Abstracts
Abstract
The use of e-textbooks has become popular in certain countries, yet there is debate in the literature about whether it is advantageous to adopt e-textbooks and if they positively influence students’ learning and performance. Prior studies on the acceptance of e-textbooks were mainly based on one theoretical perspective, and did not differentiate samples between experienced and inexperienced users. From a social- and task-related view, this study aims to identify the critical factors that stimulate acceptance intentions of e-textbooks among tertiary students, particularly between experienced and inexperienced users. Based on 912 questionnaires, this study found that performance expectancy, perceived enjoyment, and perceived task-technology fit are the factors affecting students’ behavioral intention for acceptance in both sampling groups. However, social impact only has significant influence on acceptance intention of inexperienced users. Also, gender has a moderating effect on the relationship of performance expectancy and behavioral intention of inexperienced users only. This study provides useful implications for marketing e-textbooks, and fills the literature gap.
Keywords:
- e-textbooks,
- technology acceptance,
- perceived task-technology fit,
- higher education,
- perceived cost
Appendices
Bibliography
- Agarwal, R., & Prasad, J. (1997). The role of innovation characteristics and perceived voluntariness in the acceptance of information technologies. Decision Sciences, 28(3), 557-582.
- Agarwal, R., & Karahanna, E. (2000). Time flies when you're having fun: Cognitive absorption and beliefs about information technology usage. MIS Quarterly, 24(4), 665-694.
- Al-Ali, S., & Ahmed, A. (2015). E-textbooks in ESL classrooms: Are learners on board? Learning and Teaching in Higher Education: Gulf Perspectives, 12(2). Retrieved from http://lthe.zu.ac.ae/index.php/lthehome/issue/view/13
- Amoroso, D. L., & Hunsinger, D. S. (2009). Understanding consumers' acceptance of online purchasing. Journal of Information Technology Management, 10(1), 15-41.
- Baker, E. W., Al-Gahtani, S. S., & Hubona, G. S. (2010). Cultural impacts on acceptance and adoption of information technology in a developing country. Journal of Global Information Management, 18(3), 35-58.
- Boroughs, D. (2010, April). Bye the book: In educational publishing, the only certainty is change. Retrieved from http://www.prism-magazine.org/apr10/feature_01.cfm
- Bruner II, G. C., & Kumar, A. (2005). Explaining consumer acceptance of handheld internet devices. Journal of Business Research, 58(5), 553-558.
- Chen, P. Y., & Hitt, L. M. (2002). Measuring switching costs and the determinants of customer retention in Internet-enabled businesses: A study of the online brokerage industry. Information Systems Research, 13(30), 255-274.
- Chung, J., & Tan, F. B. (2004). Antecedents of perceived playfulness: An exploratory study on user acceptance of general information-searching websites. Information & Management, 41(7), 869-881.
- Clough, G., Jones, A. C., McAndrew, P., & Scanlon, E. (2008). Informal learning with PDAs and smartphones. Journal of Computer Assisted Learning, 24(5), 359-371.
- Dasgupta, S., Haddad, M., Weiss, P., & Bermudez, E. (2007). User acceptance of CASE tools in systems analysis and design: An empirical study. Journal of Informatics Education Research, 9(1), 51-78.
- Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13(3), 319-339.
- Davis, F. D., Bagozzi, R. P., & Warshaw, P. R. (1992). Extrinsic and intrinsic motivation to use computers in the workplace. Journal of Applied Social Psychology, 22(1), 1111-1132.
- Dennis, A. R., Abaci, S., Morrone, A. S., Plaskoff, J., & McNamara, K. (2016). Effects of e-textbook instructor annotations on learner performance. Journal of Computing in Higher Education, 28(2), 221-235.
- Fischer, L., Hilton, J., Robinson, T. J., & Wiley, D. A. (2015). A multi-institutional study of the impact of open textbook adoption on the learning outcomes of post-secondary students. Journal of Computing in Higher Education, 27(3), 159-172.
- Fishbein, M., & Ajzen, I. (1975). Belief, attitude, intention, and behavior: An introduction to theory and research. Reading, MA: Addison-Wesley Pub. Co.
- Gerhart, N., Peak, D., & Prybutok, V. (2015). Searching for new answers: The application of task-technology fit to e-textbook usage. Decision Sciences Journal of Innovative Education, 13(1), 91-111.
- Goodhue, D. L., & Thompson, R. L. (1995). Task-technology fit and individual performance. MIS Quarterly, 19(1), 213-236.
- Gu, X., Wu, B., & Xu, X. (2015). Design, development, and learning in e-Textbooks: What we learned and where we are going. Journal of Computers in Education, 2(1), 25-41.
- Gurung, R. A. R., & Daniel, D. (2005). Do text-based pedagogical features enhance student learning? In D. S. Dunn, & S. L. Chew (Eds.), Best practices for teaching introduction to psychology (pp. 41-55). New Jersey: Lawrence Erlbaum.
- Hair, J. F., Black, W. C., Babin, B. J., & Anderson, R. E. (2010). Multivariate data analysis - A global perspective. New Jersey: Pearson Education.
- Harrison, D. A., Mykytyn, P. P., & Riemenschneider, C. K. (1997). Executive decisions about adoption of information technology in small business: Theory and empirical tests. Information Systems Research, 8(2), 171-195.
- Hsiao, C. H., Tang, K. Y., & Lin, C. H. (2015). Exploring college students' intention to adopt e-textbooks: A modified technology acceptance model. Libri, 65(2), 119-128.
- Isa, S. M., & Wong, K. Y. (2015). Age differences in behavioral intention to use internet marketing: A comparative study between Malaysian and Taiwanese. International Journal of Business & Society, 16(3), 386-396.
- Johnston, D., Berg, S., Pillon, K., & Williams, M. (2015). Ease of use and usefulness as measures of student experience in a multi-platform e-textbook pilot. Library Hi Tech, 33(1), 65-82.
- Kaba, B., & Touré, B. (2014). Understanding information and communication technology behavioral intention to use: Applying the UTAUT model to social networking site adoption by young people in a least developed country. Journal of the Association for Information Science & Technology, 65(8), 1662-1674.
- Karahanna, E., Straub, D. W., & Chervany, N. L. (1999). Information technology adoption across time: A cross-sectional comparison of pre-adoption and post-adoption beliefs. MIS Quarterly, 23(2), 183-213.
- Kohnke, A., Cole, M., & Bush, R. (2014). Incorporating UTAUT predictors for understanding home care patients' and clinician's acceptance of healthcare telemedicine equipment. Journal of Technology Management & Innovation, 9(2), 29-41.
- Kuo, R. Z. (2011). Knowledge management system adoption: Exploring the effects of empowering leadership, task-technology fit and compatibility. Behaviour & Information Technology, 30(1), 113-129.
- Lai, J. Y., & Ulhas, K. R. (2012). Understanding acceptance of dedicated e-textbook applications for learning: Involving Taiwanese university students. The Electronic Library, 30(3), 321-338.
- Lee, M. K. O., Cheung, C. M. K., & Chen, Z. (2005). Acceptance of Internet-based learning medium: The role of extrinsic and intrinsic motivation. Information & Management, 42(8), 1095-1104.
- Lin, T. C., & Huang, C. C. (2008). Understanding knowledge management system usage antecedents: An integration of social cognitive theory and task technology fit. Information & Management, 45(6), 410-417.
- Liu, W. Y., & Tsai, C. H. (2011). An application of the UTAUT model for understanding learning management systems adoption of college teachers. Journal of Performance and Strategy Research, 8(2), 49-60.
- Marcolin, B. L., Compeau, D. R., Munro, M. C., & Huff, S. L. (2000). Assessing user competence: Conceptualization and measurement. Information Systems Research, 11(1), 37-60.
- Mathieson, K. (1991). Predicting user intentions: Comparing the technology acceptance model with the theory of planned behavior. Information Systems Research, 2(3), 173-191.
- Maynard, S., & Cheyne, E. (2005). Can electronic textbooks help children to learn? The Electronic Library, 23(1), 103-115.
- Moon, J. W., & Kim, Y. G. (2001). Extending the TAM for a world-wide web context. Information & Management, 38(1), 217-230.
- Moore, G. C., & Benbasat, I. (1991). Development of an instrument to measure the perceptions of adopting an information technology innovation. Information Systems Research, 2(3), 192-222.
- Ngafeeson, M. N., & Sun, J. (2015). The effects of technology innovativeness and system exposure on student acceptance of e-textbooks. Journal of Information Technology Education: Research, 14, 55-71.
- Pai, J. C., & Tu, F. M. (2011). The acceptance and use of customer relationship management (CRM) systems: An empirical study of distribution service industry in Taiwan. Expert Systems with Applications, 38(1), 579-584.
- Shin, S., Chung, N., Hart, R. J., Joun, Y., & Koo, C. (2015). Examining technology perception and user competence on two types of smartphone usages. In Proceedings of the Pacific Asia Conference on Information Systems (PACIS) 2015 (p. 105). Retrieved from http://aisel.aisnet.org/pacis2015/105/
- Stone, R. W., & Baker-Eveleth, L. (2013). Students' expectation, confirmation, and continuance intention to use electronic textbooks. Computers in Human Behavior, 29(3), 984-990.
- Szajna, B. (1996). Empirical evaluation of the revised technology acceptance model. Management Science, 42(1), 85-92.
- Thompson, R. L., Higgins, C. A., & Howell, J. M. (1991). Personal computing: Toward a conceptual model of utilization. MIS Quarterly, 15(1), 124-143.
- Van der Heijden, H. (2004). User acceptance of hedonic information systems. MIS Quarterly, 28(4), 695-704.
- Venkatesh, V., Brown, S. A., Maruping, L. M., & Bala, H. (2008). Predicting different conceptualizations of system use: The competing roles of behavioral intention, facilitating conditions, and behavioral expectation. MIS Quarterly, 32(3), 483-502.
- Venkatesh, V., & Davis, F. D. (2000). A theoretical extension of the technology acceptance model: Four longitudinal field studies. Management Science, 46(2), 186-204.
- Venkatesh, V., & Morris, M. G. (2000). Why don't men ever stop to ask for directions? Gender, social influence, and their role in technology acceptance and usage behavior. MIS Quarterly, 24(1), 115-139.
- Venkatesh,V., Morris, M. G., & Ackerman, P. L. (2000). A longitudinal field investigation of gender differences in individual technology adoption decision making processes. Organizational Behavior and Human Decision Processes, 83(1), 33-60.
- Venkatesh, V., Morris, M. G., Davis, G. B., & Davis, F. D. (2003). User acceptance of information technology: Toward a unified view. MIS Quarterly, 27(1), 425-478.
- Venkatesh, V., Thong, J. Y. L., & Xu, X. (2012). Consumer acceptance and use of information technology: Extending the unified theory of acceptance and use of technology. MIS Quarterly, 36(1), 157-178.
- Vessey, I. (1991). Cognitive fit: A theory-based analysis of the graphs versus tables literature. Decision Sciences, 22(2), 219-240.
- Wang, H. I., & Yang, H. L. (2005). The role of personality traits in UTAUT model under online stocking. Contemporary Management Research, 1(1), 69-82.
- Woody, W. D., Daniel, D. B., & Baker, C. A. (2010). E-books or textbooks: Students prefer textbooks. Computers & Education, 55(3), 945-948.
- Wu, J. H., & Wang, S. C. (2005). What drives mobile commerce? An empirical evaluation of the revised technology acceptance model. Information & Management, 42(5), 719-729.
- Young, J. R. (2001). A university that reveres tradition experiments with e-books. The Chronicle of Higher Education, 47(36), 35-46.
- Zhou, T., Lu, Y., & Wang, B. (2010). Integrating TTF and UTAUT to explain mobile banking user adoption. Computers in Human Behavior, 26(4), 760-767.