Modelling cost estimation for accessing spatial data using fuzzy logic and time-driven activity based costing in the context of an NSDI

References

• ACIL Tasman (2009) Spatial Information in the New Zealand Economy; Realizing Productivity Gains Available from: http://www.geospatial.govt.nz/sites/default/files/assets/News/spatial-information-in-the-new-zealand-economy-2009.pdf [Accessed on 4 May 2012].
   Google Scholar
• AlmirallP., BergadàM., & RosP. (2008) The Socio-Economic Impact of the Spatial Data Infrastructure of Catalonia. Directorate General Joint Research Centre, Technical Report, Institute for Environment and Sustainability. Ispra, Italy.
   Google Scholar
• BanA., CoroianuL., & GrzegorzewskiP. (2011) Trapezoidal approximation and aggregation. Science Direct, vol. 177, pp. 45–59.
   Google Scholar
• BernardL., & CragliaM. (2010) SDI From Spatial Data Infrastructure to Service Driven Infrastructure Joint Research Centre of the European Commission, Available from: http://www.ec-gis.org/sdi/ws/crosslearning/papers/PP%20Lars%20Bernard%20-%20Max%20Craglia.pdf. [Accessed on 22 April 2012].
   Google Scholar
• BruggemanW., EveraertP., AndersonS., & LevantY. (2005) Modeling Logistics Costs using Time-Driven ABC: A Case in a Distribution Company Available from: http://cosmic.rrz.uni-hamburg.de/webcat/hwwa/edok05/be193g/wp05-332.pdf [Accessed on 21st April, 2012].
   Google Scholar
• CampagnaM., & CragliaM. (2012) The socioeconomic impact of the spatial data infrastructure of Lombardy. Environment and Planning B: Planning and Design, vol. 39, no. 6, pp. 1069–1083.
   Web of Science ®Google Scholar
• ChanT., FeeneyM., RajabifardA., & WilliamsonI. (2001) The Dynamic Nature of Spatial Data Infrastructures: A Method of Descriptive Classification Available from: http://www.csdila.unimelb.edu.au/publication/journals/DynamicNature_of_SDI_Methodof_Descriptive_classification.pdf [Accessed on 21st April, 2012].
   Google Scholar
• ChansaadA., RattanamaneeW., ChaiprapatA., & YenradeeP. (2012) Fuzzy time-driven activity-based costing model in an uncertain manufacturing environment. Proceedings of the Asia Pacific Industrial Engineering & Management Systems Conference, Phuket, Thailand, December 2–5, 2012.
   Google Scholar
• ChiuY., & ParkC.S. (1998) Capital budgeting decisions with fuzzy projects. The Engineering Economist, vol. 43, no. 2, pp. 125–150.
   Google Scholar
• ChungC., WangW., & ChangC. (2013) Sustainable development indicators of festival activities study of modified Fuzzy Delphi theory. Proceedings of the international conference on Business and Information Bali, July 7–9, 2013.
   Google Scholar
• CianciA., & FalsettaD. (2008) Impact of investors' status on their evaluation of positive and negative, and past and future information. Accounting and Finance, vol. 48, pp. 719–739.
   Web of Science ®Google Scholar
• Commission of the European Communities (CEC) (2004) COM (2004) 516 final, Proposal for a Directive of the European Parliament and the Council Establishing an Infrastructure for Spatial Information in the Community (INSPIRE), Commission of the European Communities, Brussels.
   Google Scholar
• CragliaM., & CampagnaM. (2009) Advanced regional SDIs in Europe: comperative cost-benefit evaluation and impact assessment perspectives, International Journal for Spatial Data Infrastructures Research 2007.
   Google Scholar
• Dal-RiF., AlonsoJ., & DuarteC. (2005) Modeling the subjectivity in the target costing process; an experimental approach based on the fuzzy logic concepts. The International Journal of Digital Accounting Research, vol. 5, no. 10, pp. 203–222.
   Google Scholar
• DuboisD., & PradeH. (1987) The mean value of a fuzzy number. Fuzzy Sets and Systems, vol. 24, no. 3, pp. 279–300.
   Web of Science ®Google Scholar
• ElwoodS. (2008) Grassroots groups as stakeholders in spatial data infrastructures: challenges and opportunities for local data development and sharing. International Journal of Geographical Information Science, vol. 22, no. 1, pp. 71–90.
   Web of Science ®Google Scholar
• FlahatiA., & MirzaeianR. (2012) The economic analysis and evaluation of the investment projects with special refrences to the fuzzy approach. Life Science Journal, vol. 9, no. 3, pp. 2691–2695 Available from: http://www.lifesciencesite.com.
   Google Scholar
• GrzegorzewskiP. (1998) Metrics and orders in space of fuzzy numbers. Fuzzy Sets and Systems, vol. 97, no. 1, pp. 83–94.
   Web of Science ®Google Scholar
• HymanG., PereaC., ReyD., & LanceK. (2003) Survey of the development of national spatial data infrastructures in Latin America and the Caribbean. Proceedings of ESRI User's Conference, San Diego, CA, July 2003.
   Google Scholar
• IraniZ., SharifA., LoveP., & KahramanC. (2002) Applying concepts of fuzzy cognitive mapping to model: The IT/IS investment evaluation process. International Journal of Production Economics, vol. 75, no. 1-2, pp. 199–211.
   Web of Science ®Google Scholar
• IshikawaA., AmagasaM., ShigaT., TomizawaG., TatsutaR., & MienoH. (1993) The max-min Delphi method and Fuzzy Delphi method via fuzzy integration. Fuzzy Sets and Systems, vol. 55, no. 3, pp. 241–253.
   Web of Science ®Google Scholar
• KahnemanD., & TverskyA. (1979) Prospect theory: An analysis of decision under risk. Econometrica, vol. 47, no. 2, pp. 263–291.
   Web of Science ®Google Scholar
• KahnemanD., & TverskyA. (1984) Choices, values, and frames. American Psychologist, vol. 39, no. 4, pp. 341–350.
   Web of Science ®Google Scholar
• KaplanR., & AndersonS. (2004) Time-driven activity-based costing. Harvard Business Review, vol. 82, no. 11, pp. 131–138.
   PubMed Web of Science ®Google Scholar
• KaplanR., & AndersonS. (2007) Time-driven Activity-based Costing: A Simpler and More Powerful Path to Higher Profits, Harvard Business School Publishing, USA.
   Google Scholar
• KaplanR., & CooperR. (September 1992) Activity-based systems: Measuring the costs of resource usage. Accounting Horizons, vol. 6, no. 3, pp. 1–13.
   Google Scholar
• MaZ., ShaoC., MaS., & YeZ. (2011) Constructing road safety performance indicators using Fuzzy Delphi method and Grey Delphi method. Expert Systems with Applications, vol. 38, no. 3, pp. 1509–1514.
   Web of Science ®Google Scholar
• MakangaP., & SmitJ. (2008) A review of the status of Spatial Data Infrastructure Implementation in Africa. Free and Open Source Software for Geospatial (Foss4g) Conference, Cape Town, South Africa, 2008.
   Google Scholar
• McLarenR. (2006) How to avoid National Spatial Data Infrastructure (NSDI) Cul-de-sacs. Shaping the Change XXIII FIG Congress, Munich, Germany, October 8–13, 2006.
   Google Scholar
• MasserI. (2009) Changing notions of a spatial data infrastructure. In: van Loenen, B., Besemer, J.W.J., & Zevenbergen, J.A., eds., Netherlands Geodetic Commission 48, 2009, SDI Convergence. Research, Emerging Trends, and Critical Assessment.
   Google Scholar
• MwaikamboE., & HagaiM. (2011) The need for assessing costs of inefficient access to fundamental spatial datasets in least developed countries, Proceedings of The First Conference on Avances in Geomatics Research, Kampala, Uganda. August, 2011.
   Google Scholar
• NachtmannH., & NeedyK.L. (2003) Methods for handling uncertainty in activity based costing systems. The Engineering Economist, vol. 48, no. 3, pp. 259–282.
   Google Scholar
• NoucherM., & GolayF. (2010) From the assessment of spatial data infrastructure to the assessment of community of practice advocating an approach by uses, GeoValue 2010, Available from: http://hal.inria.fr/docs/00/64/10/59/PDF/GeoValue2010_Noucher_Golay_final.pdf [Assessed on 23 May 2012].
   Google Scholar
• NovemskyN., & KahnemanD. (2005) The boundaries of loss aversion. Journal of Marketing Research, vol. 42, no. 2, pp. 119–128.
   Web of Science ®Google Scholar
• PenevaV., & PopchevI. (1998) Comparison of clusters from fuzzy numbers. Fuzzy Sets and Systems, vol. 97, no. 1, pp. 75–81.
   Web of Science ®Google Scholar
• PigramC., & ScottG. (2007) Spatial Enablement of Australian Government Available from: http://www.csdila.unimelb.edu.au/BeyondSpatialEnablement/pdf/Pigram.pdf [Accessed on 2 May 2012].
   Google Scholar
• Rajabifard, A., ed. (2007) Towards a Spatially Enabled Society, The University of Melbourne, ISBN 978-0-7325-1620-8Australia, pp. 224.
   Google Scholar
• RajabifardA. (2009) Realising spatially enabled societies – A global perpesctive in response to millennium development goals, Proceedings of the 18 UNRCC-AP Conference, Bangkok, Thailand 26-30 October 2009.
   Google Scholar
• RajabifardA. (2010) Spatially Enabled Government and Society-the Global Perspective Figure Conference. Sydney, Australia. 11-16 April 2010.
   Google Scholar
• RajabifardA., & WilliamsonI. (2002) Key factors influencing regional SDI development and relevance to global and other levels, Proceedings of the 6 th Global Spatial Data Infrastructure (GDSI6), Budapest, Hungary, 16-19 September 2002.
   Google Scholar
• RajabifardA., FeeneyM., & WilliamsonI.P. (2002) The cultural aspects of sharing and dynamic partnerships within an SDI hierarchy. Cartography Journal, vol. 31, no. 1, pp. 21–32.
   Google Scholar
• RoztockiN., & WeistrofferH. (2005) Evaluating information technology investments: A fuzzy activity-based costing approach. Journal of Information Science and Technology, vol. 2, no. 4, pp. 31–43.
   Google Scholar
• SorokaS. (2006) Good news and bad news: Asymmetric responses to economic information. The Journal of Politics, vol. 68, no. 2, pp. 372–385.
   Web of Science ®Google Scholar
• UNGIWG (2007) Strategy for Developing and Implementing a United Nations Spatial Data Infrastructure in Support of Humanitarian Response, Economic Development, Environmental Protection, Peace and Safety Available from: http://www.ungiwg.org/docs/unsdi/UNSDI_Strategy_Implementation_Paper.pdf [Assessed on 19th April, 2012].
   Google Scholar
• WilliamsonI., GrantD., & RajabifardA. (2005) Land administration and spatial data infrastructures. FIG Working Week 2005 and GSDI-8, Cairo, Egypt, April 16–21.
   Google Scholar
• YawsonD., Ato ArmahF., Okae-AntiD., PaulK., EssandohP., & AfrifaE. (2011) Enhancing spatial data accessibility in Ghana; Prioritization of influencing factors using AHP. International Journal of Spatial Data Infrastructures Research, vol. 6, pp. 290–310.
   Google Scholar
• ZadehL. (1965) Fuzzy sets. Information and Control, vol. 8, no. 3, pp. 338–353.
   Google Scholar