A model of organizational employees' e-learning systems acceptance

This study examines the factors that influence employees' adoption and use of e-learning systems and tests the applicability of the technology acceptance model (TAM) in the organizational context. We examined the relationship of employees' perceptions of their behavioral intention to use e-learning systems in terms of four determinants (individual, organizational, task characteristics, and subjective norm), to further explore the effects of management and organizational support on the subjective norm. Data were 357 valid questionnaires from four industries in Taiwan. The findings indicate that organizational support and management support significantly affected perceived usefulness and intention to use. Individuals' experience with computers and computer self-efficacy had significantly positive effects on perceived ease of use. Task equivocality significantly influenced perceived usefulness. Organizational and management supports significantly impacted the subjective norm, perceived usefulness, perceived ease of use, and intention to use. Additionally, the results suggest that external variables that affect perceived usefulness, perceived ease of use, and intention to use, need to be considered as important factors in the process of designing, implementing, and operating e-learning systems. The results provided a more comprehensive insight of individual, organizational, and task characteristics in predicting e-learning acceptance behavior in the organizational contexts, rarely tested in previous studies. By considering these identified factors, practitioners can take corresponding measures to predict or promote organizational employees' e-learning systems acceptance more effectively and efficiently. Furthermore, by explaining employees' acceptance behavior, the findings of this research help to develop more user-friendly e-learning systems and provide insight into the best way to promote e-learning systems for employees.

[1]  Henderik Alex Proper,et al.  Matching cognitive characteristics of actors and tasks in information systems engineering , 2008, Knowl. Based Syst..

[2]  Mary P. Kosarzycki,et al.  Emerging themes in distance learning research and practice: some food for thought , 2002 .

[3]  Neil Selwyn,et al.  The use of computer technology in university teaching and learning: a critical perspective , 2007, J. Comput. Assist. Learn..

[4]  V. Grover An Empirically Derived Model for the Adoption of Customer‐based Interorganizational Systems* , 1993 .

[5]  I. Ajzen,et al.  Understanding Attitudes and Predicting Social Behavior , 1980 .

[6]  Detmar W. Straub,et al.  Measuring System Usage: Implications for IS Theory Testing , 1995 .

[7]  Dale Goodhue,et al.  Task-Technology Fit and Individual Performance , 1995, MIS Q..

[8]  Udo Konradt,et al.  Predicting user satisfaction, strain and system usage of employee self-services , 2006, Int. J. Hum. Comput. Stud..

[9]  Mohd Hishamuddin Harun Integrating e-Learning into the workplace , 2001, Internet High. Educ..

[10]  Injai Kim The effects of individual, managerial, organizational, and environmental factors on the adoption of object orientation in United States organizations: An empirical test of the Technology Acceptance Model , 1996 .

[11]  Magid Igbaria,et al.  Technology acceptance in the banking industry: A perspective from a less developed country , 2000, Inf. Technol. People.

[12]  Magid Igbaria,et al.  A Motivational Model of Microcomputer Usage , 1996, J. Manag. Inf. Syst..

[13]  Robert Phelps,et al.  Managing the risks of intranet implementation: an empirical study of user satisfaction , 1999, J. Inf. Technol..

[14]  Tom Barron,et al.  Getting IT Support for E-Learning , 2000 .

[15]  Byung Gon Kim,et al.  A structural equation modeling of the Internet acceptance in Korea , 2007, Electron. Commer. Res. Appl..

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

[17]  Patrick Y. K. Chau,et al.  Influence of Computer Attitude and Self-Efficacy on IT Usage Behavior , 2001, J. Organ. End User Comput..

[18]  Margaret Tan,et al.  Factors Influencing the Adoption of Internet Banking , 2000, J. Assoc. Inf. Syst..

[19]  Charles A. O'Reilly,et al.  Variations in Decision Makers' Use of Information Sources: The Impact of Quality and Accessibility of Information , 1982 .

[20]  Katerine Bielaczyc,et al.  Designing Social Infrastructure: Critical Issues in Creating Learning Environments With Technology , 2006 .

[21]  Charlie C. Chen,et al.  An Integrative Model to Predict the Continuance Use of Electronic Learning Systems: Hints for Teaching , 2006 .

[22]  Zhengchuan Xu,et al.  Principle-based dispute resolution for consumer protection , 2009, Knowl. Based Syst..

[23]  Albert L. Lederer,et al.  The technology acceptance model and the World Wide Web , 2000, Decis. Support Syst..

[24]  Kai R. T. Larsen,et al.  A Taxonomy of Antecedents of Information Systems Success: Variable Analysis Studies , 2003, J. Manag. Inf. Syst..

[25]  Izak Benbasat,et al.  Development of an Instrument to Measure the Perceptions of Adopting an Information Technology Innovation , 1991, Inf. Syst. Res..

[26]  Janet H. Marler,et al.  A Model of Employee Self-Service Technology Acceptance , 2005 .

[27]  Paul Jen-Hwa Hu,et al.  Examining technology acceptance by school teachers: a longitudinal study , 2003, Inf. Manag..

[28]  Dowming Yeh,et al.  What drives a successful e-Learning? An empirical investigation of the critical factors influencing learner satisfaction , 2008, Comput. Educ..

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

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

[31]  Byung Gon Kim,et al.  Factors affecting the usage of intranet: A confirmatory study , 2009, Comput. Hum. Behav..

[32]  Chris W. Clegg,et al.  Explaining intranet use with the technology acceptance model , 2001, J. Inf. Technol..

[33]  Daniel J. Brass,et al.  Changing patterns or patterns of change: the effects of a change in technology on social network str , 1990 .

[34]  Viswanath Venkatesh,et al.  Determinants of Perceived Ease of Use: Integrating Control, Intrinsic Motivation, and Emotion into the Technology Acceptance Model , 2000, Inf. Syst. Res..

[35]  Peter A. Todd,et al.  Assessing IT usage: the role of prior experience , 1995 .

[36]  Blake Ives,et al.  Web-based Virtual Learning Environments: a Research Framework and a Preliminary Assessment of Effectiveness in Basic It Skills Training Author(s): Piccoli Et Al./web-based Virtual Learning Environments Web-based Virtual Learning Environments: a Research Framework and a Preliminary Assessment of Effe , 2022 .

[37]  Diane M. Strong,et al.  Extending the technology acceptance model with task-technology fit constructs , 1999, Inf. Manag..

[38]  Mark Keil,et al.  Usefulness and ease of use: field study evidence regarding task considerations , 1995, Decis. Support Syst..

[39]  Hassan M. Selim,et al.  An empirical investigation of student acceptance of course websites , 2003, Comput. Educ..

[40]  Anol Bhattacherjee,et al.  Acceptance of e-commerce services: the case of electronic brokerages , 2000, IEEE Trans. Syst. Man Cybern. Part A.

[41]  Jorgen P. Bansler,et al.  Corporate Intranet Implementation: Managing Emergent Technologies and Organizational Practices , 2000, J. Assoc. Inf. Syst..

[42]  Norshidah Mohamed,et al.  E-Learning acceptance in a developing country: A case of the Indonesian Open University , 2007 .

[43]  Bernadette Szajna,et al.  Software Evaluation and Choice: Predictive Validation of the Technology Acceptance Instrument , 1994, MIS Q..

[44]  J. Hair Multivariate data analysis , 1972 .

[45]  Hun Choi,et al.  An empirical study on the adoption of information appliances with a focus on interactive TV , 2003, Telematics Informatics.

[46]  Viswanath Venkatesh,et al.  Why Don't Men Ever Stop to Ask for Directions? Gender, Social Influence, and Their Role in Technology Acceptance and Usage Behavior , 2000, MIS Q..

[47]  Gary Klein,et al.  Measuring Information System Service Quality: SERVQUAL from the Other Side , 2002, MIS Q..

[48]  Yi-Shun Wang,et al.  Gender differences in the perception and acceptance of online games , 2008, Br. J. Educ. Technol..

[49]  Said S. Al-Gahtani,et al.  Attitudes, satisfaction and usage: Factors contributing to each in the acceptance of information technology , 1999, Behav. Inf. Technol..

[50]  D. S. Sivia,et al.  Data Analysis , 1996, Encyclopedia of Evolutionary Psychological Science.

[51]  Anthony R. Hendrickson,et al.  Using Davis's Perceived Usefulness and Ease-of-use Instruments for Decision Making: A Confirmatory and Multigroup Invariance Analysis , 1998 .

[52]  Marc J. Rosenberg,et al.  E-Learning: Strategies for Delivering Knowledge in the Digital Age , 2000 .

[53]  Jane M. Howell,et al.  Personal Computing: Toward a Conceptual Model of Utilization , 1991, MIS Q..

[54]  Jen-Her Wu,et al.  An Empirical Study of End-User Computing Acceptance Factors in Small and Medium Enterprises in Taiwan: Analyzed by Structural Equation Modeling , 2004, J. Comput. Inf. Syst..

[55]  Debra L. Nelson,et al.  Individual Adjustment to Information-Driven Technologies: A Critical Review , 1990, MIS Q..

[56]  Chin-Lung Hsu,et al.  Why do people play on-line games? An extended TAM with social influences and flow experience , 2004, Inf. Manag..

[57]  C. Fornell,et al.  Evaluating structural equation models with unobservable variables and measurement error. , 1981 .

[58]  Hamido Fujita,et al.  Intelligent human interface based on mental cloning-based software , 2009, Knowl. Based Syst..

[59]  Timothy Teo,et al.  Understanding pre-service teachers' computer attitudes: applying and extending the technology acceptance model , 2007, J. Comput. Assist. Learn..

[60]  J. Arbaugh,et al.  Technological and Structural Characteristics, Student Learning and Satisfaction with Web-Based Courses , 2002 .

[61]  Deborah Compeau,et al.  Computer Self-Efficacy: Development of a Measure and Initial Test , 1995, MIS Q..

[62]  Magid Igbaria,et al.  Personal Computing Acceptance Factors in Small Firms: A Structural Equation Model , 1997, MIS Q..

[63]  Gordon B. Davis,et al.  Testing the Determinants of Microcomputer Usage via a Structural Equation Model , 1995, J. Manag. Inf. Syst..

[64]  Tino Fenech,et al.  Using Perceived Ease of Use and Perceived Usefulness to Predict Acceptance of the World Wide Web , 1998, Comput. Networks.

[65]  David Gefen,et al.  What Makes an ERP Implementation Relationship Worthwhile: Linking Trust Mechanisms and ERP Usefulness , 2004, J. Manag. Inf. Syst..

[66]  Fred D. Davis,et al.  A Theoretical Extension of the Technology Acceptance Model: Four Longitudinal Field Studies , 2000, Management Science.

[67]  Dale Goodhue,et al.  Understanding user evaluations of information systems , 1995 .

[68]  Hani I. Mesak,et al.  Factors influencing faculty computer literacy and use in jordan: a multivariate analysis , 2006 .

[69]  Chui Young Yoon,et al.  Measures of perceived end-user computing competency in an organizational computing environment , 2009, Knowl. Based Syst..

[70]  Nelson Oly Ndubisi,et al.  Factors of Online Learning Adoption: A Comparative Juxtaposition of the Theory of Planned Behaviour and the Technology Acceptance Model. , 2006 .

[71]  Peter A. Todd,et al.  Perceived Usefulness, Ease of Use, and Usage of Information Technology: A Replication , 1992, MIS Q..

[72]  Chao-Min Chiu,et al.  Internet self-efficacy and electronic service acceptance , 2004, Decis. Support Syst..

[73]  Elizabeth M. Weiss,et al.  Computer self-efficacy and anxiety scales for an Internet sample: testing measurement equivalence of existing measures and development of new scales , 2004, Comput. Hum. Behav..

[74]  Diane Hamilton,et al.  Adding contextual specificity to the technology acceptance model , 2006, Comput. Hum. Behav..

[75]  John Ingham,et al.  Why do people use information technology? A critical review of the technology acceptance model , 2003, Inf. Manag..

[76]  Robert Johansen,et al.  Upsizing The Individual In The Downsized Organization: Managing In The Wake Of Reengineering, Globalization, And Overwhelming Technological Change , 1994 .

[77]  Alan D. Carswell,et al.  Learner outcomes in an asynchronous distance education environment , 2002, Int. J. Hum. Comput. Stud..

[78]  Rajeev Sharma,et al.  The Contingent Effects of Management Support and Task Interdependence on Successful Information Systems Implementation , 2003, MIS Q..

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

[80]  Magid Igbaria,et al.  Microcomputer applications: An empirical look at usage , 1989, Inf. Manag..

[81]  Rolph E. Anderson,et al.  Multivariate Data Analysis with Readings , 1979 .

[82]  Detmar W. Straub,et al.  Trust and TAM in Online Shopping: An Integrated Model , 2003, MIS Q..

[83]  Detmar W. Straub,et al.  Gender Differences in the Perception and Use of E-Mail: An Extension to the Technology Acceptance Model , 1997, MIS Q..

[84]  Keenan A. Pituch,et al.  The influence of system characteristics on e-learning use , 2006, Comput. Educ..

[85]  Donald A. Norman,et al.  Things That Make Us Smart: Defending Human Attributes In The Age Of The Machine , 1993 .

[86]  Yi-Shun Wang,et al.  Investigating the determinants and age and gender differences in the acceptance of mobile learning , 2009, Br. J. Educ. Technol..

[87]  Chorng-Shyong Ong,et al.  Factors affecting engineers' acceptance of asynchronous e-learning systems in high-tech companies , 2004, Inf. Manag..

[88]  Eduardo Salas,et al.  E-Learning in Organizations , 2005 .

[89]  I. Ajzen,et al.  Belief, Attitude, Intention, and Behavior: An Introduction to Theory and Research , 1977 .

[90]  Terry Ryan,et al.  The Role of Social Presence and Moderating Role of Computer Self-Efficacy in Predicting the Continuance Usage of E-Learning Systems , 2004, J. Inf. Syst. Educ..

[91]  Debbie L. Hahs-Vaughn,et al.  Combined longitudinal effects of attitude and subjective norms on student outcomes in a web-enhanced course: A structural equation modelling approach , 2007, Br. J. Educ. Technol..