An adaptive group decision pattern and its use for industrial security management
American Journal of Environmental Protection
Volume 1, Issue 1, December 2012, Pages: 1-8
Received: Dec. 20, 2012; Published: Dec. 30, 2012
Views 4132      Downloads 160
Heiko Thimm, Pforzheim University, School of Engineering, Pforzheim, Germany
Robert Katura, Pforzheim University, School of Engineering, Pforzheim, Germany
Article Tools
Follow on us
In response to critical events Security Management Organizations (SMO) need to follow plans. Among others response plans can require decisions to be made by several SMO people. For security situations with a not too high time pressure it is possible to repeatedly perform a decision making process that includes decision makers that are separated by time and space. The better understanding and new information obtained in a decision process cycle by corresponding adaptations of the decision process and the underlying decision model can be exploited in the next following process cycle. This adaptive group decision pattern can lead to better decision results. In order to not over-challenge a SMO by the extra group coordination and moderation efforts of this pattern one can make use of a Group Decision Support System (GDSS) with special enhancements for this pattern. In this article a respective new group decision pattern is introduced and demonstrated in combination with an enhanced GDSS through a fictive industrial security case example. A process model for security incident management and a process model for adaptive complete asynchronous group decision making are described using the BPMN2.0 graphical process modeling standard. A research prototype of the assumed GDSS that is enhanced to support the new group decision making pattern is currently implemented.
Hazardous Material Management, Security Incident Management, Group Decision Making, Analytical Hie-rarchy Process (AHP), Process Modeling
To cite this article
Heiko Thimm, Robert Katura, An adaptive group decision pattern and its use for industrial security management, American Journal of Environmental Protection. Vol. 1, No. 1, 2012, pp. 1-8. doi: 10.11648/j.ajep.20120101.11
Bornstein, G., Kugler, T. andZiegelmeyer, A. (2004). In-di-vidual and group decisions in the centipede game: Are groups more "rational" players? Journal of Experimental Social Psychology, 40, 599-605.
BSI-Standard 100-4e, Business Continuity Management, Version 1.0,;jsessionid=B516CCA64C402611062EA2AD7BFAA514.2_cid294?__blob=publicationFile, accessed 11/23/2012.
Comes, T., Hiete, M. and Schultmann, F. (2010). A decision support system for multi-criteria decision problems under severe uncertainty in longer-term emergency management, Proc. 25th Mini EURO Conference on Uncertainty and Ro-bustness in Planning and Decision Making, Coimbra.
Esser, J. K. (1998). Alive and Well after 25 Years: A Review of Groupthink Research, Organizational Behavior and Human Decision Processes, Vol. 73, Nos. 2/3, pp. 116–141
Fahland, D. and Woith, H. (2008). Towards Process Models for Disaster Response. Business Process Management Workshops, pp. 254-265.
Gort, C. and Gerber, A. (2008). The Performance of Groups and Individuals in Financial Decision-Making, National Centre of Competence in Research Financial Valuation and Risk Management, Working Paper No. 460, February 2008, online version:, accessed 11/5/2012.
Kapucu,N. and Garayev, V. (2011). Collaborative De-ci-sion-Making in Emergency and Disaster Management, Taylor & Francis Group, International Journal of Public Admin-istration, 34: 366–375.
Levy, J.K., Hartmann, J., Li, K.W.,An,Y. and Asgary, A. (2007). Multi-criteria Decision Support Systems for Floor Hazard Mitigation and Emergency Response in Urban Wa-tersheds, Journal of the American Water Resources As-socia-tion, April 2007, Vol. 43, No. 2.
Mendonca, D., Rush, R., and Wallace, W.A. (2000). Timely knowledge elicitation from geographically separate mobile experts during emergency response, Elsevier Science, Safety Science 35, pp. 193-208.
Object Management Group (2011): Business Process Model and Notation (BPMN) Version 2.0 (2011), OMG Document Number: formal/2011-01-03.
Harand, A., Peinel, G. and Rose, T. (2011). Process Structures in Crisis Management, 6th Conference on Future Security, Berlin.
Ramabrahmam, B. and Swaminathan, G. (2000). Disaster management plan for chemical process industries. Case study: investigation of release of chlorine to atmosphere, Journal of Loss Prevention in the Process Industries, 13, 1, 57-62.
Saaty, T. L. (1980). The Analytic Hierarchy Process. McGraw Hill, New York.
SANS Institute Glossary,, accessed 11/21/2012.
Song, Y. and Hu, Y. (2009). Group Decision-Making Method in the Field of Coal Mine Safety Management Based on AHP with Clustering, Proc. of 6th International ISCRAM Confe-rence, Gothenburg, Sweden.
Stoner, J., (1961). A comparison of individuals and group decisions involving risks, Master Thesis, Massachusetts In-stitute of Technology, School of Industrial Management.
Thimm, H. (2011). A System Concept to Support Asyn-chronous AHP-Based Group Decision Making, IADIS In-ternational Conference Collaborative Technologies, Rom, ISBN: 978-972-8939-40-3, pp. 29-38.
Tseng, J., Liu, M., Chang, R., Su, J. and Shu, C. (2008). Emergency response plan of chlorine gas for process plants in Taiwan, Journal of Loss Prevention in the Process Industries, 21, 4, pp. 393-399.
Turoff, M., Chumer, M., Van de Walle, B., Yao, X. (2004). The Design of a Dynamic Emergency Response Management Information System, Journal of Information Technology Theory and Application (JITTA), Vol. 5(4), pp. 1-36
Science Publishing Group
1 Rockefeller Plaza,
10th and 11th Floors,
New York, NY 10020
Tel: (001)347-983-5186