The diffusion of standard information models in road asset management - A study based on the human-technology-environment model

  • Daniela L. Nastasie
  • Andy Koronios


This paper reports on findings from the first stage of an exploratory study into the factors that influence the diffusion of ontologies in the Road Asset Management sector in Australia. The study investigates issues related to the diffusion of standard information models (taxonomies, road classifications and hierarchies, as well as various information systems conceptual schemas) in Road Asset Management. Individual and group interviews were conducted with 14 industry experts in four South Australian road authorities at state and local government level. The qualitative analysis of the findings is based on the preliminary HTE (human, technology, environment) conceptual model [1]. The findings suggest that the diffusion of standard information models at industry level is a complex process that combines human characteristics with technology and environment characteristics.


Information Model Industry Level Asset Management Personal Motivation Industry Expert 
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  1. 1.
    Nastasie, D.L., A. Koronios, and K. Sandhu. (2008) Factors Influencing the Diffusion of Ontologies in Road Asset Management-A Preliminary Conceptual Model. in Proceedings of the 3rd World Congress on Engineering Asset Management and Intelligent Maintenance Systems (WCEAM-IMS). Beijing, China: Springer-Verlag London Ltd.Google Scholar
  2. 2.
    OECD (Organization for Economic Co-operation and Development), (2008) OECD Information Technology Outlook 2008: Highlights.Google Scholar
  3. 3.
    Daconta, M.C., L.J. Obrst, and K.T. Smith, (2003) The Semantic Web: a guide to the future of XML, Web services, and knowledge management. 1st ed. Indianapolis, Ind. : Wiley Publishing, Inc.Google Scholar
  4. 4.
    Hepp, M. and J. de Bruijn, (2007) GenTax: A Generic Methodology for Deriving OWL and RDF-S Ontologies from Hierarchical Classifications, Thesauri, and Inconsistent Taxonomies, in The Semantic Web: Research and Applications. p. 129-144.Google Scholar
  5. 5.
    Nastasie, D.L. and A. Koronios, (2009) The Role of Standard Information Models In Road Asset Management, in Fourth World Congress on Engineering Asset Management (WCEAM), Springer-Verlag London Ltd.: Athens, Greece.Google Scholar
  6. 6.
    Austroads. (2009) Asset Management - FAQ. [cited 2009 01 April]; Available from: Scholar
  7. 7.
    Australian Government-Productivity Commission, (2008) Assessing Local Government Revenue Raising Capacity-Research Report. Canberra.Google Scholar
  8. 8.
    Markus, M.L., C.W. Steinfield, and R.T. Wigand, (2003) The Evolution of Vertical IS Standards: Electronic Interchange Standards in the US Home Mortgage Industry, in ICIS 2003 MISQ Special Issue Workshop on Standards.Google Scholar
  9. 9.
    Markus, M.L., et al., (2006) Industry-Wide Information Systems Standardization as Collective Action: The Case of the U.S. Residential Mortgage Industry. MIS Quarterly, 30, 439-465.Google Scholar
  10. 10.
    Wigand, R.T., C.W. Steinfield, and M.L. Markus, (2005) Information Technology Standards Choices and Industry Structure Outcomes: The Case of the U.S. Home Mortgage Industry. Journal of Management Information Systems, 22(2), 165-191.Google Scholar
  11. 11.
    Koronios, A., et al., (2007) Integration Through Standards – an Overview of International Standards for Engineering Asset Management, in Second World Congress on Engineering Asset Management, 11-14 June 2007. Harrogate, United Kingdom.Google Scholar
  12. 12.
    Katz, M.L. and C. Shapiro, (1986) Technology Adoption in the Presence of Network Externalities. Journal of Political Economy, 94(4), 822.CrossRefGoogle Scholar
  13. 13.
    Rogers, E.M., (2003) Diffusion of innovations. 5th ed. New York: Free Press.Google Scholar
  14. 14.
    Tornatzky, L.G. and M. Fleischer, (1990) The Processes of Technological Innovation. Lexington, MA: Lexington Books.Google Scholar
  15. 15.
    Davis, F.D., (1989) Perceived Usefulness, Perceived Ease of Use, and User Acceptance of Information Technology. MIS Quarterly, 13(3), 318-340.CrossRefGoogle Scholar
  16. 16.
    Davis, F.D., R.P. Bagozzi, and P.R. Warshaw, (1989) User Acceptance of Computer Technology: A Comparison of Two Theoretical Models. Management Science, 35(8), 982-1003.CrossRefGoogle Scholar
  17. 17.
    Weiss, M. and C. Cargill, (1992) Consortia in the Standards Development Process. Journal of the American Society for Information Science, 43(8), 559-565.CrossRefGoogle Scholar
  18. 18.
    Kindleberger, C.P., (1983) Standards as Public, Collective and Private Goods. Kyklos, 36(3), 377.CrossRefGoogle Scholar
  19. 19.
    Skuce, D., (1997) How We Might Reach Agreement on Shared Ontologies: A Fundamental Approach in AAAI Technical Report SS-97-06. University of Ottawa.Google Scholar
  20. 20.
    Laera, L., et al., (2006) Reaching Agreement over Ontology Alignments, in The Semantic Web - ISWC 2006. 371-384.Google Scholar
  21. 21.
    Hepp, M., (2007) Possible Ontologies: How Reality Constrains the Development of Relevant Ontologies. Internet Computing, IEEE, 11(1), 90-96.CrossRefGoogle Scholar
  22. 22.
    Markus, M.L., (2002) Power, Politics and MIS Implementation, in Qualitative research in information systems : a reader, M.D. Myers and D. Avison, Editors. SAGE Publications: London. 19-48.Google Scholar

Copyright information

© Springer-Verlag 2010

Authors and Affiliations

  • Daniela L. Nastasie
    • 1
    • 2
  • Andy Koronios
    • 1
    • 2
  1. 1.Cooperative Research Centre for Integrated Engineering Asset Management (CIEAM)BrisbaneAustralia
  2. 2.Systems Integration and ITUniversity of South AustraliaMawson LakesAustralia

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