Effects of System Characteristics on Adopting Web-Based Advanced Traveller Information System: Evidence from Taiwan

This study proposes a behavioural intention model that integrates information quality, response time, and system accessibility into the original technology acceptance model (TAM) to investigate whether system characteristics affect the adoption of Web-based advanced traveller information systems (ATIS). This study empirically tests the proposed model using data collected from an online survey of Web-based advanced traveller information system users. Con­firmatory factor analysis (CFA) was performed to examine the reliability and validity of the measurement model, and structural equation modelling (SEM) was used to evaluate the structural model. The results indicate that three system characteristics had indirect effects on the intention to use through perceived usefulness, perceived ease of use, and attitude toward using. Information quality was the most im­portant system characteristic factor, followed by response time and system accessibility. This study presents implica­tions for practitioners and researchers, and suggests direc­tions for future research.

[1]  Siriluck Rotchanakitumnuai,et al.  Modeling electronic service acceptance of an e-securities trading system , 2009, Ind. Manag. Data Syst..

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

[3]  Hsiu-Fen Lin,et al.  The role of online and offline features in sustaining virtual communities: an empirical study , 2007, Internet Res..

[4]  R. P. McDonald,et al.  Structural Equations with Latent Variables , 1989 .

[5]  T. Allen.  Managing the flow of technology , 1977 .

[6]  Peter Jones,et al.  The acquisition of pre-trip information: A stated preference approach , 1993 .

[7]  Mireia Valverde,et al.  Waiting in line for online services: a qualitative study of the user's perspective , 2006, Inf. Syst. J..

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

[9]  Marjan Hericko,et al.  Developers' perceptions of object-oriented frameworks - An investigation into the impact of technological and individual characteristics , 2011, Comput. Hum. Behav..

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

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

[12]  X. Koufteros.  Testing a model of pull production: a paradigm for manufacturing research using structural equation modeling , 1999 .

[13]  Kar Yan Tam,et al.  Determinants of User Acceptance of Digital Libraries: An Empirical Examination of Individual Differences and System Characteristics , 2002, J. Manag. Inf. Syst..

[14]  Varun Singh,et al.  Web-Based Advanced Traveler Information System for Developing Countries , 2010 .

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

[16]  B. Clegg,et al.  An investigation into the acceptance of online banking in Saudi Arabia , 2009 .

[17]  Sung J. Shim,et al.  User Assessment of Personal Digital Assistants Used in Pharmaceutical Detailing: System Features, Usefulness and Ease of Use , 2007, J. Comput. Inf. Syst..

[18]  Mihir A. Parikh,et al.  Paper Versus Electronic Medical Records: The Effects of Access on Physicians' Decisions to Use Complex Information Technologies , 2009, Decis. Sci..

[19]  P. Bentler,et al.  Cutoff criteria for fit indexes in covariance structure analysis : Conventional criteria versus new alternatives , 1999 .

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

[21]  Glenn Lyons,et al.  The value of integrated multimodal traveller information and its potential contribution to modal change , 2003 .

[22]  Wei Wang,et al.  Analyzing Travelers’ Intention to Accept Travel Information , 2010 .

[23]  Jae Hyoung Lee,et al.  An empirical examination of the acceptance behaviour of hotel front office systems: An extended technology acceptance model , 2008 .

[24]  Joseph S. Valacich,et al.  The online consumer's hierarchy of needs , 2007, CACM.

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

[26]  R. Bagozzi,et al.  On the evaluation of structural equation models , 1988 .

[27]  Matthew A. Waller,et al.  LATENT VARIABLES IN BUSINESS LOGISTICS RESEARCH: SCALE DEVELOPMENT AND VALIDATION / , 1994 .

[28]  G. Lyons,et al.  What Affects Use of Pretrip Public Transport Information? , 2008 .

[29]  Ingoo Han,et al.  The impact of Web quality and playfulness on user acceptance of online retailing , 2007, Inf. Manag..

[30]  Fred D. Davis.  A technology acceptance model for empirically testing new end-user information systems : theory and results , 1985 .

[31]  M. Taniguchi,et al.  Incorporating an information acquisition process into a route choice model with multiple information sources , 1999 .

[32]  Jie Jennifer Zhang,et al.  Analysis of Critical Website Characteristics: A Cross-Category Study of Successful Websites , 2005, J. Comput. Inf. Syst..

[33]  R Sanchez,et al.  Metropolitan Model Deployment Initiative : Seattle evaluation report , 2000 .

[34]  E. Molin,et al.  Use and Effects of Advanced Traveller Information Services (ATIS): A Review of the Literature , 2006 .

[35]  Paul P Jovanis,et al.  Usability of Statewide Web-Based Roadway Weather Information System , 2004 .

[36]  Mario Anžek,et al.  Information Source Quality in Intelligent Transport Systems , 2010 .

[37]  Min-Sook Park,et al.  Consumer adoption of virtual stores in Korea: Focusing on the role of trust and playfulness , 2009 .

[38]  Yi-Shun Wang.  Assessing e‐commerce systems success: a respecification and validation of the DeLone and McLean model of IS success , 2008, Inf. Syst. J..

[39]  Gwo‐Guang Lee,et al.  KMS adoption: the effects of information quality , 2009 .

[40]  Sung Youl Park,et al.  An Analysis of the Technology Acceptance Model in Understanding University Students' Behavioral Intention to Use e-Learning , 2009, J. Educ. Technol. Soc..

[41]  J Lappin,et al.  Why don't more people use advanced traveler information? Evidence from Seattle, Washington , 2004 .

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

[43]  Tomer Toledo,et al.  Evaluation of the Potential Benefits of Advanced Traveler Information Systems , 2006, J. Intell. Transp. Syst..

[44]  Sue Abdinnour-Helm,et al.  Examining the effects of information system characteristics and perceived usefulness on post adoption usage of information systems , 2008, Inf. Manag..

[45]  Analysis of Web-based WSDOT Traveler Information: Testing Users' Information Retrieval Strategies , 2002 .

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

[47]  Tae-Gyu Kim,et al.  A Longitudinal Analysis of Awareness and Use for Advanced Traveler Information Systems , 2004, J. Intell. Transp. Syst..

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

[49]  Ying Lee,et al.  Development of Freeway Travel Time Forecasting Models by Integrating Different Sources of Traffic Data , 2007, IEEE Transactions on Vehicular Technology.

[50]  Hjp Harry Timmermans,et al.  Information impact on quality of multimodal travel choices: conceptualizations and empirical analyses , 2007 .

[51]  Mary J. Culnan,et al.  The dimensions of accessibility to online information: implications for implementing office information systems , 1984, TOIS.

[52]  Mei Cao,et al.  B2C e-commerce web site quality: an empirical examination , 2005, Ind. Manag. Data Syst..

[53]  Fiona Fui-Hoon Nah,et al.  A study on tolerable waiting time: how long are Web users willing to wait? , 2004, AMCIS.