Development and Validation of the Technology Adoption and Gratification (TAG) Model in Higher Education: A Cross-Cultural Study Between Malaysia and China

The prime objective of this study was to develop and validate the Technology Adoption and Gratification (TAG) Model to evaluate the adoption and gratification of lecturers in using ICT facilities for their teaching and research purposes in higher education. The second objective of this study was to evaluate the cross-cultural validation of the causal structure of the TAG model. A total of 396 lecturers were collected from two public universities, namely, University of Malaya in Malaysia and Jiaxing University in China using stratified random sampling procedure. The questionnaire's validity was established through Exploratory Factor Analysis (EFA) using SPSS version 21.0. The data was analyzed applying Structural Equation Modeling (SEM) using AMOS version 18. The findings of the research using the TAG model discovered that the computer self-efficacy of the lecturers had a positive direct impact on their perceived usefulness and ease of use, while the latter two factors also had a significant direct impact on gratification and intention to use, separately. Meanwhile, gratification and actual use of ICT facilities were directly affected by intention to use. Moreover, computer self-efficacy had a positive and significant indirect impact on gratification and intention to use mediated by perceived usefulness and ease of use, respectively. In addition to lecturers' perceived ease of use and usefulness had a significant indirect effect on their gratification mediated by intention to use. The results of the invariance analysis of the TAG model also demonstrated that the model was valid for measuring lecturers' adoption and gratification in using ICT facilities. However, the TAG model works differently in cross-cultural settings. The findings contribute to the existing body of knowledge in the field of ICT by developing and validating the applicability of the TAG Model within institutions of higher education. Once validated the model could then be applied by future researchers, academicians and practitioners in the diverse context of education.

[1]  Mable B. Kinzie,et al.  Computer Technologies in Teacher Education: The Measurement of Attitudes and Self-Efficacy. , 1993 .

[2]  Reza Barkhi,et al.  A Model of the Determinants of Purchasing from Virtual Stores , 2008, J. Organ. Comput. Electron. Commer..

[3]  Tunku Badariah Tunku Ahmad,et al.  Investigating Students' Attitude and Intention to Use Social Software in Higher Institution of Learning in Malaysia. , 2011 .

[4]  Sergio L. Toral Marín,et al.  A technological acceptance of e-learning tools used in practical and laboratory teaching, according to the European higher education area 1 , 2008, Behav. Inf. Technol..

[5]  Reji Kumar,et al.  Journal of Internet Banking and Commerce an Empirical Study on Service Quality Perceptions and Continuance Intention in Mobile Banking Context in India , 2022 .

[6]  Timothy Teo,et al.  A Cross-cultural Examination of the Intention to Use Technology between Singaporean and Malaysian pre-service Teachers: An Application of the Technology Acceptance Model (TAM) , 2008, J. Educ. Technol. Soc..

[7]  Halimah Badioze Zaman,et al.  Evaluation of User Acceptance of Mixed Reality Technology. , 2011 .

[8]  Cheol Park,et al.  Mobile technology usage and B2B market performance under mandatory adoption , 2008 .

[9]  Detmar W. Straub,et al.  Testing the technology acceptance model across cultures: A three country study , 1997, Inf. Manag..

[10]  George Zhou,et al.  Are secondary preservice teachers well prepared to teach with technology? A case study from China , 2011 .

[11]  A. Y. M. Atiquil Islam,et al.  Validation of the Technology Satisfaction Model (TSM) Developed in Higher Education: The Application of Structural Equation Modeling , 2014, Int. J. Technol. Hum. Interact..

[12]  Muniruddeen Lallmahamood,et al.  An Examination of IndividualâÂÂs Perceived Security andPrivacy of the Internet in Malaysia and the Influence ofThis on Their Intention to Use E-Commerce: Using AnExtension of the Technology Acceptance Model , 2007 .

[13]  A. Bandura,et al.  Cultivating competence, self-efficacy, and intrinsic interest through proximal self-motivation. , 1981 .

[14]  Christos Michalakelis,et al.  Assessment of information and communications technology maturity level , 2013 .

[15]  Echo Huang,et al.  Use and gratification in e-consumers , 2008, Internet Res..

[16]  Chorng-Jee Guo,et al.  An Empirical Assessment of Science Teachers’ Intentions Toward Technology Integration , 2008 .

[17]  Samer Khasawneh,et al.  Jordanian Pre-Service Teachers' and Technology Integration: A Human Resource Development Approach , 2011, J. Educ. Technol. Soc..

[18]  Roger Azevedo,et al.  Learning With Computer-Based Learning Environments: A Literature Review of Computer Self-Efficacy , 2009 .

[19]  Yan Xu,et al.  An Enhanced Technology Acceptance Model for Web-Based Learning , 2004, J. Inf. Syst. Educ..

[20]  Detmar W. Straub,et al.  The psychological origins of perceived usefulness and ease-of-use , 1999, Inf. Manag..

[21]  A. Y. M. Atiquil Islam,et al.  Assessing Mobile Learning Readiness in Saudi Arabia Higher Education: An Empirical Study. , 2014 .

[22]  M. Kinzie,et al.  Computer technologies: Attitudes and self-efficacy across undergraduate disciplines , 1994 .

[23]  Fred D. Davis User Acceptance of Information Technology: System Characteristics, User Perceptions and Behavioral Impacts , 1993, Int. J. Man Mach. Stud..

[24]  Lori Baker-Eveleth,et al.  Students’ intentions to purchase electronic textbooks , 2013, Journal of Computing in Higher Education.

[25]  R. Shroff,et al.  Analysis of the technology acceptance model in examining students' behavioural intention to use an e-portfolio system , 2011 .

[26]  Yasemin Koçak Usluel,et al.  A Structural Equation Model for ICT Usage in Higher Education , 2008, J. Educ. Technol. Soc..

[27]  Fred D. Davis,et al.  User Acceptance of Computer Technology: A Comparison of Two Theoretical Models , 1989 .

[28]  Mark R. Lehto,et al.  User acceptance of YouTube for procedural learning: An extension of the Technology Acceptance Model , 2013, Comput. Educ..

[29]  K. Lai Digital technology and the culture of teaching and learning in higher education , 2011 .

[30]  Fred D. Davis Perceived Usefulness, Perceived Ease of Use, and User Acceptance of Information Technology , 1989, MIS Q..

[31]  Chun-Hua Chen,et al.  A Learning Assistance Tool for Enhancing ICT Literacy of Elementary School Students , 2010, J. Educ. Technol. Soc..

[32]  A. Bandura Self-efficacy: toward a unifying theory of behavioral change. , 1977, Psychological review.

[33]  Thurasamy Ramayah,et al.  Impact of shared beliefs on “perceived usefulness” and “ease of use” in the implementation of an enterprise resource planning system , 2007 .

[34]  Chrystalla Mouza,et al.  A Framework for Addressing Challenges to Classroom Technology Use , 2008 .

[35]  Edward E. Rigdon,et al.  Experiential value: Conceptualization, measurement and application in the catalog and Internet shopping environment. , 2001 .

[36]  R. Oliver,et al.  An Empirical Test of the Consequences of Behavior-and Outcome-Based Sales Control Systems , 1994 .

[37]  Pin Luarn,et al.  Predicting consumer intention to use mobile service , 2006, Inf. Syst. J..

[38]  Yi-Chuan Hsieh,et al.  Adding Innovation Diffusion Theory to the Technology Acceptance Model: Supporting Employees' Intentions to use E-Learning Systems , 2011, J. Educ. Technol. Soc..

[39]  Yair Levy,et al.  Emerging Educational Technology: Assessing the Factors that Influence Instructors' Acceptance in Information Systems and Other Classrooms , 2008, J. Inf. Syst. Educ..

[40]  Peter Songan,et al.  ICT in the changing landscape of higher education in Southeast Asia , 2011 .

[41]  Petrus Guriting,et al.  Borneo online banking: evaluating customer perceptions and behavioural intention , 2006 .

[42]  Diljit Singh,et al.  Efficacy of the Technology Satisfaction Model (TSM): An Empirical Study , 2015, Int. J. Technol. Hum. Interact..

[43]  T. Levin,et al.  Teachers’ Views on Factors Affecting Effective Integration of Information Technology in the Classroom: Developmental Scenery , 2008 .

[44]  Rajiv Kohli,et al.  Antecedents of B2C Channel Satisfaction and Preference: Validating e-Commerce Metrics , 2002, Inf. Syst. Res..

[45]  Anastasios A. Economides,et al.  Computer Based Assessment Acceptance: A Cross-cultural Study in Greece and Mexico , 2013, J. Educ. Technol. Soc..

[46]  A. Alenezi,et al.  An Empirical Investigation into the Role of Enjoyment, Computer Anxiety, Computer Self-Efficacy and Internet Experience in Influencing the Students' Intention to Use E-Learning: A Case Study from Saudi Arabian Governmental Universities , 2010 .

[47]  Abu Yousuf,et al.  VIABILITY OF THE EXTENDED TECHNOLOGY ACCEPTANCE MODEL: AN EMPIRICAL STUDY , 2011 .

[48]  A. Yuen,et al.  Exploring teacher acceptance of e‐learning technology , 2008 .

[49]  Jijie Wang,et al.  Information technology (IT) in Saudi Arabia: Culture and the acceptance and use of IT , 2007, Inf. Manag..

[50]  Patrick Y. K. Chau,et al.  An Empirical Assessment of a Modified Technology Acceptance Model , 1996, J. Manag. Inf. Syst..

[51]  Su-Chao Chang,et al.  An empirical investigation of students' behavioural intentions to use the online learning course websites , 2007, Br. J. Educ. Technol..

[52]  Chi Cheng Chang,et al.  Perceived Convenience in an Extended Technology Acceptance Model: Mobile Technology and English Learning for College Students. , 2012 .

[53]  M. Sobel Asymptotic Confidence Intervals for Indirect Effects in Structural Equation Models , 1982 .

[54]  Neeru Malhotra,et al.  Antecedents and consequences of service quality in consumer evaluation of self-service internet technologies , 2008 .

[55]  Tunku Badariah Tunku Ahmad,et al.  Determinants of Social Networking Software Acceptance: A Multi-Theoretical Approach. , 2013 .

[56]  Ken Stevens,et al.  Factors influencing perceived usefulness of wikis for group collaborative learning by first year students , 2011 .

[57]  Belinda Shipps,et al.  Social Networks, Interactivity and Satisfaction: Assessing Socio-Technical Behavioral Factors as an Extension to Technology Acceptance , 2013, J. Theor. Appl. Electron. Commer. Res..

[58]  Payam Hanafizadeh,et al.  Mobile-banking adoption by Iranian bank clients , 2014, Telematics Informatics.

[59]  Qingxiong Ma,et al.  The Technology Acceptance Model: A Meta-Analysis of Empirical Findings , 2004, J. Organ. End User Comput..

[60]  Fred D. Davis,et al.  A Model of the Antecedents of Perceived Ease of Use: Development and Test† , 1996 .

[61]  Frank Bate,et al.  A bridge too far? Explaining beginning teachers' use of ICT in Australian schools , 2010 .

[62]  T. Teo,et al.  Influence of gender and computer teaching efficacy on computer acceptance among Malaysian student teachers: An extended technology acceptance model , 2012 .

[63]  Alain Yee-Loong Chong,et al.  Predicting consumer decisions to adopt mobile commerce: Cross country empirical examination between China and Malaysia , 2012, Decis. Support Syst..

[64]  Erdogan Tezci,et al.  Factors that influence pre-service teachers’ ICT usage in education , 2011 .

[65]  Hanudin Amin Journal of Internet Banking and Commerce Internet Banking Adoption among Young Intellectuals , 2022 .

[66]  Kamal Basha Madarsha,et al.  Faculty's acceptance of computer based technology: Cross-validation of an extended model , 2010 .

[67]  Shallone K. Chitungo,et al.  Extending the Technology Acceptance Model to Mobile Banking Adoption in Rural Zimbabwe , 2013 .