Introduction Mohammad Moshtari MBA Ph D student Moshtarihut

Introduction Mohammad Moshtari, MBA, Ph. D student Moshtari@hut. fi Research Area: Behavioral studies of Decision making Supervisor: Prof. Raimo Hämäläinen Mohammad Moshtari 1

Research Background n n n DA shows an individual how to be coherent in making inferences and choices. However, behavioral decision research (BDR) has shown that people do not always make coherent decisions and internally consistent inferences Behavioral issues have not received a great deal of attention by MCDM/MAUT researchers in recent years (Wallenius et al, forthcoming) Although behavioral research and decision analysis began with a close connection, that connection appears to have diminished over time. In reviewing the two literatures over the past 25 years, BDR has increasingly focused on psychological processes with less emphasis on helping to improve DA’s prescriptive techniques and DA ignores recent developments in BDR and still relies on methods developed in the 1970 s and early 1980 s (judge probabilities and the inconsistencies in preference judgments and decisions) Mohammad Moshtari 2

Two way for further research-1 § Using recently developed psychological models from BDR to develop improved and prescriptive methods for DA, beyond general statements about how awareness of behavioral biases can help decision makers avoid pitfalls. Instead, an appeal is made to take BDR results and models directly into the DA domain and to develop precise prescriptive methods that, according to the proposed theory, should improve judgment and/or decision making in a specific and systematic way. Decision Analysis Effective Prescriptive Methods Develop Evaluation (How they work) Improve DA Knowing Behavioral Issues Behavioral Decision Research Mohammad Moshtari 3

Two way for further research-2 n n n After developing (new) prescriptive methods, we need to know how they will apply and work in real decision settings. Put another way, the question is whether a specific, BDRbased prescriptive methods will be more effective than current DA practice or unaided intuitive judgment in getting a decision maker what he or she wants. Various research paradigms (Simulation Studies, Longitudinal Studies or Ethnological Study of Decision Making) could be used to measure the effectiveness of DA methods. Studies of effectiveness may complement the development of prescriptive DA methods by highlighting important behavioral questions about why various methods perform as they do, and behavioral research can in turn suggest specific ways to improve DA. Mohammad Moshtari 4

Research Concentration (the way forward) n n n SAL develped a number of softwares that it would be a possibility to do behaviourally oriented studies how people come up with decisions with the support of these tools. I have focusd my reasearch on Smart Swaps http: //www. smart-swaps. hut. fi/ Examination of the impacts of software support on the efficiency of the process requires experiments with real users. Mohammad Moshtari 5

References n n • n n n n Carlson, K. and L. Pearo. 2004. Limiting Predecisional Distortion by Prior Valuation of Attribute Components. Organizational Behavior and Human Decision Processes 94 48 -59. Carlson, K. and S. Bond. 2006. Improving Preference Assessment: Limiting the Effect of Context through Preexposure to Attribute Levels. Management Science 52 410 -421. Clemen, Robert T. 2006. Improving and measuring the effectiveness of decision analysis: Linking decision analysis and behavioral decision research. see: http: //faculty. fuqua. duke. edu/~clemen/bio/work. htm Delquié, P. 1993. Inconsistent Trade-offs between Attributes: New Evidence in Preference Assessment Biases. Management Science 39 1382 -1395. Delquié, P. 1997. Bi-matching: A New Preference Assessment Method to Reduce Compatibility Effects. Management Science 43 640 -658. Gregory W. Fischer. 2006. Prescriptive decision science: Problems and opportunities. Annals of Operations Research. 489 -497 J. Mustajoki and R. P. Hamalainen: A Preference Programming Approach to Make the Even Swaps Method Even Easier, Decision Analysis, Vol. 2, No. 2, 2005, pp. 110 -123. J. Mustajoki and R. P. Hamalainen: Smart-Swaps - Decision support for the Pr. OACT process with the even swaps method. Forthcoming in Decision Support Systems Keeney, R. 2002. Common Mistakes in Making Value Trade-offs. Operations Research 50 935 -945. Keeney, R. L. 1992. On the foundations of prescriptive decision analysis. W. Edwards, ed. Utility Theories: Measurements and Applications. Kluwer Academic Publishers, Boston, MA, 58 -72. Keeney, R. L. (2004). Communicating about decisions. Decision Analysis, 1, 84– 85. Keeney, R. L. D. von Winterfeldt and T. Eppel (1990)"Eliciting Public Values for Complex Policy Decisions , ", Management Science, 36, 1011 -1030. Mari Pöyhönen and Raimo P. Hämäläinen. 2001. On the convergence of multiattribute weighting methods. European Journal of Operational Research. Volume 129, Issue 3, 16 , Pages 569 -585 Mari Pöyhönen, Hans Vrolijk and Raimo P. Hämäläinen. 2001. Behavioral and procedural consequences of structural variation in value trees. European Journal of Operational Research. Volume 134, Issue 1, 1 October 2001, Pages 216 -227 Matheson, J. and D. Matheson. 2007. Organizational Decision Analysis. In W. Edwards, R. Miles and D. von Winterfeldt (Eds. ), Advances in Decision Analysis, Cambridge Univ. Press, forthcoming. Wallenius Jyrki, JAMES S. DYER, PETER C. FISHBURN, RALPH STEUER, STANLEY ZIONTS and KALYANMOY DEB. Multiple Criteria Decision Making, Multiattribute Utility Theory: Recent Accomplishments and What Lies Ahead. Forthcoming in Management Science Mohammad Moshtari 6