Opening the 'Black Box' of Simulations: Increased Transparency and Effective Communication Through the Systematic Design of Experiments

Computational and Mathematical Organization Theory

Volumn 18, Issue 1, 2012, Pages 22-62

  Lorscheid, Iris ^a   Heine, Bernd Oliver ^a   Meyer, Matthias ^a  

^a HAMBURG UNIVERSITY OF TECHNOLOGY   (Germany)

Author keywords

Communication; Design of experiments; Simulation; Standards; Transparency

Indexed keywords

EID: 84859106451     PISSN: 1381298X     EISSN: 15729346     Source Type: Journal    
DOI: 10.1007/s10588-011-9097-3     Document Type: Article

References (52)

1. Antony J (2003) Design of experiments for engineers and scientists. Butterworth-Heinemann, Amsterdam.
2. Arifovic J, Ledyard J (2004) Scaling up learning models in public good games. J Public Econ Theory 6: 203-238.
3. Arnold M, Ponick E, Schenk-Mathes H (2008) Groves mechanism vs. profit sharing for corporate budgeting: An experimental analysis with preplay communication. Eur Account Rev 17: 37-63.
4. Axelrod R (1997) Advancing the art of simulation in the social sciences. In: Conte R, Hegselmann R, Terna P (eds) Simulating social phenomena. Springer, Berlin, pp 21-40.
5. Barton R (2004) Designing simulation experiments. In: Proceedings of the winter simulation conference, Washington DC.
6. Bettonvil B, Kleijnen JPC (1996) Searching for important factors in simulation models with many factors: Sequential bifurcation. Eur J Oper Res 96: 180-194.
7. Box GEP, Hunter JS, Hunter WG (2005) Statistics for experimenters: design, innovation, and discovery. Wiley-Interscience, Hoboken.
8. Camerer C, Ho T (1999) Experience-weighted attraction learning in normal form games. Econometrica 67: 827-874.
9. Dutta P (1999) Strategies and games: theory and practice. MIT Press, Cambridge.
10. Ewert R, Wagenhofer A (2008) Interne Unternehmensrechnung. Springer, Berlin.
11. Field A, Hole G (2003) How to design and report experiments. SAGE, London.
12. Fisher RA (1971) The design of experiments. Hafner, New York.
13. Gilbert N, Troitzsch K (2005) Simulation for the social scientist. Open University Press, Maidenhead.
14. Gilbert N (2008) Agent-Based Models. SAGE, London.
15. Gode DK, Sunder S (1997) What makes markets allocationally efficient? Q J Econ 112: 602.
16. Grimm V, Berger U, Bastiansen F, Eliassen S, Ginot V, Giske J, Goss-Custard J, Grand T, Heinz SK, Huse G, Huth A, Jepsen JU, Jørgensen C, Mooij WM, Müller B, Pe'er G, Piou C, Railsback SF, Robbins AM, Robbins MM, Rossmanith E, Rüger N, Strand E, Souissi S, Stillman RA, VabøR, Visser U, DeAngelis DL (2006) A standard protocol for describing individual-based and agent-based models. Ecol Model 198: 115-126.
17. Grimm V, Berger U, DeAngelis DL, Polhill G, Giske J, Railsback SF (2010) The ODD protocol: a review and first update. Ecol Model 221: 2760-2768.
18. Groves T (1973) Incentives in teams. Econometrica 41: 617-631.
19. Groves T, Loeb M (1979) Incentives in a divisionalized firm. Manag Sci 25: 221-230.
20. Harrison J, Lin Z, Carroll G, Carley K (2007) Simulation modeling in organizational and management research. Acad Manag Rev 32: 1229-1245.
21. Heine B-O, Meyer M, Strangfeld O (2005) Stylised facts and the contribution of simulation to the economic analysis of budgeting. J Artif Soc Simul 8(4).
22. Hendricks W, Robey K (1936) The sampling distribution of the coefficient of variation. Ann Math Stat 7: 129-132.
23. Homburg C, Klarmann M (2003) Empirische Controllingforschung - Anmerkungen aus der Perspektive des Marketing. In: Weber J, Hirsch B (eds) Zur Zukunft der Controllingforschung, Wiesbaden, pp 65-88.
24. Kelton WD, Barton RR (2003) Experimental design for simulation. In: Proceedings of the 2003 winter simulation conference, New Orleans, Louisiana.
25. Kleijnen JPC (1998) Experimental design for sensitivity analysis, optimization, and validation of simulation models. In: Banks J (ed) Handbook of simulation: principles, methodology, advances, applications and practice, New York, pp 173-224.
26. Kleijnen JPC, Sanchez S, Lucas T, Cioppa T (2005) A user's guide to the brave new world of designing simulation experiments. INFORMS J Comput 17: 263-289.
27. Kleijnen JPC (2008) Design and analysis of simulation experiments. Springer, New York.
28. Law A (2007) Simulation modeling and analysis. McGraw-Hill, Boston.
29. Malerba F, Nelson R, Orsenigo L, Winter S (1999) History-friendly models of industry evolution: the computer industry. Ind Corp Change 8(1): 3-40.
30. Manuj I, Mentzer JT, Bowers MR (2009) Improving the rigor of discrete-event simulation in logistics and supply chain research. Int J Phys Distrib Logist Manag 39: 172-201.
31. Mårtensson A (2003) Managing mission-critical IT in the financial industry. Economic Research Institute, Stockholm School of Economics.
32. Mårtensson A, Mårtensson P (2007) Extending rigor and relevance: towards credible, contributory and communicable research. In: Proceedings of the 15th European conference on information systems, St Gallen.
33. Montgomery DC (2009) Design and analysis of experiments. Wiley, Hoboken.
34. Myerson R (1999) Nash equilibrium and the history of economic theory. J Econ Lit 37: 1067-1082.
35. North MJ, Macal CM (2007) Managing business complexity: discovering strategic solutions with agent-based modeling and simulation. Oxford University Press, Oxford.
36. Oh RPT, Sanchez SM, Lucas TW, Wan H, Nissen ME (2009) Efficient experimental design tools for exploring large simulation models. Comput Math Organ Theory 15: 237-257.
37. Peck SL (2004) Simulation as experiment: a philosophical reassessment for biological modeling. Trends Ecol Evol 19: 530-534.
38. Polhill JG, Parker D, Brown D, Grimm V (2008) Using the ODD protocol for describing three agent-based social simulation models of land-use change. J Artif Soc Simul 11(2). http://jasss. soc. surrey. ac. uk/11/2/3. html.
39. Raghu TS, Sen PK, Rao HR (2003) Relative performance of incentive mechanisms: computational modeling and simulation of delegated investment decisions. Manag Sci 49: 160-178.
40. Railsback SF, Grimm V (2011) Agent-based and individual-based modeling: a practical introduction. Princeton University Press, Princeton.
41. Richiardi M, Leombruni R, Saam NJ, Sonnessa M (2006) A common protocol for agent-based social simulation. J Artif Soc Simul 9(1). http://jasss. soc. surrey. ac. uk/9/1/15. html.
42. Reiss J (2011) A plea for (good) simulations: Nudging economics toward an experimental science. Simul Games 42: 243-264.
43. Sanchez SM (2006) Work smarter, not harder: Guidelines for designing simulation experiments. In: Proceedings of the 2006 winter simulation conference, Monterey.
44. Sarin R, Vahid F (1999) Payoff assessments without probabilities: a simple dynamic model of choice. Games Econ Behav 28: 294-309.
45. Saltelli A, Chan K, Scott EM (2000) Sensitivity analysis. Wiley, New York.
46. Saltelli A, Tarantola S, Campolongo F, Ratto M (2004) Sensitivity analysis in practice. Wiley, Chichester.
47. Schmolke A, Thorbek P, DeAngelis DL, Grimm V (2010) Ecological modeling supporting environmental decision making: a strategy for the future. Trends Ecol Evol 25: 479-486.
48. Siebertz K, Bebber Dv, Hochkirchen T (2010) Statistische Versuchsplanung: Design of Experiments (DoE). Springer, Heidelberg.
49. Simon H (1973) The organization of complex systems. In: Pattee HH (ed) Hierarchy theory: the challenge of complex systems. Braziller, New York, pp 1-27.
50. Taber CS, Timpone RJ (1996) Computational modeling. SAGE, Thousand Oaks.
51. Trocine L, Malone LC (2001) An overview of newer, advanced screening methods for the initial phase in an experimental design. In: Proceedings of the 2001 winter simulation conference, Arlington.
52. Wu CFJ, Hamada M (2000) Experiments: planning, analysis, and parameter design optimization. Wiley, New York.