Successfully managing dynamic complex systems requires an understanding of how structure influences both short-and long-term behavior. Therefore, decision support systems designed to improve performance by increasing user understanding require features that address both short and long time scales. The authors report the results of empirical research on the effects of features that facilitate different time scale focuses by users of management flight simulators on system understanding. System understanding was measured in two ways: with questions about structural relationships and by performance measures pertaining to the management of a complex system. Participants were divided into two time scale groups. Results were disaggregated based on causal distance and the timing of impacts to relate time scale focus and system understanding. A second experiment evaluated and improved the hypothesis to include the interaction of the time scale of system control and the time scale focus on improving system understanding and performance in managing dynamic systems.
Axelrod, R.
(Ed.). (1976). Structure of decision. Princeton, NJ: Princeton University Press.
2.
Bakken, B. E. (1993). Learning and transfer of understanding in dynamic decision environments. Unpublished doctoral dissertation, Massachusetts Institute of Technology, Cambridge.
3.
Bakken, B. E.
, Gould, J., & Kim, D. (1992). Experimentation in learning organizations: A management flight simulator approach. European Journal of Operational Research, 59, 167-182.
4.
Brehmer, B.
(1998). Effects of time pressure on fully connected and hierarchical architectures of distributed decision-making. In Y. Waern (Eds.), Co-operative process management, cognition and information technology(pp. 131-143). London: Taylor & Francis, Ltd.
5.
Cook, G. J.
,& Swain, M. R. (1993). A computerized approach to decision process tracing for decision support system design. Decision Sciences, 24(5), 931-952.
6.
Diehl, E. W.
,& Sterman, J. (1995). Effects of feedback complexity on dynamic decision making. Organizational Behavior and Human Decision Processes, 62, 198-215.
7.
Doyle, J.
, & Ford, D. N. (1998). Mental model concepts for system dynamics research. System Dynamics Review, 14(1), 3-29.
8.
Doyle, J. K.
, Radzicki, M. J.,& Trees, S. W. (1996, July). Measuring the effect of systems thinking intervention on mental models. Proceedings of the 1996 International System Dynamics Conference, Cambridge, MA.
9.
Dörner, D.
(1989). The logic of failure. Reading, MA: Addison-Wesley.
10.
Ford, D. N.
(1998). Structuring system information for improved policy development. In J. Geurts, C. Joldersma, and E. Roelofs (Eds.) Gaming/simulation for policy development and organizational change(pp. 123-130). Tilberg, the Netherlands: Tilberg University Press.
11.
Forrester, J. W.
(1961). Industrial dynamics. Portland, OR: Productivity Press.
12.
Goodman, M.
(1974). Study notes in system dynamics. Cambridge: Massachusetts Institute of Technology Press.
13.
Hollnagel, E.
(1998). Context, cognition and control. In Y. Waern (Eds.), Co-operative process management, cognition and information technology(pp. 27-52). London: Taylor & Francis, Ltd.
14.
Huff, A. S.
, Narapareddy, V.,& Fletcher, K. E. (1990). Coding the causal association of concepts. In A. Huff (Eds.), Mapping strategic thought. New York: John Wiley & Sons.
15.
Lane, D. C.
(1995). On a resurgence of management simulations and games. Journal of the Operational Research Society, 46, 604-625.
16.
Langley, P. A.
(1996, May). Using cognitive feedback to improve performance and accelerate individual learning in a simulated oil industry(Working Paper). London Management Centre, University of Westminster.
17.
Langley, P. A.
,& Morecroft, J.D.W. (1996, July). Learning from microworld environments: A summary of the research issues. Proceedings of the 1996 International System Dynamics Conference, Cambridge, MA.
18.
Lee, J. K.
, & Yum, C. S. (1998). Judgmental adjustment in time series forecasting using neural networks. Decision Support Systems, 22(2), 135-154.
19.
Machuca, J.A.D.
, Castillo, J.C.R., Carrillo, M.A.D.,& Zamora, M.M.G. (1998, July). Our 10 years of work on transparent-box business simulation. Proceedings of the 1998 International System Dynamics Conference, Quebec City, Canada.
20.
McCormack, D.E.M. (1998). Effects of time scale focus on improvement in dynamic causal understanding. Unpublished master’s thesis, University of Bergen, Norway.
21.
O’Keefe, R.
(1987). What is visual interactive simulation (and is there a methodology for doing it right?). Proceedings of the 1987 Winter Simulation Conference, Piscataway, NJ.
22.
Paich, M. (1994). Boom and bust: Decision making in a dynamic market environment. Doctoral dissertation, Massachusetts Institute of Technology.
23.
Paich, M.
,& Sterman, J. D. (1993). Boom, bust, and failures to learn in experimental markets. Management Science, 39, 1439-1458.
24.
Richardson, G. P.
,& Pugh, A. L., III. (1981). Introduction to system dynamics modeling with dynamo. Cambridge: Massachusetts Institute of Technology Press.
25.
Roberts, N.
, Andersen, D., Deal, R., Garet, M.,& Shaffer, W. (1983). Introduction to computer simulation, a system dynamics modeling approach. Reading, MA: Addison-Wesley.
26.
Senge, P.
, Roberts, C., Ross, R., Smith, B., & Kleiner, A. (1994). The fifth discipline fieldbook: Strategies and tools for building a learning organization. New York: Doubleday Currency.
27.
Senge, P.
,& Sterman, J. D. (1994). Systems thinking and organizational learning: Acting locally and thinking globally in the organization of the future. In J.D.W. Morecroft& J. D. Sterman (Eds.), Modeling for learning organizations. Portland, OR: Productivity Press.
28.
Sengupta, K.
,& Abdel-Hamid, T. (1993). Alternative conceptions of feedback in dynamic decision environments: An experimental investigation. Management Science, 39, 411-428.
29.
Simon, H.
(1974). How big is a chunk?Science, 183, 482-488.
30.
Simon, H.
(1996). The sciences of the artificial. Cambridge: Massachusetts Institute of Technology Press.
31.
Simons, K. L.
(1990, July). New technologies in simulation games. Proceedings of the 1990 International System Dynamics Conference, Chestnut Hill, MA.
32.
Singh, D. T.
(1998). Incorporating cognitive aids into decision support systems: The case of the strategy execution process. Decision Support Systems, 24, 145-163.
33.
Spector, M.
, & Davidsen, P. (1997, December). Constructing effective interactive learning environments using system dynamics methods and tools(Interim Report Number 1). Educational Information Science and Technology (EIST), University of Bergen, Norway.
34.
Sterman, J. D.
(1989). Modeling managerial behavior: Misperceptions of feedback in a dynamic decision making experiment. Management Science, 35(3), 321-340.
35.
Sterman, J. D.
(1994, Summer/Fall). Learning in and about complex systems. System Dynamics Review, 10(2/3), 291-330.
36.
Sterman, J. D.
(n.d.). Kaibab Plateau analysis(Working Paper D-3331-3). System Dynamics Group, Sloan School of Management, Massachusetts Institute of Technology.
37.
Warren, J. R.
, Van Dijk, J. N., & Jobing, M. J. (1997). Human factors in the simulation of information systems. Simulation & Gaming: An International Journal, 28(1), 65-87.
