Elderly and Internet Banking: An Application of UTAUT2

Journal of Internet Banking and Commerce An open access Internet journal (http://www.arraydev.com/commerce/jibc/) Journal of Internet Banking and Commerce, April 2015, vol. 20, no. 1 (http://www.arraydev.com/commerce/jibc/) Elderly and Internet Banking: An Application of UTAUT2 JORGE ARENAS-GAITÁN, PhD Postal Address: Department of Business Management and Marketing, University of Seville. Avda. Ramón y Cajal, 1, 41018 Seville, SPAIN Author's Personal/Organizational Website: http://admark.us.es Email: [email protected] Jorge Arenas-Gaitán is associate professor in the Department of Business Administration and Marketing at the University of Seville (Spain). Research interests include the acceptance of new technologies, e-commerce and cross-cultural analysis. His work appears in several academic journals such as Social Science Computer Review, Computers & Education and Kybernetes among other. BEGOÑA PERAL-PERAL, PhD Postal Address: Department of Business Management and Marketing, University of Seville. Avda. Ramón y Cajal, 1, 41018 Seville, SPAIN Author's Personal/Organizational Website: http://admark.us.es Email: [email protected] Begoña Peral-Peral is associate professor in the Department of Business Administration and Marketing at the University of Seville (Spain). Her research interests include the acceptance of new technologies, e-commerce, elderly and consumer behavior. Her work has been published in Social Science Computer Review, Computers & Education and Revista de Economía Aplicada. MARIA ANGELES RAMÓN-JERÓNIMO, PhD Postal Address: Department of Business Administration and Marketing, Pablo de Olavide University. Ctra. de Utrera, km. 1 41013, Seville, SPAIN Author's Personal/Organizational Website: www.upo.es Email: [email protected] Marıa A. Ramón-Jerónimo is an associate professor at Pablo de Olavide University, Spain. She participates in different research projects related to relationship marketing, innovation, strategy and international marketing, and results have been published in different journals such as the Journal of Academy of Marketing Science, Industrial JIBC April 2015, Vol. 20, No. 1 - 2 - Management & Data Systems, and Journal of Business Research. Abstract The present study aims to explain Internet banking use by the elderly, applying the UTAUT2 approach (extension of Unified Theory of Acceptance and Use of Technology in the consumer context). A sample of 415 individuals over 55 years old has been analyzed. WarpPLS 3.0 was used for the measurement models analysis and the structural model analysis. The results show that the elderly’s people’s to accept Internet banking was significantly impacted by habit, performance expectancy, price value and effort expectancy, in this order of influence of strength. The actual behavior was influenced by behavior intention and habit. However, social influence, facilitating conditions and hedonic motivation did not play a salient role in affecting the actual adoption behavior of Internet banking. Gender was proposed as a moderator variable but the results did not support this role. Keywords: elderly; Internet banking; UTAUT2 © Jorge Arenas-Gaitán, Begoña Peral-Peral, Maria Angeles Ramón-Jerónimo, 2015 INTRODUCTION Internet banking (IB) has been one of the most successful (Al-Jabri and Sohail 2012) and profitable (Lee 2009; Yuen et al. 2010) B2C applications in e-commerce during the last decade. IB is a channel that allows consumers to perform a wide range of financial and non-financial services through a bank's website (Hoehle et al. 2012). Moreover, IB customers are the most interesting ones for banks (Pikkarainen et al. 2004), as they show a higher satisfaction, more positive word-of-mouth communications and the lowest intention to change to other financial institutions (Mols 1998). However, although the advantages of IB use are noticeable, only 40% of people between 16 and 74 years old used IB in Europe (28 countries) in 2012, while in Spain the percentage is just 32% (Eurostat 2013a). These percentages of use diminish to 24% and 15%, respectively, in the case of people who were 55-74 years old in 2012. Several studies have documented the growth of the grey market (Kohlbacher et al. 2014). For example, in 2012, 36.4% of the Spanish population was over 50 years old (Eurostat 2013b) with an attractive financial status (Moschis 2012). Although, retirement can decrease household income, the effect on the purchase power per member of the household is weak since children have by then usually moved away. Thus, mature consumers have a significant purchasing power but also a need for carefully managing their assets during their lifespan making the 55-plus segment extremely lucrative for financial service providers. In this line, Chen and Holsapple (2013) develop a full examination of the e-business-adoption area, focusing on 618 journal articles, published between 2006 and 2011. They find that the quantity of e-business adoption research about individual consumers is growing. However, they include very few references about e-business adoption for elder people (as Lam and Lee 2006; Pan and Jordan-Marsh 2010, both about Internet use). JIBC April 2015, Vol. 20, No. 1 - 3 - To explain technology acceptance and use, there have been several theoretical models, developed from theories in psychology and sociology. In 2003, Venkatesh et al. review, compare and summarize eight prior theories/models of technology use: the Theory of Reasoned Action (TRA), the Technology Acceptance Model (TAM), the Motivational Model (MM), the Theory of Planned Behavior (TPB), the Model of PC utilization (MPCU), the Innovation Diffusion Theory (IDT), the Social Cognitive Theory (SCT) and the Expectation-Confirmation Theory (ECT). They propose the Unified Theory of Acceptance and Use of Technology (UTAUT; Venkatesh et al. 2003) identifying four key concepts: performance expectancy (PE), effort expectancy (EE), social influence (SI) and facilitating conditions (FC). Venkatesh et al, show how these constructs explain the use of technology. The UTAUT has been developed in organizational contexts and tested in longitudinal field studies of employee technology acceptance. In 2012, Venkatesh et al. updated their previous model adapting it to the consumer context. The UTAUT2 incorporated three new key variables: hedonic motivation (HM), price/value (PV) and habit (H), as concepts playing an important role in the use of new technologies by consumers. Our aim in this work is to analyze the acceptation and use of Internet Banking by the elderly following the UTAUT2 methodology. Three research lines converge in the present study: IB (Al-Qeisi 2009; Lee et al, 2010; Hoehle et al. 2012), the behavior of the elderly in the acceptation and use of information technologies (Eastman and Iyer 2004; Kim 2008; Ramón-Jerónimo et al. 2013) and the analysis of a consumer context applying the UTAUT2 model as a framework (Venkatesh et al. 2012). The main contribution of this work is to analyze the convergence of these three research lines. Although there are important works in each of them, we have not found significant studies which explain IB acceptation by the elderly using an approach which is specifically designed for analyzing the use of consumption technologies. To achieve the aim proposed, the work is structured as follows. In the first section the literature on the three main topics of the work: IB, the elderly and UTAUT (section 2) is described. The paper continues with the development of the hypotheses proposed (section 3), methodology (section 4) and results (section 5), finishing with the discussion (section 6), conclusions and limitations of the research (section 7). LITERATURE REVIEW Internet banking and the elderly Different research works (Ding et al. 2007; Howcroft et al. 2002; Karjaluoto et al. 2002; Mattila et al. 2003) find that there is a significant effect of multiple sociodemographic variables on the use of IB. Regarding age, Ainin et al. (2005) find a negative and significant relationship between age and IB adoption, probably because the elderly are more resistant to change and have a negative attitude toward using IB services (Laukkanen et al. 2007). An alternative approach could be the consideration of age as a moderator in the relationship between satisfaction with the offline channel and perceived usefulness, showing how the elderly are reluctant to accept IB (Falk et al. 2007). Previous results point to the idea that elderly people prefer to have face-to-face communication where JIBC April 2015, Vol. 20, No. 1 - 4 - possible (Asmi and Ishaya 2012). Hill et al. (2008) for instance, show that for people over 50 years old, the relative advantage perceived of IB was weaker than the perception of e-mail, probably due to perceptions of risk and Internet security. In this line, Leppel and McCloskey (2011) find that mature respondents (50 and older) were more likely than young respondents to worry about providing financial and personal information, although having a college education increases the level of comfort that they feel when working with technology. Rock et al. (2010) show that older respondents in the USA were less likely to use the Internet as a source of financial information. However, the reasons for this were not security concerns: they preferred contact with bank workers due to websites being difficult or confusing. Confusing web pages and complex steps discouraged the adoption of online banking by people over the age of 65 and they blamed insufficient or nonexistent training on how to use the technology for IB (Mattila et. al. 2003). Age itself may not be the only explanation of the rejection of IB. Lichtenstein and Williamson (2006) showed that elderly Australians with low incomes reported that having a lack of awareness toward IB and its advantages, a lack of Internet access and Internet confidence, inadequate knowledge and support for use or the initial setting up procedure, a lack of trust, security and high perceived privacy risks were among the reasons for not using IB services. Sohail and Shanmugham (2004) find that age and the educational qualifications of electronic and conventional banking have no significant impact on e-banking adoption. Instead, they argued that accessibility to the Internet, awareness of e-banking and customers’ resistance to change are the main factors influencing the adoption. Also, Nayak et al. (2010) show that, for older adults aged 60– 88, and for more complex Internet activities, such as banking transactions gender (male), health status (good), perceived usefulness, and attitude were the significant factors. UTAUT and UTAUT 2 Hoehle et al. (2012) perform a review of 247 peer-reviewed articles about e-banking adoption. They find that most works use models that were developed several decades ago, such as the Diffusion of innovations (DOI), Theory of reasoned action (TRA), Theory of planned behavior (TPB) and Technology acceptance model (TAM) (cf. Al- Qeisi 2009, for examples of articles about these models and IB). Although almost all studies included demographic variables such as age, gender, income, and education in models of consumers' behavior toward e-banking channels there was no convergent understanding of the ways in which these variables impact on the adoption of these channels. Hoehle et al (2012) show the need to use more current models and a clear alternative is UTAUT (Venkatesh et al. 2003). UTAUT integrates multiple models of user acceptance theory and therefore offers the most comprehensive model available at the moment. The UTAUT not only underscores the main determinants predicting the intention to adopt and actual adoption, but also allows researchers to analyze the contingencies from moderators that would amplify or constrain the effects of core determinants. UTAUT has been empirically tested and proven superior to other prevailing competing models (Venkatesh et al. 2003; Venkatesh and Zhang 2010). However, Williams et al. (2011) find that although a large number of studies have cited the original article of UTAUT, only 43 actually utilized the theory or its JIBC April 2015, Vol. 20, No. 1 - 5 - constructs in their empirical research for examining IS/IT related issues. Venkatesh et al. (2012) find that most studies using UTAUT employed only a subset of the constructs, particularly by dropping the moderator. Some research works analyze IB via UTAUT-based models, such as Yeow et al. (2008), who study positive and negative factors influencing user acceptance of IB services in Australia and Abu-Shanab et al. (2010) in the case of Jordan. Other authors compare IB acceptation in different countries, such as Yuen et al. (2010) in the United States and Australia; Al-Qeisi (2009) in the United Kingdom and Jordan, and Im et al. (2011) in the USA and Korea. UTAUT has been developed in the organizational context where acceptance and use of a technology can be mandatory. Nevertheless, for consumers, there is not an organizational mandate and thus most consumer behaviors are completely voluntary. Chen and Holsapple (2013) indicate that research topics for e-business can follow different approaches for organizations and consumers. Accordingly, UTAUT2 is proposed as a useful model to understand consumer use of technologies in general. A key difference between UTAUT and UTAUT2 is that the behavior intention and the use relationship are moderated by the experience with technology. Moreover, individual characteristics moderate the effect of habit on the behavioral intention. Following Bagozzi (2007) and Venkatesh et al. (2007), Venkatesh et al. (2012) identify three key constructs which explain the consumer’s behavior in the use of technology: hedonic motivation, price value and habit, and they propose gender, age and experience as moderator variables. UTAUT2 models how habit directly affects use behavior (USE) and indirectly through behavioral intention (BI). Comparing results from UTAUT2 and UTAUT, Venkatesh et al. (2012) find out how the variance explained in both behavioral intention (74 percent) and technology use (52 percent) are substantial, compared to the baseline UTAUT that explained 56 percent and 40 percent of the variance in intention and use respectively. RESEARCH MODEL AND HYPOTHESES Research model Figure 1 shows the research model based on UTAUT2 and the hypotheses of this study. Performance* Expectancy* (PE) Effort* Expectancy* (EE) Social* Influence*(SI) Faciliting Conditions* (FC) Price/Value* (PV) Hedonic* Motivation* (HM) Habit*(H) Behavioral Intention*(BI) Use*Behavior (USE) Gender* H1 H2 H3 H4 H5 H6 H7 H8 H9 H10 H11 JIBC April 2015, Vol. 20, No. 1 - 6 - The research model aims to explain the acceptance of IB. UTAUT (Venkatesh et al. 2003) explain how USE, in this case IB, is explained by the intention to use it (BI), and by the facilitating conditions (FC) that make it possible. Simultaneously, the BI receives effects from the performance expectancy (PE), effort expectancy (EE), social influence (SI), and facilitating conditions (FC). In a more recent work, Venkatesh et al (2012) adapt the model to the technologies adopted by consumers incorporating three new variables: price/value (PV), hedonic motivation (HM) and habit (H). These variables act as antecedents of the BI. On the other hand, habit (H) directly affects the use of the technology under study (USE). Hypotheses In previous works, the UTAUT2 model has been applied to explain the acceptance of Internet Banking. In this section the hypotheses associated with this model are explained, considering previous literature about technology adoption, IB and elderly people. The main variable in the literature about technology acceptance is the BI. BI is the degree to which a person has formulated conscious plans to perform or not perform some specified future behavior (Davis 1989; Venkatesh et al. 2003; Venkatesh et al. 2012). According to UTAUT2, PE, EE, SI, FC, HM, PV and H are antecedents of BI. PE is the degree to which using a technology will provide benefits to individuals in performing certain activities. EE is defined as the degree of ease associated with an individual’s use of technology. SI (SI) is defined as the extent to which an individual perceives that people who are important to him/her believe that he/she should use a particular technology. FC is defined as the individual’s perceptions of the resources and support available to perform behavior (Venkatesh, et al. 2003; Venkatesh, et al. 2012). PE, EE, SI and FC affect BI in adopting IB (Cheng et al. 2008; Cheng et al, 2009; Im et al. 2011; Martins et al, 2014; Yeoh and Chan, 2011; Yu, 2012; Yuen et al 2010). HM is defined as the fun or pleasure derived from using a technology (Venkatesh, et al., 2012). Some studies indicate that HM affects BI intention toward adopting technologies by consumers, such as e-learning (Lewis et al. 2013; Raman and Don, 2013), ecommerce (Escobar-Rodríguez and Carvajal-Trujillo, 2013), mobile shopping services (Yang 2010; Yang and Forney 2012) or the travel advice web (Chong and Ngai 2013). Venkatesh et al. (2012) define price/value as the individuals’ cognitive trade-off between the perceived benefits of the applications and the monetary cost for using them. Price/value affects BI toward adopting IB (Yu, 2012), as well as other technologies, such as e-learning (Lewis et al, 2013; Raman and Don 2013), e-commerce (Escobar- Rodríguez and Carvajal-Trujillo 2013), the travel advice web (Chong and Ngai 2013) or the use of 3G technology (Mardikyan et al. 2012) or smartphones (Pan et al. 2014). Finally, the literature indicates that habit, defined as the extent to which people tend to perform behaviors automatically because of learning (Venkatesh et al. 2012), affects BI toward consumer technology use context, such as e-learning (Lewis et al. 2013; Raman and Don 2013), e-commerce (Escobar-Rodríguez and Carvajal-Trujillo 2013), the travel advice web (Chong and Ngai, 2013) or the use continuance intention of Twitter (Barnes JIBC April 2015, Vol. 20, No. 1 - 7 - and Böhringer 2011). In consequence, based on the literature mentioned above and considering the importance of the segment of the elderly for IB, we propose the following hypotheses. H1. Performance expectancy is positively related to behavioral intention in the adoption of Internet Banking by the elderly. H2. Effort expectancy is positively related to behavioral intention in the adoption of Internet Banking by the elderly. H3. Social influence is positively related to behavioral intention in the adoption of Internet Banking by the elderly H4. Facilitating conditions are positively related to behavioral intention in the adoption of Internet Banking by the elderly. H5. Hedonic motivation is positively related to behavioral intention in the adoption of Internet Banking by the elderly. H6. Price value is positively related to behavioral intention in the adoption of Internet Banking by the elderly. H7. Habit is positively related to behavioral intention in the adoption of Internet Banking by the elderly. The aim of the UTAUT2 model is to explain the use of a new technology, in this case, IB. Use behavior is defined as the frequency of information technology usage (Venkatesh et al. 2003; Venkatesh et al. 2012). Previous studies provide support for the idea that behavioral intention and facilitating conditions (Chen and Chan, 2014; Im et al. 2011; Martins et al 2014; Yu 2012) explain use behavior in adopting IB. The incorporation of the variable habit in a consumer technology use context (Venkatesh, et al. 2012) for the UTAUT (Limayem et al. 2007) indicates that habit affects use behavior in the adoption for this context, such as e-learning (Lewis et al, 2013; Raman and Don, 2013) e-commerce (Escobar-Rodríguez and Carvajal-Trujillo 2013) or the travel advice web (Chong and Ngai 2013). Considering this we propose: H8. Behavioral intention is positively related to use behavior in the adoption of Internet Banking by the elderly. H9. Facilitating conditions are positively related to use behavior in the adoption of Internet Banking by the elderly. H10. Habit is positively related to use behavior in the adoption of Internet Banking by the elderly. In addition, we will investigate the moderating effects proposed in UTAUT2. Specifically, we propose to explore the moderating effect of gender in the adoption of IB by the elderly (Yu 2012; Martins et al, 2014). H11: Gender moderates Internet Banking adoption by the elderly We have not considered age as a moderator given that our analysis is carried out on people over 55 in such a way that there is little dispersion with regard to age. Likewise, the other two moderator variables (age and experience) proposed in the UTAUT2 have not been used because the context which we analyze is completely voluntary and as this JIBC April 2015, Vol. 20, No. 1 - 8 - study is longitudinal, it is incapable of capturing increasing levels of user experience at different time periods. METHODOLOGY Survey Data were collected through a survey during the months of November and December 2012 using students over 55 years old enrolled in the “Experiential Classroom” initiative in a University in the south of Spain. To eliminate possible ambiguities in the questionnaire, it was piloted using seven older adult volunteers. After some minor changes in the questionnaire, data were collected during class time, and thanks to the help of class representatives. 536 questionnaires were completed by students. After removing the incomplete cases and outliers, 474 valid responses were obtained (88.4% response rate). The number of valid surveys was 474; 62.5% were women. The average age was 63.6. Most of them had secondary studies - 54.2% - and university studies - 36.1% - and most of them considered that they were in a socioeconomical middle class - 80.2%. Measurement The measurement scales applied have been tested in prior research. Specifically, the scales proposed by Venkatesh et al. (2012) have been adapted to measure the UTAUT2 constructs for Internet banking. For the PV, we use the scale proposed by Lockett and Littler (1997) and used by Patsiotis et al. (2012). We believe that this scale gathers the PV idea better for the case of IB. A formative scale was used to measure USE. To do so, we adopted the scale set out for IB by Patsiotis et al. (2012) which includes 10 services. The items are reported in Table 1. All items were anchored on a 7-point Likert scale (1 = strongly disagree; 7 = strongly agree) except for socio-demographic and other variables related to computer use and the Internet. Statistical Tools The Partial Least Squares (PLS) path model approach to Structural Equation Modeling (SEM) was applied to test the research question (Chin 1998). The choice of PLS was justified by two aspects: First, compared to covariance structure analysis, PLS can accommodate both reflective and formative scales easily. Second, PLS does not require any prior distributional assumptions and a relatively small sample size is acceptable (Chin et al. 2003). Specifically, WarpPLS 3.0 (Kock 2011) was used for the measurement models analysis and the structural model analysis. RESULTS To assess the constructs’ measurement properties, we conducted confirmatory factor analysis (CFA) using PLS. Based on the CFA results, we analyzed convergent validity, discriminant validity, and the reliability of all the multiple-item scales, following the guidelines from the prior literature (e.g., Fornell and Larcker 1981). The measurement properties are reported in Table 1 and Table 2. JIBC April 2015, Vol. 20, No. 1 - 9 - Table 1: Reliability and Validity Reflective Variables Variable All Men Women Performance Expectancy (Venkatesh et al. 2012) All: AVE:0.872 CR:0.953 CA:0.926 Men: AVE:0.857 CR:0.947 CA:0.917 Women: AVE: 0.800 CR: 0.923 CA: 0.875 I find internet banking useful in my daily life. 0.920 0.912 0.859 Using internet banking helps me accomplish things more quickly 0.949 0.944 0.913 Using internet banking increases my productivity. 0.932 0.921 0.910 Effort Expectancy (Venkatesh et al. 2012) All: AVE:0.827 CR:0.950 CA:0.929 Men: AVE:0.805 CR:0.943 CA:0.918 Women: AVE: 0.757 CR: 0.925 CA: 0.891 Learning how to use internet banking is easy for me. 0.918 0.902 0.872 My interaction with internet banking is clear and understandable. 0.934 0.902 0.881 I find internet banking easy to use. 0.953 0.951 0.935 It is easy for me to become skillful at using internet banking. 0.827 0.806 0.785 Social Influence (Venkatesh et al. 2012) All: AVE: 0.923 CR:0.973 CA:0.958 Men: AVE:0.925 CR:0.974 CA:0.959 Women: AVE:0.905 CR:0.966 CA:0.948 People who are important to me think that I should use Internet banking 0.955 0.957 0.944 People who influence my behavior think that I should use internet banking. 0.964 0.969 0.966 People whose opinions I value prefer that I use Internet banking 0.964 0.958 0.944 Facilitating Conditions (Venkatesh et al. 2012) All: AVE: 0.724 CR:0.912 CA:0.870 Men: AVE:0.739 CR:0.919 CA:0.881 Women: AVE:0.693 CR:0.900 CA:0.852 I have the resources necessary to use Internet banking. 0.875 0.855 0.786 I have the knowledge necessary to use Internet banking. 0.900 0.889 0.853 Internet banking is compatible with other technologies I use. 0.902 0.889 0.865 I can get help from others when I have difficulties using Internet banking. 0.712 0.783 0.824 Hedonic Motivation (Venkatesh et al. 2012) All: AVE: 0.948 CR:0.982 CA:0.972 Men: AVE:0.950 CR:0.983 CA:0.973 Women: AVE:0.918 CR:0.971 CA:0.955 Using Internet banking is fun. 0.973 0.974 0.970 Using Internet banking is enjoyable. 0.984 0.985 0.977 Using Internet banking is very entertaining. 0.964 0.965 0.926 Habit (Venkatesh et al. 2012) All: AVE: 0.730 CR: 0.890 CA:0.814 Men: AVE:0.724 CR:0.887 CA:0.809 Women: AVE:0.731 CR:0.891 CA:0.815 The use of Internet banking has become a habit for me. 0.871 0.865 0.891 I am addicted to using Internet banking. 0.821 0.826 0.810 I must use Internet banking. 0.869 0.861 0.862 Price/Value (Lockett and All: AVE: 0.588 CR: 0.809 CA: 0.643 Men: AVE:0.576 CR:0.800 CA:0.621 Women: AVE:0.600 CR:0.817 CA:0.660 JIBC April 2015, Vol. 20, No. 1 - 16 - 2010). Banks should emphasize the convenience that Internet banking can provide to the elderly, such as having to go to the bank´s branches or avoiding long queues. Similarly, this fact makes the adaption of the Webpages necessary in terms of design, in order for them to be a friendly and easier environment to operate in. Website design should be very simple and should improve the clarity, visibility and navigability for customers to be able to easily operate. If banks segment the market, they can focus on the elderly’s needs and preferences. In this line, it seems reasonable to consider that the success of IB could be in the personalization of services to attract the segment of the elderly. Finally, regarding our results, we would like to offer some suggestions to practitioners. The results point out that habit (H) has a direct effect on IB use and H limits the strength of the relationship between behavior intention and the elderly’s IB use. To increase their habitual use, the resistance of older adults to a change in their way of accessing services can be achieved by reducing the perceived risk in the purchase (Lichtenstein and Williamson, 2006; Martins et al. 2014; Tai and Ku, 2013; Yu, 2012). Likewise, to properly communicate the advantages from use and promote a continuous Internet use, providers can offer discounts, gifts, contests or add other services, such as cultural offers, trips etc., which are positively valued by elderly. As an effect of a greater use, PE and EE would be increased. With respect to the effect of PE on BI, banks should underscore the usefulness of IB services. Possible improvements of PE could come from incorporating new applications which offer users value added. For example, to connect specific family finance management applications with the information available in their bank accounts. This type of applications would provide the user with a greater productivity, offering a fast and useful value added service. Regarding EE, a bank must be interested in their customers perceiving that online activities in their financial decisions are easy and that a minimum of experience leads them to be highly confident in their use of these tools. A way of doing so could be via improvements in the web design, seeking the optimization of its usability and aesthetics (Sanchez-Franco and Martín-Velicia, 2011), especially in the case of the elderly, who are digital natives and who have physical and motor constraints. Regarding price value, banks should, due to its influence on behavior intention (BI), remove any kind of doubts about there being a higher price or commissions being charged for using IB. Banks should emphasize cost savings, such online banking as reducing transaction costs sing. On the contrary, they should stress the idea of the system being free, as well as implementing better conditions for online customers whenever possible. CONCLUSIONS, LIMITATIONS AND FURTHER RESEARCH IB offers advantages for the elderly: 24 hour access, versatility, independence and the possibility of overcoming the physical barriers of age in accessing services. Elderly people are a growing segment today and present different characteristics from the rest of the population (more free time, greater freedom in their economic and financial JIBC April 2015, Vol. 20, No. 1 - 17 - decisions and less use of Internet and other ICTs). In this market, banks need to better understand the new type of relationship that the use of Internet generates and how the elderly accept and use this system. According to the results obtained, habit is a key element in IB. Given the importance of habit for use, as well as behavior intention, it would be interesting to go more deeply into the antecedents of this construct. This work must be considered as a first step in the understanding of grey IB. The difficulty of collecting data from the elderly led us to those members of the population that were at our disposal - our sample has been gathered without considering a probabilistic approach. Although the sample is diverse and the proportion of sociodemographics present in the population is consistent with the distribution of the sample used, a convenience sample must be understood as a first approach which calls for a more thorough analysis of this group. JIBC April 2015, Vol. 20, No. 1 - 18 - REFERENCES AbuShanab, E., Pearson, J., Setterstrom, A., (2010). Internet banking and customers’ acceptance in Jordan: the unified model´s perspective. Communications of the Association for Information Systems 26, article 23. Ainin, S., Lim, C.H., Wee, A., (2005). 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