Abstract
This study explores the effectiveness of disaster prevention programs using virtual reality and partial least squares techniques. The purpose is to gain an understanding of IS (information system) usage and acceptance behaviors, mainly the users’ acceptance of virtual reality, as well as provide a reference for future disaster prevention programs. Virtual reality is an important part of this process and needs a lot of special skills like knowledge of software and hardware for its development. To date, virtual reality has been used in many ways, such as in movies, for medical treatment and for educational training. This model incorporates the technology acceptance model, technology acceptance model 2 and IS success model and uses the partial least squares technique for structural modeling. The results indicate that virtual reality learning self-efficacy, subjective norms, system quality, information quality and service quality have a significant influence on perceived usefulness, perceived ease of use and playfulness. Considering the users’ intention to use and attitude while using virtual reality, playfulness is more significant than either perceived usefulness or perceived ease of use.
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References
Ahn T, Ryu S, Han I (2007) The impact of web quality and playfulness on user acceptance of online retailing. Inf Manag 44:263–275
Ajzen I, Fishbein M (1980) Understanding attitudes and predicting social behavior. Prentice-Hall, Englewood Cliffs
Chen HJ (2010) Linking employees’ e-learning system use to their overall job outcomes: an empirical study based on the IS success model. Comput Educ 55:1628–1639
Chen CH, Yang JC, Shen S, Jeng MC (2007) A desktop virtual reality earth motion system in astronomy education. Educ Technol Soc 10(3):289–304
Davis FD (1989) Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Q 13(3):319–339
Davis FD, Bagozzi RP, Warshaw PR (1989) User acceptance of computer technology: a comparison of two theoretical models. Manage Sci 35:982–1003
Davis FD, Bagozzi RP, Warshaw PR (1992) Extrinsic and intrinsic motivation to use computers in workplace. J Appl Soc Psychol 22:1111–1132
DeLone WH, McLean ER (1992) Information systems success: the quest for the dependent variable. Inf Syst Res 3(1):60–95
DeLone WH, McLean ER (2002) Information systems success revisited. In: Proceedings of the 35th Hawaii international conference on system sciences (HICSS 02). Big Island, Hawaii, pp 238–249
DeLone WH, McLean ER (2003) The DeLone and McLean of information systems success: a ten-year update. J Manag Inf Syst 19:9–30
Dishaw MT, Strong DM (1999) Extending the technology acceptance model with task-technology fit constructs. Inf Manag 36:9–21
Fornell C, Larcker D (1981) Evaluating structural equation models with unobservable variables and measurement error. J Mark Res 18:39–50
Gefen D, Straub DW (1997) Gender differences in the perception and use of e-mail: an extension to the technology acceptance model. MIS Q 21(4):389–400
Govender D, Govender I (2009) The relationship between information and communications technology (ICT) integration and teachers’ self-efficacy beliefs about ICT. Educ Change 13(1):153–165
Grandon E, Alshare O, Kwan O (2005) Factors influencing student intention to adopt online classes: a cross-cultural study. J Comput Sci Coll 20(4):46–56
Lederer AL, Maupin DJ, Sena PM, Zhuang Y (2000) The technology acceptance model and the world wide web. Decis Support Syst 29:269–282
Lee B-C, Yoon J-O, Lee I (2009) Learners’ acceptance of e-learning in South Korea: theories and results. Comput Educ 53(4):1320–1329
Lee WI, Chiu YT, Liu CC, Chen CY (2011) Assessing the effects of consumer involvement and service quality in a self-service setting. Hum Factors Ergonomics Manuf Serv Ind. doi:10.1002/hfm.20253
Legris P, Ingham J, Collerette P (2003) Why do people use information technology? A critical review of the technology acceptance model. Inf Manag 40:191–204
Liao Z, Cheung M (2001a) Internet-based e-shopping and consumer attitudes: an empirical study. Inf Manag 38:299–306
Liao Z, Cheung MT (2001b) Internet-based e-shopping and consumer attitudes: an empirical study. Inf Manag 38:299–306
Liao Z, Cheung MT (2005) Service quality in internet e-banking: a user-based core framework. IEEE international conference on e-technology, e-commerce and e-service (EEE’05), pp 628–631
Lin JCC, Lu H (2000) Toward an understanding of the behavioural intention to use a web site. Int J Inf Manage 20:197–208
Lin CP, Huang HN, Joe SW, Ma HC (2008) Learning the determinants of satisfaction and usage intention of instant messaging. Cyberpsychol Behav 11(3):262–267
Lucas HC, Spitler VK (1999) Technology use and performance: a field study of broker workstations. Decis Sci 30(2):291–311
Mason RO (1978) Measuring information output: a communication systems approach. Inf Manag 1(5):219–234
Moon JW, Kim YG (2001) Extending the TAM for a world-wide-web context. Inf Manag 38:217–230
Nunnally JC, Bernstein IH (1994) Psychometric theory. New York: McGraw-Hill, Chapters 1 and 3.
Parasuraman A, Zeithaml VA, Berry LL (1988) SERVQUAL: a multiple-item scale for measuring consumer perceptions of service quality. J Retail 64:12–40
Park SY (2009) An analysis of the technology acceptance model in understanding university students’ behavioral intention to use e-learning. Educ Technol Soc 12(3):150–162
Peterson R (2000) A meta-analysis of variance accounted for and factor loadings in exploratory factor analysis. Mark Lett 11:261–275
Selim HM (2003) An empirical investigation of student acceptance of course websites. Comput Educ 40:343–360
Shannon CE, Weaver W (1949) The mathematical theory of communication. University of Illinois Press, Urbana
Terzis V, Economides AA (2011) The acceptance and use of computer based assessment. Comput Educ 56:1032–1044
van Raaij EM, Jeroen J, Schepers L (2008) The acceptance and use of a virtual learning environment in China. Comput Educ 50:838–852
Venkatesh V, Davis FD (1996) A model of the antecedents of perceived ease of use: development and test. Decis Sci 27(3):451–481
Venkatesh V, Davis FD (2000) A theoretical extension of the technology acceptance model: four longitudinal field studies. Manag Sci 46(2):186–204
Wan C, Jiang R, Tu XM, Tang W, Pan J, Yang R, Li X, Yang Z, Zhang X (2011) The hypertension scale of the system of Quality of Life Instruments for Chronic Diseases, QLICD-HY: A development and validation study. Int J Nurs Stud. doi:10.1016/j.ijnurstu.2011.10.010
Wang YS (2008) Assessing e-commerce systems success: a respecification and validation of the DeLone and McLean model of IS success. Inf Syst J 18:529–557
Wright J, Benzie D (1994) Exploring a new partnership: children teachers and technology. IFIP and North-Holland, Amsterdam, pp 89–95
Yang JC, Chen CH, Jeng MC (2010) Integrating video-capture virtual reality technology into a physically interactive learning environment for English learning. Comput Educ 55:1346–1356
Acknowledgments
The authors are appreciative of the financial support in the form of research grants awarded to Dr. Chen-Yuan Chen from the National Science Council, Republic of China under Grant Nos. NSC 99-2628-E-153-001 and NSC 100-2628-E-153-001. The authors are also most grateful for the constructive suggestions of the anonymous reviewers, all of which have led to the making of several corrections and suggestions that have greatly improved the presentation of this paper.
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Chen, CY., Shih, BY. & Yu, SH. Disaster prevention and reduction for exploring teachers’ technology acceptance using a virtual reality system and partial least squares techniques. Nat Hazards 62, 1217–1231 (2012). https://doi.org/10.1007/s11069-012-0146-0
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DOI: https://doi.org/10.1007/s11069-012-0146-0