Topics: Decision making, Decision theory, Decision engineering Pages: 26 (5577 words) Published: February 28, 2014
Journal of Technology Research

The Hypothesis Testing of Decision Making Styles in the
Decision Making Process
Nabie Conteh
Shenandoah University
The objective of this study is to test the effectiveness of various decision making styles in the decision-making process. Four broad categories of decision making styles are utilized in this simulation study. The methodology is illustrated with a complex, semistructured problem often used to train and evaluate management personnel. In order to test the efficacies of these styles, two prototype systems will be constructed. The Decision Support Systems architecture serves as a control and the Just-in-time intelligent Decision Support Systems as the experimental architecture. The experiment will test whether the use of either of the two systems offers a significant improvement in the process of and outcome from the four decision-making styles. The paper closes with a conclusion on the results of the experiment and their implications on Information Systems Research in relation to the decision making process. Keywords: Decision Making, Decision Making styles, Decision-making Process, Simulation, simulation modeling

The Hypothesis Testing, Page 1

Journal of Technology Research
The decision making process is directly linked with the need for problem solving and or decision making. The right choices we make in solving problems and making decisions depends on how correctly we follow the steps through in the decision making process. This paper addresses the effectiveness of the process and outcomes of decisionmaking styles, in the decision-making process, puts forward a methodology for determining their effectiveness.

The merits of Non-subject Designs
The non-subject design approach assumes that human subjects will not be used in gathering data for the simulation study and in evaluating information system architectures. Using human subjects can present some serious scientific, technical, and economic problems. It will be time consuming and potentially costly to get human subjects because of the selection, training, and motivational issues involved in the acquisition of subjects (Power, 2002); (Hoover and Perry, 1990); (O’Kane and Spenceley, 1999). In addition, there may be political considerations (obtaining consent from subjects and going through bureaucratic hurdles from the Institutional Research Board - IRB) involved in selecting and utilizing human subjects in experiments. Also, humans in an experimental setting may not behave the same way as they would in practice. Moreover, it will be difficult to obtain a representative sample of human subjects. Even if the sample is representative of the defined subject group, it may not be representative of the population of potential information system users. As a result, it may be difficult to generalize the results from the subject-based experiment. Human subjects, however, may be unnecessary to conduct simulation studies of information systems, especially when information is available about user behavior. One such instance involves studies that involve decision making support systems (DMSS). There are various studies that define decision making behavior for the general population. Different decision-making styles will be generated based on a stochastic process (based on random variables). This is regulated by means of the hypothesized decision-making styles as found in the literature and specifically in: Turban and Aronson’s Decision Support Systems and Intelligent Systems (1998) pp. 62-3. Decision Style is the way and manner in which decision makers think and respond to or address problems. Decision style is also about their cognitive response to decision situations and their individual and situational differences in beliefs and values. Decision making is not linear. That is to say the emphasis, time allotment and priorities differ from individual to individual and as well as from situation to...

References: University, United Kingdom, pp. 101 – 0106. September 3 – 5, 2003a.
November 22 – 25, 2003b.
Sciences Institute, Boston, November 22 – 25, 2004a.
Forgionne, G.A (1999) An AHP model of DSS effectiveness European Journal of
Information Systems, Palgrave Macmillan Ltd Houndmills, Basingstoke,
Gordon, L.A., et al.(1975). Normative Models in Management Decision Making. New
York: National Association of Accounting.
Hunsakers, Philip L. and Hunsaker, Johanna S. Decision styles – in theory, in practice
Organizational Dynamics, Vol 10 (Autumn 1981), pp
McLeod, R. P. Academic Information Systems (AIS) Software Package II, 1986.
Available from R. P. McLeod, 1106 Glade, College Station, TX 77840, (409)
Mintzberg, H. (1973). The nature of Managerial Work. Englewood Cliffs, NJ: Prentice
O’Kane, J.F. Spenceley, J. and Taylor, R. (1999), Simulation as an enabler for
organizational excellence
CT: Greenwood/Quorum Books, 2002.
Turban, E., and Aronson, J.E., (1998) Decision Support Systems and Intelligent Systems,
Prentice Hall, Upper Saddle River, NJ
Turban, E. Decision Support and Expert Systems: Management Support Systems,
Macmillan Publishing Company, 1993.
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