User Satisfaction and Continuance Intention for Using E-Training: A Structural Equation Model

With the growth in technology, organizations have started investing in building technology infrastructure. The application of technology in enterprises has provided various advantages such as low training cost and reliable training content. This study tries to investigate the attributes influencing user satisfaction and continuance intention to use e-training. The study derives ease of use and course content as the factors that can affect user satisfaction which further results in a user’s intention to continuously use e-trainings. Following structural equation modelling (SEM), the results of the study have indicated a significant relation between ease of use, course content and user satisfaction. Furthermore, it has also indicated that continuance intention to use e-training is an outcome of user satisfaction.

[1]  Ming-Chi Lee,et al.  Explaining and predicting users' continuance intention toward e-learning: An extension of the expectation-confirmation model , 2010, Comput. Educ..

[2]  Sean Walker Intent to Use Technology: Facilitation Effect of Group Presence , 2012 .

[3]  Kyu Yon Lim,et al.  A Model for Predicting Learning Flow and Achievement in Corporate e-Learning , 2012, J. Educ. Technol. Soc..

[4]  Ephraim R. McLean,et al.  Information Systems Success: The Quest for the Dependent Variable , 1992, Inf. Syst. Res..

[5]  SinghHarminder,et al.  Understanding the effect of e-learning on individual performance , 2015 .

[6]  Minhong Wang,et al.  A Performance-Oriented Approach to E-Learning in the Workplace , 2010, J. Educ. Technol. Soc..

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

[8]  Mazleena Salleh,et al.  The Impact of E-Learning in Workplace: Focus on Organizations and Healthcare Environments , 2012, Int. Arab. J. e Technol..

[9]  Matti Mäntymäki,et al.  Towards a Decomposed Expectation Confirmation Model of IT Continuance: The Role of Usability , 2017, Commun. Assoc. Inf. Syst..

[10]  Thurasamy Ramayah,et al.  System Characteristics, Satisfaction and E-Learning Usage: A Structural Equation Model (SEM) , 2012 .

[11]  Faizuniah Pangil,et al.  E-Training Adoption in the Nigerian Civil Service. , 2015 .

[12]  V. Morel,et al.  THE DIGITAL TALENT GAP. DEVELOPING SKILLS FOR TODAY'S DIGITAL ORGANIZATIONS , 2015 .

[13]  Forouzan Rezaeian Tiyar,et al.  Understanding students' satisfaction and continuance intention of e- learning: Application of expectation-confirmation model , 2015 .

[14]  T. Farahat Applying the Technology Acceptance Model to Online Learning in the Egyptian Universities , 2012 .

[15]  Andrew B. Artis,et al.  Technology perceptions in employees' use of self-directed learning , 2014 .

[16]  Christian Seel,et al.  Evaluating E-Government , 2005, I3E.

[17]  Khloud Bou Kamal,et al.  E-Training & Employees’ Performance a Practical Study on the Ministry of Education in the Kingdom of Bahrain , 2016 .

[18]  Rosnafisah Sulaiman,et al.  A Study on E-Training Adoption for Higher Learning Institutions , 2013 .

[19]  Chin-Chung Tsai,et al.  Social Support as a Neglected E-Learning Motivator Affecting Trainee's Decisions of Continuous Intentions of Usage. , 2015 .

[20]  Gökhan Aksu,et al.  Evaluating e-government systems in Turkey: The case of the 'e-movable system' , 2014, Inf. Polity.

[21]  Winston Bennett,et al.  A META-ANALYSIS OF THE RELATIONS AMONG TRAINING CRITERIA , 1997 .

[22]  Yi-Cheng Chen,et al.  An Empirical Study of College Students' Learning Satisfaction and Continuance Intention to Stick with a Blended e-Learning Environment , 2016, Int. J. Emerg. Technol. Learn..

[23]  Anita Lee-Post e-Learning Success Model: An Information Systems Perspective. , 2009 .

[24]  Tiago Oliveira,et al.  Understanding the Internet banking adoption: A unified theory of acceptance and use of technology and perceived risk application , 2014, Int. J. Inf. Manag..

[25]  Hamed Qahri Saremi,et al.  Factors Affecting Internet Banking Pre-usage Expectation Formation , 2013, 2013 46th Hawaii International Conference on System Sciences.

[26]  Heather K. Holden,et al.  Understanding the Influence of Perceived Usability and Technology Self-Efficacy on Teachers’ Technology Acceptance , 2011 .

[27]  Francisco José García-Peñalvo,et al.  Future Trends in the Design Strategies and Technological Affordances of E-Learning , 2016 .

[28]  Cheng-Hsun Ho,et al.  Continuance Intention of e-Learning Platform: Toward an Integrated Model , 2010, Int. J. Electron. Bus. Manag..

[29]  Josua Tarigan,et al.  FACTORS INFLUENCING USERS SATISFACTION ON E-LEARNING SYSTEMS , 2012 .

[30]  Sharifah Norul Akmar Binti Syed Zamri,et al.  A Meta-Analysis Study of Satisfaction and Continuance Intention to Use Educational Technology , 2017 .

[31]  Karen L. Becker,et al.  Factors for Successful E-Learning: Does Age Matter?. , 2017 .

[32]  Harminder Singh,et al.  Understanding the effect of e-learning on individual performance: The role of digital literacy , 2015, Comput. Educ..

[33]  Yin-Chai Wang,et al.  IMPROVING THE LEVEL OF COMPETENCIES FOR SMALL AND MEDIUM ENTERPRISES IN MALAYSIA THROUGH ENHANCING THE EFFECTIVENESS OF E-TRAINING: A CONCEPTUAL PAPER , 2013 .

[34]  Karin Sixl-Daniell,et al.  A Case Study in Corporate E-Learning , 2015, Int. J. Adv. Corp. Learn..

[35]  Mohammad Alamgir Hossain,et al.  Expectation–Confirmation Theory in Information System Research: A Review and Analysis , 2012 .

[36]  J. Gerring A case study , 2011, Technology and Society.

[37]  Emmanuel O. C. Mkpojiogu,et al.  Perceived usefulness, perceived ease of use, and perceived enjoyment as drivers for the user acceptance of interactive mobile maps , 2016 .

[38]  Nur Naha Abu Mansor,et al.  Interactivity and Trust as Antecedents of E-Training Use Intention in Nigeria: A Structural Equation Modelling Approach , 2017, Behavioral sciences.

[39]  Ephraim R. McLean,et al.  The DeLone and McLean Model of Information Systems Success: A Ten-Year Update , 2003, J. Manag. Inf. Syst..

[40]  Norhayati Zakuan,et al.  Examining Users' E-Satisfaction in the Usage of Social Networking Sites; Contribution from Utilitarian and Hedonic Information Systems , 2014 .

[41]  CalisirFethi,et al.  Predicting the Intention to Use a Web-Based Learning System , 2014 .

[42]  Kwoting Fang,et al.  Perceived Ease of Use, Trust, and Satisfaction as Determinants of Loyalty in e-Auction Marketplace , 2012, J. Comput..

[43]  Chung-Kuang Hou,et al.  User Acceptance of Business Intelligence Systems in Taiwan's Electronics Industry , 2014 .

[44]  Anol Bhattacherjee,et al.  Understanding Information Systems Continuance: An Expectation-Confirmation Model , 2001, MIS Q..

[45]  Jose Noguera,et al.  A Review of Excellence in Enterprise Information Systems Education: A Globe Perspective , 2006 .

[46]  Vera Belaya,et al.  The Use of e-Learning in Vocational Education and Training (VET): Systematization of Existing Theoretical Approaches , 2018, Journal of Education and Learning.

[47]  Christian Fernando Libaque Saenz,et al.  An expectation-confirmation model of continuance intention to use mobile instant messaging , 2016, Telematics Informatics.

[48]  Timothy Teo,et al.  A comparison of non-nested models in explaining teachers' intention to use technology , 2013, Br. J. Educ. Technol..

[49]  Xianggui Qu,et al.  Multivariate Data Analysis , 2007, Technometrics.

[50]  Thurasamy Ramayah,et al.  An Assessment of E-training Effectiveness in Multinational Companies in Malaysia , 2012, J. Educ. Technol. Soc..

[51]  A. E. Bayraktaroglu,et al.  Predicting the Intention to Use a Web‐Based Learning System: Perceived Content Quality, Anxiety, Perceived System Quality, Image, and the Technology Acceptance Model , 2014 .

[52]  Wann‐Yih Wu,et al.  An online shopping behavior model integrating personality traits, perceived risk, and technology acceptance , 2015 .