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

  • Ting-Wei Lin Department of Tourism, Ming Chuan University
  • Chia-Yen Lin Department of Public Administration and Management, National University of Tainan
  • Wen-Ho Hsu Logistics & Warehouse Management Department, Taiwan Semiconductor Manufacturing Company Limited
DOI: https://doi.org/10.7307/ptt.v26i1.1224
Keywords: web-based advanced traveler information system (ATIS), system characteristics, travelers’ adoption, technology acceptance model (TAM), behavioral intention model,

Abstract

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.

Author Biography

Ting-Wei Lin, Department of Tourism, Ming Chuan University
Dr. Ting-Wei Lin is currently an assistant professor of Departmrnt of Tourism, Ming Chuan University, Taiwan. He received Ph.D. degree in Transportation and Communication Management Science from National Cheng Kung University in 2007. His teaching and research interests are intelligent transportation systems (ITS), travel information management, and tourism transportation management.

References

Singh, V., Kumar, P.: Web-based Advanced Traveller Information System for developing countries, Journal of Transportation Engineering, Vol. 136, No. 9, 2010, pp. 836-845

Toledo, T., Beinhaker, R.: Evaluation of the potential benefits of Advanced Traveller Information Systems, Journal of Intelligent Transportation Systems, Vol. 10, No. 4, 2006, pp. 173-183

Cluett, C.: Travellers’ use of the WSDOT traffic conditions Web site: Customer satisfaction evaluation; Metropolitan model deployment Initiative: Seattle, Washington. Seattle, WA: Washington State Department of Transportation. 2000

Goulias, K.G., Kim, T.G., Pribyl, O.: A longitudinal analysis of awareness and use for Advanced Traveller Information Systems, Intelligent transportation systems, Vol. 8, No. 1, 2004, pp. 3-17

Peirce, S., Lappin, J.: Why don’t more people use advanced traveller information? Evidence from the Seattle area. In Annual Meeting Compendium, Transportation Research Board of the National Academies, Washington, D.C., 10-17. 2004.

Sauer, G., Rose, E., Kolko, B.E., Haselkorn, M.: Analysis of Web-based WSDOT Traveller Information: Testing Users’ Information Retrieval Strategies. Seattle, WA: Washington State Department of Transportation. 2002

Chorus, C.G., Arentze, T.A., Timmermans, H.J.P.: Information impact on quality of multimodal travel choices: conceptualizations and empirical analyses, Transportation, Vol. 34, No. 6, 2007, pp. 625-645

Chorus, C. G., Molin, E.J.E., Van Wee, B.: Use and effects of Advanced Traveller Information Services (ATIS): A review of the literature, Transport Reviews, Vol. 26, No. 2, 2006, pp. 127-149

Polak, J., Jones, P.: The acquisition of pre-trip information - A stated preference approach, Transportation, Vol. 20, No. 2, 1993, pp. 179-198

Kenyon, S., Lyons, G.: The value of integrated multimodal traveller information and its potential contribution to modal change, Transportation Research Part F: Traffic Psychology and Behaviour, Vol. 6, No. 1, 2003, pp. 1-21

Farag, S., Lyons, G.: What affects use of pretrip public transport information? Empirical results of a qualitative study, Transportation Research Record, No. 2069, 2008, pp. 85-92

Xu, C., Wang, W., Chen, J., Wang, W., Yang, C., Li, Z.: Analyzing travellers’ intention to accept travel information, Transportation Research Record, Vol. 2156, 2010, pp. 93-100

Davis, F.D.: User acceptance of information technology - System characteristics, user perceptions and behavioral impacts, International Journal of Man-Machine Studies, Vol. 38, No. 3, 1993, pp. 475-487

Hong, W., Thong, J.Y.L., Wong, W.-M., Tam, K.-Y.: Determinants of user acceptance of digital libraries: An empirical examination of individual differences and system characteristics, Journal of Management Information Systems, Vol. 18, No. 3, 2001, pp. 97-124

Pituch, K.A., Lee, Y.-k.: The influence of system characteristics on e-learning use, Computers & Education, Vol. 47, No. 2, 2006, pp. 222-244

Polančič, G., Heričko, M., Pavlič, L.: Developers’ perceptions of object-oriented frameworks – An investigation into the impact of technological and individual characteristics, Computers in Human Behavior, Vol. 27, No. 2, 2011, pp. 730-740

Saeed, K.A., Abdinnour-Helm, S.: Examining the effects of information system characteristics and perceived usefulness on post adoption usage of information systems, Information & Management, Vol. 45, No. 6, 2008, pp. 376-386

Shim, S.J., Viswanathan, V.: User assessment of personal digital assistants used in pharmaceutical detailing: system features, usefulness and ease of use, Journal of Computer Information Systems, Vol. 48, No. 1, 2007, pp. 14-21

Davis, F.D.: A technology acceptance model for empirically testing new end-user information systems: Theory and results. In Doctoral Diddertation, Sloan School of Management: Massachusetts Institute of Technology, Cambridge, MA. 1986

Davis, F.D., Bagozzi, R.P., Warshaw, P.R.: User acceptance of computer technology - A comparison of 2 theoretical models, Management Science, Vol. 35, No. 8, 1989, pp. 982-1003

Venkatesh, V., Davis, F. D.: A theoretical extension of the Technology Acceptance Model: Four longitudinal field studies, Management Science, Vol. 46, No. 2, 2000, pp. 186-204

Fishbein, M., Ajzen, I.: Belief, attitude, intention, and behavior: An Introduction to theory and research. Reading, MA: Addison-Wesley. 1975

Davis, F.D.: Perceived usefulness, perceived ease of use, and user acceptance of information technology, MIS Quarterly, Vol. 13, No. 3, 1989, pp. 319-340

DeLone, W.H., McLean, E.R.: Information systems success: The quest for the dependent variable, Information Systems Research, Vol. 3, No. 1, 1992, pp. 60-95

DeLone, W.H., McLean, E.R.: The DeLone and McLean model of information systems success: a ten-year update, Journal of Management Information Systems, Vol. 19, No. 4, 2003, pp. 9-30

Wang, Y.-S.: Assessing e-commerce systems success: A respecification and validation of the DeLone and McLean model of IS success, Information Systems Journal, Vol. 18, No. 5, 2008, pp. 529-557

Jelusic, N., Anzek, M., Ivankovic, B.: Information source quality in intelligent transportation systems, PROMET - Traffic & Transportation, Vol. 22, No. 2, 2010, pp. 125-131

Jensen, M., Cluett, C., Wunderlich, K., Deblasio, A., Sanchez, R.: Metropolitan Model Develoyment Initiative Seattle Evaluation Report Final Draft. U.S. Department of Transportation. 2000

Fayish, A.C., Jovanis, P.P.: Usability of statewide web-based roadway weather information system. In Driver and Vehicle Simulation, Human Performance, and Information Systems for Highways; Railroad Safety; and Visualization in Transportation, 44-54 Washington: Transportation Research Board Natl Research Council. 2004

Hato, E., Taniguchi, M., Sugie, Y., Kuwahara, M., Morita, H.: Incorporating an information acquisition process into a route choice model with multiple information sources, Transportation Research Part C: Emerging Technologies, Vol. 7, No. 2–3, 1999, pp. 109-129

Polydoropoulou, A., Ben-Akiva, M.: The effect of advanced traveller information systems (ATIS) on travellers’ behaviour. In Behavioural and Network Impacts of Driver Information Systems, 317-352 (Eds Emmerink RHM, Nijkamp P). Aldershot, Ashgate, UK. 1998

Kim, T.G., Lee, J.H., Law, R.: An empirical examination of the acceptance behaviour of hotel front office systems: An extended technology acceptance model, Tourism Management, Vol. 29, No. 3, 2008, pp. 500-513

Lin, H.-F.: The role of online and offline features in sustaining virtual communities: an empirical study, Internet Research, Vol. 17, No. 2, 2007, pp. 119-138

Al-Somali, S. A., Gholami, R., Clegg, B.: An investigation into the acceptance of online banking in Saudi Arabia, Technovation, Vol. 29, No. 2, 2009, pp. 130-141

Tarafdar, M., Zhang, J.: Analysis of critical website characteristics: A cross-category study of successful websites, Journal of Computer Information Systems, Vol. 46, No. 2, 2005, pp. 14-24

Nah, F. F.-H.: A study on tolerable waiting time: how long are Web users willing to wait?, Behaviour & Information Technology, Vol. 23, No. 3, 2004, pp. 153-163

Ryan, G., Valverde, M.: Waiting in line for online services: a qualitative study of the user’s perspective, Information Systems Journal, Vol. 16, No. 2, 2006, pp. 181-211

Valacich, J.S., Parboteeah, D.V., Wells, J.D.: The online consumer’s hierarchy of needs, Communications of the ACM, Vol. 50, No. 9, 2007, pp. 84-90

Ilie, V., Van Slyke, C., Parikh, M.A., Courtney, J.F.: Paper versus electronic medical records: The effects of access on physicians’ decisions to use complex information technologies, Decision Sciences, Vol. 40, No. 2, 2009, pp. 213-241

Park, S. Y.: An analysis of the technology acceptance model in understanding university students’ behavioral intention to use e-learning, Educational Technology & Society, Vol. 12, No. 3, 2009, pp. 150-162

Rotchanakitumnuai, S., Speece, M.: Modeling electronic service acceptance of an e-securities trading system, Industrial Management & Data Systems, Vol. 109, No. 8-9, 2009, pp. 1069-1084

Allen, T. J.: Managing the flow of technology. Cambridge, Mass.: MIT Press. 1977

Culnan, M. J.: The diminsions of accessibility to online information - Implications for implementing office information systems, Acm Transactions on Office Information Systems, Vol. 2, No. 2, 1984, pp. 141-150

Kuo, R. Z., Lee, G. G.: KMS adoption: the effects of information quality, Management Decision, Vol. 47, No. 10, 2009, pp. 1633-1651

Ahn, T., Ryu, S., Han, I.: The impact of Web quality and playfulness on user acceptance of online retailing, Information & Management, Vol. 44, No. 3, 2007, pp. 263-275

Oh, S.H., Kim, Y.M., Lee, C.W., Shim, G.Y., Park, M.S., Jung, H.S.: Consumer adoption of virtual stores in Korea: Focusing on the role of trust and playfulness, Psychology & Marketing, Vol. 26, No. 7, 2009, pp. 652-668

Hair, J.F., Anderson, R.E., Tatham, R.L., Black, W.C.: Multivariate Data Analysis. NJ: Prentice-Hall. 1998

Bollen, K.A.: Structural Equations with Latent Variables. New York: Wiley. 1989.

Hu, L.-T., Bentler, P.M.: Cutoff criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives, Structural Equation Modeling, Vol. 6, No. 1, 1999, pp. 1-55

Bagozzi, R.P., Yi, Y.: On the evaluation of structural equation models, Journal of the Academy of Marketing Science, Vol. 16, No. 1, 1988, pp. 74-94

Fornell, C., Larcker, D.F.: Evaluating structural equation models with unobservable variables and measurement error, Journal of Marketing Research, Vol. 18, No. 1, 1981, pp. 39-50

Dunn, S.C., Seaker, R.F., Waller, M.A.: Latent variables in business logistics research: scale development and validation, Journal of Business Logistics, Vol. 15, No. 2, 1994, pp. 145-172

Koufteros, X.A.: Testing a model of pull production: a paradigm for manufacturing research using structural equation modeling, Journal of Operations Management, Vol. 17, No. 4, 1999, pp. 467-488

Wei, C.-H., Lee, Y.: Development of freeway travel time forecasting models by integrating different sources of traffic data, IEEE Transactions on Vehicular Technology, Vol. 56, No. 6, 2007, pp. 3682-3694

Cao, M., Zhang, Q.Y., Seydel, J.: B2C e-commerce Web site quality: An empirical examination, Industrial Management & Data Systems, Vol. 105, No. 5-6, 2005, pp. 645-661

Goodhue, D.L., Thompson, R.L.: Task-technology fit and individual performance, MIS Quarterly, Vol. 19, 1995, pp. 213-236

Published
2014-02-28
How to Cite
1.
Lin T-W, Lin C-Y, Hsu W-H. Effects of System Characteristics on Adopting Web-Based Advanced Traveller Information System: Evidence from Taiwan. Promet [Internet]. 2014Feb.28 [cited 2024Apr.20];26(1):53-. Available from: http://traffic.fpz.hr/index.php/PROMTT/article/view/1224
Issue
Vol 26 No 1 (2014)
Section
Articles

Authors who publish with this journal agree to the following terms:

  • Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a Creative Commons Attribution License that allows others to share the work with an acknowledgement of the work's authorship and initial publication in this journal.
  • Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgement of its initial publication in this journal.
  • Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work (See The Effect of Open Access).