Exploring determinants of early user acceptance for an audio-visual heritage archive service using the vignette method

References

• Agarwal, R., and Karahanna, E. 2000. Time flies when you're having fun: cognitive absorption and beliefs about information technology usage. MIS Quarterly, 24(4), 665–694. doi: 10.2307/3250951
   Web of Science ®Google Scholar
• Alexander, C. S., and Becker, H. J. 1978. The use of vignettes in survey research. Public Opinion Quarterly, 42(1), 93–104. doi: 10.1086/268432
   Web of Science ®Google Scholar
• Auffret, G., and Bachimont, B.. 1999.Audiovisual cultural heritage: from TV and radio archiving to hypermedia publishing. Proceedings of the third European conference and research and advanced technology for digital libraries. Berlin: Springer. 58–75
   Google Scholar
• Baaren, E., Van de Wijngaert, L., and Huizer, E. 2011. Understanding technology adoption through individual and context characteristics: the case of HDTV. Journal of Broadcasting & Electronic Media, 55(1), 72–89. doi: 10.1080/08838151.2011.546257
   Web of Science ®Google Scholar
• Barnett, T., Bass, K., and Brown, G. 1994. Ethical ideology and ethical judgment regarding ethical issues in business. Journal of Business Ethics, 13(6), 469–480. doi: 10.1007/BF00881456
   Web of Science ®Google Scholar
• Bellman, S., Lohse, G. L., and Johnson, E. J. 1999. Predictors of online buying behavior. Communications of the ACM, 42(12), 32–38. doi: 10.1145/322796.322805
   Web of Science ®Google Scholar
• Benbasat, I., and Barki, H. 2007. Quo vadis TAM?. Journal of the Association for Information Systems, 8(4), 211–218.
   Web of Science ®Google Scholar
• Bhattacherjee, A. 2001. Understanding information systems continuance: an expectation-confirmation model. MIS Quarterly, 25(3), 351–370. doi: 10.2307/3250921
   Web of Science ®Google Scholar
• Bhattacherjee, A., and Sanford, C. 2009. The intention–behaviour gap in technology usage: the moderating role of attitude strength. Behaviour & Information Technology, 28(4), 389–401. doi: 10.1080/01449290802121230
   Web of Science ®Google Scholar
• Caro, F., et al. 2012. Experiment choosing among residential options: results of a vignette experiment. Research on Aging, 34(1), 3–33. doi: 10.1177/0164027511404032
   Web of Science ®Google Scholar
• Chau, P. Y. K. 1996. An empirical assessment of a modified technology acceptance model. Journal of Management Information Systems, 13(2), 185–204.
   Google Scholar
• Chau, P. Y. K., and Lai, V. 2003. An empirical investigation of the determinations of user acceptance of Internet banking. Journal of Organizational Computing and Electronic Commerce, 13(2), 123–145. doi: 10.1207/S15327744JOCE1302_3
   Web of Science ®Google Scholar
• Conway, P. 1986. Facts and frameworks: an approach to studying the users of archives. The American Archivist, 49(4), 393–407.
   Google Scholar
• Courtois, C., Ongena, G., and Cannie, H. 2010. Funding the digitisation and unlocking of analogue audiovisual public service content: a look into Flanders and The Netherlands. Observatorio (OBS*) Journal, 4(1), 221–238.
   Google Scholar
• Daft, R. L., and Lengel, R. H. 1986. Organizational information requirements, media richness and structural design. Management Science, 32(5), 554–571. doi: 10.1287/mnsc.32.5.554
   Web of Science ®Google Scholar
• Davis, F. D. 1993. User acceptance of information technology: system characteristics, user perceptions and behavioral impacts. International Journal of Man-Machine Studies, 38(3), 475–487. doi: 10.1006/imms.1993.1022
   Google Scholar
• Davis, F. D., and Venkatesh, V. 2004. Toward preprototype user acceptance testing of new information systems: implications for software project management. IEEE Transactions on Engineering Management, 51(1), 31–46. doi: 10.1109/TEM.2003.822468
   Web of Science ®Google Scholar
• Dillon, A., and Morris, M. G. 1996. User acceptance of new information technology: theories and models. Review of Information Science, 31(4), 3–32.
   Google Scholar
• Gefen, D., and Straub, D. W. 2000. The relative importance of perceived ease of use in IS adoption: a study of e-commerce adoption. Journal of the Association for Information Systems, 1(8), 1–30.
   Google Scholar
• Henseler, J., Ringle, C. M., and Sinkovics, R. R. 2009. The use of partial least squares path modeling in international marketing. Advances in International Marketing, 20, 277–320. doi: 10.1108/S1474-7979(2009)0000020014
   Web of Science ®Google Scholar
• Hoffman, P. J. 1960. The paramorphic representation of clinical judgement. Psychological Bulletin, 57(2), 116–131. doi: 10.1037/h0047807
   PubMed Web of Science ®Google Scholar
• Hsu, M.-H., and Kuo, F.-Y. 2003. An investigation of volitional control in information ethics. Behaviour & Information Technology, 22(1), 53–62. doi: 10.1080/01449290301781
   Web of Science ®Google Scholar
• Ihlström Eriksson, C., and Svensson, J.. 2008. How to predict the future of an IT innovation?: examining pre-adoption of the e-newspaper. Proceedings of the 31st information systems research seminar in Scandinavia, Are, Sweden: The IRIS Association
   Google Scholar
• Jackson, C. M., Chow, S., and Leitch, R. A. 1997. Toward an understanding of the behavioral intentions to use an information system. Decision Sciences, 28(2), 357–389. doi: 10.1111/j.1540-5915.1997.tb01315.x
   Web of Science ®Google Scholar
• Jain, A., and Manviwalla, M., 2006. Preprototype perceived usefulness of a municipal wireless network: sources of variation among prospective users. Proceedings of the twelfth Americas conference on information systems, August4–6. Atlanta, GA: AIS Electronic Library. 764–771
   Google Scholar
• Jansen, J., Van de Wijngaert, L., and Pieterson, W., 2010. Channel choice and source choice of entrepreneurs in a public organizational context: the Dutch case. Proceedings of the 9th IFIP WG 8.5 international conference on Electronic government. Berlin: Springer. 144–155
   Google Scholar
• Jung, Y., Perez-Mira, B., and Wiley-Patton, S. 2009. Consumer adoption of mobile TV: examining psychological flow and media content. Computers in Human Behavior, 25(1), 123–129. doi: 10.1016/j.chb.2008.07.011
   Web of Science ®Google Scholar
• Karahanna, E., Straub, W., and Norman, L. 1999. Information technology adoption across time: a cross-sectional comparison of pre-adoption and post-adoption beliefs. MIS Quarterly, 23(2), 183–213. doi: 10.2307/249751
   Web of Science ®Google Scholar
• Karnowski, V., von Pape, T., and Wirth, W. 2011. Overcoming the binary logic of adoption: on the integration of diffusion of innovations theory and the concept of appropriation. In:. In Vishwanath, A., and Barnett, G. (Ed.), The diffusion of innovations. A communication science perspective, (pp. 57–76). New York: Peter Lang.
   Google Scholar
• Kennedy, E. J., and Lawton, L. 1996. The effects of social and moral integration on ethical standards: a comparison of American and Ukranian students. Journal of Business Ethics, 15(8), 901–911. doi: 10.1007/BF00381858
   Web of Science ®Google Scholar
• Kock, N. 2012. WarpPLS 3.0 user manual, Laredo, TX: ScriptWarp Systems.
   Google Scholar
• Lee, Y., Kozar, K. A., and Larsen, K. R. T. 2003. The technology acceptance model: past, present, and the future. Communications of the Association for Information Systems, 12(1), 752–780.
   Google Scholar
• Ling, R., and Sundsøy, P. R., 2009. The iPhone and mobile access to the internet. J. Höflich, C. Dietmar, G. Kircher, and I. Schlote, eds. Mobile media and the change of everyday life. Berlin, Germany: Peter Lang, 213–223.
   Google Scholar
• López-Nicolás, C., Molina-Castillo, F. J., and Bouwman, H. 2008. An assessment of advanced mobile services acceptance: contributions from TAM and diffusion theory models. Information & Management, 45(6), 359–364. doi: 10.1016/j.im.2008.05.001
   Web of Science ®Google Scholar
• Morris, M. G., and Venkatesh, V. 2000. Age differences in technology adoption decisions: implications for a changing work force. Personnel Psychology, 53(2), 375–403. doi: 10.1111/j.1744-6570.2000.tb00206.x
   Web of Science ®Google Scholar
• Ongena, G., Huizer, E., and van de Wijngaert, L. 2012. Threats and opportunities for new audiovisual cultural heritage archive services: the Dutch case. Telematics and Informatics, 29(2), 156–165. doi: 10.1016/j.tele.2011.05.005
   Web of Science ®Google Scholar
• Oomen, J., et al.. 2009. Images for the future: unlocking the value of audiovisual heritage. Museums and the Web 2009: proceedings. April15–18, Toronto: Archives & Museum Informatics.
   Google Scholar
• Pieterson, W. 2009. Channel choice; citizens' channel behavior and public service channel strategy, University of Twente. Thesis (PhD)
   Google Scholar
• Rogers, E. 2003. Diffusion of innovations, 5th ed. New York: Free Press.
   Google Scholar
• Rossi, P., and Anderson, A. 1982. The factorial survey approach: an introduction. In:. In Rossi, P., and Nock, S. (Ed.), Measuring social judgments: the factorial survey approach, (pp. 15–67). Beverly Hills, CA: Sage.
   Google Scholar
• Rossi, P. H., and Nock, S. L. 1982. Measuring social judgments: the factorial survey approach, Beverly Hills, CA: Sage.
   Google Scholar
• Rothensee, M.. 2008. User acceptance of the intelligent fridge: empirical results from a simulation. Proceedings of the 1st international conference on The internet of Things, March26–28. Berlin: Springer-Verlag. 123–139
   Google Scholar
• Szmigin, I., and Foxall, G. 1998. Three forms of innovation resistance: the case of retail payment methods. Technovation, 18(6/7), 459–468. doi: 10.1016/S0166-4972(98)00030-3
   Web of Science ®Google Scholar
• Urbach, N., and Ahlemann, F. 2010. Structural equation modeling in information systems research using partial least squares. Journal of Information Technology Theory and Application, 11(2), 5–40.
   Google Scholar
• van Schaik, P. 1999. Involving users in the specification of functionality using scenarios and model-based evaluation. Behaviour & Information Technology, 18(6), 455–466. doi: 10.1080/014492999118878
   Web of Science ®Google Scholar
• van Schaik, P., Bettany-Saltikov, J. A., and Warren, J. G. 2002. Clinical acceptance of a low-cost portable system for postural assessment. Behaviour & Information Technology, 21(1), 47–57. doi: 10.1080/01449290110107236
   Web of Science ®Google Scholar
• van Schaik, P., et al. 2004. The acceptance of a computerised decision-support system in primary care: a preliminary investigation. Behaviour & Information Technology, 23(5), 321–326. doi: 10.1080/0144929041000669941
   Web of Science ®Google Scholar
• Venkatesh, V., and 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. doi: 10.2307/3250981
   Web of Science ®Google Scholar
• Venkatesh, V., Morris, M. G., and 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. doi: 10.1006/obhd.2000.2896
   PubMed Web of Science ®Google Scholar
• Venkatesh, V., Thong, J. Y. L., and Xin, 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.
   Web of Science ®Google Scholar
• Wason, K. D., Polonsky, M. J., and Hyman, M. R. 2002. Designing vignette studies in marketing. Australasian Marketing Journal, 10(3), 41–58. doi: 10.1016/S1441-3582(02)70157-2
   Google Scholar
• Wetzels, M., Odekerken-Schroder, G., and Van Oppen, C. 2009. Using PLS path modeling for assessing hierarchical construct models: guidelines and empirical illustration. MIS Quarterly, 33(1), 177–195.
   Web of Science ®Google Scholar
• Xu, X., Ma, W. W. K., and See-To, E. W. K. 2008. Will mobile video become the killer application for 3G mobile Internet? A model of media convergence acceptance. Information Systems Frontiers, 12(3), 311–322. doi: 10.1007/s10796-008-9139-7
   Web of Science ®Google Scholar
• Yang, C., Hsu, Y., and Tan, S. 2010. Predicting the determinants of users' intentions for using YouTube to share video: moderating gender effects. Cyberpsychology, Behavior, and Social Networking, 13(2), 141–152. doi: 10.1089/cyber.2009.0105
   PubMed Web of Science ®Google Scholar
• Zedeck, S. 1977. An information processing model and approach to the study of motivation. Organization Behavior and Human Performance, 18(1), 47–77. doi: 10.1016/0030-5073(77)90018-6
   Web of Science ®Google Scholar
• Zhou, T. 2011. An empirical examination of users' post-adoption behaviour of mobile services. Behaviour & Information Technology, 30(2), 241–250. doi: 10.1080/0144929X.2010.543702
   Web of Science ®Google Scholar