In this study the perceived value construct of the Unified Theory of Acceptance and Use of Technology (UTAUT2) is investigated in the context of a learning management system (LMS), in which the construct is redefined from its original price value conceptualization. It was found that many researchers simply ignore the price value construct when applying the UTAUT2 model in technology use studies in the educational context. This study extends the UTAUT2 framework by integrating the learning value construct and provides fresh insight about predictors of students’ intentions towards LMS and its use. A quantitative research approach was employed by utilizing a closed-ended questionnaire to collect data from Malaysian university students who were users of LMS. Probability proportional stratified sampling was employed to select an appropriate sample. The results indicated a good measurement and structural model fit and suggested the significant influence of performance expectancy, social influence and learning value on students’ intention towards LMS and also confirmed the influence of facilitating conditions and behavioral intention on LMS use. The extended UTAUT2 framework helps in understanding students’ perceived value in the LMS context. Furthermore, this study will help institutions to consider the factors for successful implementation of an LMS in an academic setting.
Al-ShafiSWeerakkodyVJanssenM (2009) Investigating the adoption of eGovernment services in Qatar using the UTAUT model. In: Fifteenth Americas Conference on Information Systems (AMCIS), 6-9August 2009, Paper 260. California: AIS.
4.
AllyMGardinerM (2012) The moderating influence of device characteristics and usage on user acceptance of smart mobile devices. In: 23rd Australasian Conference on Information Systems (ACIS), 3-5December 2012. Geelong: ACIS, 1–10.
5.
BandyopadhyayKFraccastoroKA (2007) The effect of culture on user acceptance of information technology. Communications of the Association for Information Systems19: 522–543.
6.
BentlerPMBonettDG (1980) Significance tests and goodness of fit in the analysis of covariance structures. Psychological Bulletin88(3): 588–606.
7.
BrownSAVenkateshV (2005) Model of adoption of technology in households: A baseline model test and extension incorporating household life cycle. MIS Quarterly29(3): 399–426.
8.
ByrneBM (2013) Structural Equation Modeling with AMOS: Basic concepts, applications, and programming. New York: Routledge.
9.
ChenHJ (2010) Linking employees’ e-learning system use to their overall job outcomes: An empirical study based on the IS success model. Computers & Education55(4): 1628–1639.
10.
ChurchillGAJr (1979) A paradigm for developing better measures of marketing constructs. Journal of Marketing Research16(1): 64–73.
11.
CohenJBancilhonJ-MJonesM (2013) South African physicians’ acceptance of e-prescribing technology: an empirical test of a modified UTAUT model. South African Computer Journal50: 43–54.
12.
DavisFD (1989) Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly13(3): 319–340.
13.
De SmetCBourgonjonJDe WeverB. (2012) Researching instructional use and the technology acceptation of learning management systems by secondary school teachers. Computers & Education58(2): 688–696.
14.
DengSLiuYQiY (2011) An empirical study on determinants of web based question-answer services adoption. Online Information Review35(5): 789–798.
15.
DoddsWBMonroeKBGrewalD (1991) Effects of price, brand, and store information on buyers’ product evaluations. Journal of Marketing Research28(3): 307–319.
16.
DonaldsonRL (2011) Student acceptance of mobile learning. PhD Thesis, Florida State University, United States.
17.
El-GayarOFMoranM (2006) College students’ acceptance of tablet PCs: an application of the UTAUT model. Dakota State University820.
18.
FidaniAIdriziF (2012) Investigating students’ acceptance of a learning management system in university education: A structural equation modeling approach. In: ICT Innovations, 5th September 2012. Macedonia: ACT, 311–320.
19.
FornellCLarckerDF (1981) Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research18: 39–50.
20.
HairJFBlackWCBabinBJ. (2010) Multivariate Data Analysis: A global perspective. New Jersey: Pearson.
21.
HassanzadehAKanaaniFElahiS (2012) A model for measuring e-learning systems success in universities. Expert Systems with Applications39(12): 10959–10966.
22.
HairJFTathamRLAndersonRE. (2006) Multivariate Data Analysis. New Jersey: Pearson Prentice Hall.
23.
HowittDCramerD (2011) Introduction to SPSS Statistics in Psychology: For version 19 and earlier. New York: Pearson.
24.
HsuH-H (2012) The acceptance of Moodle: An empirical study based on UTAUT. Creative Education3: 44–46.
25.
IqbalSQureshiIA (2011) Learning management systems (LMS): Inside matters. Information Management and Business Review3: 206–216.
26.
IslamA (2013) Investigating e-learning system usage outcomes in the university context. Computers & Education69: 387–399.
KimSSMalhotraNKNarasimhanS (2005) Research note—two competing perspectives on automatic use: A theoretical and empirical comparison. Information Systems Research16: 418–432.
29.
KrejcieRVMorganDW (1970) Determining sample size for research activities. Education and Psychological Measurement30(3): 607–610.
30.
KlineRB (2011) Principles and Practice of Structural Equation Modeling. New York: Guilford Press.
31.
KrishnarajuVMathewSKSugumaranV (2013) Role of web personalization in consumer acceptance of e-government services. In: Nineteenth Americas Conference on Information Systems, 15-17August 2013. Chicago: AIS, 1–8.
32.
LaRoseRDeMaagdKChewH. (2012) Measuring sustainable broadband adoption: An innovative approach to understanding broadband adoption and use. International Journal of Communication6: 2576–2600.
33.
LewisCCFretwellCERyanJ. (2013) Faculty use of established and emerging technologies in higher education: A Unified Theory of Acceptance and Use of Technology perspective. International Journal of Higher Education2(2): 22–34.
34.
LimHLeeSGNamK (2007) Validating e-learning factors affecting training effectiveness. International Journal of Information Management27: 22–35.
35.
LinCPAnolB (2008) Learning online social support: an investigation of network information technology based on UTAUT. CyberPsychology & Behavior11(3): 268–272.
36.
LonnSTeasleySDKrummAE (2011) Who needs to do what where? Using learning management systems on residential vs. commuter campuses. Computers & Education56(3): 642–649.
37.
LaiCWangQLeiJ (2012) What factors predict undergraduate students’ use of technology for learning? A case from Hong Kong. Computers & Education59(2): 569–579.
38.
MaldonadoUPTKhanGFMoonJ. (2011) E-learning motivation and educational portal acceptance in developing countries. Online Information Review35(1): 66–85.
39.
MarchewkaJTLiuCKostiwaK (2007) An application of the UTAUT model for understanding student perceptions using course management software. Communications of the IIMA7(2): 93–104
40.
MarquesBPVillateJECarvalhoC (2011) Applying the UTAUT model in engineering higher education: Teacher’s technology adoption. In: 6th Iberian Conference on Information Systems and Technologies (CISTI), 15-18June 2011. Chaves: IEEE, 1–6.
41.
MartinsCI (2013) Exploring Digital Music Online: User acceptance and adoption of online music services. Master thesis, Technical University of Lisbon, Portugal.
42.
MotaghianHHassanzadehAMoghadamDK (2013) Factors affecting university instructors’ adoption of web-based learning systems: Case study of Iran. Computers & Education61: 158–167.
43.
NanayakkaraC (2007) A model of user acceptance of learning management systems: A study within tertiary institutions in New Zealand. The International Journal of Learning13(12): 223–232.
44.
NavehGTubinDPliskinN (2010) Student LMS use and satisfaction in academic institutions: The organizational perspective. The Internet and Higher Education13(3): 127–133.
45.
NgaiEWPoonJChanY (2007) Empirical examination of the adoption of WebCT using TAM. Computers & Education48: 250–267.
46.
NikouSBouwmanH (2013) The diffusion of mobile social network service in China: The role of habit and social influence. In: 46th Hawaii International Conference on System Sciences (HICSS), 7–10January 2010. Maui: IEEE, 1073–1081.
47.
NilsenPRobackKBroströmA. (2012) Creatures of habit: Accounting for the role of habit in implementation research on clinical behaviour change. Implementation Science7: 2–6.
48.
PaechterMMaierBMacherD (2010) Students’ expectations of, and experiences in e-learning: Their relation to learning achievements and course satisfaction. Computers & Education54: 222–229.
49.
PituchKALeeYk (2006) The influence of system characteristics on e-learning use. Computers & Education47: 222–244.
50.
RamanADonY (2013) Preservice teachers’ acceptance of learning management software: An application of the UTAUT2 Model. International Education Studies6(7): 157–164.
51.
SumakBPolancicGHerickoM (2010) An empirical study of virtual learning environment adoption using UTAUT. In: Second International Conference on Mobile, Hybrid, and On-Line Learning ELML, 10-16February 2010. Saint Maarten: IEEE, 17–22.
52.
ThongJYHongS-JTamKY (2006) The effects of post-adoption beliefs on the expectation-confirmation model for information technology continuance. International Journal of Human-Computer Studies64(9): 799–810.
53.
Van der HeijdenH (2004) User acceptance of hedonic information systems. MIS Quarterly28(4): 695–704.
54.
VenkateshVMorrisMGDavisGB. (2003) User acceptance of information technology: Toward a unified view. MIS Quarterly27(3): 425–478.
55.
VenkateshVThongJXuX (2012) Consumer acceptance and use of information technology: extending the unified theory of acceptance and use of technology. MIS Quarterly36(1): 157–178.
56.
VinodhKMathewSK (2012) Web personalization in technology acceptance. In: 4th International Conference on Intelligent Human Computer Interaction (IHCI), 27-29December 2012. Kharagpur: IEEE, 1–6.
57.
WaheedMKaurK (2014) Knowledge quality A review and a revised conceptual model. Information Development. Epub ahead of print 23 June 2014. DOI: 10.1177/0266666914539694.
58.
WaheedMKaurKAinN. (2015a) Perceived learning outcomes from Moodle An empirical study of intrinsic and extrinsic motivating factors. Information Development. Epub ahead of print 21 April 2015. DOI: 10.1177/0266666915581719.
59.
WaheedMKaurKAinN. (2015b) Emotional attachment and multidimensional self-efficacy: Extension of innovation diffusion theory in the context of eBook reader. Behaviour & Information Technology: 1–13.
60.
WaheedMKaurKQaziA (2016) Students’ perspective on knowledge quality in elearning context: A qualitative assessment. Internet Research26.
61.
WangWTWangCC (2009) An empirical study of instructor adoption of web-based learning systems. Computers & Education53(3): 761–774.
