Wireless Pers CommunDOI 10.1007/s11277-013-1596-8
An Empirical Examination of Initial Trust in MobilePayment
Tao Zhou
© Springer Science+Business Media New York 2014
Abstract Due to the high uncertainty and perceived risk associated with using mobile pay-ment, it is critical to building users’ initial trust in order to facilitate their adoption and usage.Drawing on both perspectives of self-perception-based and transference-based factors, thisresearch examined initial trust in mobile payment. Self-perception-based factors includeubiquitous connection and effort expectancy, whereas transference-based factors includestructural assurance and trust in online payment. The results indicated that both perspectivesof factors affect initial trust, which further affects performance expectancy and usage inten-tion. Thus, service providers need to build users’ initial trust in order to facilitate their usageof mobile payment.
Keywords Mobile payment · Initial trust · Structural assurance · Effort expectancy
1 Introduction
Mobile internet has been developing rapidly in the world. Especially, the application of thirdgeneration (3G) communication technologies has triggered mobile internet development.According to a report issued by China Internet Network Information Center (CNNIC) in July2013, the number of mobile internet users in China has exceeded 464 million, accountingfor 78.5 % of its internet population (591 million) [7]. Faced with the great market, serviceproviders have released a variety of mobile services, such as mobile instant messaging,mobile search, mobile games and mobile payment. These services can be categorized into fourtypes: communication, information, entertainment and transaction [13]. As a basic transactionapplication supporting mobile business, mobile payment has received considerable attentionfrom enterprises. For example, Alipay, which is the largest online payment service providerin China, has released mobile Alipay. Telecommunication service providers such as ChinaMobile have also developed mobile payment products, which enable users to pay public busfees and buy cinema tickets via their mobile phones. However, although service providers
T. Zhou (B)School of Management, Hangzhou Dianzi University, Hangzhou 310018, People’s Republic of Chinae-mail: [email protected]
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have invested great effort and resource on mobile payment, the user adoption rate is relativelylow. For example, only 17.1 % of mobile internet users have ever used mobile payment inChina [7]. In US, this figure is 12 % [34]. Service providers need to understand the factoraffecting user behavior and adopt effective measures to facilitate user adoption and usage ofmobile payment.
Mobile payment means that users access information and services, such as checkingbalance, transferring money and conducting payment via mobile devices such as mobilephones. Compared to online payment, a main advantage of mobile payment is ubiquity.That is, with the help of mobile devices and networks, users have been freed from temporaland spatial constraints. They can conduct mobile payment at anytime from anywhere. Thisprovides great convenience and value to users, which may facilitate their adoption of mobilepayment. However, mobile payment also involves great uncertainty and risk. For example,mobile networks are vulnerable to hacker attack and information interception. Mobile devicesmay be also infected by viruses and Trojan horses. These problems may increase users’concern on payment security and decrease their usage intention. They need to build trust inorder to mitigate their perceived risk and facilitate their usage of mobile payment.
In this research, we are mainly concerned with initial trust that users develop during thefirst interaction with mobile payment systems. Building initial trust is critical to mobile pay-ment user adoption. On one hand, mobile payment is a novel service to most users. Whenthese users plan to use mobile payment, they may perceive great uncertainty and risk due tothe lack of usage experience. They need to engender enough trust to alleviate this perceivedrisk. On the other hand, the switching cost is low. Users can easily switch from a serviceprovider to an alternative one. Thus, service providers also need to build users’ initial trustin order to retain them.
Extant studies have used information systems theories such as the technology accep-tance model (TAM) and innovation diffusion theory (IDT) to examine mobile payment userbehavior. Technological perceptions such as perceived usefulness and relative advantage areidentified to affect usage intention of mobile payment [16,28,36]. However, these studieshave seldom examined the effect of initial trust on user adoption of mobile payment. Asnoted earlier, due to the high perceived risk and low switching cost, building users’ initialtrust is critical to their usage behavior. Thus, it is necessary to examine initial trust in mobilepayment. We investigated two categories of initial trust determinants which include self-perception-based and transference-based factors. Users’ initial trust may not only developfrom their own perceptions, but also be transferred from other parties and channels. In thisresearch, self-perception-based factors include ubiquitous connection and effort expectancy,whereas transference-based factors include structural assurance and trust in online payment,which reflect institutional trust and cross-channel trust transference, respectively.
The rest of this paper is organized as follows. We review relevant literature on mobilepayment user adoption and initial trust in the next section. Then we develop research modeland hypotheses in Sect. 3. Section 4 reports instrument development and data collection. Wepresent results in Sect. 5 and discuss these results in Sect. 6. Section 7 presents the theoreticaland managerial implications. We conclude the paper in Sect. 8.
2 Literature Review
2.1 Mobile Payment User Adoption
As an emerging service, mobile payment has not received wide adoption among users. Thus,researchers have tried to identify the factors affecting user behavior. They have often drawn
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on information systems theories such as TAM and IDT as theoretical bases. Kim et al. [16]suggested that individual differences and system characteristics affect perceived usefulnessand ease of use, both of which in turn affect Korean users’ intention to use mobile payment.Individual differences include innovativeness and mobile payment knowledge, whereas sys-tem characteristics include mobility, reachability, compatibility and convenience. Mallat [28]conducted a qualitative study and noted that relative advantage, complexity, compatibility,costs and trust affect user adoption of mobile payment in Finland. Schierz et al. [36] statedthat compatibility, perceived usefulness, mobility and subjective norm affect user attitude,which further affects German users’ intention to use mobile payment.
In addition to technological perceptions such as perceived usefulness, trust also has asignificant effect on mobile payment user behavior. Chandra et al. [5] noted that both ser-vice provider characteristics and mobile technology characteristics affect users’ trust, whichfurther affects their adoption of mobile payment through perceived usefulness and perceivedease of use in Singapore. Service provider characteristics include reputation and perceivedopportunism, whereas mobile technology characteristics include perceived environmentalrisk and structural assurance. Shin [37] noted that perceived ease of use, perceived useful-ness, trust and perceived risk affect Korean users’ adoption of mobile payment.
2.2 Initial Trust
Trust reflects a willingness to be in vulnerability based on the positive expectation towardanother party’s future behavior [29]. Trust often includes three dimensions: ability, integrityand benevolence [15,39]. Ability means that service providers have the knowledge and exper-tise necessary to fulfill their tasks. Integrity means that service providers keep their promisesand do not deceive users. Benevolence means that service providers are concerned with users’interests, not just their own benefits.
Due to its significant role, trust has received extensive consideration in the informationsystems research [3], especially in the e-commerce context, which involves great uncertaintyand risk. Initial trust has also been attached importance by researchers. Various factors areidentified to affect initial trust. The first category of factors is related to website characteristics.Users may rely on their perceptions of website to form their initial trust. Website qualityis a significant determinant of initial trust [25]. Other factors such as information quality,site appeal and usability also affect initial trust [12,31]. In addition, both factors of TAMincluding perceived usefulness and ease of use have effects on initial trust [4,6]. The secondcategory of factors is related to company. Reputation is a strong factor affecting initial trust[9,22]. The third category of factors is related to user. Trust propensity, which reflects anatural tendency, has a significant effect on initial trust [18]. The fourth category of factors isrelated to third parties. Users may transfer their trust in third parties to websites. These trustdeterminants include portal affiliation, peer endorsement [38], web assurance seals [14], andbrand association [8].
3 Research Model and Hypotheses
3.1 Self-perception-Based Factors
Ubiquitous connection means that users can obtain ubiquitous information and services.This means a challenge for service providers as mobile networks have limited bandwidth andunstable connections. Users may encounter slow responses and service interruption under
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some circumstances. If users encounter these problems during the first interaction with mobilepayment systems, they may feel that service providers lack enough ability to offer qualityservices to them. This may decrease their trust. On the other hand, online payment oftenrequires users to sit before desktop computers. Mobile payment frees users from temporaland spatial constraints and enables them to conduct payment at anytime from anywhere.This brings a positive utility to users and may enhance their performance expectancy. Kimet al. [16] also suggests that mobility affects perceived usefulness (similar to performanceexpectancy) of mobile payment. Thus, we suggest,
H1: Ubiquitous connection positively affects initial trust in mobile payment.H2: Ubiquitous connection positively affects performance expectancy.
Effort expectancy reflects the difficulty of using mobile payment. When users find mobilepayment systems difficult to use, they may feel that service providers have not investedeffort and resources on offering an easy-to-use system to them. This may lower their trustin service providers. Extant research has identified the effect of perceived ease of use (sim-ilar to effort expectancy) on mobile user trust [23,24]. In addition, effort expectancy mayaffect performance expectancy. Users may not expect to acquire positive utility from using adifficult-to-use system.
H3: Effort expectancy positively affects initial trust in mobile payment.H4: Effort expectancy positively affects performance expectancy.
3.2 Transference-Based Factors
Structural assurance reflects that mobile internet has technological and legal structures toensure payment security. Structural assurance represents an institution-based mechanism,which can help build user trust and alleviate perceived risk [33]. According to trust transfer-ence [40], users may transfer their trust in these structures to mobile payment systems. Thatis, users believe that mobile payment systems that adopted these technological and legalstructures can guarantee their payment security. Kim et al. [17] also found that structuralassurance has a strong effect on user trust in mobile banking. In addition, structural assur-ance may affect performance expectancy. When users perceive that there exist technologicalstructures to ensure security, they may form a positive expectation toward future perfor-mance. Otherwise, they may doubt payment security, which may lower their performanceexpectation.
H5: Structural assurance positively affects initial trust in mobile payment.H6: Structural assurance positively affects performance expectancy.
Trust in online payment reflects user beliefs in the trustworthiness of online paymentsystems. Compared to mobile payment that represents an emerging service, online paymentis very popular among users. Thus, users may transfer their trust in online payment systemsto the mobile payment systems belonging to the same brand. Extant research has noted thatoffline trust affects online trust [19]. In this research, we propose that online trust can be alsotransferred to mobile trust. In addition, online trust may also affect performance expectancy.When users have developed trust in online payment systems, they may also expect that mobilepayment systems can offer quality services to them as both belong to the same brand. Thus,we suggest,
H7: Trust in online payment positively affects initial trust in mobile payment.H8: Trust in online payment positively affects performance expectancy.
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Ubiquitous connection
Effort expectancy
Initial trust in mobile payment
Usage intention
Self-perception based
Transferencebased
Performance expectancy
Structural assurance
Trust in online payment
Fig. 1 Research model
3.3 Initial Trust, Performance Expectancy and Usage Intention
Initial trust may affect performance expectancy. Trust provides a guarantee that users obtainpositive results in future [10]. Trust enables users to believe that service providers have enoughability and integrity to offer quality services to them. Extant research has identified the effectof trust on perceived usefulness [26,42,45]. Consistent with these studies, we propose,
H9: Initial trust in mobile payment positively affects performance expectancy.
Initial trust and performance expectancy may affect usage intention. Both factors asenablers may help facilitate user adoption and usage intention. According to the theory ofplanned behavior [1], trust and performance expectancy as user beliefs may affect behavioralintention. Numerous studies have identified the effects of trust and performance expectancyon user behavioral intention [3,43,44]. Thus, we propose,
H10: Initial trust in mobile payment positively affects usage intention.H11: Performance expectancy positively affects usage intention.
Figure 1 presents the research model.
4 Method
4.1 Instrument Development
The research model includes seven factors. Each factor was measured with multiple items. Allitems were adapted from extant literature to improve content validity [41]. These items werefirst translated into Chinese by a researcher. Then another researcher translated them backinto English to ensure consistency. When the instrument was developed, it was tested amongfive users that had mobile payment usage experience. Then according to their comments, werevised some items to improve the clarity and understandability. The final items and theirsources are listed in “Appendix”.
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Items of ubiquitous connection were adapted from Lee [21] to reflect that users can conductmobile payment at anytime from anywhere. Items of effort expectancy and performanceexpectancy were adapted from Venkatesh et al. [43]. Items of effort expectancy measurethe difficulty of learning to use and skillfully using mobile payment. Items of performanceexpectancy reflect the improvement of efficiency and productivity associated with usingmobile payment. Items of structural assurance were adapted from McKnight et al. [30] toreflect that mobile internet has enough technological and legal structures to ensure paymentsecurity. Items of trust in online payment and initial trust in mobile payment were adaptedfrom Kim et al.[17] to reflect that online payment and mobile payment systems provideaccurate, reliable and safe services. Items of usage intention were adapted from Lee [21] tomeasure user intention to use and continue using mobile payment.
4.2 Data Collection
Data were collected at two service outlets of China Mobile, which is the largest mobile serviceprovider in China. The service outlets were located in an eastern China city, where mobileinternet is relatively better developed than other regions. We contacted users and inquiredwhether they had mobile payment usage experience. Then we asked those with negativeanswers to experience mobile payment via the phones offered by us. We had installed mobilepayment software in these phones in advance. Users can conduct payment, transfer moneyand check balance and transaction records. To ensure that users had actually experiencedmobile payment, we told them to conduct a low-value payment. Then we asked those usersthat had successfully completed the task to fill the questionnaire based on this first usageexperience. We scrutinized all responses and dropped those with too many missing values.As a result, we obtained 229 valid responses. Among them, 53.3 % were male and 46.7 %were female. A majority of them (81.7 %) were between twenty and twenty-nine years old.Over half of the respondents (61.1 %) held bachelor degree.
4.3 Common Method Variance
We conducted two tests to examine the common method variance. First, we performed aHarman’s single-factor test [35]. The results indicated that the largest variance explainedby individual factor is 13.22 %. Thus, none of the factors can explain the majority of thevariance. Second, we modeled all items as the indicators of a factor representing the methodeffect, and re-estimated the model [27]. The results indicated a poor fitness. For example, thegoodness of fit index (GFI) is 0.617 (<0.90). The root mean square error of approximation(RMSEA) is 0.173 (>0.08). With both tests, we feel that common method variance is not asignificant problem in our research.
5 Results
Following the two-step approach recommended by Anderson and Gerbing [2], we first exam-ined the measurement model to test reliability and validity. Then we examined the structuralmodel to test research hypotheses and model fitness.
First, we conducted a confirmatory factor analysis to examine the validity. Validity includesconvergent validity and discriminant validity. Convergent validity measures whether itemscan effectively reflect their corresponding factor, whereas discriminant validity measureswhether two factors are statistically different. Table 1 lists the standardized item loadings,
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Table 1 Standardized item loadings, AVE, CR and Alpha values
Factor Item Standardizedloading
AVE CR Alpha
Ubiquitous connection (UC) UC1 0.821
UC2 0.817 0.64 0.84 0.84
UC3 0.758
Effort expectancy (EFE) EFE1 0.810
EFE2 0.873 0.68 0.87 0.86
EFE3 0.794
Structural assurance (SA) SA1 0.809
SA2 0.847 0.65 0.85 0.85
SA3 0.767
Trust in online payment (TOP) TOP1 0.794
TOP2 0.826 0.68 0.87 0.86
TOP3 0.860
Initial trust in mobile payment (TMP) TMP1 0.805
TMP2 0.837 0.69 0.87 0.87
TMP3 0.841
Performance expectancy (PEE) PEE1 0.803
PEE2 0.779 0.61 0.83 0.83
PEE3 0.768
Usage intention (USE) USE1 0.657
USE2 0.867 0.65 0.85 0.84
USE3 0.881
Table 2 The square root of AVE (shown as bold at diagonal) and factor correlation coefficients
UC EFE SA TOP TMP PEE USE
UC 0.799
EFE 0.499 0.826
SA 0.524 0.539 0.808
TOP 0.522 0.408 0.532 0.827
TMP 0.588 0.521 0.534 0.572 0.828
PEE 0.501 0.522 0.547 0.531 0.502 0.783
USE 0.416 0.389 0.465 0.482 0.530 0.592 0.808
the average variance extracted (AVE), composite reliability (CR) and Cronbach Alpha values.As listed in the table, most item loadings are larger than 0.7. The T values indicate that allloadings are significant at 0.001. All AVEs exceed 0.5 and CRs exceed 0.7. Thus, the scale hasa good convergent validity [11]. In addition, all Alpha values are larger than 0.7, suggestinga good reliability [32].
To examine the discriminant validity, we compared the square root of AVE and factorcorrelation coefficients. As listed in Table 2, for each factor, the square root of AVE issignificantly larger than its correlation coefficients with other factors. This indicates a gooddiscriminant validity [11].
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0.37***
0.35***
0.13*
0.40***
0.12*
0.20**
ns.
0.16*
0.32***
0.15*Ubiquitous connection
Effort expectancy
Initial trust in mobile payment
Usage intention
Performance expectancy
Structural assurance
Trust in online payment
0.50***
Fig. 2 The results estimated by LISREL (Note *P < 0.05; **P < 0.01; ***P < 0.001; ns, not significant)
Table 3 The recommended and actual values of fit indices
Fit indices χ2/d f GFI AGFI CFI NFI NNFI RMSEA
Recommended value <3 >0.90 >0.80 >0.90 >0.90 >0.90 <0.08
Actual value 1.81 0.872 0.814 0.969 0.951 0.962 0.059
χ2/d f is the ratio between Chi-square and degrees of freedom. GFI Goodness of Fit Index, AGFI AdjustedGoodness of Fit Index, CFI Comparative Fit Index, NFI Normed Fit Index, NNFI Non-Normed Fit Index,RMSEA Root Mean Square Error of Approximation
Second, we adopted structural equation modeling software LISREL to estimate the struc-tural model. Figure 2 presents the results. Table 3 lists the recommended and actual values ofsome fit indices. Except GFI, other fit indices have better actual values than the recommendedvalues. This indicates a good fitness [11]. The explained variance of initial trust, performanceexpectancy and usage intention is 55.1, 62.4, and 64.4 %, respectively.
6 Discussion
As shown in Fig. 2, except H4, other hypotheses are supported. Both perspectives of self-perception-based and transference-based factors affect initial trust, which in turn affectsperformance expectancy and usage intention.
1. The results indicated that trust in online payment is the main factor determining initialtrust in mobile payment. Among the factors affecting initial trust, trust in online paymenthas the largest effect (γ = 0.40). This reflects a cross-channel trust transference. Extantresearch has identified the transference from offline trust to online trust [19,20]. Thisresearch identified that online trust also affects mobile trust. As users may have developedtrust in online payment, they may transfer their trust to mobile payment belonging tothe same brand. This is good news for service providers. Trust transference will helpbuild swift trust in mobile payment. Trust in online payment also affects performanceexpectancy. This suggests that when users develop trust in online payment, they alsoexpect to obtain a positively utility from mobile payment.
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2. On the other hand, ubiquitous connection is the main factor affecting performanceexpectancy (γ = 0.32). Compared to online payment, a main advantage of mobile pay-ment is ubiquity. Users expect to conduct payment and obtain payment information atanytime from anywhere. If users encounter service interruption and unavailability duringthe first interaction with mobile payment systems, they may form a poor evaluation ofmobile payment utility. Thus, service providers need to enhance their back-end systemsand ensure reliable services offered to users. In addition, ubiquitous connection alsoaffects initial trust. This is consistent with Lee [21], which noted the effect of ubiquitousconnection on user trust in mobile internet sites.
3. Effort expectancy has a low effect (γ = 0.16) on initial trust. This result is consistentwith extant research, which noted the effect of perceived ease of use on trust [4,24].As mobile devices have small screens and inconvenient input, users may feel difficultto use mobile payment. If service providers cannot improve interface design and offeran easy-to-use mobile payment system to users, users may feel that service providerslack the ability to ensure quality services. This may decrease their trust. In addition toimproving interface design, service providers can use location-based services to providecontextual information and services to users based on their location and preferences. Thispersonalized information may decrease user effort spent on information search and helpbuild user trust. The results indicate that effort expectancy has no effect on performanceexpectancy. However, it indirectly affects performance expectancy through initial trust.This suggests that initial trust mediates the effect of effort expectancy on performanceexpectancy.
4. Structural assurance has a medium effect (γ = 0.20) on initial trust. As users lack expe-rience using mobile payment systems, they may perceive great uncertainty and risk.Structural assurance as institutional mechanisms helps build users’ trust and mitigatetheir perceived risk because users may transfer their trust in these legal and technologicalstructures to mobile payment systems. Service providers can adopt technological mea-sures such as encryption and certification to ensure payment security and increase usertrust. They can also display trust seals such as VeriSign to indicate that their systemshave been verified by the trusted organizations. When users perceive that there existenough structural assurances to ensure payment security, they may engender initial trustin mobile payment.
5. Initial trust strongly affects performance expectancy. When users have established trustin mobile payment, they believe that they can obtain positive utility such as performanceand efficiency improvement in future. If they lack trust in mobile payment, they cannotexpect a positive utility. Both initial trust and performance expectancy have significanteffects on usage intention. This indicates that both factors act as enablers of user behavior.
7 Theoretical and Managerial Implications
From a theoretical perspective, this research integrated both perspectives of self-perception-based and transference-based factors to examine initial trust in mobile payment. As notedearlier, extant research has mainly used information systems theories such as TAM and IDTto examine mobile payment user adoption, and identified the effects of perceived usefulnessand relative advantage on user behavior. However, user behavior may be not only affectedby technological perceptions such as perceived usefulness, but also affected by user trust,which is critical to user adoption of mobile payment that involves great uncertainty and risk.Our results support this argument and indicate that usage intention is affected by both initial
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trust and performance expectancy. This advances our understanding of mobile payment userbehavior. On the other hand, although extant research has recognized the effect of trust onmobile payment user behavior, it has mainly been concerned with general trust and hasseldom examined initial trust. As mobile payment represents a novel service to most users,it is necessary to build initial trust in order to facilitate their adoption and usage. Especially,the high perceived risk and low switching cost highlight the necessity to establishing initialtrust in mobile payment. Our results indicated that initial trust receives influences fromboth perspectives of self-perception-based and transference-based factors. These results alsoenrich extant research on mobile trust.
From a managerial perspective, our results imply that service providers need to be con-cerned with self-perception-based and transference-based factors in order to build users’initial trust in mobile payment. Self-perception-based factors include ubiquitous connectionand effort expectancy, whereas transference-based factors include structural assurance andtrust in online payment. On one hand, service providers need to offer reliable and ubiquitousservices to users. They also need to improve interface design and provide an easy-to-usemobile payment system to users. On the other hand, service providers should adopt legaland technological structures such as encryption and certification to ensure payment security.These structures may help effectively build user trust and mitigate his or her perceived risk.In addition, if service providers have engendered users’ trust in online payment, users maytransfer their trust to mobile payment systems.
8 Conclusion
Due to the high perceived risk associated with using mobile payment, building users’ initialtrust is critical to their adoption and usage. Integrating both perspectives of self-perception-based and transference-based factors, this research examined initial trust in mobile pay-ment. The results indicated that both perspectives of factors affect initial trust. Thus, serviceproviders need to be concerned with these factors in order to facilitate mobile payment usage.
This research has the following limitations. First, we conducted this research in China,where mobile internet is developing rapidly but still in its early stage. Thus, our results needto be generalized to other countries that had developed mobile internet. Second, besides thefour trust determinants identified in the paper, there exist other factors possibly affectingtrust, such as trust propensity and information quality. Future research can examine theireffects. Third, we mainly examined initial trust in this research. However, trust is dynamicand initial trust may develop into general trust. A longitudinal research may provide moreinsights into trust development.
Acknowledgments This work was partially supported by grants from the National Natural Science Founda-tion of China (71371004, 71001030), and a grant from Zhejiang Provincial Key Research Base of Humanisticand Social Sciences in Hangzhou Dianzi University (ZD04-201301)
Appendix: Measurement Scale and Items
Ubiquitous connection (UC) (adapted from Lee [21])
UC1: I can conduct mobile payment from anywhere.UC2: I can conduct mobile payment at anytime.UC3: If needed, I can conduct mobile payment at anytime from anywhere.
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Effort expectancy (EFE)(adapted from Venkatesh et al. [43])
EFE1: Learning to use mobile payment is easy for me.EFE2: Skillfully using mobile payment is easy for me.EFE3: I find that mobile payment is easy to use.
Structural assurance (SA) (adapted from McKnight et al. [30])
SA1: I feel confident that encryption and other technological advances on the mobile Internetmake it safe for me to use mobile payment.
SA2: I feel assured that legal and technological structures adequately protect me from pay-ment problems on the mobile Internet.
SA3: Mobile Internet is a robust and safe environment in which to use mobile payment.
Trust in online payment (TOP) (adapted from Kim et al. [17])
TOP1: Online payment always provides accurate financial services.TOP2: Online payment always provides reliable financial services.TOP3: Online payment always provides safe financial services.
Initial trust in mobile payment (TMP) (adapted from Kim et al. [17])
TMP1: Mobile payment always provides accurate financial services.TMP2: Mobile payment always provides reliable financial services.TMP3: Mobile payment always provides safe financial services.
Performance expectancy (PEE) (adapted from Venkatesh et al. [43])
PEE1: Mobile payment improves my living and working efficiency.PEE2: Mobile payment increases my living and working productivity.PEE3: I find that mobile payment is useful.
Usage intention (USE) (adapted from Lee [21])
USE1: Given the chance, I intend to use mobile payment.USE2: I expect my use of mobile payment to continue in the future.USE3: I have intention to use mobile payment.
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Tao Zhou is an associate professor at School of Management,Hangzhou Dianzi University. He has published in Decision SupportSystems, Information Systems Management, Internet Research, Elec-tronic Commerce Research, Behavior and Information Technology,Computers in Human Behavior, and several other journals. He is onthe editorial advisory board of Internet Research. His research interestsinclude online trust and mobile user behavior.
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