Assessing critical success factors for military decision support

Expert Systems with Applications

Volumn 37, Issue 12, 2010, Pages 8229-8241

  Louvieris, Panos ^a   Gregoriades, Andreas ^a   Garn, Wolfgang ^a  

^a UNIVERSITY OF SURREY   (United Kingdom)

Author keywords

Bayesian belief networks; Case based reasoning; Critical success factors; Decision making

Indexed keywords

ARTIFICIAL INTELLIGENCE; CASE BASED REASONING; COMPUTER AIDED SOFTWARE ENGINEERING; DECISION MAKING; DECISION SUPPORT SYSTEMS; ENTERPRISE RESOURCE PLANNING; INTELLIGENT AGENTS;

AUTOMATED CONFIGURATION; COMPUTER GENERATED FORCES; CONDITIONAL PROBABILITY TABLES; CRITICAL SUCCESS FACTOR; DECISION MAKING PROCESS; INFORMATION OVERLOADS; MILITARY DECISION MAKING; SYNTHETIC ENVIRONMENTS;

BAYESIAN NETWORKS;

EID: 77957850964     PISSN: 09574174     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.eswa.2010.05.062     Document Type: Article

References (50)

1. Barrientos, M., & Vargas, J. (1998). A framework for the analysis of dynamic processes based on Bayesian networks and case-based reasoning. Expert Systems with Applications, 15(3-4), 287-294.
2. Bergeron, F., & Begin, F. (1989). The use of critical success factors in evaluation of information systems: A case study. Journal of Management Information Systems, 5(4), 111-124.
3. Buntine, W. (1996). A guide to the literature on learning probabilistic networks from data. IEEE Transactions on Knowledge and Data Engineering, 8(2), 195-210.
4. Butler, T., & Fitzgerald, B. (1999). Unpacking the systems development process: An empirical application of the CSF concept in a research context. Journal of Strategic Information Systems, 8(4), 351-371.
5. Clarke, B. C. (1965). Soldier management and morale. Washington, D.C.: A-9840 Truman Library.
6. Dempster, A. P., & Laird, N. M. (1977). Maximum likelihood estimation from incomplete data via the EM algorithm. Journal of the Royal Statistical Society, 39, 1-38.
7. D́iez, F. J., & Galán, S. F. (2003). Efficient computation for the noisy MAX. International Journal of Intelligent Systems, 18(2), 165-177.
8. DoA (2001). Field manual FM 3-10: Operations.
9. Druzdzel, M. K., & Gaag, L.C. (1995). SDS: Elicitation of probabilities for belief networks: Combining qualitative and quantitative information. In Paper presented at the Proceedings of the 11th annual conference on uncertainty in artificial intelligence (UAI-95), Montreal, Quebec, Canada.
10. Druzdzel, M. K., & Van der Gaag, L. C. (2000). Building probabilistic networks: Where do the numbers come from? IEEE Transactions on Knowledge and Data Engineering, 12(4), 481-486.
11. Endsley, M. R., Bolte, B., & Jones, D. (2003). Designing for situation awareness: An approach to user-centered design. London: Taylor and Francis.
12. Falkenhainer, D., Borbus, D., & Gentner, D. (1989). The structure-mapping engine: Algorithm and examples. Artificial Intelligence, 41, 1-63.
13. Falzon, L. (2006). Using Bayesian network analysis to support centre of gravity analysis in military planning. European Journal of Operations Research, 170(2), 629-643.
14. Feng, Y., Teng, T., & Tan, A. (2009). Modelling situation awareness for context-aware decision support. Expert Systems with Applications, 36(1), 455-463.
15. Fenton, N. (1999). Applying Bayesian belief networks to critical systems assessment. Critical Systems, 8, 10-13.
16. Fenton, N., & Neil, M. (2000). Software metrics: Successes, failures and new directions. Journal of Systems Software, 47(2 - 3), 149-157.
17. Fenton, N., Neil, M., & Gallan, J. (2007). Using ranked nodes to model qualitative judgments in bayesian networks. Transactions on Knowledge and Data Engineering, 19(10), 1420-1432.
18. Gentner, D. (1983). Structure-mapping, a theoretical framework for analogy. Cognitive Science, 5, 121-152.
19. Guynes, C. S., & Vanecek, M. T. (1996). Critical success factors in data management. Information and Management, 30(4), 201-209.
20. Haider, S., & Levis, A. (2007). Effective course-of-action determination to achieve desired effects. IEEE Transactions on Systems, Man, and Cybernatics - Part A, 37(6), 1140-1150.
21. Heckerman, D., Mamdani, A., & Wellman, M. (1995). Real-world applications of Bayesian networks. Communications of ACM, 38(3), 25-26.
22. HUGIN (2006). .
23. Jain, A. K., Duin, R., & Mao, J. (2000). Statistical pattern recognition: A review. IEEE Transactions on Pattern Analysis and Machine Intelligence, 22(1), 4-37.
24. Klein, G. A. (1993). A recognition-primed decision (RPD) model of rapid decision making. In G. A. Klein, J. Orasanu, R. Calderwood, & C. E. Zsambok (Eds.), Decision making in action: Models and methods (pp. 138-147). Norwood: Ablex.
25. Klein, G., Orasanu, J., Calderwood, R., & Zsambok, C. (1993). Decision making in action: Models and methods. Norwood, NJ: Ablex.
26. Kolonder, J. L. (1993). Case-based reasoning. Morgan Kaufman.
27. Korb, A., & Nicholson, K. (2004). Bayesian artificial intelligence. CRC Press.
28. Lam, P., & Chin, K. I. p. (2005). Identifying and prioritizing critical success factors for conflict management in collaborative new product development. Industrial Marketing and Management.
29. Lee, K. J., & Chang, W. (2009). Bayesian belief network for box-office performance: A case study on Korean movies. Expert Systems with Applications, 36(1), 280-291.
30. Lemmer, J. F., & Gossink, D. E. (2004). Recursive noisy OR - A rule for estimating complex probabilistic interactions. IEEE Transactions on Systems, Man, and Cybernetics - Part B: Cybernetics, 43(5), 2252-2261.
31. Liao, S.-H. (2001). A knowledge-based architecture for implementing military geographical intelligence system on Intranet. Expert Systems with Applications, 20(4), 313-324.
32. Louvieris, P., & Beswick, P. (2004). Meeting the commander's information needs during the execution of a mission.
33. Louvieris, P. et al. (2005). Scenarios development and CSF elicitation.
34. Louvieris, P., Mashanovich, N., Henderson, S., White, G., Petrou, M., & O'Keefe, R. (2005). Smart DSS parsimonious information fusion. In Paper presented at the 8th international conference on information fusion, Philadelphia.
35. Louvieris, P., Gregoriades, A., Mashanovich, N., White, G., & Papathanassiou, C. (2006). Parsimonious analogical reasoning for smart decision support in network-enabled environments: Managing situational awareness. In Paper presented at the coalition command and control in the networked era, 11th international command and control research and technology symposium, Cambridge UK.
36. MAK: VR-Forces, M. T. (2005). .
37. Miller, D. (2004). Information dominance. The philosophy of total propaganda control: Coldtype.
38. MoD (2005). Networked enabled capability.
39. Pal, S., & Shiu, S. (2004). Foundations of soft case-based reasoning. New Jersey: John Wiley & Sons.
40. Patel, V. L., Kaufman, D. R., & Arocha, J. F. (2002). Emerging paradigms of cognition in medical decision-making. Journal of Biomedical Informatics, 35, 52-75.
41. Pearl, J. (1988). Probabilistic reasoning in intelligent systems: Networks of plausible information. San Francisco: Morgan Kaufman.
42. Rey-Long, L., & Yun-Ling, L. (2003). Distributed agents for cost-effective monitoring of critical success factors. Decision Support Systems, 35, 353-366.
43. Rockart, J. F. (1979). Chief executives define their own data needs.
44. Salmeron, J., & Herrero, I. (2005). An AHP-based methodology to rank critical success factors of executive information systems. Computer Standards and Interfaces, 28(1), 1-12.
45. Takikawa, M., & D'Ambrosio, B. (1999). Multiplicative factorization of noisy-max. In Paper presented at the proceedings of the uncertainty in AI conference.
46. Turban, E., Aronsosn, J., Liang, T., & Sharda, R. (2008). Decision support and business intelligence systems: Pearson.
47. Umble, E., Haft, R., & Umble, M. (2003). Enterprise resource planning: Implementation procedures and critical success factors. European Journal of Operational Research, 146(2, 1), 241-257.
48. Vanecek, M., & Guynes, C. (1996). Critical Success factors in data management. Information Management, 30, 201-208.
49. Wellman, M. P. (1990). Fundamental concepts of qualitative probabilistic networks. Artificial Intelligence, 44(3), 257-303.
50. Westerveld, E. (2003). The project excellence model: Linking success criteria and critical success factors. International Journal of Project Management, 21(6), 411-418.