Older-Users Acceptance of Smartcard Payment Systems: An Investigation of an Old-street Venders 1 Sheng-Chin Yu, 2 Fong-Ling Fu, 3 Chia-jen Ting, 4 Hsing-Chuan Lu 1, Assoc Prof. of TungNan University, scyu@mail.tnu.edu.tw *2, Assoc Prof. of National Chengchi University, flfu@nccu.edu.tw 3,4 Phd. Candidate of National Chengchi University, eggfacejen@gmail.com, Assoc Prof. of TungNan University, hclu@mail.tnu.edu.tw Abstract Taipei city EASYCARD Corp. continues to explore avenues to integrate more services and plans to extend the use of its smart card to other business activities beyond transportation systems, such as smart card use in the payment systems of small-value purchases. The ultimate aim is to allow people to travel around Taiwan with only one card. However, despite the many lessons that can be learned from the experiences of those company initiatives, there are still various issues pertaining to the implementation of their new services. Based on the Unified Theory of Acceptance and Use of technology (UTAUT) model, this paper specifically investigates planned usage of the Easycard payment systems between oldstreet venders and their customers. Analysis of the results indicates that there is significant difference between the venders and customers perception in the behavioral intentions to use smart card payment systems services. It is implicated that females, older and lower- educated users lack influence on the new technology's performance expectancy, lack facilitating conditions, and lack social influence, so as to affect their intension to use technology. Keywords: UTAUT, Older Customers; Smart Card, Intention to Use, Perceived Credibility 1. Introduction The usage of smart cards has changed peoples life style around the world and its application as a means of transactional payment has potential to supplant the conventional methods of wallet-based payment and more. [1] Government is seen and seeking it as a means to promote efficiency in government operations and to improve the delivery of public services[2], The EASYCARD Corporation was officially established in March 2000 and the main shareholder in the corporation is the Taipei City Government.[5] In order to continue to explore avenues of growth and expansion into daily-life transactions, Taipei city EASYCARD Corp. plans to integrate more services into its smart card beyond basic transportation applications, such as payment the Maokong Gondola service, for Taipei Zoo admission, as a library card, intercity bus services and on river boat services, and designated stores, to provide greater convenience to users. The ultimate aim is to allow people to travel around Taiwan with only one card. The ShenKeng Old-street is near by Maokong Gondola and Taipei Zoo. It is a famous scenic area in Taipei, which constantly draws large crowds of people who go there to have fun. ShenKeng's Old Streets are a commercial area made up of shops and stores, well preserved and keeping their original scenes, while integrating cultural and historical charm and bringing people back to its glorious past. The EASYCARD Corp. hopes to integrate with the services of this scenic area, so plans have been made to apply small payment services in ShenKeng Old-street shops[5]. However, despite the many lessons that can be learned from the experiences of those company initiatives, there are still various issues pertaining to the implementation of their new services. ShenKeng's Old Streets shops' venders are considered to be non-technological people residing in the modern technology world. This might lead to failure in smart card applications of transaction payments. In order to understand users acceptance for using smart card payment systems, this study conducts a survey to investigate and to understand the questions below: 1) Are the old street venders considered to be a non technological people? 2) If they are, do different user groups have different styles in their intentions to use technology? Journal of Communications and Information Sciences(JCIS) Volume3, Number3, Jul 2013 doi:10.4156/aiss.vol3.issue3.14
2. Theory Foundation 2. 1 The Adjusted Unified Theory of Acceptance and Use of Technology (UTAUT) The UTAUT model incorporates eight previously established models (i.e. Theory of Reasoned Action, the TAM, the Motivational Model, the Theory of Planned Behavior, a model combining the TAM and the Theory of Planned Behavior, the Model of Personal Computer Utilization, the Innovation Diffusion Theory, and the Social Cognitive Theory) into an unified model with four core determinants of user acceptance and usage behavior regarding a given technology: (1) performance expectancy, (2) effort expectancy, (3) social influence, and (4) facilitating conditions related to the technology [3]. Using the above concepts, the present study developed a research framework based on the UTAUT model with the inclusion of one additional variable: perceived credibility of technology. The adjusted model was then used to explore the factors affecting user acceptance of Malaysian government multipurpose smartcard applications. The determinants of the model and the added variable (with their justifications for our research) are explained below. 1) Intention to use: is defined as an individual's positive or negative feelings about performing the target behavior in the given technology[3]. It relates to planning, intending, and predicting the use of the respective technology in the future[2]. In our research model, user acceptance is treated as a dependent variable and it is examined by intention to use, rather than actual usage. 2) Performance expectancy: is defined as the degree to which an individual believes that using the system will help him or her to attain gains in job performance[3]. In our research context, performance expectancy refers to the perception that using Easycard payment systems will help cardholders to attain benefits in commercial transactions. 3) Effort expectancy: is defined as the degree of ease associated with use of the technology system. In fact, three constructs from the models mentioned earlier capture the concept of effort expectancy. These are: perceived ease-of-use (TAM), complexity (Model of Personal Computer Usage), and easeof-use (Innovation Diffusion Theory)[3]. In our research context, the effort expectancy refers to users' perception that the Easycard payment systems will be found to be easy to use. 4) Social influence: is defined as the degree to which an individual perceives the importance of the beliefs of others that he or she should use the new system [3]. In the present study, social influence refers to the social pressure of their reference groups influencing the intentions of Easycard holders to use the Easycard for payment applications. 5) Facilitating conditions: are defined as the degree to which an individual believes that an organizational and technological infrastructure exists to support the use of the system[3]. In the present context, facilitating conditions refers to the objective factors in the environment that make an act of technology use easy to accomplish. For the Easycard payment systems, factors include government encouragement and availability of facilities usages during all commercial transaction operations. 6) Perceived credibility: In a study on Internet banking, perceived credibility of the financial technology was found to be the direct determinant of an indvidual s intention to use[6]. In our study, the perceived credibility is defined as the degree to which a user feels certainty in the pleasant consequences of using an electronic application service, that there is no financial risk, physical risk, functional risk, social risk, time-loss risk, opportunity cost risk, and information risk[7]. 7) Anxiety: is used to measure anxiety in using applications, and includes fear of losing the actual EasyCard and fear of security damage problems. [2]. The EasyCard is a contactless smartcard system without any cash withdrawal functionality on the card, with no user credit checks required, and with no links to personal data, and is therefore free from common concerns about technology security. Thus, anxiety is not considered to be a direct determinant of intention to use EasyCard technology in our study. 2.2 Personality Traits as Moderators of Intention to Use Some past research studies have indicated that personality traits influence the intention of technology behavior through intervening variables such as performance expectancy, social influences and facilitating conditions. [7]. Venkatesh et al. s finding was that technological attitude was more salient for men, while subjective norm and perceived behavioral control were more salient for women
in early stages of technology experience [3]. Finally, Morris and Venkatesh found that technology attitude was most salient for younger workers. While perceived behavioral control was more salient for older workers, a subjective norm was more salient to older women [3]. The impact of age, sex, and education level are found to be associated differentially with beliefs about the Internet and their Internet usage experience[8][9]. Since personality traits may dominate a person s behavior towards technology, the effects of personality traits (gender, age, and level of education) on user s intention of behavior will be considered in our research context. 3. Research Methodology 3.1 Research Conceptual Model and Hypotheses Based on the above literature, a research framework was developed as depicted in Fig. 1 below. Adjusted UTAUT performance expectancy effort expectancy social influence facilitating conditions Perceived credibility H5, H6,H7, Intention H8,H9,H10 to use H1,H2, H3 Roles Gender Age Education H4 Figure 1. Research Framework The UTAUT posits the age and gender as the key moderator variables[3]. To bridge the digital divide, Reffat suggests that governments can help by providing computer education especially to elderly and younger people.[2] El-Gayar, O. F and Moran, M. evaluated the moderated effect of level of education on users' acceptance of Tablet PC [4]. It is presumed: H1a: The relationship between users performance expectancy and intention to use Easycard payment systems are moderated by gender of users. H1b: The relationship between effort expectation and user's intention to use Easycard payment systems are moderated by gender of users. H1c: The relationship between Social influence and intention to use Easycard payment systems are also moderated by gender of users. H1d: The relationship between facilitating conditions and intention to use Easycard payment systems are moderated by gender of users. H1e: The relationship between Perceived credibility and intention to use Easycard payment systems are moderated by gender of users. H2a: The relationship between performance expectancy and intention to use Easycard payment systems are moderated by level of education of users. H2b: The relationship between effort expectation and user's intention to use Easycard payment systems are moderated by level of education of users. H2c: The relationship between Social influence and intention to use Easycard payment systems are moderated by level of education of users. H2d: The relationship between facilitating conditions and intention to use Easycard payment systems are also moderated by level of education of users. H2e: The relationship between Perceived credibility and intention to use Easycard payment systems are moderated by level of education of users.
H3a: The relationship between technology performance expectancy and intention to use Easycard payment systems are moderated by age of users. H3b: The relationship between effort expectation and user's intention to use Easycard payment systems are moderated by age of users. H3c: The relationship between Social influence and intention to use Easycard payment systems are moderated by age of users. H3d: The relationship between facilitating conditions and intention to use Easycard payment systems are moderated by age of users. H3e: The relationship between Perceived credibility and intention to use Easycard payment systems are moderated by age of users. H4: There exist at gender, age, and level of education differences between old street venders and their customers. In addition, due to differences of gender, age, level of education, and different roles (the old street venders vs. their customers) it is likely that different groups would have differences in cognitions of UTAUT and intention to use. [3][8],Thus it is presumed: H5: There exist cognition differences at performance expectancy between old street venders and their customers. H6: There exist differences at Effort expectation between old street venders and their customers. H7: There exist cognition differences at Social influence between old street venders and their customers. H8: There exist cognition differences at facilitating conditions between old street venders and their customers. H9: There exist cognition differences at Perceived credibility between old street venders and their customers. H10: There exist differences at Intention to use between old street venders and their customers. 3.1 Questionnaire Design The study s questionnaire consisted of two sections which include (1) the respondent's demographic information; (2) the respondent's intention to use Easycrad, comprised of 19 questions related to the research framework (see Fig. 1). The section 2 questions are on a five-point Likert Scale shown in Table II. The measures of participants technology performance expectancy, social influence, facilitating conditions, perceived credibility and intention to use were adapted from a previous study by Loo, Yeow and Hong [2], while the measures of effort expectancy was revised from the Venkatesh et al. [3]. 3.2 Data Collection The study s questionnaire consisted of two sections which include (1) the respondent's demographic information; (2) the respondent's intention to use Easycrad, comprised of 19 questions related to the research framework (see Fig. 1). The section 2 questions are on a five-point Likert Scale shown in Table II. The measures of participants technology performance expectancy, social influence, facilitating conditions, perceived credibility and intention to use were adapted from a previous study by Loo, Yeow and Hong [2], while the measures of effort expectancy was revised from the Venkatesh et al. [3].
4. Results 4.1 Sample Analysis Analysis of the samples structure were divided into two sections, data on old street venders, and data of their customers. Demographic data is shown below: Table1. Sample profile Category Roles Frequency (Percentage) Venders Customers Gender M 17 (35.4%) 38 (46.9%) F 31 (64.6%) 43 (53.1%) Age <=19 20-29 30-39 40-49 >=50 0 (.0%) 11 (22.9%) 12 (25%) 23 (47.9%) 2 (4.2%) 8 (9.1%) 63 (71.6%) 9 (10.2%) 6 (6.8%) 2 (2.3%) Education Under Secondary school 33 (68.8%) 11 (13.6%) Above Diploma 15 (31.2%) 70 (86.4%) Had been used Easy card Yes No 40 (83.3%) 8 (16.7%) 77 (95.1%) 4 (4.9%) Times/per week of Easy card used <= 2 25 (52.1%) 35 (43.2%) Had been used easy card in nontransportation applications >=3 Yes No 4.2 Consistency of the Measurement 23 (47.9%) 22 (45.8%) 26 (54.2%) 46 (56.8%) 36 (44.4%) 45 (55.6%) The overall internal consistency coefficients (Cronbach α) of above 0.70 proved the factors to be acceptable (Hair, et al., 1998), and is shown in Table 2. Table2. Reliability of Questionnaire Statement presented in the questionnaire Performance expectancy E1 Using Easycard payment systems is convenient. E2 Using Easycard payment systems allows quick verification process. E3 Easycard payment systems can fit well into my lifestyle. E4 Using Easycard payment systems simplifies verification process. Facilitating conditions F1 It is easy for you to make an Easycard payment. F2 Adding value to Easycard is available to all MRT stations and convenient stores. F3 I could obtain assistance from the MRT customer service center staff if I have any inquiry about Easycard payment systems. Social influence S1 My peer group affects my intention to use Easycard payment systems. S2 The Easycard Corporation's encouragement affects my intention to use Easycard payment systems. S3 The fact that most Taipei people have Easycard affects my intention to use Easycard payment systems. Perceived credibility C1 I do not believe that Easycard could be used to pay for other services. C2 Using Easycard payment systems would erode my privacy. C3 The fact that most Taipei people have Easycard affects my intention to use Easycard payment systems. α value.820.797.796.724
Effort expectation EE1 Using Easycard to pay for transportation is convenient. EE2 I feel satisfied with adding value to Easycard available to all MRT stations and convenient stores. EE3 To sum up, I feel totally satisfied with using Easycard to pay for transportation. Intention to use I1 I plan to use Easycard payment systems in the near future. I2 I predict I would use Easycard payment systems in the near future. I3 I predict I would use Easycard payment systems in the near future..754.910 4.3 Moderated Eeffects Analysis on Ajusted UTAUT Model The moderated effect was tested using the statistical method ANCOVA, with the variable of performance expectancy as independent variable, intention to use as dependent variable, and gender as moderator. Hypothesis 1a indicates that the influence of performance expectancy on behavioral intention will be moderated by gender, such that the effect will be stronger for men. From the same results, we learnt that the overall model (see Table 3) is significant, meaning that gender moderates the relationship between adjusted UTAUT model constructs and intention to use the payment systems. Therefore, H1b, H1c, H1d and H1e are valid. Checking the F values on Table III shows that H2a is valid, meaning that the influence of performance expectancy on behavioral intention will be moderated by level of education, such that the effect will be stronger for higher educated people. From the same results, we learnt that the overall model (see Table 3) is significant, Therefore, H2b, H2c, H2d and H2e are valid. It is also shown that the influence of performance expectancy on behavioral intention will be moderated by age, such that the effect will be stronger for younger people. From the same results, we learnt that the overall model (see Table 3) is significant, Therefore, H3a, H3bc, H3c, "H3d" and H3e are valid. Table3. The Influence of Moderated Effects of Gender, Education, and Age on Adjusted UTAUT Model Gender Education Age UTAUT Factors F value P value F value P value F value p value Performance expectancy 27.573.000** 31.924.000*** 28.225.000** Facilitating conditions 18.921.000** 23.454.000*** 28.225.000** Social influence 20.461.000** 27.886.000*** 22.577.000** Perceived credibility.495.611 7.757.001*** 3.658.029* Effort expectation 3.112.048* 8.117.001*** 5.186.007* **p<0.01, *p<0.05 4.4 Moderator, the Role of Vender and Customer Category M Gender F <=19 20-29 Age 30-39 40-49 >=50 Educatio Under Secondary school n Above Diploma **p<0.01 *p<0.05 Table 4. Moderator Effects Roles Frequency (Percentage) Venders Customers 17 (35.4%) 38 (46.9%) 31 (64.6%) 43 (53.1%) 0 (.0%) 8 (9.1%) 11 (22.9%) 63 (71.6%) 12 (25%) 9 (10.2%) 23 (47.9%) 6 (6.8%) 2 (4.2%) 2 (2.3%) 33 (68.8%) 15 (31.2%) 11 (13.6%) 70 (86.4%) χ 2 (P value) 41.63(.000)** 42.26(.000)** 41.83(.000)**
According to statistical significance (Table III), the moderators gender, level of education and age could be the personality traits to distinguish between ShenKeng's Old Streets venders and their customers. The Chi-square Test shown in Table IV indicates that Hypothesis H4 is valid. Differences do exist in gender, age, and level of education between old street venders and their customers. 4.5 The Influences of Role effect on Adjusted Model Using the Role as independent variable to check the different role s perceptions of each and every adjusted construct and intention to use, and based on the F values (see Table V), there existed significant differences between venders and their customers in the perception of using Easycard payment systems in attaining benefits in commercial transactions, in ease of use, and in the social pressure of their reference groups influencing their intentions to use the technology. The other two measurements: perceptions of credibility and effort expectation were not significantly different between the two roles. This means that users perceptions of pleasantness and financial risk as a consequences of using an electronic application service were not significantly different between the two groups. Table 5. Moder5tor Effects UTAUT Factors F value p value Performance expectancy 17.838.000*** Facilitating conditions 4.318.040* Social influence 10.943.001*** Perceived credibility.464.497 Effort expectation.810.370 Intention to use 12.803.000*** **p<0.01 *p<0.05 5. Conclusions and Suggestions ShenKeng's Old Street are a commercial but preserved area. The shops' venders are still underconsidered in the technology world and seen as non technological people. In order to understand older users acceptance for using EASYCARD Corp. smart card payment systems, this study has presented a new research framework based on the well-known technology acceptance model (the UTAUT model), but with the addition of the perceived credibility of technology variable. Several ANCOVA analyses showed there are significant moderated effects of gender, education and age on the UTAUT model. Consistent with the UTAUT study by Venkatesh, et. al.[3], these findings suggest that the age effects are greater for older workers, and also among younger workers with a stronger willingness to adopt new IT products. The study also discovered age does have a high influence on intentions to use payment systems. Similar to the age variable, gender and level of education have been recognized by our research to play an important moderating role in payment systems acceptance. Because, old people were less educated in most situations among smart card users, the author further tested the synergy effect of age and education in the UTAUT model using two groups of data: venders of older ages but lower education and customers of younger ages with higher education. Based on data of the significant differences in performance expectancy, facilitating conditions, social influence, and intention to use technology between old street venders and their customers, the authors infer that the old street venders may resist usage of the smartcards if the EASYCARD Corp. attempts to implement the payment systems under the current situation. With respect to the above conclusion, and in order to tie the prior theories to practice, the authors recommend that the ShenKeng's Old Street venders should be convinced of the value of having a multipurpose card to increase their intentions to use Easycard applications beforehand, exemplifying how smart cards can enable people to perform different functions more conveniently in commercial transactions. In addition, aside from more mass
media promotions, such as advertisements and social community activities, old-street venders should be introduced to increased social influence of Easycard usage. In sum total, only 48 of 141 old-street venders accepted the survey, and therefore the sample data may exhibit a bias. Those which refused the survey might be more likely to refuse to use actual smart cards as well. Therefore, the authors suggest that EASYCARD Corp. deliver more real (understandable) value for those old people. The real value can stem on one hand from extended possibilities to communicate with reference groups, and on the other hand from critical services, such as the services that can provide real benefits for the venders. 6. References [1] DH. Shin, "Toward an understanding of the consumer acceptance of mobile wallet", Computer in Human Behavior, vol.25, pp.1343-1354, 2009. [2] WH. Loo, HP. Yeow and SC. Hong, " User acceptance of Malaysian government multipurpose smartcard applications", Government Information Quaterly, vol.26, pp.358-367, 2009. [3] V. Venkatesh, M. Morris, G. Davis, and F. Davis, "User acceptance of information Technology: Toward a unified view" MIS Quarterly, 27(3), pp. 425-478, 2003. [4] S. Al-Shafi and V. Weerakkody, "Understanding citizens' behavioral intention in the adoption of e-government services in the state of QATAR" Paper presented at the Proceedings of the 17th European Conference on Information Systems (ECIS 2009), 2009. EASYCARD Corporation, http://www.easycard.com.tw/ [5] T. Zhou, Y. Lu and B. Wang, "Integrating TTF and UTAUT to explain mobile banking user adoption" Computers in Human Behavior, 26, pp.760 767, 2010. [6] HI. Wang, "The role of personality traits in UTAUT model under online stocking" Contemporary Management Research, 1(1), pp.69-82, 2005. [7] V. Assadi, "Continence intention to use high maintenance information systems: the Role of Perceives Maintenance Effort" 18th European Conference on Information Systems, 2010M. Conci, F. Pianesi and M. Zancanaro, "Useful, Social and Enjoyable: Mobile Phone Adoption by Older People", LNCS 5726, pp.63-76, 2009. [8] CE. Porter and N. Donthu, "Using the technology acceptance model to explain how attitudes determine Internet usage: The role of perceived access barriers and demographics", Journal of Business Research, 59, pp.999 1007, 2006.