Association for Information Systems AIS Electronic Library (AISeL) PACIS 2016 Proceedings Pacific Asia Conference on Information Systems (PACIS) Summer 6-27-2016 USE AND UPTAKE OF E-BOOKS IN THE LENS OF UNIFIED THEORY OF ACCEPTANCE AND USE OF TECHNOLOGY Dong Kyoon Yoo Virginia State University, dyoo@vsu.edu James Jungbae Roh Rowan University, roh@rowan.edu Follow this and additional works at: http://aisel.aisnet.org/pacis2016 Recommended Citation Yoo, Dong Kyoon and Roh, James Jungbae, "USE AND UPTAKE OF E-BOOKS IN THE LENS OF UNIFIED THEORY OF ACCEPTANCE AND USE OF TECHNOLOGY" (2016). PACIS 2016 Proceedings. 125. http://aisel.aisnet.org/pacis2016/125 This material is brought to you by the Pacific Asia Conference on Information Systems (PACIS) at AIS Electronic Library (AISeL). It has been accepted for inclusion in PACIS 2016 Proceedings by an authorized administrator of AIS Electronic Library (AISeL). For more information, please contact elibrary@aisnet.org.
USE AND UPTAKE OF E-BOOKS IN THE LENS OF UNIFIED THEORY OF ACCEPTANCE AND USE OF TECHNOLOGY Dong Kyoon Yoo, Reginald F. Lewis School of Business, Virginia State University, Petersburg, VA, USA, dyoo@vsu.edu James Jungbae Roh, Rohrer College of Business, Rowan University, Glassboro, NJ, USA, roh@rowan.edu Abstract As digital penetration is accelerated, consumers have been exposed to a variety of digital content. As such, a projection is suggested that printed books will lose the battle and be rendered obsolete with e- books cost-effectiveness and ubiquity. By contrast, there is a prediction that consumers will still prefer printed books for intensive reading and rather use e-books just for fun and pleasure. To respond to the research call, this study examines why and how individuals adopt and use e-books in the digital innovation era by utilizing the theory of UTAUT together with cognitive judgmental processes. The survey methodology with 1,419 consumers was used to test the research model by employing structural equation modeling. The results of the study show that performance expectancy, effort expectancy, and facilitating conditions are critical to the adoption and use of e-books. Gender, age, and experience have no moderating impacts in this study. Job relevance, result demonstrability, and effort expectancy have a positive impact on performance expectancy. Output quality shows a moderating influence between job relevance and performance expectancy. This study also discusses theoretical and practical implications by bridging every-changing consumer technology use and users cognitive impact with the case of e- books. Keywords: e-books, Consumer Information Technology, Unified Theory of Acceptance and Use of Technology, Cognitive Judgmental Processes, Technology Mediated Learning
1 INTRODUCTION Many of the consumers, organizations, and the government have been adopting and using digital content as e-books bring lower prices, convenient access together with mobile Internet technology, and increasing availability of e-content (Bansal 2011; Yu et al. 2011; Hao & Fan 2014). An e-book, described as a digital object with textual and other content in an electronic environment, has tremendously evolved with functionality, such as interactive tools, hypertext links, bookmarks, search, cross-reference functions, highlights, or annotations, as well as a variety of topics and subjects. As the digital penetration and transformation accelerate in the information age, some argue that printed books will be rendered obsolete due to consumers growing interactions with digital contents ubiquitously. Others, on the other hand, contend that users continue to prefer printed books for intensive reading, but use e-content just for pleasure and fun (Torres et al. 2014; Gaurav et al. 2010). This assertion is grounded on the notion that individuals already have pre-established schema with papers rather than digitals. In other words, individuals perceive the mitigation of their cognitive load from the familiarity of printed books as opposed to e-books tending to skim digital content without mental absorption (Baron 2015). As part of this arguments, some studies show that users are likely to use printed book if a price is not a factor (Rosenwald 2015). Although e-books have provided consumers with cost effectiveness and convenience, it is also apparent that a large number of individuals still weigh between e-books and printed books or between digital advances and traditional cognitive scheme. It leads a call to examine what makes users adopt e-books and how the process is enhanced in a more holistic approach. Despite e-books significance in the digital era, studies exploring users technology acceptance in the context is surprisingly scarce in the IS field. Given that mobile devices with mobile Internet technology have exponentially advanced in functions, design, and services, a transition to e-books has been facilitated rapidly. Therefore, understanding dynamics of the adoption and use of e-books will be of great interest and value to both academic and practical communities. Theories of technology acceptance have been developed in the literature, explaining human-computer interactions. Of theories developed, the unified theory of acceptance and use of technology (UTAUT) has integrated eight models illustrating users intention and use of technology (Venkatesh et al. 2003). Grounded upon the robust theory, the purpose of this study is to tailor UTAUT into the use and uptake of e-books along with four cognitive judgmental processes in the technology-mediated learning (TML) context. Just as there is much to be learned in the area of the adoption and use of e-books, so this study contributes to the literature by shedding light on the development of proper strategies for the use of e- books. 2 ADAPTING UTAUT INTO THE E-BOOK CONTEXT UTAUT was developed by integrating eight models of technology acceptance, namely, the theory of reasoned action (TRA) (Fishbein & Ajzen 1975), the technology acceptance model (TAM) (Davis 1989), TAM2 (Venkatesh & Davis 2000), the motivation model (Davis et al. 1992), the theory of planned behavior (TPB) (Ajzen 1991), the combined TAM and TPB (Taylor & Todd 1995), the model of PC utilization (Thompson et al. 1991), innovation diffusion theory (Rogers 1995), social cognitive theory (Bandura 1986) as part of predicting individuals adoption and use of information technology. UTAUT initially consists of four main constructs (i.e. performance expectancy, effort expectancy, social influence, and facilitating conditions) with four moderators (i.e., gender, age, experience, and voluntariness) (Venkatesh et al. 2003). Over the years, the theory has been tested in different contexts such as consumer technology use (Venkatesh et al. 2012), different cultures (Gupta et al. 2008; Im et al. 2011), healthcare (Chang et al. 2007; Shibl et al. 2013), mobile technology (Lu et al. 2009), e- government (Chan et al. 2010), and online blogs (Parameswaran et al. 2015). While progressing on the UTAUT structure, studies have adopted the replication or a subset of the entire model as underpinning of the study. UTAUT has also been extended by adding additional constructs, removing some or all of
the moderating variables, and adding more social-demographic variables (Venkatesh et al. 2012; McKenna et al. 2013; Niehaves & Plattfaut 2014). Overall, the literature acknowledges that UTAUT provides a solid theoretical foundation for technology acceptance studies (Brown et al. 2010). Also, the literature directs researchers to investigate the interplay of UTAUT with other research streams (Brown et al. 2010; Venkatesh et al. 2012; Lancelot Miltgen et al. 2013). Based upon the well-grounded theory and the literature review, this study makes a contribution to examining how and why individuals adopt and use e-books in the digital innovation area. Performance expectancy is introduced as the first construct of UTAUT. This construct indicates that users adopt new information systems as they believe the technology will increase effectiveness for the completion of their task. The notion is depicted as the degree to which using a technology will provide the benefits to consumers in performing certain activities (Venkatesh et al. 2012). In other words, users assess salient benefits when accepting and using technology, and the extrinsic motivation plays a pivotal role in engaging in the exploration of new information systems. The construct is also termed as perceived usefulness, extrinsic motivation, job-fit, relative advantage, or outcome expectations in the literature (Brown et al. 2010; Niehaves & Plattfaut 2014). It is also worth noting that research has consistently found that the construct is the strongest predictor of behavioral intention (Venkatesh et al. 2012; Shibl et al. 2013). It illustrates that individuals are willing to use e-books when they apparently see utility in conjunction with their performance expectation and further improvement. Effort expectancy describes ease in view of using technology. This construct has a close relationship with complexity, and users see any type of technology unfavorable if it is too complicated to adopt and use it. It was defined as the degree to which ease associated with consumers use of technology (Venkatesh et al. 2012). Research has shown that effort expectancy is conceptually and empirically associated with perceived ease of use from technology acceptance model (TAM). Some studies argue that effort expectancy is particularly significant in the context of consumer technology use as opposed to organizational members who have systematic support for their use (Venkatesh & Bala 2008; Brown et al. 2010). The uptake of e-books, a typical case of consumer technology implementation, is attributed to effort expectation as users assess the value of ubiquity and interactive tools (e.g., fast searchers or cross-references) and increase their likelihood of using it at their convenience. UTAUT has presented social influence, also referred to as subjective norm, social factors, or image in the literature, in light of predicting intention to use information systems. This concept is described as an individuals perception that important others believe he/she has to use a particular technology. Intriguing results have been found that the impact of social influence is significant in the mandatory setting, but not in the voluntary use (Venkatesh & Davis 2000; Venkatesh et al. 2003). Due to a shift from printed to digital contents, consumers are exposed to the terrain of e-reading, and the move has been done on a voluntary basis. The last construct of UTAUT is facilitating conditions, which are depicted as consumers perception of the resources and support available to perform a behavior (Venkatesh et al. 2012). This concept is related to behavioral control or compatibility in the literature. Originally, this notion was not a predictor to behavioral intention, but rather a direct impact on technology use (Venkatesh et al. 2003). Research, however, extends that facilitating conditions are also a critical determinant to explaining the variance of behavioral intention (Venkatesh et al. 2012). The relationship between intention to use and actual system use have been well established in the literature, and its theoretical grounding is also well discussed in the prior studies (Venkatesh et al. 2003; Brown et al. 2010). This present study includes e-book use as the ultimate dependent variable, and we hypothesizes that behavioral intention will have a positive impact on actual use. Taken together, this research, shown in Figure 1, is based upon UTAUT with some adaptations for this study. H1a: Performance expectancy, effort expectancy, and facilitating conditions about e-books have positive impacts on users intentions to adopt it. H1b: Social influence about e-books has no impact on users intentions to adopt it.
H2a: Behavioral intention to use e-books has a positive impact on usage. H2b: Facilitating conditions about e-books have a positive impact on usage. Job Relevance Performance Expectancy Output Quality Effort Expectancy Intention to Use Use Behavior Result Demonstrability Social Influence Facilitating Conditions Gender Age Experience Figure 1. Research framework explaining the adoption and use of e-books Four moderating variables such as gender, age, and experience and voluntariness of use have been employed for UTAUT (Venkatesh et al. 2003). As noted above, some studies tested no moderating variable or added social demographic variables to examine technology adoption (Venkatesh et al. 2012; McKenna et al. 2013; Lancelot Miltgen et al. 2013). Particularly in the context of consumer technology use, voluntariness is removed as individuals choose information systems for their own preference (Venkatesh et al. 2012). For that reason, this study uses gender, age, and experience only and tests their moderating impacts on the structure of UTAUT. While gender was predicted to influence three of UTAUT (i.e. performance expectancy, effort expectancy, and social influence) in the organizational setting (Venkatesh et al. 2003), the variable s impact was expanded to test its moderating relationship between facilitating conditions and behavioral intention in UTAUT2 (Venkatesh et al. 2012) which was undertaken in the consumer technology use context. This study, however, argues that gender moderates none of the four UTAUT predictors. Gender schema theory, explaining gender roles and socialization processes, has been used to logically support the moderating role of gender (Venkatesh et al. 2003, 2012; Brown et al. 2010). For instance, men are highly task-oriented and spend more effort than women to face constraints and challenges in pursuit of goals (Venkatesh et al. 2012). Also, the theory illustrates that women are more sensitive to others opinions (Venkatesh & Morris 2000). On the other hand, research has been progressed on gender bias in the society, and studies argues that women are compatible with masculine or male-dominated roles (Koch et al. 2015) and that women persist as much as men and do even more with male counterparts (Bowles & Flynn 2010). Additionally, statistics show that female are more likely than males to earn high-school and bachelor s degrees and beyond, and that the trend has been steadily increasing over the past 30 years (Aud et al. 2011; Koch et al. 2015). As technology becomes more and more pervasive
especially in e-books, the impact of gender is biased, and thus this study test that gender will moderate no variable in the structure of UTAUT. H3: Gender will not moderate the influence of performance expectancy, effort expectancy, social influence, and facilitating conditions on behavioral intention to use e-books. Age is also part of moderating variables for the intention to use technology outlined in UTAUT, and the impact was extend in the relationship between facilitating conditions and behavioral intention in the test of UTAUT2. The overall argument of age and technology acceptance stems from aging cognitive and memory capabilities, indicating that older people, more than younger generations, have a challenge to adopt new ways of doing despite technology advances (Morris et al. 2005; Venkatesh et al. 2012). It increases the likelihood that their habits shaped over the years deter new attempts to learn new information systems and change their behavior. As a matter of fact, the IS literature has acknowledged the status quo perspective that people have a tendency to remain in existing ways of doing even in the presence of better alternatives (Polites & Karahanna 2012). As such, in the context of e-books, older people may prefer printed books in part because their mindset and habit have already been established in the printed format. That is, they would find themselves in lowering cognitive load and gaining a perception of control in the printed book. By contrast, younger people are more likely to use a digital format with the propensity of accepting new technology and new ways. H4: Age will moderate the influence of performance expectancy, effort expectancy, social influence, and facilitating conditions on behavioral intention to use e-books. Like other variables above, experience was first examined to see if there is a moderating impact on the three constructs (i.e. effort expectancy, social influence, and facilitating conditions) of UTAUT, and it was then extended for facilitating conditions and use in the consumer technology context of UTAUT2. It is rather certain that users will be more familiar with operations and dynamics with more experiences, which also enable users to find multiple sources of support. Users weigh benefits against efforts required in light of using information systems, and experience will enhance a sufficient level of knowledge, skill, and abilities and thus remove hurdles to use. Experiences make it clear about contextual cues and lead user to engage in information systems. H5a: Experience will moderate the influence of effort expectancy, social influence, and facilitating conditions on behavioral intention to use e-books. H5b: Experience will moderate the influence of facilitating conditions on use behavior. H5c: Experience will moderate the influence of behavioral intention on use behavior. Drawing upon work motivation theory, action theory, and behavioral theory, four cognitive instrumental processes, designed to assess benefits and usefulness of information systems, were theorized: job relevance, output quality, result demonstrability, and perceived ease of use (Venkatesh & Davis 2000). These elements are essential to elaborating on the adoption and use of e-books since users go through judgmental processes of weighing pros and cons of digital contents. Cognitive matching plays a critical role in generating a positive or negative drive for decisions on the uptake of information systems. Also, the literature consistently indicates that performance expectancy is the strongest predictor to influence behavioral intentions (Venkatesh et al. 2012; Shibl et al. 2013). As such, it is worth examining the variables and exploring their unique impacts on UTAUT particularly in the context of e-books. Consumers have a propensity to investigate the fit between capabilities of information technology and the nature of their goals and tasks. More to the point, consumers will choose e-books over printed books when they perceive that it is more useful and beneficial for their tasks. A component of this matching process is a consumer s sensitivity of job relevance, which is defined as an individual perception regarding the degree to which the target system is applicable to his or her job (Venkatesh & Davis 2000). Apparently, individuals are aware of the scope, cost, and time of their work, and subsequently attempt to assess what work can be done with the use of the information systems. If it is considered to be irrelevant or insufficient, users will not take them into consideration for their choice. If seen
otherwise, the target technology will be of great value and users are willing to engage in it. That is, people rely on the match between their job goals of reading and the consequence of e-books, and it is a foundation for their perception on performance expectancy. Because consumers want to make sense of what e-books are capable of performing and how the performing matches their goals, this study tests the following hypothesis: H6: Job relevance has a positive impact on performance expectance in the context of e-books. While job relevance describes how much information systems are capable of doing, there is also another angle assessing cognitive judgmental processes. Information systems should be evaluated by output quality, which measures how well information systems can perform tasks. Output quality is depicted as the degree to which an individual believes that the system performs his or her job tasks well (Venkatesh & Davis 2000). Studies have shown that the aspect of how much (i.e. job relevance), and how well (i.e. output quality) are critical cognitive elements in decision-makings. The literature also illustrates that output quality moderates the relationship between job relevance and performance expectancy (Venkatesh & Davis 2000). Following the literature, this study tests an interactive effect in the context of e-books. H7: Output quality moderates the relationship between job relevance and performance expectancy in the context of e-books. When results, produced by information systems, are not easy to understand or interpret, consumers are unlikely to recognize that the technology is useful for their work. This judgmental process was dubbed as result demonstrability, defined as tangibility of the results of using the innovation (Moore & Benbasat 1991). Result demonstrability is regarded as a key psychological state with work motivation (Venkatesh & Morris 2000; Venkatesh & Bala 2008), and the communicable, observable results will increase the likelihood of the perception that the use of the information systems will bring positive impacts. H8: Result demonstrability has a positive impact on performance expectance in the context of e-books. Of the four cognitive judgmental processes, perceived ease of use has been received wide attention in relation to perceived usefulness in the literature. When consumers feel ease of use in their information systems, they will be able to explore different features and maximize the technology s functionality. When users perceive that information systems require less effort, technology s usability will be enhanced and subsequently performance expectancy will be escalated (Brown et al. 2010). Accordingly, this study tests the following hypothesis, and Figure 1 describes a research model adapted from UTUAT along with cognitive matching processes. H9: Effort expectancy has a positive impact on performance expectance in the context of e- books. 3 RESEARCH METHODS The survey methodology was used to test the research model. SmartPLS 2.0 was employed to test the measurement and structural models. Instruments for performance expectancy, effort expectancy, social influence, facilitating conditions, and intention to use were adopted from Venkatesh et al. (2003, 2012). Items for job relevance, output quality, and result demonstrability were adopted from Venkatesh and Davis (2000). Because the present study was designed to examine the dynamics of the use and uptake of e-books, e-textbooks were particularly chosen. E-Textbooks require more attention for reading for a relatively long period of time, and this will be significant to examining the mechanism of the interaction between users and e-books. All items were asked to answer on a seven-point Likert scale where 1 was Strongly Disagree and 7 was Strongly Agree. Gender was used a dummy variable that was 0 for women and 1 for men. Age was measured in years. Experience was coded as an indicator variable with
the value of 0 for non-users and 1 for prior users. Use was measured with frequency of e-book use in a seven-point Likert scale. Appendix A shows survey instruments entering the large-scale survey. Data were collected from students at a Mid-Atlantic University. The survey invited 9,578 students, and 1,419 answered the online survey, resulting in a 14.82% response rate. To encourage participation, a prize drawing was offered in return for responding to the online survey. 3.1 Measurement Model To test the convergent and discriminant validity, confirmatory factor analysis was examined using SmartPLS 2.0. Table 1 describes item loadings which exceed the 0.70 threshold. Composite reliabilities and all the constructs AVE are good enough to meet the convergent validity. Discriminant validity was examined by comparing the square root of AVE to all associated correlations. Results, shown in Table 2, illustrate that all of the square root of AVE are greater than respective correlations. PE EE SI FC IU JR OQ RD PE1 0.902 0.580 0.274 0.240 0.576 0.545 0.567 0.270 PE2 0.879 0.551 0.285 0.218 0.511 0.532 0.563 0.301 PE3 0.832 0.456 0.261 0.217 0.709 0.565 0.356 0.230 EE1 0.548 0.892 0.194 0.189 0.431 0.393 0.571 0.277 EE2 0.601 0.898 0.222 0.236 0.540 0.418 0.512 0.239 EE3 0.402 0.822 0.138 0.126 0.350 0.290 0.407 0.196 SI1 0.288 0.195 0.880 0.033 0.187 0.268 0.239 0.163 SI2 0.246 0.176 0.831 0.016 0.160 0.214 0.207 0.143 FC1 0.233 0.200 0.030 0.873 0.217 0.168 0.146 0.036 FC2 0.209 0.172 0.020 0.837 0.200 0.193 0.158-0.019 IU1 0.644 0.496 0.204 0.209 0.946 0.547 0.386 0.226 IU2 0.652 0.486 0.203 0.235 0.958 0.559 0.375 0.224 IU3 0.662 0.484 0.169 0.246 0.927 0.578 0.364 0.237 JR1 0.623 0.415 0.287 0.210 0.575 0.937 0.521 0.335 JR2 0.538 0.379 0.234 0.176 0.524 0.915 0.458 0.292 OQ1 0.560 0.557 0.249 0.157 0.399 0.540 0.954 0.363 OQ2 0.511 0.536 0.246 0.180 0.353 0.465 0.944 0.365 RD1 0.155 0.125 0.132-0.134 0.076 0.173 0.236 0.719 RD2 0.319 0.294 0.168 0.081 0.276 0.355 0.381 0.942 PE: Performance Expectancy, EE: Effort Expectancy, SI: Social Influence, FC: Facilitating Conditions, IU: Intention to Use, JR: Job Relevance, OQ: Output Quality, RD: Result Demonstrability. Table 1. Item loadings of confirmatory factor analysis Composite Reliability PE EE SI FC IU JR OQ RD PE 0.904 0.871 EE 0.904 0.606 0.871 SI 0.845 0.313 0.217 0.856 FC 0.845 0.258 0.218 0.029 0.855 IU 0.961 0.692 0.518 0.203 0.244 0.944 JR 0.923 0.630 0.429 0.284 0.210 0.595 0.926 OQ 0.947 0.566 0.576 0.261 0.177 0.397 0.531 0.949 RD 0.822 0.305 0.275 0.180 0.012 0.243 0.340 0.384 0.838 Note: The diagonal elements in bold indicate the square root of AVE. PE: Performance Expectancy, EE: Effort Expectancy, SI: Social Influence, FC: Facilitating Conditions, IU: Intention to Use, JR: Job Relevance, OQ: Output Quality, RD: Result Demonstrability. Table 2. Descriptive statistics, correlations, and average variance extracted
3.2 Structural Model In pursuit of examining consumers adoption and use of e-books effectively, this study assembled three different models. While the full model included all the data collected from respondents, it was split into two different groups (i.e., consumers with and without prior e-book experience). This approach contributes to the literature by showing how the view of the non-experienced progressively changes in light of the e-book adoption. It will also increase the understating of how the non-experienced have a different mental scheme in term of interaction with new technology. While the overall structure of UTAUT is confirmed, social influence has no influence on behavioral intention, shown in Table 3. This finding is consistent across the full and the split-sample models, except that facilitating conditions in the group of no prior experience are not significant to behavioral intention. Therefore, H1a and H1b are generally supported by the results of the analysis. Statistical results also show that behavioral intention has a significant impact on actual use across all models and thus H2a is supported. For facilitating conditions, the construct is significant to actual use in the full model, supporting H2b. Gender, age, and experience have no moderating impact on relationships between the structure of UTAUT and behavioral intention. This implies that H3 is supported, but H4 and H5a are not statically supported. While experience shows no moderating impact between facilitating conditions and actual use, not supporting H5b, the variable has a significant moderating influence between intention to use and actual behavior, supporting H5c. In light of cognitive judgmental variables, job relevance, result demonstrability, and effort expectancy have statistical significance across the three models, supporting H6, H8, and H9. In particular, result demonstrability has an impact on performance expectancy in the full model and the non-experienced model, but is not significant to the group of the experienced. Output quality has a positive mediating impact on the relationship between job relevance and performance expectancy, supporting H7. The variance in intention to use explained by UTAUT with direct effects only were 50%, 65% and 40% respectively in the three models. Also, the variance in intention to use explained by UTAUT with moderating variables were 53%, 67%, and 41%. In case of the variance in performance expectancy with direct effects, 54%, 65%, and 39% were explained by cognitive judgmental processes. As for their moderating variables, 56%, 67%, and 42% were attributed to the variance in performance expectancy. DV: Intention to Use Full Data (N = 1,419) Consumers with Prior Experience (N = 636) Consumers with No Prior Experience (N = 783) D only D + I D only D + I D only D + I R 2.50.53.65.67.40.41 Adj. R 2.50.52.65.66.39.39 Performance Expectancy (PE).59**.56**.54**.54**.59**.58** Effort Expectancy (EE).15**.20**.30**.30**.07.08** Social Influence (SI) -.02 -.01.00.01 -.02 -.02 Facilitating Conditions (FC).06**.05**.06**.07**.04.04 Gender (GDR) -.20.70 -.23 Age (AGE) -.06 0.05 -.08* Experience (EXP) -.21* GDR AGE.21.03.24 AGE EXP.16 GDR EXP.07 GDR AGE EXP -.08 PE GDR.04.14.02 EE GDR.02.03.00 SI GDR.02.05.08 FC GDR -.13 -.05 -.04 PE AGE.05.04.06 EE AGE.01.05 -.02
SI AGE -.03 -.01 -.01 FC AGE -.02 -.03.01 EE EXP.11 SI EXP -.05 FC EXP.03 PE GDR AGE -.02 -.13 -.01 EE GDR AGE -.03 -.09 -.08 SI GDR AGE.00 -.04 -.07 FC GDR AGE.13.03.02 EE GDR EXP.03 SI GDR EXP.06 FC GDR EXP.14 EE AGE EXP.02 SI AGE EXP.06 FC AGE EXP -.01 EE GDR AGE EXP -.08 SI GDR AGE EXP -.08 FC GDR AGE EXP -.19 DV: Use D only D + I D only D + I D only D + I R 2.10.37.20.20.01.01 Adj. R 2.09.35.19.17.00-0.02 Intention to Use (IU).29**.22**.43**.43**.06.06 Facilitating Conditions (FC).09**.05**.05.07.07 Experience (EXP).49** IU EXP.19** FC EXP.00 DV: Performance Expectancy D only D + I D only D + I D only D + I R 2.54.56.65.67.39.42 Adj. R 2.54.55.65.66.38.40 Effort Expectancy (EE).40**.32**.42**.34**.36**.29** Job Relevance (JR).44**.40**.50**.44**.39**.36** Result Demonstrability (RD).04**.01.01.00.07**.04 Output Quality (OQ).19**.18**.16** JR OQ.12**.02.12** Note: ** Significant at α <.05 *** Significant α <.01 Table 3. Structural model results 4 DISCUSSIONS As studies on technology acceptance and use have been a vital theme in the IS literature, the research stream was conducted in the organizational setting and is also extending to consumers everyday computing. Particularly, UTAUT was developed to integrate eight models, and this study extends the theory into the specific context of e-books by altering the original conceptualization with cognitive judgmental processes. This study makes a contribution to better understanding consumers daily computing and the implication of UTAUT in the context of e-books. The results of the study show that performance expectancy is the key predictor to consumers intention to use e-books, and the finding is consistent across all models. The novelty of information systems would be a primary factor to attract users at the beginning, but the pragmatic functions and usefulness of information systems are the pivotal element to let individuals keep on using the technology (Venkatesh et al. 2012). In other words, consumers may utilize e-books out of curiosity at the early stage, but the
choice can be sustained when the technology properly serves their goals and objectives. The extrinsic motivation plays a critical role in adopting and using information systems. Effort expectancy is considered to be an important factor to adopt and use information systems, particularly consumer information technology. As described above, the full model supports the argument, explaining the perception of ease of use is a critical element in the use and uptake of e-books. In addition, the split-group analysis illustrates interesting statistical results that effort expectancy for the non-experienced is insignificant to behavioral intention. This could be interpreted that those who have not used e-books in the past still feel uncomfortable to utilize them for their tasks and that they are more likely to be aligned with printed format with their pre-existing cognitive schemes. Like other studies on UTAUT, social influence is not a contributing factor for e-book use. Given that e- books are widespread and mobile devices are part of a daily life, individuals choose to weigh in to discover advantages against disadvantages on their own instead of being affected by others decisions or opinions. Like prior studies, the variable has no impact on behavioral intention in the consumer technology context. While facilitating conditions are statistically significant to the full model, the split-sample analysis provides intriguing results as to fairly variant perceptions of different user groups. In the experienced group, the construct is significant to behavioral intention, but insignificant to actual use. In fact, facilitating conditions are less critical to experienced users intention to adopt and use e-books, compared to the path coefficients of performance expectancy and effort expectancy. Users with prior experiences may be well equipped with the overall pattern of the consumer context of technology use and thus facilitating conditions would be less important. Greater experience increases more familiarity with information systems, and they tend to depend on external support on a lesser degree (Venkatesh et al. 2012). The split-sample test of users with no prior experience illustrates that performance expectancy is the only significant variable in UTAUT and others are insignificant. This indeed suggests that the unexperienced prefer printed books over e-books, and it is much more effective to use existing ways for their goals and objectives. As a matter a fact, there were studies that users find printed books easy to concentrate when reading for work or even pleasure in print (Baron 2015), and that users are likely to use printed book if a price is not a factor (Rosenwald 2015). UTAUT introduced four moderating variables (i.e. gender, age, experience, and voluntariness) and later dropped voluntariness in the context of consumer technology use. The results of the study show that gender, age, and experience have no moderating impact on intention to use e-books. The literature has employed gender schema theory as part of illustrating gender roles and their socialization. In the context of consumer technology use, this study argues that there is no gender predictor to adopt and use information systems. Integrating cognitive judgmental constructs into UTAUT will complement the understanding of consumer information technology and help understand how consumers make a decision. The results of this study illustrates that job relevance is the strongest construct to affect performance expectancy. In determining usefulness in information systems, users assess what the technology is capable of and how much it can accomplish for their goals and objectives. The propensity is consistent across all models (i.e., all, experienced, and non-experienced groups). Users are willing to use e-books when it is viewed as effective and efficient. Also, the path coefficients indicates that the impact of job relevance on performance expectancy is bigger than that of effort expectancy. It could be interpreted that consumer information technology are relatively easier to use and users mentally evaluates its ability for their work. Result demonstrability illustrates interesting results in both experienced and non-experienced users. Individuals with experience do not see result demonstrability as a variable to influence usefulness, while the other group perceives it is critical to performance expectancy. When people are familiarized with structures of e-books, their mental scheme is already adjusted to the format and the tangible results from e-books are apparent. In a sense, that is why they have been using it without resistance. For those users,
job relevance is more important than result demonstrability. By contrast, people with no experience are still in need of formulating their scheme into the e-books context. Result demonstrability is regarded as a crucial variable for their cognitive judgment on usefulness. Output quality also shows similar patterns to result demonstrability. That is, it is significant as a moderating variable between job relevance and performance expectancy. However, when it comes to different users groups, the impact is different. While it is insignificant for the experienced, there is statistical influence for the non-experienced individuals. It illustrates that users with experiences are already familiarized with the format and structure of e-books and that output quality has minimal influences. By contrast, users with no prior experience consider output quality as an important aspect for effectiveness in adopting and using e-books. Overall, variables for cognitive judgmental processes complement UTAUT that emphasizes the use and uptake of information systems. 5 CONCLUSION Consumers are exposed to many different types of information systems, and they adopt and use them on a daily basis. Particularly, the functionality and accessibility of e-books have been tremendously progressed, and many people have been using them for their work anytime and anywhere. By contrast, the market research shows that many people still prefer printed books over e-books due to their preestablished schema. This study shows what aspects are critical to users adoption and uptake of e-books. In addition, this study illustrates the difference between the experienced and the non-experienced in light of their perception to e-books use. Given that research on consumer technology use should grow in scope, this study makes another step to the endeavor. In addition, the results of the study provide theoretical and practical implications. References Ajzen, I. (1991). The theory of planned behavior. Organizational Behavior and Human Decision Processes, 50 (2), 179 211. Aud, S., Hussar, W., Kena, G., Bianco, K., Frohlich, L., Kemp, J., and Tahan, K. (2011). The Condition of Education 2011 (NCES 2011-033). National Center for Education Statistics. Bandura, A. (1986). Social Foundations of Thought and Action: A Social Cognitive Theory. NJ, Prentice Hall, Englewood Cliffs. Bansal, G. (2011). e-book usage: Role of environmental consciousness, personality and past usage. Journal of Computer Information Systems, 52 (2), 93 104. Bansal, G., Zahedi, F.M. and Gefen, D. (2010). The impact of personal dispositions on information sensitivity, privacy concern and trust in disclosing health information online. Decision Support Systems, 49 (2), 138 150. Baron, N.S. (2015). Why reading on a screen is bad for critical thinking. The Huffington Post. Bowles, H.R. and Flynn, F. (2010). Gender and persistence in negotiation: A dyadic perspective. Academy of Management Journal, 53 (4), 769 787. Brown, S.A., Dennis, A.R. and Venkatesh, V. (2010). Predicting collaboration technology use: Integrating technology adoption and collaboration research. Journal of Management Information Systems, 27 (2), 9 54. Chan, F.K., Thong, J.Y., Venkatesh, V., Brown, S.A., Hu, P.J. and Tam, K.Y. (2010). Modeling citizen satisfaction with mandatory adoption of an e-government technology. Journal of the Association for Information Systems, 11 (10), 519 549. Chang, I.-C., Hwang, H.-G., Hung, W.-F., & Li, Y.-C. (2007). Physicians acceptance of pharmacokinetics-based clinical decision support systems. Expert Systems with Applications, 33 (2), 296 303. Davis, F.D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13 (3), 319 340.
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