign=\"top\" width=\"16.16954474097331%\"\u003e\n \u003cp\u003e0.912\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"5\" valign=\"top\" width=\"14.442700156985872%\"\u003e\n \u003cp\u003e0.676\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"18.181818181818183%\"\u003e\n \u003cp\u003eSI2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"25.691699604743082%\"\u003e\n \u003cp\u003e4.57\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"21.73913043478261%\"\u003e\n \u003cp\u003e1.640\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"34.387351778656125%\"\u003e\n \u003cp\u003e0.805\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"18.181818181818183%\"\u003e\n \u003cp\u003eSI3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"25.691699604743082%\"\u003e\n \u003cp\u003e4.67\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"21.73913043478261%\"\u003e\n \u003cp\u003e1.655\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"34.387351778656125%\"\u003e\n \u003cp\u003e0.915\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"18.181818181818183%\"\u003e\n \u003cp\u003eSI4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"25.691699604743082%\"\u003e\n \u003cp\u003e4.98\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"21.73913043478261%\"\u003e\n \u003cp\u003e1.657\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"34.387351778656125%\"\u003e\n \u003cp\u003e0.785\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"18.181818181818183%\"\u003e\n \u003cp\u003eSI5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"25.691699604743082%\"\u003e\n \u003cp\u003e4.57\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"21.73913043478261%\"\u003e\n \u003cp\u003e1.677\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"34.387351778656125%\"\u003e\n \u003cp\u003e0.742\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eDiscriminant validity - The degree to which assessment tools are uncorrelated with other different constructs is known as discriminant validity. If a construct\u0026apos;s square roots of AVE are higher than its correlation coefficient with any other construct, discriminant validity is demonstrated [75]. The constructs\u0026apos; strong discriminant validity is demonstrated in Table 3.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 3: Discriminant validity\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"0\" cellpadding=\"0\" cellspacing=\"0\" width=\"100%\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"10%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\"\u003e\n \u003cp\u003eCI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\"\u003e\n \u003cp\u003eEE\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\"\u003e\n \u003cp\u003eFC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\"\u003e\n \u003cp\u003eRI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\"\u003e\n \u003cp\u003ePOI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\"\u003e\n \u003cp\u003ePE\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\"\u003e\n \u003cp\u003ePI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\"\u003e\n \u003cp\u003eSAT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\"\u003e\n \u003cp\u003eSI\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"10%\"\u003e\n \u003cp\u003eCI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.797\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"10%\"\u003e\n \u003cp\u003eEE\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\"\u003e\n \u003cp\u003e0.624\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.815\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"10%\"\u003e\n \u003cp\u003eFC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\"\u003e\n \u003cp\u003e0.662\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\"\u003e\n \u003cp\u003e0.685\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.749\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"10%\"\u003e\n \u003cp\u003eRI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\"\u003e\n \u003cp\u003e0.761\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\"\u003e\n \u003cp\u003e0.569\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\"\u003e\n \u003cp\u003e0.567\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.837\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"10%\"\u003e\n \u003cp\u003ePOI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\"\u003e\n \u003cp\u003e0.75\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\"\u003e\n \u003cp\u003e0.802\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\"\u003e\n \u003cp\u003e0.657\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\"\u003e\n \u003cp\u003e0.66\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.807\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"10%\"\u003e\n \u003cp\u003ePE\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\"\u003e\n \u003cp\u003e0.518\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\"\u003e\n \u003cp\u003e0.647\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\"\u003e\n \u003cp\u003e0.64\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\"\u003e\n \u003cp\u003e0.512\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\"\u003e\n \u003cp\u003e0.624\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.791\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"10%\"\u003e\n \u003cp\u003ePI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\"\u003e\n \u003cp\u003e0.677\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\"\u003e\n \u003cp\u003e0.605\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\"\u003e\n \u003cp\u003e0.601\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\"\u003e\n \u003cp\u003e0.599\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\"\u003e\n \u003cp\u003e0.632\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\"\u003e\n \u003cp\u003e0.561\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.744\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"10%\"\u003e\n \u003cp\u003eSAT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\"\u003e\n \u003cp\u003e0.696\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\"\u003e\n \u003cp\u003e0.638\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\"\u003e\n \u003cp\u003e0.644\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\"\u003e\n \u003cp\u003e0.594\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\"\u003e\n \u003cp\u003e0.66\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\"\u003e\n \u003cp\u003e0.643\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\"\u003e\n \u003cp\u003e0.578\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.791\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"10%\"\u003e\n \u003cp\u003eSI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\"\u003e\n \u003cp\u003e0.451\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\"\u003e\n \u003cp\u003e0.633\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\"\u003e\n \u003cp\u003e0.61\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\"\u003e\n \u003cp\u003e0.492\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\"\u003e\n \u003cp\u003e0.559\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\"\u003e\n \u003cp\u003e0.543\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\"\u003e\n \u003cp\u003e0.521\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\"\u003e\n \u003cp\u003e0.505\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.822\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cstrong\u003eStructural Model Analysis\u003c/strong\u003e - Table 4 and Figure 2 display the findings of the hypothesis testing, including standardised path coefficients and the percentage of variance explained. Results demonstrate that, with the exception of social influence, all hypotheses were supported (H3). The statistical significance of the association between performance expectations and satisfaction supports hypothesis H1. The findings demonstrate the importance of EE, FC and PI on users\u0026apos; satisfaction with UPI apps. H1, H2, H4, and H5 were supported as a result of this study\u0026apos;s identification of the impacts of antecedents on satisfaction. Additionally, this study discovered that H7 was supported and that satisfaction significantly influences continuing usage intention. This study also confirmed the favourable association between continuing intention and intention to recommend. In addition, as displayed on Table 4 and Figure 2 we found effect of personal innovativeness and pace of innovation on continued usage intention with UPI. Hence, H6 and H8 were supported.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e5000 bootstrap samples, which have been shown to be more accurate than the Sobel test [73, 77], were used in this investigation to investigate the mediating model. The estimates of the estimated mediation effects have a 95% confidence interval that excludes zero, as shown in Table 5, and all indirect effects are significant [27]. As a result, the bootstrapping findings demonstrated that the mediation effects of satisfaction were significant.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 4:\u0026nbsp;\u003c/strong\u003eResults of the Hypotheses Testing.\u003c/p\u003e\n\u003ctable border=\"1\" cellpadding=\"0\" cellspacing=\"0\" width=\"99%\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"10.309278350515465%\"\u003e\n \u003cp\u003eHypothesis\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"12.371134020618557%\"\u003e\n \u003cp\u003eEndogenous Construct\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"13.402061855670103%\"\u003e\n \u003cp\u003eExogeneous Construct\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"15.463917525773196%\"\u003e\n \u003cp\u003ePath Coefficients\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"16.49484536082474%\"\u003e\n \u003cp\u003eStandard Deviation\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"9.278350515463918%\"\u003e\n \u003cp\u003eT Stats\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"9.278350515463918%\"\u003e\n \u003cp\u003eR Square\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"13.402061855670103%\"\u003e\n \u003cp\u003eRemark\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"10.309278350515465%\"\u003e\n \u003cp\u003eH1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"5\" valign=\"top\" width=\"12.371134020618557%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eSAT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"13.402061855670103%\"\u003e\n \u003cp\u003ePE\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"15.463917525773196%\"\u003e\n \u003cp\u003e0.247\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"16.49484536082474%\"\u003e\n \u003cp\u003e0.04\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"9.278350515463918%\"\u003e\n \u003cp\u003e6.114**\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"5\" valign=\"top\" width=\"9.278350515463918%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e47.1%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"13.402061855670103%\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; Supported\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"13.157894736842104%\"\u003e\n \u003cp\u003eH2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"17.105263157894736%\"\u003e\n \u003cp\u003eEE\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"19.736842105263158%\"\u003e\n \u003cp\u003e0.203\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"21.05263157894737%\"\u003e\n \u003cp\u003e0.034\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"11.842105263157896%\"\u003e\n \u003cp\u003e5.889**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"17.105263157894736%\"\u003e\n \u003cp\u003eSupported\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"13.157894736842104%\"\u003e\n \u003cp\u003eH3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"17.105263157894736%\"\u003e\n \u003cp\u003eSI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"19.736842105263158%\"\u003e\n \u003cp\u003e0.035\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"21.05263157894737%\"\u003e\n \u003cp\u003e0.037\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"11.842105263157896%\"\u003e\n \u003cp\u003e0.934\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"17.105263157894736%\"\u003e\n \u003cp\u003eNot Supported\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"13.157894736842104%\"\u003e\n \u003cp\u003eH4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"17.105263157894736%\"\u003e\n \u003cp\u003eFC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"19.736842105263158%\"\u003e\n \u003cp\u003e0.202\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"21.05263157894737%\"\u003e\n \u003cp\u003e0.038\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"11.842105263157896%\"\u003e\n \u003cp\u003e5.296**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"17.105263157894736%\"\u003e\n \u003cp\u003e\u0026nbsp;Supported\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"13.157894736842104%\"\u003e\n \u003cp\u003eH5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"17.105263157894736%\"\u003e\n \u003cp\u003ePI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"19.736842105263158%\"\u003e\n \u003cp\u003e0.159\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"21.05263157894737%\"\u003e\n \u003cp\u003e0.035\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"11.842105263157896%\"\u003e\n \u003cp\u003e4.485**\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"17.105263157894736%\"\u003e\n \u003cp\u003eSupported\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"10.309278350515465%\"\u003e\n \u003cp\u003eH6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"4\" valign=\"top\" width=\"12.371134020618557%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"13.402061855670103%\"\u003e\n \u003cp\u003ePI\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"15.463917525773196%\"\u003e\n \u003cp\u003e0.132\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"16.49484536082474%\"\u003e\n \u003cp\u003e0.041\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"9.278350515463918%\"\u003e\n \u003cp\u003e3.256\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"4\" valign=\"bottom\" width=\"9.278350515463918%\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp;48.0%\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"13.402061855670103%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;Supported\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"13.157894736842104%\"\u003e\n \u003cp\u003eH8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"17.105263157894736%\"\u003e\n \u003cp\u003ePOI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"19.736842105263158%\"\u003e\n \u003cp\u003e0.261\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"21.05263157894737%\"\u003e\n \u003cp\u003e0.047\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"11.842105263157896%\"\u003e\n \u003cp\u003e5.551**\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"17.105263157894736%\"\u003e\n \u003cp\u003eSupported\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"13.157894736842104%\"\u003e\n \u003cp\u003eH7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"17.105263157894736%\"\u003e\n \u003cp\u003eSAT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"19.736842105263158%\"\u003e\n \u003cp\u003e\u0026nbsp; 0.144\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"21.05263157894737%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0.039\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"11.842105263157896%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e3.655**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"17.105263157894736%\"\u003e\n \u003cp\u003eSupported\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"13.157894736842104%\"\u003e\n \u003cp\u003eH9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"17.105263157894736%\"\u003e\n \u003cp\u003eIR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"19.736842105263158%\"\u003e\n \u003cp\u003e0.693\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"21.05263157894737%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0.026\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"11.842105263157896%\"\u003e\n \u003cp\u003e26.878**\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"17.105263157894736%\"\u003e\n \u003cp\u003eSupported\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cstrong\u003eTable 5: \u0026nbsp;\u003c/strong\u003eBootstrapping analysis of the mediation effect of satisfaction.\u003c/p\u003e\n\u003cdiv align=\"center\"\u003e\n \u003ctable border=\"1\" cellpadding=\"0\" cellspacing=\"0\" width=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"15.46218487394958%\"\u003e\n \u003cp\u003e\u003cstrong\u003eType of Effect\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"20.168067226890756%\"\u003e\n \u003cp\u003e\u003cstrong\u003eRelationship\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"20.672268907563026%\"\u003e\n \u003cp\u003e\u003cstrong\u003eStandardized Path Coefficient\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"17.478991596638654%\"\u003e\n \u003cp\u003e\u003cstrong\u003eP value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"26.218487394957982%\"\u003e\n \u003cp\u003e\u003cstrong\u003eRemarks\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"15.46218487394958%\"\u003e\n \u003cp\u003eTotal Effect\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"20.168067226890756%\"\u003e\n \u003col\u003e\n \u003cli\u003ePE\u003c/li\u003e\n \u003cli\u003eEE\u003c/li\u003e\n \u003cli\u003eSI\u003c/li\u003e\n \u003cli\u003eFC\u003c/li\u003e\n \u003cli\u003ePI\u003c/li\u003e\n \u003c/ol\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"20.672268907563026%\"\u003e\n \u003cp\u003e0.518\u003c/p\u003e\n \u003cp\u003e0.626\u003c/p\u003e\n \u003cp\u003e0.452\u003c/p\u003e\n \u003cp\u003e0.664\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;0.609\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"17.478991596638654%\"\u003e\n \u003cp\u003e12.974***\u003c/p\u003e\n \u003cp\u003e16.748***\u003c/p\u003e\n \u003cp\u003e11.618***\u003c/p\u003e\n \u003cp\u003e19.844***\u003c/p\u003e\n \u003cp\u003e18.750***\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"26.218487394957982%\"\u003e\n \u003cp\u003eSignificant total effect\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"15.46218487394958%\"\u003e\n \u003cp\u003eIndirect Effect\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"20.168067226890756%\"\u003e\n \u003col\u003e\n \u003cli\u003ePE\u003c/li\u003e\n \u003cli\u003eEE\u003c/li\u003e\n \u003cli\u003eSI\u003c/li\u003e\n \u003cli\u003eFC\u003c/li\u003e\n \u003cli\u003ePI\u003c/li\u003e\n \u003c/ol\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"20.672268907563026%\"\u003e\n \u003cp\u003e0.398\u003c/p\u003e\n \u003cp\u003e0.320\u003c/p\u003e\n \u003cp\u003e0.317\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;0.295\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;0.221\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"17.478991596638654%\"\u003e\n \u003cp\u003e10.599***\u003c/p\u003e\n \u003cp\u003e9.142***\u003c/p\u003e\n \u003cp\u003e8.75***\u003c/p\u003e\n \u003cp\u003e8.321***\u003c/p\u003e\n \u003cp\u003e8.445***\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"26.218487394957982%\"\u003e\n \u003cp\u003eSignificant indirect effect found\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"15.46218487394958%\"\u003e\n \u003cp\u003eDirect Effect\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"20.168067226890756%\"\u003e\n \u003col\u003e\n \u003cli\u003ePE\u003c/li\u003e\n \u003cli\u003eEE\u003c/li\u003e\n \u003cli\u003eSI\u003c/li\u003e\n \u003cli\u003eFC\u003c/li\u003e\n \u003cli\u003ePI\u003c/li\u003e\n \u003c/ol\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"20.672268907563026%\"\u003e\n \u003cp\u003e0.120\u003c/p\u003e\n \u003cp\u003e0.306\u003c/p\u003e\n \u003cp\u003e0.135\u003c/p\u003e\n \u003cp\u003e0.369\u003c/p\u003e\n \u003cp\u003e0.388\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"17.478991596638654%\"\u003e\n \u003cp\u003e2.630***\u003c/p\u003e\n \u003cp\u003e6.211***\u003c/p\u003e\n \u003cp\u003e3.003***\u003c/p\u003e\n \u003cp\u003e7.164***\u003c/p\u003e\n \u003cp\u003e9.418***\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"26.218487394957982%\"\u003e\n \u003cp\u003eSignificant direct effect found\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n"},{"header":"4. Discussion","content":"\u003cp\u003eThe objective of the research is to explore the impact of users continuance intentions of UPI usage from the perspective of extension \u0026nbsp;of the UTAUT model with personal innovativeness and pace of innovation. Our results proved that performance expectancy, effort expectancy, social influence, facilitating conditions, personal innovativeness have positively and significantly influenced the users continuance intentions through the mediation role of satisfaction\u003c/p\u003e\n\u003cp\u003eMoreover, users\u0026rsquo; continuance intention positively affects the intention to recommend the UPI apps. \u0026nbsp;It is also found identified that personal innovativeness of using UPI increases the significant effect on continuance intention. This study identifies that personal innovativeness \u0026nbsp;of using UPI \u0026nbsp; directly affects users\u0026rsquo; continuous intentions and users should be try out to use new UPI features. Personal innovativeness described that personal trait are the significant factors of continuance intentions towards using UPI payments system. Pace of innovation in this study affects the continuance intentions of UPI users. Pace of innovation is repetitive because it is continuously committed with new emerging innovations. The empirical findings of this study demonstrate that all predictions have been supported, and the extended UTAUT is a crucial theoretical model for estimating the future use of UPI.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ePractical implications of the study\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study aims to explore the influences of users\u0026rsquo; continued intentions of UPI usage from the perspective of UTAUT. The majority of studies focused on digital payments, as adoption of digital payments, as continuation and recommendation intentions of UPI users, has not been explored in the Indian context. The results of the study will be vital for UPI service providers and banking institutions to provide different services to their users. The UPI service providers should focus on performance and effort expectations, facilitating conditions that enhance user satisfaction. To increase the continued intention of using UPI, service providers must pay attention to making and communicating useful and non-useful benefits of new features of UPI. They must emphasize the useful aspect of new UPI apps, features, etc. promoting or advertising new products of UPI can create more opportunities for users to experience new things which can increase their continuance intention towards using UPI. The UPI service providers must provide advanced technology and infrastructure on the UPI platform. Constant professional growth and progressive training are essential for successful and well-organized use of UPI services.\u0026nbsp;\u003c/p\u003e"},{"header":"5. Theoretical Implications Of The Study","content":"\u003cp\u003eThe UTAUT model has been used with additional variables personal innovativeness, pace on innovation, continuance intentions, and intention to recommend. A comprehensive study framework has been drawn representing relationship between user satisfaction and continuance intention. The proposed comprehensive research framework is empirically tested in the context of UPI. The findings provide evidence supporting the validity and reliability of the framework. Therefore, it could be claimed that this comprehensive research framework can be used as a research tool in examining determinant factors in decision to continue and recommend in technological innovations. This study investigates the impact of performance expectancy, effort expectancy, social influence, facilitating conditions, and personal innovativeness on users\u0026rsquo; satisfaction. It examines the influence of personal innovativeness, and pace of innovation on continued intentions. It also examined the influence of performance expectancy, effort expectancy, social influence, facilitating conditions, and personal innovativeness on the continuance intentions of the UPI system through the mediating role of user satisfaction. The study has used the validated instrument which will be extremely useful for future researchers in understanding the users' retention and recommendation intentions\u003c/p\u003e"},{"header":"6. Conclusion","content":"\u003cp\u003eIn order to investigate the effects of factors on the continuing use of UPI, we offer a research model based on the suitable theoretical model that adds two factors, personal innovativeness and pace on innovation, to the original UTAUT. Our findings demonstrate that, via the mediating effect of satisfaction, users' intentions to continue using a product or service are significantly positively impacted by performance expectations, effort expectations, social influence, facilitating conditions, and individual inventiveness. Additionally, consumers' intention to continue around influences their intention to recommend.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n \u003cli\u003e\u003cspan\u003eAgrebi, S., and J. 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Factors Influencing Continued Usage Behavior on Mobile Health Applications. In \u003cem\u003eHealthcare\u003c/em\u003e (Vol. 10, No. 2, p. 208). MDPI.\u003c/span\u003e\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Digital payments, UPI, Satisfaction, UTAUT, personal innovativeness, Continuance Intention ","lastPublishedDoi":"10.21203/rs.3.rs-1966920/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-1966920/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eThe with development of smartphones, technology has played a greater role in recent years, drastically altering how we trade in daily life. Now that all payments and transactions take place online, life has gotten more simpler. This accelerated the development of the UPI platform. The goal of the current study is to gauge user satisfaction and continuance intentions\u0026nbsp;for UPI. This study develops a research model using personal innovativeness and pace\u0026nbsp;of innovation to predict the continuance intention toward UPI based on the Unified theory\u0026nbsp;of acceptance and use of technology\u0026nbsp;(UTAUT). We conduct an online survey to collect data from participants who have used UPI. The research model is tested in this study utilising a partial least squares structural equation model with 651 valid replies. According to our findings, satisfaction with UPI serves as a mediator between antecedents and continuing intentions by positively affecting them. This paper explores theoretical implications for the UTAUT and offers an insight of how to manage UPI in India on a practical level.\u003c/p\u003e","manuscriptTitle":"Factors Influencing Continuance Intentions of Unified Payment Interface (UPI) users","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2022-08-19 17:54:34","doi":"10.21203/rs.3.rs-1966920/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"7a74f188-745c-4455-9f02-57488afdd77c","owner":[],"postedDate":"August 19th, 2022","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2022-09-13T09:29:18+00:00","versionOfRecord":[],"versionCreatedAt":"2022-08-19 17:54:34","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-1966920","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-1966920","identity":"rs-1966920","version":["v1"]},"buildId":"rHA-KDH7Qsr4HCuvH75dn","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}