A composite indicator model to assess natural disaster risks in industry on a spatial level

Journal of Risk Research

Volumn 16, Issue 9, 2013, Pages 1077-1099

  Merz, Mirjam ^a   Hiete, Michael ^b   Comes, Tina ^a   Schultmann, Frank ^a  

^a KARLSRUHE INSTITUTE OF TECHNOLOGY   (Germany)

^b UNIVERSITY OF KASSEL   (Germany)

Author keywords

Composite indicator; Indirect losses; Industrial disaster risk; Multicriteria decision analysis; Vulnerability assessment

Indexed keywords

COMPOSITE INDICATORS; ENVIRONMENTAL CONSEQUENCES; INDUSTRIAL DISASTERS; INDUSTRIAL PRODUCTION; MULTI-ATTRIBUTE VALUE THEORIES; MULTI-CRITERIA DECISION ANALYSIS; VULNERABILITY ASSESSMENTS; VULNERABILITY FACTORS;

DECISION MAKING; DECISION THEORY; DISASTERS; INFORMATION MANAGEMENT; RISK ASSESSMENT; RISK MANAGEMENT; SUPPLY CHAINS;

INDUSTRY;

EID: 84887076191     PISSN: 13669877     EISSN: 14664461     Source Type: Journal    
DOI: 10.1080/13669877.2012.737820     Document Type: Article

References (70)

1. Adger, W.N. 2006. Vulnerability. Global Environmental Change 16, no. 3: 57-63.
2. Alexander, D. 2000. Confronting catastrophe. Hertfordshire: Terra.
3. ATC. 2002. Seismic vulnerability and impact of disruption of lifelines in the conterminous United States. Washington, DC: Earthquake Hazard Reduction Series, 58, Applied Technology Council.
4. Baas, S., S. Ramasamy, J.D. DePryck, and F. Battista. 2008. Disaster risk management systems analysis, environment, climate change, and bioenergy divisions. Rome: Food and Agriculture Organisation of the United Nations (FAO).
5. Bertsch, V. 2008. Uncertainty handling in multi-attribute decision support for industrial risk management. Karlsruhe: Universitätsverlag Karlsruhe. http://digbib.ubka.uni-karlsruhe.de/volltexte/1000007378.
6. Belton, V., and T. Stewart. 2002. Multiple criteria decision analysis - an integrated approach. Boston: Kluwer Academic Press.
7. Birkmann, J. 2006a. Indicators and criteria for measuring vulnerability: Theoretical bases and requirements. In Measuring vulnerability to hazards of natural origin - towards disaster resilient society, ed. J. Birkmann, 55-77. Tokyo: UNU Press.
8. Birkmann, J. 2006b. Measuring vulnerability to promote disaster-resilience societies: Conceptual frameworks and definitions. In Measuring vulnerability to hazards of natural origin - towards disaster resilient society, ed. J. Birkmann, 9-54. Tokyo: UNU Press.
9. Birkmann, J. 2007. Risk and vulnerability indicators at different scales: Applicability, usefulness and policy implications. Environmental Hazards 7: 20-31. (Pubitemid 47385414)
10. Birkmann, J., and B. Wisner. 2006. Measuring the un-measurable: The challenges of vulnerability. SOURCE, Publication Series of UNU-EHS, 5, Bonn.
11. Cardona, O.D. 2004. The need for rethinking the concepts of vulnerability and risk from a holistic perspective: A necessary review and criticism for effective risk management. In Mapping vulnerability, disasters, development, and people, ed. G. Bankoff, G. Frerks, and D. Hilhorst, 37-51. London: Earthscan.
12. Cruz, A.M., and N. Okada. 2008. Consideration of natural hazards in the design and risk management of industrial facilities. Natural Hazards 44, no. 2: 213-27.
13. Cutter, S.L., B.J. Boruff, and W.L. Shirley. 2003. Social vulnerability to environmental hazards. Social Science Quarterly 84, no. 2: 242-61. (Pubitemid 36737557)
14. Cutter, S.L., Ch.G. Burton, and C. Emrich. 2010. Disaster resilience indicators for benchmarking baseline conditions. Journal of Homeland Security and Emergency Management 7, no. 1: 1-22.
15. Dastous, P.-A., J. Nikiema, and S. Megaloconomos. 2008. Risk management: All stakeholders must do their part. Journal of Loss Prevention in the Process Industries 21: 367-73.
16. Destatis, Federal Statistical Office Germany. 2003. Klassifikation der Wirtschaftszweige - mit Erläuterungen [Classification of sectors of the economy with explanations]. Wiesbaden: Federal Statistical Office.
17. Destatis, Federal Statistical Office Germany. 2008. Kostenstruktur im Produzierenden Gewerbe 2006 [Cost structure in industry 2006], In Statistisches Jahrbuch für die Bundesrepublik Deutschland 2008, 366-399. Wiesbaden: Statistisches Bundesamt.
18. Dilley, M., R.S. Chen, U. Deichmann, A.L. Lerner-Lam, and M. Arnold. 2005. Natural disaster hotspots: A global risk analysis. Washington, DC: Weltbank.
19. Ellinger, T., and R. Haupt. 1996. Produktions- und Kostentheorie [Production and cost theory]. Stuttgart: Schäffer-Poeschel Verlag.
20. European Commission (EC). 2010. Risk assessment and mapping guidelines for disaster management. Brussels: Commission Staff Working Paper.
21. Fekete, A. 2009. Validation of a social vulnerability index in context to river-floods in Germany. Natural Hazards and Earth System Sciences 9: 393-403.
22. Fontela, E., and A. Gabus. 1976. The DEMATEL observer, DEMATEL report 1976. Genf: Battelle Geneva Research Center.
23. French, S. 2003. Modelling, making inferences and making decisions: The roles of sensitivity analysis. TOP 11, no. 2: 229-51.
24. Freudenberg, M. 2003. Composite indicators of country performance - a critical assessment, OECD Science, Technology and Industry Working Papers 2003/16, DSTI/DOC(2003) 16-JT00153477. Paris: OECD.
25. Gall, M. 2007. Indices of social vulnerability to natural hazards: a comparative evaluation. PhD thesis, University of South Carolina, Columbia City.
26. Gheorghe, A.V., R. Mock, and W. Kröger. 2000. Risk assessment of regional systems. Reliability Engineering & System Safety 70: 141-56.
27. Green, C.H., and A. van der Veen. 2007. Indirect economic damage: Concepts and guideline. In Evaluating flood damages: Guidance and recommendations on principles and methods, eds. F. Messner, E. Penning-Rowsell, C.H. Green, V. Meyer, S. Tunstall and A. van der Veen, 95-105. FLOODsite Report, T09-06-01, Wallington.
28. Hahn, H. 2003. Indicators and other instruments for local risk management for communities and local governments. Eschborn: Gesellschaft für Technische Zusammenarbeit GmbH (GTZ).
29. Hiete, M., and M. Merz. 2009. An indicator framework to assess the vulnerability of industrial sectors against indirect disaster losses. Proceedings of the International Conference on Information Systems for Crisis Response and Management (ISCRAM), 2009, Gothenburg, Paper Nr. 131.
30. Hiete, M., M. Merz, T. Comes, and F. Schultmann. 2011. Trapezoidal fuzzy DEMATEL method to analyze and correct for relations between variables in a composite indicator for disaster resilience, OR Spectrum. http://www. springerlink.com/content/qg561n2l2632 7573/fulltext.pdf.
31. Hossini, V. 2008. The role of vulnerability in risk management - Summary of the third PhD block course. Working Paper 8/2008, UNU Institute for Environment and Human Security (UNU-EHS), Bonn.
32. KBA. 2008. Verkehrsaufkommen im Jahr 2008 nach Güterabteilungen [Traffic volumes by type of goods in 2008]. In Verkehr deutscher Lastkraftfahrzeuge - Verkehrsaufkommen, Eigenschaften der Ladung, Kraftfahrt Bundesamt (KBA) [Traffic of German freight vehicles - volume of traffic, freight properties], Flensburg: German Federal Motor Transport Authority.
33. Khazai, B., M. Merz, C. Schulz, and D. Borst. 2013. An integrated indicator framework for spatial assessment of industrial and social vulnerability to indirect disaster losses. Natural Hazards, 1-23. Published online 20 January 2013, 10.1007/s11069-013-0551-z.
34. Kleindorfer, P.R., and H.G. Saad. 2005. Managing disruption risks in supply chains. Production and Operations Management 14, no. 1: 53-68. (Pubitemid 40763476)
35. Leitch, M. 2010. ISO 31000: 2009 - the new international standard on risk management. Risk Analysis 30: 887-92.
36. Liou, J.J.H., L. Yen, and G.H. Tzeng. 2008. Building an effective safety management system for airlines. Journal of Air Transport Management 14: 20-6.
37. Merz, M., M. Hiete, and F. Schultmann. 2010. An indicator framework for the assessment of the indirect disaster vulnerability of industrial production systems. Proceedings of the International Conference on Disaster Risk Reduction (IDRC), May 2010, Davos, Paper Nr. 131.
38. Messner, F., and C. Green. 2007. Fundamental issues in the economic evaluation of flood damage. In Evaluating flood damages: Guidance and recommendations on principles and methods, ed. F. Messner, E. Penning-Rowsell, C.H. Green, V. Meyer, S. Tunstall and A. van der Veen, 95-105. FLOODsite Report, T09-06-01, Wallington, 95-105.
39. Messner, F., and V. Meyer. 2005. Flood damage, vulnerability and risk perception - challenges for flood damage Research, UFZ Discussion Papers 13/2005, Umweltforschungszentrum Leipzig, Germany.
40. Munda, G., and M. Nardo. 2009. Non-compensatory/nonlinear composite indicators for ranking countries: a defensible setting. Applied Economics 41, no. 12: 1512-23.
41. Nardo, M., M. Saisana, A. Saltelli, and S. Tarantola. 2005a. Tools for composite indicator building. Report, EUR 221682 EN. Ispra: Joint Research Center.
42. Nardo, M., M. Saisana, A. Saltelli, M. Tarantola, and E. Giovanni. 2005b. Handbook on constructing composite indicators: Methodology and user guide, OECD Statistics Working Paper, TD/DOC(2005)3-JT00188147. Paris: OECD.
43. Nicolett, G., S. Scarpeta, and O. Boylaud. 2000. Summary indicators of market regulation with an extension to employment protection legislation, OECD Economic Department Working Papers, 226 ECO/WKP (99)18, Paris.
44. Okuyama, Y. 2007. Economic modeling for disaster impact analysis: Past. Present and Future, Economic systems research 19, no. 2: 115-24. (Pubitemid 46860604)
45. Peck, H. 2005. Drivers of supply chain vulnerability: An integrated framework. International Journal of Physical Distribution & Logistics Management 35, no. 4: 210-32. (Pubitemid 40831571)
46. Purdy, G. 2010. ISO 31000:2009 - setting a new standard for risk management. Risk Analysis 30, no. 6: 881-6.
47. Saisana, M., M. Nardo, and A. Saltelli. 2005. 2005 ESI sensitivity analysis, 2005 Environmental Sustainability Index Report, Yale Center for Environmental Law and Policy, New Haven, CT. http://www.yale.edu/esi.
48. Saisana, M., and A. Saltelli. 2008. Sensitivity analysis of the 2008 Environmental Performance Index, JRC Scientific and Technical Reports, EUR 23485 EN 2008, Joint Research Center (European Commission), Brüssel.
49. Saisana, M., A. Saltelli, and S. Tarantola. 2005. Uncertainty and sensitivity analysis techniques as tools for the quality assessment of composite indicators. Journal of the Royal Statistical Society 168, no. 2: 307-23. (Pubitemid 40427712)
50. Saisana, M., and S. Tarantola. 2002. State-of-the-art report on current methodologies and practices for composite indicator development, JRC Report, EUR 20408 EN. Ispra: Joint Research Centre.
51. Saltelli, A., M. Ratto, T. Andres, F. Campolongo, J. Caribani, D. Gatelli, M. Saisana, and S. Tarantola. 2009. Global sensitivity analysis - the primer. Chichester: Wiley & Sons.
52. Sauerwein, E., and M. Thurner. 1998. Der Risikomanagementprozess im Überblick [An overview of the risk management process]. In Betriebliches Risikomanagement [Operational risk management], ed. H. Hinterhuber, E. Sauerwein, and Ch. Fohler-Norek, 19- 39. Wien: Verlag Österreich.
53. Schaffer, A. 2002. Ecological input-output analysis: 'ECOLIO' - a model for conventional and ecological key sector analyses in Germany. Karlsruher Beiträge zur wirtschaftspolitischen Forschung, Vol.13. Baden-Baden: Nomos-Verlags-Gesellschaft.
54. Schmidtlein, M.C., R.C. Deutsch, W.W. Piegorsch, and S.L. Cutter. 2008. Sensitivity analysis of the social vulnerability index. Risk Analysis 4: 1099-114.
55. Statistical Office of Baden-Wuerttemberg. 2006a. Bruttowertschöpfung in jeweiligen Preisen für Deutschland und Baden-Württemberg [Gross value added in corresponding prices for Germany and Baden-Wuerttemberg] (available upon request in electronic form). Landesamt für Statistik Baden-Württemberg.
56. Statistical Office of Baden-Wuerttemberg. 2006b. Sozialversicherungspflichtig Beschäftigte am Arbeitsort nach Kreisen/kreisfreien Städten [Employees subject to social insurance contribution at place of work differentiated according to districts and urban municipalities] (available upon request in electronic form). Landesamt für Statistik Baden-Württemberg.
57. Statistical Office of Baden-Wuerttemberg. 2009. Baden-Württemberg - ein Standort im Vergleich [Baden-Wuerttemberg - a location in comparison]. http://www.statistik.badenwuerttemberg. de/Veroeffentl/803609002.pdf (accessed December 27, 2010).
58. Steinberg, L., H. Sengul, and A.M. Cruz. 2008. NATECH risk and management: An assessment of the state of the art. Natural Hazards 46, no. 2: 143-52.
59. Thywissen, K. 2006. Components of risk - a comparative glossary. SOURCE, 02/2006, UNU Institute for Environment and Human Security (UNU-EHS), Bonn.
60. Turner, B.L., R.E. Kasperson, P.A. Matsone, J.J. McCarthy, R.W. Corellg, L. Christensene, N. Eckley, et al. 2003. A framework for vulnerability analysis in sustainability science. Proceedings of the National Academy of Science (PNAS) 100, no. 14: 8074-9. (Pubitemid 36842500)
61. Twigg, B.L. 2001. Sustainable livelihoods and vulnerability to disasters. Disaster Management Working Paper, 2/2001, Benfield Greig Hazard Research Centre, London.
62. UNDP. 2004. A global report, reducing disaster risk: A challenge for development. Genf: United Nations Development Program.
63. UN/ISDR. 2005. Hyogo framework for action 2005-2015: Building the resilience of nations and communities to disasters. Genf: United Nations International Strategy for Disaster Reduction.
64. UN/ISDR. 2004. Living with risk. A global review of disaster reduction initiatives. Genf: United Nations International Strategy for Disaster Reduction.
65. Villagrán de Léon, J.C. 2006a. Vulnerability assessment. The sectoral approach. In Measuring vulnerability to hazards of natural origin - towards disaster resilient society, ed. J. Birkmann, 300-15. Tokyo: UNU Press.
66. Villagrán de Léon, J.C. 2006b. Vulnerability - a conceptional and methodological review, SOURCE, 04/2006, UNU Institute for Environment and Human Security (UNU-EHS), Bonn.
67. West, G.R., and R.P.C. Brown. 2003. Structural Change, Intersectoral Linkages And Hollowing-Out in the Taiwanese Economy, 1976-1994. Discussion Paper No 327, School of Economics, University of Queensland.
68. Wu, D., and D.L. Olson. 2008. A comparison of stochastic dominance and stochastic DEA for vendor evaluation. International Journal of Production Research 46, no. 8: 2313-27. (Pubitemid 351272743)
69. Wu, H.H., H.K. Chen, and J.I. Shieh. 2010. Evaluating performance criteria of employment service outreach program personnel by DEMATEL method. Expert Systems with Applications 37, no. 7: 5219-23.
70. Zhou, P., L.-W. Fan, and D.-Q. Zhou. 2010. Data aggregation in constructing composite indicators: A perspective of information loss. Expert Systems with Applications 37, no. 1: 360-5.